Solving Urban Infrastructure Problems Using Smart City Technologies: Handbook on Planning, Design, Development, and Regulation [1 ed.] 0128168161, 9780128168165

Table of contents :
Cover
Solving Urban Infrastructure Problems Using Smart City Technologies
Copyright
Dedication
Contents
List of Contributors
About the editor
Foreword
Preface
Organization of this book
Part I: Overview of smart cities and infrastructure technologies: a comprehensive introduction
Part II: Planning, design, development, and management of smart cities and infrastructure technologies
Part III: Renewable energy technologies for smart cities and the critical infrastructure
Part IV: Standardization and regulation of technologies and security for smart cities and the critical infrastructure
Part V: Smart-grid technologies for smart cities and the critical infrastructure
Part VI: Recommended technologies and solutions for smart cities and the critical infrastructure
Part VII: The future of smart cities and the critical infrastructure
Supplemental materials
Acknowledgments
1 Introduction to the critical success factors of E-government adoption of the utilization of emerging smart cities technol...
1.1 Introduction
1.2 E-government and M-government
1.3 M-government adoption in developing countries
1.4 Smart government in developing counties: the case of United Arab Emirates
1.5 Conceptual model of smart government adoption
1.6 Conclusion and future research
1.7 Summary
1.8 Chapter review questions/exercises
1.8.1 True/False
1.8.2 Multiple choice
1.8.3 Exercise
1.8.3.1 Problem
1.8.4 Hands-on projects
1.8.4.1 Problem
1.8.5 Case projects
1.8.5.1 Problem
1.8.6 Optional team case project
1.8.6.1 Problem
References
2 Smart-city infrastructure components
2.1 Introduction
2.2 Smart-city definitions
2.3 Smart-city key foundations (PILARS)
2.4 Smart-city infrastructure platforms and domains
2.4.1 Smart-society infrastructures
2.4.1.1 Smart people
2.4.1.1.1 Education/digital education
2.4.1.1.2 Human capital
2.4.1.1.3 Public participation in life
2.4.1.1.4 Community engagement
2.4.1.2 Smart governance
2.4.1.2.1 E-government
2.4.1.2.2 E-governance
2.4.1.2.3 Citizenry engagement
2.4.1.2.4 Distance services
2.4.1.3 Smart economy
2.4.1.3.1 E-Business and finance
2.4.1.3.2 Tourism
2.4.1.3.3 Culture
2.4.1.3.4 Entrepreneurship
2.4.1.3.5 Innovative economy
2.4.1.3.6 Smart marketing
2.4.1.4 Smart lifestyle
2.4.1.4.1 Health care
2.4.1.4.2 Social services
2.4.1.4.3 Smart surveillance
2.4.1.4.4 Social inclusion
2.4.1.4.5 Flexible workplaces
2.4.1.4.6 Smart home
2.4.2 Smart physical infrastructures
2.4.2.1 Smart environment
2.4.2.1.1 Energy
2.4.2.1.2 Water
2.4.2.1.3 Waste and sanitation
2.4.2.1.4 Pollution
2.4.2.1.5 Building
2.4.2.1.6 Relocation
2.4.2.2 Smart mobility
2.4.2.2.1 Intelligent public transport/E-mobility
2.4.2.2.2 Traffic
2.4.2.2.3 Departure: Locomotion
2.4.2.2.4 Logistic
2.4.2.3 Smart utility
2.4.2.3.1 Internet technologies
2.4.2.3.2 Building information modeling and services
2.4.2.3.3 Urban facilities
2.4.2.4 Smart living
2.4.2.4.1 E-connection
2.4.2.4.2 Housing/shelter
2.4.2.4.3 Cultural facilities
2.4.2.4.4 Safety, security, and emergency
2.4.2.5 Smart digital infrastructures
2.4.2.6 Smart network
2.4.2.6.1 Socially reliable networks
2.4.2.6.2 International connectivity
2.4.2.6.3 Smart-city dashboard
2.4.2.6.4 Surveillance network
2.4.2.7 Smart data
2.4.2.7.1 Data resource
2.4.2.7.2 Data analysis
2.4.2.7.3 Information linkage
2.4.2.8 Smart sensor
2.4.2.8.1 Citizen sensors
2.4.2.8.2 Urban sensors
2.4.2.8.3 Smart communication
2.4.2.8.4 E-communication
2.4.2.8.5 Industry 4.0
2.5 Summary
2.6 Chapter review questions/exercises
2.6.1 True/false
2.6.2 Multiple choice
2.6.3 Exercise
2.6.3.1 Problem
2.6.4 Hands-on projects
2.6.4.1 Project
2.6.5 Case projects
2.6.5.1 Problem
2.6.6 Optional team case project
2.6.6.1 Problem
References
3 Smart buildings and urban spaces
3.1 Introduction
3.2 Smart building systems
3.2.1 Building systems hardware
3.2.2 Enterprise and integration system software
3.2.3 Smart building technologies applied in the Philippines
3.3 Building types in the urban space
3.3.1 Types of building construction in the Philippines
3.4 Permits and standards for smart buildings
3.4.1 Building permits and standards in the Philippines
3.4.2 Green building standards in the Philippines
3.4.3 A smart building case study—Stratford Building
3.5 Smart building market potentials
3.5.1 Stakeholders for smart building in the Philippines
3.5.2 Government
3.5.3 Building association
3.5.4 Real-estate developers/owners
3.5.5 Contractors
3.5.6 Designers
3.5.7 Suppliers
3.5.8 Financial institution
3.5.9 Real-estate agent
3.5.10 End-users
3.5.11 Relationship mapping
3.5.12 Market potential discussion for smart buildings in the Philippines
3.5.13 Influential factor discussion
3.6 Summary
3.7 Chapter review questions/exercises
3.7.1 True/false
3.7.2 Multiple choice
3.7.3 Exercise
3.7.3.1 Problem
3.7.4 Hands-on projects
3.7.4.1 Problem
3.7.5 Case projects
3.7.5.1 Problem
3.7.6 Optional team case project
3.7.6.1 Problem
References
4 Urban mobility systems components
4.1 Introduction
4.2 Mobility, transportation, and accessibility
4.2.1 Mobility versus transportation
4.2.2 Accessibility-based urban mobility
4.3 Evolution of urban mobility
4.3.1 The walking-horse car era (1800s–1890s)
4.3.2 The electric streetcar or tram era (1890s–1920s)
4.3.3 The automobile era (1930s–1950s)
4.3.4 The freeway era (1950s–2010s)
4.3.5 The integrated mobility era (2010s onward)
4.4 Types of transit systems
4.4.1 Collective transportation: public transit
4.4.2 Individual transportation
4.4.3 Freight transportation
4.5 The urban mobility challenge
4.6 Urban mobility in the context of sustainability
4.6.1 Sustainable urban mobility and public transport development
4.6.2 Challenges of urban transport and mobility
4.6.3 Sustainable urban mobility and land-use planning
4.7 Urban mobility in the smart-city age
4.7.1 Benefits of smart urban mobility
4.7.2 Infrastructure components of smart urban mobility system
4.7.2.1 Physical infrastructure
4.7.2.2 Operational technology
4.7.2.3 Communications technology: networks
4.7.2.4 Information technology: software
4.7.3 Switching from traditional to smart mobility
4.7.4 Integration of smart mobility solutions within and across sectors
4.7.5 Urban planners to improve planning via predictive modeling
4.8 Summary
4.9 Chapter review questions/exercises
4.9.1 True/false
4.9.2 Multiple choice
4.9.3 Exercise
4.9.3.1 Problem
4.9.4 Hands-on projects
4.9.4.1 Project
4.9.5 Case projects
4.9.5.1 Problem
4.9.6 Optional team case project
4.9.6.1 Problem
References
5 Coupling of the mobility and energy infrastructures as urban mobility needs evolve
5.1 Introduction
5.1.1 Why is this chapter needed?
5.1.2 Added value for user to read it
5.1.3 Selected components of mobility systems
5.1.3.1 Urban versus rural
5.1.3.2 Mobility infrastructure
5.1.3.3 Energy infrastructure
5.1.3.4 Electric vehicles
5.1.4 Charge points (Electric vehicle supply equipment)
5.2 Trends that shape urban mobility
5.3 An answer from energy and mobility sectors to urbanization and clean trends
5.3.1 Electric vehicles mitigate air and noise pollution
5.3.2 Commercial use of electric vehicles
5.3.3 Successful electromobility cities around the world
5.3.4 For true sustainability, a wider thinking is needed
5.3.5 Traditional transport business models
5.3.6 Mobility as a service caters to customer demands—better?
5.3.7 Shared means of transport as an alternative component to personal means
5.3.8 Improving connectivity via cars
5.4 Examples of urban mobility components
5.4.1 Optimal charging solutions for E-mobility
5.4.2 Necessity of charging hubs
5.4.3 Green charging as an alternative
5.4.4 Electric vehicles supporting the energy ecosystem—vehicle-to-grid
5.4.5 Examples of shared mobility
5.4.6 Electrified car-sharing models
5.4.7 Rise of mobility service platforms
5.5 Action recommendations for regulators
5.5.1 Right to electric vehicle chargers
5.5.2 Education and incentives for clean vehicle drivers
5.5.3 Regulation that anticipates innovation and new business models
5.5.4 Sustainable supply chains for clean transport
5.6 Outlook
5.6.1 Leisure time while traveling
5.6.2 Artificial intelligence taking over the task of driving
5.6.3 Autonomous vehicles in logistics
5.7 Summary
5.8 Chapter review questions/exercises
5.8.1 True/false
5.8.2 Multiple choice
5.8.3 Exercise
5.8.3.1 Problem
5.8.4 Hands-on projects
5.8.4.1 Project
5.8.5 Case projects
5.8.5.1 Problem
5.8.6 Optional team case project
5.8.6.1 Problem
References
6 Smart urban mobility traffic control system components
6.1 Introduction
6.2 Electric mobility
6.3 Types of electric vehicles
6.3.1 Hybrid electric vehicle
6.3.2 Plug-in hybrid electric vehicle
6.3.3 Extended range electric vehicle
6.3.4 Battery electric vehicle
6.3.5 Fuel cell electric vehicle
6.4 Electric vehicle supply equipment
6.5 Electric vehicle charging modes
6.5.1 EV connector type
6.6 Summary
6.7 Chapter review questions/exercises
6.7.1 True/false
6.7.2 Multiple choice
6.7.3 Exercise
6.7.3.1 Problem
6.7.4 Hands-on projects
6.7.4.1 Project
6.7.5 Case projects
6.7.5.1 Problem
6.7.6 Optional team case project
6.7.6.1 Problem
References
7 Urbanization and smart cities
7.1 Introduction
7.2 The future of urbanization and need for the smart city
7.2.1 Challenges with conventional planning approaches
7.3 IoT- and ICT-led initiatives as enablers of smart cities
7.3.1 Efficiency and flexibility by adopting technology
7.4 Smart cities, urban planning, and policy
7.4.1 Defining smart-city goals: guiding policy with urban planning and technology
7.5 Challenges and opportunities of smart cities
7.5.1 Need for an integrated approach
7.5.2 Outside-in approach
7.5.3 Inside-out approach
7.6 Conclusion
7.7 Summary
7.8 Chapter review questions/exercises
7.8.1 True/false
7.8.2 Multiple choice
References
8 Priority activities for smart cities and the infrastructure
8.1 Introduction
8.2 Background information
8.3 Generating the market
8.4 Blocks to the market
8.5 Expanding the market
8.6 Greening the market
8.7 Enablers
8.7.1 Smart government
8.7.2 Standardization
8.7.3 Smart incorporated city planning
8.8 Training and involving stakeholders
8.9 Summary
8.10 Chapter review questions/exercises
8.10.1 True/False
8.10.2 Multiple choice
8.10.3 Exercise
8.10.3.1 Problem
8.10.4 Hands-on projects
8.10.4.1 Project
8.10.5 Case projects
8.10.5.1 Problem
8.10.5.2 Problem
References
9 Open Data for smart cities
9.1 Introduction
9.2 The rise of urban data
9.3 Open Data, Big Data, Linked Data, and Linked Open Data
9.3.1 Big Data
9.3.2 Open Data
9.3.3 Linked Data
9.3.4 Linked Open Data and Linked Open Government Data
9.4 More about Open Data
9.4.1 Challenges
9.4.2 Free versus not free
9.4.3 Licenses
9.4.4 Open Data formats
9.4.4.1 JSON
9.4.4.2 XML
9.4.4.3 RDF and DCAT (and DCAT-AP)
9.4.4.3.1 Spreadsheets
9.4.4.3.2 Comma-separated files
9.4.4.3.3 Text documents
9.4.4.3.4 Plain text
9.4.4.3.5 Scanned images
9.4.4.3.6 HTML
9.4.4.3.7 Geospatial data
9.4.5 Five-star Linked Open Data
9.5 National paths to open data
9.5.1 The EU path
9.5.2 The US path
9.5.3 The Indian path
9.5.4 Other paths
9.6 Open Data value chain
9.6.1 Consumption/commercialization
9.6.2 Processing
9.6.3 Governance
9.6.4 Interoperability
9.6.5 Security and Trust
9.7 Eliminating silos by sharing or Open Data
9.8 Data marketplaces
9.9 Conclusion
9.10 Summary
9.11 Chapter review questions/exercises
9.11.1 True/False
9.11.2 Multiple choice
9.11.3 Exercise
9.11.3.1 Problem
9.11.4 Hands-on projects
9.11.4.1 Project
9.11.5 Case projects
9.11.5.1 Problem
9.11.6 Optional team case project
9.11.6.1 Problem
Acknowledgments
References
10 The role of citizens in smart cities and urban infrastructures
10.1 Introduction
10.2 Smart city
10.3 Citizens
10.4 Urban infrastructures
10.5 From passive citizen to active citizens
10.6 Open government
10.7 Governance
10.8 Technological governance
10.9 Hybridizations and changes in citizen governance
10.10 Citizens in the city and urbanism in smart-cities world
10.11 Practical cases
10.11.1 Barcelona Lesseps Square example
10.11.2 The Diagonal Avenue referendum in Barcelona
10.11.3 Planning cases: Yinchuan, Dubai, and Neom
10.12 Corruption and urbanism
10.13 Transparency and citizen role in urbanism and infrastructures
10.14 Superation of citizen participation topics
10.15 Summary
10.16 Chapter review questions/exercises
10.16.1 True/false
10.16.2 Multiple choice
10.16.3 Exercise
10.16.3.1 Problem
10.16.4 Hands-on projects
10.16.4.1 Project
10.16.5 Case projects start here
10.16.5.1 Problem
10.16.6 Optional team case project
10.16.6.1 Problem
References
11 Smart city and metropolitan governance
11.1 Introduction
11.2 How can cities benefit from cooperation on the smart city subject in a metropolitan area?
11.2.1 Intermunicipal coordination increases overall productivity
11.2.2 Difference in financial capacity among the cities is a common challenge
11.3 What metropolitan governance arrangement is needed?
11.3.1 An Inter-Municipal Forum or Council
11.3.1.1 The process is as important as the outcome
11.3.1.1.1 Ensure strong support by the local governments
11.3.1.1.2 Start simple and design for success
11.3.1.1.3 Agree on resourcing
11.3.1.1.4 Be clear on “Who does what”
11.3.2 More comprehensive arrangements
11.4 What are the obstacles to collaboration across jurisdictions?
11.4.1 Parochialism is a common phenomenon
11.4.2 The level of trust may not be strong enough
11.4.3 The prerequisites for effective teamwork are not there
11.5 Application of the intermunicipal cooperation arrangement
11.6 Summary
11.7 Chapter review questions/exercises
11.7.1 True/False
11.7.2 Multiple choice
11.7.3 Exercise
11.7.3.1 Problem
11.7.4 Hands-on projects
11.7.4.1 Project
11.7.5 Case projects
11.7.5.1 Problem
11.7.6 Optional team case project
11.7.6.1 Problem
References
12 Distributed energy in smart cities and the infrastructure
12.1 Introduction
12.1.1 Energy storage
12.1.2 Smart microgrids
12.1.3 Smart and sustainable balance
12.2 Smart cities
12.2.1 Distributed power generation
12.2.2 Automatic distribution system
12.2.2.1 Smarter home
12.2.3 HVAC and audio visual
12.2.4 Advanced metering system infrastructure
12.2.5 Energy storage with grid integration
12.2.6 Electric vehicle
12.3 Instrumental procedures in smart cities
12.3.1 Energy efficiency practices
12.3.2 Smart grid
12.3.3 Demand management
12.3.4 Improved access to information
12.3.5 Environmental sustainability
12.3.6 Application of Clean Technologies
12.3.7 Use of ICT
12.3.8 Citizen participation
12.3.9 Smart governance
12.3.10 Identifying the smart cities
12.4 A selection of smart cities standards
12.4.1 Process-level standards
12.4.2 Technical-level standards
12.5 Energy strategy
12.6 Factors affecting energy in smart city
12.6.1 Global governance of energy
12.6.2 Public exemplary plan
12.6.3 Carbon-free mobility plan
12.6.4 Energy refurbishment plan of buildings
12.6.5 Plan new neighborhoods
12.7 Smart-city hacking
12.7.1 Manipulation of law-enforcement response
12.7.2 The solution for smart cities
12.8 Energy efficient designs of sustainable buildings
12.8.1 Literature review and background
12.8.2 Holistic (overall) approach
12.8.3 Energy-efficient buildings
12.8.4 Energy declaration of existing buildings
12.8.5 Energy declaration of new buildings
12.9 Summary
12.10 Chapter review questions/exercises
12.10.1 True/False
12.10.2 Multiple choice
12.10.3 Exercise
12.10.3.1 Problem
12.10.4 Hands-on projects
12.10.4.1 Project
12.10.5 Case projects
12.10.5.1 Problem
12.10.6 Optional team case project
12.10.6.1 Problem
References
13 Energy efficient automated warehouse design
13.1 Introduction
13.2 Literature review
13.3 System description and model assumptions in the system
13.3.1 Operations and assumptions in the system
13.4 Simulation modeling of the system
13.4.1 Design scenarios for experiments
13.5 Results and discussion
13.5.1 Graphical results and comments
13.5.1.1 Effect of number of shuttles on average energy consumption per transaction
13.5.1.2 Effect of arrival rate on the both performance metrics
13.5.1.3 Effects of acceleration/deceleration values on both performance metrics
13.6 Suggested future works
13.7 Summary
13.8 Chapter review questions/exercises
13.8.1 True/false
13.8.2 Multiple choice
13.8.3 Exercise
13.8.3.1 Problem
13.8.4 Hands-on projects
13.8.4.1 Project
13.8.5 Case projects
13.8.5.1 Problem
13.8.6 Optional team case project
13.8.6.1 Problem
Acknowledgment
References
14 Smart utilities
14.1 Introduction
14.2 Smart solutions
14.2.1 Overview
14.2.2 Consumer requirements and expectations
14.2.3 Energy need
14.2.4 National energy plans
14.2.5 Resource availability
14.2.6 Smart infrastructure
14.2.7 Virtual utility
14.2.8 Benefits of VU model
14.3 Electricity
14.3.1 Overview
14.3.2 Infrastructure
14.3.3 Regulations and standards
14.3.4 Ongoing failures of existing networks
14.3.5 Advanced control methods
14.3.6 Smart energy hub
14.3.7 Smart grid
14.3.8 Advantages of smart grids
14.3.9 Smart stations
14.3.10 Smart distribution
14.3.11 Smart metering
14.3.12 Integrated communication
14.3.13 Review of state-of-the-art studies
14.4 Water
14.4.1 Overview
14.4.2 Infrastructure
14.4.3 Smart water grid
14.4.4 Smart meter
14.4.5 Management of water utility system
14.4.6 Inventory management
14.4.7 Subscriber management
14.4.8 Geographical information system and infrastructure management
14.4.9 SCADA-database based control surveillance system
14.4.10 Review of state-of-the-art studies
14.5 Natural gas
14.5.1 Overview
14.5.2 Infrastructure
14.5.3 Natural gas grid
14.5.4 Management of natural gas system
14.5.5 Device maintenance
14.5.6 Customer requirements and expectations
14.5.7 Review of state-of-the-art studies
14.6 Summary and business models for utility industry
14.7 Chapter review questions/exercises
14.7.1 True/false
14.7.2 Multiple choice
14.7.3 Exercise
14.7.3.1 Problem
14.7.4 Hands-on projects
14.7.4.1 Project
14.7.5 Case projects
14.7.5.1 Problem
14.7.6 Optional team case project
14.7.6.1 Problem
References
15 Smart cities and infrastructure standardization requirements
15.1 Introduction
15.2 Data monetization: open data to increase community engagement
15.3 Smart-city technology architecture
15.4 Smart-city application architecture
15.4.1 Smart tourism
15.4.2 Hygiene/cleanliness drive
15.4.3 Traffic and travel management
15.4.4 E-buses
15.4.5 E-rickshaw
15.4.6 Public bicycle sharing
15.4.7 Passenger information system through mobile application and travel cards
15.4.8 Intelligent transport management system
15.4.9 Management of E-charging stations
15.4.10 Speed management, based on the time of the day
15.4.11 Management of traffic lights
15.4.12 Building management
15.4.12.1 Usage-based cleaning
15.4.12.2 Automated garage entry
15.4.12.3 Renewable energy and smarter energy utilization
15.4.12.4 Water conservation/harvesting
15.4.13 Disease management
15.4.14 Road and city cleanliness
15.4.15 Special care for elders
15.4.16 Care for physically disabled
15.4.17 Usage of data for safety
15.4.18 Fire safety
15.4.19 Smart contracts
15.4.20 Smart grid
15.4.21 Smart water
15.4.22 Smart homes
15.4.23 Smart working spaces
15.4.24 Smart waiting areas and smart advertisements
15.4.25 Smart urban forests
15.4.26 Research, education, skilling, and reskilling institutes
15.4.27 Medical institutes and hospitals
15.4.28 Start-up ecosystem and investor forums
15.5 Smart energy and light
15.6 Gearing-up for smart health in cities
15.6.1 Supported technology environment for smart healthcare
15.6.2 Expected benefits of these applications in smart city
15.7 City services’ architecture and assets management
15.7.1 Asset management and data aggregation services
15.7.2 Tourist spots and hotel management
15.7.3 Streetlights
15.7.4 CCTV across cities
15.7.5 Manpower skill database
15.7.6 Smart entertainment
15.7.7 Cloud kitchens
15.7.8 Connectivity of assets across the city and managing solar lights/energy storage
15.7.9 Solid waste management and zero waste policy and green houses
15.7.10 Disaster/emergency management and emergency response teams
15.7.11 Smart governance
15.7.11.1 Analysis
15.7.11.2 Policy making
15.7.11.3 Planning
15.7.11.4 Execution
15.7.11.5 Enforcement
15.8 Smart-city data democracy architecture
15.8.1 Components of smart-city data
15.8.2 Data infrastructure
15.8.3 Connectivity and data hub
15.8.4 Smart city metadata model
15.8.5 AI for smarter decisions in smarter cities
15.8.6 The need for new operational requirements, skills, and expertise
15.9 Security, privacy, and business continuity concerns of data hub
15.10 Summary
15.11 Chapter review questions/exercises
15.11.1 True/False
15.11.2 Multiple choice
15.11.3 Exercise
15.11.3.1 Problem
15.11.4 Hands-on projects
15.11.4.1 Projects
15.11.5 Case projects
15.11.5.1 Problem
15.11.6 Optional team case project
15.11.6.1 Problem
References
16 Securing smart-grid infrastructure against emerging threats
16.1 Introduction
16.2 Emerging cyber threats targeting smart grid
16.2.1 Ukraine power plant attacks
16.2.2 Aurora generator test
16.3 Security solutions for protecting smart grid
16.3.1 Limitations of existing cyber-security solutions
16.4 Supervisory control and data acquisition command authentication as additional line of defense
16.4.1 Trends in supervisory control and data acquisition command authentication
16.4.2 Command authentication using power flow dynamics simulation
16.4.3 Active command mediation defense (A*CMD) system and practical integration
16.4.3.1 Artificial command-delaying
16.4.3.2 Overall A*CMD system architecture and deployment options
16.4.3.3 Deployment option 1: All-in-one substation gateway
16.4.3.4 Deployment option 2: Bump-in-the-wire approach
16.5 Summary
16.6 Chapter review questions/exercises
16.6.1 True/false
16.6.2 Multiple choice
16.6.3 Exercise
16.6.3.1 Problem
16.6.4 Hands-on projects
16.6.4.1 Project
16.6.5 Case projects
16.6.5.1 Problem
16.6.6 Optional team case project
16.6.6.1 Problem
References
17 Components of the smart-grid system
17.1 Introduction
17.2 Components of smart grid
17.2.1 Smart appliances
17.2.1.1 Energy use
17.2.1.2 Communication: connectivity and home savings
17.2.2 Electric vehicles
17.2.2.1 Smart charging of electric vehicles
17.2.3 Smart meters
17.2.3.1 Working principle of smart meters
17.2.4 Smart substation
17.2.5 Distributed generation
17.2.6 Phasor measurement unit
17.2.7 Integrated communication system
17.2.8 Sensing and measurements
17.3 Summary
17.4 Chapter review questions/exercises
17.4.1 True/false
17.4.2 Multiple choice
17.4.3 Exercise
17.4.3.1 Problem
17.4.4 Hands-on projects
17.4.4.1 Project
17.4.5 Case projects
17.4.5.1 Problem
17.4.6 Optional team case project
17.4.6.1 Problem
References
18 Introduction to energy management in smart grids
18.1 Introduction
18.2 Elements of the smart grid
18.3 Energy management
18.3.1 Base line of energy assessment
18.3.2 Organizational integration
18.4 Energy management in operational functions
18.5 Energy management challenges
18.5.1 Energy strategies
18.5.2 Energy strategies of companies
18.5.3 Political energy strategies
18.5.4 Ethical and normative basis of the energy strategies
18.6 Energy management standards
18.7 Summary
18.8 Chapter review questions/exercises
18.8.1 True/false
18.8.2 Multiple choice
18.8.3 Exercise
18.8.3.1 Problem
18.8.4 Hands-on projects
18.8.4.1 Project
18.8.5 Case projects
18.8.5.1 Problem
18.8.6 Optional team case project
18.8.6.1 Problem
References
19 DER, energy management, and transactive energy networks for smart cities
19.1 Introduction
19.2 TEN for smart cities—stakeholders, market forces, and technologies
19.2.1 Customers and stakeholders
19.2.2 Digitization and smart systems
19.2.3 Markets and operators
19.2.4 Transactive energy networks
19.3 DER: distributed energy resources
19.4 Evolution of key subsystems for transactive energy
19.4.1 Building management systems
19.4.2 Grid interactive BMS/BEMS
19.4.3 Levels of operation
19.5 Digital systems and components—10 enablers
19.5.1 IoT and sensors
19.5.2 IoT for home and building automation
19.5.3 IoT for energy
19.5.4 IoT Communication Technologies for TEN
19.5.4.1 Bluetooth
19.5.4.2 Zigbee
19.5.4.3 LoRa and LoRaWAN
19.5.4.4 Cellular networks 5G/4G/3G
19.5.5 Cloud systems
19.5.6 Cyber security and federation
19.5.7 Big data, analytics
19.5.7.1 Distributed centralized AI and ML and blockchain
19.5.8 Interoperability and standards
19.6 Smart TE microgrids
19.7 Markets and operators (short and long term)
19.8 Transactive energy strategy and challenges
19.8.1 Challenges
19.9 Summary
19.10 Chapter review questions/exercises
19.10.1 True/false
19.10.2 Multiple choice
19.10.3 Exercise
19.10.3.1 Problem
19.10.4 Hands-on projects
19.10.4.1 Project
19.10.5 Case projects
19.10.5.1 Problem
19.10.6 Optional team case project
19.10.6.1 Problem
References
20 Managing the generation and demand inside the smart-grid structure
20.1 Introduction
20.1.1 Importance of energy management
20.2 Energy management techniques in smart grid
20.2.1 ZigBee network interfaced with field programmable gate array
20.2.2 Global system for mobile communication
20.2.3 Supervisory control and data acquisition
20.2.4 Remote energy management system using smart meter
20.3 Smart energy management system
20.3.1 Supplier-side management
20.3.2 Demand response
20.3.3 Demand-side management
20.3.4 Peak clipping
20.3.5 Valley filling
20.3.6 Load shifting
20.3.7 Strategic conservation
20.3.8 Strategic load growth
20.3.9 Flexible load shape
20.4 Summary
20.5 Chapter review questions/exercises
20.5.1 True/false
20.5.2 Multiple choice
20.5.3 Exercise
20.5.3.1 Problem
20.5.4 Hands-on projects
20.5.4.1 Project
20.5.5 Case projects
20.5.5.1 Problem
20.5.6 Optional team case project
20.5.6.1 Problem
References
21 Introduction to energy management in smart grids
21.1 Introduction
21.2 Energy management system: the optimization procedure XEMS13
21.2.1 Components
21.2.2 Energy vector balance equations
21.2.3 Cost function
21.2.4 Optimization
21.3 Case study
21.3.1 Optimal scheduling
21.3.2 Hourly load profiles
21.3.3 Energy prices
21.3.4 Proposed configurations
21.3.5 Scenario 1: adding a local boiler
21.3.6 Scenario 2: further addition of a CHP, absorption chiller, and storage
21.3.7 Scenario 3: further addition of solar heating
21.3.8 Scenario 4: further addition of heat pump
21.3.9 Results
21.4 Summary
21.5 Chapter review questions/exercises
21.5.1 True/false
21.5.2 Multiple choice
21.5.3 Exercise
21.5.3.1 Problem
21.5.4 Hands-on projects
21.5.4.1 Project
21.5.5 Case projects
21.5.5.1 Problem
21.5.6 Optional team case project
21.5.6.1 Problem
References
22 Hybrid renewable energy systems, load and generation forecasting, new grids structure, and smart technologies
22.1 Introduction
22.1.1 Smart grid: smart technologies and new grids structures
22.1.2 Load and generation forecasting
22.2 Summary
22.3 Conclusions
22.4 Chapter review questions/exercises
22.4.1 True/false
22.4.2 Multiple choice
22.4.3 Exercise
22.4.3.1 Problem
22.4.4 Hands-on projects
22.4.4.1 Project
22.4.5 Case projects
22.4.5.1 Problem
22.4.6 Optional team case project
22.4.6.1 Problem
References
23 Smart lighting for smart cities
23.1 Introduction
23.2 Smart lighting basics
23.2.1 Luminaires
23.2.2 LEDs
23.2.3 Controls
23.2.4 Drivers and dimming
23.2.5 Networks
23.2.6 Interface and controller
23.2.7 Control methodologies
23.3 More advanced concepts
23.3.1 Ubiquitous network and infrastructure
23.3.2 Color
23.4 Smart lighting example
23.4.1 On-demand roadway lighting
23.4.1.1 General architecture
23.4.1.2 Results and lessons learned
23.5 Potential challenges
23.6 Summary
23.7 Chapter review questions/exercises
23.7.1 True/false
23.7.2 Multiple choice
23.7.3 Exercise
23.7.3.1 Problem
23.7.4 Hands-on projects
23.7.4.1 Project
23.7.5 Case projects
23.7.5.1 Problem
23.7.6 Optional team case project
23.7.6.1 Problem
References
24 Smart cities critical infrastructure recommendations and solutions
24.1 Introduction
24.2 Critical city infrastructures
24.2.1 Overview
24.2.2 Identifying critical infrastructures
24.2.3 Protection of critical infrastructures
24.3 Communications
24.3.1 Overview
24.3.2 Channels used for communications
24.3.2.1 The flexibility of communication systems
24.3.3 Safety and security of communication systems
24.3.4 Recommendations and solutions
24.4 Energy (electricity, gas, and oil)
24.4.1 Overview
24.4.2 Smart grid infrastructure
24.4.3 Smart grid system usage in the world
24.4.4 Microgrids
24.4.5 Natural gas
24.4.6 Renewable energy resources
24.4.7 Recommendations and solutions
24.4.7.1 Advanced heating, ventilation, and air-conditioning systems
24.4.7.2 District heating and cooling
24.4.7.3 Sector coupling
24.5 Water
24.5.1 Overview
24.5.2 Infrastructures for water systems
24.5.2.1 Leakage detection and control
24.5.2.2 Water efficiency via smart metering
24.5.2.3 Water quality monitoring
24.5.3 Recommendations and solutions
24.6 Public transportation
24.6.1 Overview
24.6.2 Integration via information and communication technology applications
24.6.2.1 Electrification of motorized public transportation
24.6.2.2 Integration of parking and public transportation system
24.6.3 Recommendations and solutions
24.7 Emergency services
24.7.1 Overview
24.7.2 Fire detection and prevention
24.7.3 First-aid alerts
24.7.4 Emergency response optimization
24.7.5 Recommendations and solutions
24.7.5.1 Crime prediction
24.7.5.2 Smart surveillance
24.7.5.3 Disaster early warning systems
24.8 Summary
24.9 Chapter review questions/exercises
24.9.1 True/false
24.9.2 Multiple choice
24.9.3 Exercise
24.9.3.1 Problem
24.9.4 Hands-on projects
24.9.4.1 Project
24.9.5 Case projects
24.9.4.1 Problem
24.9.6 Optional team case project
24.9.6.1 Problem
References
25 The city as a commons: the concept of common goods
25.1 Introduction
25.2 Defining the topic
25.3 The commons and the OECD
25.4 The commons and the European Union
25.5 Coproduction and the European Social Fund
25.6 The Bologna regulation on public collaboration for urban commons: theoretical basis
25.7 Italy and the commons
25.8 The Bologna regulation on public collaboration for urban commons
25.9 From the commons to the city as a commons
25.10 The cocity index
25.11 Urban innovative action in the city of Turin
25.12 The city of Verona and subsidiarity pacts with active citizens
25.13 The commons and civic crowdfunding
25.14 Best Italian practices in matching public funds with private ones: the city of Milan and Turin
25.15 The role of institutions in promoting civic crowdfunding
25.16 Summary
25.17 Chapter review questions/exercises
25.17.1 True/false
25.17.2 Multiple choice
25.17.3 Exercise
25.17.3.1 Problem
25.17.4 Hands-on projects
25.17.4.1 Project
25.17.5 Case projects
25.17.5.1 Problem
25.17.6 Optional team case project
25.17.6.1 Problem
References
26 Resilient future energy systems: smart grids, vehicle-to-grid, and microgrids
26.1 Introduction
26.1.1 The changing face of energy networks
26.1.1.1 Control-oriented stochastic modeling
26.1.2 Model predictive operation control
26.1.3 Flexible future smart-grid systems
26.2 Optimization of urban electric grids with EV charging load and V2G generation
26.2.1 Statement of the optimization problem
26.2.2 Lower level of optimization
26.2.3 High-level model description
26.2.4 Minimization of losses in the electric grid
26.2.5 Minimization of voltage deviations
26.2.6 Reducing environmental impact
26.2.7 Probabilistic statement of the problem
26.2.8 Dynamic optimization
26.3 Resilient operational control of microgrids
26.3.1 Risk-averse multistage optimization and risk-averse MPC
26.3.2 Numerical optimization methods for multistage optimization
26.4 Smart grids and digital twins
26.5 Summary
26.6 Chapter review questions/exercises
26.6.1 True/false
26.6.2 Multiple choice
26.6.3 Exercise
26.6.3.1 Problem
26.6.4 Hands-on projects
26.6.4.1 Project
26.6.5 Case projects
26.6.5.1 Problem
26.6.6 Optional team case project
26.6.6.1 Problem
References
27 Future of connected autonomous vehicles in smart cities
27.1 Introduction
27.2 Components of smart city
27.3 Connected and autonomous vehicle functional architecture
27.3.1 Localization
27.3.2 Perception
27.3.3 Path planning
27.3.4 Control
27.4 CAV and smart mobility
27.5 CAV and smart energy
27.6 CAV and smart home
27.7 CAV and smart health
27.8 CAV testing and verification platform
27.9 Summary
27.10 Chapter review questions/exercises
27.10.1 True/false
27.10.2 Multiple choice
27.10.3 Exercise
27.10.3.1 Problem
27.10.4 Hands-on projects
27.10.4.1 Project
27.10.5 Case projects
27.10.5.1 Problem
27.10.6 Optional team case project
27.10.6.1 Problem
References
28 Future developments in vehicle-to-grid technologies
28.1 Introduction
28.2 Smart grid
28.3 Vehicle to grid
28.3.1 Architecture
28.3.2 Advantages
28.4 State-of-the-art of the V2G
28.4.1 Classification
28.4.2 Bidirectional charger
28.4.3 Voltage source rectifier
28.4.4 DC–DC converter
28.4.5 Charger control method
28.5 Charging/discharging strategy
28.5.1 Grid view
28.5.2 User view
28.5.3 Time-of-use electricity price
28.5.4 Traditional TOU
28.5.5 Game theory TOU
28.6 Summary
28.7 Chapter review questions/exercises
28.7.1 True/false
28.7.2 Multiple choice
28.7.3 Exercise
28.7.3.1 Problem
28.7.4 Hands-on projects
28.7.4.1 Project
28.7.5 Case projects
28.7.5.1 Problem
28.7.6 Optional team case project
28.7.6.1 Problem
References
29 Designing inclusive smart cities of the future: the Indian context
29.1 Introduction
29.1.1 Need for the study: the Indian context
29.1.2 Flow of the chapter
29.2 Review of literature
29.3 Learning from existing global implementations
29.3.1 Seattle, USA
29.3.2 Alexandria, USA
29.3.3 European Union—City4Age
29.3.4 Sonoma, USA
29.3.5 Korsør, Denmark
29.3.6 Melbourne, Australia
29.3.7 Global Initiative for Inclusive ICTs
29.4 Understanding Indian context
29.4.1 Existing smart India initiatives
29.5 Proposed conceptual model of an inclusive smart city
29.5.1 Implementation of the proposed conceptual model
29.5.2 Data capture block
29.5.3 Data storage block
29.5.4 Data analytics block
29.5.5 Data-based decision block
29.6 Recommendations
29.6.1 Initiatives taken by the Government of India
29.6.2 Study of 3As
29.6.3 Accessibility
29.6.4 Adaptability
29.6.5 Affordability—high Capex and Opex
29.6.6 Objective of inclusive smart cities
29.6.7 Use of real-time apps—SeenAb
29.6.8 Collaboration of Smart-City Mission and Startup India
29.6.9 Smart vans
29.6.10 Visual, hearing, and cognitive ICT-based solutions
29.6.11 Public infrastructure
29.7 Summary
29.8 Chapter review questions/exercises
29.8.1 True/false
29.8.2 Multiple choice
29.8.3 Exercise
29.8.3.1 Problem
29.8.4 Hands-on projects
29.8.4.1 Project
29.8.5 Case projects
29.8.5.1 Problem
29.8.6 Optional team case project
29.8.6.1 Problem
References
Appendix A List of top smart cities and critical infrastructure implementation and deployment companies
Appendix B List of smart cities and critical infrastructure products/projects
Appendix C List of smart cities and critical infrastructure standards
Appendix D List of miscellaneous smart cities and critical infrastructure resources
Appendix E Smart cities and critical infrastructure frequently asked questions
Appendix F List of smart cities and critical infrastructure case studies
Appendix G Answers to review questions/exercises, hands-on projects, case projects, and optimal team case project by chapter
G.1 Chapter 1: Introduction to the critical success factors of e-government adoption of the utilization of emerging smart c...
G.1.1 Review questions/exercises
G.1.1.1 True/false
G.1.1.2 Multiple choice
G.1.1.3 Exercise
G.1.1.3.1 Solution
G.1.1.4 Hands-on project
G.1.1.4.1 Solution
G.1.1.5 Case projects
G.1.1.5.1 Solution
G.1.1.6 Optional team case project
G.1.1.6.1 Solution
G.2 Chapter 2: Smart-city infrastructure components
G.2.1 Review questions/exercises
G.2.1.1 True/false
G.2.1.2 Multiple choice
G.2.1.3 Exercise
G.2.1.3.1 Solution
G.2.1.4 Hands-on project
G.2.1.4.1 Solution
G.2.1.5 Case projects
G.2.1.5.1 Solution
G.2.1.6 Optional team case project
G.2.1.6.1 Solution
G.3 Chapter 3: Smart buildings and urban spaces
G.3.1 Review questions/exercises
G.3.1.1 True/false
G.3.1.2 Multiple choice
G.3.1.3 Exercise
G.3.1.3.1 Solution
G.3.1.4 Hands-on project
G.3.1.4.1 Solution
G.3.1.5 Case projects
G.3.1.5.1 Solution
G.3.1.6 Optional team case project
G.3.1.6.1 Solution
G.4 Chapter 4: Urban mobility systems components
G.4.1 Review questions/exercises
G.4.1.1 True/false
G.4.1.2 Multiple choice
G.4.1.3 Exercise
G.4.1.3.1 Solution
G.4.1.4 Hands-on project
G.4.1.4.1 Solution
G.4.1.5 Case projects
G.4.1.5.1 Solution
G.4.1.6 Optional team case project
G.4.1.6.1 Solution
G.5 Chapter 5: Coupling of the mobility and energy infrastructures as urban mobility needs evolve
G.5.1 Review questions/exercises
G.5.1.1 True/false
G.5.1.2 Multiple choice
G.5.1.3 Exercise
G.5.1.3.1 Solution
G.5.1.4 Hands-on project
G.5.1.4.1 Solution
G.5.1.5 Case projects
G.5.1.5.1 Solution
G.5.1.6 Optional team case project
G.5.1.6.1 Solution
G.6 Chapter 6: Urban mobility system components
G.6.1 Review questions/exercises
G.6.1.1 True/false
G.6.1.2 Multiple choice
G.6.1.3 Exercise
G.6.1.3.1 Solution
G.6.1.4 Hands-on project
G.6.1.4.1 Solution
G.6.1.5 Case projects
G.6.1.5.1 Solution
G.6.1.6 Optional team case project
G.6.1.6.1 Solution
G.7 Chapter 7: Urbanization and smart cities
G.7.1 Review questions/exercises
G.7.1.1 True/false
G.7.1.2 Multiple choice
G.7.1.3 Exercise
G.7.1.3.1 Solution
G.7.1.4 Hands-on project
G.7.1.4.1 Solution
G.7.1.5 Case projects
G.7.1.5.1 Solution
G.7.1.6 Optional team case project
G.7.1.6.1 Solution
G.8 Chapter 8: Priority activities for smart cities and the infrastructure
G.8.1 Review questions/exercises
G.8.1.1 True/false
G.8.1.2 Multiple choice
G.8.1.3 Exercise
G.8.1.3.1 Solution
G.8.1.4 Hands-on project
G.8.1.4.1 Solution
G.8.1.5 Case projects
G.8.1.5.1 Solution
G.8.1.6 Optional team case project
G.8.1.6.1 Solution
G.9 Chapter 9: Open data for smart cities
G.9.1 Review questions/exercises
G.9.1.1 True/false
G.9.1.2 Multiple choice
G.9.1.3 Exercise
G.9.1.3.1 Solution
G.9.1.4 Hands-on project
G.9.1.4.1 Solution
G.9.1.5 Case projects
G.9.1.5.1 Solution
G.9.1.6 Optional team case project
G.9.1.6.1 Solution
G.10 Chapter 10: The role of citizens in smart cities and urban infrastructures
G.10.1 Review questions/exercises
G.10.1.1 True/false
G.10.1.2 Multiple choice
G.10.1.3 Exercise
G.10.1.3.1 Solution
G.10.1.4 Hands-on project
G.10.1.4.1 Solution
G.10.1.5 Case projects
G.10.1.5.1 Solution
G.10.1.6 Optional team case project
G.10.1.6.1 Solution
G.11 Chapter 11: Smart city and metropolitan governance
G.11.1 Review questions/exercises
G.11.1.1 True/false
G.11.1.2 Multiple choice
G.11.1.3 Exercise
G.11.1.3.1 Solution
G.11.1.4 Hands-on project
G.11.1.4.1 Solution
G.11.1.5 Case projects
G.11.1.5.1 Solution
G.11.1.6 Optional team case project
G.11.1.6.1 Solution
G.12 Chapter 12: Distributed energy in smart cities and the infrastructure
G.12.1 Review questions/exercises
G.12.1.1 True/false
G.12.1.2 Multiple choice
G.12.1.3 Exercise
G.12.1.3.1 Solution
G.12.1.4 Hands-on project
G.12.1.4.1 Solution
G.12.1.5 Case projects
G.12.1.5.1 Solution
G.12.1.6 Optional team case project
G.12.1.6.1 Solution
G.13 Chapter 13: Energy efficient automated warehouse design
G.13.1 Review questions/exercises
G.13.1.1 True/false
G.13.1.2 Multiple choice
G.13.1.3 Exercise
G.13.1.3.1 Solution
G.13.1.4 Hands-on project
G.13.1.4.1 Solution
G.13.1.5 Case projects
G.13.1.5.1 Solution
G.13.1.6 Optional team case project
G.13.1.6.1 Solution
G.14 Chapter 14: Smart utilities
G.14.1 Review questions/exercises
G.14.1.1 True/false
G.14.1.2 Multiple choice
G.14.1.3 Exercise
G.14.1.3.1 Solution
G.14.1.4 Hands-on project
G.14.1.4.1 Solution
G.14.1.5 Case projects
G.14.1.5.1 Solution
G.14.1.6 Optional team case project
G.14.1.6.1 Solution
G.15 Chapter 15: Smart cities and infrastructure standardization requirements
G.15.1 Review questions/exercises
G.15.1.1 True/false
G.15.1.2 Multiple choice
G.15.1.3 Exercise
G.15.1.3.1 Solution
G.15.1.4 Hands-on project
G.15.1.4.1 Solution
G.15.1.5 Case projects
G.15.1.5.1 Solution
G.15.1.6 Optional team case project
G.15.1.6.1 Solution
G.16 Chapter 16: Securing smart-grid infrastructure against emerging threats
G.16.1 Review questions/exercises
G.16.1.1 True/false
G.16.1.2 Multiple choice
G.16.1.3 Exercise
G.16.1.3.1 Solution
G.16.1.4 Hands-on Project
G.16.1.4.1 Solution
G.16.1.5 Case projects
G.16.1.5.1 Solution
G.16.1.6 Optional team case project
G.16.1.6.1 Solution
G.17 Chapter 17: Components of the smart-grid system
G.17.1 Review questions/exercises
G.17.1.1 True/false
G.17.1.2 Multiple choice
G.17.1.3 Exercise
G.17.1.3.1 Solution
G.17.1.4 Hands-on project
G.17.1.4.1 Solution
G.17.1.5 Case projects
G.17.1.5.1 Solution
G.17.1.6 Optional team case project
G.17.1.6.1 Solution
G.18 Chapter 18: Introduction to energy management in smart grids
G.18.1 Review questions/exercises
G.18.1.1 True/false
G.18.1.2 Multiple choice
G.18.1.3 Exercise
G.18.1.3.1 Solution
G.18.1.4 Hands-on project
G.18.1.4.1 Solution
G.18.1.5 Case projects
G.18.1.5.1 Solution
G.18.1.6 Optional team case project
G.18.1.6.1 Solution
G.19 Chapter 19: DER, energy management, and transactive energy networks for smart cities
G.19.1 Review questions/exercises
G.19.1.1 True/false
G.19.1.2 Multiple choice
G.19.1.3 Exercise
G.19.1.3.1 Solution
G.19.1.4 Hands-on project
G.19.1.4.1 Solution
G.19.1.5 Case projects
G.19.1.5.1 Solution
G.19.1.6 Optional team case project
G.19.1.6.1 Solution
G.20 Chapter 20: Managing the generation and demand inside the smart-grid structure
G.20.1 Review questions/exercises
G.20.1.1 True/false
G.20.1.2 Multiple choice
G.20.1.3 Exercise
G.20.1.3.1 Solution
G.20.1.4 Hands-on project
G.20.1.4.1 Solution
G.20.1.5 Case projects
G.20.1.5.1 Solution
G.20.1.6 Optional team case project
G.20.1.6.1 Solution
G.21 Chapter 21: Energy management of multienergy and hybrid energy networks in smart grids
G.21.1 Review questions/exercises
G.21.1.1 True/false
G.21.1.2 Multiple choice
G.21.1.3 Exercise
G.21.1.3.1 Solution
G.21.1.4 Hands-on project
G.21.1.4.1 Solution
G.21.1.5 Case projects
G.21.1.5.1 Solution
G.21.1.6 Optional team case project
G.21.1.6.1 Solution
G.22 Chapter 22: Hybrid renewable energy systems, load, and generation forecasting, new grids structure and smart technologies
G.22.1 Review questions/exercises
G.22.1.1 True/false
G.22.1.2 Multiple choice
G.22.1.3 Exercise
G.22.1.3.1 Solution
G.22.1.4 Hands-on project
G.22.1.4.1 Solution
G.22.1.5 Case projects
G.22.1.5.1 Solution
G.22.1.6 Optional team case project
G.22.1.6.1 Solution
G.23 Chapter 23: Smart lighting for smart cities
G.23.1 Review questions/exercises
G.23.1.1 True/false
G.23.1.2 Multiple choice
G.23.1.3 Exercise
G.23.1.3.1 Solution
G.23.1.4 Hands-on project
G.23.1.4.1 Solution
G.23.1.5 Case projects
G.23.1.5.1 Solution
G.23.1.6 Optional team case project
G.23.1.6.1 Solution
G.24 Chapter 24: Smart cities critical infrastructure recommendations and solutions
G.24.1 Review questions/exercises
G.24.1.1 True/false
G.24.1.2 Multiple choice
G.24.1.3 Exercise
G.24.1.3.1 Solution
G.24.1.4 Hands-on project
G.24.1.4.1 Solution
G.24.1.5 Case projects
G.24.1.5.1 Solution
G.24.1.6 Optional team case project
G.24.1.6.1 Solution
G.25 Chapter 25: The city as a commons: the concept of common goods
G.25.1 Review questions/exercises
G.25.1.1 True/false
G.25.1.2 Multiple choice
G.25.1.3 Exercise
G.25.1.3.1 Solution
G.25.1.4 Hands-on project
G.25.1.4.1 Solution
G.25.1.5 Case projects
G.25.1.5.1 Solution
G.25.1.6 Optional team case project
G.25.1.6.1 Solution
G.26 Chapter 26: Resilient future energy systems: smart grids, vehicle-to-grid, and microgrids
G.26.1 Review questions/exercises
G.26.1.1 True/false
G.26.1.2 Multiple choice
G.26.1.3 Exercise
G.26.1.3.1 Solution
G.26.1.4 Hands-on project
G.26.1.4.1 Solution
G.26.1.5 Case projects
G.26.1.5.1 Solution
G.26.1.6 Optional team case project
G.26.1.6.1 Solution
G.27 Chapter 27: Connected autonomous vehicles in smart cities
G.27.1 Review questions/exercises
G.27.1.1 True/false
G.27.1.2 Multiple choice
G.27.1.3 Exercise
G.27.1.3.1 Solution
G.27.1.4 Hands-on project
G.27.1.4.1 Solution
G.27.1.5 Case projects
G.27.1.5.1 Solution
G.27.1.6 Optional team case project
G.27.1.6.1 Solution
G.28 Chapter 28: Future developments in vehicle-to-grid (V2G) technologies
G.28.1 Review questions/exercises
G.28.1.1 True/false
G.28.1.2 Multiple choice
G.28.1.3 Exercise
G.28.1.3.1 Solution
G.28.1.4 Hands-on project
G.28.1.4.1 Solution
G.28.1.5 Case projects
G.28.1.5.1 Solution
G.28.1.6 Optional team case project
G.28.1.6.1 Solution
G.29 Chapter 29: Designing inclusive smart cities of the future: the Indian context
G.29.1 Review questions/exercises
G.29.1.1 True/false
G.29.1.2 Multiple choice
G.29.1.3 Exercise
G.29.1.3.1 Solution
G.29.1.4 Hands-on project
G.29.1.4.1 Solution
G.29.1.5 Case projects
G.29.1.5.1 Solution
G.29.1.6 Optional team case project
G.29.1.6.1 Solution
Appendix H Glossary
Index
Back Cover

Citation preview

Solving Urban Infrastructure Problems Using Smart City Technologies

Solving Urban Infrastructure Problems Using Smart City Technologies Handbook on Planning, Design, Development, and Regulation

Edited by

John R. Vacca

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2021 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress ISBN: 978-0-12-816816-5 For Information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Joe Hayton Acquisitions Editor: Romer Brian Editorial Project Manager: Charlotte Kent Production Project Manager: Omer Mukthar Cover Designer: Greg Harris Typeset by MPS Limited, Chennai, India

In memory of Michael Erbschloe (1951 2019).

Contents

List of contributors About the editor Foreword Preface Acknowledgments

Part I Overview of smart cities and infrastructure technologies: a comprehensive introduction 1

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Introduction to the critical success factors of E-government adoption of the utilization of emerging smart cities technologies Nasser A. Saif Almuraqab 1.1 Introduction 1.2 E-government and M-government 1.3 M-government adoption in developing countries 1.4 Smart government in developing counties: the case of United Arab Emirates 1.5 Conceptual model of smart government adoption 1.6 Conclusion and future research 1.7 Summary 1.8 Chapter review questions/exercises References Smart-city infrastructure components Amir Hoshang Fakhimi, Ali Hossein Khani and Javad Majrouhi Sardroud 2.1 Introduction 2.2 Smart-city definitions 2.3 Smart-city key foundations (PILARS) 2.4 Smart-city infrastructure platforms and domains 2.5 Summary 2.6 Chapter review questions/exercises References Smart buildings and urban spaces Zheng Ma, Bo Nørregaard Jørgensen and Joy Dalmacio Billanes 3.1 Introduction

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1 3 3 4 5 6 9 9 10 11 12 17 17 18 20 21 47 48 50 55 55

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3.2 Smart building systems 3.3 Building types in the urban space 3.4 Permits and standards for smart buildings 3.5 Smart building market potentials 3.6 Summary 3.7 Chapter review questions/exercises References

57 60 66 72 80 81 83

Urban mobility systems components Doaa M. El-Sherif 4.1 Introduction 4.2 Mobility, transportation, and accessibility 4.3 Evolution of urban mobility 4.4 Types of transit systems 4.5 The urban mobility challenge 4.6 Urban mobility in the context of sustainability 4.7 Urban mobility in the smart-city age 4.8 Summary 4.9 Chapter review questions/exercises References

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Coupling of the mobility and energy infrastructures as urban mobility needs evolve Andreas Pfeiffer, Alexandra Burgholzer and Dilara Kanag 5.1 Introduction 5.2 Trends that shape urban mobility 5.3 An answer from energy and mobility sectors to urbanization and clean trends 5.4 Examples of urban mobility components 5.5 Action recommendations for regulators 5.6 Outlook 5.7 Summary 5.8 Chapter review questions/exercises References Smart urban mobility traffic control system components Michela Longo, Wahiba Yaici and Federica Foiadelli 6.1 Introduction 6.2 Electric mobility 6.3 Types of electric vehicles 6.4 Electric vehicle supply equipment 6.5 Electric vehicle charging modes 6.6 Summary 6.7 Chapter review questions/exercises References

89 89 91 93 94 95 98 104 104 106 107 107 109 110 114 118 121 123 124 126 129 129 130 132 135 135 138 139 141

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Urbanization and smart cities Ritu Mohanty and Bipin Pradeep Kumar 7.1 Introduction 7.2 The future of urbanization and need for the smart city 7.3 IoT- and ICT-led initiatives as enablers of smart cities 7.4 Smart cities, urban planning, and policy 7.5 Challenges and opportunities of smart cities 7.6 Conclusion 7.7 Summary 7.8 Chapter review questions/exercises References Priority activities for smart cities and the infrastructure Cathryn Peoples 8.1 Introduction 8.2 Background information 8.3 Generating the market 8.4 Blocks to the market 8.5 Expanding the market 8.6 Greening the market 8.7 Enablers 8.8 Training and involving stakeholders 8.9 Summary 8.10 Chapter review questions/exercises References

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143 143 143 145 147 151 154 155 156 158 159 159 161 162 163 166 167 169 173 176 177 179

Part II Planning, design, development and management of smart cities and infrastructure technologies

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Open Data for smart cities Bipin Pradeep Kumar 9.1 Introduction 9.2 The rise of urban data 9.3 Open Data, Big Data, Linked Data, and Linked Open Data 9.4 More about Open Data 9.5 National paths to open data 9.6 Open Data value chain 9.7 Eliminating silos by sharing or Open Data 9.8 Data marketplaces 9.9 Conclusion 9.10 Summary 9.11 Chapter review questions/exercises Acknowledgments References

185 186 187 190 194 196 202 204 206 207 207 209 209

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The role of citizens in smart cities and urban infrastructures Carles Agustı´ Herna`ndez 10.1 Introduction 10.2 Smart city 10.3 Citizens 10.4 Urban infrastructures 10.5 From passive citizen to active citizens 10.6 Open government 10.7 Governance 10.8 Technological governance 10.9 Hybridizations and changes in citizen governance 10.10 Citizens in the city and urbanism in smart-cities world 10.11 Practical cases 10.12 Corruption and urbanism 10.13 Transparency and citizen role in urbanism and infrastructures 10.14 Superation of citizen participation topics 10.15 Summary 10.16 Chapter review questions/exercises References Smart city and metropolitan governance Mats Andersson 11.1 Introduction 11.2 How can cities benefit from cooperation on the smart city subject in a metropolitan area? 11.3 What metropolitan governance arrangement is needed? 11.4 What are the obstacles to collaboration across jurisdictions? 11.5 Application of the intermunicipal cooperation arrangement 11.6 Summary 11.7 Chapter review questions/exercises References

213 213 213 214 214 215 217 218 219 219 221 223 228 228 230 232 232 234 235 235 236 237 241 242 243 244 246

Part III Renewable energy technologies for smart cities and the critical infrastructure

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Distributed energy in smart cities and the infrastructure Essam E. Khalil 12.1 Introduction 12.2 Smart cities 12.3 Instrumental procedures in smart cities 12.4 A selection of smart cities standards 12.5 Energy strategy 12.6 Factors affecting energy in smart city

249 250 252 255 255 257

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12.7 Smart-city hacking 12.8 Energy efficient designs of sustainable buildings 12.9 Summary 12.10 Chapter review questions/exercises References

259 260 265 266 267

Energy efficient automated warehouse design Melis Ku¨c¸u¨kya¸sar, Banu Yetkin Ekren and Tone Lerher 13.1 Introduction 13.2 Literature review 13.3 System description and model assumptions in the system 13.4 Simulation modeling of the system 13.5 Results and discussion 13.6 Suggested future works 13.7 Summary 13.8 Chapter review questions/exercises Acknowledgment References

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Smart utilities Tuncay Ercan and Mahir Kutay 14.1 Introduction 14.2 Smart solutions 14.3 Electricity 14.4 Water 14.5 Natural gas 14.6 Summary and business models for utility industry 14.7 Chapter review questions/exercises References

269 272 273 277 279 288 288 289 291 291 293 293 295 300 312 318 321 323 325

Part IV Standardization and regulation of technologies and security for smart cities and the critical infrastructure

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Smart cities and infrastructure standardization requirements Neena Pahuja 15.1 Introduction 15.2 Data monetization: open data to increase community engagement 15.3 Smart-city technology architecture 15.4 Smart-city application architecture 15.5 Smart energy and light 15.6 Gearing-up for smart health in cities 15.7 City services’ architecture and assets management 15.8 Smart-city data democracy architecture

331 332 333 335 343 343 346 350

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15.9 Security, privacy, and business continuity concerns of data hub 15.10 Summary 15.11 Chapter review questions/exercises References

354 355 355 357

Securing smart-grid infrastructure against emerging threats Daisuke Mashima 16.1 Introduction 16.2 Emerging cyber threats targeting smart grid 16.3 Security solutions for protecting smart grid 16.4 Supervisory control and data acquisition command authentication as additional line of defense 16.5 Summary 16.6 Chapter review questions/exercises References

359 359 360 361 365 377 378 380

Part V Smart grid technologies for smart cities and the critical infrastructure

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Components of the smart-grid system Baseem Khan, Habtamu Getachew and Hassan Haes Alhelou 17.1 Introduction 17.2 Components of smart grid 17.3 Summary 17.4 Chapter review questions/exercises References

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Introduction to energy management in smart grids Essam E. Khalil 18.1 Introduction 18.2 Elements of the smart grid 18.3 Energy management 18.4 Energy management in operational functions 18.5 Energy management challenges 18.6 Energy management standards 18.7 Summary 18.8 Chapter review questions/exercises References

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DER, energy management, and transactive energy networks for smart cities Satyam Bheemarasetti and Ravi Prasad Patruni 19.1 Introduction 19.2 TEN for smart cities—stakeholders, market forces, and technologies

385 385 393 393 395

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19.3 DER: distributed energy resources 19.4 Evolution of key subsystems for transactive energy 19.5 Digital systems and components—10 enablers 19.6 Smart TE microgrids 19.7 Markets and operators (short and long term) 19.8 Transactive energy strategy and challenges 19.9 Summary 19.10 Chapter review questions/exercises References 20

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Managing the generation and demand inside the smart-grid structure Baseem Khan, Esayas Gidey, Habtamu Getachew and Hassan Haes Alhelou 20.1 Introduction 20.2 Energy management techniques in smart grid 20.3 Smart energy management system 20.4 Summary 20.5 Chapter review questions/exercises References Introduction to energy management in smart grids P. Lazzeroni, M. Repetto and H. Gabbar 21.1 Introduction 21.2 Energy management system: the optimization procedure XEMS13 21.3 Case study 21.4 Summary 21.5 Chapter review questions/exercises References Hybrid renewable energy systems, load and generation forecasting, new grids structure, and smart technologies ¨ Aliona Dreglea, Aoife Foley, Ulf Hager, Denis Sidorov and Nikita Tomin 22.1 Introduction 22.2 Summary 22.3 Conclusions 22.4 Chapter review questions/exercises References Smart lighting for smart cities Matthew Palmer and Ronald Gibbons 23.1 Introduction 23.2 Smart lighting basics

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23.3 More advanced concepts 23.4 Smart lighting example 23.5 Potential challenges 23.6 Summary 23.7 Chapter review questions/exercises References

492 494 495 496 497 499

Part VI Recommended technologies and solutions for smart cities and the critical infrastructure

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Smart cities critical infrastructure recommendations and solutions Tuncay Ercan and Mahir Kutay 24.1 Introduction 24.2 Critical city infrastructures 24.3 Communications 24.4 Energy (electricity, gas, and oil) 24.5 Water 24.6 Public transportation 24.7 Emergency services 24.8 Summary 24.9 Chapter review questions/exercises References

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The city as a commons: the concept of common goods Marco Buemi 25.1 Introduction 25.2 Defining the topic 25.3 The commons and the OECD 25.4 The commons and the European Union 25.5 Coproduction and the European Social Fund 25.6 The Bologna regulation on public collaboration for urban commons: theoretical basis 25.7 Italy and the commons 25.8 The Bologna regulation on public collaboration for urban commons 25.9 From the commons to the city as a commons 25.10 The cocity index 25.11 Urban innovative action in the city of Turin 25.12 The city of Verona and subsidiarity pacts with active citizens 25.13 The commons and civic crowdfunding 25.14 Best Italian practices in matching public funds with private ones: the city of Milan and Turin 25.15 The role of institutions in promoting civic crowdfunding 25.16 Summary

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25.17 Chapter review questions/exercises References

Part VII The future of smart cities and the critical infrastructure 26

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Resilient future energy systems: smart grids, vehicle-to-grid, and microgrids ¨ Alexander Domyshev, Ulf Hager, Daniil Panasetsky, Denis Sidorov and Pantelis Sopasakis 26.1 Introduction 26.2 Optimization of urban electric grids with EV charging load and V2G generation 26.3 Resilient operational control of microgrids 26.4 Smart grids and digital twins 26.5 Summary 26.6 Chapter review questions/exercises References Future of connected autonomous vehicles in smart cities Hossam Gaber, Ahmed M. Othman and Abul Hasan Fahad 27.1 Introduction 27.2 Components of smart city 27.3 Connected and autonomous vehicle functional architecture 27.4 CAV and smart mobility 27.5 CAV and smart energy 27.6 CAV and smart home 27.7 CAV and smart health 27.8 CAV testing and verification platform 27.9 Summary 27.10 Chapter review questions/exercises References Future developments in vehicle-to-grid technologies Michela Longo, Wahiba Yaici and Federica Foiadelli 28.1 Introduction 28.2 Smart grid 28.3 Vehicle to grid 28.4 State-of-the-art of the V2G 28.5 Charging/discharging strategy 28.6 Summary 28.7 Chapter review questions/exercises References

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569 571 571 576 584 589 590 591 593 599 599 600 601 605 605 606 607 607 609 609 611 613 613 615 616 618 623 626 627 628

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Designing inclusive smart cities of the future: the Indian context Charru Malhotra, Vinti Manchanda, Anushka Bhilwar and Aniket Basu 29.1 Introduction 29.2 Review of literature 29.3 Learning from existing global implementations 29.4 Understanding Indian context 29.5 Proposed conceptual model of an inclusive smart city 29.6 Recommendations 29.7 Summary 29.8 Chapter review questions/exercises References

Part VIII

Appendices

631 631 633 637 640 644 648 653 654 656

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Appendix A: List of top smart cities and critical infrastructure implementation and deployment companies Appendix B: List of smart cities and critical infrastructure products/projects Appendix C: List of smart cities and critical infrastructure standards Appendix D: List of miscellaneous smart cities and critical infrastructure resources Appendix E: Smart cities and critical infrastructure frequently asked questions Appendix F: List of smart cities and critical infrastructure case studies Appendix G: Answers to review questions/exercises, hands-on projects, case projects, and optimal team case project by chapter Appendix H: Glossary

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Index

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663 681 685 693 695 699

List of Contributors

Hassan Haes Alhelou Tishreen University, Latakia, Syria Nasser A. Saif Almuraqab Dubai Business School, University of Dubai, United Arab Emirates Mats Andersson Urban Management Consultant, San Francisco, United States Aniket Basu Indian Institute of Public Administration, New Delhi, India Satyam Bheemarasetti NeoSilica Technologies Pvt. Ltd. Cyber Towers, Hi-Tech City, Hyderabad, India Anushka Bhilwar Shallate Service Pvt. Ltd, New Delhi, India Joy Dalmacio Billanes Department of Business Development and Technology, Aarhus University, Herning, Denmark Marco Buemi Turin, Italy Alexandra Burgholzer E.ON Solutions GmbH, Essen, Germany Alexander Domyshev Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences (ESI SB RAS), Irkutsk, Russia Aliona Dreglea Energy Systems Institute, Russian Academy of Sciences, Irkutsk National Research Technical University, Irkutsk, Russia Banu Yetkin Ekren Department of Industrial Engineering, Yasar University Doaa M. El-Sherif Urban Training and Studies Institute “UTI”—Housing and Building National Research Center “HBRC,” Cairo, Egypt Tuncay Ercan Faculty of Engineering Universite cad., School of Applied Sciences, Yasar University, Izmir, Turkey Abul Hasan Fahad University of Ontario Institute of Technology (UOIT), Oshawa, ON, Canada

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List of Contributors

Amir Hoshang Fakhimi Department of Civil Engineering, Kashan University, Islamic Azad University, Kashan, Iran Federica Foiadelli Politecnico di Milano, Milan, Italy Aoife Foley Queens University Belfast, Belfast, United Kingdom H. Gabbar Energy Systems and Nuclear Science Research Centre (ERC), North Oshawa, Ontario, Canada Hossam Gaber University of Ontario Institute of Technology (UOIT), Oshawa, ON, Canada Habtamu Getachew Hawassa University, Awassa, Ethiopia Ronald Gibbons Virginia Tech Transportation Institute, Center for Infrastructure Based Safety Systems, Blacksburg, VA, United States Esayas Gidey Hawassa University, Awassa, Ethiopia Ulf H¨ager Institute of Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund, Germany Carles Agustı´ Herna`ndez Open Government Presidency Area, Barcelona, Spain Bo Nørregaard Jørgensen SDU Center for Energy Informatics, The Maersk McKinney Moller Institute, University of Southern Denmark, Odense, Denmark Dilara Kanag E.ON Solutions GmbH, Essen, Germany Essam E. Khalil Faculty of Engineering, Cairo University, Cairo, Egypt Baseem Khan Hawassa University, Awassa, Ethiopia Ali Hossein Khani Department of Civil Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran Melis Ku¨c¸u¨kya¸sar Department of Industrial Engineering, Yasar University Bipin Pradeep Kumar Gaia Smart Cities Solutions Pvt Ltd, Mumbai, India Mahir Kutay Faculty of Engineering Universite cad., School of Applied Sciences, Yasar University, Izmir, Turkey P. Lazzeroni LINKS Foundation, via Pier Carlo Boggio, Torino, Italy

List of Contributors

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Tone Lerher Faculty of Mechanical Engineering, University of Maribor Michela Longo Politecnico di Milano, Milan, Italy Zheng Ma SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark Charru Malhotra Indian Institute of Public Administration, New Delhi, India Vinti Manchanda Shallate Service Pvt. Ltd, New Delhi, India Daisuke Mashima Advanced Digital Sciences Center, Illinois at Singapore Pte Ltd, Singapore, Singapore Ritu Mohanty Padora Urban Design, Mumbai, India Ahmed M. Othman University of Ontario Institute of Technology, and Zagazig University, Oshawa, ON, Canada Neena Pahuja ERNET India, Ministry of Electronics and Information Technology, New Delhi, India Matthew Palmer Virginia Tech Transportation Institute, Center for Infrastructure Based Safety Systems, Blacksburg, VA, United States Daniil Panasetsky Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences (ESI SB RAS), Irkutsk, Russia Ravi Prasad Patruni NeoSilica Technologies Pvt. Ltd. Cyber Towers, Hi-Tech City, Hyderabad, India Cathryn Peoples Ulster University, Londonderry, United Kingdom Andreas Pfeiffer CUT POWER AG, Essen, Germany; RWTH Aachen University, Essen, Germany M. Repetto Politecnico di Torino - Dipartimento Energia “Galileo Ferraris,” Corso Duca degli Abruzzi, Torino, Italy Javad Majrouhi Sardroud Department of Civil Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran Denis Sidorov Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences (ESI SB RAS), Irkutsk, Russia; Irkutsk National Research Technical University, Irkutsk, Russia; Institute of Energy Systems Russian Academy of Sciences (SB), Irkutsk, Russia

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List of Contributors

Pantelis Sopasakis Queen’s University Belfast, School of Electronics, Electrical Engineering and Computer Science and i-AMS Centre, Belfast, United Kingdom Nikita Tomin Energy Systems Institute SB RAS, Irkutsk, Russia Wahiba Yaici CanmetENERGY Research Centre, Ottawa, Canada

About the editor

John R. Vacca is an information technology consultant, researcher, professional writer, editor, reviewer, and internationally known, best-selling author based in Pomeroy, Ohio. Since 1982, John has authored/edited 82 books (some of his most recent books include): G

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Online Terrorist Propaganda, Recruitment, and Radicalization, 1st Edition [Publisher: CRC Press (an imprint of Taylor & Francis Group, LLC) (August 9, 2019)] Nanoscale Networking and Communications Handbook, 1st Edition [Publisher: CRC Press (an imprint of Taylor & Francis Group, LLC) (July 22, 2019)] Computer and Information Security Handbook, 3E [Publisher: Morgan Kaufmann (an imprint of Elsevier Inc.) (June 10, 2017)] Cloud Computing Security: Foundations and Challenges [Publisher: CRC Press (an imprint of Taylor & Francis Group, LLC) (September 14, 2016)] Security in the Private Cloud [Publisher: CRC Press (an imprint of Taylor & Francis Group, LLC) (August 26, 2016)] Handbook of Sensor Networking: Advanced Technologies and Applications [Publisher: CRC Press (an imprint of Taylor & Francis Group, LLC) (January 14, 2015)] Network and System Security, Second Edition, 2E [Publisher: Syngress (an imprint of Elsevier Inc.) (September 23, 2013)] Cyber Security and IT Infrastructure Protection [Publisher: Syngress (an imprint of Elsevier Inc.) (September 23, 2013)] Managing Information Security, Second Edition, 2E [Publisher: Syngress (an imprint of Elsevier Inc.) (September 23, 2013)] Computer and Information Security Handbook, 2E [Publisher: Morgan Kaufmann (an imprint of Elsevier Inc.) (May 31, 2013)] Identity Theft (Cybersafety) [Publisher: Chelsea House Pub (April 1, 2012)] System Forensics, Investigation, And Response [Publisher: Jones & Bartlett Learning (September 24, 2010)] Managing Information Security [Publisher: Syngress (an imprint of Elsevier Inc.) (March 29, 2010)] Network and Systems Security [Publisher: Syngress (an imprint of Elsevier Inc.) (March 29, 2010)]

and, more than 600 articles in the areas of advanced storage, computer security and aerospace technology (copies of articles and books are available upon request).

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About the editor

He was also a configuration management specialist, computer specialist, and the computer security official (CSO) for NASA’s space station program (Freedom) and the International Space Station Program, from 1988 until his retirement from NASA in 1995. In addition, he is also an independent online book reviewer. Finally, he was one of the security consultants for the MGM movie titled: “AntiTrust,” which was released on January 12, 2001. A detailed copy of my author bio can be viewed at URL: http://www.johnvacca.com. He can be reached at: [email protected].

Foreword

The combined forces of urbanization and technology are disrupting existing cities and placing new demands on municipal governments. Local leaders are striving to sustain effective and economical basic services (water, energy and transportation, and connectivity). In the hope that economic growth and opportunities for prosperity will continue, many cities are embracing smart city technology and planning methods. Smart cities are emerging as the next-generation approach for city management and urban planning as well as integrating intelligent transportation systems, connected vehicle technologies, automated vehicles, and electric vehicles and the soon to be flying cars and trucks. The smart-city concept also includes the interconnection of transportation and nontransportation services to improve city services and the quality of life for citizens. The expectations of smart city technology include improved transportation safety as well as enhanced mobility for all citizens along with expanded ladders of opportunity through connectivity to employment, education, and other services. Smart city technology will also help address climate change through the deployment of technologies and adoption of policies that support a sustainable and cost-effective relationship between urban needs and the environment such as the development of interconnected multimodal transportation centers that serve as hubs for mobility, economic development, and community activity. Green technology is an integral part of smart city management including the use of renewable energy sources, practicing energy efficient operations, the management of municipal solid waste, recycling or reuse of consumables, and implementation of urban agriculture and sustainable forestry practices that can produce fresh food closer to the point of consumption. Solving Urban Infrastructure Problems Using Smart City Technologies handbook is an essential tool for all of the stakeholders in a smart-city environment. It provides insights as well as actionable knowledge for the numerous elements and aspects of creating, maintaining, governing, and living in a smart city. Michael Erbschloe Author and Information Security Consultant Michael Erbschloe taught information security courses at Webster University in St. Louis, MO, United States.

Preface

This comprehensive handbook serves as a professional reference, as well as a practitioner’s guide to today’s most complete and concise view of the rapidly growing phenomenon of smart cities next generation engineering approaches for urbanization. It offers an in-depth coverage of how smart cities aim to exploit the intellectual and social capital as its core ingredient for urbanization, in addition to the physical and information and communication technology critical infrastructure. A functional approach has been adopted regarding the classification of smart cities that are driven by several interdependent trends. This approach explores practical problems and solutions in identifying the following somewhat overlapping categories: the pressing need for environmental sustainability, and peoples increasing demands for personalization, mobility, and higher quality of life. This handbook also examines the technological developments such as miniaturization of devices, big data, and the decreasing costs of computational entities that have also accelerated the smart cities developments. In other words, smart cities encompass all aspects of modern day life, transportation, healthcare, entertainment, work, businesses, social interactions, governance, etc. It is therefore necessary to solve the problems of how to engineer smart cities as complex systems of systems supported by a converged ubiquitous critical infrastructure. A key problem in the realization of smart cities is to create an ecosystem of digital critical infrastructures that are able to work together and enable dynamic real-time interactions between various smart-city subsystems. With this background, this handbook invites contributed submissions by experts in the field that propose state of the art solutions for smart cities systems engineering problems. It will bring together experts from academia, government, and industry to give their views on how smart technology can be used to improve the lives of billions of people living in towns and cities around the globe. A wide range of topics will be covered providing exclusive insights into how we can transform our urban areas to make them more efficient, more sustainable, and safer. The primary audience for this handbook consists of researchers and practitioners in industry and academia, as well as executives; policy-makers; regulators; city planners; utility network specialists; industry experts; startuppers; chief information officers; heads of economic development; heads of sustainability; heads of planning; heads of transport; heads of innovation; e-government leads; heads of inward investment; financial investors and entrepreneurs, heads of growth and regeneration; councilors; local authority officials; community managers; development managers; directors; senior managers; strategic directors; heads of planning; urban planners; project and program managers and heads of research and innovation that will be drawn from government; government leaders involved with new urban

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economic growth, designing new cities, and urban creative regions or zones; engineers and designers; local decision-makers; local authorities; local enterprise partnerships; higher education, health and social care; transport; business unit leaders; and local businesses and the voluntary and private sector. This comprehensive reference and practitioner’s guide will also be of value to a secondary audience, which is comprised of students in upper-division undergraduate and graduate-level courses in the engineering of smart cities and infrastructure technologies.

Organization of this book The book is organized into 8 parts composed of 29 contributed chapters by leading experts in their fields, as well as 8 appendices, including an extensive glossary of smart cities and critical infrastructure terms and acronyms.

Part I: Overview of smart cities and infrastructure technologies: a comprehensive introduction Part I discusses how to build smart cities; technology and trends; smart city infrastructure components; smart buildings and urban spaces; urban mobility systems components; urbanization and smart cities; and priority activities for smart cities and the infrastructure. For instance: Chapter 1, “Introduction to the Critical Success Factors of E-Government Adoption of the Utilization of Emerging Smart Cities Technologies,” addresses the major factors that influence user acceptance of digital government services. Chapter 2, “Smart City Infrastructure Components,” describes the main components of the smart-city infrastructure, in the form of social, physical, and digital platforms with 12 domains and 48 main components. Chapter 3, “Smart Buildings and Urban Spaces,” introduces four aspects that are strongly interconnected: the software and hardware of the smart building systems; building types in the urban spaces; permits and standards for smart buildings; and smart building market potentials. Chapter 4, “Urban Mobility Systems Components,” reviews the basic definitions related to its topic; illustrates the interrelationship between mobility, transportation, and accessibility as the core of accessibility-based urban mobility; discusses the urban mobility challenges, and urban mobility in the context of sustainability; addresses different aspects of sustainable urban mobility, its relation with public transport development and land-use planning; and discusses the urban mobility in the smart-city age. Chapter 5, “Coupling of the Mobility and Energy Infrastructures As Urban Mobility Needs Evolve,” presents the positive impact that recent technological developments can have on urban energy and mobility infrastructures, as well as recommendations for urban policy shapers for nurturing these. Chapter 6, “Urban Mobility Systems Components,” presents a general discussion of the panorama of electric mobility, which includes: a brief introduction of, and current developments regarding electric vehicles around the world; the different types of electric vehicles (EVs) currently available according to their hybridization levels; the various charging

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methods and the related systems and equipment as part of infrastructure of the electric vehicle supply equipment (EVSE). Chapter 7, “Urbanization and Smart Cities,” focuses on the challenges of global urbanization by recognizing the potential of integrating physical, social, ecological, and technological infrastructures. Chapter 8, “Priority Activities for Smart Cities and the Infrastructure,” discusses the activities required to support the achievement of anticipated projections for the smart-city domain.

Part II: Planning, design, development, and management of smart cities and infrastructure technologies Part II discusses smart cities and infrastructure planning and development; smart infrastructure design principles and policy approaches; and smart city and infrastructure governance. For instance: Chapter 9, “Open Data for Smart Cities,” presents the anthropological description of the common hallmarks and legacies of urbanization; a general overview of the perspectives and issues of data and open data with specific implications for cities and the public sector; discusses whether and how open data can promote more participative and collaborative forms of governance; describes the extension of open data by linked data and linked open/government data; discusses the value chain of open data in cities with its set of activities; describes whether open data needs to be free, the data formats used to make data open, the kinds of licenses used and the challenges posed by open data projects and initiatives; covers the path taken by a few nations with their open data portals in order to introduce the progress behind the theory; explores and illustrates (by way of relevant scenarios) the benefits of sharing data even between departments, and the impact the successful implementation of services has on another department; and presents the possibilities for cities to create data market places from which they may derive additional revenue and commercial value. Chapter 10, “The Role of Citizens in Smart Cities and Urban Infrastructures,” looks at how the evolution of society changes the role of citizens in the governance of modern cities, as well as its role in relation to city infrastructures. Chapter 11, “Smart City and Metropolitan Governance,” outlines how cities in a metropolitan area can benefit from collaboration on their smart city developments through an intermunicipal forum or council.

Part III: Renewable energy technologies for smart cities and the critical infrastructure Part III discusses distributed energy in smart cities and the infrastructure; and smart utilities. For instance: Chapter 12, “Distributed Energy in Smart Cities and the Infrastructure,” presents the important factors affecting the energy efficiency in a built environment, through reviewing the issues of energy storage and related problems; the need for smart microgrids; and how to keep a smart and sustainable balance.

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Chapter 13, “Energy Efficient Automated Warehouse Design,” proposes a novel design concept for SBS/RS design, namely, tier-to-tier SBS/RS design; and investigate how its performance change in terms of energy consumption and cycle time per transaction under different warehouse design metrics, such as rack design, number of shuttles, and velocity profiles of shuttles and lifts. Chapter 14, “Smart Utilities,” examines the needs and expectations of the customers; residents who use smart utilities and services; general information about these services; the need for energy; the availability of resources; the balance of supply and consumption from the point of consumers and providers; and intelligent infrastructures.

Part IV: Standardization and regulation of technologies and security for smart cities and the critical infrastructure Part IV discusses smart cities and infrastructure standardization requirements; and regulating smart cities: critical infrastructure, sharing, and financing. For instance: Chapter 15, “Smart Cities and Infrastructure Standardization Requirements,” covers the need for standardization by collating some of the basic requirements of smart cities; and keeping data security guidelines in mind, with a usable list of applications, which can benefit from open architecture and infrastructure standardization. Chapter 16, “Securing Smart Grid Infrastructure Against Emerging Threats,” discusses the details of the representative cybersecurity incidents that have targeted the power grid systems.

Part V: Smart-grid technologies for smart cities and the critical infrastructure Part V discusses smart grids in smart cities and the infrastructure; components of smart grids; and introduction to energy management in smart grids. Chapter 17, “Components of The Smart Grid System,” discusses the various components of the power system such as smart appliances, smart meters, smart substations, distributed generations, integrated communication and sensing, and measurement components in detail. Chapter 18, “Introduction to Energy Management in Smart Grids,” contains a wide range of energy management techniques that have been adapted for smart homes, with the goal of increasing efficiency and reducing wasted energy. Chapter 19, “DER, Energy Management, And Transactive Energy Networks For Smart Cities,” describes the new energy paradigm with integrated smart systems from field to cloud; IoT and AI, as part of the digital transformation, which will allow energy to be transacted between prosumers, through energy markets; various DER, from renewable generation to demand response (DR); and the details of underlying digital components that form the foundation of OT 1 IT systems for transactive energy and smart microgrids. Chapter 20, “Managing the Generation and Demand Inside the Smart Grid Structure,” addresses the different techniques for the management of the generation and demand inside the smart grid structure; how the traditional power grid is transforming into the smart grid system in various part of the world; and how inside the smart grid environment, more and more energy sources are integrated into the system, and the management of energy generation and demand becomes a very critical issue.

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Chapter 21, “Energy Management of Multi-Energy and Hybrid Energy Networks in Smart Grids,” addresses the simulation of power in multienergy or hybrid energy networks and evaluation of their key performance indexes; mathematical optimization of hybrid energy networks by means of mixed integer linear programming; the computational cost of the procedure; interaction with forecasting of power demand and prices; and a case study in planning and operation of energy management systems—both in case of industrial and residential facilities, district heating and cooling systems, water networks, and transportation infrastructures. Chapter 22, “Hybrid Renewable Energy Systems, Load and Generation Forecasting, New Grids Structure and Smart Technologies,” gives a brief introduction to the management of energy in smart grids, by focusing on the hybrid renewable energy systems, load and generation forecasting, new grids structure and smart technologies; and the classification of smart infrastructure systems and smart energy management systems—with a focus on both the demand side management and supply side management. Chapter 23, “Smart Lighting for Smart Cities,” focuses on what “smart lighting” is and the benefits of such a system; dimmable LED luminaires with sensor and controller interfaces; a controlling system; support infrastructure; how the control system is comprised of luminaire nodes; a communication network with one or more luminaire node controllers; a human interface; and when adaptive lighting is implemented, how it reduces lighting energy usage, while providing higher quality light for improved safety.

Part VI: Recommended technologies and solutions for smart cities and the critical infrastructure Part VI discusses smart cities critical infrastructure recommendations and solutions; and applying smart city concepts: key challenges of science, technology and innovation (STI)-driven solutions. For instance: Chapter 24, “Smart Cities Critical Infrastructure Recommendations and Solutions,” discusses recommendations and solutions about how the ideal city management should be structured, with regards to critical city services and current state-of-art technologies. Chapter 25, “The City as a Commons: The Concept of Common Goods,” examines the concept of common goods and, more specifically, of the city as a commons; focuses on Italian experiments developed during the last decade; paying particular attention to the model adopted by the city of Bologna, which has gained international recognition as a pioneer in the field; and to three other Italian cities as study cases: Turin, Verona, and Milan.

Part VII: The future of smart cities and the critical infrastructure Part VII discusses a more futuristic livable, high-performance, entrepreneurial smart cities, and infrastructure solution; resilient future energy systems like: smart grids, vehicle-to-grid, and microgrids; and the future of urban implementation and development. For instance: Chapter 26, “Resilient Future Energy Systems: Smart Grids, Vehicle-to-Grid, and Microgrids,” presents a brief introduction to data-driven energy systems, with a special focus on methods and algorithms for hedging against the ever increasing uncertainty that surrounds their operation; and special attention is paid to operation control, stochastic

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optimization, and introduction of the digital twins to achieve higher resilience in future energy systems of smart cities. Chapter 27, “Future of Connected Autonomous Vehicles in Smart Cities,” presents the connected and autonomous vehicles (CAV) in the context of the smart city; the interaction and integration of CAV with important smart-city components; and the communication and verification platform for CAV at the University of Ontario Institute of Technology (UOIT). Chapter 28, “Future Developments in Vehicle-To-Grid (V2G) Technologies,” focuses on the previous developments made in vehicle-to-grid (V2G) technologies, as well as their considerations, constrains, and advantages—to take them as a starting point for future research topics related to methods, simulations, and analysis. Chapter 29, “Designing Inclusive Smart Cities of the Future: The Indian Context,” aims to enhance the existing concept of smart cities to inclusive smart cities; advocates a threesieved filter that insists all smart cities to be necessarily “accessible,” and “adaptable,” as well as “affordable” (AAA), to the needs and aspirations of the “elderly,” “poor and disadvantaged”; and with “people with disabilities,” henceforth referred together as “differently abled communities” (DAC).

Supplemental materials Instructor materials including appendices and glossary, lecture slides, figures from the text, exercise solutions, and sample syllabi are available at: store.elsevier.com/product. jsp?isbn 9780128168165 (click the “Resources” tab at the bottom of the page). [email protected] www.johnvacca.com John R. Vacca

Acknowledgments

There are many people whose efforts on this book have contributed to its successful completion. I owe each a debt of gratitude and want to take this opportunity to offer my sincere thanks. A very special thanks to my Senior Acquisitions Editor, Brian Romer, without whose continued interest and support would not have made this book possible. In addition, a very special thanks to Editorial Project Managers, Ali Afzal-Khan and Alex Ford, who provided staunch support and encouragement when it was most needed. Thanks to my Project Manager, Omer Mukthar; Sr Copyrights Coordinator, Swapna Praveen; Copyeditor, M. Vijayachamundeeswari, whose fine editorial work has been invaluable. Thanks also to my marketing manager, Neil McLeod, whose efforts on this book have been greatly appreciated. Finally, thanks to all of the other people at Morgan Kaufmann Publishers/Elsevier Science & Technology Books, whose many talents and skills are essential to a finished book. Thanks to my wife, Bee Vacca, for her love, her help, and her understanding of my long work hours. In addition, a very special thanks to the late Michael Erbschloe, for writing the foreword. Finally, I wish to thank all the following authors who contributed chapters that were necessary for the completion of this book: Mats Andersson, Aniket Basu, Satyam Bheemaraseti, Anushka Bhilwar, Joy Dalmacio Billanes, Marco Buemi, Alexandra Burgholzer, Aliona Dreglea, Doaa Elsherif, Tuncay Ercan, Abul Hasan Fahad, AmirHoshang Fakhimi, Federica Foiadelli, Aoife Foley, Hossam Gaber, Habtamu Getachew, Ronald Gibbons, Esayas Gidey, Ulf Haeger, Hassan Haes Alhelou, Carles Agustı´i Herna`ndez, Bo Nørregaard Jørgensen, Dilara Kanag, Essam E Khalil, Baseem Khan, Ali Hossein Khani, Bipin P. Kumar, Mahir Kutay, Paolo Lazzeroni, Michela Longo, Zheng Ma, Jonas Maasmann, Charru Malhotra, Vinti Manchanda, Daisuke Mashima, Ritu Mohanty, Nasser Al Muraqab, Ahmed M. Othman, Matthew Palmer, Neena Pahuja, Ravi Prasad Patruni, Andreas Pfeiffer, Cathryn Peoples, Maurizio Repetto, Javad Majrouhi Sardroud; Denis Sidorov, Panteli Sopasakis, Nikita Tomin, Wahiba Yaici, and Banu Yetkin Ekren.

Introduction to the critical success factors of E-government adoption of the utilization of emerging smart cities technologies

1

Nasser A. Saif Almuraqab Dubai Business School, University of Dubai, United Arab Emirates

1.1

Introduction

A city that screens and integrates its critical infrastructures, including roads, bridges, tunnels, rail/subways, airports, seaports, communications, water, and power can better optimize its resources, plan its preventive maintenance activities, and monitor security aspects while maximizing services to its citizens [1]. It is a city that is managed by a network and provides its citizens with services and content via the network using both fixed and mobile smart-city infrastructure, based on higher performance information and communication technology (ICT) [2]. In the smart-city age, government services aim to provide many benefits such as humanizing the processes and operations of government services and improving information sharing between the government and community. It also delivers citizens the services in professional means, securely, safely, expediently, and with significant time savings. However, implementing smart government requires its citizen to understand and accept these services to achieve the intended plan of the government initiative [3]. Mobile government (M-government) is seen as a class of E-government applications and refers to any transaction thru mobile technologies. For the purpose of this chapter, the terms M-government and smart government are used interchangeably. The research aims to discuss the M-government services available in various countries. With this aim, this chapter identifies the factors that affect the successful adoption of mobile services from the academic perspectives. Mobile technologies are one of the pillars of smart cities; however, technologies that are available to use are not very welcomed by the end-users. The study will help to understand the key issues surrounding the mobile applications that hamper the successful operations of M-government. If the technologies of M-government cannot smoothly operate then the vision of having a smart city in place will be impossible. In fact, one of the main digital government project failure is lack of awareness of the potential factors that may help people or citizens to adopt the services, because smart government require engagement and use by people. Therefore this research work will provide a Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00001-2 © 2021 Elsevier Inc. All rights reserved.

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Solving Urban Infrastructure Problems Using Smart City Technologies

theoretical framework or conceptual model to help us to pursue further empirical research for successful implementation of smart government and smart cities.

1.2

E-government and M-government

There is a strong relationship between E-government and M-government. The main reasons that influence the move from E-government to M-government are mobile devices penetration, appearance of mobile Internet, mobile applications, and services [4]. Internet-enabled mobile devices’ penetration rates are growing compared to the traditional wired personal computers (PCs) as well as Internet penetration rates. This spectacular growth has changed how citizens perceive the mobile phones functionality [5]. It is no longer used only for voice communication anymore, but also as a way for convenient connectivity to the Internet used for transferring information, exchanging instant messages, and emails as well as doing business transactions. E-government involves a multidimensional approach embracing the consideration (from the strategic layer to the technical layer) of distinct aspects (organizational, cultural, economic, social, and political) and the core phases of E-government (from information to personalization level of E-government maturity). Among other things, enumeration of success factors that are crucial for adopting E-government is becoming an important task. Most governments around the globe utilize the latest ICT to improve services’ delivery to citizens by introducing E-government [6,7]. E-government has been defined as the application of ICTs to transform the efficiency, effectiveness, transparency, and accountability of informational and transactional exchanges within government units, between government units at state and local levels, citizens, and businesses; and to empower citizens through access and use of public information and public services. Previous researches and other works allow us to draw the following concept of E-government. E-government represents: G

G

G

G

E-administration: Improving government processes by using ICTs and government process management. E-government services: Providing government services electronically for citizens, businesses, employees, and other stakeholders. E-democracy: Improving transparency and democratic decision making as well as citizen’s participation. E-governance: Developing cooperation, networking, and partnerships between government units, citizens, and business.

In the last decade, some of the governments have observed the rapid progression of wireless technologies and the extensive of Internet-enabled mobile devices in many countries [4]. This encouraged these governments to move naturally toward mobile government as a next step to improve the quality and delivery of their services [8,9]. M-government is an added value to the E-government, since citizens will be able to access E-government services using mobile technologies such as mobile phones as well as Wi-Fi enabled devices and wireless networks in delivering public services [10].

Introduction to the critical success factors of E-government adoption

1.3

5

M-government adoption in developing countries

M-government is essential for socio-economic development of a country with such support that a government cannot efficiently operate. In the many countries, mobile services such as M-payment and M-banking are available. To my knowledge, the adoption of M-government in many developing countries is generally not taken seriously by academia and practitioners. By reviewing the existing literature, the chapter will identify the determinants of the success acceptance of M-government that expedite the successful establishment of smart city. This study has analyzed many research papers to identify success factors. Academics have identified various E-government adoption success factors (e.g., [11]; [12]). Additionally, there is a lack of proven scientific theories on and experience in the adoption of M-government in developing countries. These countries face challenges in making ICTs work over time and institutionalizing them in daily routines within their government units. Among other things, it is very important to identify success factors for successful E-government adoption. Having reviewed the relevant literature, the possible success factors for adopting M-government are shown in Tables 1.1 and 1.2. Table 1.1 Summarized critical success factors for E-government. Author(s)

Critical success factors

Ifinedo and Singh [13]

Higher levels of human capital resources, greater human capabilities and knowledge, rule of law, the availability of ICT infrastructure, transparency levels, national wealth and government efficiency Strategic alignment, value delivery and risk management, resource management, performance measurement Dimensions: Organizational, technological, human, natural, environmental Citizen perspective: Lack of Internet access, disparities in computer knowledge, generation gap, lack of awareness, language barrier, security fears, lack of trust, non user-friendly websites. Government perspective: Lack of finances, lack of skills and technology, political pressures, data protection and security laws, staff resistance to change ICT infrastructure, organizational and operational cost Citizen privacy and security, adequately skilled citizens and government employees, elimination of tendency for E-government to replicate traditional government

Nfuka and Rusu [14] Sultan and Alkutbi (2007) Choudrie et al. [15]

Ebrahim and Irani [16] Davison et al. [17], Marche and McNiven [18]

(Continued)

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Solving Urban Infrastructure Problems Using Smart City Technologies

Table 1.1 (Continued) Author(s)

Critical success factors

Almarabeh and AbuAli [11]

ICT infrastructure development, law and public policy, digital divide, e-literacy, accessibility, trust, privacy, security, transparency, interoperability, records management, permanent availability and preservation, education and marketing, public/private competition/ collaboration, workforce issues, cost structures and benchmarking Website age, size of an organization, manager’s professionalism and they have studied the influence of those factors on E-government ICT infrastructure development, human resources capability, leadership and management at the organizational level determine the E-government successful adoption Social, political, and economic conditions and a correlation between country’s conditions with its level of E-government maturity The coordination of many activities of government units, close cooperation of employees, managers, IT specialists as well as citizens and businesses

Reddick [19], Moon and Norris [20] Oyomno [21]

Kachwamba and Hussein [22] Pina et al. [23], Choudrie et al. [15], Beynon-Davies [24].

1.4

Smart government in developing counties: the case of United Arab Emirates

Nowadays, government sectors aim to provide citizens with more accessible, accurate, real-time, and high-quality services and information. In the United Arab Emirates (UAE), His Highness Shaikh Mohammad Bin Rashid Al Maktoum, VicePresident and Prime Minister of the UAE and Ruler of Dubai, has declared a project to convert Dubai into a “smart city,” linking the emirate’s government services and the public through the use of smart devices accessed freely using high-speed wireless Internet connections. He directed all the government services to create mobile services within 2 years, and they have spent a lot to achieve his objective. Dubai Smart Government (DSG) is an inventive initiative that provides a wide array of online services for both business and personal requirements. Shaikh Mohammed stated his move toward smart government on March 22, 2013. DSG mission is to formulate and implement policies and initiatives for innovative and smart ICT usage contributing to economic welfare, social progress, and global competitiveness of Dubai. According to His Highness, “I want UAE Government services to be delivered to the public through mobile phones.” In May 2013, he formally broadcasted a new “vision for the future” following a meeting with government officials. The project “M-government” followed an earlier E-government initiative announced in 2000 to bring all the

Table 1.2 Summarized literature of both E-government and M-government adoption factors. Author(s)

Research field

Adoption factors

Almuraqab [12]

M-government

Abu-Shanab and Haider [25]

M-government

Abdelghaffar and Magdy [26]

M-government

Althunibat and Sahari [27]

M-government

Babullah et al. [28]

M-government

Jasimuddin et al. [29] Dahi and Ezziane [30] Sabraz Nawaz and Thelijjagoda [31] Khalil [32]

M-government

Compatibility, perceived ease of use, social influence, and trust of technology Social influence, perceived usefulness, perceived ease of use, perceived compatibility, and perceived responsiveness Perceived usefulness, compatibility, awareness, social influence, and face-toface interactions Social influence, quality of service, perceived usefulness, perceived risk, cost of service, perceived compatibility, trust of government, and trust of technology Performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, and price value Social influence, perceived ease of use, and trust of technology Perceived usefulness, perceived ease of use, subjective norms, and trust Performance expectancy, effort expectancy, and social influence

Alsaif [33]

E-government

Ovais Ahmad et al. [34] Alshehri et al. [35] Alomari et al. [36] Rehman et al. [37]

E-government

Hussein et al. [38]

E-government

Shareef et al. [39]

E-government

E-government E-government

E-government

E-government E-government E-government

Effort expectancy, social influence, facilitating condition, trust, and awareness Performance expectancy, effort expectancy, social influence, trust of Internet, computer self-efficacy, and availability of resources Performance expectancy, effort expectancy, facilitating conditions, and social influence Performance expectancy, effort expectancy, and facilitating condition Trust of government, website design, beliefs, complexity, and perceived usefulness Information quality, awareness, perceived ease of use, service quality, and transaction security Perceived ease of use and perceived usefulness, trust in the government, image, compatibility, and service quality Resource availability, perceived information quality, awareness, trust, image, multilingual options, and computer self-efficacy (Continued)

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Solving Urban Infrastructure Problems Using Smart City Technologies

Table 1.2 (Continued) Author(s)

Research field

Adoption factors

Sang et al. [40]

E-government

Carter [41]

E-government

Carter and Be´langer [42] Carter and Be´langer [43] AlAwadhi and Morris [44]

E-government

Perceived usefulness, relative advantage, trust, and perceived ease of use Perceived usefulness, trust of the Internet, and perceived ease of use Compatibility, image, and relative advantages

Suki and Ramayah [45]

E-government

Carter and Weerakkody [46] Al-Shafi and Weerakkody [47]

E-government

E-government E-government

E-government

Perceived ease of use, trust, perceived usefulness Performance expectancy, effort expectancy and peer influence, facilitating condition, and Internet experience Perceived usefulness, perceived ease of use, attitude, facilitating conditions, selfefficacy, subjective norms, perceived behavioral control, interpersonal influence, and external influence Relative advantages and trust Effort expectancy, peer influence, performance expectancy, and facilitating condition

government services online. Shaikh Mohammed tweeted at the time. DSG department offers services to government entities and employees through its corporate website, and many smart mobile applications “The government of the future works 24/7 and 365 days a year. A successful government is one that goes to the people and does not wait for them to come to it” [48]. Telecommunication manufacturing especially in mobile phones are moving into an era where data and video usages will be as important as voice practices. In 2015 the number of mobile phone users reached up to 4.4 billion, this reflects the potential of mobile business. Smart government has become a present focus of government efforts in many countries. Some of these countries have proceeded to implement and adopt their smart government mobile applications and services. It replicates the target for public organizations and governments to take advantage of the communications improvements made possible by the ICT revolution. In recent years, Smart devices entered the market and somehow replacing computers, and laptops, as a result, governments aligned its strategy on with these technologies. For the next stage of government strategies, there was a big jump from being E-governments serving citizens from web pages over Internet browsers using

Introduction to the critical success factors of E-government adoption

9

desktop or laptops, to serving users from the mobile smart devices. Therefore the M-government is an essential part of the E-government. M-government definition is the strategy to taking advantage of all resources such as services, applications, wireless mobile technologies, and devices for providing benefits to end-users of E-government. The Telecommunication Regulatory Authority [49] report mentioned that UAE ICT development considered the fastest growing segment globally moving from rank 45 to 33 in 2013, and now they moved one place to be 32 in 2014 (TRA Sixth Annual Market Review). The report presented that UAE is second to Bahrain in terms of mobile services readiness. The TRA confirmed that more than 85% of UAE population is using mobile services and accessing Internet from their smart devices. The total number of broadband subscribers increased by 4.6% between 2013 and 2014. UAE Vision 2021: it is found out about the services that users want to get it and deliver them easy services that surpass their expectations via mobile phones [50]. On the other hand, when it comes to M-government utilization, Khaleej Times (newspaper) reported based on a survey in May 2015 that 65% of the respondents have never used the M-government applications, while 96% of them have smartphones, and furthermore they also found out that 71% installed less than 10 apps, which is an indicator that there is a problem in M-government services adoption in the UAE [51]. This problem required to be researched and to reveal the main factors influencing endusers’ behavior to use or accept the M-government services in the GCC.

1.5

Conceptual model of smart government adoption

From the literature, it was found that citizen’s satisfaction; information accuracy; information exchange; security; privacy and trust; support from the government; ICT skills; and facilities that were offered, were some of the factors for the success of M-government. This research attempted to clarify the concept of smart government and reviews key success factors of E-government and M-government as mentioned by scholars in the existing literature. Based on the previous work, the researcher gathered the key success factors for adopting smart government are identified and the model of success factors is proposed as a theoretical framework, taking in consideration the gaps found in literature especially the social-cultural values as argued by Ref. [52] such as gender, age and education, as shown in Fig. 1.1. The conceptual model is an extended UTAUT (Unified Theory of Acceptance and Use of Technology) with some major factors and moderators found from literature.

1.6

Conclusion and future research

This research explored the relevant issues around smart government; adoption by citizens; and, their relationship to the publics’ intention to accept these services.

10

Solving Urban Infrastructure Problems Using Smart City Technologies

Figure 1.1 Smart government conceptual framework.

The successful adoption of E-government using the emerging technologies or smart government means the successful implementation of the services by all stakeholders (government employees, citizens, and businesses). However, it requires: G

G

the coordination of many activities of government units and close cooperation of employees, managers, IT specialists as well as citizens and businesses ([15,24]).

In the future, it is important to test the developed model in the context to examine the success factors that influencing such digital government services adoption.

1.7

Summary

This chapter focused on the smart services adoption generally and more specific on government new smart initiatives; it is critical to investigate the predictors to provide better insight of the factors required for better implementation and to achieve the government objectives, people must accept and use these digital services. Governments moved to smart-city era due to the high penetration of smart devices. The extensive literature review summarized in Table 1.2 explained the major determinants of digital government acceptance, which also should be considered in any smart-city technology or system for better acceptance. The study suggested a conceptual model based on UTAUT with additions of major variables and moderators drawn from previous studies in order to understand these services from citizens/ people point of view, or in other words from bottom-up direction for better perception. In addition, it covered one of the major gaps found in literature that is sociocultural values because it is critical to understand citizens’ acceptance predictors of digital government services.

Introduction to the critical success factors of E-government adoption

11

Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

1.8

Chapter review questions/exercises

1.8.1 True/False 1. True or False? In the smart-city age, government services aim to provide many benefits such as humanizing the processes and operations of government services and improving information sharing between the government and community. 2. True or False? E-government involves a single-dimensional approach that embraces the consideration of distinct aspects and the core phases of E-government. 3. True or False? M-government is essential for socio-economic development of a country with such support that a government can efficiently operate. 4. True or False? Nowadays, government sectors aim to provide citizens with more accessible, accurate, real-time, and high-quality services and information. 5. True or False? The successful adoption of E-government using the emerging technologies or smart government means the unsuccessful implementation of the services by all stakeholders (government employees, citizens, and businesses).

1.8.2 Multiple choice 1. Most governments around the globe utilize the latest: a. Transparency and accountability technology b. Informational and transactional technology c. Aggregate technology d. Information and communication technology e. Silo model technology 2. E-government represents: a. E-administration b. E-government services c. E-democracy d. E-governance e. All of the above 3. There is a lack of proven scientific theories on and experience in the adoption of ________________ in developing countries. a. M-government b. E-government c. I-government d. U-government e. S-government 4. What is moving into era where data and video usages will be as important as voice practices? a. Wireless mobile technologies b. Mobile services readiness c. Telecommunication manufacturing

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Solving Urban Infrastructure Problems Using Smart City Technologies

d. M-government services e. All of the above 5. What is an extended UTAUT (Unified Theory of Acceptance and Use of Technology) with some major factors and moderators? a. Silo model b. Conceptual model c. Session model d. Virtual model e. Flexible model

1.8.3 Exercise 1.8.3.1 Problem What are the critical success factors of E-government policy formulation, implementation, and execution?

1.8.4 Hands-on projects 1.8.4.1 Problem Why is E-government implementation not straightforward?

1.8.5 Case projects 1.8.5.1 Problem How is the meta-ethnography method used for synthesizing qualitative findings?

1.8.6 Optional team case project 1.8.6.1 Problem With regards to E-government implementation, how do researchers seek to describe, understand, and translate phenomena through the meanings that people assign to them?

References [1] R.E. Hall, B. Bowerman, J. Braverman, J. Taylor, H. Todosow, U. Von Wimmersperg, The Vision of a Smart City (No. BNL-67902; 04042). Brookhaven National Lab., Upton, NY, 2000. [2] J.H. Lee, R. Phaal, S.H. Lee, An integrated service-device-technology roadmap for smart city development, Technol. Forecast. Soc. Change 80 (2) (2013) 286 306. [3] M. Kaliannan, H. Awang, M. Ramann, Technology adoption in the public sector: an exploratory study of e-government in Malaysia, in: Proceedings of the 1st International

Introduction to the critical success factors of E-government adoption

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Conference on Theory and Practice of Electronic Governance, ACM, December 2007, pp. 221 224. [4] M. Hassan, T. Jaber, Z. Hamdan, Adaptive mobile-government framework, in: Proceedings of the International Conference on Administrative Development: Towards Excellence in Public Sector Performance, November 2009. [5] I. Kushchu, H. Kuscu, From E-government to M-government: facing the inevitable, in: The 3rd European Conference on e-Government, MCIL Trinity College Dublin Ireland, July 2003, pp. 253 260. [6] J. Choudrie, Y. Dwivedi, A survey of citizens adoption and awareness of e-government initiatives, the government gateway: a United Kingdom perspective, in: E-Government Workshop, Brunel University, West London, 2005. [7] S.I. Mofleh, M. Wanous, Understanding factors influencing citizens adoption of egovernment services in the developing world: the case for Jordan, INFOCOMP 7 (2) (2008) 1 11. [8] S. Al-khamayseh, E. Lawrence, A. Zmijewska, Towards understanding success factors in interactive mobile government, in: The Proceedings of Euro mGov, December 2006. [9] L. Antovski, M. Gusev, M-government framework, in: Euro mGov, vol. 2005, July 2005, pp. 36 44. [10] A.F. Ghyasi, I. Kushchu, m-Government: Cases of Developing Countries. M-GovLab Intl. Univ. Japan. Electron. Ref., 2004 (Retrieved September 19, 2009). [11] T. Almarabeh, A. AbuAli, A general framework for e-government: definition maturity challenges, opportunities, and success, Eur. J. Sci. Res. 39 (1) (2010) 29 42. [12] N.A.S. Almuraqab, M-Government adoption factors in the UAE: a partial least squares approach, Int. J. Bus. Inf. 11 (4) (2017). [13] P. Ifinedo, M. Singh, Determinants of eGovernment maturity in the transition economies of Central and Eastern Europe, Electron. J. e-government 9 (2) (2011) 166. [14] E.N. Nfuka, L. Rusu, The effect of critical success factors on IT governance performance, Ind. Manag. Data Syst. 111 (9) (2011) 1418 1448. [15] J. Choudrie, V. Weerakkody, S. Jones, Realising e-government in the UK: rural and urban challenges, J. Enterp. Inf. Manag. 18 (5) (2005) 568 585. [16] Z. Ebrahim, Z. Irani, E-government adoption: architecture and barriers, Bus. Process. Manag. J. 11 (5) (2005) 589 611. [17] R.M. Davison, C. Wagner, L.C. Ma, From government to e-government: a transition model, Inf. Technol. People 18 (3) (2005) 280 299. [18] S. Marche, J.D. McNiven, E-government and e-governance: the future isn’t what it used to be, Can. J. Adm. Sci. 20 (1) (2003) 74 86. [19] C.G. Reddick, A two-stage model of e-government growth: theories and empirical evidence for US cities, Gov. Inf. Q. 21 (1) (2004) 51 64. [20] M.J. Moon, D.F. Norris, Does managerial orientation matter? The adoption of reinventing government and e-government at the municipal level, Inf. Syst. J. 15 (1) (2005) 43 60. [21] G.Z. Oyomno, Towards a framework for assessing the maturity of government capabilities for ‘e-government’, Afr. J. Inf. Commun. 2003 (4) (2003) 77 97. [22] M. Kachwamba, A. Hussein, Determinants of e-government maturity: do organizational specific factors matter? J. US-China Public. Adm. 6 (7) (2009) 1 8. [23] V. Pina, L. Torres, S. Royo, E-government evolution in EU local governments: a comparative perspective, Online Inf. Rev. 33 (6) (2009) 1137 1168. [24] P. Beynon-Davies, Models for e-government, TGPPP 1 (1) (2007) 7 28.

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Solving Urban Infrastructure Problems Using Smart City Technologies

[25] E. Abu-Shanab, S. Haider, Major factors influencing the adoption of m-government in Jordan, Electron. Govern. Int. J. 11 (4) (2015) 223 240. [26] H. Abdelghaffar, Y. Magdy, The adoption of mobile government services in developing countries: the case of Egypt, Int. J. Inf. 2 (4) (2012) 333 341. [27] A. Althunibat, N. Sahari, Modelling the factors that influence mobile government services acceptance, Afr. J. Bus. Manag. 5 (34) (2011) 13030 13043. [28] A. Babullah, Y.K. Dwivedi, M.D. Williams, Saudi citizens’ perceptions on mobile government (mGov) adoption factors, in: UKAIS, April 2015, p. 8. [29] S.M. Jasimuddin, N. Mishra, N.A.S. Almuraqab, Modelling the factors that influence the acceptance of digital technologies in e-government services in the UAE: a PLSSEM Approach, Prod. Plan. Control. 28 (16) (2017) 1307 1317. [30] M. Dahi, Z. Ezziane, Measuring e-government adoption in Abu Dhabi with technology acceptance model (TAM), Int. J. Electron. Gov. 7 (3) (2015) 206 231. [31] S. Sabraz Nawaz, S. Thelijjagoda, Sri Lankan Citizens’ Use Behaviour Towards EGovernment Services, 2015. [32] O.E. Khalil, The adoption of the traffic violation E-payment system (TVEPS) of Kuwait, Electron. J. E-Government 12 (1) (2014) 3. [33] M. Alsaif, Factors Affecting Citizens’ Adoption of E-government Moderated by Sociocultural Values in Saudi Arabia (Doctoral dissertation), University of Birmingham, 2014. [34] M. Ovais Ahmad, J. Markkula, M. Oivo, Factors affecting e-government adoption in Pakistan: a citizen’s perspective, TGPPP 7 (2) (2013) 225 239. [35] M. Alshehri, S. Drew, R. AlGhamdi, Analysis of Citizens Acceptance for E-government Services: Applying the UTAUT Model. arXiv preprint arXiv:1304.3157, 2013. [36] M. Alomari, P. Woods, K. Sandhu, Predictors for e-government adoption in Jordan: Deployment of an empirical evaluation based on a citizen-centric approach, Inf. Technol. People 25 (2) (2012) 207 234. [37] M. Rehman, V. Esichaikul, M. Kamal, Factors influencing e-government adoption in Pakistan, TGPPP 6 (3) (2012) 258 282. [38] R. Hussein, N. Mohamed, A. Rahman Ahlan, M. Mahmud, E-government application: an integrated model on G2C adoption of online tax, TGPPP 5 (3) (2011) 225 248. [39] M.A. Shareef, N. Archer, Y.K. Dwivedi, Examining adoption behavior of mobile government, J. Comput. Inf. Syst. 53 (2) (2012) 39 49. [40] S. Sang, J.D. Lee, J. Lee, E-government adoption in Cambodia: a partial least squares approach, TGPPP 4 (2) (2010) 138 157. [41] L. Carter, E-government diffusion: a comparison of adoption constructs, TGPPP 2 (3) (2008) 147 161. [42] L. Carter, F. Belanger, Citizen adoption of electronic government initiatives, in: Proceedings of the 37th Annual Hawaii International Conference on System Sciences, IEEE, January 2004, 10pp. [43] L. Carter, F. Be´langer, The utilization of e-government services: citizen trust, innovation and acceptance factors, Inf. Syst. J. 15 (1) (2005) 5 25. [44] S. AlAwadhi, A. Morris, The use of the UTAUT model in the adoption of Egovernment services in Kuwait, in: Proceedings of the 41st Annual Hawaii International Conference on System Sciences, IEEE, January 2008, p. 219. [45] N.M. Suki, T. Ramayah, User acceptance of the e-government services in Malaysia: structural equation modelling approach, Interdiscip. J. Inform. Knowl. Manag. 5 (2010) 395 414.

Introduction to the critical success factors of E-government adoption

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[46] L. Carter, V. Weerakkody, E-government adoption: a cultural comparison, Inf. Syst. Front. 10 (4) (2008) 473 482. [47] S. Al-Shafi, V. Weerakkody, Factors Affecting E-government Adoption in the State of Qatar, 2010. [48] Dubai smart government. ,http://www.dsg.gov.ae/en/AboutUs/Pages/VisionMission. aspx., 2018. [49] TRA, UAE telecommunications sector developments & indicators, 2010 2013, 5th Annual Sector Review. ,http://www.tra.gov.ae/en/open-data/annual-market-review. aspx., 2014. [50] Dubai.ae. ,http://www.dubai.ae/SiteCollectionDocuments/UAE_Vision_2021_English. pdf., 2016. [51] Khaleej Times.,http://www.khaleejtimes.com/nation/government/96.3-marks-for-mgovernment-initiative-in-41-entities., 2015. [52] N.A.S. Almuraqab, W. Mansoor, Does gender matter on mobile government (M-government) services acceptance? An exploratory study, Int. J. Eng. Technol. Manag. Appl. Sci. 5 (4) (2017) 2349 4476.

Smart-city infrastructure components

2

Amir Hoshang Fakhimi1, Ali Hossein Khani2 and Javad Majrouhi Sardroud3 1 Department of Civil Engineering, Kashan University, Islamic Azad University, Kashan, Iran, 2Department of Civil Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran, 3Department of Civil Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran

2.1

Introduction

Anytime, Smart cities necessitate the infrastructure that need to perform the functions they are intended for. Since there is no single definition for smart city yet [1], its infrastructure cannot be considered as a single and unique set. Therefore, different references have introduced various sets and categories of infrastructure for a smart city. Infrastructure has different definitions which, each of them based on its own context. Infrastructure includes core systems and services that are essential to the productivity of an organization or country (an overall view), support growth and prosperity (business perspective), and are based on the interconnection of various equipment over a networked platform (IT technology perspective) [2]. Infrastructures are crucial to boosting the efficiency of cities and have undeniable effects on boosting productivity and supporting the national economy. Therefore, it can be argued that the main goals of infrastructure in cities are to improve local, regional, national, and international communications for the people by expanding the physical systems needed and utilizing new information technologies. Since infrastructures have a major impact on sustainable urban development, quality of life, and economics in urban communities [1], their development is one of the most important functions of governments around the world. In addition to infrastructure, the word smart also has different meanings. Intelligence in the economic environment is focused on the people (users) and differs in consciousness because of its user friendly and applicability [3]. Intelligence can be explored and defined from different perspectives. Intelligence for smart cities focuses on strategic orientation in smart growth of people and statesmen (urban planning perspective) with the use of intelligent technologies based on intelligent services and artificial intelligence (technological perspective) to achieve the main goals of the smart city [3]. Today industry is transitioning from the Third Industrial Revolution to the Fourth Industrial Revolution. In the fourth industrial revolution, known as Industry 4.0, the parameters are based on the use of intelligence as its Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00002-4 © 2021 Elsevier Inc. All rights reserved.

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Solving Urban Infrastructure Problems Using Smart City Technologies

main parameters. Thus smart cities are expected to be one of the main pillars of the Fourth Industrial Revolution [4]. Researchers, standards, and guidelines for smart city have made different definitions. Each of them has defined the smart city based on their ideas and perceptions and has provided various subcategories such as base, scope, core components, subcomponents, and identications (IDs). For example, the EU has introduced 6 characters, 31 parameters, and 74 identifiers for smart cities [5]. In this chapter, first of all, based on the realities of smart cities, an academic literature review based on journal articles and conference proceedings, case studies, standards, and business reports, smart city is defined and then its platforms, domains, and the main components with its subcomponents have been developed. Since the main purpose of this chapter is to explain the smart-city infrastructure components, the platforms, domains, and main components of the smart city have been explained and other items including subcomponents, and identifiers are not described in detail.

2.2

Smart-city definitions

“Cities are places where many people live and work. They are the poles of government, commerce and transportation” [6]. Therefore cities are the intersection of people’s lives and infrastructure. Today, urban and urban life is on the rise, and over time the population is increasing. For example, at the beginning of the 20th century, the number of cities with a population of over one million was 371, reaching 548 in 2018 and expected to reach 701 by 2030 [6]. Increasing the urban population increases the need for urban infrastructure. On the other hand, with the advancement of technology and the development of digital technologies, their use in different aspects of people’s lives and welfare has increased. What is now called the smart city has also been created by the use of digital technologies in better city administration. The city of Amsterdam was introduced to the world as the first digital city in 1994, and since then the concept has grown rapidly in the world. Since then various titles such as wired city, ubiquitous city, intelligent city, digital city, smart community, knowledge city, learning city, sustainable city, green city, virtual city, hybrid city, eco city, etc. have been used to integrate digital technology in cities [3,7,8]. In addition, much research has been done on the research from a study in 1994 to 184 articles in 2012 [8] and has reached over 1931 related articles in 2018 [9]. It comes from the multitude of titles and terms used for the concept of smart city that its definition and function have not yet been defined and unified, but they all agree on the intersection of the key parameters in the concept of smart city including urban society, physical infrastructure, and digital technologies. Despite the various definitions that have been provided for the smart city so far, the two procedures are clearly distinguishable in terms of the definition of the smart city. On the one hand, there are a set of definitions that emphasize an urban aspect (technological, ecological, or . . .) regardless of the other conditions involved in a city. This group does not realize that the ultimate goal of smart city is to create a new urban management perspective that addresses all

Smart-city infrastructure components

19

aspects of urban real life, and improvement in one part of the urban ecosystem does not imply that all problems are resolved. On the other hand, some scholars emphasize that the main difference between smart cities and existing cities is the connection between all aspects of the city. Problems of urbanization, infrastructure, social, and organizational are reflected at the same time in the concept of smart city. According to this definition, infrastructure is a central element in a smart city and is the technology, which enables it, but to be a truly smart city, the combination, communication, and integration of all systems is essential. From this definition, it can be deduced that the concept of smart city implies a holistic view of urban management and development. It illustrates the equilibrium of technology and the socio-economic factors involved in the urban ecosystem [10]. Based on the second view, some of the definitions proposed for smart cities as shown below by various researchers, are given in terms of these parameters of urban society, physical infrastructure and digital technologies: Smart cities respond to challenges such as climate change, rapid population growth, and political and economic instability, and fundamentally improve how society participates. Adopts participatory leadership practices, across disciplines and urban systems, work and utilize new data, information and technologies to better deliver services and quality of life to those are in the city (residents, businesses, and visitors) and for the foreseeable future, without harming others or destroying the natural environment [11]. Smart city is a city that integrates technology and the natural environment to increase the effectiveness and efficiency of processes in all aspects of operations, to achieve sustainable development, safety, and health for residents, with the aim of enhancing the quality of life of citizens, society, and the environment [12]. Smart city strives to improve urban performance through the use of data, information, and information technologies to provide more efficient services to citizens, monitor and optimize existing infrastructures, increase collaboration between different economic actors, and innovative business models in both public and private sectors [13]. A smart city is recognized as a distinct geographical area capable of managing sustainably resources (natural, human), equipment, buildings and infrastructure, and waste without causing environmental damage [14]. The application of information and communication technology (ICT) along with its effects on education/human resources, communication and social resources, and environmental issues are often illustrated by the concept of smart city [15]. Smart city is a city that monitors all essential infrastructure needs, including roads, bridges, tunnels, rails, subways, airports, seaports, communications, water, power, and even major buildings, to provide maximum service to citizens. It can optimize its resources, plan preventive activities, and monitor aspects of safety [16]. Given the preceding definitions of smart city, it is possible to provide an integrated definition of smart city that encompasses all major parameters including society, physical infrastructure, and digital technologies. Obviously, neglecting any of the parameters will causes imbalances in functions of the smart city. Therefore, the definition provided by the ISO standard can be taken into account and the definition of smart city is as follows:

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Solving Urban Infrastructure Problems Using Smart City Technologies

A smart city is a city focused on participatory leadership practices, enhancing community participation and united services, facilities, physical, and digital infrastructures to provide better services and a higher quality of life to those are in the city (residents, businesses, and visitors) by looking at the future and avoiding environmental degradation.

2.3

Smart-city key foundations (PILARS)

Smart cities are rapidly expanding in terms of how they deliver services and use of new technologies; thus, smart cities require a certain type of planning, such as dynamic adaptive policy paths, to adapt themselves to changes in unknown environment [17]. Cities in their essence are constantly changing. Technology, on the other hand, is constantly changing. So smart-city planning needs to be fully coordinated with these changes. Today, urban planners for smart cities are interested in their interactions [18,19]. Lack of a well-defined and widely accepted definition of smart city on the one hand and the lack of a standardized plan with specific parameters at all levels, strategic, tactical, and operational, on the other hand has made urban planners operationalize some of the features available to them to take smart parameters in cities. Researchers have done various research to introduce the pillars of smart cities, which have led to different categories for them. The way researchers look at key pillars of smart cities varies. Some have focused on digital technologies and some have focused on the physical infrastructure needed as key pillars of the smart city. However, some scholars have focused on community-centric, smart cities and emphasized that physical infrastructure and digital technologies support the lifestyle, culture, behavior, and needs of the community [1,20,21]. The Table 2.1 provides a summary of some research in this area. From the research cited by various researchers, it can be seen that they all agree on three main pillars: community, physical infrastructure, and digital technologies for the smart city. Therefore, in this chapter, considering the vital role of society, smart society is considered as the basis of smart city. Smart physical infrastructure Table 2.1 Summary of some research in key pillars of smart cities. Key smart-city dimension

Reference

Technology, community, and people People, infrastructure, and operations Land, technology, citizens, and government Technology, people, and institutions Human capital, infrastructural capital, social capital, and entrepreneurial capital Internal factors (citizen participation, leadership, and infrastructure) and external factors (Fourth Industrial Revolution, political will, and stakeholders) Smart-city infrastructure, core platform facilities, and value-added services

[22] [23] [3] [18] [24] [25]

Smart-city infrastructure components

21

Figure 2.1 Three main pillars of a smart city.

and digital infrastructure are also considered as two other basic platforms for a smart city (Fig. 2.1). Urban planning for the smart city has strategic, tactical, and operational levels that will add to its technological richness as we move from strategic level to operational level. The platforms of the smart city lie at the strategic level and at the tactical level finds different domains. Smart-city domains also have their own operational-level components, which is the subject of this chapter. To implement the plans of a smart city, we need to be able to implement each of its components in practice, and that is why some of the components of the smart city will go deeper. The subcomponents for each of the main components fall into this category. In addition, identifiers are defined to measure the performance of the main components and subcomponents and to use feedback from each component of the smart-city subcomponent. The main task of identifiers is to evaluate the effectiveness of the strategies, tactics, and components considered to implement them. Therefore, in this chapter, in order to make it possible to adapt urban planning and its stages, the hierarchical smart-city structure is based on platforms (strategic level), domains (tactical level), main components (operational level), subcomponents, and identifiers.

2.4

Smart-city infrastructure platforms and domains

As it mentioned earlier, infrastructure consist of core systems and services that enhance the country’s productivity by supporting growth and prosperity based on the interconnection of various equipment over the network platform [2]. Given this

22

Solving Urban Infrastructure Problems Using Smart City Technologies

definition and key factors involved in the creation of smart-city infrastructure, an academic literature review has been conducted in this research, including research papers, case studies, standards, and guidelines and based on it, (1) smart-society infrastructure, (2) smart physical infrastructure, and (3) smart digital infrastructure, were chosen as the basic infrastructures (platforms) of a smart city. In addition to three basic infrastructures for any smart city, research was carried out to find the domains, the main components and the subcomponents of each platform, which resulted in the selection of 12 domains and 48 main components (see Table 2.2). The selection of domains for each platform is based on the identified functions for each platform in literature review. Accordingly, smart-society infrastructure domains include people, governance, economy, and lifestyle, while smart physical infrastructure domains include the environment, mobility, utility, and living. Networks, data, sensors, and communication are considered as the smart digital infrastructure domains of a smart city. The difference between the main components and the subcomponents is whether or not each component is dependent on the other components. Components associated and dependent to each component are considered as subcomponents. Later in this chapter, the main components of the smart city are described in more detail.

2.4.1 Smart-society infrastructures The smart society is so intertwined with the concept of the smart city, that it has been accepted as the future of the smart city or the next generation of smart-city initiative by some scholars. Despite extensive research and efforts to make the community smarter, research has not yet been completed on the precise definition of the smart society and its infrastructure and components. Governments of Japan, Singapore, China, and the European Union have done extensive research on the smart society and its infrastructure [70,71]. The concept of Society 5.0 introduced by the Japanese government, is the richest concept for it. In this sense, the capability for richer live by integrating physical and digital infrastructures for the citizens of a smart city is centered on what people consider to be the next generation of information society or Society 4.0 [72]. In addition, a society where digital technology improves people’s well-being, economic power, and effectiveness of organizations is considered a smart society [73]. Infrastructure in the smart society links people’s lifestyles and economies by using facilities that governments have prepared for their well-being. Accordingly, smart people, smart government, smart economy, and smart lifestyles are considered as domains of smart-society infrastructure (Fig. 2.2).

2.4.1.1 Smart people Cities are the places of living, work, and recreation for the inhabitants and their users [30]. Urban planners design cities based on the wishes and needs of the people, and the people are the primary beneficiaries of the cities. People in cities face many problems to meet their needs. Smart people can point to the fact that people

Table 2.2 Smart-city platforms, domains, main components, and secondary components. Platform

Domain

Main component

Secondary component

Reference

Smart-society infrastructure

Smart people

Education /digital education

Education and training e-Learning m-Learning E-skill/skilled workforce Cosmopolitanism/Open-mindedness Creativity Social and ethnic plurality Level of qualification ICT enabled Involved actors

[26 30] [31] [31] [26,32] [26,27,33] [27,33] [27] [27] [26] [27,30,34 36]

Cocreate open platform Good administration Good policy Innovative organization and administration Intergovernmental agreements Innovate governance network Transparent governance M-governance Participatory decision making/ democracy Administration services to citizens/ City Hall services Citizen participation ICT-based transparency and open data Cocreated e-services

[32,37,38] [26,28,39] [27,39] [39]

Human capital

Smart governance

Public participation in life Community engagement E-government

E-governance Citizenry engagement

Distance services

[32] [26,39] [27,33,40] [26] [26,27,30,31,39,41] [41 43] [19,30,40] [26,27] [26] (Continued)

Table 2.2 (Continued) Platform

Domain

Main component

Smart economy

E-business and finance Tourism

Culture Entrepreneurship Innovative economy Smart marketing

Smart lifestyle

Health care Social services Smart surveillance Social inclusion

Secondary component

Reference

E-services Local and global interconnectedness Touristic attractiveness/natural condition attractiveness Six A’s (attractions, accessibility, amenities, available packages, activities, ancillary services)

[26,31,33] [26,27,42] [27,42,44,45]

New businesses registered Creative industry High-tec industry ICT-enabled innovation Innovative spirit Smart banking/commerce High productivity Flexibility of labor market International market connectivity Production in demand E-health, M-health, home health Social care Public services/activities Recreation Environmental monitoring/alert Noise detection Social cohesion Social capital Social media Social innovation

[31,46,47] [29,32,33,48] [5,26,27] [32] [32] [26] [27] [31,33] [27,33] [27,33] [33,49] [49] [29,43,45,50 52] [28,31,41] [44,53] [11] [41,43,54] [45] [26,27,42] [26,40] [26] [26,40]

Smart physical infrastructure

Smart environment

Smart home Energy

Water Waste &Sanitation Pollution Building

Smart mobility

Relocation Intelligent Public transport/E-mobility

Traffic

Flexible workplaces Home automation Sustainable energy solutions Grid Green/renewable energy sources Smart metering Resource use efficiency, reuse, and resource substitution

[55] [51] [26,27] [20,26,45,52] [26,27,33,52] [26,45,52,53] [26,31]

Water resource system Waste management Drainage systems Solid waste Control and monitoring Home/residential Commercial center Green buildings Renovation of buildings and amenities Sustainable land use Electric vehicle Charging facilities Integrated mobility management (bus, train, metro, car sharing, bike sharing, pedestrian) Parking management Tolling and congestion charging Real-time ticketing/e-ticketing Dynamic traffic management Vehicle information services/real-time road navigation

[26,28,31,45] [26,31,45] [26,31] [11] [26,27] [31,56] [30] [26,27] [26] [51,57] [26,45] [26,27,33,43,45] [28,31,43,44] [26,58] [26,28,31,45,58] [31,43] (Continued)

Table 2.2 (Continued) Platform

Domain

Main component

Departure (locomotion)

Smart utility

Smart living

Logistic Internet technologies Building information modeling (BIM) and services Urban facilities E-connected Housing/shelter

Smart digital infrastructure

Smart networks

Cultural facilities Safety, security, and emergency Socially reliable networks International connectivity Smart-city dashboard Surveillance network

Secondary component

Reference

Travel guiding/real-time public transit info Smart airport Roads and highways Road bike Walkway Demand-based logistics

[31,43]

Preventive maintenance Maintenance and services Building automation systems Smart irrigation Street lighting Eco heating Digital payments Wi-Fi connected city e-Identity Good-quality housing and accommodation Community biking Crime or disaster prevention/ management Broadband cheap Internet—Wi-Fi

[51,59] [59] [45] [59] [26,43,49] [26,49] [33,60] [45] [33,43] [43] [26,43,45,53] [26] [43] [26] [61] [26,27,31,56] [27,45,51] [24,26,27,31,42,43,45] [38,58] [38,42,50,58]

Common operational framework Wireless sensor networks Interoperable sensor networks

[26,45,50,53,62] [38,53,63] [58]

Smart data

Data resource

Data analysis Smart sensors

Information linkage Citizen sensors Urban sensors

Smart communications

E-communication Industry 4.0

Laser-scanned data (LiDAR) Real-time data Open data portal Data monitoring Interoperable data Big data Spatial data Cloud computing/platforms Artificial intelligence Citizen as a sensor/on body sensors Safety and security Clinical sensors Public transportation sensors Sensors for parking Road/traffic sensors Building sensors Environmental sensors Digital signage (RFID) High-speed communication Virtual reality/virtualization ICTs/telecommunication Internet of Things (IoT) Internet of Services (IoS) Internet of People (IoP) Internet of Energy (IoE)

[50] [26,40,53] [26,62] [26] [40,62] [64,65] [18] [26,41,53,65] [40,49] [24,49] [26] [66] [26,66]

[45,63] [31,60,67] [49,68] [11,26,30,42] [4,24,49,52,58,63,64,68,69]

28

Solving Urban Infrastructure Problems Using Smart City Technologies

Figure 2.2 Smart-society infrastructures.

are using their own learning to provide smart solutions to urban problems [18]. Therefore smart people are a major domain for smart cities [38]. People in cities are not the last consumers, but the main contributors to the change process. People live in cities alongside others and share common and sometimes conflicting interests that need to be addressed through interaction and so they need to be educated. Various smart people components of smart city have been suggested by researchers, most of them which have been accepted by others [3] are affinity to lifelong learning, social and ethnic plurality, flexibility, creativity, cosmopolitanism, openmindedness, and participation in public life. In this chapter, education, human capital, public participation in life, and community engagement are listed as the main components of smart people.

2.4.1.1.1 Education/digital education

Citizens of smart cities must have the skills needed to use the most of the facilities and available services offered in smart cities, so that governments can focus on urban planning to improve the quality of existing services and to serve citizens [26,74]. Mastering these skills requires training and educational services in all areas of services provided. Given the demographic range of cities and the presence of middle-aged and elderly people away from technology, necessitate the need for digital education in urban planning [30]. As citizens become more skilled and able to take advantage of smart-city services, cities will be able to achieve high level of living standard and be closer to the goals of smart city.

2.4.1.1.2 Human capital

Smart cities are human centered and ICT enabled. Being human centered in cities means planning all the facilities and services for humans, and these are the people who use them with their work and creativity [30]. People from different ethnicities come together in one city and have to live together comfortably. These people are the resource that shape smart cities with their power, skill, creativity, and level of competence. Smart cities without human resource cannot be formed and must be invested in [29,32]. Human resource includes people, their communities, and their associated infrastructures.

Smart-city infrastructure components

29

2.4.1.1.3 Public participation in life

Public participation in urban decision making improves governments “ability to identify and act on citizens” preferences [34] which has been cited by various references as an important factor in smart social infrastructure [27,30]. Public participation means engaging people in governance through the involvement of city stakeholders (people, communities, universities, officials, organizations, businesses, etc.), in a wide range of public administration activities such as health, safety, housing, economy, and education that supports the smart process [34,35]. These activities cover the needs of individuals and urban communities (neighborhoods, families, immigrants, tourists, social organizations, the media, etc.). To increase public participation, it is necessary to inform citizens about the issues facing the city, along with the development and encouragement of innovations in civil attitude through urban communities, and its result will be a fundamental link between citizens and governments [36].

2.4.1.1.4 Community engagement

Urban planners seek to establish a two-way relationship with the community to enrich life through long-term public participation in the planning, development and implementation of infrastructure systems [38]. People’s life can be enriched through their shared experiences with efficient community engagement systems. Sharing experiences and using the experiences of others requires a network with a shared open platform. It is not possible to achieve a smart community without community engagement where networks of individuals and communities could share ideas and information through open platforms and mobilize collective action [37].

2.4.1.2 Smart governance Smart-society infrastructures are inefficient without smart governance. Governance means how organizations or countries are managed at the highest level and systems, while government is a group of people who formally control a country. Therefore, those in charge of the country management should apply the highest level of management and related systems that this implementation requires smart-society infrastructure. Smart-society infrastructure focuses on the creation of new forms of social organization such as e-government, e-governance, and telecommunication services for mediated communication, citizenry engagement in decision making, and distance services and its use in decision making [40]. By using these infrastructures, the communication among citizens and subsystems of the city will be increased, and national and local authorities will use stakeholder views in public decision making. In other words, the main actors of the government prioritize, implement, and monitor the goals of the government in order to meet the interests of the stakeholders by evaluation and assessment of stakeholder wishes [30].

2.4.1.2.1 E-government

Improving and simplifying public services to maximize transparency by making data available to all community actors in general (citizens, businesses, and firms) is the ultimate goal of e-government. This goal has been made possible by the synergy

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between social structure and new technologies over the decades and has made the use of e-government services simple and attractive to key community actors [26]. Cities become smarter by using e-government services [39]. Good administration good policy, innovative organization and administration, and intergovernmental are the subcomponents that make a good e-government.

2.4.1.2.2 E-governance

There is no explicit view on defining the governance method [39]. While some emphasize citizen-centered sovereignty, others emphasize decentralization of government and engaging citizens to increase transparency and accountability of the government and ultimately participatory governance [32]. However, while accepting any view of governance, it is clear that smart governance requires the existence of e-governance through innovate and transparent governance networks using upto-date tools such as mobile applications. In this way we can ensure that the right policies are implemented effectively and efficiently by the government and the main actors of the society are fully involved in these policies and monitor their proper implementation [18]. E-governance actually seeks to institutionalize people’s participation in all governance decisions through a two-way and easy communication [30]. It should be noted that the use of technologies alone does not create egovernance. Because technology is only as effective as the institution that employs it. The use of technology to transform urban environments in a more meaningful way requires new thinking about e-governance [43].

2.4.1.2.3 Citizenry engagement

Since stakeholders carry essential and useful information for understanding and resolving urban problems and their opinion in decision making are determinative [40], the involvement of all society stakeholders in decision making and public/ social services makes smart governance meaningful [18]. The presence of the necessary infrastructure such as city hall services, transparency based on information and open data technologies, democratic requirements, and participatory decision making are key requirements for engaging citizens in smart governance [30]. Increasing citizen engagement not only requires their trust in the security systems used in privacy, data governance, and key elements of data security [43] but also necessitate the ability of all stakeholders to be educated by the urban government [39]. In this regard, web or mobile networks and smart devices provide an unprecedented opportunity for wider engagement of stakeholder to develop smart-city functionality and open new channels for social dialog and civil innovation [42].

2.4.1.2.4 Distance services

Distance services (including e-services and integrated e-services), are used by some governments for limited communication with stakeholders and their participation. The limited use of these services cannot be considered equivalent to e-government or e-governance [40]. Proper use of these services, along with other communication ports, creates a complete support umbrella for reciprocal communication between governance and stakeholder [41]. Electronic and distance services are a good tool for governing democracy.

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2.4.1.3 Smart economy The urban economy is a broad concept that encompasses from culture, art, and history to food, water supply, facilities, diplomacy, and commerce, and its growing interaction with all components of society and its competitiveness for the people. All stakeholders need economic security in society to be able to work for business, income, and life [44]. Therefore economics requires special attention, and its intelligence does not merely mean the use of information technologies, and it should be able to increase efficiency through the use of its production and distribution systems [26]. From this perspective, the smart economy is considered when the key economic drivers in the society are driven intelligently to be able to support the survival and growth of the city and to embrace new businesses with creativity and innovation [32]. These include e-business and finance, tourism, culture, entrepreneurship, innovative economy, and smart marketing, and cover all participants of society from producer to consumer.

2.4.1.3.1 E-Business and finance

The increasing development of business along with advances in information technology has increased the need to exploit the infrastructure provided for this purpose. E-commerce implies the use of information technology for business, and in addition to the important intraorganizational applications, it creates interorganizational applications such as interorganizational communication for sharing and using information, preparing management reports, creating the necessary dashboards for decision making, creating important intraorganizational applications. E-business facilitates financial transactions, guarantees financial communication, works closely with partners, and communicates with customers for prepurchase, purchase, and after-sales. In general, through e-business all the necessary mechanisms for establishing a twoway relationship between the employer and the customer are created easily at the interorganizational and intraorganizational levels and at the local, national, and international scales.

2.4.1.3.2 Tourism

Smart tourism is intricately intertwined with all aspects of the smart city including the capability of living, how to interact with information technology, resource management, smart governance, and physical infrastructure [46]. People are using information technology to find appropriate outputs to respond to dynamic environmental changes as well as the changing situations in which they are located. Nowadays, natural attractions alone are not enough to make a place a tourist destination, but tourist attractions, security, ready travel packages, online outreach, access, activities, and services must also be taken into consideration. Therefore, readiness to provide online information on the required fields of tourism using smart infrastructure such as IoT and mobile is required [46].

2.4.1.3.3 Culture

Cities are microcultural communities with acceptable standards in health, educational and social infrastructure that support innovation, creativity, and economic

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development [UNESCO]. Culture is one of the economic components of the smart-society infrastructure. Culturally embedded urban heritage is called smart culture, which utilizes information and communication technology and focuses on enhancing the capability of cities. Smart culture as an industry relying on the city’s cultural heritage (cultural events, art galleries, monuments and historical museums, and centers) can significantly boost a city’s economic growth [29].

2.4.1.3.4 Entrepreneurship

Entrepreneurship and its promotion play a central role in the development of urban communities. The creative industry, High-tech technologies, and the development of new businesses represent entrepreneurship and development. Digital infrastructure has been identified entrepreneurship promotion in most implemented strategies in smart cities as an essential requirement for access to information, knowledge sharing, and supply/consumption of resource [42]. In addition, training with the necessary tools and investing in startups promotes entrepreneurship and ultimately economic growth [41]. Entrepreneurship can enhance the integration and solidarity of societies through increasing the economic trade, and prevent social anomalies.

2.4.1.3.5 Innovative economy

In the traditional economy where prices were based on competition, land, capital, and labor had been accepted the three main pillars of economic growth. Today, factors such as knowledge, technology, entrepreneurship, and innovation play a basic role in the innovative economy, and rely on them to generate the driving force for economic growth. Innovative economy pushes business boundaries out of geographical and political boundaries by moving away from traditional components of economic growth, and brings economic prosperity by relying on smart social infrastructure and smart digital infrastructure.

2.4.1.3.6 Smart marketing

Economic growth in societies requires marketing tailored to the tools and components used in smart economics. The economic infrastructure of the smart society described earlier is fully marketable for which they are built. Therefore, smart marketing tries to produce on the basis of need so that it can promote economic growth by increasing efficiency and connecting with international markets.

2.4.1.4 Smart lifestyle Due to the tremendous advances in equipment and facilities technologies and the development of ICT, and the increasing population density in urban environments and the need for infrastructure and social services, cause the urbanization and its infrastructure has become a major issue today. Welfare, public health, recreational activities, safe environment in terms of financial and life risks, a safe environment free from radiation, sound and noise, available technology to the public and their use at home, and social belonging are people’s needs about lifestyle. Therefore, the revision of social infrastructure and meeting the basic needs of people with an innovative attitude has become an urgent need that their cost-effective and functional

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solution requires a new approach tailored to the latest technology and innovation in their lives. Technology applications and advanced communication methods lead cities to smart cities that can solve most problems [44]. Therefore smart social infrastructures should be used to solve the fundamental problems of people’s lifestyles in order to ensure that their needs are met in a proper and timely manner. Cities and social environments have formed and evolved over time. Therefore change cannot only mean change in the exterior of the city, but also change should be apply in people’s lifestyle. Forming ideas and comments for developing smartsociety infrastructure to make the needed changes in lifestyle is a task that is shared by governments and the public to maximize benefits for stakeholders.

2.4.1.4.1 Health care

Maintaining and improving the physical and mental health of individuals, in particular through the provision of medical services (health care) as one of the main concerns of all stakeholders in society, has changed dramatically with respect to smart digital infrastructures and smart physical infrastructures. The wave of digital innovation is changing every aspect of health care, from medical research and clinical care to telecommunications between people and health-care centers, and even the provision of medicines with a specific composition for one person [43]. Smart health care has increased the efficiency of technology innovations in the health sector by utilizing smart digital infrastructure as an activator [26]. In this care system, patient records are available electronically wherever necessary, thereby enabling rapid response to emergency services [44]. However, support for smart digital infrastructure in smart health care is expanding day by day, allowing society stakeholders to work to improve public health, expand access to services, and improve the quality of care.

2.4.1.4.2 Social services

The form, amount, and variety of delivery and use of social services have a pivotal role in improving the lifestyle. The main purpose of social services such as social care, public services, recreation, and health is to provide equal opportunities for people to live a healthy and safe life and to achieve their desired lifestyle. Social services play a vital role in involving all society members in achieving smart-city goals by providing timely and accurate services needed by all sectors of society, including the elderly, children, and women.

2.4.1.4.3 Smart surveillance

Smart surveillance is done to increase community security by detecting, preventing, or controlling anomalies/crime or social and health crises. Smart surveillance is implemented by systems based on imaging and control tools including traffic control and license plate cameras, face recognition cameras, smart CCTVs, air pollution, and noise monitoring tools [43]. Smart surveillance using smart digital infrastructure-based security systems reduces risks and minimizes vulnerabilities to threats [54].

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2.4.1.4.4 Social inclusion

Individuals’ lifestyles are directly related to the social inclusion of individuals and the opportunity that society offers to improve the social participation of individuals and groups. Social inclusion improves the ability and dignity of deprived people based on their identity. Community integration, creative, and innovative society and the increase in human resource are the achievements that have made social inclusion for smart cities. One of the powerful tools for social inclusion is the expansion and inclusion of mass media provided by the smart digital infrastructure.

2.4.1.4.5 Flexible workplaces

Flexibility in workplace allows employees to choose where and how to work. In traditional models, it is the workplace that specifies when and how employees perform their work. Therefore, a lot of resources are spent to make employees at the workplace, and these resources cause many problems for the community and citizens. Nowadays, with the advances in smart-city social infrastructure and changing attitudes toward improving the lifestyle of the community, flexibility in the workplace has replaced traditional models.

2.4.1.4.6 Smart home

The factors described so far have described changes in the lifestyle of individuals in the community. However, in a smart city, lifestyle changes are also spreading indoors. Smart buildings such as smart home, smart hospital, and smart airport have the influence of intelligent penetration into living environments to improve lifestyle through better utilization of resources and opportunities. Smart homes allow residents to maximize energy efficiency and maximize the use of the natural environment for harmony. This has both saved energy and contributed to the economy of the community. In addition, it has also provided residents with security and improved physical and mental health.

2.4.2 Smart physical infrastructures The smart physical infrastructure is the second platform of infrastructure needed to make cities smart. Smart physical infrastructure plays a decisive role in creating smart cities, so that it is impossible to achieve the goals of the smart city without them [18]. This platform covers a wide range of necessary smart-city requirements through four domains, including the smart environments, smart mobility, smart utility, and smart living (Fig. 2.3). Smart physical infrastructure is one of the most important parts of the Industry 4.0 [68] as it creates an efficient collaboration between domains via deploying of information effectively [3].

2.4.2.1 Smart environment The growth of urbanization in the world has been increasing rapidly, for the first time in 2008, the number of urban residents was higher than in the countryside. The urbanization process has been estimated to be over 60% of the world’s population before half a century ago. Urbanization has a variety of consequences, most notably

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Figure 2.3 Smart physical infrastructures.

the increasing need for buildings, energy, and water, on the one hand, increasing wastewater, waste, and pollution on the other hand, all of which affect the living environment. Due to the small size of the land they occupy, cities have gone to various smart infrastructure programs to overcome the environmental impacts of urbanization by increasing efficiency and service efficiency and reducing costs [20]. The smart environment helps to respond appropriately to the growing needs of resource and urban waste management.

2.4.2.1.1 Energy

Energy means the most important infrastructure for living anywhere on the earth. Humans need fuel, lighting, air conditioning to live on, which has traditionally provided them with fossil fuel energy. With the passage of time and the increasing use of this type of energy, future supply on the one hand and its detrimental effects on the environment on the other hand have caused concern. In this regard, energy supply has been considered in ways that have a zero or minimal impact on environment and are either renewable or recyclable. Sustainable energy, clean energy, green energy, renewable energy, low carbon energy, zero energy, and smart energy are concepts that human beings have pursued to overcome energy problems. The use of energy such as wind, sun, tide, geothermal, and waves had low economic cost and had not been able to solve energy problems. Smart energy means smart generation, smart grids, smart storage, and smart consumption is a new solution to meet the energy demand. Smart energy manages the supply of all forms of energy from fossil fuels to solar and wind energy, efficient distribution through the grid and smart metering, and optimizes its use with the use of information technology [52].

2.4.2.1.2 Water

With the increasing population of cities and urbanization coupled with climate change, water-scarcity problems have become more pronounced in recent decades and the availability of clean water has become the most important prerequisite for continued urbanization [30]. Water-scarcity problems are not only about reducing available water levels, but also inadequate distribution, excessive consumption,

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rising costs, water losses from the distribution network (water leakage), and inadequate pressure on the distribution network are water related problems in the urban area. In this way, cities are trying to solve water-scarcity problems by using innovative tools and technologies and better water management. These tools include smart metering, pressure and flow metering systems, water resource management, flow distribution management, smart water consumption information systems to help save, reduce costs, and increase reliability. Nowadays, in addition to water management and saving methods for waterscarcity management, collection, and use of running water and reuse of water as gray water are considered for specific purposes [20].

2.4.2.1.3 Waste and sanitation

Waste materials, garbage, and sewage are all synonymous words for unpleasant or unwanted and polluting substances from human activities. Waste can be gas, liquid, or solid. Gases are usually in the category of pollutants and liquids and solids are considered waste. Waste can be hazardous or safe, organic, reusable, and recyclable. Liquid waste such as liquids from the bathroom sink, washing machine, bathtub, and spa that does not contain poop or urine are gray wastewater or reusable. Old car tires, old newspapers, broken furniture, construction waste, and even nonliquid food waste are solid waste and can be recycled and used as raw materials. In general, the trend of increasing waste is faster than the increase in population, which is why waste and especially suitable waste-disposal areas have become a major problem for communities. Smart cities are employing different approaches to overcome this problem, mainly based on the separation of recyclable waste from the source and reuse of gray wastewater and efforts to reduce the production of unusable wastewater. Solid waste separation into aluminum (metal), plastic, glass, and paper or use of refined gray wastewater in flash tanks and green space irrigation are examples of these solutions. In addition, digital infrastructure has been used for smart waste management, including monitoring, collection, transportation, processing, recycling, and waste disposal. This system focuses on improving the efficiency of waste collection, separation, recycling, and reuse [20].

2.4.2.1.4 Pollution

Water pollution, noise, parasite, and air pollution with harmful substances are among the pollutions that are caused by human activity and endanger the environment. Some of the pollutants such as fines, floods, and storms are created by nature and are temporary in nature. Urban environments to avoid pollution apply smart pollution control management and monitoring systems by using the collected data from them take the necessary executive action. Governments are actively pursuing pollution control programs, especially carbon pollutants, for pollution control. The physical infrastructure of solar power, green energy, wind turbines, electric cars, smart parking as well as digital infrastructure such as sensors, IoTs, and mobile to monitor pollutants and deciding on practical action in smart cities are used for smart pollution control are used [26].

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2.4.2.1.5 Building

Buildings account for more than 50% of smart-city services [31]. Smart buildings are one of the most important components of smart environment. Smart building management system, while maintaining the efficiency of buildings and their users’ satisfaction, effectively contributes to the optimal consumption of energy and water and in this way helps to protect the environment [20]. Concepts such as green building have been developed to measure the extent to which buildings contribute to the environment [27]. Buildings are being built today that inject more electricity into the grid than their energy consumption [20].

2.4.2.1.6 Relocation

Although a small percentage of the land is covered by infrastructure, people are trying to relocate to get better services and have a better quality of life. Moving means migrating people to another place to get the right services. Displacement planning is done by governments to protect people from natural disasters and environmental changes [57]. Smart cities should provide services based on citizens’ needs and sustainable land use [51] to minimize displacement and thus control the effects of displacement on the environment. In any case, relocation should be carefully planned for the needs, rights, and ideals of the society.

2.4.2.2 Smart mobility Smart mobility focuses on the mobility of all users of the city, whether citizens or visitors. In other words, smart mobility is the mobility of people on foot or on rides using vehicles such as bicycles, cars, buses, monorail, subways, railways, boats, airplanes, and ships [51]. Smart mobility integrates optimal and comprehensive use of different vehicles by using provided accurate information and real data from the information and communication technology and create a sustainable transport system. Smart mobility prioritizes clean and often noncarbon or nonengine-fueled options [26]. Smart mobility makes cities clean and the environment peaceful. Solving the problems of increasing urbanization and cities requires smart mobility infrastructure with the aim of reducing personal cars, optimizing the use of public transport, improving the quality of urban traffic performance, saving energy, and protecting the environment [44]. Cities with smart mobility applications can reduce commute time by at least 15% depending on the density of cities and the amount of smart mobility components used [43]. The main components of smart mobility, including public transport, traffic, transportation, and smart logistics, can build successful smart mobility using digital infrastructure.

2.4.2.2.1 Intelligent public transport/E-mobility

Public transportation happens with vehicles such as shared bicycles, nonowned cars, buses, subways, monorail, and like that. The existence of a platform for shared vehicles, services to facilitate the passage of electric vehicles, electronic payments for tickets and transfers in various ways, and smart parking have a major impact on the development of the smart transport management system. Using IoT, digital signage, and ICTs via mobile applications or other means of communication to

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communicate with the public transport management system to obtain travel information and real-time data on the status of the route as well as to create an integrated management for the use of all means of public transportation has led to its smartening [43]. The public transport management system’s responsiveness to peak times of need is very effective in welcoming it and it will generate enough revenue to cover the costs of operating it [44].

2.4.2.2.2 Traffic

Traffic congestion on roads and streets or so-called traffic due to its direct impact on people’s living standards is one of the major problems of metropolitan areas [44], which is of particular concern to urban planners. The efforts of city officials have always been based on changing traffic patterns and encouraging the use of public transport. However, the use of personal vehicles and the lack of sufficient infrastructure to use them have exacerbated the traffic problem. Confronting traffic problems on city streets and suburban roads need for a smart traffic-management system that interacted with citizens was felt. The smart traffic-management system is an effort to work together with smart digital infrastructure such as IoT, sensors, and RFIDs to streamline traffic flow [26]. It features all of the smart traffic subsystems including dynamic traffic management, vehicle information services, real-time road navigation, travel guides, real-time public transport information, public parking, digital signboards, emerging priority traffic lights public transport, fire trucks, and ambulances are managed seamlessly. Proper traffic management obviously avoids unnecessary traffic, encourages the use of public transport fleets, and reduced travel times will greatly reduce CO2 emissions and thus protect the environment.

2.4.2.2.3 Departure: Locomotion

Smart-city planners have been considered optimal utilization of residential and motor infrastructure including pavements, bike paths, streets, bridges, tunnels, rails, subways, airports, building ports residential, administrative, and commercial businesses to maximize service to their citizens [51,59]. Moving in cities start from residential areas, workplaces, recreation areas, historical-tourist areas, and commercial areas. In other words, these places are the source of movement. To create high mobility, avoid waste of time and energy, and protect the environment, an IT-based system (smart origin such as smart airport) can be used to provide practical information for people to plan their movement and optimize it [59]. In addition, the system based on the freedom of the citizens’ working hours, increases the flexibility for citizens to move and thus optimize their movement from the source (locomotion).

2.4.2.2.4 Logistic

Procurement is one of the important sources of mobility in cities, which if not controlled, can have negative effects on traffic flow and volume increase. Therefore, logistics-based procurement by need-based procurement is one of the methods of logistics control and reduction of unnecessary logistics [43]. In addition, the use of new technologies for delivering packages (such as drones) is changing the logistics

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and moving it to smart [49]. In smart logistics, distribution centers and logistics organizations communicate with each other using information technology, for freight, staging points, and stations to enable any mobility as needed. In addition, innovative methods such as using people to move packages that are on their way to moving are also among the smart logistics. Mobile applications can be used for this purpose.

2.4.2.3 Smart utility Unlike other main components of smart physical infrastructure, there is no single definition for smart utilities. Some references have considered energy, water, and wastewater as utilities [26,43], while others have incorporated these components into other domains. However, Internet technology-related infrastructures, services derived from the application of building information modeling, and urban infrastructure are components of the domain of smart utilities. These utilities cover the facilitation of the operation and maintenance of the spaces and services they require.

2.4.2.3.1 Internet technologies

Internet of things, cloud computing, cyber-physical systems, big data, and other Internet technologies have been widely used in urban planning, construction, management, integrated industrialization, and sustainable development. These technologies can also be described in the Industry 4.0. These new technologies create new forms of interaction in production systems based on the link among manufacturers, suppliers, and customers [43]. In smart cities, Internet technology infrastructures (such as public/free Internet) are the basis for communication between servers and people as clients [26].

2.4.2.3.2 Building information modeling and services

Maximum and high-quality service to citizens requires planning for preventive maintenance by monitoring all physical infrastructure conditions seamlessly and optimizing resources, which is not possible without the use of appropriate technology [60]. Nowadays the concept of a smart building system or building information modelling technology in operation and maintenance has greatly helped to optimize activities and save resources [53]. In addition, it integrates all of the infrastructure information to provide accurate and timely information when we need it, such as in times of crisis. This technology interacts well with digital infrastructure such as smart sensors [43,60].

2.4.2.3.3 Urban facilities

The number of opportunities that cities offer to citizens to optimize urban services management, provide better and more efficient infrastructure and online services or to control the urban environment, are very much. These facilities are online, so can be linked to each other using information and communication technologies [53]. Urban management always controls them to make the most of these facilities and save costs and sustain citizens’ service. In this regard using smart tools to enable

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them to optimize resources and consumption is in priority. Facilities such as street lighting, urban signs, reallocating street lanes, generating eco heating for citizens’ use, and irrigation are facilities that have been used smartly in cities so far [43].

2.4.2.4 Smart living Living in cities is a continuous 24-hour 7 days a week. In order to build a good quality of life, provide security for all city users, especially for women, children, and the elderly, providing high-quality, improved, and enriched public facilities and services must be planned. In addition, the esthetics of people’s everyday life, attention to its artistic, cultural, and natural heritage and its preservation and exploitation, and ultimately the creation of strong shared values must be taken into account. People need to be able to communicate appropriately with each other and with other communities and to take advantage of information and communication technologies to facilitate everyday life and introduce the culture and attractions of the city. The people must be fully aware of the dangers and crises that may threaten them and have full security in the exploitation of their natural and cultural assets. Smart living by providing the facilities that meet the high demands helps urban communities to make sustainable use of the facilities provided [51].

2.4.2.4.1 E-connection

Electronic and sustainable communication for everyday life due to the achievements of digital technologies has become one of the most important components of smart life. Creating more savings, ease of providing better quality services, eliminating unnecessary traffic, maximizing decentralization, and maintaining the necessary controls for order and security are all made possible by electronic communications [61]. Today, the use or nonuse of electronic communication is not discussed, rather the level of its usage in life has been highlighted. A city connected to Wi-Fi, electronic payments with a variety means of communication, virtual reality technology in specific cultural and cultural locations, and electronic e-identity are among the infrastructures created for the use of citizens and users of cities [26,43].

2.4.2.4.2 Housing/shelter

Homes and residences make up the bulk of citizens’ lives time. Most of these places are traditional and built in ancient times. Today, the tendency to move to higher-quality housing is considered. In order to get back to the cycle of using the old places and to control the housing crisis, and their depletion does not waste resources and create social and security threats, these places should be updated and their quality must be improved [61]. Urban planners strive to improve the quality of life and provide sustainable living in all urban areas, by focusing on the area of urban real estate and presenting improvement plans, remodeling, providing appropriate access, and resolving the challenges of each area.

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2.4.2.4.3 Cultural facilities

Creating a sense of national belonging by emphasizing cultural and religious backgrounds along with cultivation to achieve collective aspirations improves the quality of life. Smart life depicts the big picture of urban life in all its small and great details in all its dimensions. Therefore urban planners have focused on cultural status and traditional values for preserving values and creating identity in life. Traditional ceremonies and festivals to enrich the aesthetics and pay attention to the values and aspirations of the society are among these programs [51]. In addition to this, cultivation is done to meet the new needs of society, such as cycling and using public transport to protect the environment.

2.4.2.4.4 Safety, security, and emergency

Establishing security and managing it for the lives of citizens is necessary for all times. However it is more important to prevent the occurrence of crises and accidents, to anticipate unexpected crises and accidents, and to provide safety and security for the citizens in these situations. In this situation, citizens are more likely to be involved in their own affairs and less likely to contribute to security [51]. Therefore planning is necessary to manage and control the effects of sensitive disasters on people’s lives. Digital technologies such as big data are used to identify and control criminals, crimes, social crises, etc. to deploy police patrols and preventive measures [43].

2.4.2.5 Smart digital infrastructures The third indispensable platform for a smart city that has received a lot of investment in recent years is the smart digital infrastructure. Cities have been around for a long time and have provided different infrastructure depending on the need. The infrastructures created for the different functions of cities are like huge silos of data and information that have been created over the time. Digital communication between the data of each function with the aim of digitizing, collecting more data through new technologies and providing new services to citizens has led to vertical integration and development of functions [62]. The next step was to integrate digital infrastructure, build interoperability between citizens, office staff, various functions, and big data silos to horizontally expand functions. This enables decision support systems and dashboards to interact with each other. To this end, main components of this infrastructure including smart grids, smart data, sensors, and smart communications were developed (Fig. 2.4). Through these components, all horizontal and vertical levels of data flow were integrated, interactions between citizens and urban departments were seamlessly integrated, and the information and data needed to make decisions were transmitted online through smart sensors and digital networks [25].

2.4.2.6 Smart network Smart networks are responsible for collecting, storing, and sending data and information from all locations and components defined to the center for processing,

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Figure 2.4 Smart digital infrastructures.

receiving, and responding to relevant entities. The quality, versatility, and accuracy of data collected during this task in real time and the volume that can be processed in real time is of particular importance [65]. Smart networks dynamically synchronize the reception and transmission of data in real time [26]. Therefore, responding to dynamic changes in the structure of economic and social activities requires the existence of highly adaptive smart networks [42]. These networks should function seamlessly at all levels of the urban (horizontal) and citizen service offices (vertical). For this purpose, secure and reliable social networks, environmental networks, international communications, and urban dashboards are integrated as interconnected smart cities to integrate functional levels of cities and citizens. Smart networks are essential for establishing smart governance.

2.4.2.6.1 Socially reliable networks

With the advances in information and communication technology and the development of real-life social networks, people are intertwined with their virtual lives, and people are eager to attend and share information without the need for transportation [26]. Social networking is meant to symbolize a smart society, and urban departments have also communicated with citizens [60]. What is important about the public use of social networks is their reliability. In general, trusted social networks are widely used by people and offices to communicate and in the meantime, the networks that establish the two-way communication are the priority.

2.4.2.6.2 International connectivity

Better communication between stakeholders at all levels should not be limited to the geography of the city. Therefore, to increase the intelligence of a city, possibility of better connection with its stakeholders from any place at any time in real time should increase in order to increase the effectiveness of the city [26]. In addition, connecting with other cities and participating in networks to share knowledge and experience as well as sharing resources for agreed functions requires real-time connectivity between them from any location at any time. International connectivity provides smart communication between all the key stakeholders in the smart grid channel in order to remove the spatial and temporal constraints of connectivity between them [42]. International connectivity is achieved through the use of digital infrastructures to collect and process information [50].

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2.4.2.6.3 Smart-city dashboard

Smart-city stakeholders, including all stakeholders from citizens to departments, need to communicate vertically and horizontally to record information and interact with prepared programs. The need for horizontal information flow in smart cities has been addressed by creating an interactive database such as a dashboard or portal [50]. The result of the lack of horizontal data flow between vertical applications is the loss of internal consistency between dedicated applications for each performance and the loss of integration [62]. Managing urban systems, responding to disasters and crises, better managing the city, providing timely responses to the needs of citizens and the city, and real-time decision making is possible through the creation of real-time dashboards [53].

2.4.2.6.4 Surveillance network

Various networks of wireless sensors are collecting real-time data and information from the environment and transmitting them to data centers for various purposes such as monitoring pollution, traffic, traffic lights, security, etc. These networks can be independent or merge. If created independently, it is possible that the data they collect does not match. In this case, large amounts of duplicate and albeit incomplete data are collected, which in addition to requiring very large volumes of storage, will be processed one-dimensional [53]. Therefore, it is preferable that all required environmental data be integrated into a network that integrates its components and send the collected data to the relevant centers by interacting with one another. This network, called the peripheral network, enables much more qualitative and multidimensional processing of data with a much smaller volume of data than the sum of the individual components. Environmental networks have a dual use. While people use these networks to find the best route, the government can use them for purposes of monitoring air pollution, water and sanitation, finding criminals, and terrorists [26,38].

2.4.2.7 Smart data The data is stored and refined after collection. The refined data are sent to the relevant centers for analysis and analysis in cloud computing or artificial intelligence, and the results are sent to the operating authorities. Obviously, due to the vastness and variety of data collection agencies, the volume of data is very large. Unlike big data, smart data is not just information but also digitally selected, valid and meaningful information that can speed up information processing [26]. This data is collected by smart grids using a variety of sensors and sent to the processing center. The important point in this data, collection is selective and based on the need to submit them to the relevant processing centers. In this method, using the planned algorithms, from all possible data, appropriate data is selected, stored, and sent for processing [38]. An inclusive example of this data is the storage of images by CCTV cameras. Cameras can be programmed to send data to storage only when motion is felt, and when no motion is felt, do not send any images. In this way the data volume is greatly reduced and the stored data can be processed more

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qualitatively. The source of this data is data gathering tools such as portals, dashboards, and sensors.

2.4.2.7.1 Data resource

The different data generation groups in cities are all stakeholders of cities including citizens, visitors, offices, and organizations. The various functions of the smart city have led to data being generated by various sources such as smartphones, computers, sensors, portals, dashboards, websites, apps, and even people. The performance of each stakeholder has a variety of goals and tasks, and the different rights of all data sources and data collected belong to the same stakeholder. On the other hand, data is produced in various formats such as photos and videos, many of which are unstructured. These data must be structured, managed, and classified [65]. Therefore, agreement to achieve a well-matched platform for data collection and integration is important [50]. This platform should be able to store, process and distribute data securely in a unified operational framework [26]. To do this, data sources must adopt an approved data collection strategy to enable their storage, retrieval, and multidimensional processing, along with the needs of individual stakeholders.

2.4.2.7.2 Data analysis

The volume of data collected is very high, even by means of smart-data collection and removal of unnecessary, low-value data. Therefore data processing requires considerable processing capabilities and modern methods of analysis [38,65]. Decisions to provide real-time services and more effective solutions are made using data analysis results [26,41]. Processing (monitoring, scanning, and filtering) and analyzing data using human resources is very time consuming and costly, therefore, how data is processed and analyzed is important.

2.4.2.7.3 Information linkage

Data is born in the physical world and connected to the virtual world using smart networks for scheduled operations. Efficient data linkages between the physical and virtual worlds are essential for smart-data infrastructure [49]. The number of these transplants reached more than 9 billion in 2012 (one and a half times the population of the earth) and is predicted to reach 24 billion in 2020 [63]. The data associated with any vertical-level performance should be linked to other horizontal-level data in a manner that is consistent with all data collectors and information. So that all connectivity components provided by the networks can be linked through the information link to support each other appropriately [26,62]. Digital and Industry 4.0 technologies at the vertical and horizontal levels of automated chains promote data value creation at the local, regional, national, and global levels. Linking the information of the various physical and digital components of smart cities with such technologies can lead to very effective, qualitative and demand-driven productivity [49,50].

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2.4.2.8 Smart sensor A smart sensor is a device that processes incoming inputs from the physical environment before sending to data centers using predefined internal algorithms, and removes irrelevant data and send related data. These sensors record information automatically and accurately and are used as a main component of smart networks. Smart sensors in terms of performance include electronic sensors, chemical sensors, biosensors, and smart grid sensors. These sensors in smart cities have a variety of applications such as safety and security management, citizen clinical monitoring, service delivery optimization, traffic and parking control, smart building, public transportation, and environmental sensing, which fall into two main categories of citizen sensors and urban sensors that have been described further [66].

2.4.2.8.1 Citizen sensors

Citizen sensors are in two categories. In the first category, sensors are used to monitor citizens’ behavior. Citizens’ health surveys in the workplace, sports environments, hospital environments as well as safety and security surveys to rid society of criminals and terrorists are applications of these types of sensors [66]. In the second category, citizens act as sensors with their smart devices. Smartphones, navigation systems connected to cars and wearable gadgets fall into this category. In this case, citizens can share information from personal experiences in their environments through the infrastructure prepared for this purpose [26].

2.4.2.8.2 Urban sensors

Urban sensors or environmental sensors are used to monitor the entire urban environment in order to enhance the quality of life, change lifestyles, and provide functional information to bring peace to the urban environment. These sensors provide all stakeholders with the information they need to use the urban environment for their associated operations (see checklist: “An Agenda for Action for Checking the Status of Operations in the Urban Environment”). An Agenda for Action for Checking the Status of Operations in the Urban Environment Sensors provide information on how to use the urban environment for checking the status of operations, which include the following key activities (check all tasks completed): _____1. Public transport (bus, subway, monorail, shared car, parking lot, pedestrian and bicycle routes, etc.). _____2. Traffic status of roads (accidents, traffic jams, local obstructions, width changes, etc.). _____3. Environmental pollution status (air, water, sewage, noise, and parasite). _____4. Smart metering of service and power grids and providing the necessary hints to optimize consumption. (Continued)

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Solving Urban Infrastructure Problems Using Smart City Technologies

(cont’d) _____5. Status of buildings in terms of safety, security, and energy use. _____6. Situation of crises and unexpected events (protesters’ marches, street protests, fires, etc.).

2.4.2.8.3 Smart communication

Smart communication between the physical environment and the digital environment is created by human-to-human (H2H), machine-to-human (M2H), and machine-tomachine (M2M) communication. Electronic communications and Industry 4.0 are main components of this infrastructure. In electronic communication, communication is human-to-human and human-to-machine. In Industry 4.0, communication is about machine-to-machine and machine-to-human communication.

2.4.2.8.4 E-communication

Electronic communications technologies make it easier, faster, more qualitative, and safer to communicate with other people elsewhere in the world [37]. This component of smart communication, like a nerve center, brings together all the components of the smart, social, and digital community so that they can function seamlessly. Electronic communications communicate through the main components of the smart city through high-speed communications and ICT information technologies (fiber optic, Wi-Fi and wireless networks, instrumentation systems, and network security) and in this way virtualization is also used [30,52]. The ICT infrastructure is the cornerstone of consolidating stakeholder engagement, enhancing urban wealth, increasing innovation and entrepreneurship, and enhancing social cohesion by utilizing all physical and digital infrastructure (real and virtual) and gathering, processing and transmitting information. The expansion of electronic communications is possible by enabling high-speed and free public internet, launching secure online space, and increasing the influence of community networks to provide e-government services [8].

2.4.2.8.5 Industry 4.0

Industry 4.0, through smart grids, facilitates seamless horizontal communications between the components of the smart city that serve as vertical information columns. In order to provide horizontal-level communication, it is essential to meet all the key needs of smart cities. For this purpose Industry 4.0: G

G

G

G

Creates communication between machines (such as sensors with networks) and humans with machines (electronic payment services) through the IoTs. Internet service uses any device that connects to the Internet to meet the expected service. The IoP optimizes, services, processes, and environments based on feedback received and creates a connection between the environment and individuals as well as between reality and virtual reality (combining real world with virtual world and creating applications). The IoE is a dynamic, integrated network infrastructure that connects the energy network and the Internet. The IoE connects data from smart functions such as smart meters and

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47

smart devices, data from the status of renewable energy sources, and other such data through the smart grid.

Industry 4.0 seeks to optimize all smart-city parameters by making smart connections between all smart-city stakeholders while controlling them, using powerful processing tools for big data [49,68].

2.5

Summary

According to UN reports, more than two-thirds of the world’s population will live in cities, by 2030. Urban population growth has put governments in serious challenge in various areas of urbanization. Population in cities is not ethnically, religiously, economically, and socially homogeneous, there is a growing need for security, safety, air pollution, traffic, energy, and safe water management. Innovative approaches based on technological advancements are needed to address the issues ahead and resource constraints have increased. Urban planners have realized that traditional ways of responding to the diverse and growing needs of key stakeholders, including people (citizens, tourists and migrants), communities, universities, authorities, organizations, and businesses, are insufficient and should move to modern and efficient methods. Although urbanization problems in different cities around the world have similar characteristics, but, finding the right solution depends on the conditions prevailing in cities. Smart city and concepts like sustainable city, green city is a new approach that urban managers have taken to tackle a wide range of emerging problems mentioned in urbanization. Much effort has been made to fully define the smart city and its core platforms, domains and components. However, there has not yet been a single, generally accepted standard definition. Even platforms and domains that have a direct impact on smart-city performance are still unanimous. What resembles all solutions offered is the widespread use of digital technologies in cities. In this case, the solutions provided are topical and do not comply with other solutions provided for the functions required by the smart city. However, given the tremendous impact that this approach has on the interests of key stakeholders, the move toward smart cities has accelerated, in which some countries moving toward smart country. From the planner point of view, smarting is not just about using digital technologies in current and routine cities plan, it is also an approach that leads to improving the quality of citizens in real time. This chapter by examining the concepts presented for smart city and their implementation experiences around the world, it has been attempted to make the main smart-city infrastructures structured to be functional and based on vertical-level functions. Surveys showed that the infrastructure needed for smart cities can be categorized into three platforms. These platforms include smart-society infrastructure, smart physical infrastructure, and smart digital infrastructure. At the strategic level, these platforms have been selected to respond to human, physical, and technological developments. At the tactical level, these platforms include the domains that each

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platform needs to cover its intended task. These platforms at the horizontal-level mean that the domains of each platform are highly interconnected, so that they cannot be defined without this horizontal connection. Horizontal-level platform communication reflects the full coverage of related concepts and the integration of functions at vertical and horizontal levels. Four essential domains were introduced for each platform. Each domain at the operational level includes the main components, subcomponents, and identifiers. This chapter introduces the 20 core components for smart-society infrastructure platform domains, the 17 core components for the smart physical infrastructure platform domain and the 11 core components for the digital infrastructure platform domain. The total number of subcomponents in all domains including 117 subcomponents were introduced (Appendix A). Obviously, subcomponents can increase over time. The subcomponent-related identities have not been explored in this chapter. The content presented in this chapter shows that the concept of smart city as a pioneering concept for solving urban problems is of interest to all stakeholders and that the development of digital technologies has helped to implement the solutions presented in this concept. The future plan for smart cities is based on collective convergence to solve community problems. The need to collaborate and share all the data at all levels, both vertical and horizontal, has led to a large volume of data and a problem in how to process and respond to real-time needs that has demonstrated the need for more advanced technologies. In addition, noncompliant applications have proven the need for protocols. On the other hand, physical infrastructure needs to be upgraded and new infrastructure created at the state of the art. Developing concepts such as Society 5.0 in Japan and Industry 4.0 in Europe aim to harmonize the concepts of smart digital infrastructure with smart-society infrastructure and smart physical infrastructure. In this way, they will increase the integration between vertical and horizontal surfaces and be closer to the main goal of moving to smart cities, which is to improve the quality of life of people in all aspects. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

2.6

Chapter review questions/exercises

2.6.1 True/false 1. True or false? Smart cities are expected to be one of the main pillars of the Fourth Industrial Revolution. 2. True or false? Smart cities are mutually exclusive of people’s lives and infrastructure. 3. True or false? Smart cities are rapidly expanding in terms of how they deliver services and use of new technologies; thus, smart cities require a certain type of planning, such as dynamic adaptive policy paths, to adapt themselves to changes in unknown environment.

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4. True or false? Smart-city infrastructure consists of core systems and services that decrease a country’s productivity, by supporting growth and prosperity based on the interconnection of various equipment over the network platform. 5. True or false? The smart society is so intertwined with the concept of the smart city, that it has been accepted as the future of the smart city; or, the next generation of the smartcity initiative by some scholars.

2.6.2 Multiple choice 1. Smart cities are: a. Transparent b. Human centered c. Sufficient d. ICT enabled e. Preferred 2. Public participation means engaging people in governance through the involvement of city stakeholders (people, communities, universities, officials, organizations, businesses, etc.), in a wide range of public administration activities such as: a. Health b. Safety c. Housing d. Economy e. All of the above 3. Urban planners seek to establish a two-way relationship with the community to enrich life through long-term public participation in the planning, development, and implementation of: a. Economies b. Infrastructure systems c. Urbanization d. Autonomous systems e. Transport sharing 4. Smart-society infrastructures are inefficient without: a. Wireless mobile technologies b. Mobile services readiness c. Infrastructure of cities d. Smart governance e. All of the above 5. Improving and simplifying public services to maximize transparency by making data available to all community actors in general (citizens, businesses, and firms) is the ultimate goal of: a. E-government b. E-governance c. Citizenry engagement d. Distance services e. Smart economy

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Solving Urban Infrastructure Problems Using Smart City Technologies

2.6.3 Exercise 2.6.3.1 Problem What are the core infrastructure elements in a smart city?

2.6.4 Hands-on projects 2.6.4.1 Project Do research: Modularize the structure of utilities and develop a system for following up on the activities electronically on the smart-city scale.

2.6.5 Case projects 2.6.5.1 Problem What are the variety of ways in which individuals can engage with smart-city ecosystems, by using smartphones and mobile devices; as well as, connected cars and homes?

2.6.6 Optional team case project 2.6.6.1 Problem How can smart cities combat economic loss by becoming smog free?

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Smart buildings and urban spaces

3

Zheng Ma1, Bo Nørregaard Jørgensen2 and Joy Dalmacio Billanes3 1 SDU Health Informatics and Technology, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark, 2SDU Center for Energy Informatics, The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark, 3Department of Business Development and Technology, Aarhus University, Herning, Denmark

3.1

Introduction

Today, different countries from all over the world develop smart buildings that operate as standalone energy-consuming entities [1]. Countries like Korea, Japan, Singapore, Hong Kong, and Dubai are among the known countries engaged in smart buildings [2]. Smart buildings are high performance, user-friendly, and automated buildings that save energy and increase efficiency and security through integration of Information and communication technologies [3]. Smart building stakeholders include end-user, building owners, finance, intelligent building consultants, security, information and communication technologies (ICT) consultants, and environmental compliance [4]. Stakeholders’ benefits from smart building are operational efficiency, utility consumption reduction, financial performance improvements, sustainability, prestige, and user experience [5]. There are three types of commercial buildings: residential, commercial, and industrial buildings. Commercial buildings operate as business establishments like office, banks, retail stores, and others. The residential or smart home is composed of mini building management system (BMS) connected to a centralized control system accessible to the homeowners for monitoring and adjusting smart home performance [6]. On the other hand, industrial buildings involved in manufacturing and production. One-third of the energy supply in cities consumed by commercial and residential buildings mainly in developing countries [7,8]. In the United States, about 70% of the total energy consumed by buildings including 21% on residential, 18% on commercial, and 33% on industrial energy consumption [9]. Smart buildings are flexible and eco-friendly buildings that can improve grid management [4]. For instance, the smart homes consist of controllable consumers, suppliers, and storage to realize a flexible consumption and supply of thermal and electrical energy [10]. In addition, it requires a skilled system installer in smart homes to avoid technical issues [6]. Smart buildings are integrated into ICT. Thus it provides smart features including the ability to monitors electricity usage [11], provides dynamic pricing, wind twinning, demand response (DR), electric vehicle Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00003-6 © 2021 Elsevier Inc. All rights reserved.

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(EV) charging and battery storage [12], energy efficiency, and ability to connect to smart grid and generate its own electricity [12]. The development of smart building requires high investment and therefore it is important to determine the return on investment (ROI). Smart buildings can obtain operational energy savings of $1/sq. ft. of 4-year payback and 95% ROI over 5 years [13]. Moreover, smart building has an additional impact of 1% on employees’ productivity [13]. It is estimated that smart home gathers strength with a global estimate of 26 billion devices connected to smartphones by 2020 [6]. Residents experience the same technology and building systems at workplace like the other commercial buildings [2]. Intelligent systems, comfortable and efficient residential buildings are attractive for households [13]. Therefore, it is important for real estates to consider those qualities when developing smart buildings to be more competent in the market. The design and development of smart buildings are the same processes for traditional buildings that the location, size, height, design, and cost are drafted, and the design of the intelligent systems must be agreed upon before starting the construction [5]. Retrofitted systems are more expensive because they require replacing systems in existing buildings. However, building developers can still get good ROI after some years [2]. Therefore, smart buildings in urban spaces can be illustrated in Fig. 3.1. Fig. 3.1 is inspired and modified from the SGAM (smart grid architecture model) framework which is a popular EU (European Union) standard proposed by the CENCENELEC-ETSI Smart Grid Coordination Group [14] and aims to provide a guide for the smart grid architecture. This chapter introduces the smart building architecture based on the proposed smart building architecture model (SBA) framework with a case study of smart buildings in the Philippines. Section 3.2 introduces the three lower layers (component, communication, and information layers) of the smart building architecture. In addition, Sections 3.3 3.5, cover the upper layers (function and business layers).

Figure 3.1 The Smart building architecture model framework.

Smart buildings and urban spaces

3.2

57

Smart building systems

Smart buildings are integrated into ICT and consist of software and hardware systems including the enterprise and integration systems and building systems [15]. The smart building systems can be divided into building systems (hardware) and enterprise and integration systems (software) shown in Table 3.1.

3.2.1 Building systems hardware Smart buildings are equipped with smart building systems including HVAC, lightings, fire alarm, security control, smart metering, smart plugs, etc. [5,15]: G

G

G

G

G

Building automation includes the implementation of an effective control strategy on the HVAC systems [16]. HVAC are commonly used in smart buildings [17]. An efficient HVAC provides constant and comfortable temperature as well as fresh and filtered air with a comfortable humidity range to the buildings [16]. Smart meters are smart building devices that provide real-time information on energy use and allow building owners to better manage their energy use and save money. LED lightings can reduce power losses of DC (direct current) distribution grid in smart buildings [18]. T5 tube lamp and T8 tube lamp are examples of LED lightings that are energy widely used nowadays in smart buildings [19]. The smart building will have a variety of charging points for EV, most of which will be public charging points [20]. CCTV (closed-circuit television) is a security system primarily used for building surveillance and security purposes.

3.2.2 Enterprise and integration system software Enterprise and integration system software for smart homes and buildings is computer software, which connects existing integrating systems with distinct software and hardware. It also includes various schemas and components that handle multiple message types: G

WSN is a widely recognized communication technology used in green buildings [21]. It is more efficient than the traditional communication technology [22] as WSN enhances various electric power systems, including generation, delivery, and utilization, making them a vital component of the next-generation electric power system, the smart grid. It provides a Table 3.1 Smart building systems. Smart building systems Building systems Enterprise and integration systems

Heating, ventilation, and air-conditioning (HVAC), smart meter, LED lighting, EV port SCADA, wireless sensor networks (WSNs), home energy management systems (HEMS), energy management systems (EMS), building automation systems (BAS)

58

G

G

G

G

G

G

Solving Urban Infrastructure Problems Using Smart City Technologies

reliable solution for the smart grid’s end-user metering, control, and communication [23], which is commonly used as monitoring tools in many fields including military, health, and critical infrastructures [24]. WSNs are essential for smart grid implementation on smart buildings and energy management applications [25]. Generally, wireless sensors used as a platform to monitor the building’s demand and response, load scheduling, occupancy-based control, intelligent lighting, and other general-purpose control strategies [26]. Wireless sensor and actuator network. It is integrated with computer intelligence intended for a large range of applications and for EMS [27]. Outdoor sensor reads the temperature of ambient air outside the building and adjusts the temperature of fluids in the heating system to maximize efficiency in the transfer of heat to buildings [28]. The carbon dioxide (CO2) sensor is wireless and battery driven, and it requires no wiring for power or for the control signal to any controller [6]. SCADA (supervisory control and data acquisition) system maintains the confidentiality and authentication of the transported data in building automation network domains [29]. The integration of SCADA and ICT infrastructure improve the energy efficiency and enable groups of stakeholders to offer services to customer [30]. Building automated system (BAS) with control over buildings’ HVAC systems has long been viewed as the core smart system in commercial buildings [5]. The BAS and smart building technologies are the main components of smart buildings [28]. BAS integrated with information technology improves building efficiency [9]. BAS controls HVAC equipment indirectly related to temperature [1]. HEMS controls the appliances such as AC units [31], battery energy storage systems, EVs, and heat pump water heaters [32] and enable DR implementation [33] that the operations match occupants’ behaviors when electricity price changes. EMS should be constantly and intelligently find the balance between user requirements and energy saving [34]. The EMS of smart building provides this abstraction layer, by means of which it is possible to schedule energy consumption and generation [35]. The growing share of fluctuating power generation by renewable resources and the increasing distribution of battery EVs require the integration of intelligent EMS into the electrical power grid [10]. EMS can reduce the energy consumption of consumers at the peak load hours and thus reduces the carbon emissions of buildings [36].

Others enterprise systems integration mainly in smart homes include smart plug, advanced metering infrastructure, and in-home display that can recognize, control, and reduce energy [37].

3.2.3 Smart building technologies applied in the Philippines The Philippines embraces smart technologies in buildings. AC, lightings, and security systems are the three important building technologies in the Philippines. Lightings are one of the first things to consider when establishing buildings. In 2015, new smart technologies including LED lightings, solar tubes, and solar panels are presented during the European Chamber of Commerce of the Philippines Energy Smart Philippines [38]. Security is the first concern of Filipinos because of the high crime rate in the country. Safety and security system (CCTV, intercom, and fire alarms) is the most common smart devices installed in condominiums. For instance, the city

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government of Davao city required companies to install CCTV before acquiring business permits [39]. This shows that the government can really influence the stakeholders to adopt smart devices. Moreover, due to frequent power outage condominiums prepared an emergency power generator. While the intelligent BMS are mostly found in luxury condominium units. The Philippines is a tropical climate. Therefore AC system in buildings is very important. As a matter of fact, AC has the largest energy consumption especially in commercial buildings [40]. The real-estate developers concern providing a healthy atmosphere for building occupants so that workers work in clean air, good lighting, and comfortable workplace [41]. Moreover, smart building technologies are available and utilize in the Philippine market. Home Automation.PH (HAP), IOT, and Schneider are just a few companies providing smart technologies. Table 3.2 indicates the presence of smart devices in Philippines such as intelligent lightings, building, and management systems and access control systems. However, it is hard to identify how many users of smart home devices because there is no report showing the market sales of smart home technologies. Table 3.2 Companies that produce smart devices. Smart company

Company profile

Products

HAP (Home Automation. PH)a

Provides an electrical system installed in buildings to control the building appliances and utilities through sensors, remote and automated technologies

IOT (Internet of Things Philippines Inc)b

Provides a smart building system that connects building electronic devices to the Internet to automate and control various devices even from a remote location Leading designer and manufacturer of building automation and control solutions

Intelligent lighting system Electric curtain system Background music system Access control system Centralized control system Security monitoring system Entertainment system Lighting, HVAC, building security system, entertainment system

Schneiderc

Grundfosd

a

Leading producer of commercial building devices such as pump systems for fire protection, HVAC, and pressure boosting

Building management and security Cybersecurity solutions Electrical distribution Installation systems and control BMS (connected to HVAC systems)

Home Automation. http://homeautomation.ph/ IOT. http://www.iotphils.com/solutions/smart-home/#prettyPhoto Schneider. http://www.schneider-electric.com.ph/philippines/en/products-services/buildings/intelligent-buildings/ building-management system.page d Grundfos. http://ph.grundfos.com/about-us/introduction-to-grundfos.htm b c

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3.3

Building types in the urban space

Buildings include commercial, residential, and industrial. One-third of the energy supply in cities is consumed by commercial and residential buildings mainly in developing countries [7,8]. Basically, 21% on residential, 18% on commercial, and 33% on industrial energy consumption in the United States [9]. The commercial and residential building sectors account for 39% of CO2 emissions in the United States per year, more than any other sector [42]. Energy costs represent about 30% of an office building’s total operating costs (excluding staffing costs) [43]. Commercial buildings are buildings of different sizes and are intended for commercial purposes such as wholesale, retail, and service trades, that is, stores, hotels, restaurants, banks, disco houses, etc. [44]. Commercial buildings operate at least 8 hours per day and consume large energy, especially for ventilation and airconditioning system. For instance, largest and prominent malls in the Philippines are located in Luzon area such as SM Megamall, Mall of Asia, and Glorietta Mall. The smart commercial buildings have an additional impact of 1% on employees’ productivity [13]. Smart offices facilitate the working processes by helping to create a habitat that is not only comfortable, but is also energy efficient. Industrial buildings are buildings that cater the production and warehousing activities of industrial establishments including factories, plants, mills, repair shops, machine shops, printing press, storage plant, and electric-generating plants [44]. Industrial sites employ energy-intensive systems to heat, ventilate, air condition, light, and support processes and personnel. Industrial smart buildings are automated and energy saving that involve in product manufacturing and processing [45]. There are three main types of residential buildings: house and lot, townhouse, condominiums, or apartments [46]. The Philippines statistics authority classifies residential buildings as a single type, duplex, an apartment and/or accesoria, and residential condominiums [44]: G

G

Houses and lots are single buildings and typically have a living area, bedrooms, bathroom, kitchen, and dining area. The houses and lots are spacious, which has balcony, carport, garden, and sometimes with swimming pool. House and lot residences can be either single-floor or multifloor buildings [46]. Buildings in subdivision or subdivided residential lots are commonly known as “subdivisions” or “villages.” Subdivisions are exclusive and secured community mostly resided in families with regular incomes. For instance, the Lancaster estate is one of the modern subdivisions in Manila, the Philippines comprised of 2000-hectare English countryside theme buildings with minimum lot area of 80 m2. In this case, Lancaster just designed and constructed the building with installed electricity system, Cable TV (CATV), telephone, and air-condition outlet. The homeowners provide the rest of the house appliances and devices. Residential condominiums are privately owned buildings and operate as commercial purposes. The accessibility to commercial-business centers and other public establishments attract the target customers to buy condominium units. Condominiums can either be a mid-rise or high-rise building and it can be a studio type (18 m2 total floor area) or a penthouse (bigger and more expensive condominium unit) [46]. Condominium developments are equipped with elevators, parking, spa, and many other facilities.

Smart buildings and urban spaces G

G

61

Townhouse is a combination of house and condominium concepts. A townhouse a single or duplex type building and typically has several houses lined up next to each other that have their own garage, backyard, or entrance [46]. Apartments/accesorias are privately owned buildings operating as commercial buildings rented out to private individuals. Apartments are mostly located in cities occupied by students, professionals, and even families. A studio-type apartment unit consists of kitchen, dining, and sleeping area. There are studio and convertible types of apartments. A studio apartment has an open floor plan and with no interior walls. Convertible is another type of apartment that has a bigger space large and walls that provide privacy and comfort [46].

A smart home is composed of a mini BMS connected to a centralized control system accessible to homeowners for monitoring and adjusting smart home performance [6,10]. It is estimated that smart home technology gathers strength with a global estimate of 26 billion devices connected to smartphones by 2020 [6].

3.3.1 Types of building construction in the Philippines This section represents the number of constructed building buildings in the Philippines from 2012 to 2015 based on Annual Survey of Philippine Statistics Authority (shown in Table 3.3). In 2012, there are 20,218 constructed residential buildings accounting for 90% of the total of building construction in the Philippines. There are 1919 constructed commercial buildings sharing 9% of the Table 3.3 Summary for construction establishment by industry (2012 15) [47 50]. Construction

2012

2013

2014

2015

12,380 3472 4366 20,218

9744 2721 4942 17,407

11,871 3014 6270 21,155

13,124 5035 6115 24,274

1004 440 475 1919

1070 425 416 1911

1163 352 530 2045

1229 466 608 2303

233 52 85 370 22,507

241 35 93 369 19,687

309 52 89 450 23,650

277 50 73 400 26,977

Residential Luzon Visayas Mindanao Subtotal Commercial Luzon Visayas Mindanao Subtotal Industrial Luzon Visayas Mindanao Subtotal Total

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Solving Urban Infrastructure Problems Using Smart City Technologies

total building construction in fourth quarter 2012 and 370 industrial buildings sharing 1% of the total building construction in fourth quarter 2012. Based on the approved building permit report of the Philippines Statistics Authority in the fourth quarter of 2013, the total building construction of 19,687 in 2013 decreased 12.5% (2820) from the total building construction of 22,507 in 2012 (shown in Fig. 3.2). On the other hand, the total building construction in the Fourth Quarter of 2014 reached 23,650 and 26,977 in 2015. It shows an increase of 12.3% compared to the 23,650 constructions recorded during the same quarter in 2014. The increasing numbers of building construction in the Philippines show a good market for smart building systems. Among the three types of building construction, residential buildings are the most promising market. Luzon region with 12,110 residential buildings in 2012, 9744 in 2013, 11,874 in 2014, and 13,124 in 2015, has the highest numbers of residential construction from 2012 to 2015 (shown in Fig. 3.3). Mindanao with a residential building construction of 4366 (2012), 4942 (2013), 6270 (2014), and 6115 (2015) has second-highest number of residential construction in the fourth quarter of 2012 15. Even though the total number of residential building construction decreased in 2012, Mindanao region still continues its growth. Visayas region constructed the least number of residential buildings with 3272 (2012), 2721 (2013), 3014 (2014), and 5035 (2015). The residential buildings consist of single, duplex/quadruplex, apartments, condominiums, and others. Among the residential building constructions, the singletype residential building shows the greatest number of projects with 17,634 accounting for 87% of the total residential building construction in the fourth quarter 2012. Apartments are the second largest number of residential building construction with 2215 accounting for 11% (shown in Fig. 3.4). There are 254 condominium buildings sharing 1% of the total residential building construction

Figure 3.2 An overall total of building construction the fourth quarter (2012 15).

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Figure 3.3 Total residential building construction, by area, the fourth quarter 2012 15 [51 54].

Figure 3.4 Total residential, by types, the fourth quarter 2012 15 [55 58].

in the fourth quarter of 2012. The duplex/quadruplex building construction reached 254 in 2012, 255 in 2013, 1,986 in 2014, and 972 in 2015. The apartment/accesoria building construction reached 2215 in 2012, 1844 in 2013, 2317 in 2014, and 2188 in 2015. There are 61 in 2012 consist of other residential buildings sharing less than 1% of the total residential building construction, 31 (2013), 23 (2014), and 39 (2015). The data shows that Luzon area has the largest number of commercial buildings constructed in the fourth quarter 2012 15 (shown Fig. 3.5). For instance, in

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Solving Urban Infrastructure Problems Using Smart City Technologies

2012 there are 1004 (52%) constructed commercial buildings in Luzon, sharing 52% of the total commercial building construction in the Philippines. There are 475 buildings constructed in Mindanao sharing 25%. In addition, there are 440 buildings constructed in Visayas sharing 23% of the total commercial building construction. The commercial buildings in the Philippines consist of banks, hotels/motels, offices, stores, and others (shown in Fig. 3.6). Retail stores are the largest numbers of commercial buildings constructed in Fourth quarter of 2012 15. There are 968

Figure 3.5 Total commercial building construction, by area, the fourth quarter 2012 15.

Figure 3.6 Types of commercial building construction, the fourth quarter, 2012 15.

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retail stores sharing 51% of the total building commercial construction and it the largest commercial building constructed in the fourth quarter 2012. While in 2013, there are 1002, 987 in 2014 retail stores in 2015. There are 391 banks’ construction and accounting for 20% of the total commercial building construction in 2012. There are 219 in 2013, 198 in 2014, and 336 constructed banks in 2015. In addition, there are 222 hotels constructed in 2012, sharing 12% of the total commercial building construction. There are 391 commercial building constructions classified as other types of commercial building, 350 in 2013, 468 in 2014, and 507 in 2015. The office construction consists of 296 in 2012, 288 in 2013, 348 in 2014, and 215 in 2015. Among the three areas, Luzon has the greatest number of industrial construction projects with 233 accounting for 63% of the total industrial building construction in the fourth quarter of 2012 (shown in Fig. 3.7). Mindanao has the second greatest number of industrial building construction with 85 sharing of 23% of the total numbers of industrial building construction in the fourth quarter of 2012. Moreover, Visayas had the least numbers of industrial building construction of 52; sharing 14% of the total building construction in the fourth quarter of 2012. The industrial building construction consists of a factory, repair/machine shops, printing press, refinery, and others. There are 283 other industrial buildings constructed in 2012 sharing 76% of the total industrial building construction. However, there is no specified data from the Philippine Statistics Authority regarding the subtypes of other industrial buildings are. There are 62 constructed factories that account for 17% of the total industrial building construction, 19 repair, or machine shops share 5% of the total industrial building construction, and four constructed printing presses share 2% of the industrial building construction (shown in Fig. 3.8).

Figure 3.7 Total industrial construction, the fourth quarter, 2012 15.

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Figure 3.8 Types of industrial building construction, the fourth quarter, 2012 15.

3.4

Permits and standards for smart buildings

The building industry strongly complies building codes and regulations. For instance, buildings/constructions in a European country need to comply with the national building regulations. Meanwhile, as a member of the European Union, the national building regulations need to comply with the European building regulations. The European Standard EN15232 is popularly implemented for the building automation control systems (BACS) and technical building management (TBM). This European Standard is for estimation of the impact of BACS and TBM on energy performance and energy use in buildings. With the requirement and deployment of the Paris agreement1 of the global climate goal, the energy efficiency, and flexibility of buildings (including energy performance and energy use) is more and more important and popularly discussed. The Leadership in Energy and Environmental Design (LEED) and Energy Star are international organizations that provide certifications for the design, construction, and implementation of energy-efficient buildings [1]. Directive 2010/31/EU on the energy performance of buildings (hereafter called the “EPBD”)2 is the main legislative instrument at EU level for improving the energy efficiency of European buildings. In the objectives of the EPBD 2010/31/EU,3 Article 8-Technical Building Systems introduces the system requirement s for technical building systems, 1

https://ec.europa.eu/clima/policies/international/negotiations/paris_en#tab-0-0 http://eur-lex.europa.eu/legal-content/EN/ALL/; ELX_SESSIONID 5 FZMjThLLzfxmmMCQGp2Y1s2d3TjwtD8QS3pqdkhXZbwqGwlgY9KN! 2064651424?uri 5 CELEX:32010L0031 3 http://ec.europa.eu/smart-regulation/roadmaps/docs/2016_ener_023_evaluation_energy_performance_of_buildings_directive_en.pdf 2

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especially for the existing buildings. Article 8 is the main driver for the optimization of the technical building systems. For the energy flexibly of buildings, Buildings-to-grid (B2G) refers to the connection of the building sector with the electric grid. The B2G integration enables buildings to contribute to changes in electricity supply and/or demand and helps to maintain electricity system reliability [59]. The B2G is usually discussed with the term of DR. DR reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized” [60]. A DR program can be implemented in three key ways of manual DR, semiautomated DR, and fully automated DR or AutoDR. The automation level of the buildings strongly influences the buildings’ participation in DR programs. For instance, AutoDR can be defined as a DR initiated by a signal from a service provider or other appropriate entity that provides fully automated connectivity to preprogrammed end-use control strategies within buildings [61]. One US standard for DR and distributed energy resources (DER) is Open AutoDR or OpenADR. The OpenADR standard is an open specification to communicate DR and DER signals.

3.4.1 Building permits and standards in the Philippines The Philippine national government established Republic Act 6541 or the National Building Code or standards to manage the development, administration, and enforcement of buildings, under the Secretary of Public Works, Transportation and Communication, and other agencies [62]. The Republic Act 6541 or the national building code of the Philippines serves as the Philippines National Standards. The National Building Code of the Philippines requires building permits from the specified government agencies prior to construct, alter, repair, or demolish a building. The law applies to any person, firm, or corporation including government buildings. There are documents need to submit when securing a building permit declaring the types, specifications, nature, and building plan certified by licensed engineers and architects [62]. Asia-Pacific Economic Cooperation (APEC) report shows the Building Codes, Regulations, and Standards for energy efficiency in buildings. Philippines is one of the members of APEC. APEC evaluates the members’ utilization of building codes that increase building performance, aligning with the “green” vision of resource conservation and waste reduction [63]. This includes the conservation and reduction of energy waste on buildings. The Department of Energy imposed a Renewable Energy Act of 2008 does not only encourages the big companies but also the endusers to participate in the movement by generating renewable energy by offering fiscal and nonfiscal incentives (FIT, green energy option program, and net metering for renewable energy) [64]. APEC report shows that the Philippines National Building Code has a section on light and ventilation but nothing on indoor air

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quality, just minimum air ventilation in buildings through the Clean Air Act of the Department of Environment and Natural Resources [63]. There are plans to establish Green Building Codes in the Philippines including Senate Bill 2574, Senate Bill 1799 and Green Building Act (2009) [63]. In 2015, the Department of Public Work and Highways (DPWH) together with World BankIFC and Philippines Green Building Initiative introduced the Green Building Code to enhance the efficiency of building performance [65]. The Green Building Code is applicable to all new construction and/or with alteration of buildings with a minimum total gross floor of: Residential condominium building (20,000 m2), hotel/ resort (10,000 m2), educational institution (10,000 m2), hospital (10,000 m2), business office (10,000 m2), retail store (15,000 m2), and mixed occupancy building (10,000 m2) [65]. In addition, building developers, technical professionals, builders, property managers, and other agencies involved in the planning, design, construction, and management of buildings helps the government to implement the green building code [65].

3.4.2 Green building standards in the Philippines Similar to LEED [1] that allocates points based on a building’s environmental impact and human benefits [66], Philippine Green Building Council (PHILGBC) established Building for Ecologically Responsive Design Excellence (BERDE) Program (shown in Table 3.4) in 2010 to improve commercial building performance [66] and address the negative impacts of climate change in the property sector [40]. In 2012, the Philippine government initiated a green efficiency project under the Department of Energy and Asian Development Bank by replacing old lighting system of government offices in Metro Manila to T40/T35 fluorescent tube. In addition, there is an installation of light-emitting diode (LED) solar home systems to 223 households in off-grid areas and distribution of 8.6 million compact fluorescent lamps to residential sector nationwide resulted in an annual energy savings of 310 GWh [67]. PHILGBC encourages commercial buildings to reduce energy consumption and improve indoor environment through innovation. BERDE points include the integration of BAS to lightings, water system, chillers, and other mechanical ventilation and air-condition systems (MVAC) [66]. Retail stores started to adopt green building standards. SM Malls are among the first retails stores that aim to acquire the US Green Building Council LEED certificate. SM redesign their buildings incorporating green building features like rain harvesting, water recycling, the use of solar, insulating glass units and LED/CFL light bulbs [68]. BERDE rating scheme also considers the transportation system as it is another major contributor to worldwide carbon emissions. The location of buildings that allows tenants easy connectivity and access to public transportation, bicycle stands and showers for office users gains additional credits on for BERDE certification [66].

Table 3.4 BERDE rating scheme [66]. Summary of the points

No. of points

Management MN-PT-1: BERDE Consultant MN-PT-2: Stakeholder Consultation MN-PT-3: Design Charrette MN-PT-4: Security MN-PT-5: Sustainability Commitment

2 6 1 1

1 4

Land use and ecology LE-PT-1: Land Reuse LE-PT-2: Protection and Improvement of Ecological Features LE-PT-3: Pro- Local Biodiversity Open Space LE-PT-4: Heat Island Effect: Non-Roof LE-PT-5: Heat Island Effect: Building Roof LE-PT-6: Flood Risk Minimization

2 6 2 6 2 3 1 2 1 2

Water WT-PT-1: Water Sub-Metering WT-PT-2: Potable Water Consumption Reduction WT-PT-3: Efficient Landscape Irrigation

1 1 4 1 2

EN-PT-1: Energy Sub-Metering EN-PT-2: Energy Efficient Lighting EN-PT-3: Natural Ventilation EN-PT-4: On-Site Renewable Energy Generation EN-PT-5: Energy Efficiency Improvement EN-PT-6: Energy Efficiency Building Envelope EN-PT-7: Energy Efficient Equipment EN-PT-8: Building Automation Systems

1 1 3 3 1

Energy

1 3 1 4 2

Transportation TR-PT-1: Bicycle Rider Amenities TR-PT-2: Fuel Efficient and Low Emitting Vehicles TR-PT-3: Parking TR-PT-4: Proximity to Key Establishments TR-PT-5: Public Access TR-PT-6: Contribution to Public Transport Amenities TR-PT-7: Public Transportation Access TR-PT-8: Transportation Impact Assessment

1 1 3 3 1

1 3 1 4 2

Indoor environment quality EQ-PT-1: External View and Daylighting EQ-PT-2: Illumination Control EQ-PT-3: Glare Control

1 1 1 (Continued)

Table 3.4 (Continued) Summary of the points

No. of points EQ-PT-4: Thermal Control EQ-PT-5: Indoor Air Quality EQ-PT-6: Microbial Contamination Prevention EQ-PT-7: Low VOC Environment

1 1 1 1

MT-PT-1: Civil Works MT-PT-2: Electrical Works MT-PT-3: Architectural Works and Finishes

2 2 2

EM-PT-1: Pollutant and Greenhouse Gas Inventory EM-PT-2: Ozone Protection EM-PT-3: Emission Control

2 1 1

Materials

Emissions

Waste WS-PT-1: Construction Waste Diversion WS-PT-2: Materials Recovery Facility

2 6 5

Heritage conservation HC-PT-1: Heritage Feature Protection HC-PT-2: Heritage Features Promotion

3 1

Innovation IN-PT-1: Innovation in Design or Process IN-PT-2: Innovation in Performance Innovation under management Conduct a design phase commissionability review Conduct of extended commissioning after 1 year Innovation under land use and ecology Flood risk assessment report data based on 50-year, 24-h rainfall Flood risk assessment report data based on 100-year, 24-h rainfall Innovation under WT Installation of water submeters for major water usages accounting for 40% of total water consumption Integration of water metering system with BAS Innovation under energy BAS in place for monitoring MVAC Conduct of CFD studies of naturally ventilated spaces Annual energy reduction cost greater than 15% 25% energy reduction OR 150 kWh/m2 per year (12-h operation) OR 300 kWh/m2 per year (24-h operation) Energy modeling reports representing building performance

10 maximum 10 maximum 1 1 1 1 1 1 1 1 1 1 1 (Continued)

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Table 3.4 (Continued) Summary of the points

No. of points 10% improvement above minimum EER for unitary A/Cs OR 10% improvement in efficiency baseline for chillers 20% improvement above minimum EER for unitary A/Cs OR 20% improvement in efficiency baseline for chillers 30% improvement above minimum EER for unitary A/Cs OR 30% improvement in efficiency baseline for chillers Inclusion of lifts, lighting, RE systems, and external loads in BAS Innovation under environmental quality Use of automatic lighting controls 100% compliance with required VOC levels for materials Innovation under MT Any three of the criteria identified in MT-PT-1 are met All criteria identified in MT-PT-1 are met All criteria identified in MT-PT-2 are met

Total

1 2 3 1 1 1 1 2 1 100

On the other hand, the government established a Green Building Code in 2015 that promotes the efficiency of building performance through green technologies [65]. The green Building Code is applicable to all new construction and/or with alteration of buildings with a minimum total gross floor of: residential condominium building (20,000 m2), hotel/resort (10,000 m2), educational institution (10,000 m2), hospitals (10,000 m2), business office (10,000 m2), retail store (15,000 m2), and mixed occupancy buildings (10,000 m2) [65]. The building developer companies, technical professionals, property managers, and building owners and other agencies involved in the planning, design, construction, and management of buildings are responsible for helping the government to implement the green building code [65]. According to architect Emelito Punsalan, Philippine Green Building Initiative the concept of Green building features includes cold air recycling, low solar heat gain coefficient of glass, waste-recycle system, sensors, vegetation, and sustainable design [69]. Zuelig [70] and Net Lima buildings [40] are just an example of buildings that installed green technologies like on-grid photovoltaic solar power system, Fiberglass fuel storage tanks rainwater collection systems and gray water recycling systems, sun shading, and a full glass curtain wall.

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3.4.3 A smart building case study—Stratford Building Stratford Building4 is a smart and high-class condominium located in Makati City, Philippines, estimated completion from 2016 to 2017—a 74-story building with 1136 high-end residential units targeting high-end market. Stratford Building is developed by Picar Development Inc., which has a vision of developing an innovative and luxurious real estate in main cities. Stratford Buildings have different types of residential units: Studio, 1BR, 2BR, 3BR, Penthouse cost from P5,000,000 to P40,000,000 per unit. Studio units are comprised of one to two-bedroom units intended for young professionals. There are 1-bedroom, two-bedroom, and threebedroom units mainly intended for families. Through the partnership with Cisco Systems, the tallest residential building in the Philippines equipped with smart home technologies [71] such smartphone, child locators, smart work centers, hands-free shopping, smart cards, virtual concierge, smart kiosk, and digital signage. The condo units are integrated into intelligent building systems management that controls room temperature and lightings and security control systems, electric stove, intercom, Wi-Fi, CCTV, and fire alarms [71] (shown in Table 3.5). Stratford Building has a luxurious lifestyle with common amenities, including high-speed elevators, beauty salon, a gym, a mini-theater, swimming pool, meditation garden, music library, and a day care center [72]. Stratford Building is trying to feature security, luxury, and comfort that the building brings because of the smart technologies and facilities. It has a perfect location, as it is located close to retail stores, business centers, schools, and other public amenities.

3.5

Smart building market potentials

This section introduces the smart building market and analyzes the market potentials with a business ecosystem driven market analysis approach [73] with the Table 3.5 Stratford Building amenities, services, and features. Condo building common amenities/services G

G

G

G

G

G

G

G

G

G

G

4

Swimming pool area Gym Meditation garden Mini-theater Beauty salon Music library Day care center and children’s playground Virtual concierge Back-up generator High-speed elevators Automatic sprinkler system

Stratford building. http://stratford.ph/?page_id 5 108

Condo unit features G

G

G

G

G

G

G

G

G

G

Safety and security control systems Intelligent BMS Smoke and heat detectors Intercom Electric stove CCTV Fire alarms Automated lightings Wi-Fi Ventilation

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example of the smart building market potentials in the Philippines. This business ecosystem driven market analysis approach includes (1) a systematic market analysis with the structured ecosystem system mapping is introduced by using the Philippines’ intelligent building market as a case study; (2) discussion of the influential factors to the target market. There are three steps for the business ecosystem mapping: 1. Stakeholder listing: list the main stakeholders in the targeted market and their roles and functions. 2. Relationship mapping: identify the relationships between the listed stakeholders and visualize the stakeholders and their relationships. 3. Market potential discussion: discuss factors influence the targeted market and the stakeholders.

3.5.1 Stakeholders for smart building in the Philippines Smart building stakeholders include the government, building owners, building developers, financial institutions, suppliers, real-estate agents, and end-users. This section will discuss the role of every stakeholder in smart building development in the Philippines.

3.5.2 Government The national and local governments are involved in smart building activities. The national government implements the National Building Code of the Philippines as a standard for building construction. The two main agencies involved in building construction in the Philippines are the DPWH and the Department of Communication and Transportation [62]. The government provides access to housing opportunities for every Filipinos. The government also concerns about building developers’ business. As a matter of fact, Pag-IBIG Fund (government-owned and controlled corporation) helps boost the real-estate business mainly the condominium industry [74]. In addition, the government allocates budget for housing projects with total of less than 1% total government expenditures [75]. The government program, “Gaganda ang buhay kung may bahay at hanap-buhay” (life will improve with housing and livelihood) targeted 1.47 million housing units between 2011 and 2016 [75]. This is a mass housing program (intended to poor families) implements the housing standard with potable water, safe and sufficient electricity, access roads to the nearest commercial centers, and ICT considering the disaster risk reduction and management, and climate change adaptation measures [75]. The mass housing program provides a comfortable living to poor families but not considered as smart homes. The municipalities or cities are obliged to comply with the National Building code [62] and responsibility to enforce the code in planning, checking, inspection, and issuance of building permits and certificates [63]. The city government

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departments involved in dealing with building construction permits in the Philippines [76] are: G

G

G

G

G

G

G

G

Register of Deeds (RD): This is a government agency that provides a certified true copy of the land title that serves as proof of ownership of the land on which to build the building. Barangay: The smallest form of the government in the Philippines provides barangay clearance, which is a requirement for obtaining the locational clearance. City Planning and Development Office (CPDO): After securing the barangay clearance, obtaining a locational clearance from the planning Office is required to ensure that the building construction conforms to the municipality or city’s comprehensive land use plan and zoning ordinances [76]. Bureau of Fire Protection (BFP): The City Bureau of Fire evaluates building plans and specifications to ensure that the building conforms to the fire safety and control requirements of the fire code. In acquiring the fire safety clearance, the applicants need to building plans, bill of materials, and locational clearance. Bureau of Fire Protection still needs to inspect the building after completion to make to certify that the required fire safety construction, fire protective, and/or warning systems are properly installed and working efficiently. Office of the Building Official (OBO): All the documents and clearance mentioned earlier submitted to the OBO. Documents include the certified true copy from RDs, building permit application form, survey plans, design plans, specifications, and other related documents and locational clearance from the CPDO. The OBO is responsible for providing the building permit and ancillary permits consisting of architectural permit, civil permit, electrical permit, mechanical permit, sanitary permit, plumbing permit, and electronic permit. Water District: This provides water to the city and is responsible for water and sewage inspection. City Assessor’s Office (CAO): City Assessor’s Office is responsible for inspection or appraisal of the real property.

In general, acquiring building construction permit in the Philippines is costly and involved in a long process. There are 24 procedures to comply when applying for building permits taking an average of 80 days [76].

3.5.3 Building association Philippine Green Building Council (PHILGBC) is a nonstock organization that is composed of corporations and organizations from every sector of the building industry in the Philippines. PHILGBC established the BERDE certification program that provides green building rating system.

3.5.4 Real-estate developers/owners An individual or corporation (public or private) who involved in land acquisition, property development, and selling of the developed properties. Real-estate developers/owners approach contractors to build their desired buildings (residential,

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commercial, or industrial). In some cases, real-estate developers/owners also own construction companies. In the Philippines, mostly private companies are involved in building developments. The top 12 private building developers in the country build modern residential, commercial, and industrial buildings all over the country. The building developers approach the building designers and construction companies. Government agencies also own buildings.

3.5.5 Contractors These construction companies or builders focus on production of buildings. Contractors are engaged in various subcontractors like electricians, designers, suppliers, and construction laborers to complete site projects.

3.5.6 Designers Mainly architectural agencies engaged in architectural and interior design of buildings in consideration to structural, mechanical, electrical, sanitary, and other disciplines. Building designers embrace the principles and methodologies of the PHILGBC and LEED when designing buildings in the Philippines.

3.5.7 Suppliers Most of the suppliers are private companies supplying materials for building developers. Suppliers have a big role in smart building developments. Suppliers who are concern about smart buildings can introduce smart building technologies to their customers.

3.5.8 Financial institution These government and private agencies either banks, Pag-ibig Fund, and others that are involved in financing the construction and buying the buildings. Companies that would like to build, lease, or buy buildings approach the financial institution for financial help.

3.5.9 Real-estate agent End-users buy buildings through direct sellers or sales agents. For example, in the Philippines, building developer companies hire real-estate agents involved in the sales and marketing of buildings. The real-estate agents are experienced in condominiums and the ones who explain the buyers about the housing unit and can influence the end-users’ buying decision. This means that the real-estate agents can explain to the end-users about the other features of the building including the advantages of smart buildings.

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3.5.10 End-users The Overseas Filipino Workers (OFW) and high-income professionals are commonly engaged in investing in real estate. Simply because OFW and high-income professionals have the financial resources or are qualified for taking loans from government agencies or banks. The OFW are the main drivers for real-estate growth, as they believed real estate is a good investment. It is about P240-billion of the $20-billion sharing 30% of the total OFW remittances invest in real estate, mostly to condominium units in Metro Manila [74]. On the other hand, professionals prefer to live in condominiums as they concern location and convenience because condominiums are located in the heart of the city [74]. This shows that smart building features are not the main concern for residential building investments in the Philippines.

3.5.11 Relationship mapping This step is developed from a market perspective. Therefore, the common ecosystem mapping that allocates a focal company or industry in the core of the business ecosystem is not suitable here. Allocation of all the relevant stakeholders found at the previous step into the business ecosystem mapping based on the value chain is recommended. The value chain of the smart buildings is adopted as the building life cycle (shown in Fig. 3.9). Based on step one of the listed stakeholders and their functions, with the value chain of the smart buildings, the ecosystem mapping is shown in Fig. 3.10. The relationships across the stakeholders are mainly bidirectional. For instance, realestate developers provide smart buildings to the occupants. Meanwhile, occupants expect technology like high-speed Wi-Fi access and integrated building systems, because such systems are present in various commercial smart buildings [2]. An intelligent system, comfortable, and efficient buildings are attractive for the occupants [13]. Therefore, it is important for real-estate builders to consider those qualities when developing a smart building to be more competitive in the market. There are three characteristic types of species in the ecosystem: dominators, niche species, and keystones [78]. In the business ecosystem mapping shown in Fig. 3.10, based on the numbers of connections for each stakeholder, the dominator is the real-estate developers and building owners (connect with eight other

Figure 3.9 The building life cycle and selected energy efficiency opportunities [77].

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Figure 3.10 The business ecosystem for the bright green buildings in the Philippines.

stakeholders), the niche species are the financial institution and energy suppliers (only connect with one other stakeholder), and the keystones are the government and the building associations. Three types of flows at this step are recommended to be mapped: monetary flow, product/service flow, and data flow. The analysis of the business opportunity can be recolonized based on these three flows.

3.5.12 Market potential discussion for smart buildings in the Philippines In the Philippines, private companies are the top players in the smart building industry. Real-estate development is one of the most competitive industries in the Philippines that build residential, commercial, and industrial buildings. The top 12 real-estate builders are private companies and more engaged in building modern residential and commercial buildings. Table 3.6 is an indication that modern and high-rise buildings surround the Philippines. The residential industry in the Philippines is growing. There were 51,000 new high-rise residential condo units disclosed in 2013 [74]. Ayala Land, Inc. is one of the known and largest building developers that engaged in building residential and commercial buildings nationwide (condominiums, malls, offices, hotels, and resorts). Ayala Land5 and its subsidiaries are engaged in engineering, procurement, and construction management including building administration center and 5

Ayala Land http://www.ayalaland.com.ph/services/

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Table 3.6 Top 12 real-estate developers in the Philippines [79]. Real-estate developers

Services (construction)

Ayala Land, Inc. SM Land, Inc. Megaworld Corporation Robinsons Land Corporation Rockwell Land, Inc. Office Federal Land, Inc. Eton Properties Philippines, Inc. Century Properties Group, Inc. Filinvest Land, Incorporated DMCI Homes Shang Properties Vista Land and Lifescapes

Houses, malls, offices, hotels, and resorts Residential, malls, and cyber park Residential and hotels Malls, hotels, offices, and houses Residential and business center Residential, hotels, business centers, and resorts Residential, offices, and parkview Residential and malls Malls, residential, and hotels Residential Office, residential, and malls Residential

subdivision maintenance, and special technical services for shopping centers, subdivisions, parking structures, waterworks operations, and other properties. The Philippines is one of the emerging markets for LED lightings that attract both foreign and local firms to operate in the country. It is currently available in the market and among the five known LED lighting enterprises in the Philippines are: Firefly Electric & Lighting Co, Akari Lighting & Technology Corp., General Electric Philippines Inc., Philips Lighting Philippines Inc., and Yatai International Corp.6 The government plays an important role in the smart building market by promoting the use of LED Lightings in buildings. The government program started by passing House Bill 6892 (LED Light Savings Act of 2013) promoting LED lights that could save almost 70% in energy consumption and eliminate the use of toxic mercury, which is found within the traditional lightings [38]. This encourages building owners to utilize LED lightings.

3.5.13 Influential factor discussion The influential factors on the market potentials can be divided into global and local factors. The global-local factors influence the market structure, as smart building technologies are developed globally, but the market demand is comparatively localized. The market players can be both local (e.g., construction companies and endusers) and international stakeholders who involve and collaborate for the building projects, for example, the smart building technology providers are mainly international companies, for example, Schneider, Siemens, and Honeywell. The design, consortium, platform providers are also mainly international companies. 6

http://www.syhdee.com/newsshow-22-193-1.html#.V7W7caIg1Vr

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Comparatively, the construction companies, building owners and end-users are locally based. There are also global and local trends. For instance, the climate change debate and its potential impact on building owners have incited action to reduce greenhouse gas (GHG) emissions by using energy-efficient technologies and practices in the commercial and industrial sectors. Property owners are under increasing pressure to provide detailed accountings of their GHG emissions. An example is New York City’s Greener, Greater Buildings Plan, where Local Law 84: Benchmarking: requires annual public benchmarking of energy and water consumption. Many companies will also be buffeted by changes in consumer preferences and demands resulting from increased awareness of climate change risks [43]. The global-local policies and regulations: different countries develop the concept of smart buildings in different ways to cope with various regulations and standards imposed by their own government [80]. For instance, in the Philippines, there is the Republic Act 6541 or the National Building Code or standards to administer the development, administration, and enforcement of buildings [62]. Although there is no mandatory green building code in Philippines, there are plans to establish Green Building Codes in Philippines, such as: G

G

Senate Bill 2574 (Act to create the Green Building Code Commission to Draft the National Green) Senate Bill 1799 (Act establishing a Green Energy for Homes and Buildings Program in the Department of Energy)

Figure 3.11 Local-global matters to the smart building market [73].

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Green Building Act (2009) that requires government buildings to follow green building practices and use environmentally responsible materials in its construction

The extensibility should be considered into the smart building design, due to the gap between current market demand, technology readiness, and future trend. The demand for smart buildings can be changed in the future due to the technology development or the changes in the national economic/political situations [81] (shown in Fig. 3.11). Meanwhile, some technologies still have not been ready yet, such as the integration of the smart grid and energy flexibility with smart building energy management. Therefore, extensibility is necessary to support further investigation addressing the integration of smart grid, energy flexibility, and smart building energy management. The results of the business ecosystem mapping and the influential factors can assist companies to develop the triple-layer business models (organizational-niche, environmental-intermediate, and global-dominators) that explained in the work of [82].

3.6

Summary

The understanding of the smart buildings in urban spaces should not only focus on the technical aspects, for example, the software and hardware of the smart building systems (discussed in Section 3.2), but also the building types, standards, and the markets. Especially the building types influence the standards for smart buildings. For instance, lightings, CCTV, and ACs are the most commonly used smart building technologies in the Philippines and residential buildings are the largest numbers of building construction in the Philippines especially in Luzon area. The reasons for residential building occupants of buying and residing in condominiums and apartments because of location, security, and price. This shows that end-users are not really concern about other smart building technologies. There are different types of businesses in the Philippines that vary in size, features, demand, and location, for instance, houses made by concretes, bamboos, and woods using minimal electrical technologies. However, house and lot developed by real-estate developers because these residential units have more potential to adopt smart building technologies than the houses owned by low-income occupants. The house and lots developers ensure the standard installation in houses including electrical systems, cable TV, telephone, AC outlet, and homeowners provide the rest of the technologies. Moreover, for end-users, it is important to have good building designs, affordable prices, and good location. In other words, there is a low demand for “green” or “smart” buildings in the Philippines. The market needs of smart buildings influence the policies and development of the smart building market. For instance, on one hand, the real-estate competition in the Philippines is high and therefore building developers have to develop modern and attractive buildings for the users using smart devices as accessories, especially for luxury buildings. In the hand, real-estate developers intend to develop smart

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buildings to promote luxurious lifestyle, which is clearly intended for the high-income population. While average- and low-income populations do not really care about smart devices. Therefore, only the premium buildings in the Philippines fully utilized smart devices integrated into Business management system serving as accessories of luxury buildings. The government plays an important role in smart building development. For instance, BERDE green buildings certification established by the PHILGBC emphasized the used of the automation system to monitor energy consumption. The building code is one way to promote smart buildings. The government also needs to empower end-users about the benefits of smart or green technologies to life and the environment. Lastly, the continuous building construction in Philippines, the government’s initiative toward green buildings is an indication of a potential market for smart buildings especially in residential condominium buildings, hotels, and retail stores. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

3.7

Chapter review questions/exercises

3.7.1 True/false 1. True or false? The three types of buildings are residential, commercial, and industrial buildings. 2. True or false? The smart home is usually composed of BMS and not connected to any centralized control system. 3. True or false? The development of smart buildings requires high investment. 4. True or false? The smart building has an additional impact of 10% on employees’ productivity. 5. True or false? Retrofitted systems are not expensive although they require replacing systems in existing buildings.

3.7.2 Multiple choice 1. The qualities that real estates need to consider when developing smart buildings to be more competent in the market include: a. ROI b. Intelligent system c. Comfort d. Energy efficiency e. All of the above 2. The SBA framework includes: a. Component layer b. Communication layer c. Information layer

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d. Function layer e. Business layer 3. Building systems include: a. HVAC b. Smart meter c. LED lighting d. EV port e. All of the above 4. ____________ is not a type of the residential buildings: a. Townhouse b. Office c. Condominiums d. Apartments e. None of the above 5. ____________ are industrial buildings: a. Factories b. Mills c. Supermarkets d. Repair shops e. Hospitals

3.7.3 Exercise 3.7.3.1 Problem Today’s smart buildings and urban spaces are beginning to leverage the industrial internet for improved business outcomes, such as better energy efficiency, improved occupant experience, and lower operational costs. With the preceding in mind, what can be done to overcome existing technology barriers to address the high volume of untapped opportunities in the smart buildings and urban spaces market?

3.7.4 Hands-on projects 3.7.4.1 Problem What are some inspiring ideas of how to enrich smart cities and urban spaces lives, with impressive new smart urban development options?

3.7.5 Case projects 3.7.5.1 Problem With regards to smart cities and urban spaces, please develop ideas on how to make city services smart; huge capital investments to build new infrastructure; entire cities; and policy level initiatives to build smarter communities, which are sustainable and scalable, that avoid prior implementation mistakes.

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3.7.6 Optional team case project 3.7.6.1 Problem Why is viability such a crucial parameter for every project, especially during a financial recession, where smart cities and urban spaces demand extensive investments, which affect large communities and local life in a significant manner?

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[50] TABLE 5 Number, floor area and value of industrial building constructions by type and by province: fourth quarter, 2015. Available from: ,https://psa.gov.ph/sites/ default/files/attachments/itsd/specialrelease/Table%205_5.pdf., 2015. [51] Number of new residential building constructions, floor area and value of constructions, by type and by province: fourth quarter, 2012. Available from: ,https://psa.gov.ph/ sites/default/files/attachments/itsd/specialrelease/BP2012Q4_Table%202.pdf., 2012. [52] TABLE 2 Number, floor area and value of new residential buildings by type and by province: fourth quarter, 2013. Available from: ,https://psa.gov.ph/sites/default/files/ attachments/itsd/specialrelease/BP_2013Q4_Tab2.pdf., 2013. [53] TABLE 2 Number, floor area and value of residential constructions, by type and by province: fourth quarter, 2014. Available from: ,https://psa.gov.ph/sites/default/files/ attachments/itsd/specialrelease/Table%202_7.pdf., 2014. [54] TABLE 2 Number, floor area and value of residential constructions by type and by province: fourth quarter, 2015. Available from: ,https://psa.gov.ph/sites/default/files/ attachments/itsd/specialrelease/Table%202_12.pdf., 2015. [55] Number of new commercial building construction started, floor area and value of constructions, by type and by province: fourth quarter, 2012. Available from: ,https://psa. gov.ph/sites/default/files/attachments/itsd/specialrelease/BP2012Q4_Table%204.pdf., 2012. [56] TABLE 4 Number, floor area and value of new commercial buildings by type and by province: fourth quarter, 2013. Available from: ,https://psa.gov.ph/sites/default/files/ attachments/itsd/specialrelease/BP_2013Q4_Tab4.pdf., 2013. [57] TABLE 4 Number, floor area and value of commercial building constructions, by type and by province: fourth quarter, 2014. Available from: ,https://psa.gov.ph/sites/ default/files/attachments/itsd/specialrelease/Table%204_17.pdf., 2014. [58] TABLE 4 Number, floor area and value of commercial building constructions by type and by province: fourth quarter, 2015. Available from: ,https://psa.gov.ph/sites/ default/files/attachments/itsd/specialrelease/Table%204_20.pdf., 2015. [59] C. Goldman, Coordination of energy efficiency and demand response, 2010. [60] U.S. Department of Energy, Benefits of demand response in electricity markets and recommendations for achieving them, in: A Report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005, Lawrence Berkeley National Laboratory. Available from: ,https://eetd.lbl.gov/sites/all/files/publications/ report-lbnl-1252d.pdf., 2006. [61] R. Yin, P. Xu, M.A. Piette, S. Kiliccote, Study on auto-DR and pre-cooling of commercial buildings with thermal mass in California, Energ. Buildings 42 (7) (2010) 967 975. [62] CRALAW, The National Building Code of the Philippines [Online]. Available from: ,http://www.chanrobles.com/republicactno6541.htm#.V4x8HqIg2Xd.. [63] APEC, APEC Building Codes, Regulations and Standards (Minimum, Mandatory and Green), Nathan Associates, Singapore, 2013. [64] RA 9513, Renewable Energy Act of 2008, IRR. Available from: ,http://lia.erc.gov.ph/ documents/290#., 2009. [65] A. De Jesus, Philippine green building code. Available from: ,http://business.inquirer. net/195889/philippine-green-building-code., 2015. [66] BERDE for new construction commercial buildings. Available from: ,http://philgbc. net/berde/berde-nc/1.1.0/BERDE-NC-COM-v110.pdf., 2013. [67] IIEC, Implementation and dissemination of energy efficiency measures in the Philippines. Available from: ,http://www.iiec.org/index.php/iiec-news/517-implementation-anddissemination-of-energy-efficiency-measures-in-the-philippines.html., 2012.

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[68] Phil Star, SM Mall designs through the decades. Available from: ,http://www.philstar. com/business/2015/08/16/1488495/sm-mall-designs-through-decades., 2015. [69] P. Ranada, 10 features of a ‘green’ building. Available from: ,http://www.rappler. com/science-nature/environment/56190-ten-features-green-building., 2014. [70] T. Prieto-Valdez, Zuellig Building’s new technologies and newest tenant. Available from: ,http://business.inquirer.net/152557/zuellig-buildings-new-technologies-andnewest-tenant., 2013. [71] The Philippine Star, Innovating condo units with smart home technology. Available from: ,http://www.philstar.com/business/2014/01/14/1278483/innovating-condo-unitssmart-home-technology., 2014. [72] Business Inquirer, The Stratford Residences conquers the global scene. Available from: ,http://business.inquirer.net/189434/the-stratford-residences-conquers-the-globalscene., 2015. [73] Z. Ma, J.D. Billanes, B.N. Jørgensen, A business ecosystem driven market analysis: the bright green building market potential, in: The First Annual International Conference of the IEEE Technology and Engineering Management Society, Santa Clara, California USA, IEEE, Santa Clara, CA, 2017. [74] DMCI, The growing condo rental market in the Philippines. Available from: ,http:// leasing.dmcihomes.com/condo-rental-market-philippines/.. [75] Accelerating infrastructure development. Available from: ,http://www.neda.gov.ph/ wp-content/uploads/2013/09/CHAPTER-5.pdf., 2011. [76] Doing Business, Dealing with construction permits in Philippines. Available from: ,http://www.doingbusiness.org/data/exploreeconomies/philippines/dealing-with-construction-permits/., 2016. [77] SwitchAsia, Country components: Philippines. Available from: ,http://www.switchasia.eu/policy-support-components/psc-philippines/.. [78] L.S.M. Mary, E. Power, The Keystone cops meet in Hilo, Trends Ecol. Evol. 10 (1995) 182 184. [79] Hoppler, The builders: 12 top real estate developers in the Philippines. Available from: ,https://www.hoppler.com.ph/blog/featured-real-estate-developers/the-builders-12-topreal-estate-developers-in-the-philippines-part-1-of-3., 2013. [80] Danish Enterprise and Construction Authority, Danish Building Regulations 2010 [Online], Available from: ,http://www.buildup.eu/en/practices/publications/danishbuilding-regulations-2010-br10., 2013. [81] L. Qingnan, M. Zheng, N. Jørgensen, Discussion on China’s power sector reforms and where to next?, in: 2016 13th International Conference on the European Energy Market (EEM), 2016, pp. 1 5. [82] Z. Ma, M. Lundgaard, B.N. Jørgensen, Triple-layer smart grid business model: a comparison between sub-Saharan Africa and Denmark, in: 2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), Melbourne, Australia, 2016, pp. 347 352.

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Doaa M. El-Sherif Urban Training and Studies Institute “UTI”—Housing and Building National Research Center “HBRC,” Cairo, Egypt

4.1

Introduction

Cities are made up of a complex web of overlapping sectors, of which mobility is just one. Energy, water, public services, buildings and homes, and information and communication technologies are all part of the essential fabric of cities. They are designed to meet the everyday needs of citizens and to cope with peak demands, not just in the mobility sector but also in other sectors. Each one of these sectors faces similar challenges in balancing peak demand against a limited level of supply. Rapid urban development occurring across much of the globe increased the volume of passengers and freight moving within urban areas. Urban areas are the most complex settings in which the mobility of passengers and freight is taking place. In several instances, passengers and freight movements are complementary, but sometimes they may be competing for users, the usage of available land and transport infrastructures. However, cities are fundamentally self-organizing systems. With an appropriate combination of physical infrastructure, operational, and information technologies, cities can be guided toward a more efficient level of operation over time. These transformation technologies can generate huge value for urban economies, while enabling behavioral change, securing a more reliable service for citizens, and reducing negative environmental impacts like greenhouse gas emissions [1]. Cities require models of smart urban mobility based on sustainable transport systems to improve economic efficiency, the well-being of citizens and environmental health.

4.2

Mobility, transportation, and accessibility

There are a number of terminologies highly interconnected with mobility, namely, transportation, accessibility, and urban mobility. This part clarifies the different definitions and the interrelationship between mobility and of each of them. Mobility refers to the movement of people or goods. It assumes that “travel” means person- or ton-miles, “trip” means person- or freight-vehicle trip. It means that getting to places necessary for living a healthy life—job, school, doctor’s offices, community centers, and parks—is possible [2]. Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00004-8 © 2021 Elsevier Inc. All rights reserved.

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Accessibility (or just access) refers to the ability to reach desired goods, services, activities, and destinations (collectively called opportunities) [3]. Transportation is basically moving stuff and people [4]. Urban mobility concept (UMC) is an innovative mobility concept; characteristics of UMC include its suitability for short distance travel, for easy transport by train and the possibility to use it on public roads [5].

4.2.1 Mobility versus transportation Mobility is not just having access to one mode of transportation. It is having transportation options that anyone can count on to get to the desired destination. These transportation options should be of good quality. Quality of transportation options depends on three necessary aspects, namely: time (it should not take forever to get to the desired destination); affordability (transportation options need to be affordable); and safety (it should be safe to walk, bike, or drive) [6]. Without mobility, transportation is meaningless. Improving people’s mobility should be the goal of any transportation project. There may be many ways of improving transportation, including improved mobility, improved land-use accessibility (which reduce the distance between destinations), or improved mobility substitutes such as telecommunications or delivery services. Mobility is being more widely used today with the broader meaning of “any type movement of persons or things” regardless of whether it involves the use of a motor vehicle or not [4].

4.2.2 Accessibility-based urban mobility Mobility and accessibility are two main components of a transportation system. In directing attention beyond transport and mobility, and giving importance to the aspect of accessibility, a call should be for a paradigm shift in transport policy; that is, accessibility should be at the core of urban mobility. This approach emphasizes the need to reduce the global preoccupation on mobility enhancement and infrastructure expansion. However, “most fundamentally, a focus on mobility as a transportation-policy goal neglects that the vast majority of trips are not taken for the sake of movement itself, but in order to reach destinations, or more broadly, to meet needs” [6]. While the speed and efficiency of travel are important, more critical, however, is the ease of reaching those destinations in terms of proximity, convenience as well as positive externalities. Transport and mobility as derived demands are treated as means for enabling people to access other people and places. Reducing the need for such demands and minimizing travel time also entails optimizing the value of being at the destination [4]. “Mobility is thus properly viewed as a means to the greater end of accessibility.” However, it is not the only means to this end: “accessibility can be enhanced through proximity” as well as “electronic connectivity.” Thus, accessibility should be the ultimate goal of most transportation. The backbone of accessibility-based urban mobility is public transport, particularly high-capacity public transport systems that are well integrated in a multinodal

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arrangement. The bottom line for accessibility is not the hardware; rather it is the quality and efficiency of reaching destinations whose distances are reduced. Equally important is the affordability and inclusiveness in using the provided facilities [6].

4.3

Evolution of urban mobility

Historically, mobility has been viewed largely as a product, which includes the vehicles, physical infrastructure, and fuels required to move people around. Increasingly, however, mobility is approached as a service: the method by which we procure food, engage in economic activity, access entertainment, or meet with friends and family, all through seamless movements from place to place. Different transport technologies and infrastructures have been implemented, resulting in a wide variety of urban transport systems around the world [1]. In the history of urban mobility, there have been four general eras of urban development (as discussed next)—each associated with a different form of urban mobility, with a fifth phase unfolding [7].

4.3.1 The walking-horse car era (1800s 1890s) Even during the industrial revolution, the dominant mean of getting around was on foot. Walking cities were typically less than 5 km in diameter, making it possible to walk from the downtown to the city edge in about 30 min. Land use was mixed, and density was high (e.g., 100 200 people per hectare). The city was compact, and its shape was more-or-less concentric. Still, the industrial revolution brought additional populations through rural to urban migrations, improved construction techniques allowing for higher densities and new forms and locations of employment. The development of the first public transit in the form of omnibus service extended the diameter of the city but did not change the overall urban structure. The railroad facilitated the first real change in the urban morphology. New developments, often referred to as trackside suburbs, emerged as small nodes that were physically separated from the city itself and from one another. The nodes coincided with the location of rail stations and stretched out a considerable distance from the city center, usually up to a half hour train ride. Within the city proper, rail lines were also laid down and horse-cars introduced mass transit.

4.3.2 The electric streetcar or tram era (1890s 1920s) The invention of the electric traction motor created a revolution in urban travel. The first electric trolley line opened in 1888 in Richmond, Virginia. The operating speed of electric trolley was three times faster than that of horse-drawn vehicles and addition of not generating wastes. The streetcar city was able to spread outward 20 30 km along the streetcar lines, creating an irregular, star-shaped pattern. The urban fringes became areas of rapid residential development. Trolley corridors

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became commercial strips that would come to characterize the main commercial areas. The city core was further rooted as a mixed-use, high-density zone. As street congestion increased in the first half of the 20th century due to the dissemination of automobiles, the efficiency of streetcar systems deteriorated as cars exceeded their right of way. Further, many cities had decrees that prevented fare increases, implying that many streetcar systems became unprofitable, leading to a lack of maintenance and investment in additional services. These factors contributed to the decrease of many streetcar systems in the later part of the 20th century.

4.3.3 The automobile era (1930s 1950s) The automobile was introduced in European and North American cities in the 1890s, but only the wealthy could afford this innovation. From the 1920s, ownership rates increased dramatically, with lower prices made possible by assembly-line production techniques. As automobiles became more common, land development patterns changed. Developers were attracted to green-field areas located between the suburban rail corridors, and the public was attracted to these single-use zones, thus avoiding many inconveniences associated with city, mainly pollution, crowding, and lack of space. Still, this phase usually represented the peak share of public transit in urban mobility as suburban developments did not yet account for a large share of the urban landscape and cities were still high density and transit dependent.

4.3.4 The freeway era (1950s 2010s) In the second half of the 20th century, the massive diffusion of the automobile as well as the construction of highway networks had substantial impacts on urban mobility. Highways were built to connect the central business district to outlying areas and, in many cases, complete or partial ring roads were built. The personal mobility offered by the automobile represented a paradigm shift in terms of lifestyle, consumption patterns as well as residential location. The automobile reduced the friction of distance considerably, which led to urban sprawl. The emergence of the suburb created a new landscape in which public transit did not fit well with few services being offered to these new residential areas. Commercial activities also began to suburbanize as well, creating additional passenger and freight mobility systems. Within a short time span, from the 1970s the automobile became the dominant mode of travel in a growing number of developed and developing economies. Motorization and the diffusion of personal mobility has been an ongoing trend linked with substantial declines in the share of public transit in urban mobility.

4.3.5 The integrated mobility era (2010s onward) Throughout their evolution, urban transportation modes remained rather disconnected, particularly since they are owned and operated by separate entities such as

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transit agencies, automobile owners, or trucking companies that did not interact much. The dissemination of information technologies is changing this relationship. Emerging urban mobility systems are gaining from a higher level of integration resulting better levels of asset utilization. An early example concerns on-demand vehicle services pooling individual drivers and matching their mobility supply with the consumer demand through a platform accessible through a mobile device. A further development concerns self-driving vehicles that could expand mobility options and a better utilization level of automobile assets. This era is also associated with the diffusion of e-commerce and its associated home deliveries, underlining the issue of city logistics and last mile freight distribution.

4.4

Types of transit systems

Modern societies demand a high degree of mobility of a variety of types. This makes it essential to a complex transport system adapted to social needs, to ensure that people can move and goods be transported in safe and economically efficient ways. An efficient and flexible transport system that offers intelligent and sustainable patterns of mobility is essential for the health of our economy and our standard of living. In general, there are three different types of transit systems [3]:

4.4.1 Collective transportation: public transit The purpose of collective transportation is to provide publicly accessible mobility over specific parts of a city. The systems are usually owned and operated by an agency and access is open to all as long as a fare is paid—the reason why they are called public transit. The efficiency of public transit systems is based upon transporting large numbers of people and achieving economies of scale. The components of a public transit system include modes such as metro, tramways, buses, trains, subways, and ferries.

4.4.2 Individual transportation Includes any mode where mobility is the outcome of a personal choice and means such as the automobile, walking, cycling, or the motorcycle. Most people walk to satisfy their basic mobility, but this number varies according to the city being considered.

4.4.3 Freight transportation As cities are dominant centers of production and consumption, urban activities are accompanied by large movements of freight. These movements are mostly characterized by delivery trucks moving between industries, distribution centers, warehouses, and retail activities as well as from major terminals such as ports,

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rail yards, distribution centers, and airports. The growth of e-commerce has been associated with an increase in the home deliveries of parcels. The mobility of freight within cities tends to be overlooked but is part of an emerging field related to city logistics.

4.5

The urban mobility challenge

Mobility seems to be a distinguishing feature of urban areas, where more than half of the world’s population currently resides. By 2005, approximately 7.5 billion trips were made each day in cities worldwide. In 2050, there may be three to four times as many passenger-kilometer’s traveled as in the year 2000 [6]. Mobility flows have become a key dynamic of urbanization, with the associated infrastructure invariably constituting the backbone of urban form. Despite the increasing level of urban mobility worldwide, access to places, activities, and services has become increasingly difficult. Current urbanization patterns are causing unprecedented challenges to urban mobility systems, particularly in global south countries. Not only is it less convenient—in terms of time, cost, and comfort—to access locations in cities, but the process of moving around in cities generates a number of negative externalities [8]. Accordingly, many of the world’s cities face an unprecedented accessibility crisis, and are characterized by unsustainable mobility systems. Urban mobility supports everything we do as individuals, as communities and as regional, national, and international economies. People need to move around to secure basic human needs. In the city, high-quality mobility is a necessity for the success of other urban sectors and the creation of jobs, and plays a key role in cultivating an attractive environment for residents and business [1]. Mobility is widely cited as one of the most intractable and universal challenges faced by cities the world over. As urban populations increase, existing and emerging cities face the challenge of meeting the rising demands for efficient mobility within limited physical infrastructure capacity. Simultaneously, citizens’ expectations are changing continually, influenced by ongoing innovations around low carbon and efficient vehicle technologies and improvements in infrastructure management [8]. Increasingly, cities are the focus for regional, national, and international economic activity and social development, drawing growing business and resident communities. The combined influence of population growth, demographic change, and changing urban form leads to increasing demand for travel in city centers, suburbs, and between the two. Demand for improved intercity mobility is also growing, to create faster and more direct connectivity between settlements [1]. This growing demand converges with an inadequate supply of physical transport capacity in many cities, which can result in crowding, congestion, and an unpleasant experience of the city. In established cities, this problem is attributed to spatial constraints—which inhibit additional growth of transport networks—together with

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budgetary limitations on physical infrastructure maintenance and renewal. Meanwhile, in many developing cities investment in infrastructure construction is struggling to keep pace with the rapid rate of urban growth [9].

4.6

Urban mobility in the context of sustainability

As urban populations grow and economic prosperity increases, cities are increasingly under pressure to deliver fast, safe, and environment-friendly transport to citizens and businesses. There is a need to develop models on which the various stakeholders can draw to devise effective and sustainable mobility policy [5]. Building on the seminal Brundtland Report of 1987, a sustainable urban mobility system is one that satisfies current mobility needs of cities without compromising the ability of future generations to meet their own needs [6]. Sustainable urban mobility can also be identified as “the ability to meet society’s need to move freely, gain access, communicate, trade and establish relationships without sacrificing other essential human or ecological values, today or in the future” [4]. The idea of sustainability in urban mobility has moved beyond a focus on ecology and the natural environment to also include social, economic, and institutional dimensions. Furthermore, it has moved beyond the preoccupation with movement and flows within urban settings to looking at enhancing proximity in space. A holistic and integrated approach to urban land-use and transport planning and investment is needed if urban areas are to become socially, environmentally and economically sustainable [2]. Accordingly, the four pillars of sustainability of urban mobility are the social, environmental, economic, and institutional dimensions. These pillars are not separate or isolated, as there are important synergies and cobenefits [6]. The current transport system presents significant and growing challenges for the environment, human health, and sustainability. Current schemes of mobility have become highly reliant on private vehicles, which have shaped citizens’ lifestyles and the layout of our cities, with the impacts on sustainable land use in urban areas and their hinterlands [3]. Consequently, mobility is not only a matter of developing transport infrastructure and services, but also of overcoming the social, economic, political, and physical constraints to movement. These constraints are influenced by factors such as class, gender relations, poverty, physical disabilities, affordability, etc. Sustainable mobility extends beyond technicalities of increasing speed and improving the effectiveness and efficiency of transport systems, to include demand-oriented measures (e.g., promoting walking and cycling, and reducing the need to travel)[9]. In the move toward a more sustainable transport, demand will be addressed as part of a package of long-term strategies to eliminate the negative health and environmental consequences of mobility by itself. In this way, strategies will be able to bring measurable economic and environmental sustainability benefits and improve traveler experience in terms of [1]:

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Lower fuel and power consumption by vehicles and infrastructure, leading to: reduced transport-related greenhouse gas emissions improved local air quality and related environmental conditions Reductions in congestion and traveler frustration A more efficient and cost-effective system to operate and maintain, leading to: greater affordability for transport providers and travelers reduced requirement for hard infrastructure in dense urban environments

4.6.1 Sustainable urban mobility and public transport development A developed country is not a place where the poor people have cars but it is where the rich people use public transport. Development of sustainable urban mobility and public transport networks leads by all means to radical improvement of citizens’ quality of life. It improves access to markets and job opportunities, to education, to health-care services, to leisure, to the things citizens need in everyday life [10]. Citizens that use public transport walk more. Walking increases fitness levels, leading to healthier citizens and less strain on the health-care systems. Quality of life is also affected by commuting times. In several cities commuters often travel more than an hour to and from work. While sustainable urban transport system should better handle the negative externalities, at the same time, it should be providing enhanced mobility, including for the poor and vulnerable groups, which was an important element of the Millennium Development Goals [10]. Sustainable urban transport system is thus determined by the degree to which the city as a whole is accessible to all its residents, including lowincome people, the elderly, the youth, the disabled as well as women with children [6]. Furthermore, transport interventions should be explicitly targeted to prevent negative outcomes. By permitting high levels of innovative services and giving priority to public and nonmotorized transport, the need for private cars is reduced. Strategies to change public attitudes and encourage sustainable forms of mobility thus have a key role to play [11]. Government institutions and planning processes should emphasize accessibility over mobility. The process of achieving more sustainable urban transportation systems designed with the principle of accessibility at their core is dependent on the participation of all stakeholders in cities, the authorities, the private sector, and the citizens, along the lines of principles of democracy. A successful process will depend on effective governance of land use and transportation, where new housing and commercial planning will entail simultaneous transportation systems design, careful neighborhood design, strategic infrastructure investments, and fair, efficient, and stable funding [10].

4.6.2 Challenges of urban transport and mobility The accessibility of any transportation system in urban mobility is influenced by the availability of an efficient and effective transport system. An effective and efficient urban transport system is one that can satisfy the numerous and diverse requirements of the metropolitan mobility, including minimizing traveling time between various

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locations, while at the same time internalizes externalities to positively affect the well-being and the quality of life of the citizens of that area. Among the most apparent externalities are traffic congestion, traffic accidents, and environmental pollution [11]. Introducing and sustaining an effective and efficient transport system is therefore not an easy but possible task. This requires that the appropriate authorities transform the available land and financial resources, both limited capital inputs, into relevant transport infrastructure and networks to provide, what is considered, the right combination between the various motorized individual or collective/public and nonmotorized transport modes as well as easy transfers between them to meet the mobility demand. The development of the infrastructure and networks, thus creating the urban transport supply side to meet the mobility demand is not the end of the challenging task. While the available transport options created through available infrastructure and networks can influence the shifts of the population between the various modes of transport, this in itself may not be sufficient to create an effective and efficient transport system. The authorities also need to create a relevant culture for mobility and through it influence the shifts between various transport modes. They can hence create demand for what is considered the right combination between the various motorized individual or collective and nonmotorized transport modes [12]. Furthermore, connectivity should be ensured among different public transport modes with the national transport networks. Good connectivity is a prerequisite for efficient functioning of urban and national transport systems. Efficiency of urban transport for various transport modes depends on their interconnectivity and connectivity with national transport, especially in suburban areas where people may choose to live outside the metropolitan areas and to commute every day. Usually, these commuters are actually using the national or regional transport. No wonder that transport terminals started to become commercial centers where a number of daily-life services are provided. Beyond the fact that these terminals became extra revenue sources for railways and for metro operators they facilitate commuters’ life by covering daily needs while commuting [11].

4.6.3 Sustainable urban mobility and land-use planning Urban planners have to consider access as the basis for urban mobility planning. Urban planners and decision makers should move away from a “transport bias” in urban mobility planning, toward a focus on the human right to equitable access to opportunities [8]. Enhancing accessibility is at the core of sustainable mobility, this focus on accessibility emphasizes the need for a holistic and integrated approach to sustainable urban mobility. It establishes a link between urban form (in terms of shape, structure, function as well as demographics) and urban transportation systems. Particular attention is given to the urban form’s potential to support the increased proximity of places and functions, thus minimizing the need for extended movement. Relationships between locations, as well as obstacles and suitability between them, are critical in determining the ease and convenience of accessing them. The development of a sustainable urban mobility system starts with the organization of urban space [6].

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Land-use planning ensures the proximity and compactness of locations, and diversifies functions, so as to cater to a variety of needs. The accessibility focus for sustainable mobility also entails paying due consideration to the built form of the city, particularly the optimization of urban density and the fostering of a sense of place. The combination of high-density settlements, strong sense of place and mixed-used functions not only minimize the need for extended movement, but also enhance economies of agglomeration and encourage nonmotorized mobility. Furthermore, appropriate design and layout of streets and neighborhoods, proper allowance for building configuration and density, and streamlined arrangement of arterial streets and roads, should also be taken into account [6].

4.7

Urban mobility in the smart-city age

As city populations explode and private car ownership increases, city transport becomes unsustainable. Not only from the environmental perspective, but economic growth and quality of life will also be severely hurt if current trends continue. Forward-looking municipalities are learning about and actively trying to move toward “smart cities.” A smart city is an efficient city, a liveable city, as well as an economically, socially, and environmentally sustainable city [13,14]. This vision can be realized today, using innovative operational and information technology, and leveraging meaningful and reliable real-time data generated by citizens and city infrastructure. Smart city can also be defined as the city that uses technology, data and intelligent design to enhance its liveability, workability, resilience, and sustainability [15]. Mobility is a cornerstone of the smart city [1]. Smart urban mobility is concerned with finding new ways to improve the flow of traffic in cities and encourage more efficient use of transport infrastructure. Achieving smart solutions for urban mobility might take the form of smart transport infrastructure, mobile apps, and digital services that allow more efficient use of existing transport methods, and completely new transport methods like autonomous vehicles. Whatever the means, the goal should be clear—every city should aim to reduce private car ownership, reduce congestion and pollution, and measure if these goals are met. All possible assets—including technology, city regulations, taxes, and political leadership—should be leveraged toward the goal of smart sustainable, efficient urban mobility.

4.7.1 Benefits of smart urban mobility In the technological era, we are facing the emergence of a new market, in which new business models and creative thinking are required to design contemporary systems based on hard infrastructure working together with operational and digital technologies; to develop the service relationships between existing and new actors; and to finance a strong and future-proof mobility system. Mobility infrastructure

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has been identified as the number one priority for cities seeking to attract investors, and as such it is high on the agenda for many growing cities [12]. Smart Urban Mobility is articulated both as a critical difficulty and a potential source of hope to transform city operations. What is becoming clear is the need to invest in infrastructure with a view to it serving long-term needs of 50 years or more, and not only immediate or short-term needs; the need to treat smart mobility as one tool to enhance economic, social, and environmental well-being. Important benefits of smart urban mobility include [1]: G

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Quality of life—improving the efficiency and accessibility of public transport improves quality of life and saves expenses for citizens, and makes a city more attractive for tourists. Reduced pollution—smart systems promote the use of public transport, by offering access to multiple transport options, and providing real-time schedules and delays. This acts to reduce private car usage and encourages eco-friendly habits like bike sharing and carpooling. Public transport safety and security—improved monitoring of public transport can help identify and respond to emergencies, disasters, or terror attacks. In advanced stages of implementation, it can also reduce the accident rate across a city. Mobility marketplace—open data about transportation and movement in the city creates a market for mobile apps, which can help consumers travel and consume transport services across the city. Smart parking solutions—with the right infrastructure, sensors, security cameras, and internet connectivity, cities can reduce the problem of parking in busy urban areas. Cities can share data on available parking, and consumers can access this data via mobile apps and web interfaces.

A number of technological advancements and social trends have a major impact on the transfer to smart urban mobility [12]: G

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Public transit first: Public transportation development and the integration of digital transport management platforms are becoming common throughout the world. Autonomous driving, data gathered via internet of things (IoT), and real-time analytics, are turning the old bus and rail system into a modern, digital-friendly transportation alternative. Autonomous driving: Self-driving vehicles are expected to make driving effortless and make roads safer. This will save lives and will change the economics of road and parking infrastructure in large cities. Electric vehicles (EVs): EV sales are rapidly growing; they are now more affordable and governments are encouraging their production and use. The price of EVs may soon be low enough to compete with traditional gasoline-fueled cars. Decentralization of energy systems: It is now easier to own and recharge EVs, as renewable energy sources are more widely available, and electricity can be generated by companies and private individuals. Decentralization of energy reduces demands on urban power grids and creates more charging stations, private and public. Ride-hailing: Travelers can use this service to “hail” a driver who will take them to their destination. This service is used on demand via apps or a phone call. It is safe and ecofriendly as it reduces the number of private vehicles on the road.

There is a common agreement that significant investment and creative financing will be required, if mobility infrastructure is to cope with growing pressures. However, there is a consensus that the existing sufficient technologies available today should be taken into positive steps to transform to smart mobility systems.

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4.7.2 Infrastructure components of smart urban mobility system The smart mobility system requires a variety of infrastructure components, including physical infrastructure, operational technologies, and communication and information technologies. Without any single component of them, smart mobility products cannot meet their full potential to manage operational efficiency and user demand. Coordination and integration between different layers in the structure allow improved operational efficiency, as well as new products for demand management. The infrastructure components of a smart mobility system can be conceived as a number of “layers,” each of which depends on and adds value to those beneath and above it. The infrastructure components of a smart urban mobility system include the following [1].

4.7.2.1 Physical infrastructure The whole system is underpinned by the physical infrastructure of urban mobility, that is, the roads, railways, bike paths, footpaths, and other physical assets that enable transport to operate. The data and information that support smart mobility are generated continuously from dynamic patterns of human behavior as people navigate the city using the available infrastructure.

4.7.2.2 Operational technology Operational technologies generate the raw material required for smart solutions: the data. They allow real-time collection and communication of raw data from physical infrastructure and services, and rapid adjustment of infrastructure management to create additional capacity where it is needed. Such technologies are already installed in many cities to direct traveler behavior and maintain traffic flows, therefore contributing to increased operational efficiency on the network. Intelligent transport systems (ITS) are becoming a reference for the promotion of more sustainable and rational urban mobility. This approach embraces a variety of technologies, such as electronic tickets and payments, traffic management, travel information, access control, demand management, and smart cards for urban transport, in airports, railway, and bus stations. These new technologies will make it possible to offer citizens new services and enable improved real-time management of traffic and capacity use, as well as enabling traceability and monitoring of transport flows for environmental and safety purposes [3]. ITS equipment continuously generates new data and information about the transport network, and allows transport operators to make immediate interventions to manage traffic and travel.

4.7.2.3 Communications technology: networks Wi-Fi, 3G, 4G, and bluetooth channels are fundamental for real-time communication of location-based data from machine to machine (the “IoT”), and between human operators, data processors and information consumers. Data are

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communicated from operational technologies to command and control centers, where it can be used to enable instant responses via remote controls. There are over 6 billion mobile phone subscriptions in the world, held by customers who are already using cellular technologies to give and receive information. More than 1 billion of these are smart phone owners, and this number is growing by 42% each year. In many countries, the speed and extent of wireless network coverage, together with the protocols governing wireless use, are major limitations to the quality of data available from operational technologies. Hard-wired communications will play a role in some cities, where existing fiber installations are more effective than wireless channels.

4.7.2.4 Information technology: software Data are collected and aggregated by public and private sector actors engaged in data processing, anonymization, analytics, contextual modeling, simulation, and software programming. These specialist data handlers take advantage of the vast supply of city data and information from operational technologies to create innovative software applications and interfaces for users. These applications are pushed out to users via communications networks, providing useful information to influence network operations and demand. The software response to urban mobility is currently the more dynamic area for growth in the mobility market, with many new players proposing innovative ideas to influence travel management. While operational technology is already well understood and adopted by many city governments and transport operators, its role in supplying data for software innovation is only just being recognized. Many cities are just beginning to embrace the potential of software solutions.

4.7.3 Switching from traditional to smart mobility There is a common agreement that significant investment and creative financing will be required, if mobility infrastructure is to cope with growing pressures. However, there is a consensus that the existing sufficient technologies available today should be taken into positive steps to transform to smart mobility systems [12] (see checklist: “An Agenda for Action for Taking Steps to Transform to Smart Mobility Systems”). An agenda for action for checking the status of operations in the urban environment A number of steps are required to switch into smart mobility, which includes the following key activities (check all tasks completed): 1. Holistic view: Switching from traditional to smart and sustainable mobility requires a holistic view of the city, nearby regions, and current traffic flows. Initiatives should be coordinated with other municipalities and higher-level authorities such as state-level transportation authorities. (Continued)

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(cont’d) 2. Policies and finance: Ensure that policies support the smooth operation of integrated mobility systems. A city should apply relevant taxes and redistribute the funds to support integrated mobility projects. 3. Smart mobility regulation: Many cities and governments are introducing laws and regulations that encourage and support the use of mobility apps and new transport methods. These include financial incentives for companies using EVs or ride sharing and locally established traffic rules that prioritize public transportation and integrated mobility solutions. 4. Changes to the physical landscape: Consider changes to city layout and infrastructure, such as modifying roads to provide extra lanes for new forms of mobility. 5. Smart mass transit system: Optimize public transport systems and add smart technology elements to make public transport more effective and attractive. Over time, this can reduce the number of vehicles on the road. 6. Parking space: Offer services that use real-time information to guide drivers to available parking space. Support ride-hailing services by converting some parking spots into stops where passengers can switch vehicles, or assign curb space for companies to rent for this purpose. 7. Revenue: Leverage IoT to collect transport-related taxes—this can make up for losses in revenue in other areas such as the reduction in fuel taxes. For example, leveraging underroad sensors, it is possible to tax the use of road infrastructure by metering how many miles citizens travel on city roads. 8. Smart infrastructure: Cities are adopting new technology, supplementing existing infrastructure with sensors, data analysis, and decision support systems. Smart cities are finding new ways to improve the flow of traffic and encourage more efficient use of transport infrastructure. Upgrading existing roads, and augmenting them with technology, can be more efficient than building new ones. Smart transport systems can improve traffic flow; public transportation lanes can encourage public transport use, and autonomous vehicle lanes can allow such vehicles to travel at faster speeds than regular vehicles.

4.7.4 Integration of smart mobility solutions within and across sectors Technology has the potential to make our cities more humane and liveable. We need to make sure that citizens are at the center of our efforts by combining top down and bottom up approaches to governance of projects—top down through city leadership and bottom up through citizen engagement and transparency. By mainstreaming smart technologies in this way, the “smart” tag and revert to “cities” will be distributed. Integration between mobility and other systems could include different options. The following examples show that the integration of systems through technology has the potential to increase efficiency and address safety and sustainability [1]:

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Mobility/street lighting: Each system optimizes itself, but they collaborate during events and incidents, for example to provide increased lighting when needed for emergency services, or security lighting as needed around bus stops. Mobility/weather: The capacity and safety of roads and streets highly depend on weather conditions. Special response plans may be needed, using smart devices to activate maintenance services and optimize the use of resources. Mobility/emergency: The so-called “Golden Minutes” effect is created when transport corridors are proactively managed to allow emergency vehicles to pass through quickly.

4.7.5 Urban planners to improve planning via predictive modeling Planners have the opportunity to use the vast amounts of data generated by public and private actors to improve the planning and delivery of transport services and facilities to citizens. They can also use data to identify and address problems. The full range of opportunities available to planners is only beginning to be recognized, and is moving gradually from the research forum to become an integrated part of urban planning practice [3]. Mobile phones, parking sensors, congestion charging zones, and smart card ticketing all yield valuable data about how and when people are moving around the city, and how these patterns are affected by variables like traffic, weather or public events. Supplemented by social media, aggregated data can also provide details of citizens’ thoughts and feelings about places and experiences. Personal privacy is ensured through anonymization of the data, before it is made available for use [1]. Increasingly, mobile phone data is being used to improve transport modelling practice. Mobile phone datasets comprise anonymous information on users’ origin, destination, route and mode of transport, and journey time. In the global north countries, these data are being used to validate models, to confirm that they are replicating realworld behavior. As confidence grows in their reliability, they can replace expensive and disruptive roadside interview surveys as the primary data source. In the global south countries there is normally very little reliable travel demand data available and the “conventional” data required for transport planning is virtually nonexistent, thus, new sources of data can be exploited to provide insight into travel behavior that would otherwise have been impossible to achieve. Mobile phone data can revolutionize the analysis of travel patterns and planning of urban transport systems. With the right skills and software capabilities, this massive anonymous data bank can allow urban planners to understand the detailed use characteristics of city facilities and services, and to create places that are tailored to the people who use them. Simulation and parametric design tools are becoming increasingly user friendly, allowing predictive modeling to inform future design. Using sensor-derived real time data, different planning conditions can be quickly tested and simulated. By supplementing urban planning and management practices with digital technologies, there is an opportunity to improve mobility services for citizens, while managing demand on physical transport networks and generating wider economic and environmental value. In addition, by utilizing data in planning, planners have

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the opportunity to create a more humane and functional urban environment, which responds to the evolving needs and expectations of its populace.

4.8

Summary

This chapter started with a review of the basic definitions related to its topic. Then the chapter illustrated the interrelationship between mobility, transportation, and accessibility as the core of accessibility-based urban mobility. The history of urban mobility and its evolution during different eras since 1800s till the current era and the types of transit systems were presented. In addition, the chapter included a discussion of the urban mobility challenges, and urban mobility in the context of sustainability. Under the topic of sustainable urban mobility, the chapter discussed different aspects of sustainable urban mobility, its relation with public transport development, and land-use planning. The last part of the chapter discussed the urban mobility in the smart-city age. This part includes the process of switching from traditional to smart mobility, infrastructure components of smart urban mobility system, integration of smart mobility solutions within and across sectors, and how can urban planners improve planning via predictive modeling. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

4.9

Chapter review questions/exercises

4.9.1 True/false 1. True or false? Rapid urban development occurring across much of the globe increased the volume of passengers and freight moving within urban areas. 2. True or false? There are a number of terminologies highly interconnected with mobility, namely: transportation, accessibility, and urban mobility. 3. True or false? Mobility is not just having access to two modes of transportation. It is having transportation options that anyone can count on to get to the desired destination. 4. True or false? Accessibility should not be at the core of urban mobility. 5. True or false? Mobility is approached as a service: the method by which we procure food, engage in economic activity, access entertainment, or meet with friends and family—all through seamless movements from place to place.

4.9.2 Multiple choice 1. The purpose of ________ transportation is to provide publicly accessible mobility over specific parts of a city. a. Transparent

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b. Human centered c. Collective d. ICT enabled e. Preferred What includes any mode where mobility is the outcome of a personal choice and means such as the automobile, walking, cycling, or the motorcycle? a. Individual transportation b. Safety c. Housing d. Economy e. All of the above As cities are dominant centers of production and consumption, urban activities are accompanied by large movements of: a. Economies b. Infrastructure systems c. Freight d. Autonomous systems e. Transport sharing Urban mobility supports everything we do as: a. Individuals b. Communities c. Regional economies d. National and international economies e. All of the above What can be identified as the ability to meet society’s need to move freely, gain access, communicate, and trade and establish relationships without sacrificing other essential human or ecological values, today or in the future? a. E-government b. Sustainable urban mobility c. Citizenry engagement d. Distance services e. Smart economy

4.9.3 Exercise 4.9.3.1 Problem What aspects are the most important in urban transport systems?

4.9.4 Hands-on projects 4.9.4.1 Project Do research: Show how mobility is a vital part of a thriving urban economy. However also show how mobility solutions that do not take account economic, environmental, and societal impacts can also be detrimental to urban life.

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4.9.5 Case projects 4.9.5.1 Problem What are the top-priority problems in urban areas, and how can they be solved?

4.9.6 Optional team case project 4.9.6.1 Problem Develop an urban mobility plan.

References [1] The Climate Group: Urban Mobility in the Smart Age, Smart Cities - Strategy & Innovation, Schneider Electric, Smart Cities cornerstone series, ARUP, London, 2019. [2] The Energy and Resources Institute: Defining Sustainable Urban Mobility, TERI-NFA Working Paper No. (11), New Delhi, 2012. [3] Herrero, L. Transport and Mobility: The Keys to Sustainability, Universidad Complutense de Madrid (UCM) and Observatorio de la Sostenibilidad en Espan˜a (OSE), March 2011. [4] Litman, T. Measuring Transportation Traffic, Mobility and Accessibility, Victoria Transport Policy Institute, March 1, 2011. [5] Audenhove, F., et al. The Future of Urban Mobility 2.0: Imperatives to Shape Extended Mobility Ecosystems of Tomorrow, Arthur D. Little Global CEO, January 2014. [6] UN-Habitat: Planning and Design for Sustainable Urban Mobility, A global report on human settlements, January 15, 2014. [7] J. Rodrigue, C. Comtois, B. Slack, The Geography of Transport Systems, Third Edition, Routledge Publisher, USA, 2013. [8] El-Sherif, D. Energy Efficient Strategies for Urban Transportation Planning, International Conference on “ENERGY in TRANSPORTATION”, ASHRAE Hellenic Chapter Athens Greece, November 2018. [9] World Business Council for Sustainable Development (WBCSD): Sustainable Urban Mobility, WBCSD Mobility - Switzerland, March 2015. [10] Alexopoulos, K. and Wyrowski, L. Sustainable Urban Mobility and Public Transport in UNECE Capitals, the United Nations Economic Commission for Europe, 2015. [11] Sustainable Urban Transport Technical Document # 13: Urban Mobility Plans National Approaches and Local Practice, German International Cooperation “GIZ” & Institute for Transportation & Development Policy “ITDP,” November 2014. [12] HERE Mobility: Smart Urban Mobility: A Quick Start Guide, HERE Mobility Company, Endhoven, The Netherlands, 2019. [13] Department of Economic and Social Affairs: Revision of World Urbanization Prospects, A United Nation’s Report, May 16, 2018. [14] Division of Water; Urban Development; Mobility: Urban Mobility Strategies for Liveable Cities, Federal Ministry for Economic Cooperation and Development (BMZ), Germany, Berlin, August 2016. [15] El-Sherif, D. and Khalil, E.E. Smart Cities A Myth or Reality, Proceedings ASHRAE Region14 CRC, September 2019.

Coupling of the mobility and energy infrastructures as urban mobility needs evolve

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Andreas Pfeiffer1,2, Alexandra Burgholzer3 and Dilara Kanag3 1 CUT POWER AG, Essen, Germany, 2RWTH Aachen University, Essen, Germany, 3 E.ON Solutions GmbH, Essen, Germany

5.1

Introduction

Urban transport infrastructure and vehicles are becoming ever more flexible and have to adapt to changing user needs. For example, the traditional concept of private car ownership has become a nuisance for many, as it implies being bound to investments that are of significant size for average private households and as it causes additional hassle due to ever decreasing capacities for moving around and “storing” (i.e., parking) personal vehicles during idle times. What is more, with increasing urbanization and a space volume that remains stable, quality of life is put under pressure. One of the major resulting trends is a call for more sustainable infrastructures that shall prevent deterioration of air quality and the like. Energy and mobility infrastructures go hand in hand to respond to this need. Electric mobility (E-mobility), embedded into concepts such as connected transport and smart-city infrastructure, is one of the dominant answers that has been found during the last years that caters to the aforementioned trends. In this chapter, examples of the applications of electric mobility are described in detail. A light is shed on the angle of what actors are involved in these applications and what the value add is both for the customer/user as well as for the public.

5.1.1 Why is this chapter needed? The use of electric cars in urban mobility systems supports cities in the transition to more sustainable commuting and by that also living in cities. The chapter presents the positive impact that recent technological developments can have on urban energy and mobility infrastructures as well as recommendations for urban policy shapers for nurturing these.

5.1.2 Added value for user to read it The reader will get insight into major trends and developments of electric mobility infrastructure. Scholars will get an impression of the wide scope of trends that Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00005-X © 2021 Elsevier Inc. All rights reserved.

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shape the E-mobility sector today and in the future. They will get an impression of today’s solutions for these trends as well as an outlook on next developments in the sector. Policy makers will especially profit from an overview of successful actions to promote sustainable energy and transport in cities.

5.1.3 Selected components of mobility systems In order to have a common understanding with the reader, we first define a selected set of components that are required to describe mobility systems in cities. Especially for E-mobility, the reader will need to understand the specific components such as electric vehicles (EVs) and their charging infrastructure.

5.1.3.1 Urban versus rural In this chapter, we refer to “urban” systems as the opposite of “rural.” By this a large conglomeration of citizens is to be understood within a space that is defined by law as a “city” and limited in terms of space, legal, and institutional boundaries. These are set out by a government, which is solely responsible for this space.

5.1.3.2 Mobility infrastructure The wider ecosystem required to transport goods, animals, or people from one place to another is understood as mobility infrastructure. This does not only require adequate vehicles in terms of size and speed, but also refers to structures that allow travel such as roads, air, or sea. The latter are usually defined and governed by local and/or international law. However, also “fueling” infrastructures are required as part of the ecosystem as only they enable vehicles to actually move from A to B. The latter can take all forms —they could be traditional petrol stations as well as solar panels attached to a vehicle.

5.1.3.3 Energy infrastructure Energy forms the basis of many of today’s activities. Energy infrastructure traditionally focused on distributing power from a point of generation such as a plant to a point of consummation such as a factory or office building. Today, points of generation and consummation move closer together. For example, the point of consummation and generation can be in the same location such as for a factory using its own waste products to provide power, or private households installing solar panels on the roof to fuel their EVs in the garage.

5.1.3.4 Electric vehicles One option of alternative fuel driven vehicles are EVs. This chapter focuses on pure battery EVs, plug-in hybrids vehicles and the underlying infrastructures. A combination of political push, technological advancements, and growing availability for charging infrastructure for this type of vehicle has led to an increasing availability across the world. Instead of traditional petrol or diesel, these cars’

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motors use electrical current to operate the vehicles’ wheels. Speed of charging (i.e., “fueling”) and driving range are dependent on the car’s battery size. The former is also impacted by the power of the charge point.

5.1.4 Charge points (Electric vehicle supply equipment) As “part of the infrastructure to supply a vehicle’s battery with energy,” charge points are used. They are “used to connect EVs to the energy grid and transfer energy from the grid into the car or back” [1]. These infrastructures are installed next to a parking lot for the respective vehicle. They can be found in the private space mostly as socalled wallboxes or they can take the form of charging columns in the public or semipublic space (i.e., at publicly used private areas such as super market parking lots).

5.2

Trends that shape urban mobility

Growing cities are a trend that has been anticipated and visible around the world. Chinese metropolis, South American, and Indian megacities are the most impressive examples, but also smaller cities with fewer than 500,000 inhabitants grow very fast as people are moving to urban or suburban regions where the chances for employment and cultural participation are higher than in rural areas. Today, 55% of the world’s population lives in cities and this is expected to grow further to over 68% in 2050 [2]. Growing urbanization leads not only to a higher tear and wear of existing city infrastructure of all kinds—from streets to public equipment—, but it also pushes existing infrastructure to its boundaries such as parking spaces, public transport, or housing. While worn out infrastructure can be replaced, some boundaries of infrastructure are a natural given. An example for this is parking lots on public streets. In a city with a given number of square meters, the available number of parking lots in streets will eventually be exhausted. Creative minds have hence approached this capacity limitation from a different angle. They came up with the idea to not only use streets, but also build up parking houses or go underground. The problem was advanced from a different angle and traditional business models were hence expanded. However, as cities grow, so does the competition for space. When more people need a place to live in, skyscraping apartment buildings use up space above ground. By this, new forms of vertical districts are more and more part of urban living. By this, new forms of vertical districts are more and more part of urban living. Underground transportation expands to cover an increasing need of transport. Today, private vehicles are widely common. An indication for this is the number of passenger cars per person in the European Union: one passenger car is met by only two citizens [3]. With the relatively decreasing number of public parking spots and the growth of the share of apartment houses, the question arises of how a personally owned car can be parked. This question becomes even more pressing, when the price for parking a car overnight in cities like Copenhagen can easily get more expensive than for having a hotel room for the person driving the car.

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For those who cannot afford to live in the center of cities or who prefer less crowded areas, suburban regions are attractive. Yet, their daily life revolves often around the cities they live close by to and pushes capacity boundaries even more. For the suburban population, a normal workday often implies travel from their suburban homes to a work place in the city. This can be done directly, if sufficient parking spaces exist at their target location. However, city governments can be observed to ever more promote options were commuters park their car at outer city hubs and use alternative transport to move around the cities. Many examples exist; one of the very large ones is the Vyttila Mobility Hub in the city of Vyttila in India. Here, commuters can park their cars and drive onward with different modes of public transport, such as buses, metro, or even by boat [4]. As the number of personal transport vehicles in cities decreases, also the hubs of the opposite direction should be anticipated and promoted. City dwellers who do not own a car due to limited space or need, would profit from attractive offers to rent out cars for long-distance travels to places that are insufficiently served by long-distance public transport. However, urban transport modes are not only impacted by limited infrastructure availability. In addition, a trend of living clean, healthy, and mindful of oneself as well as one’s environment can be observed to have increased during the last years. As traffic increases with urbanization, so does pollution of the air. Cities contribute greatly to global pollution already today: they create over 70% of greenhouse gas emissions and use 80% of energy consumed in the world [5,6]. Polluted air deteriorates life, and the urban one in particular, as densities increase with less space and more production of pollution. Particulate matter (particle pollution) is not only creating a nonpretty scenery by hazing the air, it also impacts citizen health. Its smaller variants, PM10 and PM2.5, are inhalable and can get deep into human lungs and bloodstreams [7]. Various studies have proven that high particle pollution increases the risk of asthma in children as well as of heart attacks in older people [8]. This pollution can not only be produced by industrial production or power generation, but also from transport. Here, it has to be mentioned that this stems both from the combustion process in traditional vehicles as well as from tear and wear of vehicle wheels. Outdoor activities hence increasingly become uncomfortable for urban citizens. And as citizens get more educated on the health impacts, governments have also started to react. Current activities are for example bans on personal vehicle traffic. In Chinese cities like Beijing, specific license plate-dependent car-free days for nonelectric cars are a policy instrument already in use. European cities such as Milan or various German ones limit vehicles by pollution categories to enter cities [9].

5.3

An answer from energy and mobility sectors to urbanization and clean trends

Aforementioned trends have been already responding by a set of market activities, starting from EVs in multiple applications, to a lookout for actual sustainability along the value chain, to better use of capacities in cities through efficient implementation and usage of mobility as a service and shared transport.

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5.3.1 Electric vehicles mitigate air and noise pollution First of all, with all of the above trends, clean transport options become a major component of urban mobility systems. Moreover, EVs are part of the solutions that have been found to overcome the challenges of modern living in cities. For this purpose, recent innovations and developments in the energy and mobility sectors are brought together to support a vision of providing a better living in cities. EVs do not only have the advantage of reducing air pollution by using locally produced energy from clean resources fitting seamless into the new energy infrastructures of cities. They also reduce noise pollution in cities, contributing to citizen comfort even more in comparison to other clean fuels. Electric engines cater to all stakeholder groups: public transport uses it for public buses, companies renovate their logistic fleets, private households exchange their personal vehicles, and new sustainable mobility business models (e.g., car- or ride sharing) with clean vehicles develop.

5.3.2 Commercial use of electric vehicles As cities limit access for vehicles with high levels of pollution ever more radically, companies have to adjust their commercial fleets, especially for city transport, accordingly. Established vehicle producers have been reacting: for example, Nissan’s e-NV200, PSA’s Partner/Berlingo Electric, and Renault’s Kangoo Z.E. make the switch to clean vehicles simple for inner city logistics. Recently new arising manufacturers of vehicles such as StreetScooter directly target the still-niche market with electric commercial vehicles only.

5.3.3 Successful electromobility cities around the world Cities have so far been the most prominent nurturing ground for EVs. About 44% of global EVs can be found within the 25 cities with highest EV numbers in the world. In addition, this does not yet include smaller cities with EVs. The five cities with most prominent absolute EV stocks are Shanghai ( . 150,000), Beijing (B150,000), Los Angeles (B150,000), Shenzhen (,90,000), and Oslo (,90,000) [10]. The policies that drive these positions are described in Section 5.5.

5.3.4 For true sustainability, a wider thinking is needed As already implied earlier, EVs are not automatically cleaner. Only, if the electricity consumed stems from renewable sources, a fair share of transport pollution of cities can be reduced. Here, it is also important to provide more energy from sustainable resources, to adapt at the underlying energy infrastructures, and to also use concepts like cogeneration to produce energy for transportation in a sustainable and smart way. Furthermore, as mentioned before, also wear and tear of wheels contributes to pollution. With particle filters built onto vehicles, air can be filtered “on the go” to counter the latter. An example for this is provided by German company StreetScooter. Amongst other vehicles, it produces the vehicle fleet for the German postal services

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(Deutsche Post). As these distribute parcels every day, the company plans to filter the air across the cities from the amount of particles that it produces [11]. What is more, production of vehicles also needs to become CO2 neutral. For example, companies like Audi have recently achieved this. Audi is producing its first fully EV at CO2 neutral production in its factory in Brussels [12].

5.3.5 Traditional transport business models Over the past decades, both city and rural inhabitants became used to having their personal car. Today, most people are very much focused on owning a personal means of transport. Just to recap the previous example: The European Union counts more than 0.5 cars per inhabitant, including children. Hence, the predisposition of today’s population is focused on owning an individual means of transport to get from A to B. In cities, for those parts of the population that do not own a personal means of transport, public transport such as metro, bus or tram, or traditional walking are the only alternatives. Previously, resource constraints have been discussed which underlined the limitations on urban space and infrastructure capacity. The consequences are reduced ownership of cars due to lack of storage or other frustrations resulting from capacity limitations such as traffic.

5.3.6 Mobility as a service caters to customer demands—better? Several city governments in different countries have tried to mitigate these capacity constraints by optimizing existing infrastructure usage rather than expanding space. Instead of answering to a visible physical demand, they aimed to understand the basic need of their citizens. They looked at it not by taking the perspective of “I have to get from A to B with my personal means of transport,” but rather of “I need to get from A to B.” A personal means of transport gives a certain type of comfort that city governments today try to recreate or surpass with a new business model called “mobility as a service.” In 2016, the city of Helsinki introduced their Mobility as a Service offer called “Whim.” Citizens can purchase a monthly subscription or pay as they go in a onestop shop for using all kinds of urban transport. Depending on their need, they use the means of transport that best suits them at the moment: bike share, bus, train, taxi, and car share. An app supports the user in exploring the most practical end-toend route and vehicle. Users can also register individual preferences such as time versus cost preferences [13]. Various cities provide similar examples, such as the Viennese WienMobil service, German Moovel, or UbiGo Gothenburg [14]. The advantages of mobility as a service are that it caters to citizens who cannot or do not want to have their own vehicle and that it allows users in general to optimize their transport costs according to their individual needs. It also helps the broader public to use existing urban transport infrastructure more efficiently as it reduces idle times and moves previous personal car users to travel in larger groups per vehicle. Users are incentivized by these services to use a transport based on its comfort and need fit for each trip.

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In regard to required infrastructure for this service, cities will require hubs for intermodality. The European Union has started investigation of this matter since 2018 and 2019 with various projects. The transition to this new service will probably not happen instantaneously. Long-grown value concepts tend to take time to change. However, already today value notions of new generations bring about a change.

5.3.7 Shared means of transport as an alternative component to personal means One of these changing values is the notion of owning a personal means of transport. As pointed out before, it persists until today. However, the so-called “Sharing Economy” trend hints that this notion might be about to change also for transport. The best example is car sharing. In 2014, 5 million people around the world had signed up for a car-sharing service. This went up from 350,000 in 2006 and is expected to reach 23 million members by 2024. Also bike sharing is widely available—in over 50 countries globally [12,15,16]. While the need for and willingness to use public transport increases ever more with urbanization, it cannot satisfy transport needs fully. Individualized transport continues to be needed for various use cases. Among them are uses for accessing places that are not opened up by general public transport, to transport larger amounts of goods, or travel for people who are physically inhibited, to name a few. In addition, a differentiation between ride and car sharing has to be made. The International Transport Forum (ITF) at the Organisation for Economic Co-operation and Development (OECD) has identified that (autonomous) ride sharing has the capacity to reduce the number of required vehicles in a city more than (autonomous) car sharing as the repositioning travel is needed much more than for ride sharing [17]. More on this can be found in the section on examples. For sharing of transport means to become an attractive business across the globe, several stakeholders in the ecosystem need to work together. Car producers need to provide cars that can actually keep up with required adaptions and servicing offers that cater to the public fleet needs. BMW and Ford have already announced that they plan to produce cars that are capable of autonomous sharing on a mass-market scale by 2021 [18]. In addition, sufficient users need to pick up the services in order to gain a minimum critical mass for usage. A first step can also be to create intracompany car-sharing systems with respective company policies that can easily push users to engage with services.

5.3.8 Improving connectivity via cars In the upcoming years, significant developments are expected in the car industry and in the infrastructure of cities. They both are becoming smart and connected more and more every day. For instance, cars send signal to other cars, when they detect traffic jams. Additionally, construction sites could alert drivers about possible delays by displaying real-time data on the dashboard. In other words, vehicles

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would be information centers of the future ensuring their users safety and optimized routings. As traffic flows are improved, this would result in reduced pollution and congestion [19]. This has already been initiated. Technology that plays a role in building this connection is called V2X—vehicle to everything. It connects the car not only to other cars, but also with its surroundings by using enhanced technology that has the potential to improve the safety of roads dramatically.

5.4

Examples of urban mobility components

The described market activities can be observed in various applications. A set of these have been described on the next pages to give an impression of these applications as well as to give a concrete idea of where industries are heading in this context.

5.4.1 Optimal charging solutions for E-mobility As mentioned before, one of the biggest parts of today’s urban mobility is formed by electric mobility. There are different players in this mobility world, even though it is a new market that has existed for a short time. It is essential to create value for users and to create competition among service providers, while they are presenting a new, electrified world to their customers. As this market is new, the number of charge points does not automatically meet the geographic and timing demands of each EV driver. This becomes a problem for charge points, which are located in business areas or in big shopping centers that are visited by large numbers of drivers during the day. This had led charge point operators (CPOs) and mobility service providers (MSPs) to become creative and invent optimal charging solutions in order to provide smart allocation of drivers to charge points. One of the other subjects of the E-mobility world that causes discussion today is the payment process. Currently, most of the charge points require radio-frequency identification (RFID) keys or charging apps to initiate the charging process. However, some companies are working on new solutions in order to remove the requirement of having any card or mobile app. In addition to smart payment solutions, charge points can also be used to make money. One solution is developed by E.ON with the IT platform service provider Virta. Their cloud-based solution manages peak energy consumption and its prices. This solution would allow hotel owners or other providers of semipublic chargers, like supermarkets, to set their individual charging prices for their customers. This cloud solution creates an opportunity as well for private chargers to identify themselves as public charge points and take advantage of this billing [20].

5.4.2 Necessity of charging hubs Even though the number of smart charging solution is increasing thanks to the development of different types of technologies, including blockchain, VIP Charging, ISO 18115, and NFC; the number of charging stations still needs to rise for optimal customer comfort. E-mobility is a new concept, if it is compared with conventional cars

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and their fueling solutions. The capacity of charging stations in cities has not yet increased enough to meet the needs of drivers. Many people have already purchased EV charging boxes for their homes, such that they can charge when they return from work in the evenings. However, it is not possible for every EV driver to own their own charging station. For this reason it is necessary to set up a charging hub in big cities, which provides huge numbers of charge points with fast and ultrafast charging features. Currently, these kinds of charging hubs have not yet been established. EBL, an energy company based in Switzerland, has conducted a project recently in Basel to build Europe’s largest E-mobility Hub, which is planned to begin operations in 2023. The Hub will feature 280 EV Charge Points, including 60 fast chargers. In terms of obtaining the electricity for the Hub, EBL plans to use green energy supplied from renewable energy using local power sources [21].

5.4.3 Green charging as an alternative With the rise of EVs, the usage of and the need for traditional fuels such as petrol or diesel could be strongly reduced. The energy need of these EVs could come from traditional CO2 heavy power plants. However, the alternative way is to obtain energy through renewable sources, even with the opportunity of eliminating the need for expensive transmission and distribution infrastructure upgrades. There are a variety of companies currently working on building this system or already serving it to their customers, in order to improve utility grid reliability and to leverage renewable energy resources. It is also possible to use green charging at home. There are some energy providers that offer photovoltaic systems integrated into customers’ cars. It ensures users the green charging experience by using their own 100% green solar energy. This way, customers do not only reduce their CO2 footprint, but can also save money on their travel expenses. E.ON is providing one of these green charging systems for EV users. With the product “E.ON SolarCloud Drive,” homeowners can use the electricity they generate from their solar panels to charge an electric car. To ensure that the solar power reaches the garage, solar experts establish the appropriate connection already during the solar panel installation. This saves unnecessary costs for the subsequent retrofitting of charging boxes with an output of up to 22 kilowatts (kW). As Sebastian Eisenberg, head of Photovoltaic Operations Germany at E.ON, explains, this does not only make the home more sustainable, but also makes it possible to use solar power on the move. With the E.ON SolarCloud virtual power storage system, it is already possible for EV drivers to supply 100% of their charging needs with their own solar energy, even when the sun is not shining [22].

5.4.4 Electric vehicles supporting the energy ecosystem— vehicle-to-grid Until now, only one-directional charging has been described. Additionally, there are CPOs that work together with charging infrastructure providers to build bidirectional charging stations. By using bidirectional charging stations, it is possible to not only

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power cars from the grid, but to also return stored energy from the car to the grid. Thus, the battery of EVs could be used as a buffer for local grids or households. With the help of smart energy systems, energy in the battery can be sent back to the house when energy consumption is at its peak. This would lead customers to use energy efficiently and save money. One of the first initiators of this technology in Europe are E.ON and its partner, car manufacturer Nissan. The Nissan Leaf has a special engine system that is capable of returning stored energy from its battery to the grid [23]. Another application of vehicle-to-grid has been initiated by car manufacturer Renault. The company uses an intelligent charging system on the Atlantic Island of France, “Belle ˆIle en Mer,” to create the first smart French island. In order to achieve this goal, Renault works together with French charging infrastructure provider Morbihan Energies, mobility provider of the island Les Car Bleus and grid operator Enedis. Together, they are creating an innovative program to provide e-car sharing fleet services, stationary storage of solar energy, and smart charging on the French island [24]. The smart system of this island combines EVs with local solar energy storage and an intelligent charging system. That means the EVs provided by Renault will be charged at smart charge stations through the energy overflow obtained from solar energy located on the roof of public buildings. In addition to that, the batteries of these cars store extra power from the solar panels, which can be used to provide energy to the largest holiday resort on the island [25].

5.4.5 Examples of shared mobility As mentioned before, different alternative concepts for mastering the need of personal transportation have emerged, like car-sharing, ride-hailing, and intelligent mobility platforms. They provide advantages both for drivers and for the environment. For drivers, it takes out the hassle of paying taxes for cars and maintenance. Car sharing has been existing for a while. Car2Go and DriveNow are carsharing companies with German origin, which were founded in 2008 and 2011, respectively. In Germany, DriveNow provides its services in Berlin, Cologne, Hamburg, Duesseldorf, and Munich. In addition, it is available in several European cities in Austria, the United Kingdom, Denmark, Belgium, Italy, Finland, and Portugal. Car2Go extended its service out of Europe also to China, Canada, and the United States. A difference has to be made between free-floating and stationary car sharing. With free-floating car sharing, users leave their rental car in any parking space within a certain area where the car-sharing company is operating. With stationary car-sharing models, users are limited by the obligation to return the car to the original rental location. These sharing platforms free people from owning a vehicle, whilst still ensuring easy and smart access to mobility. Apart from these existing sharing platforms, the sharing economy is also developing and has expanded into different variations. One variation is car-pooling services, which provide drivers a platform to share their ride with other passengers who need to reach a given destination. One of most well-known car-pooling platforms is Blablacar which launched in 2006 and provides their ride-sharing services through an app and a web portal in various cities

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and countries. In other countries, similar services are for example offered by Liftshare, Carshare, or Carpool Karaoke. These platforms offer cost saving and flexibility advantages to their users. What is more, the journey of car sharing developed into another direction that lets customers sit only in the passenger side by offering them free time without worrying about traffic and the ride. These services are called “ride-hailing” or “ride-pooling.” They could be regarded as modern taxi-sharing services demanded through app by entering a target destination. However, as the opposite of taxi services, this app collects passengers in one ride, who would travel in closer areas. City Mapper, uberPOOL, Lyft Line, Clever Shuttle, Moovel, and MOIA are examples of these mobility services run by different companies. The principle of ridehailing works through a platform that customers sign up for and request to travel from A to B. According to the requests from different users on the platform, smart routes are created to optimize the total route. Thus, service providers offer a pleasant passenger experience, while further reducing the carbon and financial footprint.

5.4.6 Electrified car-sharing models As mentioned previously, the sharing economy has become a big trend for mobility with its different types of sharing models that ensure users easy, smart, and profitable mobility options. Although it is also possible to make this sharing mobility culture cleaner by electrifying sharing vehicles, so that the quality of air and environment can increase with the lower amount of greenhouse gases emitted by EVs. Thus, the combination of these concepts with EVs enables an even more impactful improvement of live in cities. From an economic, social, and ecological perspective, the impact of EVs in these new mobility concepts on the environment and the society by decreasing air pollution and allowing social participation should not be underestimated. Some companies already took action to provide users electrified sharing facilities, including BMW, Renault, Volkswagen, and Daimler. In parting with energy solutions provider BMW DriveNow and Ariva introduced electric car sharing in the city of Copenhagen back in 2015. Today the E.ON charging infrastructure is the green backbone for over 950 electric car-sharing vehicles of five car-sharing providers. E.ON provides green energy per year on its more than 1500 charge points in Denmark and thereby helps to reduce the amount of carbon footprints in Copenhagen every year [26]. Renault launched the service Moov’in. Paris, together with French car rental company ADA. In this cooperation, Renault deployed 120 EVs—100 Zoe as well as 20 Twizy. Renault covers the cost of their maintenance and repair services; meanwhile ADA provides a digital interface for the platform so users can reach the car-sharing services through an app. Furthermore, ADA is also responsible for charging and positioning the vehicles and for processing financial payments. The App Moov’in is already available at App Stores and Google Play for download, since October 2018. The aim of Renault is to raise the number of vehicles up to 2.000 by January 2019 [27]. Car2Go is one of the car-sharing companies that already lets its customers ride EVs. In Amsterdam, Stuttgart, and Madrid, their fleets are already fully electric.

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It has more than 400,000 customers, that have driven their EVs already for 79 million kilometers, according to its statement in the last quarter of 2018. As Daimler announced, they are launching electric car-sharing service also in Paris in the beginning of 2019, by offering 400 Smart EQ Fortwo [28,29]. Electrifying mobility initiatives are not only led by car-sharing services, but also by electronic bike sharing services and long-distance bus operators. French Mobility Provider IDFM (Ile-de-France Mobilite´s) is conducting a project, which will launch in September 2019 in Paris. IDFM plans to offer 10,000 e-bikes for long-term rental in the project scope, which could be expanded to 20,000 e-bikes in the following term. In that case, IDFM would have established the world’s largest e-bike rental service [30]. Another supporter of E-mobility is Flixbus. Flixbus, a start-up from Munich, launched the first electric long-distance bus in Germany, cooperating with Greenpeace Energy. The aim of their first test project is to create an electric bus route between Paris and Amiens. In addition to Buses, they are also designing an electric train network, called FlixTrain. It is planned to connect Berlin and Stuttgart, as well as Hamburg and Cologne. It would get its electricity from renewable energy sources that would be provided by Greenpeace [21].

5.4.7 Rise of mobility service platforms Car sharing is not the only way to promote a sharing economy in the mobility sector. For traveling from A to B, there are different alternatives that citizens can take, including bike, train, car, bus, or simple walking. However, travelers today often end up losing time while considering options and comparing them based on speed and price. However, thanks to MSPs and their smart application platforms, this problem has become manageable. Mobility service platforms, like City Mapper, Transit, and Moovel, provide a comparison of transportation through their applications, aiming to take users to their destinations quicker and more affordably. The general payment procedure of the mobility platform is pay-as-you-go. Users choose from the listed transportation options and pay for the one that they will take. Mass Global with its “Whim” App provides an alternative which has integrated a variety of transportation types into one application with special tariffs. Whim offers three different tariff options to users based on monthly fees. A standard pay as you go option, a monthly fee that includes public transportation for free and provides special offers on taxi, car and bike sharing, and an all-in monthly paid offer which allows to use all transportation options with a single monthly payment, including bike, train, bus, taxi, car rental. With those three different offers, Whim ensures passengers easy, fast, affordable, and smart access to reach their destination. Only within the first 6 months after launch, the app increased the number of users to 45,000 in the Helsinki region, among those 5100 paying customers [31].

5.5

Action recommendations for regulators

In general, one can state that regulators need to expand their policy work for future mobility. Mobility today does not anymore relate only to streets, rail, and sea,

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but it already touches upon topics such as land use, environment, and safety. Furthermore, today also energy sources, construction, digital technologies, and data as well as security, business, and economic policy need to be considered. What is more, government policy on mobility should focus less on specific technologies and more on mobility as a service where holistic comfort of the population—both for individuals as well as for the community—is put into the focus [5].

5.5.1 Right to electric vehicle chargers Especially for EVs, the question arises, how a personal car should be charged at home or close by. This is relevant both for personal as well as for shared cars. For public charging close by where citizens need it, cities in the Netherlands and Belgium have come up with a proposal for their inhabitants. Citizens have the “right to a charger.” This means that they can request a charger in front of their home or where their daily need is most urgent. With this approach, governments hope to build infrastructure on a need basis, yet prevent the hen-egg problem where customers do not consider an electric car because they do not know where to charge it [9]. While this covers one part of the story, the other part must be that also apartment garages can be equipped easily with a private charger. This is currently still one of the most compromising factors preventing citizens from getting an electric car in European cities like Paris, Berlin, or Vienna. The “right to a private charger” in one’s own apartment building still has to be established. To ensure possibility of construction of these chargers, also the cost of new grid connections will have to be tackled by policy makers. Today, grid connection extensions can cost up to millions of euro depending on the type of charger that is to be attached and the geographic location of the nearest grid connection point. If chargers are supposed to benefit the greater public and a sufficient regional coverage is supposed to ensure fair access for all, grid companies and/or governments will have to rethink their own grid infrastructure investments to help charging infrastructure providers in offering fairly spread services.

5.5.2 Education and incentives for clean vehicle drivers To switch to cleaner and more capacity-friendly mobility, education, and incentives are needed. It is both a lack of awareness and a fear of loss of comfort that city governments have to tackle. General public awareness programs can be helpful together with attractive incentive schemes. However aware customers also question whether they will be able to go sufficient distances, satisfy their more complex transport needs in terms of target location or volume of goods or people to transport, etc. Hence, securing comfort as well as an education on how customers will be able to keep their comfort has to be put forward by governments. In regard to incentives, several initiatives have been used by successful E-mobility cities to push cleaner mobility. These can be narrowed down to six categories:

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1. Financial purchase incentives: Several high EV stock cities have significant purchase incentives. While German cities offer up to h2000/full EV (BEV), Chinese cities provide up to h8400, and Californian cities up to h8800. 2. Car registration: China has reacted to the capacity shortage of public space with limitations on personal vehicles. Hence, receiving a license plate for certain cities often involves a waiting time that can surpass a year as well as high prices (up to over h11,000). The incentives some cities provide EVs with are both more affordable license plates as well as a larger volume thereof and hence quicker access to car ownership in these cities. 3. Sufficient charging infrastructure: Sufficient per inhabitant charging infrastructure is not an automatic accelerator for higher EV numbers, as the example of German cities proves. While the German city stock for EVs does not keep up with its international competitors, for example, Stuttgart can compare in terms of charging infrastructure with several Top 25 cities analyzed in the ICCT report. However, sufficient availability of charging infrastructure mostly goes along in strong EV markets. While most Chinese cities only look to massive numbers of charging infrastructure, Dutch and Belgian cities build EV infrastructure on a need basis, following proactive citizen requests. Here, as in many other cities, city governments partner up with utility companies to build up this infrastructure. 4. Parking benefits and preferred lanes: With differing intensities, several Top 25 EV stock cities incentivize EV driving via free parking in payable parking zones. Depending on local geography and transportation policy, also a system of preferred lane access has been observed to have a positive impact. 5. Limited traffic zones: Several international cities have already announced plans to reduce emissions to zero in certain parts of their cities until 2030. Among them are Paris, London, Los Angeles, Oslo, Seattle, Tokyo, Milan, and many more. In addition, already today, German cities, and also Milan and Paris go ahead and limit car access by their pollution levels. 6. Public fleets: Several vehicles driving in cities belong to public fleets—public buses, commercial as well as passenger cars. Already switching these to electric engines can strongly drive EV stock. For example, 100% of Shenzhen’s 16,000 public buses drive electric. Also, the city’s taxi fleet is supposed to become fully electric by end 2018 [9,10].

5.5.3 Regulation that anticipates innovation and new business models Innovation is pushing ahead, while government is often trying to follow and sometimes simply prohibiting. A balance needs to be found between fostering innovation and sharing data to create collaboration and nurture even more learning and development of new solutions. If data ownership and sharing needs are not clearly regulated, businesses might be hesitant to share the data or, on the contrary, build innovative business models with them. Shared transport and charging services as well as mobility as a service require the anticipation or codevelopment of regulation for the new type of service for consumer rights, safety, data protection, liability interoperability, and similar areas [13]. Also sharing transactions on more informal levels between private individuals will have to be accounted for. Especially when it comes to autonomous services, a much wider ethical discussion has already started. Government should be

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codeveloping this regulation together with representatives of all stakeholder groups today, as especially city governments will benefit from the technology. There are first cities taking on the challenge together with private partners, for example, Uber in San Francisco. The intermediary time will bear significant need for coordination as autonomous and nonautonomous vehicles share the same roads.

5.5.4 Sustainable supply chains for clean transport As discussed before, clean transport will only be truly sustainable, if the full supply chain is led according to sustainable principles. This needs to start at sourcing of battery materials, cover low-emission transport of goods during production and lead up to production of energy from renewable sources. While some public funding programs, for example, for infrastructure deployment in Germany, already do focus on requiring green energy at publicly funded chargers, the European Union has also started a program in 2018 that focuses on clean battery production. The European Battery Alliance investigates how batteries in general, one of the foci being EV batteries, can be produced in a sustainable manner.

5.6

Outlook

Business models are developing rapidly in urban mobility and as this chapter is being published, further applications might have reached the market. Many actors on the market are pushing for innovation, in order to create meaningful and pleasant user experience for travelers and to obtain an efficient and an emission free mobility ecosystem for each user. A few new applications that can be anticipated today have been outlined in the following text.

5.6.1 Leisure time while traveling The future of mobility is shaped by different aspects, not only to meet with users’ needs for faster and smarter travel, but also to create value in the life of customers. Mobility providers are aware of the value of their customers’ time. That is why they focus on maximizing the efficiency and enjoyability of traveling, while they are designing the scope of their services. One of these services is concentrated on the free time that passengers are spending in their cars or in shared cars. MSPs are in the planning phase of providing entertainment during their customers’ ride. Customers could watch a movie, play games, or even take naps, while they are traveling to their destinations. Apart from private rides, the services meet also with the needs of passengers during their business trips, ensuring the possibility to conduct meetings or conference calls. Thus, spending time in the car can be used in the most productive way, instead of concentrating on driving the car.

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This future trend will be promoted by adopting autonomous vehicles and mobility hubs where hyperloops, drones, shared cars, cycle highways, and public transit would be located. These mobility hubs would create opportunity for users to choose one of the transportation devices according to their current needs. However “car as home” and “executive saloons” are the future phase of mobility that would play a role in creating value in their users’ life. With the “car as home” concept, the car provides its user facilities like daily personalized care and control over their health-wearables. Moreover, users could use cars as an interactive space for further work during their commuting. In terms of “executive saloons,” it would be possible to conduct meetings with business partners while commuting and enables people to spend their leisure time with productivity [32,33]. The precondition of applying and implementing this technology is the production and adoption of driverless cars building on artificial intelligence.

5.6.2 Artificial intelligence taking over the task of driving Autonomous driving builds upon smart and connected abilities of cars today and in the future. Here, the human element of traffic is reduced to a minimum that ensures safety-critical control functions and algorithms and data exchange allow optimized driving. Industry speakers expect this to reduce fuel consumption and thereby emissions, as well as to make traffic safer and manage limited space of roads and parking lots more efficiently. Furthermore, this service is expected to offer access to mobility for new customer groups, such as the elderly, disabled people, as well as users in remote areas [34]. In the mid-term, when autonomous cars and regulation for them are ready, (urban) drivers overall will gain comfort in all aspects of their mobility. They will save time before their drive when having to find a car. Drivers will gain time during their drive by both an optimized traffic flow as well as a time gain thanks to reduced effort during the drive. In addition, after the drive, no parking, cleaning, fueling, and little repairing would have to be a part of their actively managed duties. Especially for ride-hailing, no matter whether it is individual rides or shared rides, this optimized system becomes attractive. Several cities are already considering opportunities to make this service more efficient. An example is Milan, where “Robo-taxis” have been investigated and are expected to run on the streets [35]. According to a study conducted in Milan, Italy, upcoming Robo-Taxis would have a great impact by optimizing use of existing infrastructure. The study shows that approximately 9000 six-seater microbuses could reduce traffic in Milan by 30%. By leaving the existing local public transport system, it is possible to remove traffic jams in Milan, while also ensuring 40% less emissions and by decreasing the need of parking places by 30% [35]. The ITF at the OECD has done a study on the impact of autonomous driving on traffic and space capacity in cities. In their analysis of a model European city, they assumed that all trips remain the same in terms of origin, destination, and timing and that all car and bus trips would be replaced. In regard to ride-hailing services they differentiate between AutoVots and TaxiBots. While AutoVots are similar to

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taxis and transport individuals, TaxiBots combine several individuals according to their location similar to an optimized bus service. The ITF found that in a model European city that combines high-capacity public transport with TaxiBots, 9 out of 10 cars could be removed. Where high-capacity public transport is combined with AutoVots, 8 out of 10 cars could be removed. In all cases the need for on-street parking was eliminated completely. About 80% of the need for off-street parking was removed as well. They also identified that this would lead to an overall increase of car travel as for TaxiBots (16% more car-kilometers) also bus travel would have to be replaced and for AutoVots (189% of car-kilometers) repositioning and servicing trips would increase [17].

5.6.3 Autonomous vehicles in logistics The arrival of autonomous technology will not only affect transportation of people, but also transportation of goods. Since the vehicles would be driven autonomously, logistic services could get an advantage from it. That means they could deliver their goods with driverless vehicles. Some companies have already started to conduct their test projects, including Uber, Google’s parent company Alphabet, and Ford with their technology partner in autonomous sector Argo AI. Uber successfully delivered their first delivery in 2016. In order to develop driverless delivery, Uber bought the autonomous vehicle manufacturer start-up Otto. With the technology that Otto provides within their trucks, Uber was able to transport 50,000 beer cans to their target point [36]. Google is also working on autonomous delivery with parent company Alphabet and their drones “Wing.” This drone service has been tested in Australia with 55,000 journeys, delivering medicine, coffee, and household goods. Helsinki will be the first European location where Alphabet will launch its test project in 2019 [37]. Another approach toward autonomous mobility comes from car manufacturer Ford. They have invested in a self-driving start-up company, Argo AI. With this cooperation, both companies have successfully delivered the orders of Domino’s Pizza to its customers with autonomous cars in Miami. For safety precautions, they place controllers in the front seat during the delivery. However, the pizzas have so far been delivered without any interruption of the controllers. Ford’s reported goal is to have a fleet of autonomous vehicles to deliver goods on US roads by 2021 [38].

5.7

Summary

The chapter described that increasing urbanization and a trend for mindful sustainability drive a change in habits and needs of urban populations. More demand by more people in a city meet a stable supply of space, fresh air, infrastructure, and more environmental aspects. This causes constraints such as more pollution of air and sound, increased traffic, low availability of space, and requires both a new approach to reducing consumption as well as an optimization of available infrastructure and space.

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The energy and mobility sectors have responded to this change by developing the electromobility ecosystem further that allows for sustainable and clean transport. It needs to consist of the optimal mix of charging and driving infrastructure availability as well as of power supply from renewable energy supplies and production of materials in sustainable ways. Furthermore, electric mobility of the future goes hand in hand with new business models of mobility as a service and sharing vehicles such as electric cars, electric scooters, or bikes. In addition, an optimal usage of the cars, infrastructure, and power supply is ensured by connecting all of the components digitally. A set of use cases have been described for the aforementioned cases. In addition, a set of recommended actions for policy makers have been described by describing industry best practices. The story does not end at connected cars and mobility as a service. The future of mobility is already underway with autonomous vehicles on the verge. The following outlook will give some highlight notes on the topic and invite for staying curious on the next developments. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

5.8

Chapter review questions/exercises

5.8.1 True/false 1. True or false? Urban transport infrastructure and vehicles are becoming less flexible and have to adapt to changing user needs. 2. True or false? Growing cities are a trend that has been anticipated and visible around the world. 3. True or false? EVs only have the advantage of reducing air pollution by using locally produced energy from clean resources fitting seamless into the new energy infrastructures of cities. 4. True or false? Even though the number of smart charging solution is increasing thanks to the development of different types of technologies, including blockchain, VIP Charging, ISO 18115, and NFC; the number of charging stations still needs to rise for optimal customer comfort. 5. True or false? In general, one can state that regulators need to reduce their policy work for future mobility.

5.8.2 Multiple choice 1. With regard to incentives, several initiatives have been used by successful E-mobility cities to push cleaner mobility. Which one of the following is not one of those incentives? a. Transparency and accountability technology b. Financial purchases c. Car registration

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d. Sufficient charging infrastructure e. Parking benefits and preferred lanes A personal means of transport that gives a certain type of comfort that city governments today try to recreate or surpass with a new business model is called: a. Transportation as a service b. Mobility as a service c. Sharing economy as a service d. E-governance as a service e. All of the above The so-called ___________ trend hints that the notion of owning a personal means of transport might be about to change also for transport. a. Sharing economy b. Public transport c. Urbanization d. Autonomous e. Sharing of transport In the upcoming years, significant developments are expected in the car industry and in: a. Wireless mobile technologies b. Mobile services readiness c. Infrastructure of cities d. Mobile-government services e. All of the above One of the biggest parts of today’s urban mobility is formed by: a. Charge points b. CPOs c. RFID keys d. Green charging e. Electric mobility

5.8.3 Exercise 5.8.3.1 Problem What could be ways to use the existing infrastructure in a different way to get more out of it?

5.8.4 Hands-on projects 5.8.4.1 Project Do research: Which incentives is the country you are living in using to promote EVs?

5.8.5 Case projects 5.8.5.1 Problem What other initiatives would be promising to push further sustainability of the EV supply chain?

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5.8.6 Optional team case project 5.8.6.1 Problem Select a case study for urban mobility systems from the C40 Website: https://www.c40. org/case_studies. Do a check on their project status today: Were they successful or not?

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[14] International Association of Public Transport AISBL (UITP). The mobility as a service (MaaS) success story: WienMobil, UITP. ,https://www.uitp.org/ThE-Mobility-as-aService-MaaS-success-story-WienMobil., 2017 (accessed 18.11.18). [15] H. Rosamond, Mapping of bike-sharing data will change the way you see these cities, World Economic Forum. ,https://www.weforum.org/agenda/2016/08/what-bike-sharedata-can-tell-us-about-our-cities., 2016 (accessed 08.12.18). [16] S. Shaheen, A. Cohen, Innovative mobility carsharing outlook: Carsharing market overview, analysis, and trends, Transportation Sustainability Research Center—University of California: Berkeley. ,https://docplayer.net/7409226-InnovativE-Mobility-carsharingoutlook-carsharing-market-overview-analysis-and-trends-summer-2013.html., 2016 (accessed 05.12.18). [17] International Transport Forum (ITF), Urban mobility system upgrade: how shared selfdriving cars could change city traffic, OECD International Transport Forum. ,https:// www.itf-oecd.org/sites/default/files/docs/15cpb_self-drivingcars.pdf., 2015 (accessed 04.11.18). [18] N. E. Boudette, Ford promises fleets of driverless cars within five years, New York Times. ,https://www.nytimes.com/2016/08/17/business/ford-promises-fleets-of-driverless-cars-within-five-years.html., 2016 (accessed 08.12.18). [19] McKinsey Berlin, Urban mobility 2030: how cities can realize the economic effects, McKinsey: Berlin. ,https://www.mckinsey.com/B/media/mckinsey/industries/automotive%20and%20assembly/our%20insights/urban%20mobility%202030%20berlin/urban %20mobility%202030%20berlin.ashx., 2016 (accessed 02.12.18). [20] N. Manthey, E.ON launching smart charging powered by Virta, electrive.com. ,https:// www.electrive.com/2018/10/10/e-on-launching-smart-charging-powered-by-virta/., 2018 (accessed 21.11.18). [21] N. Manthey, First electric long distance bus in Germany, electrive.com. ,https://www. electrive.com/2018/10/24/first-electric-long-distance-bus-in-germany/., 2018 (accessed 19.11.18). [22] E.ON Energie Deutschland GmbH (E.ON). Drive ready E.ON macht solaranlagen fit fu¨r das laden von elektroautos, E.ON. ,https://www.eon.de/de/pk/unternehmen/presse/ pressemitteilungen/2018/2018-06-19-drive-ready-eon-macht-solaranlagen-fit-fuers-laden-vonelektroautos.html., 2018 (accessed 21.11.18). [23] C. Werwitzke, Nissan and e.on work on EV-based energy services, electrive.com. ,https://www.electrive.com/2018/03/06/nissan-e-work-ev-based-energy-services/., 2018 (accessed 28.11.18). [24] G. Renault, Groupe Renault unveils France’s first smart island on Belle-Iˆle-En-Mer. Groupe Renault Press Office. ,https://media.group.renault.com/global/en-gb/grouperenault/media/pressreleases/21216115/le-groupe-renault-devoile-la-premiere-ile-intelligente-de-france-a-belle-ile-en-mer., 2018 (accessed 11.11.18). [25] C. Randall, Renault is converting Belle-Iˆle-en-Mer to a smart island, electrive.com. ,https://www.electrive.com/2018/09/23/renault-is-converting-belle-ile-en-mer-to-a-smartisland/., 2018 (accessed 17.11.18). [26] H. Matthias, P. Andreas, O. Katarina, B. Sven, Leveraging the service-dominant logic for the design of smart E-mobility services, in: Albert Albers, et al. (Eds.), Mobility of the Future, 2018, pp. 160 161. [27] C. Randall, Renault and ADA start e-car sharing Moov’in in Paris, electrive.com. ,https://www.electrive.com/2018/07/23/renault-and-ada-start-e-car-sharing-moovin-inparis/., 2018 (accessed 11.11.18).

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[28] DAIMLER, Paris Motor Show: car2go announces launch in the French capital for January 2019, Daimler Press Release. ,https://media.daimler.com/marsMediaSite/en/ instance/ko.xhtml?oid 5 41413011., 2018 (accessed 14.12.18). [29] C. Randall, Car2Go will launch in Paris with 400 E-Smarts in 2019, electrive.com. ,https://www.electrive.com/2018/10/03/car2go-will-launch-in-paris-with-400-e-smarts-in2019/., 2018 (accessed 11.11.18). [30] C. Randall, Paris to launch world’s largest electric bicycle fleet, electrive.com. ,https:// www.electrive.com/2018/11/11/paris-to-launch-worlds-largest-electric-bicycle-fleet/., 2018 (accessed 16.11.18). [31] K. Pohjanpalo, How Helsinki arrived at the future of urban travel first, Bloomberg. ,https://www.bloomberg.com/news/articles/2018-07-15/how-helsinki-arrived-at-the-futureof-urban-travel-first., 2018 (accessed 07.12.18). [32] M. Mu¨nster, Mobility 2030 1 : from urban shuttle to car-a-home, NUANCE. ,https:// whatsnext.nuance.com/connected-living/futurE-Mobility-2030-userstories/., 2018 (accessed 23.11.18). [33] G. Watson, Working from car. Autonomous Vehicles and the Future of the 9-5. ,https://www.2025ad.com/latest/2018-11/autonomous-driving-and-working-culture/., 2018 (accessed 27.11.18). [34] European Automobile Manufacturers Association (ACEA), Connected and automated driving, ACEA. ,https://www.acea.be/industry-topics/tag/category/connected-andautomated-driving., 2018 (accessed 18.11.18). [35] d-fine GmbH, and Agenzia Mobilita` Ambiente Territoro, The impact of shared and autonomous robo-taxis on future urban mobility - a simulation approach for Milan 2030, Milan, Frankfurt: d-fine GmbH. ,https://www.d-fine.com/unternehmen/aktuellethemen/urban-mobility-mailand-2030/., 2018 (accessed 07.12.18). [36] D. Galeon, 50.000 beers: Uber’s self-driving truck just made its first delivery, Futurism. ,https://futurism.com/50000-beers-ubers-self-driving-truck-just-made-its-first-delivery., 2016 (accessed 21.11.18). [37] BBC, Google’s wing delivery drones head to Europe. ,https://www.bbc.com/news/ technology-46456694., 2018 (accessed 07.12.18). [38] P. LeBeau, Ford teams with Domino’s, Postmates in Miami to test delivery via autonomous vehicles, CNBC. ,https://www.cnbc.com/2018/02/27/ford-teams-with-dominosto-test-deliveries-by-autonomous-vehicles.html., 2018 (accessed 07.12.18).

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Michela Longo1, Wahiba Yaici2 and Federica Foiadelli1 1 Politecnico di Milano, Milan, Italy, 2CanmetENERGY Research Centre, Ottawa, Canada

6.1

Introduction

In the last few years there has been increased conversation about the “smart cities.” The concept of the smart city originated within the Renaissance cities during the 14th century—at a time of advancing urban planning, and with the aim of launching new projects to improve these urban centers. A smart city is a sustainable, efficient, and socially innovative city. It is a city that ensures a high quality of life for citizens by working to meet the needs of populations, businesses, and institutions concurrently. This challenge of satisfying multifarious and diverse needs can be addressed by implementing multiple projects in the fields of energy efficiency, technology, environment, communication, and mobility. These projects are therefore united by a single factor: sustainability. Significant innovations and new technologies have been introduced in the last few years that are aimed at simplifying daily life in many Italian cities, with particular attention to environmental protection. Examples include some urban changes and new services to revitalize urban centers; reduction of energy, waste, and polluting emissions; projects to enhance the efficiency of buildings; promotion of electric mobility; free Wi-Fi networks; and measures being implemented to enable the use of a smartphone to pay for parking for cars, and to or purchase tickets for use in public transportation. Four participants are believed to be involved in creating a smart city. These are the people, the government, businesses, and universities. Additional support is required from designers, developers, and financial organizations. However, it must be borne in mind that each of these groups also includes other interested parties. Smart cities are the “cities of the future.” The most common time reference in the smart city definitions is therefore the future, without any time limit. The recent innovations and new technologies in the fields of development, research, and ecosustainability aspire for continuous improvement of urban situations, and it is expected that every city can become smarter. In this chapter, a general discussion of the panorama of electric mobility is first presented. Then a brief introduction of, and current developments regarding electric vehicles (EVs) around the world and the different types of EVs currently available according to their hybridization levels will be described in some details. Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00006-1 © 2021 Elsevier Inc. All rights reserved.

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The various charging methods and the related systems and equipment as part of infrastructure of the electric vehicle supply equipment (EVSE) are then reviewed.

6.2

Electric mobility

Going back in time to its origins, the electric mobility has been in use since the end of the 19th century. Long before problems associated with massive use of fossil fuels manifested, there were indications of the unsustainability of that form of energy in the long term. In 1898, following a contest in which several prototypes of vehicles [both electric and with internal combustion engine (ICE)] were presented, the jury announced, in what may be regarded almost as prophetic vision that: “It seems clear that petrol coaches cannot sustain a public car operating system in a large city” [1]. The early 1900s witnessed the evolution of these means of electric transport [2]. Electric cars seemed preferable to petrol cars that were noisy, and carried the risk of fire and explosions, with annoying vibrations and smoky exhaust gases. Furthermore, manual gearbox and cranking made them difficult to use. It is true that, for the first electric cars, the distances that could be covered were meager (only 80 90 km) but since transportation requirements were limited to domestic purposes, this did not constitute an obstacle, at least in an initial phase. But then, the situation seemed destined to change in favor of a means of transport that comprised an ICE, sequel to the following events: G

G

G

The emergence of mass production of vehicles which was first introduced by Ford Motor Company with its famous T model The reduction in oil prices The extension and improvement of the road network which facilitated greater distances to be traveled

All these factors changed the focus in favor of fossil fuel mobility which became predominant throughout the 20th century up to the present day. The oil crisis of the 1970s and the resultant economic downturn however, highlighted the fragility of an economic system based mainly on fossil fuels which, in addition to their obvious limitations and massive pollution of the environment, tend to be located in volatile regions that are notorious for political instability. This crisis prompted world governments to radically rethink and modify their assets/investments with the aim of reducing dependency of the western world on Middle Eastern oil sources. Concerted efforts have included reduction in consumption, reorganization of industrial production, and the search for alternative energy sources. The crisis also involved the transport sector, particularly in the changeover to an electric transport mode which had hitherto been confined to niche applications, was now viewed seriously as a viable alternative. As mentioned earlier in this chapter, it is perhaps premature to talk about an “electrical revolution,” even though the probability of a mass changeover to this alternative energy source is becoming more realistic than ever. Coupled with the fact that fossil fuels will become increasingly scarcer in years to come, the move to electricity-powered vehicles has been in the spotlight for the last ten years and will

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remain topical in the foreseeable future. As stated in [3], currently, concerning the Europe panorama, the transportation sector is the fourth greatest emitter of greenhouse gas responsible for 14% of total emissions. A proliferate use of an electric type mobility could therefore reduce this percentage and thereby mitigate the increasingly troubling problem of pollution in urban centers. This diffusion is however discouraged, today, by diverse factors including the following: G

G

G

G

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Consistently high costs of EVs available on the market compared to traditional vehicles with ICE EVs’ extensive time needed for charging The anxiety range as the limited energy that can be stored in the batteries only allows the vehicle to cover a distance of between 100 and 300 km Limited charging points The requirement for continuous production and disposal of batteries which causes environmental problems and raises ethical questions

On the other hand, cars powered exclusively by electricity have several advantages. These include: G

G

G

G

G

They do not need fossil fuels to work and therefore can be charged with renewable sources only They introduce zero air pollutant emissions at the local level They are quieter than their counterpart that has ICE Their users enjoy many incentives that somewhat cushion the initial high purchase costs Overall, the cost per kilometer traveled is lower compared to petrol transport

Despite the initial hurdles and problems encountered in switching from thermal to electric mobility, a multigovernmental initiative to accelerate and control the deployment of EVs worldwide was inaugurated in 2009 under the clean energy Ministerial, also known as “Electric Vehicles Initiative” (EVI) [4]. The most recent initiative proposed by the EVI is the EV30@30 Campaign [5], launched at the Eighth Clean Energy Ministerial in 2017 in Beijing (China). The goal of this campaign is to achieve 30% sales of EVs by 2030. The main action steps to reach this include: G

G

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Providing support to the governments in need of policy and technical assistance Promoting programs (such as Global EV Pilot City Programme) to facilitate the exchange of experiences in the EVs field and propose the best practices for the promotion of EVs in cities Encouraging public and private sector commitments for EV uptake in company and supplier fleets Supporting the deployment of EV chargers and tracking progress

According to [4] in 2017, the global stock of electric passenger cars was 3.1 million, with an increase of 57% in 2016. Approximately two-thirds of the world’s electric car fleet are battery electric vehicles (BEVs). In addition to the 3.1 million passenger electric cars, there were nearly 250,000 electric light commercial vehicles (LCVs) on the road in 2017. Fig. 6.1 represents the growth of the EV market. The largest electric LCV fleet is in China (170,000 vehicles), followed by France (33,000 vehicles), and Germany (11,000 vehicles). Electric LCVs are often

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Figure 6.1 The growth of the EV market.

part of a company or government fleet. For instance, the DHL Group, a major logistics company, operates with the largest EV fleet in Germany (16,000 electric vans, bicycles and tricycles). It has also undertaken in-house development and manufacturing of its own electric vans, tricycles and bicycles as part of this vision. Following its success, the company is now selling its EVs to third parties (mainly municipalities and other businesses) [5]. Regarding the sales of EVs, the year 2017 is notable for sales of over one million vehicles worldwide, an increase of about 50% compared to the previous year, although this is still too modest to be considered an electric mobility revolution. The two leading nations in this sector are Norway and China, for different reasons. Regarding China, it has the largest car market and nearly 580.000 electric cars were sold there in 2017. On the other hand, Norway can boast of greater market penetration for EVs, as about 39% of vehicles sold in 2017 were electric.

6.3

Types of electric vehicles

This chapter has reviewed the evolution and spread of the EV, but as will be seen in the next paragraph, the EV’s typology is quite varied. So let us start by conceiving a suitable definition of an EV. In general, an EV is that vehicle that utilizes some form of energy to feed its electric motor for propulsion. Not all EVs are the same; rather, they differ according to their hybridization degree, which is the ratio between the secondary source and the total power. It is therefore possible to recognize five main categories of EVs based on the type of power supply: G

G

G

G

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Hybrid-electric vehicle (HEV) Plug-in hybrid electric vehicle (PHEV) Extended range electric vehicle (EREV) BEV Fuel cell electric vehicle (FCEV)

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6.3.1 Hybrid electric vehicle HEVs exploit, simultaneously or separately, the combination of the ICE and the electric motor. The presence of the electric powertrain is intended to achieve either a better fuel economy than a conventional ICE vehicle, or better performance. For instance, many HEVs reduce idle emissions by shutting down the engine during idling and restarting it when needed (start-stop system). The electric powertrain is used to deliver a high torques during the vehicle start-up phase, thereby reducing fuel consumption. The batteries are not rechargeable from the mains, but only by the regenerative braking system and from the ICE equipped with a suitable generator. A hybrid-electric produces less tailpipe emissions than a comparably sized gasoline car, since the hybrid gasoline engine is usually smaller than a comparably sized, pure gasoline-powered vehicle and if not used to directly drive the car, can be geared to run at maximum efficiency, and this further improves fuel economy.

6.3.2 Plug-in hybrid electric vehicle The PHEV type is based on the same concept of HEV, whereas the battery of a normal hybrid vehicle, cannot be recharged from the outside. In the case of a PHEV, the vehicle is also equipped with a socket that allows the recharge of the battery from an external source. This allows an increase in the driving range of the vehicle and a decrease in the cost of charge since the electric energy produced by the main network is cheaper than the electric energy produced on board. It runs on electricity until its battery pack is depleted, ranging from 15 kilometers to over 65 [6]. However, depending on the type of connection, it is possible to recognize three different arrangements: Series PHEV, Parallel PHEV, and Series-Parallel PHEV. In this example the vehicle has one electric traction motor. The energy is provided by the generator linked to the ICE or by the storage system. In the parallel PHEV, it is possible to have three different arrangements: G

G

G

In Case A, the mechanical transmission receives power both from the ICE and the electric motor. In Case B, ICE and electric motor are mounted on the same shaft. This configuration allows recharge of the storage system when the car is stopped, since the motor can act also as generator. In Case C, the two motors are decoupled. The rear wheel-set is driven by an ICE while the front wheel-set is driven by an electric motor fueled by a storage system. This configuration does not allow the recharge of the battery with the ICE as in the case of B.

Finally, it is also possible to have a combination of series and parallel configurations. In this case both electric motor and ICE are linked to the same shaft, but the ICE can be decoupled from the shaft through a clutch allowing series or parallel configurations depending on the requirement. When decoupled, the ICE can feed the electric motor through a generator and AC/DC-DC/DC stages. Or it can also recharge the battery when the vehicle is at standstill. In this case, just one system supplies the electric motor at a certain instance. In parallel configurations, the

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Figure 6.2 Schematic of a charging load for a generic EV.

traction is guaranteed both from mechanical power provided by the ICE and the electric motor fueled by the storage system.

6.3.3 Extended range electric vehicle ER-EV can be considered a kind of hybrid vehicle; but, not completely so. In fact, the traction of the vehicle, in any case, relies on the electric motor. The difference from a hybrid vehicle lies in the fact that an ER-EV, is equipped with a small ICE that allows the recharge of the battery to extend the driving range. In some applications, it is also possible to have a fuel cell generator. The drawback is an increase of the weight of the vehicle.

6.3.4 Battery electric vehicle BEV is an EV powered integrally from the battery pack, often coupled with a regenerative braking system. The battery is recharged by connecting the vehicle to the electric grid. BEVs do not have any tailpipe emissions and they have highest degree of hybridization.

6.3.5 Fuel cell electric vehicle In the case of FCEV, the electric energy is produced on board by a fuel cell generator, eventually coupled with batteries to exploit the regenerative braking and assists the vehicle during the start-up phase. However, the FC-EVs presents some difficulties that need to be resolved. These include: lack of a dedicated infrastructure, high costs of the overall system and a relatively low tank-to-wheel efficiency (  40%).

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Figure 6.3 Example of peak-shaving in the public charging.

6.4

Electric vehicle supply equipment

In discussing EVs, apart from the vehicle itself, it is important to address the “fixed” infrastructure part, represented by the EVSE. It is clear that the batteries inside the EVs which are necessary for storing energy for propulsion need a system for recharge. These recharge systems and their critical role in the distribution network must not be underestimated. Taking into account the ever-increasing levels of both power and storage capacities of the various models proposed by the manufacturers, an EV can be assimilated, from an energy point of view, as a full-fledged small apartment “on wheels” [7]. It therefore appears evident that the installation of the various EVSEs (whether in a public or private environment), deserve special attention in the design stage in order to ensure optimal coordination with the distribution network as it directly impacts the power demand [8]. As illustration, Figs. 6.2 and 6.3 show, respectively, a generic power curve of a battery in charge and the impact on the daily load demand in a public parking lot with an uncontrolled charge of EVs at different penetration levels [9]. In the remaining part of this chapter, we will analyze the various recharge methods foreseen by the standards and the various types of connections that are currently available in the market of EVSEs.

6.5

Electric vehicle charging modes

Let us now analyze the various modes of recharging foreseen by the standards. The European standard IEC 62196 [10] sets four different charging modes based on different power charging levels, protection systems and connector types (Fig. 6.4):

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Figure 6.4 Presentation of the charging modes. G

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G

G

Charging mode 1 (home charging without PWM (pulse width modulation) is the simplest form of connection: The EV is directly connected to the AC supply network (single-phase or three-phase) without any control contacts, using standardized socket outlets with a maximum current allowed of 16 A and not exceeding 230 V (single-phase) or 400 V (three-phase). Charging mode 2 (home/company charging with PWM): The EV is connected to the AC supply network (single-phase or three-phase) not exceeding 32 A and not exceeding 230 V (singlephase) or 400 V (three-phase) using standard socket (max. 22 kW). The cable is equipped with a Control Box (PWM safety system) that ensures the safety of operations during recharging. Charging mode 3 (public spaces charging): This type of connection is mandatory for public places. The EV is connected to the AC supply network using EVSE. Therefore, the control pilot has also to control the safety equipment of the EVSE, which is permanently connected to the AC supply. The communication cable between the vehicle electronics and the charging station enables integration with smart grids. Charging mode 4 (FAST DC connection): The EV is connected to the AC supply network using an off-board charger where the control pilot is responsible also for safety of the equipment permanently connected to the AC supply. In mode 4 the charger is no longer in the vehicle but in the charging station.

6.5.1 EV connector type In order to recharge the batteries, present on board the EVs, a suitable connection must be made between the vehicle and the supply network. The fundamental parameters to take into account that can drastically affect the recharging time are: G

G

G

G

The rated battery capacity installed on board (typically 20 80 kWh). The initial state of charge of the EV (SOC). Rated charging power of the EVSE. The actual power that can be withdrawn from the network.

Depending on the preceding factors, the charging time can range from few minutes to 10 hours or more. Table 6.1 shows typical charging times for a generic medium-sized electric car. Concerning the modes of charging and the connectors currently available, it often happens when a new technology begins to develop, that there are no standards or predefined protocols, and there is always an initial phase in which different

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Table 6.1 Typical charging times for a generic medium-sized electric car. Recharge power (kW) AC AC AC DC

Slow Fast Fast Fast

Autonomy reinstate in

3.3 22 43 50 kW

1 hour

15 min

13 15 km 90 100 km Complete Complete

3 5 km 25 30 km 50 60 km 60 70 km

Times required to reinstate 10 km 40 45 min 6 7 min 3 4 min 2 3 min

Figure 6.5 Type of connection for the recharge.

products that perform the same function take place, often independently. The same applied to the EV’s charging systems that have experienced the development of a varied amount of connectors and protocols promoted by the various companies that have worked in the development of this new technology. But once the technology is developed, the main objective must be to achieve the interoperability of the charging systems without neglecting performance, safety and economy. At present, the European standard, which contains the requirements for charging EVs, is the CEI EN 61851-1: 2012-05 Standard: “Conductive Charging System for Electric Vehicles - Part 1: General Requirements” [10]. Basically, as Fig. 6.5 shows, there may be three different connection configurations: G

G

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Configuration A: the EV is connected to the charging point by means of a power cord and a plug permanently attached to the vehicle itself. Configuration B: the EV is connected to the charging point by means of a removable power cord provided with the relative plug. Configuration C: the EV is connected to the charging point by means of a power cord and a plug permanently attached to the supply equipment.

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Beyond the type of connection, regarding the connectors, nowadays in the EV market it is possible to find different models and brands with different configurations and technical characteristics. Below, some types of connectors are described: G

G

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Schuko plug is the common name for a system of plug and socket for alternating current, defined as CEE 7/4, which is available in many European countries. It has a ground connection, two terminals and supports current of up to 16 Amps, so it is only compatible with slow recharges. It is common in some motorcycles and electric bicycles, and also in some electric cars such as the Twizy. Type 1 (SAE J1772), also known as “J plug”, is a North American standard for electrical connectors for EVs. It is characterized by five pin-and-sleeve: two active conductors (L1N), one for the earth grounding (PE) two for the signaling (PP and CP). The type 1 connector can also have an additional configuration that implements the Fast Recharge trough a DC connection allowing the recharge of the vehicle up to 200 A (90 kW) [11]. The power pins do not carry energy until the proximity and control pins are inserted. The latter are structured in such a way as to be the first to slip off when there is a threatened interruption of the charging process. The physical button of the connector instead acts on the proximity pin that commands the vehicle’s on-board charger to open up. Once the vehicle charger is open, the control pin causes the power relay in the charging station to open, thereby cutting all current flow to the J1772 plug. This prevents any arcing on the power pins, thus prolonging their lifespan [12]. Type 2 (Mennekes), also known under the name of Mennekes (from the name of the company specialized in industrial plugs and connectors) proposed this configuration in 2009. Type 2 connector is a connector widely used especially in Europe. Generally, the cars that employ/have this type of connector present male vehicle inlet, whilst charging stations are fitted with a female outlet, either directly on the outside of the charging station, or via a flexible cable with permanently attached connector on the end. As Fig. 1.21 shows the type 2 connector presents seven different pins: four pins for the power supply (L1, L2, L3, N), one for earth grounding (PE) and two for signaling (PP, CP). Technically, this type of plug can support a maximum voltage of 480 V and absorb a maximum current of 300 A for a theoretical charging power up to 144 kW [13]. CHAdeMO is the trade name of a fast-charging method proposed in 2010 by an association with the same name. The name comes from a Japanese phrase “Ocha demo ikaga desuka” that literally means, “How about a cup of tea?” in order to highlight the fastcharging nature of this connection. Most EVs have an on-board charger that uses an AC/ DC rectifier in order to recharge the EV’s battery pack but, since CHAdeMO works at very high power (up to in 400 kW in some tests experiments [14]) for thermal issues limit, the charger is installed directly in the EVSE, dropping the CHAdeMO charging protocol in mode 4 recharge.

6.6

Summary

By 2050, the percentage of European citizens residing in urban areas will reach 82%. Migration from cities to suburbs is leading to settlement structures that involve long distances to travel. This phenomenon of urban expansion goes hand in hand with an increase in the number of cars owned and commuter traffic. Added to this is the European objective of reducing CO2 emissions by 60%, compared to

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1990 values, by 2050. To meet these challenges, it will be necessary to increase mobility and reduce traffic, accidents and air pollution through local mobility policies. Digitization, urbanization, globalization, and demographic changes are changing the conditions of our society and therefore it is necessary to modify the current paradigms of transport policy in order to face the challenges of the future. The issue of urban mobility is crucial not only because it is directly and immediately connected to the quality of life of citizens but also because it is the component most responsible for polluting emissions. Acting on the improvement of energy efficiency, emphasizing the importance of promoting electromobility and electric public transport systems, promoting the spread of new forms of mobility are crucial points. Another central aspect is the behavior of transport users, increasingly active and protagonist, crucial for the development of a more sustainable system. In order to reverse the trend of the current modal split, it becomes necessary to provide users (especially young people) with the motivation and the possibility of using safer and more sustainable means of transport (walking, cycling, using the bike sharing and rental, public transport, use of car sharing, or car pooling)—which, should be used within a secure infrastructure. To make this practicable, information for travel planning and real-time information must be made available in order to facilitate the intermodal use of different modes of transport through intelligent transport systems. Finally, let’s move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

6.7

Chapter review questions/exercises

6.7.1 True/false 1. True or false? It is perhaps premature to talk about an “electrical revolution,” even though the probability of a mass changeover to this alternative energy source is becoming more realistic than ever. 2. True or false? In general, an EV is that vehicle that utilizes some form of energy to feed its electric motor for propulsion. 3. True or false? HEVs exploit, simultaneously or separately, the combination of the internal combustion engine (ICE) and the electric motor. 4. True or false? The PHEV type is based on the same concept of HEV, whereas the battery of a normal hybrid vehicle can be recharged from the outside. 5. True or false? BEV is hybrid vehicle powered integrally from the battery pack, often coupled with a regenerative braking system.

6.7.2 Multiple choice 1. The electric energy is produced on board by a fuel cell generator, eventually coupled with batteries to exploit the regenerative braking and assists the vehicle during the start-up phase, in the case of:

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a. BEV b. FCEV c. ER-EV d. PHEV e. HEV It appears evident that the installation of the various EVSEs (whether in a public or private environment), deserve special attention in the design stage, in order to ensure optimal coordination with the distribution network, as it directly impacts the: a. Generic power curve b. Daily load demand c. Uncontrolled charge d. Penetration levels e. Power demand The simplest form of connection is: a. Charging mode 2 b. Charging mode 1 c. Charging mode 3 d. Charging mode 4 e. Charging mode 5 In order to recharge the batteries, present on board the EVs, a suitable connection must be made between the vehicle and the: a. Wireless network b. Mobile network c. Supply network d. Private network e. All of the above By 2050, the percentage of European citizens residing in urban areas will reach: a. 82% b. 72% c. 68% d. 47% e. 100%

6.7.3 Exercise 6.7.3.1 Problem Please discuss: Even though mobility is a vital part of a thriving urban economy, why is it though, that mobility solutions that do not take into account economic, environmental, and societal impacts, can also be detrimental to urban life?

6.7.4 Hands-on projects 6.7.4.1 Project Do research: With regard to urban mobility system components: What are the conditions that can facilitate growth and make sure that such growth is sustainable?

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6.7.5 Case projects 6.7.5.1 Problem How would you go about developing a knowledge base to help authorities in implementing policies to foster more sustainable systems for urban transport and mobility?

6.7.6 Optional team case project 6.7.6.1 Problem Provide an analysis of the demand for urban mobility and its distribution between the different transport modes through the accessibility and comfort that is provided by urban public transport.

References [1] La Nature. Revue des Sciences, 1898. [2] Encyclopædia Britannica, Oil Crisis. Retrieved December 16, 2019. Available from: ,https://www.britannica.com/topic/oil-crisis/media/1/2002436/162563. [3] E. Fortin, Identifying and Reducing the Negative Impacts of Transportation, Laboratoire Ville Transport Mobilite´, E´cole des Ponts ParisTech, p. 57. [4] IEA/OECD, Global EV Outlook 2018: Towards Cross-Modal Electrification, International Energy Agency, Retrieved December 16, 2019. Available from: ,https:// webstore.iea.org/download/direct/1045?filename 5 global_ev_outlook_2018.pdf. [5] Dmove, Il costruttore che vende piu` auto elettriche in Germania e`. . . DHL. (2018, August 21). Retrieved 16 December 2019. Available from: ,https://www.dmove.it/ news/ilcostruttore-che-vende-piu-auto-elettriche-in-germania-e-dhl. [6] UCSUSA, How Do Plug-in Hybrid Electric Cars Work? Last revised date: November 12, 2015, Retrieved December 16, 2019. Available from: ,https://www.leadingthecharge.org.nz/nz_electric_car_guide. [7] V. Boutueil, Electric Mobility: Actual Changes Brought On by Electric Vehicles in Terms of Mobility Systems, Laboratoire Ville Transport Mobilite´, E´cole des Ponts ParisTech, pp. 1 4. [8] G.A. Ramos and M.A. Rios (2012). Connection Schemes for Electric Vehicle Supply Equipment Retrieved. pp. 1 2. Retrieved December 16, 2019. Available from ,https://ieeexplore.ieee.org/document/6955230. [9] K. Qian, C. Zhou, et al., Modeling of load demand due to EV battery charging in distribution systems, IEEE Trans. Power Syst. 26 (2011) 4 9. [10] IEC Norme. Normativa per la ricarica dei veicoli elettrici stradali. Retrieved December 16, 2019. Available from: ,https://www.ceinorme.it/it/news-en/comunicati-stampa/ 163-normativa-per-la-ricarica-dei-veicoli-elettrici-stradali.html. [11] N. Watson & A. Miller. (2016). Rapid EV Chargers: Implementation of a Charger. Paper presented at EEA Conference & Exhibition, Wellington, New Zealand. Retrieved from: ,https://www.researchgate.net/publication/319162700_Rapid_EV_Chargers_ Implementation_of_a_Charger.

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[12] M. Raya, J.-P. Hubaux, Securing vehicular ad hoc networks, J. Comp. Security 15 (2007) 39 68. [13] S. Zeadally, R. Hunt, Y.-S. Chen, A. Irwin, A. Hassan, Vehicular ad hoc networks (VANETS): status, results, and challenges, Telecommun. Syst. 50 (4) (2012) 217 241. [14] Vaielettrico, CHAdeMO lancia la ricarica a 400 kW: il pieno in 5 minuti (2018, June 28). Retrieved December 16, 2019. Available from: ,https://www.vaielettrico.it/chademolancia-la-ricarica-a-400-kw-il-pieno-in-5-minuti/.

Urbanization and smart cities

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Ritu Mohanty1 and Bipin Pradeep Kumar2 1 Padora Urban Design, Mumbai, India, 2Gaia Smart Cities Solutions Pvt Ltd, Mumbai, India

7.1

Introduction

By 2030, about 60% of the world’s population is expected to live in urban areas. According to a UN study, also by 2030, the world is projected to have over 10 million people inhabiting approximately 43 megacities each, and most of them in developing regions. The rate of urbanization will be the fastest in low-income and lower-middleincome countries; and hence urban growth has to be managed in a sustainable manner. Demand for key services will increase exponentially and maintaining the livability index of cities will be an enormous developmental challenge. Smart-city initiatives as a strategy to tackle the several challenges that the growth of urban population constitutes need to be comprehensive and especially so if we are to achieve the global goals of sustainable development. With shifting global demographics and the rise of high-growth economies, how will the public and private sector look for new approaches and models to meet the challenges of the UN’s sustainable development goals (SDGs) and address climate change? As commonly known, the SDGs are a list of 17 goals, which, in the context of smart cities include the elimination of poverty, clean water and sanitation, renewable energy, good jobs and economic growth, innovation and infrastructure, sustainable cities and communities, and climate change—for countries to achieve by 2030. Individual countries and its steering committee would recommend measures to adopt/include SDGs into ongoing national policies, programs, and strategic action plans to address the developmental challenges. International Telecommunication Union and United Nations Economic Commission for Europe along with other UN (United Nations) bodies created U4SSC (United for Smart Sustainable Cities). U4SSC has already released key performance indicators for the smart sustainable cities to establish the criteria to evaluate information and communication technologies (ICT’s) contributions in making cities smarter and more sustainable [1].

7.2

The future of urbanization and need for the smart city

Smart-city interventions have emerged in an attempt to address issues of urbanization such as economic development and creation of jobs, climate change, resource Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00007-3 © 2021 Elsevier Inc. All rights reserved.

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efficiency, equity, and citizen engagement. How can smart cities simultaneously relate to the livability index and UN SDGs as well as comprehensive development? For example, as a policy framework in India, smart cities relate not only to the SDG goals but also with the four pillars (institutional, social, economic, and physical) of comprehensive development. Smart cities bring together infrastructure and technology to enhance the quality of life of citizens and improve their interactions with the urban environment. By integrating, regulating, optimizing, and controlling the city’s impact on communities and the natural environment, smart cities also unlock the potential for economic growth. However how can data from areas relating to everyday lifestyle such as public transport, air quality meters, and energy production be integrated and effectively used? The need for smart cities has emanated from focusing on improving sustainability, efficiency, reliability, safety, and quality of services in relation to public operations, amenities, and assets of our cities. A strong thrust on smart-city applications has the potential to facilitate the ultimate goal of better infrastructure facilities and improving quality of life in our cities. However as Dr. Rick Searle points out, “before investing millions or even billions, cities need to have an idea of what kind of future they want to have and not be swayed by the latest technological trends.” Fig. 7.1 depicts the kind of ecosystem a smart city should have for proper implementation and functioning. Citymanagement methods, by integrating ICT into city systems require a large number of considerations like leveraging existing physical assets, engaging local data ecosystems, applying clear data-management strategies, transparency, security, and privacy concerns.

7.2.1 Challenges with conventional planning approaches As detailed further in this chapter, the current urban design and planning mechanisms (especially in developing regions) have not proven to be effective in incorporating all the urban complexities of their cities. This has arisen due to insufficient and not so accurate data collection methods, as well as little connection between socio-economic and spatial processes, and less dynamic nature of master plans. Our present-day cities represent a paradigm shift on the notions of infrastructure that is required in our cities to make them more humane. While undoubtedly our cities have experienced rapid transformations over the last few decades, driven by large-scale infrastructural projects, the benefits of these seem to have bypassed the majority of the citizenry (in the context of developing economies) or an underrepresented group of citizens and caused severe environmental damage. Whether it is a search to create affordable housing, build accessible infrastructure, negotiate the public realm, revive environmental systems, or enable participatory process of planning and design, the challenge(s) addressed by the smart cities must be relevant to our contemporary city.

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Figure 7.1 The kind of smart city. Source: RJB:CPL.

7.3

IoT- and ICT-led initiatives as enablers of smart cities

As the world becomes progressively more interconnected and technology dependent, a new upsurge of smart applications is transforming how we approach day-to-day activities. The internet of things (IoT), created as part of the smart-technology movement, facilitates a wide range of technological innovations that could help improve everyday services such as public transport and pedestrian security, give accurate traffic reports, and/or provide real-time energy consumption data. By rendering more technology capable of communicating across platforms, IoT creates more data that can help improve various aspects of daily life. Cities can identify both opportunities and challenges in real time, reducing costs by identifying issues prior to their emergence and allocating resources more accurately to maximize impact. Efficiency and flexibility can be achieved through the use of sensors, data and advanced computing to help speed up the flow of information, reduce time, and improve the value of various city-management services—traffic management, resource management, waste management, etc. while providing environment-friendly infrastructure. Applications of ICT in urban planning, design, and development, in general, are not new. However the new thrust on ICT in “smart-city” developments places more

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emphasis on IoT and ICT technologies. Smart cities try to focus on ‘smarter use of resources, smarter ways of collecting data, and smarter ways to make decisions’ [2]. From the perspective of the need of cities to improve efficiency, productivity, speed, and quality of service delivery or introduce new types of interconnected services, the use of ICT technologies become imperative.

7.3.1 Efficiency and flexibility by adopting technology Here are a few global cases of multiple smart cities and/or smart-city initiatives across the world focusing on components of efficiency and flexibility [3]: G

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The value of IoT-based infrastructure in Amsterdam, where traffic flow, energy usage, and public safety are monitored and adjusted based on real-time data, has been tested by the Netherlands. Using technology, UK’s smart campus idea in Manchester reinforces the initiatives of student engagement. There is collaboration between the Andorran government and the MIT Media Lab for developing a living lab to test the use of data for addressing urban design, tourism, and innovation for the country of Andorra. The city of Barcelona has adopted smart technologies by implementing a network of fiber optics throughout the city, providing free high-speed Wi-Fi that supports the IoT and in this way invested in enhancing their public spaces. Smart-city areas in Barcelona include public and social services, environment, mobility, job creation through companies and businesses, research and innovation, communications, infrastructure, tourism, and citizen cooperation. By integrating smart water, lighting, and parking management, Barcelona has saved millions of city funds and created several new jobs in the smart-technology sector. Meanwhile, in the United States, major cities like Boston and Baltimore have deployed smart bins that relay how full they are and determine the most efficient pick-up route for sanitation workers. Singapore city’s water management system is among the world’s most advanced, and the government is testing a new desalination technology for seawater that would be 50% more energy efficient than any current method. In addition, in Singapore, superfast, nextgeneration broadband network already reaches 95% of homes and businesses. In Japan, Yokohama Smart City has embraced smart homes, electric vehicles, energy management systems by involving members of public and commercial customers, CO2 emission reduction, and photovoltaic systems. In Abu Dhabi, the city of Masdar relies on solar energy and other renewable energy sources, and additionally is designed to be a hub for clean technology companies.

In relation to benchmarking city efficiency and effectiveness KPMG International released a report in 2017 to lay a foundation for future city service benchmarking, and also to create a platform for cities to share new ideas, innovations, and approaches for improving city services. Working in partnership with 35 cities around the world (representing almost all geographic regions and sizes), KPMG International worked on creating efficiency and effectiveness measures across 12 distinct city service “groups”—key areas such as road access, transit, drinking water supply, and garbage collection. They then mapped their participants’

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data in a way that allowed them to—for the first time—reliably compare their relative performance across various city service areas. What they established was that the leading cities were not those that had implemented a specific technology or platform, but rather those that viewed technology enablement as part of the wider effort to transform city service delivery, efficiency, and effectiveness. The report concluded that citizens will continue to demand more effective and efficient city services, and governments will need to make difficult and long-lasting decisions about where to invest tax capital [4]. Considering that new approaches and new innovations will continue to disrupt the status quo, being a smarter city in this environment is not about technology alone. It is about understanding, managing, and influencing our city’s efficiency and effectiveness in a way that delivers smarter services and greater value. However beneficial in improving city services and cross learning for city administrators across the globe, benchmarking city efficiency and effectiveness is a tremendously arduous and time-consuming exercise. In part, this is because no two cities measure the exact same things in the exact same way. However it is also because each city faces a very different social, political, economic, and environmental challenge. In addition, hence, their unique identity and realities have a direct impact on their specific costs and capabilities. Technology can make city systems resilient, enable remote measurement and monitoring of city services, allow cross-functional city system interaction, and create new closed loops to improve the system and monetize services. These solutions could be sector specific—for example, transportation, traffic and roads, waste management, energy, water, environment, e-governance, ad citizen engagement. These solutions could be function specific—such as distribution, marketing, billing, and payments for a specific sector. In each sector, function and solution is underpinned by ICT design to collect and analyze information, control processes, and enable faster, better decision making. While the objectives of “smart cities” have been proposed as the future of urbanism, the question remains: How do we relate this new technology for the ultimately “efficient” yet contextually relevant and humane society?

7.4

Smart cities, urban planning, and policy

It is imperative that smart cities address not only the technologies that reinforce smart infrastructure, but also emphasize the comprehensive master planning of cities; best practices that minimize a city’s carbon footprint by integrating water, waste management, energy efficiency, etc., into architectural design and forging partnerships between the multiple stakeholders around the future of our built environment. City administrators must ensure that the interests of all the stakeholders are addressed through planned initiatives; especially the financial incentives to build, operate, and manage the solution in the longer term, are aligned for a sustainable outcome.

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In the case of ICT/IoT for smart cities, the stakeholders would specifically include [5]: 1. Government 2. Service providers (investors, industry, and service providers) 3. Citizens

A simple relationship between the preceding three stakeholders is shown in Fig. 7.2. Smart cities embrace a new paradigm where the government moves away from unilateral management, allowing for greater collaboration between agencies, municipalities, businesses, citizens, and other stakeholders to better face current/future urban challenges and opportunities. To a large extent, this is possible due to improved data collection and digital connectivity. There are multiple terms for public participation in urban design and planning, such as collaborative, communicative, deliberative, and community planning. Whatever the approach, a broad understanding of participatory processes need to be encouraged at the outset—one that is not limited to information gathering or dissemination regarding the government’s work, but also includes a dialogue with public authorities, decision making, and assessment of the final outcomes.

Figure 7.2 Stakeholders of a city. Source: Gaia.

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As planners we ought to understand spatial justice and develop our understanding toward community self-representations and cultural identity. We ought to influence the ability to orient outcomes toward redistribution of resources and opportunity, and to understand deliberation as equal respect for the perspectives of all who may be affected by collective decisions. Influencing public decision making in the public interest promotes spatial justice. In the context of smart cities we can attempt to develop a communication and information technology platform to enable participation in planning. While this process may not be new to developed regions there is certainly a lack of an executional framework for implementing the process of communicative design at the city scale in most developing regions [6].

7.4.1 Defining smart-city goals: guiding policy with urban planning and technology Evidently, every city, regardless of its location in the world, is different and will face a unique range of urbanization challenges. Defining smart-city goals and objectives begins with a deep understanding of citizen and business needs and a community’s unique attributes—its demographics, infrastructure, and resources. Engagement with all stakeholders is the critical initial point for jump-starting smart-city programs. Cities will need to harness real-time urban intelligence to power their smart mobility, energy, utilities, and city commerce programs, connecting all their smart urban applications and scaling these with ease. ICT’s effect on urban design and urban planning is expected to revolutionize and change the way all businesses, governments, and citizens interact with the physical realm. This level of disruption will have a significant impact on the world in improving the quality of life of every individual. The impact of ICT applications on urban design concepts like placemaking, mixed-use development, form-based code, transit-oriented development, etc., need much more closer examination and studies. The discourse that is available in the public domain on smart cities, as well as its applications, are largely led by technology specialists and administrators, with secondary inputs from architects, urban designers, and planners. Many applications of smart-city technologies rely heavily on ICT. Architects, urban designers, and planners believe that focus is lacking on understanding the values of local context and/or the physical built-form of the city, and/or its socio-cultural and political environment. In the current debate on smart cities the kind of socio-spatial consequences the smart-city engenders has been neglected. It is imperative to address the large gap in the current mainstream discourse between the physical manifestation of cities of the future and a well-defined urban vision for the spatial and typological configurations of the smart city. Guaranteed access to physical infrastructure and social services for all citizens through integrated policies for managing urban growth is fundamental. Where there is a gap in policy, strategy, and planning, as well as an ambiguous overlap of multiple planning authorities, ICT can enable integrated planning systems to work across administrative bodies. Having access to data should motivate planning authorities

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to improve the planning and administration of cities, with the aim to maximize economic opportunities and minimize environmental damage, toward a sustainable development. Megacities in the rapidly urbanizing economies, more often than not, develop an excess of urban policies and plans nurtured by various state and local agencies. These are often overlapping or conflicting and as a result do not produce the desired results. Prospective smart cities tend to add a new layer of strategy and devise extra institutional instrument into this already complex environment. The idea of smart cities cannot be successful as another standalone initiative and one must explore how integration of plans and unification of smart-city visions with primary city development goals can better support effective urban transformation and local innovation. Developing a smart-city policy that converges with other key city development goals is imperative. The smart-city policy must align with the overall urban development framework of the city that focuses on a more process-oriented path than a simple project-oriented path, guiding all related schemes to achieve sustainable urban development. For example, the NITI Aayog is a policy think tank of the government of India (GoI), established with the aim to achieve SDGs with cooperative federalism by fostering the involvement of state governments of India in the economic policy-making process using a bottom-up approach. It highlights the need for a holistic approach to urban development, requiring an integration of physical, institutional, social, and economic infrastructure with people at its center. One of its smart-city-related policy documents—a report, “Reconceptualizing Smart Cities: A Reference Framework for India” by Center for Study of Science, Technology and Policy (CSTEP) is a step toward fusing various aspects related to smart cities as a proposal framework, for the Smart City Mission in India initiated by the GoI in 2014 [7]. The framework aims to develop future pathways for smart cities development in India, by laying emphasis on the process of city development that leads to sustainable outcomes. The report is expected to guide policy makers, urban practitioners, and implementing agencies in making critical decisions and fine tuning urban strategy for the entire country; and envisioned to make Indian cities smart. What has remained missing from the policy document, however, in the smart cities discourse is a technically sound, integrated system, and framework based on which the city operates. Another serious concern is that equity fails to be mentioned anywhere. The National Urban Policy Framework by the Ministry of Housing and Urban Affairs in India, published in 2018 in collaboration with the NITI Aayog, is an additional reference of a supporting urban policy document as an integrated approach toward the future of urban planning in India [8]. It includes equity and a cohesive approach toward planning and urban management; thereby addressing the gaps in the CSTEP report. Another effort in this direction and reference of an urban policy document is the “Report to the President: Technology & the Future of Cities by Executive of Office of the President” by the President’s Council of Advisors on Science and Technology, USA, 2016 [9]. Initiating smart governance where policy-making is more flexible, practical, and closer to citizens—enabling experimentation, open dialogue, and fast-paced adaption, in which guidelines are not made merely with a top-down approach but also a

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bottom-up one, and thereby encouraging participatory processes of planning and design. As cities of the future define what urban life will mean for those who live and work in their neighborhoods/municipalities, they will need to reconcile conflicting economic, environmental, and social goals. In addition, while facilitating digital infrastructure is important, it is the ability to truly connect with citizens that will support an open society and spur ideas, entrepreneurship, innovation, and growth.

7.5

Challenges and opportunities of smart cities

The one-size-fits-all approach is not appropriate for the smart city. Each city has to formulate its own concept, vision, mission, and plan for a smart city that is appropriate to its local context, resources, and levels of ambition. Based on conversations with stakeholders and multilayered field studies of communities a more nuanced approach may be adopted to reimagine the smart-city project. An in-depth research of the context, culture, diversity, and local attributes (and values) of the city need to better inform urban policy and practice; and thereby shape the approach for the smart city. The book “Smart City in India: Urban Laboratory, Paradigm or Trajectory?” by the authors Dr. Binti Singh and Prof. Manoj Parmar, published recently, is a critical reflection on key opportunities in Indian cities. However, it is extremely relevant to smart cities being developed world over based on tenets of innovation, sustainability, and inclusiveness, as the major drivers for cities. Despite the seemingly robust policy framework of the Smart City Mission in India as mentioned previously, there are certain restraints and scope for improvement. This book assesses the transformative possibilities and limitations of the program. It examines the 10 core infrastructural elements that make up a city, including water, electricity, waste, mobility, housing, environment, health, and education, and lays down the basic tenets of urban policy in India. Through empirical cases, the volume underlines the need to recognize transitional spaces and the plans to make the “smart city” an inclusive one. The authors also look at maintaining a link between the older heritage of a city and the emerging urban space. They examine the spatial relationships emerging from the insertion of new digital infrastructures into existing urban realities, powered by large-scale government spending and orchestrated to increase further private investment, and aggravate existing social problems. The authors explain not only the challenges facing India, but facing cities worldwide under the new regimes of neoliberal smartness [10]. New technologies hold great promise for more effective urban solutions. From smart grids and district energy solutions, or real-time traffic management, to waste management and water systems, smart technologies will enable our future cities to operate more effectively [11]. They could also make them more inclusive and accessible for all. Can participatory processes be encouraged at the outset? Can the smart-city paradigm balance the top-down and bottom-up approaches? Why is communicative design not reaching its objective fully? Emphasizing technological

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aspects and economic development only creates greater social and spatial exclusion as it reduces the social considerations and leads to unsustainable cities from a social standpoint.

7.5.1 Need for an integrated approach There is a need for an integrated approach—a more holistic approach as opposed to a technocentric one [12]. We can identify two models of conceptualization of the smart city. On the one hand, there is the more technocentric approach, promoted by the ICT sector according to which, urban processes and services can be made more efficient and flexible in a connected city. The massive collection of data and its transformation into information through powerful analysis tools allows improving urban management. On the other hand, there is a holistic approach to the concept that associates it with a balance between social, economic, environmental, human, cultural, and technological factors. As more and more real smart-city projects are launched, the needs and interests of cities and citizens are becoming clearer, as well as the difficulties they face daily. The holistic conception of the smart city has risen in academia as a response to the challenges the cities currently face, such as climate change, economic development, efficiency in the use of resources, etc. Fig. 7.3 defines a model for smart-city ICT design from the outside-in and inside-out perspectives.

Figure 7.3 Outside-in and inside-out model.

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7.5.2 Outside-in approach Using the outside-in approach framework for smart cities ICT design, planners and city administrators would look at technology and nontechnology led factors that govern the cities ecosystem, as well as the smartness the city envisions for itself, based on its unique advantages. This includes: G

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Existing and legacy technology and data architecture of the city and its multiple functions Potential for collaboration across city entities to create common data and communication architectures to ensure seamless interoperability and efficiency Shifting and evolving needs of consumers, and prosumers—people who are both service providers as well as consumers—and the level of technology, real-time information, and management they require within the city services Evolving aspirations of citizens, and how they perceive themselves—for example, makers, innovators, etc. Strengths and weaknesses of available set of ICT suppliers and vendors New global and national trends in creating experiences for the citizen in delivering basic amenities, social services, livelihood and training opportunities, measuring service performance or impact, et al. Alternatives such as citizen or private sector or partnership-based service delivery models to augment the services provided by city authorities, for example, advertisers, security products companies, e-wallet firms, citizen action groups, etc. could come together to build a smart parking solution

7.5.3 Inside-out approach Cities are unique—not just in terms of geographical assets, environmental resources, commercial and economic strengths, culture, and heritage, but also in terms of the mindsets of its people and the kind of life they value. It is critical then to layer the outside-in approach with an inside-out approach to create the unique vision of the city and then translate it into ICT design, infrastructure, and urban design. This includes: G

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Unique culture, history, and heritage of the city and how that influences its vision and the emergent ICT strategy Existing strengths of a city including its environmental/ecological assets Unique skills and values of citizens

City administration the world over is concerned that private enterprise led technology is worsening the inequality in communities in direct contrast with the desire of cities to create more social inclusion [13]. However the long-term sustenance of optimal solutions deployment and operations will require city administrators to consider and approve new types of business models, and multiple revenue streams that allow private players and innovators to thrive in the ecosystem. To address a range of infrastructure, transit, utilities, and connectivity challenges, city administrators will need to harness data-driven intelligence to identify appropriate priorities and ensure overall livability for all residents.

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However that is not all. To counter the multiple social challenges arising from urbanization, they must ensure that data sources—which today mostly sit in silos across agencies and departments and commercial third-party providers—can be brought together seamlessly. Only then will they be able to ease citizen burden through the delivery of predictive services—getting the right services to the right population cohort, at the right time [14].

7.6

Conclusion

The potential to improve several aspects of public service systems as well as quality of life and reduce costs has driven the demand for smart cites. An effective response to this demand calls for integrated planning across all levels of government. Greater consideration needs to be given to demographic and land use trends to anticipate their impacts and minimize environmental damage. These trends should inform our investments in all infrastructure development related plans including water, energy, and transport as well as other city services. Clearly, every city is different and will face a unique range of urbanization challenges. Defining smart-city goals and objectives begins with a deep understanding of citizen and business needs and a community’s unique attributes—its demographics, infrastructure, and resources. Urban design and planning–especially in developing regions, needs to focus on dynamic, integrated, responsive, and transparent characteristics for its cities. In other words, urban design and planning needs to focus on the following characteristics: G

G

G

G

Dynamic with the use of ICT tools in data collection, analysis, and simulation. Responsive to its citizens with participatory tools, a– bottom-up planning approach and capacity building of civic authorities and users. Transparent with the use of real-time data in government institutions; as well as, transparent to its citizens with open data policies and strategies. Its systems integrated, using a common data architecture over a comprehensive planning platform.

Engaging citizens in the design and planning process of their own cities as well as redefining roles of the agencies for improved local governance are the prospects of ICT in participatory design process. Citizen centric viewpoint is essential to the eventual success of any smart-city project. Bringing in human-centered design and user experience feedback to ensure ease of usage is critical. Cities are constantly evolving for the better based on citizen feedback and consequent actions. How can we encourage increased levels of public participation in addition to democratizing planning and design of cities through open data and ICT? For interventions related to smart cities, there are four suggested critical and overarching principles of city planning: 1. 2. 3. 4.

Design solutions to impact urban life Design technology to improve city performance Design systems for mass use in local environments Design solutions that are built to last

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By applying urban design frameworks with design, systems, and futures thinking principles to the ecosystem of a city one can get smart-city services designed and delivered optimally, efficiently, and feasibly. It is essential to provide a framework for the city and urban local body leadership to ensure their plans are suited to their city and its unique challenges, constraints, and strengths, and at the same time leverage typical best-in-class design and technology principles. More mature societies and cities, in Japan as an example, have articulated that in an information society—termed Society 4.0, the cross-sectional sharing of knowledge and information was not enough, and cooperation was difficult [15]. The next step in their evolution, termed Society 5.0 is achieving a high degree of convergence between cyberspace (virtual space) and physical space (real space). Japan has taken the lead to realize Society 5.0, a super-smart society, ahead of the rest of the world. Society 5.0 is a response to a society where we can resolve various social challenges by incorporating the innovations of the fourth industrial revolution (e.g., IoT, big data, artificial intelligence, robot, and the sharing economy) into every industry and social life. By doing so the society of the future will be one in which new values and services are created continuously, making people’s lives more conformable and sustainable. It is a society centered on each and every citizen, where new value created through innovation will eliminate regional, age, gender, and language gaps and enable the provision of products and services finely tailored to diverse individual and latent needs. In this way, it will be possible to achieve a society that can promote economic development and find solutions to social problems. Design, systems, futures, and thinking—echo similar principles. Achieving Society 5.0 with these attributes would enable not just every city, but even individual countries as a whole to realize economic development while solving key social problems. It would also contribute in meeting the SDGs established by the United Nations [16]. Can we accelerate structural transformations by addressing inequalities and exclusion, transitioning to zero-carbon development and building more effective governance that can respond to megatrends such as globalization, urbanization, and technological and demographic changes? What kind of systemic changes will be necessary for the smart cities movement to be relevant in the context of urbanization and future of cities?

7.7

Summary

Smart-city technologies expand the scope of urban planning, specifically with respect to data collection and data analysis for improved urban interventions. All stakeholders including city administrators, city planners, urban designers, bureaucrats, industry leaders, and citizens can harness the full potential of technologies by employing its tools to understand and participate in the process of urbanization; and thereby increase the quality of life index of our cities. The visionary intelligence

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that some cities have shown through the initiatives of increasing efficiency and flexibility of their urban infrastructure, will vastly increase livability—by making urban services more sustainable. With an added dimension of citizen centric values and comprehensive policies, decision makers in other countries will be inspired to make sustainable choices for new and user-friendly urban infrastructure. The following recommendations have been discussed—firstly, we need to develop capacities and processes for using data within municipal environments at the local scale; secondly, we need to ensure that design and implementation uphold democratic values; thirdly, we need to prioritize innovative policy and program reforms above innovative technology for comprehensive planning of cities; and lastly, we need to implement technology to address social equity, environmental framework, and advance policy, rather than amending goals and values to align with the available technology [17]. The chapter also questions the notion of urban infrastructure always being associated with hard engineering solutions as against being soft approaches associated with harnessing natural processes that improve the overall experience of the public realm of our cities. We need to investigate more ways our technologies, settlements, and patterns of consumption can be made sustainable for our ecosystem. As an endnote, “smart cities” as an approach needs to be comprehensive, inclusive, integrated, and contextually relevant. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

7.8

Chapter review questions/exercises

7.8.1 True/false 1. True or false? Smart-city interventions have emerged in an attempt to address issues of urbanization such as economic development and creation of jobs, climate change, resource efficiency, equity, and citizen engagement. 2. True or false? The current urban design and planning mechanisms (especially in developing regions) have not proven to be effective in incorporating all the urban complexities of their cities. 3. True or false? By rendering less technology capable of communicating across platforms, IoT creates less data that can help improve various aspects of daily life. 4. True or false? Considering that old approaches and old innovations will continue to disrupt the status quo, being a smarter city in this environment is about technology alone. 5. True or false? The smart society is so intertwined with the concept of the smart city, that, it has been accepted as the future of the smart city; or, the next generation of the smartcity initiative by some scholars.

7.8.2 Multiple choice 1. It is imperative that smart cities address not only the technologies that reinforce smart infrastructure, but also emphasize the comprehensive master planning of cities; best practices that minimize a city’s carbon footprint by integrating water, waste management,

Urbanization and smart cities

2.

3.

4.

5.

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energy efficiency, etc. into architectural design and forging partnerships between the multiple stakeholders around the future of our: a. Government b. Service providers c. Citizens d. Built environment e. Stakeholders Evidently, every city, regardless of its location in the world, is different and will face a unique range of: a. Design challenges b. Urbanization challenges c. Planning challenges d. Disruptive challenges e. All of the above The one-size-fits-all approach is not appropriate for the: a. Economy b. Infrastructure systems c. Urban laboratory d. Smart city e. Paradigm There is a need for an: a. Holistic approach b. Technocentric approach c. Academic approach d. Integrated approach e. All of the above City administration the world over is concerned that private enterprise led technology is worsening the inequality in communities in direct contrast with the desire of cities to create more: a. E-government b. E-governance c. Social inclusion d. Distance services e. Smart economies

Start here Exercise Problem Do research: Are smart cities the answer to urbanization challenges? Hands-on projects Project Do research: What makes a city smart? Case projects Problem Develop a global smart cities project. Optional team case project Problem Develop an iterative approach for implementing urbanization and smart-city solutions.

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References [1] United 4 Smart Sustainable Cities, UNECE and ITU (2015), ,https://www.itu.int/en/ ITU-T/ssc/united/Pages/default.aspx. (Viewed on December 5, 2019). [2] Saunders & Baeck, Rethinking Cities from the Ground Up (2015) ,https://ofti.org/wpcontent/uploads/2015/06/rethinking_smart_cities_from_the_ground_up_2015.pdf., (Viewed on December 10, 2019). [3] J. Ellsmoor, Smart Cities: The Future of Urban Development (2019), Forbes, ,https:// www.forbes.com/sites/jamesellsmoor/2019/05/19/smart-cities-the-future-of-urbandevelopment/#327e8ac32f90. (Viewed on December 10, 2019). [4] A.S. Mitchell, A Smarter Route to Smart Cities, KPMG, ,https://home.kpmg/xx/en/home/ insights/2018/04/a-smarter-route-to-smart-cities.html. (Viewed on December 8, 2019). [5] Telecommunication Engineering Center, Ministry of Communications, Government of India (2019), Design and Planning Smart Cities with IoT/ICT, (TEC Report), ,http:// tec.gov.in/pdf/M2M/Design%20Planning%20Smart%20Cities%20with%20IoT%20ICT. pdf. (Viewed on December 12, 2019). [6] M. Parmar (Ed.), Reflections, KRVIA Publications Cell, Kamla Raheja Vidyanidhi Institute for Architecture and Environmental Studies, Mumbai, 2017. [7] Bhattachary, S., Rathi, S. (2015), Reconceptualising Smart Cities: A Reference Framework for India (CSTEP-Report-2015-03). [8] National Urban Policy Framework (2018), Ministry of Housing & Urban Affairs ,https://smartnet.niua.org/sites/default/files/resources/nupf_final.pdf. (Viewed on December 15, 2019). [9] “Report to the President, Technology and the Future of Cities” (2016), Executive Office of the President, President’s Council of Advisors on Science and Technology, ,https://www.whitehouse.gov/sites/whitehouse.gov/files/images/Blog/PCAST%20Cities %20Report%20_%20FINAL.pdf. (Viewed on December 15, 2019). [10] B. Singh, M. Parmar, Smart City in India: Urban Laboratory, Paradigm or Trajectory? Routledge, India, 2019. [11] A.S. Alisjahbana, Smart Cities Hold the Key to Sustainable Development (March 2019), ,https://www.unescap.org/op-ed/smart-cities-hold-key-sustainable-development. (Viewed on December 13, 2019). [12] M. Johannes, Smart City and Urbanization Challenges (2019), ,https://www.e-zigurat. com/blog/en/smart-cities-urbanization-challenges/. (Viewed on December 12, 2019). [13] K. O’Brien, “From Smart City to Future City: the 21st-Century Urbanization Challenge” (2018), ,https://www.digitalistmag.com/improving-lives/2018/01/26/fromsmart-city-to-future-city-21st-century-urbanization-challenge-05809136. (Viewed on December 14, 2019). [14] E. Brynjolfson, Andrew McAfee, and Michael Spense, Foreign Affairs, “New World Order: Labor, Capital and Ideas in the Power Law Economy” (2014), ,https://www. foreignaffairs.com/articles/united-states/2014-06-04/new-world-order.. [15] Cabinet Office, Government of Japan (2019) ,http://www8.cao.go.jp/cstp/english/society5_0/index.html. (Viewed on December 6, 2019). [16] ICTs for a Sustainable World #ICT4SDG, International Telecommunication Union, ,https://www.itu.int/en/sustainable-world/Pages/default.aspx. (Viewed on December 6, 2019). [17] B. Green, The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future, MIT Press., 2019.

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8

Cathryn Peoples Ulster University, Londonderry, United Kingdom

8.1

Introduction

The Internet of Things (IoT) market has grown rapidly since inception, with impressive forecasts for the following period routinely being made. A statement was released in August 2018 by Forbes with regard to IoT growth: “IoT Market Predicted to Double by 2021, Reaching $520B” [1]. By 2025, the International Telecommunication Union (ITU) predicts that the global market will reach $1567 billion [2]. Statista, in a figure close to that projected by the ITU, estimates the worldwide IoT market at $1612 billion by 2025 [3]. The International Data Corporation, on the other hand, predicts that global market revenue will increase much more significantly beyond this, reaching $11 trillion by 2025 [4]. To put these projections in context, the logistics industry is predicted to reach $15.5 trillion by 2023 [5], the agriculture industry is valued to reach approximately $23.14 billion by 2022 [6], and the construction industry is valued at $14 trillion by 2025 [7]. While the IoT is somewhat behind in value, it should be remembered that this environment was first considered only 20 years ago, in 1999 by Kevin Ashton. The IoT therefore, nonetheless, plays a significant role in our society, and indications are that the interest witnessed in the technology to date will persist. Any challenges with the current infrastructure will therefore be exacerbated. Now is a pertinent time to respond: Technology is integrated in a piecemeal approach throughout our lives, yet solutions that are a consolidation of applications do not exist. This is a major block to technology’s capability to manage our lives in a more thorough way. Challenges which exist in relation to the IoT in general, of which the smart city is an individual domain, include the range of domains to provision solutions for and therefore the diversity of technological solutions to manage, the volume of customer demand, the inaccessibility of services to everyone, the lack of interoperability across solutions, and trust levels in technology, to name a few. The smart city is a particularly challenging domain to consider within the IoT, given the range of areas it can cover, including smart homes, smart education, smart transportation, water, and electricity supplies, among others. Coupled with this is the challenge of continued urbanization, which puts increasing strain on the systems in place. It is important to recognize the volume of demand, which puts pressure on technology, given the associated implication on resource provision. Without resource provision sufficient to meet customer needs, the quality of service (QoS), and Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00008-5 © 2021 Elsevier Inc. All rights reserved.

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therefore ability to fulfill Service Level Agreements (SLAs), will become a more difficult problem to solve from the perspective of Service Providers. From the perspective of citizens, there may be a general dis-satisfaction with the service in the best-case scenario, or a risk to life in the worst. Another problem relates to the fact that there is extensive diversity in the way in which smart-city resources and services are provisioned. As a result, there is a general lack of interoperability between systems across cities. This has been allowed to be created through the unavailability of standardized technologies: each currently operates according to its own design, with little concern for the way in which other systems have been designed and implemented. As a consequence of this, there is a lack of consistency in the way in which services are provided: Each time a system is rolled out, it requires development in its entirety, with the negative impact of increasing the costs of deployment. Further complicating the provisioning of smart-city technologies are the number of competing perspectives from everyone involved—economic, social, political, and environmental [8]. Each drives a set of different requirements. To consider how this may be the case: To support continued growth of the economy through online opportunities, reports of criminal behavior in the online world may be hidden from society. This does not meet the full complement of societal needs and may indeed contribute to increased anxiety or levels of depression across a society. From a political perspective, the government may wish to demonstrate that their society is excelling in the online economy, bringing modern and state-of-the-art opportunities to its citizens through the smart city. The definition of “smart city” considered in this chapter is taken from the European Commission. Here, it is described that a smart city, “is a place where traditional networks and services are made more efficient with the use of digital and telecommunications technologies for the benefit of its inhabitants and businesses” [9]. This is a relatively common understanding of what the smart city involves; however, the variety of technologies within this domain can vary on a case-specific perspective. Within the context of this chapter, the term ‘infrastructure’ refers to the networked elements, which may be connected to one another. This can include a connection between the lamppost integrated with sensors, the electric car charging points, and the buses that drive past them all. Studies have been carried out to assess the extent to which cities can be considered to be smart. Juniper performs this evaluation using four metrics—mobility, healthcare, public safety, and productivity [10]. The aim of the study was to identify how much time the smart city rewards citizens with, in recognition of the fact that smart cities are intended to make citizens’ lives easier and more productive. Another study by Ofcom examines the extent to which citizens feel included in modern technology, and therefore how they use it [11]. Understanding the way in which the infrastructure is used has become a priority by some, so that it can be exploited for maximum reward. It should be noted that examination of the internet in any context results in localized findings when considered on an international basis. From the popularity of contactless payments [12] to the frequency of online purchases [13], there can be

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vast differences in the services and usage of smart-city technology. When considering the priority areas in future steps with regard to the smart-city infrastructure, the locality will be an influencing factor; this quality of localization is therefore also considered in this chapter. In this chapter, the activities required to support achievement of anticipated projections for the smart-city domain are discussed. The remainder of the chapter is organized as follows: In Section 8.2, background information is presented from the perspective of who is using IoT/smart-city technology, and what they are using it for. This is followed in Section 8.3 with a consideration of how the smart-city market will be generated, in the sense of the reasons why citizens will become interested in using the technologies. In Section 8.4, blocks to the market are discussed, with a view to understanding some of the aspects that need to be overcome to enter the next phase of the smart-city IoT. Potential approaches to expand the market are presented in Section 8.5, and approaches to green the market are evaluated in Section 8.6. Section 8.7 on enablers describes some aspects of what may be needed to support continued growth of the smart city. In Section 8.8, it is recognized that the technology is only angle, which supports a smart city; training and involving stakeholders is another important aspect, which is discussed in this section. The chapter concludes in Section 8.10.

8.2

Background information

Consideration of the smart-city infrastructure is important from the perspective of who is using it. This helps to draw conclusions on their objective for doing so, with a view to identifying their demands and therefore the weaknesses of the current infrastructure. This information may subsequently be used to understand the priority activities, which will support the needs and subsequent continued growth as we move into the future. Different studies have been carried out to contextualize who uses internet technology. A 2019 study on internet users by the Office of National Statistics describes that, “Since the survey began in 2011, adults aged 75 years and over have consistently been the lowest users of the internet” [14]. However, by 2019 it is recognized that, “Recent internet use by retired adults increased by 27 percentage points since 2011” [14]. It is also significant to learn that the proportion of disabled users who are now active internet users has reached its highest levels to date, at 78% of disabled adults [14]. The research also indicates that women aged between 65 and 74 years use the internet less than men (82% of women compared to 84% of men in 2018) [15]. The difference is even more significant in users who are aged over 75 years old, for which 54% of men in the United Kingdom were users compared with 41% of women [14]. The study from the Office of National Statistics also describes that 99% of citizens aged between 16 and 44 years old are recent users, that is, they have used the internet in the last three months [14]. Popular applications vary dependent on age:

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A significant proportion (79%) of the 16 24 age group, for example, watch ondemand or streamed content [16], compared to 69% of the 45 54s. This different in application use is also verified in a study by KPMG, for example, which identifies that, “Among the different age groups, Generation X (consumers born between 1966 and 1981) made more online purchases last year than any other age group” [13]. Unlike many others, the IoT is an industry, which reaches a broad group of users. While this brings advantages, it also introduces complications in terms of how to ensure accessibility for all, how to manage the collected data in a way, which all users trust, how to integrate the diverse technologies, which are used to appeal to the different user groups, and how to standardize the widely varying operational environment. All of this is essential to ensure that the market continues to be generated and that the industry continues to grow.

8.3

Generating the market

The smart-city IoT has continued to evolve relatively naturally since inception, with rapid rates of uptake to date. Section 8.3 is therefore presented from a perspective to ensure that the current users continue to use it, and that any portions of society who are not using it begin to become more integrated. When considering how to continue to generate the market, it is worthwhile noting that some domains generate wider appeal than others. Banking and Financial Institutions hold the largest share of the global IoT market [17]. Gartner predicted in August 2019 that utilities will be the highest user of IoT endpoints [18]. The next two most popular domains are predicted to be automotive and healthcare [18]. Awareness of the popular domains is important, given the subsequent implications placed on the supporting network infrastructure. Identification of the domain helps to gain an understanding of, for example, the volume of data being generated, its frequency of transfer, its QoS requirements, its sensitivity, and its vulnerability to security breaches. All of these factors should influence the way in which the infrastructure is provisioned. One ideal goal of the smart-city IoT is that it improves citizen quality of life. Improvements to quality of life are a key contributor to the uptake of smart-city technologies and applications. It can assist, for example, independent living in homes by the elderly [19 22]. Furthermore, a study by Juniper describes how much time the IoT saves consumers [10]. Nonetheless, despite the benefits, careful effort is required to ensure that the market continues to be generated. It is core to contribute solutions that people want: ETSI describe that, “A ‘smart city’ uses digital technologies to engage more effectively and actively with its citizens . . .” [23]. However, there is a general lack of awareness as to whether the solutions provisioned actually respond to citizen needs. In fact, it is argued in Ref. [24] that, “. . . smart city projects . . . tend to exclude the perspective and interests of citizens.” This may not be the fault of the Service Providers: The KPMG study describes, for example, that, “The burning question is how can consumers and . . . companies achieve this nirvana of consumer mindreading?” They go on to question, “How can

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they ensure their online strategy is acutely tailored to attract and win the drivers and dynamic outcome segments they serve?” [13]. Smart-city programs help to generate the market. The Smart City Mission is one example of a program, led by the Government of India with an objective of establishing 100 smart cities across the country [25]. Running in a 5-year program from 2017 to 2022, cities are competing for funding to implement the Smart City Mission. The second phase of the program is likely to be launched in 2020, Smart City Mission 2.0 [26], and the plan is to eventually roll out the mission to all 4,000 cities across the country. Smarter London Together is another smart-city program, which aims to place London as a world leader in smart cities. One of the ways in which it anticipates this will be done includes, “More user-designed services,” which will, “put users at the heart of what we do” [27]. The importance of placing people as the priority is widely reported: “cities are about people” [8]. The World Economic Forum describes that, “Smart Cities Must Pay More Attention to the People who Live in Them” [28]. An aspect that is popular within smart-city programs is the support of a remote workforce. There is a wide range of benefits coming from a remote workforce: It can lead to reduced congestion on the roads for people who would otherwise be traveling to the workplace, and subsequently reduced emissions from transport. It can lead to reduced costs, which would be incurred when supporting buildings populated with staff, from heating to maintenance costs. It can potentially lead to fewer disputes between members of staff as a result of working less closely with one another while executing their jobs remotely, and subsequent reduced need for interventions by management. The social benefits of home working have also been widely discussed. Remote working however, places demands on the infrastructure to support homeowners; away from metropolitan areas, bringing a need for reliable and powerful connections in traditionally residential areas. Fulfilling smart-city goals is challenging. In relation to India’s Smart City Mission, as of September 2019, only 10% of the planned projects had been completed. With planned completion of these projects between 2019 and 2023, the challenges associated with long-term funding, lack of private participation and capacity building may need to be given greater attention before this is possible. There is therefore some uncertainty as to whether the program will complete. Continuing to generate the market is likely to be supported by increasing the transparency with which activities take place here. From the fact of online crime generally not being reported in our day-to-day news outlets, to the myriad range of ways in which a service may be set up with a provider, the ambiguous aspects of IoT applications and services can block participation here.

8.4

Blocks to the market

When considering blocks to the smart-city market, it is interesting to consider the reasons why 13% of adults in the United Kingdom still did not use the Internet by 2018 [16]. It has been described that, “Those who don’t use the internet are the

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very oldest who have made an active choice” [29]. Driving their “choice,” however, may be a range of factors. The Oxford Internet Surveys explained in 2013 that reasons for failure to use the internet included factors, such as “cost, access, interest and skills” [30]. The survey also states that, “Many non-users are simply not interested in being online. In fact, nearly all non-users cite a lack of interest as one reason for not being online” [30]. It should be questioned why this lack of interest exists. As it has been identified that it is, in general, a particular demographic, which is not participating, there is likely to be a common set of reasons. For elderly users, it may be due to these services not being marketed to their needs. It may be a lack of disposable income. It may also be due to health factors. Nonetheless, with the proportion of the elderly population increasing in their use of the internet in recent years, it is valuable to continue to explore the reasons why, so that priority activities include facilitating their involvement. One potential block for elderly customers has been identified as being due to the complexity of accessing online services. Ofcom reported in January 2019 that, “just under four in ten older consumers (75 1 ) . . . are confident that they understand the language and terminology used by providers, compared to the 75% average” [11]. This factor has therefore been recorded as a block to the market, and priority activities as we move forward should aim to reduce complexity where possible. The number of parties operating in this industry creates complexity from another perspective. While the number of service providers creates effective competition in terms of the costs involved and services received, it can lead to a lack of transparency in the way that services are provided. The negotiations executed, for example, to set up a service with one provider may differ from the steps to set up one with another. This is a consequence of the fact that a standardized approach does not exist in relation to the IoT in general, and unfortunately has a negative impact of uncertainty and potentially a lack of trust in IoT services. Blocks to creating smart cities are considered in India to include “local mindsets” [31]. In one example, local mindsets could potentially lead to poor management of money, and electronic forms of cash may lead to increased levels of debt. It may therefore become the case that such citizens will be unable to use this form of currency, which will complicate the ability to roll out a cashless environment. This may potentially result in a block to generating the smart-city IoT market. This local mindset can, however, be important in understanding how citizens operate, with a view to identifying what they want. Restricting the ability to identify this however, is the fact that it can be difficult to get close to the citizens to understand their needs. Furthermore, even if close access to citizens were possible, the variety of definitions of what the “smart city” involves means that it can be difficult for citizens to know exactly what they want. Modern technology is extending the boundaries of what has ever been possible before, and it is largely primarily those with technological know-how who are able to appreciate what is possible in reality. The New Paradigm for Safe City Streets instructs that we should “Let Cities Lead” [32]; however, this generally does not penetrate to the citizen level. Instead, it is often the case that the government controls the path, which a city takes. The Mayor of London, for example, describes how he believes that London is

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leading in smart-city solutions worldwide; one exemplar technology in London includes cameras worn on the body of the Met Police [27]. The Mayor also anticipates that a leading smart city is achieved by providing services, which respond to customer needs. However, it is unclear what this means in practice, and the steps which should be taken to facilitate this. Taking the body-worn cameras as an example, if citizens become aware of their reported weaknesses, for example, [33], this is likely to hamper their trust with regard to the ways in which smart cities are being rolled out, despite initial appearances that the technologies are for their benefit. The physical network infrastructure is considered to be a major barrier to IoT establishment in the United Kingdom in particular, in comparison to countries such as South Korea, Singapore, and Japan [6] (See Table 8.1). In addition to an infrastructure possibly inadequately supporting networking needs within a society, it can also introduce challenges with regard to the extent to which services might be interoperable on an international basis. A region or a country should not be considered on a standalone basis in today’s networked environment, although this is unfortunately the situation due to the way in which the standardization bodies exist. The potential impact of standardization practices operating on a largely continental basis is disruption of a service being accessed across disparate jurisdictions. An internationally consistent IoT infrastructure would be the ideal scenario, however the probability of ever achieving this is highly unlikely. Supporting a society in which citizens are increasingly exposed to smart technologies requires that they are educated so that they are supported in order to exist in an online world. While citizens have had an opportunity to grow up and be exposed to risks and criminal activity in the physical world, the majority have not been exposed to the equivalent in the online world. Due to the hidden and remote world of online technology, there is less opportunity to learn from this until we become victims. This fact is likely to be a block for some citizens, particularly depending on how the environment evolves. Critical thinking may support citizens in the online environment; it is described by Ofcom as, “. . . the skill that enables people to assess and evaluate their media environment . . .” [16]. This includes ability to decipher an advertisement message and an Table 8.1 Network infrastructure capability [34]. Country

ISP

Average download speed (Mbps)

South Korea Taiwan Singapore Jersey Sweden Denmark Japan UK

SKBroadband Hoshin Multimedia Center MyRepublic Jersey Telecom Banhof EnergiMidt Fiberbredband A/S @Home Network Japan Virgin Media

43.97 40.11 96.17 25.91 48.41 55.31 49.5 57.36

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editorial message. Critical thinking in relation to online use is limited, despite the fact that four in five internet user report confidence in identifying online advertising in 2017 [16]; Ofcom notes that there has been little change in this over the years. Critical thinking refers to people being aware that they are being advertised to online, particularly in the case of search engine results. Awareness of the accuracy of content online is another important skill under the umbrella of critical thinking. While the evidence suggests that there is relatively broad variation in critical thinking ability, the fact that only over half of internet users consider “some” of the information found online to be true is significant, indicating that there is general doubt [16]. Doubts in the safety of technology may act as a block in its uptake and continued use. In this section, a selection of blocks to the smart-city IoT has been considered. It should also be recognized within the context of blocks to the market that in the future IoT, it may become necessary that blocks are put in place for ensuring that internet services are accessible for the “right” people. For example, if certain types of users have a propensity to enter into debt with the use of electronic cash, the companies providing these services may be unlikely to want them as customers, and therefore block their use. This will create a situation where the social needs of a society should be responded to as a priority over political goals for the society’s wider benefit as steps continue to be taken to expand the market.

8.5

Expanding the market

The World Economic Forum described in October 2019 their ideal perspective of the world by 2030 [35], that of a world in which: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

We are winning the fight against climate change Cutting violent crime in half Empowering 8 billion minds with mobile technology Clean air is a human right We build a fair and democratic gig economy There is a new platform for peace in the Middle East We create cities where you can walk to everything you need Clean electricity will dominate the energy sector Virtual reality will protect our mental health The circular economy has become the economy

To consider a few of the preceding items in more detail: The objective of empowering human minds using technology will have greater potential if the market blocks discussed in Section 8.4 can be overcome. There is a need to make technology accessible and easy to use for the general public: Over complexity can paralyze the extent to which people participate. The variety of ways in which solutions are provisioned limits the transparency of any. Furthermore, these are typically more accessible to users with technical capacity, and are less accessible for users without; this has specific implications for particular user groups, and limits their ability to become involved in expanding the market.

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While it has been recognized that the 75 years and over are a growing market, there are opportunities to extend services to groups who have been undertargeted to date, such as the elderly and also the disabled. The ITU-T acknowledges that a city must be, “responsive to the needs of the citizens” [8]; therefore it is important that the groups with a lower rate of uptake than others are specifically accommodated in future efforts. Furthermore, it is noted that physically disabled citizens can benefit in particular from technical advancement [36], which may include autonomous cars and devices to support independent living in the home. As observed with the elderly population, uptake rates by disabled users have been growing recently, and services should continue to be rolled out with a view to encouraging this user group to participate. As in the case of certain domains being more popular than others, it is also the case that certain applications have a higher rate of uptake. In some circumstances, however, it may be the case that citizens have little choice in relation to whether or not they participate in online activities. In one example, electronic payments are helping to expand the market: As outlets increasingly move to a cashless mode of operation, customers are left with little choice but to adopt the electronic equivalent of cash if they wish to avail of the service. This attempt at expanding the market has contrasting objectives, from a political: “we are a cashless society,” to the social and ethical: “I am being forced to integrate technology into my life.” There are potential ethical consequences of rolling-out technology in this way: The impact of citizens being forced to use technology has been somewhat assessed. In 2008, an experiment was carried out to assess the impact of forcing consumers to use technology-based self-service; the results indicate a negative attitude in general [37]. A study by Pew Research Center in 2018 reports that, “nearly a third think that digital life will be mostly harmful to people’s health, mental fitness and happiness” [38]. While expanding the market, care should be taken that, in line with the World Economic Forum, we build a fair society. It is interesting that three, potentially four, of the idealisms from the World Economic Forum presented at the opening of this section are related to climate change. The opportunities for using this fast-growing industry to contribute positively to these issues can therefore be examined for exploitation.

8.6

Greening the market

“It is a truth universally acknowledged that a (smart) city in possession of a good ICT infrastructure must also be sustainable” [39]. The term “smart city” often goes hand-in-hand with the term “sustainability”; indeed, there is frequently overlap in the use of these terms [40] [41]. A perspective that was originally more focused on sustainability has now evolved to become smart-city goals of a social and economic nature: “In recent years, there has been a shift in cities striving for smart city targets instead of sustainability goals” [40]. While a wider range of goals are now a focus of smart cities in general, sustainability nonetheless remains an important part of what smart cities are about, and what technologies are provisioned for.

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Reinforcing the fact that greening the market should be a priority as we consider the next phase of the smart-city infrastructure, “nine out of ten people now breathe polluted air” [42]. Furthermore, “Over 91% of the world’s population lives in places where air quality exceeds WHO limits” [43]. It is estimated that approximately 9500 people a year die earlier than they would have due to poor air quality [44]. Transport is the biggest contributor to greenhouse gas emissions in the United Kingdom, responsible for 21% of emissions in 2016 [45], 28% of emissions in 2017 [44]. The Committee on Climate Change stated in July 2018 that efforts should be made to reduce emissions from vehicles [44]. In April 2019, Regulation (EU) 2019/631 was adopted by the European Parliament, which sets new CO2emission standards for cars and vans [45]. Ericsson estimates that ICT can help to reduce emissions by up to 15% by 2030, which is, “more than the current carbon footprint of the EU and US combined” [46]. However, increasing intelligence within smart cities and a subsequent pull of citizens to avail of these technologies creates significant sustainability challenges. Energy consumption will increase where devices require power from the mains. Furthermore, devices that are generating vast amounts of data will require storage. The Cisco Visual Networking Index predicts that, “Mobile data traffic will grow at a CAGR of 46% from 2017 to 2022” [47]. It has been estimated that data generated from online sources could consume one-fifth of global electricity by 2025 [48]. Some smart-city initiatives are driven by a desire to positively contribute to climate change. ETSI has, for example, set up the Sustainable Digital Multiservice Cities working group in 2016 [49]. The Committee’s goal is zero greenhouse gas emissions by 2050. While previous budgets have been met, the United Kingdom is not on track to meet the 2023 27 carbon budget [50]. There are several areas in which emissions are being monitored. One of these includes the emissions from new cars and the rate of electric vehicle development [50]. There is general encouragement to influence uptake of electric cars. Smart cities should include capabilities to support this quest in their programs. The European Commission is behind such initiatives, with a goal of working toward improved citizen quality of life, “by promoting sustainable urban mobility and increased use of clean and energy efficient vehicles” [51]. Furthermore, in October 2019, the European Commission launched “New Guidelines for Sustainable Urban Mobility Planning” [52]. In its Request for Proposals call, investments were encouraged in the areas of physical charge points, and the software required to make the technology “smart, communicative and interoperable” [53] to support its ease of operation. The goal of greening the market through electric vehicles is somewhat restricted due to blocks from different perspectives. The On-street Residential Chargepoint Scheme [54] exists in recognition of the fact that many citizens across the United Kingdom do not have access to off-street parking, where they might otherwise be able to charge their electric vehicles at home, with an objective of increasing the opportunities available for citizens through the scheme. This is another reminder that the solutions, and the ways in which they are provisioned need to be done so in a way, which responds to citizen needs. Enabling citizens is required from a range of perspectives when prioritizing activities in the roll out of the smart-city infrastructure.

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8.7

169

Enablers

In terms of enablers of the smart-city infrastructure, we consider continued development and growth to be essential in the near, and possibly long-term future to support the gaps and blocks which exist at present. Technology enablers are described by Ernst and Young in Ref. [4] as including: 1. 2. 3. 4. 5. 6. 7. 8.

Decrease in sensor and electronic cost Increase in computing power On-demand cloud computing Decrease in connectivity cost Digital business models Evolving partnerships Advancements in connectivity technologies Flagship government programs such as smart cities

While it is recognized that technology already has a strong foothold in society, there are opportunities to improve its spread and the general levels of satisfaction from its services. This can be supported through the standardization of technology and services, supported by the government.

8.7.1 Smart government The role to be played by the government and standardization bodies is a particularly important influence in enabling the smart-city IoT. Smart-city technologies have evolved in an ad hoc manner, as and when they become available by vendors who were responding to gaps in the solutions available, or were provisioning new solutions. However, smart capabilities are increasingly becoming part of the city infrastructure and citizens are relying on the technologies to support their day-to-day lives. It is therefore essential that planning, and importantly, governance is applied to ensure that interoperable solutions are provisioned and citizen needs are met, without compromise. A report released in June 2018 by the Eden Strategy Institute ranks the top 50 smart cities worldwide [55]. The ranking is performed using metrics, which include vision, budget, people-centricity, and support programs, among others. The smart cities are evaluated in terms of the capacity shown for, “A sincere, people-first design of the future city” (people-centricity), as one example. This is important, as there is evidence that the solutions deployed may be good for marketing purposes, but not necessarily that they respond to citizen needs in the best way possible. It is believed that the ten metrics proposed by the Eden Strategy Institute provide the required considerations that city governments should use to design smart-city strategies. The top 50 smart-city governments are found in London (1), New York (4), Barcelona (9), Hong Kong (18), and Dubai (40), to name a few. In their study, they identify that the most successful smart cities find innovative ways of raising funds to support their program. This suggests that there may be a parallel between the way in which money is raised and the provision of effective solutions, which

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respond to citizen needs. Innovation in solutions is important and is possible as a result of the lack of standardization in the ways in which solutions are provisioned in general. However, an effective compromise is needed, given that standardization is also considered to be important due to the inefficiencies and ineffectiveness where it is lacking.

8.7.2 Standardization Achieving a degree of commonality between the works of the different standards bodies is difficult, but important to support interoperable solutions, ease of deployment, and transparency. The work underway by a selection of these bodies is presented in Table 8.2 for comparison. The ITU-T, as one example, supported a Smart Sustainable Cities (SSC) Focus Group to consider the use of technology and its support of day-to-day life. This group concluded its activities in May 2015, and the work is now continued by Study Group 20 Internet of Things (IoT) and Smart Cities and Communities (SC&C). Twenty-one technical specifications and reports were output at the time of the FG-SSC conclusion. While these standards are applicable, they are not enforceable and, as a result, inconsistent operations continue to persist. Considering standardization more broadly than just sustainable cities, there is also wide variation of the ways in which services are made available by Service Providers. Interoperability between the systems deployed is a significant challenge in the smart city. IoT systems are generally rolled out in a bespoke vendor-specific manner to respond to a particular smartcity aspect, such as smart street lighting or smart waste management. Systems that are made available by one manufacturer are generally not interoperable with those from another, due to the lack of a standardized provision. This is evident when examining the attributes used by each provider to set up a SLA: In the case of the IBM Watson IoT Platform, for example, information collected includes Service Name, Device Type, Device Description, Attributes (Serial Number, Description, Manufacturer, Firmware Version, Model, Hardware Version, Class, Descriptive Location), and Optional Metadata. In relation to the Bosch IoT suite, on the other hand, detail collected includes Tenant ID, Device ID, Credential, and Secret. This lack of a consistent information set makes it impossible to access services made available between vendors in a consistent way.

8.7.3 Smart incorporated city planning As described earlier, citizens can be forced to use technology, which can also be seen as an enabler of the smart-city infrastructure to some extent. One particular case of this is electronic cash, and the increasing number of opportunities for its use throughout society. A survey conducted in 2018 by Loudhouse a London-based agency on consumers in the United Kingdom, Canada, and the United States, identified that, “one in four Canadians between the ages of 18 and 34 are cash-free. One in five Americans aged between 56 and 64 are also cash-free” [60]. While some citizens may be forced into using it, there are other situations in which it becomes

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Table 8.2 Work underway by standardization bodies. Body

Priority

European Commission

European Innovation Partnership on Smart Cities and Communities (EIP-SCC) [9] 1 Priorities include: Sustainable urban mobility Sustainable districts and built environment Integrated infrastructures and processes in energy, information, and communication technologies and transport Citizen focus Policy and regulation Integrated planning and management Knowledge sharing Baselines, performance indicators, and metrics Open data governance 2 Standards 3 -Business models, procurement, and funding ISO/TC 260 Sustainable Cities and Communities [56] 1 Published ISO standards, include: Maturity model for smart sustainable communities Indicators for smart cities Indicators for resilient cities Descriptive framework for cities and communities 2 ISO standards under development, include: Management guidelines of open data for smart cities and communities Practical guidance for project developers Business districts—guidance for practical local implementation Study Group 20—IoT, smart cities, and communities [57] 1 Questions being investigated include: End-to-end connectivity, networks, interoperability, infrastructures, and big data aspects related to IoT and SC&C Requirements, capabilities, and use cases across verticals Architectures, management, protocols, and QoS e/Smart services, applications, and supporting platforms Research and emerging technologies, terminology, and definitions Security, privacy, trust, and identification for IoT and SC&C Evaluation and assessment of Smart Sustainable Cities and Communities SyC Smart Cities, electrotechnical aspects of smart cities [58] 1 Projects under examination include: City service continuity against disasters—the role of the electrical supply Smart cities reference architecture methodology G

G

G

G

G

G

G

G

G

ISO

G

G

G

G

G

G

G

ITU-T

G

G

G

G

G

G

G

IEC

G

G

(Continued)

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Table 8.2 (Continued) Body

Priority Smart-city standards inventory and mapping Part 1 Methodology Use case collection and analysis: City information modeling for smart cities The ETSI Sector Forum on Smart and Sustainable Cities and Communities is involved in [59]: prepare an overview on suitable standards already publicly available analyze and recommend standards for development, implementation, adaptation, or revision organize events on standardization activities for smart and sustainable cities open to relevant stakeholders advise stakeholders on any strategic issues and developments concerning standardization G

G

ETSI

G

G

G

G

more difficult to do so. Moving to a cashless society is more difficult, for example, in regions where citizens have a low income, as they generally rely entirely on cash. It also becomes more challenging in rural regions where broadband access can be restricted [61]: this may be significant in the fact that only 34% of transactions in the United Kingdom were paid for using cash [62]. Reliance that the infrastructure will be in place to support the lifestyle within the region subsequently becomes more difficult. Priority activities in relation to the infrastructure should therefore ensure that citizens are adequately supported when there is an expectation on their technology use. As one example of a cashless society, Amazon opened a checkout-free shop in January 2018 at its offices in Seattle. Use of the store requires that an app is downloaded, which links to an Amazon account and credit card. A code is generated by the app, which is scanned at a gate into the shop to grant access. Movements are then tracked by ceiling cameras and pressure plates on the shelves. A receipt is automatically received on the phone after exit from the shop. Frictionless payments are considered to have optimized online and offline purchasing experiences. A frictionless payment is characterized as having a checkout process which: G

G

G

G

G

“eliminates or reduces waiting time” “allows a faster checkout” “reduces the number of steps required to complete the checkout process” “it feels like a natural part of the customer experience” “it reduces the customer’s cognitive strain” [63].

Frictionless payments can introduce a new layer of anxiety for customers; however, due to the speed of actions. Prepaid cards are another method of operating within a cashless society, such as the Starbucks card. In 2015, it was reported that

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“Nearly 46 million Americans received Starbucks gift cards this holiday” [64]. By 2016, it was reported that, “Starbucks’ loyalty program now holds more money than some banks” [65]. As society comes to rely more on technology, there is less ability to cope if the technology fails. TSB Bank Plc in the United Kingdom has branches across the United Kingdom. They suffered a failure in April 2018, which affected customer ability to view their account balances or make transactions. Propagating the effects of the failure was the fact that the bank communicated poorly about what had happened. The disruption happened due to a transfer of the bank’s IT system to a new platform when it split from the Lloyd’s Banking Group. This had been a planned move, and while TSB reported that it had told customers about the disruption in advance, some were unaware and some continued to experience problems after the indicated disruption period. Fraud then became a problem, when customers mistakenly allowed others to access their accounts. There is little evidence, however, that cash is dying out completely. While citizens are carrying less cash than before [60], there are indications that cash continues to be the prominent method of making payments—80% of transactions in Europe are made using cash [66]. The evidence suggests that, at this stage, we are unprepared in general to live in a cashless society; indeed, 17% believe it would be impossible to live in a cashless society [61]. A completely cashless society is somewhat unachievable at this point, in the United Kingdom at least. A bank account cannot be assumed to be held by all citizens for example. The World Bank reports, for example, that, “In high-income economies 94 percent of adults have an account; in developing economies 63 percent do” [67]. Without a bank account, it is impossible to join the cashless society, regardless of the capabilities of the infrastructure in place. This fact reminds us that while the technology that supports solutions is important, it is only one aspect of an effective smart city: working with the citizens is also a priority.

8.8

Training and involving stakeholders

The stakeholders are one of the metrics used by the Eden Strategy Institute to rank smart cities worldwide. Also known as the “Innovation Ecosystems,” the stakeholders are evaluated from the perspective of, “A comprehensive range of engaged stakeholders to sustain innovation” [55]. Smart-city planning is therefore seen as an activity, which should take place alongside stakeholders, and these stakeholders need to be in time with what society wants. The Eden Strategy Institute also identifies that, while a number of smart cities involve citizens only as the technologies become usable, cities which are within the top 10 successful example involve stakeholders in addition to the Government to develop the smart city together. Engaging stakeholders from an early stage is therefore a priority activity in support of the future successful smart-city infrastructure.

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Competitions are one approach to engage stakeholders and explore which novel projects should be supported [55]. In 2017 in India, New Delhi, for example, a financial prize was awarded for innovation, which enhances the quality of life for citizens. This was assessed within the categories of “Improving Governance,” “Social Aspects,” “Culture and Economy,” “Environment Impact,” and “Transportation and Mobility.” In total, 90 cities have been identified as making contributions. As another example, the Smart Cities-Smart Futures Competition allows innovation from students in Wisconsin to be captured in the creation of smart-city solutions [68]. In 2018, Miami’s City of Coral Gables hosted a competition to prototype a solution for Transportation and Traffic Challenges [69]. Each of these attempts to engage stakeholders and encourage innovative solutions. Stakeholder types can be considered from the perspectives presented by Mitchell et al. (1997) [70]. Stakeholders in their work are considered in terms of belonging to one of eight categories, with each category varying dependent on: (1) power, measured by the ability to influence and achieve their desired outcomes, (2) legitimacy, the fact of stakeholder actions being appropriate, and (3) urgency, the stakeholder’s need for immediate action. The most powerful stakeholders have aspects of each of the three qualities. Stakeholders can be: G

G

G

G

G

G

G

G

Dormant: have power but little legitimacy or urgency Discretionary: have legitimacy but no power or urgency Demanding: have urgency but little power or legitimacy Dominant: powerful and legitimate and have a strong influence Dangerous: have power and urgency but lack legitimacy Dependent: do not have power, but have both legitimacy and urgency Definitive: have power, legitimacy, and urgency Non-stakeholders: do not have power, legitimacy, or urgency

To contextualize these categories, we can consider the way in which citizens are perceived within the Acorn classification (see Table 8.3). General consumers of the IoT are most likely to exist within the Dependent category. This information is useful in that it highlights their needs from the infrastructure and how they are likely to continue to be attracted to the future smart-city infrastructure. It also highlights how general citizens are unlikely to participate in the more sophisticated activities of the smart city, such as application design and provision. The smart city is an interesting industry in that anyone, in theory, can have power, urgency, and legitimacy due to the fact that smart-city solution deployments can be carried out by anyone. Limiting the ability to do this is the technical knowhow, as the more successful solutions are generally made available by large industrial bodies as opposed to individuals. One reason for this is due to the limited interoperability between the solutions already available, in the sense that solutions are largely vendor specific and are not interoperable between vendors. More technical knowledge is therefore needed to support their roll out. A Call for Projects was released by eNGie in 2016 for the purpose of “Helping Citizens become Stakeholders in the Smart City” [71]. This is in recognition of the fact that, “Residents . . . have a broad range of potential ways to get involved in the

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Table 8.3 Examples of user groups from the Acorn guide. Category

Classification

Characteristics

Online activity

Category 1 Group A Type 2

“Metropolitan money”

Live in large apartments or town houses in London or other major cities

Category 1 Group C Type 10

“Better-off villagers”

Live in the larger, more expensive housing found in villages and the edge of small towns

Category 3 Group F Type 22

“Larger families in rural areas”

Large detached houses or bungalows in more sparsely populated areas

Category 4 Group K Types 34, 35, 36

“Student life”

Students living in a hall of residence or in flats or shared houses

Likely to use their tablet to access content relating to travel, news, weather and to play games and, less frequently, read blogs. More prolific Internet users when organizing leisure, finances, or household services. Use smartphones for email and to exchange pictures, or download and listen to music. Few are regular users of social media accounts. Occasional rather than regular users of the internet, shop online slightly more than average, research finances, cars, consumer electronics, and property. Online purchases might be gardening equipment, wine, and flowers. Use of social media is likely to be much lower than average. Many will find it convenient to bank online, monitor investments, and read newspapers. Some will be active on auction sites such as eBay. They will also buy gardening equipment, electrical goods, cosmetics, tickets, travel, and holidays online. Internet use is likely to be extensive, going online to research purchases, download music, stream TV or videos, and play games. Ownership of (Continued)

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Table 8.3 (Continued) Category

Category 4 Group M Types 41, 42, 43, 33

Classification

“Striving families”

Characteristics

Low-income families typically living on traditional low-rise estates

Online activity smartphones, tablet, and hand-held computers will be above average. Their phone is less likely to have internet capabilities and with the possible exception of games consoles and TVs, these people are less likely to purchase the latest technological goods. Visiting the pub, computer games, DVDs, betting, bingo, and the lottery are amongst the more common leisure activities.

smart city, for example, by producing energy, helping to regulate public space, by initiating or promoting new uses . . .” In Ref. [72], the authors examine, “Which stakeholders are involved in the planning process of a smart city district and how can their stakes be understood in terms of smartness?” This considers a broader range of stakeholders, including politicians, architects, and construction firms. “A Guide for City Leaders” has been prepared by the ITU-T to support smart, sustainable cities. This identifies that local government should increasingly become responsible for the activities in the smart city, helping to facilitate an infrastructure and set of services, which respond to local needs.

8.9

Summary

A study by Pew Research Center describes that most experts recognize, “there is no turning back” [38] in relation to digital life. It is a technology that is integrated in bits and pieces throughout our day-to-day lives. However, solutions are often incomplete, and continue to evolve. The online world is challenging to manage and control. This is further complicated by the close interrelatedness between many different aspects, each of which may have some level of dependency with others. A change to one aspect is likely to have an impact on another and another and another, and the full set of consequences may be difficult to completely contextualize in advance. As discussed earlier, Professor Klaus Schwab describes his perspective of the Fourth Industrial Revolution, and the impact of the IoT on this. He also describes

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his fears, if the successes of the anticipated IoT lifestyle are not fulfilled. This includes the fact of organizations being unable to adapt, the impact of shifting power on creating new security concerns, and the increase of inequality and society fragmentation. He asks, to ensure that the IoT results in a positive impact, that people are considered as a priority—“. . . that all of these new technologies are first and foremost tools made by people for people” [73]. A theme that crops up again and again is the importance of ensuring that citizen needs are met in the solutions provided. However, there is little evidence of verification of this, and this may become the most important activity to prioritize as we continue to roll out the infrastructure in the future. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

8.10

Chapter review questions/exercises

8.10.1 True/False 1. True or False? The smart city is not a particularly challenging domain to consider within the IoT, given the range of areas it cannot cover, including smart homes, smart education, smart transportation, water, and electricity supplies, among others. 2. True or False? Consideration of the smart-city infrastructure is not important from the perspective of who is using it. 3. True or False? When considering how to continue to generate the market, it is worthwhile noting that some domains generate wider appeal than others. 4. True or False? When considering blocks to the smart-city market, it is interesting to consider the reasons why 13% of adults in the United Kingdom still did not use the internet by 2018. 5. True or False? As was observed with the elderly population, uptake rates by disabled users have been decreasing recently, and services should continue to be rolled out with a view to encouraging this user group to participate.

8.10.2 Multiple choice 1. It is a truth universally acknowledged that a (smart) city in possession of a good ICT infrastructure must also be: a. Transparent b. Human centered c. Sufficient d. Sustainable e. Preferred 2. Which one of the following is not a technology enabler: a. Decrease in connectivity cost b. Safety c. On-demand cloud computing d. Increase in computing power e. Decrease in sensor and electronic cost

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3. The role to be played by the government and standardization bodies is a particularly important influence in enabling the smart city: a. Economy b. Infrastructure systems c. Urbanization d. IoT e. Transportation sharing 4. Achieving a degree of commonality between the work of the different standards bodies is difficult, but important to support: a. Interoperable solutions b. Ease of deployment c. Transparency d. None of the above e. All of the above 5. Citizens can be forced to use technology, which can also be seen as an enabler of the smart city: a. E-government b. E-governance c. Infrastructure d. Distance services e. Smart economy

8.10.3 Exercise 8.10.3.1 Problem How do cities and communities become smart cities and smart communities?

8.10.4 Hands-on projects 8.10.4.1 Project Do research: Although information technology promises enormous public benefits, it also introduces new challenges. What are those challenges?

8.10.5 Case projects 8.10.5.1 Problem What are the central goals that motivate a smart-city/community strategic plan? Optional team case project

8.10.5.2 Problem What is a key objective of a smart-city/community strategic plan?

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[20] D. Perez, S. Memeti, S. Pilana, A Simulation Study of a Smart Living IoT Solution for Remote Elderly Care, in: Proceedings of the third International Conference on Fog and Mobile Edge Computing, pp. 227 232, Available from: https://doi.org/10.1109/ FMEC.2018.8364069. [21] S.B. Kumar, W.W. Goh, S. Balakrishnan, Smart medicine reminder device for the elderly, in: Proceedings of the fourth International Conference on Advances in Computing, Communication & Automation, October 2018, pp. 1 6, Available from: https://doi.org/10.1109/ICACCAF.2018.8776734. [22] A. Almeida, A. Fiore, L. Mainetti, et al., An IoT-aware architecture for collecting and managing data related to elderly behaviour, Hindawi Wireless Communications and Mobile Computing 2017 (2017) 1 17. Available from: https://doi.org/10.1155/2017/5051915. [23] ETSI, Smart Cities. Available from: ,https://www.etsi.org/technologies/smart-cities.. [24] J. Engelbert, L. van Zoonen, F. Hirzalla, Excluding Citizens from the European Smart City: The Discourse Practices of Pursuing and Granting Smartness, in Technological Forecasting & Social Change 142, 2019, pp. 347 353. [25] Smart Cities Mission Homepage, Available from: ,smartcities.gov.in.. [26] S. Khan, Smart City Mission 2.0 Likely in 2020, The Economic Times. Available from: ,https://economictimes.indiatimes.com/news/economy/infrastructure/smart-city-mission-2-0-likely-in-2020/articleshow/71324372.cms., September 2019. [27] Mayor of London, Smarter London Together. Available from: ,https://www.london. gov.uk/sites/default/files/smarter_london_together_v1.66_-_published.pdf., June 2018. [28] V. Weber, Smart Cities Must Pay More Attention to the People Who Live in Them, World Economic Forum. Available from: ,https://www.weforum.org/agenda/2019/04/ why-smart-cities-should-listen-to-residents/., April 2019. [29] The Local, Young People in Sweden More Likely to Question Information Online. Available from: ,https://www.thelocal.se/20171019/young-people-in-sweden-more-likelyto-question-information-online., October 2017. [30] G. Blank, Why Do Some People not Use the Internet? Oxford Internet Surveys. Available from: ,https://oxis.oii.ox.ac.uk/blog/why-do-some-people-not-use-internet/., September 2013. [31] S. Khan, Smart Cities Mission Hit by Funding Blocks. Available from: ,https:// economictimes.indiatimes.com/news/economy/infrastructure/smart-cities-mission-hit-byfunding-blocks/articleshow/71306563.cms., September 2019. [32] Eurocities, The New Paradigm for Safe City Streets. Available from: ,http://wsdomino. eurocities.eu/eurocities/news/The-New-Paradigm-for-Safe-City-Streets-WSPO-BG5E7X., September 2019. [33] M. Ellison, L. Adams, Issues with Police Body-worn Camera System Revealed, BBC. Available from: ,https://www.bbc.co.uk/news/uk-scotland-39730665., April 2017. [34] Broadband Speed Checker Homepage, Available from: ,https://www.broadbandspeedchecker.co.uk/.. [35] C. Parker, What If We Get Things Right?, World Economic Forum. Available from: ,https://www.weforum.org/agenda/2019/10/future-predictions-what-if-get-things-rightvisions-for-2030/., October 2019. [36] C. Lewis, IoT: A Revolution for the Disabled, INFORM. Available from: ,https:// inform.tmforum.org/internet-of-everything/2014/05/iot-revolution-disabled/., May 2014. [37] Future of Privacy Forum, The Internet of Things (IoT) and People with Disabilities: Exploring the Benefits, Challenges, and Privacy Tensions, January 2019. [38] J. Anderson, L. Rainie, The Future of Well-being in a Tech-saturated World, Pew Research Center. Available from: ,https://www.pewresearch.org/internet/2018/04/17/ the-future-of-well-being-in-a-tech-saturated-world/., April 2018.

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[39] ITU-T, Smart Sustainable Cities: A Guide for City Leaders, May 2015. [40] H. Ahvenniemi, A. Huovila, I. Pinto-Seppa, M. Airaksinen, What are the differences between sustainable and smart cities? Cities 60 (2017) 234 245. [41] I. Greco, M. Bencardino, The Paradigm of the Modern City: SMART and SENSEable Cities for Smart, Inclusive and Sustainable Growth, in: Proceedings of the International Conference on Computational Science and Its Applications, 2014, pp. 579 597. [42] World Health Organization, How Air Pollution Is Destroying Our Health. Available from: ,https://www.who.int/air-pollution/news-and-events/how-air-pollution-is-destroying-our-health., October 2018. [43] World Health Organization, Air Pollution. Available from: ,https://www.who.int/airpollution/en/., no date. [44] Southwark Council, Electric Cars, Available from: ,https://www.southwark.gov.uk/ transport-and-roads/electric-cars.. [45] European Commission, Road Transport: Reducing CO2 Emissions from Vehicles. Available from: ,https://ec.europa.eu/clima/policies/transport/vehicles_en. [46] Ericsson, Climate Action, ,https://www.ericsson.com/en/about-us/sustainability-andcorporate-responsibility/environment/climate-action.. [47] Cisco Visual Networking Index, Available from: ,https://www.cisco.com/c/en/us/solutions/service-provider/visual-networking-index-vni/index.html.. [48] J. Vidal, Tsunami of Data Could Consume One Fifth of Global Electricity by 2025, Climate Home News. Available from: ,https://www.climatechangenews.com/2017/12/ 11/tsunami-data-consume-one-fifth-global-electricity-2025/., December 2017. [49] G. Babinov, Sustainable Digital Multiservice Cities: A New Workgroup in ETSI, European Digital SME Alliance. Available from: ,https://www.digitalsme.eu/sustainable-digital-multiservice-cities-new-workgroup-etsi/., April 2016. [50] Committee on Climate Change, How the UK Is Progressing. Available from: ,https:// www.theccc.org.uk/tackling-climate-change/reducing-carbon-emissions/how-the-uk-isprogressing/.. [51] European Commission, Clean Transport, Urban Transport. Available from: ,https://ec. europa.eu/transport/themes/urban_en.. [52] European Commission, New Guidelines for Sustainable Urban Mobility Planning. Available from: ,https://ec.europa.eu/transport/themes/urban/news/2019-10-02-new-guidelines-sump_en., October 2019. [53] HM Treasury, Charging Infrastructure Fund: Request for Proposals. Available from: ,https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/727576/CIIF_RFP.pdf.. [54] Office for Low Emission Vehicles, Grants to Provide Residential On-street Chargepoints for Plug-in Electric Vehicles. Available from: ,https://www.gov.uk/ government/publications/grants-for-local-authorities-to-provide-residential-on-streetchargepoints., March 2019. [55] Eden Strategy Institute, Top 50 Smart City Governments, 2018. [56] ISO, ISO/TC 268 Sustainable Cities and Communities, Available from: ,https://www. iso.org/committee/656906.html.. [57] ITU, SG20: Internet of Things (IoT) and Smart Cities and Communities. Available from: ,https://www.itu.int/en/ITU-T/studygroups/2017-2020/20/Pages/default.aspx.. [58] International Electrotechnical Commission, SyC Smart Cities. Available from: ,https://www.iec.ch/dyn/www/f?p 5 103:186:1821662055856::::FSP_ORG_ID,FSP_ LANG_ID:13073,25., no date.

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[59] ETSI, Smart Cities. Available from: ,https://www.etsi.org/technologies/smart-cities.. [60] Paysafe, Lost in Translation, Volume 1. ,https://www.paysafe.com/lostintransaction/.. [61] Access to Cash, Access to Cash Review - Is Britain Ready to go Cashless. Available from: ,https://www.accesstocash.org.uk/media/1159/interim-report-final-web.pdf., December 2018. [62] R. Sewraz, 25 Million Brits Would Struggle in a Cashless Society. Available from: ,https://www.which.co.uk/news/2018/12/25m-brits-would-struggle-in-a-cashless-society/., December 2018. [63] Payment Highway, Frictionless Payments: Everything You Need to Know, Available from: ,https://www.paymenthighway.io/blog/frictionless-payments.. [64] J. Kell, Nearly 46 Million Americans Received Starbucks Gift Cards This Holiday. Available from: ,http://fortune.com/2015/01/05/starbucks-holiday-gift-cards/., January 2015. [65] A. Meola, Starbucks’ Loyalt Program Now Holds More Money than Some Banks, Business Insider. Available from: ,https://www.businessinsider.com/starbucks-loyaltyprogram-now-holds-more-money-than-some-banks-2016-6?r 5 US&IR 5 T., June 2016. [66] O. Nieboer, Do UK Consumers Really Want to Go Cashless? Paysafe. Available from: ,https://www.paysafe.com/blog/do-uk-consumers-really-want-to-go-cashless/., no date. [67] The World Bank, The Global Findex Database. Available from: ,https://globalfindex. worldbank.org/.. [68] Smart Cities Smart Futures Homepage, Available from: ,https://www.wismartcitiessmartfutures.com/.. [69] University of Miami, Design Your Own Coral Gables: Smart City Solutions Competition. Available from: ,http://smartcities.miami.edu/competition/., November 2018. [70] R.K. Mitchell, B.R. Agle, D.J. Wood, Toward a theory of stakeholder identification and salience: defining the principle of who and what really counts, Acad Manage Rev 22 (4) (1997) 853 886. [71] Engie, Helping Citizens become Stakeholders in the Smart City. Available from: ,https://innovation.engie.com/en/detail/opportunities/helping-citizens-become-stakeholders-in-the-smart-city/3218., June 2016. [72] K. Axelsson, M. Granath, Stakeholders’ stake and relation to smartness in smart city development: insights from a Swedish city planning project, Gov Inform Quarter 35 (2018) 693 702. [73] K. Schwab, The Fourth Industrial Revolution, by Klaus Schwab, World Economic Forum. Available from: ,https://www.weforum.org/about/the-fourth-industrial-revolutionby-klaus-schwab..

Open Data for smart cities

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Bipin Pradeep Kumar Gaia Smart Cities Solutions Pvt Ltd, Mumbai, India

9.1

Introduction

Throughout the course of evolution, most civilizations have historically established their own hallmarks of urbanization and architecture. These are hallmarks with which we may easily identity them and which showcased not just the planning, architectural, or engineering capabilities that existed during those times, but are also a testimony to the technology, the knowledge, the building capabilities, and the social and cultural fabric of those civilizations. Mohenjo-Daro and Harappa that emerged circa 2600 BCE in the Indian subcontinent, amongst the earliest examples of social organization and urbanization, were characterized by their planned grid-like layout and their drainage and sanitation systems. The Egyptian civilization in North Africa, alongside similar timescales with the early period beginning from 3100 BCE is notably characterized by the Giza pyramids and the Great Sphinx, which were built by the old kingdom from 2600 BCE. The Egyptians were among the first civilizations to believe in an afterlife and the pyramids reflected the social ethos prevalent during those times. The Mayas, a Mesoamerican people developed cities spread across North and Central American countries around 750 BCE. These possessed monumental architecture of palaces, pyramid-temples, ceremonial ballcourts and structures aligned for astronomical observation. They believed in the divine association with the stars and their hallmarks of urbanization reflect the influence of cosmology and geomancy. The Teotihuacan, another Mesoamerican civilization around similar timelines as the Mayas but extending well into 400 AD built the city of Teotihuacan meaning “Place of the Gods.” This city is best known by the Pyramid of the Moon, the Pyramid of the Sun, and the Ciudadella (Citadel), which are connected by the Avenue of the Dead. The pyramids were aligned to sunrises and sunsets on specific dates and reflected not just the knowledge and technological capabilities, but also the underlying concepts of the Teotihuacan worldview—a celestial connection and sacred geography. The Greek civilization, one of the earliest urban civilizations of Europe is best characterized by the Acropolis and Parthenon. Functionally among its several purposes, it was designed to present a succession of genealogical narratives that track Athenian identity back through the ages. With their attention to records keeping, philosophical enquiry, and meaning, Greek urbanization reflected a synthesis that paved the way for scientific probing, dialogues, and discussion. This is generally Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00009-7 © 2021 Elsevier Inc. All rights reserved.

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Figure 9.1 Hallmarks.

considered to be the seminal culture that provided the foundation of the modern Western world and is considered the cradle of Western civilization. Moving ahead in time, Rome had begun expanding after the founding of the republic in 6th century BCE. The Roman Empire was one of the largest in history, with contiguous territories throughout Europe, North Africa, and the Middle East. In its quest to expand and administer its vast areas, the Romans built roads, bridges, and aqueducts, but from a city perspective the Roman empire is best personified by Rome. Its Coliseum, the Forum, atriums in houses, and other structures for public interaction reflect the new ideology of open debate, dialogue, and social engagement. From Grid layouts and Drainage and Sanitation to rebirth and astronomy to enabling modern scientific thought, debate, dialogue introspection, each civilization left their respective legacies in urbanization by representing the best of knowledge, methods, material, and technology available to them in their time and characterizing the society they lived in. Each was transformational in its own way. In the last 300 years, we have rapidly moved from the Manufacturing age with the formation of assembly lines and mass manufacturing, to the Distribution age with logistics that enabled manufactured goods to reach global markets, to the Information and Automation age we currently inhabit. The digital revolution created the Information age in the latter part of the 20th century. Since then, unlike ever before in history, we have the ability to gather data from every area, to which we may then apply relevant social, cultural, and operational information. Deep insights through analytics, patterns, and predictions from the data obtained follow. Eventually this enables creating automation to significantly advanced degrees, mature forms of service delivery and dynamically adjusting systems; in essence creating full systems that are augmented with intelligence. Extending this to urbanization and cities, ours is an era where data, computing, and electronics are applied to different city functions and used for delivering public services as illustrated in Fig. 9.1. We are at the crux of a cyber-physical metamorphosis of cities that can truly transform urbanization—to enhance the quality of life of its citizens and provide public services more efficiently. Will the usage of data and its application to city functions be the legacy of our urbanization?

9.2

The rise of urban data

Digital transformation and information and communication technologies (ICT) initiatives together, particularly in the context of smart cities, have created a pathway for substantial data creation in cities. At the same time, several public- and private-sector organizations have incorporated digital processes that accumulate and facilitate data

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and metadata creation. In this practice, data has gone from relatively small-scale databases relegated inside information systems to superabundant data that is available. The variety and depth of this data is only growing as new and increasingly technological solutions that enable data creation or rely on data are implemented to solve the problems of governments, businesses, and private citizens of smart cities. Data comes in from many different data sources—institutional and enterprise datasets, social media, transactions, sensors, and people themselves. In addition, this data can be used to benefit and address cities’ and communities’ challenges. Typically though, this data is stored beyond the reach of most people, secured in private, government, or proprietary databases or on individual electronic devices. It is well acknowledged that data allow problem identification, understanding, diagnostics, and solution. It acts as a raw material, input, and also output depending on the problem, the mechanism used and its application. For cities, it helps determine their problems, shape appropriate solutions, validate outcomes, and progressively even predict events and make long-term accurate projections. Data act as a highly critical ingredient in offering sustainable solutions and building a path toward resiliency that cities require. In the context of smart cities, amongst many, three fundamental motivations for making government or public data Open [1] are: 1. Transparency: The premise behind a democracy is that citizens know what their government is doing. When citizens and other stakeholders have the opportunity to scrutinize the government’s activities, it results in an increased accountability that in turn is expected to hinder corruption. Achieving transparency results in considerable increase in citizen-led control. 2. Releasing social and commercial value: As exemplified by the likes of Facebook, Twitter, and other social platforms, data is a key resource for social and commercial activities. In cities, from environmental data, transport data, planning data, budget data, or even finding addresses and relevant officials to building a search engine, all requires access to data, much of which is generated by government-to-government, government-to-business, or government-to-citizen activities, or held by government. This data can encourage the innovation of new businesses and services that deliver social and commercial value. 3. Participatory governance: This is as much about citizen engagement as it is about participation in governance. In a democracy most citizens are only able to engage with a government machinery decision-making process at an election typically every 3 5 years. By giving stakeholders and citizens a simplified approach to participate in more government functions and decision-making processes, it empowers citizens and enables governments to be more citizen oriented. By lowering barriers and opening up participation, it also allows citizens to provide feedback on government actions and collaborate in policy making.

However data as simple as it may seem, has many avatars and is complex.

9.3

Open Data, Big Data, Linked Data, and Linked Open Data

The deployment of Information and Communication Technology-based systems across many verticals inevitably result in the creation of “Big Data”—data that is

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massive, often complex, and always changing. It could emanate from sensors, people, various transactions that occur, the environment and other sources [2]. If and when such “Big Data” could be made “Open,” the true power of the development of smart-city infrastructure can be unleashed. The act of opening data is akin to extending an invitation to prospectors—software developers, entrepreneurs, journalists, and anyone else for that matter—to freely take the data and turn it into something useful, innovative, or profitable, or all three. Data is a valuable national resource and strategic asset. The US Federal CIO’s portal in their Open Data Policy [3] recognize that managing this data as asset and making it available, discoverable, and usable—in a word, Open, not only strengthens democracy and promotes efficiency and effectiveness in government, but also has the potential to create economic opportunity and improve citizens’ quality of life. Linked Data lies at the heart of the Semantic Web, a vision about extending the existing World Wide Web from just putting information and sites on the web, to making it machine-readable and interpretable, such that software programs and machines can explore the web of data. However while the web is about interlinked documents, Linked Data is about interlinked data. The principle behind it is that when you have some data, through links, you can find other related data. As such, it is a method for publishing structured data using vocabularies (like schema.org) that can be connected together and interpreted by machines. Linked Open Data (LOD) is a powerful blend of Linked Data and Open Data. It is both linked and uses Open Data sources. Linked Open Government Data is the practice of applying LOD principles to Government Data. Fig. 9.2 illustrates the role of the different data types and how they intersect. Strict definitions of the

Figure 9.2 Various types of data.

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most relevant ones in our context, namely, Big Data, Open Data, Linked Data, and LOD are: G

G

G

G

Big Data Open Data Linked Data Linked Open Data and Linked Open Government Data

9.3.1 Big Data According to an accepted definition “Big Data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making” [4]. These are extremely large data sets and their importance is associated with the belief that they may be analyzed computationally to reveal patterns, trends, associations, and even make projections, especially relating to human behavior and interactions.

9.3.2 Open Data Open Data is defined as data that can be freely used, reused, and redistributed by anyone, subject only, at most, to the requirement to attribute and share alike. Open Data is a foundational brick in the Smart City context. It is a subset of the commonly used term Big Data. The term Open Data is used as a noun, where it is used as a term to identify a particular set of Data. It can also be used as a verb to describe an activity and state, or occurrence of Data. In most cases in this chapter, it is loosely and interchangeably used. The word Data itself is used in a plural context. The Open Data Charter [5] describes six principles that aim to make data easier to find, use, and combine: 1. 2. 3. 4. 5. 6.

Open by default Timely and comprehensive Accessible and usable Comparable and interoperable For improved governance and citizen engagement For inclusive development and innovation

9.3.3 Linked Data Linked Data is a set of design principles for sharing machine-readable data on the Web for use by public administrations, business, and citizens [6]. Linked Data is structured data that is interlinked with other data so it becomes more useful through semantic queries. It builds upon standard Web technologies such as HTTP, Resource Description Framework (RDF), and URIs, but rather than using them to serve web pages only for human readers, it extends them to share information in a way that can be read automatically by computers.

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9.3.4 Linked Open Data and Linked Open Government Data According to Tim Berners Lee, LOD is Linked Data, which is released under an open license, which does not impede its reuse for free. Data can be open but not linked or linked but not open; however if data is open and linked it becomes LOD. When Linked Data-based practices are adopted by Open Data portals such as Data. gov in the United States and Data.gov.uk in the United Kingdom, to offer an open and incremental ecosystem that interconnects consumers and contributors of open government data, it is referred to as a Linked Open Government Data system.

9.4

More about Open Data

Not only are there different types of Open Data, but also the existence of the characteristics and properties of the data; and, by making it available, it is also prone to interpretation. Now, let us look at the challenges with Open Data.

9.4.1 Challenges A challenge with Open Data is that despite its widespread use, there is no uniform understanding to what constitutes it and how it is to be made open. Whether it is in the type of data—raw data or processed data or aggregated data, whether it has a focus—traffic, mobility, pollution data, health data, etc. and when it does have a focus, what the semantics are to be. Neither does it address the target group of this data—whether it is for citizens, businesses, application developers, NGOs, etc. Due to this wide array, the vast set of urban initiatives labeled Open Data differs in all of these aspects despite sharing common characteristics of information that is meant to serve the public at large. In a digitally driven Open Data environment, programs that are intended to increase access to information can be counterproductive and be impacted by and can affect inequality. The digital divide could be further enhanced and the digital denied could be completely left out of the race. The positive impact could be deep especially where citizens are poor or marginalized. Making some data—for example, economic data, transaction data, consumption data, can also pose risks to privacy and may enable the misuse of data for the exploitation of individuals and markets.

9.4.2 Free versus not free There are diverging views on whether Open Data can be monetized, as in, whether Open Data should be free. The traditional definition includes free as a stated matter. It is also an uncontested fact that Open Data is an asset. According to the Govt Tech website [7], Open Data must first be both “technically open” and “legally open,” namely:

Open Data for smart cities G

G

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Technically open data: Data that is available in a machine-readable standard format, which means it can be retrieved and meaningfully processed by a computer application. Legally open data: Data that is explicitly licensed in a way that permits commercial and noncommercial use and reuse without restrictions.

The more accepted view is that Open Data must be free to access but need not necessarily be free to use. There is a cost to creating, maintaining, and publishing quality data and this needs to be borne. By virtue of the fact that data is an asset, it is not that a value cannot be associated with it. In an open market scenario, it is a necessary to establish a prolific innovation environment for the ecosystem to thrive. Historically, commercialization and monetization schemes are necessary to achieve tangible social benefits while contributing to sustainability and creating a viable economy. This is similar with data. To obtain the full benefits of Open Data, it is vital that a prolific innovation ecosystem is created with the right incentives and monetizing mechanisms to create a sustainable economy around data. While the debate about Open Data is an evolving one and will continue to go through its evolutionary phases, Open Data is inevitable and indisputably here to stay

9.4.3 Licenses In the Open source software world, there are several licenses based on different kinds of features, permissions, and limitations. This primarily concern the subjects of Linking; Distribution; Modification; Patenting; Public/Private Usage; Sublicensing and Trademarks; Gnu Public License (GPL), Creative Commons (CC), Open Database License (ODbL), Apache; and Open Data Commons (ODC)—which are some of the most prolific and used licenses. The Open Data world is not far behind when it comes to various features and the terms and conditions behind the usage of data. Most Open Data licenses are based on the framework of the Open source software ones. Some nations and city platforms have created their own version of Open Data licenses. A noticeable difference in some Open Data licenses is that in cases, access to data is proactive, which means users do not have to request the information in order to use it. A broad collection of Open Data licenses can be found at Opendefinition.org [8], a site that has a list of examples and links to Open Data licenses that meet the definition of open use. These Open licenses fundamentally cover the “domain” of application, that is, what type of material the license should/can be applied to, whether it requires “attribution” to the source, whether it requires the data to be further “share-alike” and if the data is “reusable.” With attribution, an Open license might say that people who use the data must credit whoever has published it. Or with share-alike, it can say that people who mix the data with other data have to release the results as Open Data as well. At a basic level, the data licenses build on and must be compatible with at least one of the following: G

G

G

Gnu Public License: GPL-3.0 1 [9], Creative Commons: CC-BY-SA-4.0 [10], or Open Database License: ODbL-1.0 [11].

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Permissive/attribution-only licenses must be compatible with all three of the aforementioned licenses, and at least one of the following: G

G

G

Apache: Apache-2.0 [12], Creative Commons: CC-BY-4.0, or Open Data Commons: ODC-BY-1.0 [13] licenses.

Thus, Open Data licenses are used to dispel ambiguity and encourage use.

9.4.4 Open Data formats The in California Open Data handbook lists a few sample data formats used in its Open Data portal [14]. This illustrates the heterogeneity of data that is a barrier to both data providers and data consumers. The heterogeneity can be overcome with adept technical handling and platforms that are the state-of-the-art. In addition to the data formats, there is also a large number of diverse data structures that make machine readability and interpretation of practically impossible. This variety often hinders society from realizing government data transparency.

9.4.4.1 JSON JavaScript Object Notation (JSON) is a widely used file format that is very easy for any programming language to read. Its simplicity means that it is generally easier for computers to process than other formats.

9.4.4.2 XML eXtensible Mark-up Language (XML) is a widely used format for data exchange because it lets users and developers create and maintain their own data structure. Developers can include documentation to it without interfering with reading of the data.

9.4.4.3 RDF and DCAT (and DCAT-AP) RDF makes it possible to present data in a form that makes it easier to combine data from multiple sources. RDF data can be stored in XML and JSON, among other serializations. RDF encourages the use of URLs as identifiers, which provides a convenient way to directly interconnect existing Open Data initiatives on the Web. RDFs are the heart of Linked Data and LOD. The use of RDF is not widespread, but it has seen an uptrend among open government initiatives. Data Catalog Vocabulary (DCAT) [15] is an RDF vocabulary designed to facilitate interoperability between data catalogues published on the Web. DCAT enables data publishers to describe datasets and data services in a catalogue using a standard model along with vocabulary that facilitates the consumption and aggregation of metadata from multiple catalogues. The DCAT Application profile for data portals in Europe (DCAT-AP) is a specification based on DCAT for describing public

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sector datasets in Europe. Its basic use is to enable cross-data portal search for datasets and make public sector data better searchable across borders and sectors.

9.4.4.3.1 Spreadsheets

Many agencies have information in spreadsheet formats like Microsoft Excel. This data can often be used with the correct tagging of what the different columns mean. Spreadsheets may also contain graphs, macros and formulas, which can be more cumbersome to handle.

9.4.4.3.2 Comma-separated files

Comma-separated value (CSV) files are compact and thus suitable to transfer large sets of data with the same structure. However, the format is so Spartan that data are often useless without documentation since it can be almost impossible to guess the significance of the different columns. Furthermore it is essential that the structure of the file is respected.

9.4.4.3.3 Text documents

These include a plethora of documents in word processing formats like DOC, DOCX, ODF, OOXML, or PDF. They are sufficient to show certain kinds of data but the format typically gives no support to keep the structure consistent, which often makes it difficult to enter data by automated means. Generally it is recommended not to exhibit in word processing format, if data exists in a different format.

9.4.4.3.4 Plain text

Plain text documents (.txt) are easy for computers to read. They generally exclude structural metadata from inside the document, meaning that developers will need to create a parser that can interpret each document as it appears.

9.4.4.3.5 Scanned images

This is probably the least suitable form for most data, but both TIFF and JPEG2000 formats can at least be marked with documentation of what is in the picture. Scanned image formats may be relevant for displaying information that was not born electronically.

9.4.4.3.6 HTML

Vast amounts of data are available in HTML format on various websites on the Internet. This may well be sufficient if the data is very stable and limited in scope. In some cases, it could be preferable to have data in a form that is easier to download and manipulate, but it is resource-wise less intense and easy to refer to a page on a website.

9.4.4.3.7 Geospatial data

Geospatial data is used for representing Map based or geographical data. It is often more complex than simple tabular datasets or formats used for textual content. Formats like geoJSON (based upon JSON) and KML (based upon XML) are considered in this set.

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9.4.5 Five-star Linked Open Data In 2010, the inventor of the World Wide Web and the creator and advocate of the Semantic Web and Linked Data, Sir Tim Berners-Lee, suggested a five-star deployment scheme for LOD. The rating begins at one star and the more proprietary formats that are removed and links added, the more stars the data gets. The five-star LOD system is as follows: G

G

G

G

G

One star: The data is available on the web with an open license. Users can look, search, store, change data and share the data with anyone. Two star: The data is structured and machine readable. For example, an excel spreadsheet instead of an image scan. Three star: The data does not use a proprietary format. An example of this is the CSV format that stores tabular data in plain text. Four star: The data uses only open standards from W3C (RDF, SPARQL). RDF is the standard used in a semantic graph database. This graph database, also called an RDF triplestore, is a method for storing and managing interlinked data and making sense of that interconnected data. SPARQL is the W3C-standardized query language for the RDF database. Five star: The data is linked to that of other data providers. Using W3C standards and Linked Data principles, data publishers link their data to other people’s data to provide context.

Every star level includes the conditions of the previous levels; for instance, data with three stars must also be available on the web in machine-readable form. ETSI built upon the Open Mobile Alliance Next Generation Service Interface and created the Next Generation Service Interface Linked Data specification [16] to exchange context information in line with the 5-star model in the preceding.

9.5

National paths to open data

There are several national, city level and even international partnerships to make city or public sector data open. The common belief shared is that as governments become sustainably more transparent, more accountable, and more responsive to their own citizens, they realize the goal of improving the quality of governance and the quality of services that citizens receive. Other rationales for undertaking such efforts and engage in creating reforms that enable Open Data is to promote the use of data to build new services, create intellectual capital and a desire to enable more high-value jobs. Next, an overview of three adopters is provided.

9.5.1 The EU path As early as 2003, under “Directive 2003/98/EC” of The European Parliament and of The Council [17] the European Commission introduced a set of measures to make it easier for businesses to obtain access and permission to reuse governmentheld information. Subsequently in 2011 the European Commission launched an

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Open Data Strategy for Europe, which was stated to deliver a h40 billion boost to the EU’s economy each year [18]. At the time of launch, Commission Vice President Neelie Kroes said: “We are sending a strong signal to administrations today. Your data is worth more if you give it away. So start releasing it now.” In its latest version, the Directive on open data and the re-use of public sector information, also known as the “Open Data Directive” (Directive (EU) 2019/1024) entered into force on July 16, 2019.

9.5.2 The US path In their report on Technology and the Future of Cities, the US President’s council of Advisors on Science and Technology [19] mentions that an information-sharing platform would help to extend activities beyond the local confines of city, benefiting all cities, including those that lack the capacity to innovate on their own. It sees both the potential and the beginnings of such a platform and refers to it here as “City Web.” In 2018, the US Federal government passed the Foundations for Evidence-Based Policymaking Act of 2018 Public Law 115 435. Also known as the Open Government Data Act [20], it makes its portal Data.gov a requirement in statute, rather than a policy. By virtue of the act, it requires federal agencies to publish their information online as Open Data, using standardized, machine-readable data formats, with their metadata included in the Data.gov catalogue.

9.5.3 The Indian path The Government of India saw the need for an Open Data policy quite early. It brought out the NDSAP (National Data Sharing and Accessibility Policy) as a gazette in 2012 [21] designed to apply to all sharable nonsensitive data available either in digital or analog forms but generated using public funds by various Ministries/Departments /Subordinate offices/organizations/agencies of Government of India. The NDSAP policy is designed to promote data sharing and enable access to Government of India owned data for national planning, development, and awareness. As mentioned in the implementation guidelines of the policy [22], the principles on which data sharing and accessibility are based include Openness, Flexibility, Transparency, Quality, Security, and Machine readability. As an extension to this, as part of its Smart City Mission that plans to make 100 cities in India smart, the Ministry of Housing and Urban Affairs also created the Indian Urban Data Exchange [23]. This platform, which will eventually lead to a city data “marketplace,” aims to facilitate secure, authenticated, and managed exchange of Open Data among various data platforms, third-party authenticated and authorized applications, and other data sources, data producers and consumers, both within a city to and scaled up across cities eventually at a national level, in a uniform and seamless way. Besides being an Open Data platform for the 100 1 9 cities, it would be expanded to cover 500 cities by 2022 and all urban centers in India by 2024.

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9.5.4 Other paths Besides the 3 nation/regions earlier, Table 9.1 lists 57 nations that have made inroads into national Open Data systems. This is a nonexhaustive list and is solely compiled with the intention of depicting the spread of deployments across the world. Absence in this list is by no means any indication of the absence of such efforts. These initiatives are aimed at facilitating consumer access to national government data, saving the trouble of collecting data from various authorities, offices, or websites. Even in China, much riled for its closedness, at the national level, Open Data was officially recognized and listed as one of the ten national projects to develop the Big Data industry in 2015. Much like the EU data portal, the African Development Bank Group has a regional Open Data portal [24] for several countries in the African continent. However, it must be duly noted that despite the vast number of national Open Data initiatives, countries are still at a very nascent stage in the implementation of processes and reforms at government level, in the overall availability of data, and in the use of Open Data for transparency and accountability. At an international level, beyond what the EU has formed for its 28 1 member countries, 78 countries and a growing number of local governments, representing more than two billion people, along with thousands of civil society organizations are members of the Open Government Partnership [25]. The World Bank has released an Open Government Data Toolkit that is designed to help governments understand the basic precepts of Open Data, and get “up to speed” in planning and implementing an open government data program [26]. This toolkit includes an Open Data Readiness Assessment Tool [27] that provides a methodological tool to diagnose the actions that a government needs to take to launch an Open Data initiative and a section that outlines a list of technical assistance and funding resources [28] from the World Bank and other organizations which can be extremely relevant to governments in developing countries in their Open Data endeavor.

9.6

Open Data value chain

The data value chain describes the various processes that are involved in enabling Open Data. From the creation and use or generation of data, to discovering a need for data and its final use, possible reuse and revenue realization exists. The data value chain has five major stages—five that are necessary and with one that includes the optional activity of pricing and commercialization. This comprises of the stages of Commercialization, Processing, Governance, Interoperability, and Security/Trust. Each of these stages has several activities in them. These activities are outlined briefly in the sections devoted to the stages. The activities are also illustrated in Fig. 9.3. They can be used as a succinct tool that depicts these stages and lists the various set of activities in each of them. These activities go from data sourcing and generation to use and monetization, as a

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Table 9.1 Nonexhaustive list of nations with national initiatives on Open Data. No.

Country

Open Data portal

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.

Argentina Australia Austria Bahrain Belgium Brazil Canada Chile Colombia Denmark Estonia Finland France Germany Ghana Greece Hong Kong India

19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43.

Indonesia Ireland Italy Japan Kenya Malaysia Mexico Moldova Morocco Nepal Netherlands New Zealand Norway Oman Peru Philippines Portugal Qatar Republic of Korea Romania Russia Saudi Arabia Serbia Sierra Leone Singapore

https://datos.gob.ar/ https://data.gov.au/ https://www.data.gv.at/ https://www.bahrain.bh/wps/portal/ https://data.gov.be/en http://dados.gov.br/ https://open.canada.ca/en http://datos.gob.cl/ https://www.datos.gov.co/ https://digitaliser.dk/ https://opendata.riik.ee/en/ https://www.avoindata.fi/en https://www.data.gouv.fr/fr/ https://www.govdata.de/ https://data.gov.gh/ http://geodata.gov.gr/ https://data.gov.hk/en/ https://data.gov.in/ https://www.iudx.org.in/ https://data.go.id/ https://data.gov.ie/ https://www.dati.gov.it/ https://www.data.go.jp/ http://opendata.go.ke/ http://www.data.gov.my/ https://datos.gob.mx/ https://dataset.gov.md/ http://data.gov.ma/fr http://opendatanepal.com/ https://data.overheid.nl/ https://www.data.govt.nz/ http://data.norge.no/ https://data.gov.om/ https://www.datosperu.org/ https://data.gov.ph/ https://dados.gov.pt/pt/ https://www.data.gov.qa/ https://www.data.go.kr/ http://data.gov.ro/ https://opengovdata.ru/ https://data.gov.sa/ https://data.gov.rs/sr/ https://opendatasl.gov.sl/ https://data.gov.sg/ (Continued)

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Table 9.1 (Continued) No.

Country

Open Data portal

44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54. 55. 56. 57.

Slovak Republic Sri Lanka South Africa Spain Sweden Tanzania Thailand Timor Leste Trinidad and Tobago Tunisia Ukraine United Arab Emirates United Kingdom Uruguay

http://data.gov.sk/ http://www.data.gov.lk/ http://www.scoda.co.za/ http://datos.gob.es/ https://oppnadata.se/ http://opendata.go.tz/ https://data.go.th/default.aspx http://www.transparency.gov.tl/ https://data.gov.tt/ http://www.data.gov.tn/ https://data.gov.ua/ https://bayanat.ae/ https://data.gov.uk/ http://datos.gub.uy/

management tool to monitor and evaluate the data-production process to securing and providing the trust necessary to establish a data economy.

9.6.1 Consumption/commercialization Open Data is recognized as a valuable asset, a national resource in fact. However, there is a debate about deriving commercial value and earning revenues by trading of data through Open Data systems. This debate across political and religious spectrums is an evolving one that will to go through its various arguments and will not be the matter of discussion in this section. Regardless, it is crucial that a prolific innovation ecosystem is created with the right incentives and benefit mechanisms to create a sustainable economy around data. Open Data when consumed with or without commercial tie-ins has the potential to create economic opportunity and improve citizens’ quality of life. Table 9.2 describes the set of activities associated with this stage.

9.6.2 Processing The processing stage incorporates both the core set of activities as well as all other value adding peripheral and nonspecific activities in the data lifecycle. Data processing starts with data in its raw form and converts it into a more useful pieces— cleaning it, enriching it deriving more meaning with further analysis applied to it, and eventually storing it all. Across this wide range of operations, it could include manual or automated means at some points in its lifecycle. Table 9.3 describes the set of activities associated with this stage.

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Figure 9.3 Open Data value chain. Table 9.2 Consumption/commercialization activities. No.

Activity

Description

1

Discovery

2

Pricing

3

Licensing

4

Reuse

5

Marketing

6

Tracking

7

Management information system (MIS) and reporting

This enables users or applications to access the data without actually having to know a-priori the actual data, the source of data, its creator, or intent. Discovery typically occurs by data description or metadata techniques. The mechanism of determining a value for the data by the owner of the data for realizing revenue from it, or its derived products and service. In a truly open scenario, this may be a nonactivity. An activity that sets and makes conditions for legally binding agreements between the producer of data and consumer of data, or the data licensor and the data licensee wherever appropriate. Enriched data can be repurposed and reused. Data models may be altered or reused as is with additional data. In a commercial context, Blockchain technology may be used to empower multitiered realization of revenues from data reuse. The mechanism of conducting activities to create awareness for data, incentivize its usage as well as sales order management. Where required the capability to trace the benefits of data that is made available. Attribution is often a means of tracking and acknowledging all the sources of the data if data has been manipulated or enriched. MIS provides the relevant data on data usage, consumption, where, when, how it was used, and assists in deriving useful insights and patterns. Reports can be accessed at will or mailed to relevant stakeholders.

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Table 9.3 Processing activities. No.

Activity

Description

1

Sourcing/ generation

2

Categorization

3

Masking/ anonymization

4

Cleaning and validation

5

Transport

6

Integration

7

Enriching

8

Analysis and visualization

9

Storage

The activity of creation of data or acquiring it from first sources. It could include further identifying data, data source, type, owner, etc. The process of classifying, organizing and categorizing the data, its policies, licensing, and the governance level of the data The activity of delinking data with its source, owner, etc. Techniques such as anonymization and pseudonymization are employed to enable the privacy of data. The combined activity of data anomaly detection, removing useless data along with the activity of ensuring data is accurate by internal or external checks and subsequently removing incorrect or error prone data. The act of moving data from one location to another, with appropriate tracking mechanisms where required. It typically uses wired or wireless communication technologies between different entities. Different datasets of data and metadata may need to be combined to make new data, make better sense of data as well as draw more precise insights or make more insightful and accurate projections. Data can be heterogenous in nature. By itself, some data may have little or no value. But by adding descriptors, the activity of integration, or selecting data from different sources and creating new datasets, it can create new data with value. Analysis of data used, consumed, where, when, how, etc. aids in deriving useful insights and patterns. Data visualization supports business intelligence, different metrics, and MIS purposes. The activity of accumulating data for future processing and use. All data has to be stored in one form of storage or another. This is a fundamental activity to facilitate most other activity.

9.6.3 Governance The governance stage includes a framework to address the wide range of activity that occurs from creation or generation of data to its use and operations. At the very outset, governance begins by setting a strategic path and enabling a decisionmaking process that fosters innovation and economic development. Prudent governance will also create a culture that is data driven, aware, and evidence based. Governance mechanisms also provide for effective ways of enabling data privacy

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Table 9.4 Governance activities. No.

Activity

Description

1

Validation

2

Disposal

3

Legal framework

4

Policies and regulation

5

Audit framework

6

Data reuse

The activity of ensuring data is accurate by internal or external checks. Inaccurate data may cause social and economic damage as well as an erosion of trust. The activity of removing data. At various stages of its life, data may either have to be archived, backed up, or destroyed. An activity that sets and makes conditions for legally binding agreements between the data licensor and the data licensee wherever appropriate. This could change over a duration or different periods of time. It includes the development and upgradation of all the laws, regulations and policies that directly impact or indirectly shape Open Data. A plural activity that is concerned with policies that deal with the technically governing data and use of data and the governance framework, along with appropriate regulation of data without unreasonably constraining its use. An activity that ensures a methodology is in place to systematically measure the impact of Open Data. Auditing is performed to measuring progress and effective governance. In the context of governance, reuse is an activity to enable proliferation of data within the framework adequate legality, policies, and regulation to further empower the community of users and reusers.

and security protection along with a legal framework to provide recourse. The below Table 9.4 describes the set of activities associated with this stage.

9.6.4 Interoperability Data interoperability addresses the ability of systems and services that create, exchange, and consume data to have clear, shared expectations for the contents, context, and meaning of that data [29]. Providing homogenized access to metadata descriptions and adhering to national and domain specific Standards are pivotal activities of this stage. Table 9.5 describes the set of activities associated with this stage.

9.6.5 Security and Trust Without ensuring that security and privacy requirements are fulfilled, the uptake of Open Data by the publishers and users themselves falls apart. This stage covers the set of activities that provide all the different stakeholders in this ecosystem with levels of trust, security, and privacy with supporting processes that ensure them along with the laws and policy level support to maintain them. Table 9.6 describes the set of activities associated with this stage.

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Table 9.5 Interoperability activities. No.

Activity

Description

1

Harmonization

2

Standards

3

Filtering

4

Definitions

5

Audit framework

6

Data reuse

The activity of ensuring consistency by following a standard for the description of metadata. For example, harmonization of RDF metadata can be done with the DCAT or DCAT-AP. Adhering to all the commonly established norms, specifications, and procedures related to data developed by relevant Standards Development Organizations (SDOs). The activity of removing useless data and duplicate data. Along with cleansing Good data definitions by virtue of data models improve the discovery of datasets, increases reuse, and also improves quality of data. This enables searching through different access points. In the context of interoperability, auditing is the activity of ensuring data and metadata is accurate by internal or external checks. Inaccurate data may cause damage at massive scale. A focused activity to enable easier access to datasets that will in turn increase their discoverability and use, thus enlarging and empowering the community of users and reusers.

9.7

Eliminating silos by sharing or Open Data

There are several different departments and a vast number of agents and stakeholders working to enable urban environments to function. The coordination of this vast array of departments, ministries, agencies, and citizens—the various stakeholders of the city is one of the most important factors that enable urban environments to function. However the different departments and agencies do not necessarily collaborate and communicate with each other. When digitalization takes place, data from these stakeholders, typically using their own dataset and data models, completely different from one another, provides the signals and the basis for decisions that make each agency/department functioning possible. Each department thus creates its own data silo. The term data silos, where one agency/department creates and “owns” certain data, but keeps it to themselves, isolated from the rest, takes its name from grain in a farm silo which is closed off from all outside elements. Open & Agile Smart Cities [30] is a nonprofit, international smart city network that has the goal of creating and shaping the nascent global smart city data and services market and is working toward creating the knowledge that will eliminate these silos. This requirement is best illustrated by the following example depicted in Fig. 9.4. Ambulance services are typically run by the health department or the municipal corporation, but the traffic signals, for purposes of this illustration let us assume are run by the transport department. However in a scenario, where the sensors and communication from the ambulance (owned by the Health department) need to coordinate in right time

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Table 9.6 Security and trust activities. No.

Activity

Description

1

Confidentiality

2

Integrity

3

Transparency

4

Availability and unlinkability

5

Laws and policy

6

Control

In security and trust, the activity of ensuring that information is not made available or disclosed to unauthorized individuals, entities, or processes. This may vary for different sources of data. The activity of providing assurance of the accuracy and consistency of, data and maintaining it, over its entire life cycle. Transparency forms the core of Open Data. In the context of security, it is the set of tasks that ensures that an adequate level of clarity of the processes in privacyrelevant data processing is reached so that the collection, processing, and use of the information can be understood and reconstructed at any time. This activity provides data access and usability upon demand by a user. It ensures that users will not be denied or prevented from using data that is made open. At the same time, unlinkability ensures that a user can make multiple use of resources or services without others being able to link these diverse uses together. When trust is supported by appropriate laws and policy measures to ensure justice to victims and perpetrators it becomes a strong deterrent to engaging in activities that cause harm. The activity of ensuring that the data owner has absolute control over the data produced.

Figure 9.4 Sharing of data between city departments.

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or in advance with the traffic signal (owned by the Transport department), appropriate handshakes, data exchange, verification, etc. by calling relevant application program interface (API’s) need to take place. This is illustrated by the number 1 in Fig. 9.4. Extending this example further, when there is a need to reroute traffic in real time because of increased pollution detected across particular routes, where traffic routing capabilities belong to the Traffic department and environmental data is typically owned the Environment department, appropriate handshakes, data exchange, verification, etc. by calling relevant API’s need to take place. This is illustrated by the number 2 in Fig. 9.4. Extending this even further, when cities decide to incentivize users for using the newly suggested routes, the Integrated Smart Card may be owned by a third department or agency. Again, for doing so, handshakes, data exchange, verification, etc. by calling relevant API’s need to take place. In such cases Open Data mechanisms with syntactic or semantic interoperability is needed to unify the format of knowledge sources and enable distributed queries and responses. Semantic and syntactic interoperability can be achieved by conforming to either or all of REST API’s, RDF, DCAT, and SPARQL. In such cases it is not just data that is Open, but so is the services that enable such functions to be performed. Such interdisciplinary, interagency, interdepartmental behavior can include providing essential services such as public transportation, affordable housing, safe water and sanitation, participatory democracy tools, environmental quality, or universal health services. In modern cities, especially in large urban areas, most of these issues are metropolitan in that they transcend existing departmental and legal jurisdictions. Globally there are several standardizing bodies working toward harmonizing these processes. ETSI in Europe, TSDSI in India, and TIA in the United States are examples of such institutions

9.8

Data marketplaces

A data marketplace is a platform that connects providers and consumers of data sets and data streams. It may also ensure some of the other activities in the Open Data value chain like high quality data, confidentiality, transparency, reuse, and security. The data providers will authorize the marketplace to license their information on their behalf following defined terms and conditions. Consumers can use the data, and play the role of a provider too, by enriching the data and providing data back to the marketplace. This flow of data and revenue across the different stakeholders is depicted in Fig. 9.5. Akin to a traditional market where the consumer pays higher for quality or immediacy, in a data marketplace setting, consumer may pay a premium for quality data or the real or right timeliness of the data they consume. This effectively creates a strong incentive for data providers to offer the highest-quality, most sought-after data possible at the right time as this maximizes their revenue. By allowing data providers to set their own prices on the marketplace and allowing data consumers

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Figure 9.5 Sharing of data between city departments.

to choose who and where they purchase data from, data marketplaces allow consumers to signal which data/sellers provide value. By doing so they also solve the data-pricing conundrum by taking a market-driven approach. Typically, cities and states regularly collect data of various kinds from activities under their purview—tax collection, marriage licenses, food safety inspections, bus ridership, crime reports, court records, disease outbreaks, new businesses, energy and water consumption, building permits, etc. These “datasets” can contribute to tremendous value creation either singly or together with other data. This guarantee of access to public or city data in the true spirit of Open Data, when endorsed by other stakeholders presents a huge economic opportunity for each of the cities that incorporates it. Copenhagen noticeably became the first city in the world to attempt to monetize its, and others’, data through a city data marketplace [31]. In an analysis by the European Data portal of the EU 28 1 countries that studied the extent to which public sector bodies charged for data, they found that over half of the countries (17 countries, 61%) charge above marginal costs [32]. A data economy fueled by commercialization opportunities unleashed by Open Data, will lead to entrepreneurial activity, generate jobs, and boost revenues from commercial activity both new and old. All of this is in addition to providing tremendous value to citizens in terms of improved quality of life through combining different sets of data together. In its report on Creating Value through Open Data, a Study on the Impact of Reuse of Public Data Resources [33], the direct market size of Open Data as estimated by the European Data Portal in 2016 was 55.3 billion EUR and it was expected to grow by 36.9% to 75.7 billion EUR in 2020 in the EU 28 1 countries. The total market value of Open Data was estimated between 193 billion EUR and 209 billion EUR for 2016 with an estimated projection of 265 286 billion EUR for 2020, including inflation corrections. For the period 2016 2020, the cumulative direct market size is estimated at 325 billion EUR. The cumulative total market size for Open Data is forecasted to be between 1138 and 1229 billion EUR. In its report on unlocking innovation and performance through Open Data, McKinsey [34] estimates that Open Data via public information and shared data from private sources can help create $3 $5 trillion value a year in the global economy. In another report by Accenture, Data marketplaces are estimated to unlock more than $3.6 trillion in value by 2030 [35].

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However, in a very early study of Business models for Linked Open Government Data [36] (LOGD) in 2013, commissioned by the Interoperability Solutions for European Public Administrations (ISA) Programme of the European Commission, 37 use cases were identified in which public administrations used LOGD to make open government data available as a service on the Web. None of them charged a fee for LOGD. Notably those were early days for the true monetization of Open Data and data marketplaces that make an impact on the economy, but the hope for a bright future with high potential remains undiminished. Going forward, a decentralized city Data marketplace that is blockchain and other distributed ledger technologies enabled may well be upon us [37]. Such blockchain-enabled marketplaces can ensure fairness, efficiency, security, privacy, and adherence to regulations in addition to enabling tiered revenue mechanisms along the chain.

9.9

Conclusion

We are just beginning to witness and realize the many uses and impacts of data in the context of cities and urbanization, its role in participation and empowerment of citizens and the commercial and social value it can generate. Open Data with its various attributes and contexts is ultimately aimed at collective development of solutions and services for the greater good. Cities and nations are realizing the potential of this new data economy. Unlocking it can not only break silos by its exchange, but by equalizing access to data for all, become a leveler. With tools that allow to experiment and the development of new business models, the net societal value of data when it is made Open is waiting to be unlocked The subject of Open Data is vast though, will continue to be work in progress for a number of years and a chapter is grossly insufficient to cover the diverse array of topics that constitute it. Neither can one chapter alone provide deeper contextualization of or make a deeper connection to the technology in the areas discussed. This chapter glosses over several topics to present a case for Open Data. Open Data presents both great promise and some challenges. While the promises are plenty, with regard to challenges, on one hand some of the concerns with Open Data can be described as technical problems addressing interoperability, data storage, semantics access, inquiry, and display, and on the other, the challenges of social and cultural issues such as defining the rationale and benefits of data collection and access. In addition, there are policy concerns like balancing budgets and the priority of internal government needs of data versus more fundamental needs of its citizens. Open Data requires superior technical capabilities, better democratic structures, evolved privacy mechanisms, greater social cohesion, and a grand strategic vision for its successful execution. True value—net societal and economic, will be realized only when these are better aligned, the market becomes more mature with innovation that drives more data creation and uptake, and these align with the needs of users and citizens.

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207

Summary

The reader would have realized the immense potential of Open Data whilst also awakening to some of its challenges through this chapter. Navigating the space between potential and challenges in creating transformational governance is a work in progress. In this chapter, the focus has been on describing the various attributes, types, and properties of Open Data, along with some of the hurdles that are endured in making data open. The Open Data value chain that identifies the five stages that enable Open Data describes the plethora of activities that cover each of the stages. The reader would also appreciate the incremental but steady progress in this area made evident by the approaches taken by several nations and cities. In the concluding sections of the chapter, readers are drawn to the benefits of Open Data by concrete settings of collaborative governance of how government agency or departmental silos can be eliminated. The final section describes how Open Data marketplaces drive the creation of an ecosystem of problem solvers that can help cities realize economic benefits from their Open Data initiatives. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

9.11

Chapter review questions/exercises

9.11.1 True/False 1. True or False? Digital transformation and ICT initiatives together, particularly in the context of smart cities, have created a pathway for substantial data reduction in cities. 2. True or False? The deployment of Information and Communication Technology-based systems across many verticals, inevitably result in the creation of “Big Data”—data that is small, often complex, and always stable. 3. True or False? According to an accepted definition “Big Data” is low-volume, lowvelocity, and low-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. 4. True or False? Open Data is defined as data that can be freely used, reused, and redistributed by anyone, subject only, at most, to the requirement to attribute and share alike. 5. True or False? Linked data is a set of design principles for sharing machine-readable data on the Web for use by public administrations, business, and citizens.

9.11.2 Multiple choice 1. Data can be open but not linked or linked but not open; however if data is open and linked, it becomes: a. Linked Open Government Data b. Human-centered data c. Linked Open Data d. ICT-enabled data e. Preferred data

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2. A challenge with Open Data is that despite its widespread use, there is no uniform understanding to what constitutes it and how it is to be made: a. Open b. Legally open c. Technically open d. Prone to interpretation e. All of the above 3. Data that is available in a machine-readable standard format, which means it can be retrieved and meaningfully processed by a computer application, is known as: a. Legally open data b. Open data c. Technically open data d. Privately open data e. Publicly open data 4. In the Open source software world, there are several licenses based on different kinds of: a. Features b. Permissions c. Limitations d. Subjects e. All of the above 5. What is a widely used file format that is very easy for any programming language to read? a. XML b. JSON c. RDF d. DCAT e. DCAT-AP

9.11.3 Exercise 9.11.3.1 Problem What are the existing possibilities for business generation around open data in a specific ecosystem, with regards to smart cities?

9.11.4 Hands-on projects 9.11.4.1 Project Do research: What are the perspectives and issues of Big Data and Open Data in Smart Cities, with specific implications for municipalities?

9.11.5 Case projects 9.11.5.1 Problem Give some examples of how Open Data can help create and develop smart cities.

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9.11.6 Optional team case project 9.11.6.1 Problem Which ethical issues arise in the use of smart city artificial intelligence (AI), Big Data, and Open Data, when striving toward smarter cities; and, how these ethical issues can be addressed?

Acknowledgments The support of Pollyanna Nethersole and Olaf-Gerd Gemein for provoking my thoughts, developing my ideas, and in creating a factually correct chapter is gratefully acknowledged.

References [1] Open Government Data. ,https://opengovernmentdata.org/., 2019 (accessed 24.12.19). [2] J. Kerber, How sensors will shape Big Data and the changing economy. ,https://dataconomy.com/2015/01/how-sensors-will-shape-big-data-and-the-changing-economy/., 2015 (accessed 24.12.19). [3] US Federal CIO, Project Open Data. ,https://project-open-data.cio.gov/., 2019 (accessed 25.12.19). [4] Gartner, Gartner Big Data definition. ,https://www.gartner.com/en/information-technology/glossary/big-data., 2019 (accessed 26.12.19). [5] Open Data Charter, Principles of Open Data. ,https://opendatacharter.net/., 2019 (accessed 24.12.19). [6] W3C Linked Data, What is Linked Data? ,https://www.w3.org/standards/semanticweb/data., 2019 (accessed 24.12.19). [7] J. Shueh, Open data: what is it and why should you care? ,https://www.govtech.com/ data/Got-Data-Make-it-Open-Data-with-These-Tips.html., 2014 (accessed 15.12.19). [8] Open Definition Conformant Licenses, Open Data Licences. ,http://opendefinition. org/licenses/., 2019 (accessed 15.12.19). [9] GNU Operating System, Gnu General Public License. ,https://www.gnu.org/licenses/ gpl-3.0.en.html., 2007 (accessed 16.12.19). [10] Creative Commons, Creative Commons License. ,https://creativecommons.org/ licenses/by-sa/4.0/., 2019 (accessed 18.12.19). [11] Open Data Commons, Open Database License (ODbL) v1.0. ,https://opendatacommons.org/licenses/odbl/1-0/index.html., 2019 (accessed 18.12.19). [12] Apache Software Foundation, Apache License version 2.0. ,https://www.apache.org/ licenses/LICENSE-2.0., 2004 (accessed 18.12.19). [13] Open Data Commons, Open Data Commons Attribution License (ODC-By) v1.0. ,https://opendatacommons.org/licenses/by/1-0/index.html., 2019 (accessed 18.12.19). [14] California Government Open Data Handbook. ,https://handbook.data.ca.gov/portaluse/., 2019 (accessed 18.12.19).

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[15] W3C, Data Catalog Vocabulary (DCAT) - version 2. ,https://www.w3.org/TR/vocabdcat/., 2019 (accessed 18.12.19). [16] ETSI, Context Information Management (CIM); NGSI-LD API. ,https://www.etsi.org/ deliver/etsi_gs/CIM/001_099/009/01.01.01_60/gs_CIM009v010101p.pdf., 2019 (accessed 05.01.20). [17] Directive 2003/98/EC Of The European Parliament And Of The Council, European data portal. ,https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri 5 OJ:L:2003:345:0090:0096: EN:PDF., 2003 (accessed 14.12.19). [18] Digital agenda: turning government data into gold, European Commission. ,https://ec. europa.eu/commission/presscorner/detail/en/IP_11_1524., 2011 (accessed 14.12.19). [19] Report to the president, technology and the future of cities, Executive Office of the President, President’s Council of Advisors on Science and Technology. ,https://www. whitehouse.gov/sites/whitehouse.gov/files/images/Blog/PCAST%20Cities%20Report% 20_%20FINAL.pdf., 2016 (accessed 14.12.19). [20] H.R.4174 - Foundations for Evidence-Based Policymaking Act of 2018, 115th US Congress. ,https://www.congress.gov/bill/115th-congress/house-bill/4174/., 2018 (accessed 14.12.19). [21] National Data Sharing and Accessibility Policy (NSDAP), Govt. of India, Department of Science and Technology. ,https://dst.gov.in/national-data-sharing-and-accessibilitypolicy-0., 2012 (accessed 16.12.19). [22] Implementation Guidelines for National Data Sharing and Accessibility Policy (NDSAP), Data Centre and Web Services Division, National Informatics Centre, Government of India. ,https://data.gov.in/sites/default/files/NDSAP_Implementation_ Guidelines-2.1.pdf., 2013 (accessed 16.12.19). [23] Indian Urban Data Exchange, Ministry of Housing and Urban Affairs. ,https://www. iudx.org.in/., 2019 (accessed 16.12.19). [24] African Develoopment Bank Group, Africa Information Highway Open Data for Africa. ,https://dataportal.opendataforafrica.org/., 2020 (accessed 10.01.20). [25] Open Government Partnership. ,https://www.opengovpartnership.org/., 2019 (accessed 16.12.19). [26] Open Government Data Toolkit, The World Bank. ,http://opendatatoolkit.worldbank. org/en/., 2019 (accessed 16.12.19). [27] Readiness Assessment Tool, Open government data toolkit, The World Bank. ,http:// opendatatoolkit.worldbank.org/en/odra.html., 2019 (accessed 16.12.19). [28] Technical assistance and funding, open government data toolkit, The World Bank. ,http://opendatatoolkit.worldbank.org/en/technical-assistance.html., 2019 (accessed 16.12.19). [29] What is data interoperability? Data Interoperability Standards Consortium. ,http:// datainteroperability.org/., 2019 (accessed 16.12.19). [30] Open and agile smart cities. ,https://oascities.org/., 2020 (accessed 10.01.20). [31] P. Nelson, Copenhagen to sell public and private city data via exchange marketplace, Network World. ,https://www.networkworld.com/article/3079810/copenhagen-to-sellpublic-and-private-city-data-via-exchange-marketplace.html., 2016 (accessed 19.12.19). [32] Open Data maturity report 2019, European Data Portal. ,https://www.europeandataportal.eu/sites/default/files/open_data_maturity_report_2019.pdf., 2019 (accessed 19.12.19).

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[33] Creating value through Open Data, European Data Portal, European Commission. ,https://www.europeandataportal.eu/sites/default/files/edp_creating_value_through_open_ data_0.pdf#page 5 11., 2019 (accessed 19.12.19). [34] J. Manyika, M. Chui, D. Farrell, S. Van Kuiken, P. Groves, and E.A. Doshi, Open Data: unlocking innovation and performance with liquid information. ,http://www. mckinsey.com/business-functions/digital-mckinsey/our-insights/open-data-unlockinginnovation-and-performance-with-liquid-information., 2013 (accessed 21.12.19). [35] D. Tang, J. Fujii-Hwang, E. Colwill, S. Arora, A. Shah, A. Mendizabal, et al., Value of data: the dawn of the data marketplace, Accenture. ,https://www.accenture.com/us-en/ insights/high-tech/dawn-of-data-marketplace., 2018 (accessed 21.12.19). [36] P. Archer, M. Dekkers, S. Goedertier, N. Loutas, Study on business models for linked open government data, European Commission. ,https://ec.europa.eu/isa2/sites/isa/files/ study-on-business-models-open-government_en.pdf., 2013 (accessed 21.12.19). [37] A. Bro¨ring, Future data marketplaces, Big Data Value Association. ,http://www.bdva. eu/node/1220., 2019 (accessed 21.12.19).

The role of citizens in smart cities and urban infrastructures

10

Carles Agustı´ Herna`ndez Open Government Presidency Area, Barcelona, Spain

10.1

Introduction

Managing urban infrastructures is not only stones or cement, but it also requires strategic planning and an actor that has not always been taken into account: citizens, concrete, and the collective intelligence of citizens. Citizens can contribute to the whole process of implementing a city infrastructure, it is a key element for their success, and in this chapter we will try to analyze why. Digital revolution, technology applied to city strategy, what is known as smart cities, opens up a world of possibilities for us to use this citizen knowledge, for the role of citizens in infrastructures and for to a greater efficiency and service of them. Let us look at the formulas, theories, and realities that allow it.

10.2

Smart city

The smart city is a concept that begins in the second decade of the current century, as a fuzzy marketing principle, and without clear content beyond an appearance linked to a city strategy. Over time, this fuzzy concept begins to be perceived as something linked to technology, smart cities was technology, technology for cities, but there was a need to define what, how, why . . . Not few governments that go began to apply strategies that were supposedly smart cities, poorly defined, or not landed to the benefit of the citizen, had difficulty in understanding or justifying certain investments. With the passing of time, and with help of the more academic part of the smart city, this concept, which we already see linked to technology, is even more embedded in a definition that makes sense. Smart city would finally be technological tools at service of the day-to-day improvement of the citizens of our cities. Any smartcity positioning strategy must end up, as a result of this, in solutions for citizens, solutions that citizens perceive as palpable as improvements in some aspect of their daily lives. We can see here a first link between smart cities and people, citizens. What is more, the concept “smart city,” does not make sense applied directly to cities, it does not make sense without being applied and landed for people, and then we will see that also with “people.” Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00010-3 © 2021 Elsevier Inc. All rights reserved.

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Citizens

From the initial relationship between citizens and smart cities comes a hybridized concept: Smart Citizens. What are smart citizens? Well, first of all, it is the recognition that smart-city concept, without citizens, without being useful for the daily life of citizens, it does not make sense. Smart citizens, also refers to the fact that with technology and more specifically with the technological tools provided by smart cities strategies, are smarter. Not from the point of view of sudden increases of brain or thinking capacity of citizens; but, from one of these technological tools that improve their day-to-day activities thus, making them more capable of getting many more things done. A prime example is public governance, politics, and public administrations. Technological tools developed and available for citizens, such as social networks or platforms for citizen participation and opinion that have proliferated in all municipalities and through many mobile applications, allow for a capacity of influence and speed in this influence, to the citizen, never seen so far. A tweet, a post on Facebook, a message running on WhatsApp, or any “call to action” expressed through social media or technology tools, can lead to a real crisis, or revolution, or influence and even a change in any specific public policy in minutes. We have all seen examples of tweets that have moved mountains, or calls to action that circulate on networks, and in minutes, thousands of citizens are concentrating on a concrete site for a concrete purpose. We have a clear example in social movements around the world, but especially today is Catalonia, where such strategies move citizens from one place to another and are, in fact, the great framework of the Catalan independence social movement. A third meaning of Smart Citizens term would be derived from active and prepared citizens, in the sense of citizens who count and citizens who influence and participate in city governance and strategy. We can talk about “with” citizens, we incorporate them into decision-making processes, recognize and want to use their knowledge, and create the tools to make it possible. Hence the reflection that we will see throughout this chapter is what is the role of citizens in society? Passive? Active? Observer? Main character? The changes and evolution of society, especially at the end of the 20th century and the beginning of the current one, lead it to demand more prominence, to demand, not only to receive, and therefore to an active, influential citizen model, which must be leveraged and incorporated into the dynamics of governance. Citizen wants and must participate and take part.

10.4

Urban infrastructures

We talked about smart cities as strategy tools. We also talked about citizens who would be the soul of cities as well as the urban infrastructure that would be the skeleton of them. So, can we apply a specific strategy to the skeleton of cities with

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their souls (citizens)? Somehow, the answer to this question is what makes this chapter of the book meaningful. The answer to the preceding is YES, in capital letters. Just as the concrete strategic situation of the cities at its beginning (close to sea, protected on the top of a mountain, next to a river . . .) or made sense in its subsequent growth (around a cathedral, a church, a castle . . .) or later its urban development (grids, streets, parks, residential areas . . .) all sense that, arrived at 21st century and at digital age, cities are betting on the strategic layer that smart cities represent, and as we have said, in practice, means technological solutions that improve the everyday life of citizens. So, do citizens have any sense of the deployment of the smart-city strategy to large urban infrastructures? Well, from the moment that smart city means solutions for citizens, cities are the places where citizens live, and urban infrastructure the skeleton of these spaces where citizens live in, it seems of common sense count with their opinion and participation, from the design stage to the evaluation once the infrastructure is completed and operational. Certainly the fact of having citizens, give them values, intelligence, knowledge, is new, almost in the 21st century. It is strange that it took us so long, and in fact up from 4 days ago, to decide that those people who have to live in cities and who are the final recipients of any policy, every strategy, and in this case of specific technological solutions, have a fundamental role in the whole development of the project. However it is so simple and we find it normal today, citizens have value, intelligence, and knowledge, and as end users of everything, we must take advantage of all that knowledge and opinion and count on them.

10.5

From passive citizen to active citizens

Before we get into the specific role of citizens in city design and implementation of smart-city policies, I think it is interesting to analyze how the role of citizens in society has evolved. Where, we can say, especially in the last three centuries, it has grown from a passive agent to an increasingly active agent. It is in the field of politics, governments, and public administrations that we can best appreciate this change and this evolution of citizen’s role. First, we must analyze the context of the so-called “crisis of politics,” which would be a growing crisis of the confidence citizens have toward the institutions that theoretically represent them. An increasing distance and distrust where three actors play a decisive role, obviously citizens, politicians or public representatives, and media. All three have shared responsibilities, not balanced, but shared at the same time in causes and in finding the solution. We could say that the cause is that society has evolved faster than public institutions, including political parties, and this has created this growing distance. In the field of communication we find a clear enough example. Few years ago, governments were in control of communication, they could strategize with it, dose it, and decide how it came to citizens. Today, as a result of the technological revolution,

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or rather we could say that accelerated by the technological revolution, citizens now have the information, at the minute, at the moment, circulating on their smartphones and on social networks. Moreover, they are active players in this communication even in its generation. As we mentioned above, a tweet, a WhatsApp or a comment on Facebook can cause a change in a policy or, at the moment, call thousands of people around a specific idea or goal. In the face of the preceding change, from passive citizens without tools, to active citizens that are more educated (already born in mature democracies), the adaptation of governments and public administrations are absolutely necessary and indisputable. On a strictly political level, this change of citizen role is clearly reflected in the decline in election participation, the lower membership of political parties, the crisis of traditional political parties, and the emergence of new ones, and at low valuation of political leaders, while voting fidelity to the same party has been volatilized. This social change has transformed the traditional parliamentary representations with the emergence of new parties and the atomization of congresses and parliaments, and with increasing political instability. In practice, however, what are citizens asking of us? How can we identify this social change? If we analyze surveys, in practically every country in the world, logically adapted to the situation and culture of each place, we could say that citizens ask for five great things: G

G

G

G

G

Transparency: Where a citizen wants to know what is inside an administration, what is happening there, and what is done with their taxes. Thus, there is a growing awareness that this is everyone’s responsibility, and not just voting some representatives in to do it all. Pedagogy: To understand the political and administrative language, what politicians have said, and the facilitation of understanding it. In that statement we would already find significant leverage for smart-city policies and solutions, which in practice facilitate this citizen-administration dialogue. Opening: Opening of structures, administration, attitudes, and policies in general. Proximity: This is where citizens want nearby public representatives at street level to talk and have a dialogue with them; as well as, get closer to them. Participation/involvement: If we call it citizen participation or citizen involvement, it is part of another discussion that is not for now, but that citizens want to participate in what affects or interests them, there is no doubt. It is a mistake to believe that citizens will participate in everything, in everything that we call them. It is a grave mistake to judge participation as low in concrete participatory processes, as citizens will be called to participate in what they feel close to, interest, or question them, such as urban reforms near their homes or projects in specific fields, where they consider themselves experts and want to contribute.

Finally, the question is: How do people or society that has knowledge take advantage of it? This is the question that we must answer. The ancient societies regarded the people as ignorant, and as such were ignored and disregarded, there were no votes and when they began they were permitted vote only a men. Later comes universal suffrage and with, governments of everything for people but without people. It is with 21st century that society begins to take value as such, coinciding with transformation we discussed earlier, and governments are beginning to

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become aware of and take into account citizens, not just from a formal point of view, but realizing that this citizen knowledge can be very useful for the projects and development of the city. Furthermore, we already have a formed, mature, and restless society. Who knows a street better than the citizens who live and walk there? Who knows better a square, a neighborhood or a certain area of a city than its inhabitants? Or who knows a particular sector better than the people, companies, university professors, and experts who work there? A practical example, who knows better the practical mobility of a city than for example the taxi drivers or Tourist Vehicle with Driver (VTC) drivers? In a street or neighborhood we have dozens of experts in many things, restless, with ideas and desire. Why not take advantage of it? There is a new concept that works in depth this question, both for public use and of course for private use, is “collective intelligence” concept, referring to the sum and synergy of knowledge that we can all contribute, to any topic or question, and around which ideas, theory and practical tools are being drawn for their use.

10.6

Open government

From theory to practice, the first formulas have already emerged through which the logic of citizen integration in public, or more recently in private governance, have already begun to be applied. A practical definition of open government (see Fig. 10.1) would be to say that the function of open government is to create necessary channels for maximum use of people’s knowledge or of collective intelligence. A more classic and theoretical definition of open government could be that it responds to the demands of citizens of change in the way to govern or to do politics, being the unification in a single strategy of transparency policies, open data, and citizen participation in a transversal way throughout the organization where it is applied. It is not just a website, it is a change of paradigm in the relationship between governments and citizens; it is an

Figure 10.1 Open government. Unification in only one strategy of transparency, open data, and citizen participation influenced by collaboration principle.

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internal and external cultural change based on openness, transparency, pedagogy, proximity and citizen involvement or participation. From this definition three aspects stand out: G

G

G

It is not only a web page: It is a basic and important precept. Renaming the municipality’s website and giving it “open government” to the name by adding four details is not open government, as we have seen, open government is a deep change in culture and mentality throughout the organization, and not a superficial cosmetic change. Transversal: Open government is or is not transversal. It is not worth having a specific experience in a specific department of the City Council or institution. However it can be a good and innovative (a very good experience) experience, but not a profound cultural change that affects the whole institution, as is in open government. An experience and application of open government must be endorsed from the top of the institution to allow its homogeneous deployment to the whole and to reduce the possible and more than predictable internal resistance. Cultural change: Open government is a cultural change; if successful, it will end up affecting all the employees of the institution, from the Mayor or President to the last worker. Beyond the strategic application of specific policies of transparency, open data, or citizen participation, it must end up affecting the daily life of all the people of the institution in line with the aforementioned basic principles, derived in an attitude more inclined to listen, to observe, to capture, and to share knowledge, and in general to involve and take advantage of knowledge, of whatever kind, that comes to us from the citizens.

10.7

Governance

With open government, and in general everything that has come from social changes and demands of citizens, new long-term concepts have emerged, and in which, like everything we have talked about so far, there is an impact on both public and private sectors. Among them a whole world that opens around a term that until recently did not exist and, in fact, is still in process of being recognized in many languages of the world: governance. Governance is a concept that refers to the model of how a government, association, or company is managed internally and in relation to its workers and its citizens. So let us talk about government, model, management, and relationship that applies to workers and/or citizens, all of these concepts would be linked to governance. We might start to wonder if cities, smart cities, and urban infrastructure have governance. The answer would be not only yes but also bad if they do not have it. Cities obviously have a specific model of governance, taking into account the definition of the term, as well as the smart-city strategy, which we have already said is ultimately aimed at citizen well-being. Finally, urban infrastructures, beyond being stone and cement, are part of a human design of a city, they are veins and arteries, also the soul, of the body that is a city, and more, they are for citizen use, therefore, how can they be done without the citizen’s opinion and knowledge? How can they be done without effective governance from the design stage to the evaluation of use?

The role of citizens in smart cities and urban infrastructures

10.8

219

Technological governance

Another discussion, I would give for another chapter, is about governance of all this technology generated through smart-city strategies. We are experiencing times of competition and even international tension over technology control, for example, it has recently been known that Russia ratifies the obligation to introduce Russian products into smartphones [1], such as China forces facial recognition for acquisition of SIM cards [2,3], commercial technological war between Trump and Putin [4], or Spanish government decree [5] that protected by national security reasons allows the intervention of Internet or any citizen smartphone without a court order and without the need to decree a state of emergency. Who controls technology? To what extent can states intervene? Who rules it? What are the rights of citizens in the new digital age? These are areas still unclear in the new technological age and we must know how to move and where we need to adapt the legislation. The Government of Catalonia, for example, is doing an interesting job of drafting a Charter of digital rights and responsibilities of citizens [6]. In another sense, we could talk about technological data governance, or the management and use of all the data. With regards to the smart-city strategy, that would include the products and tools derived from it; the dialogue with which citizens generate a big data that requires a specific strategy for maximum use; understanding that big data is cross-cutting and present everywhere; and especially when it comes to smart cities.

10.9

Hybridizations and changes in citizen governance

Fifteen or twenty years ago, only reflections and paths through which interactions between governments and citizens that took place was what was known, and still is known, as citizen participation (see Fig. 10.2). Political field isolated from the rest, nontransversal, nonproactive, and through which concrete actions of citizen participation or pacification were undertaken only in those areas where government agreed to do so at a specific moment. Although written before, the open government effectively comes under the Obama Directive of 2009 [7], and is flexibly extending different forms of implementation around the globe. It is since then that citizen participation alone ceases to make sense and to take it all within the logic of open government, which is more ambitious, now transversal, and with a real effect on the governance of institutions, responding to demands of citizens. No more than 7 or 8 years ago comes the second major hybridization in citizen governance. The concept “smart cities” begins to emerge, which is first completely diffuse and poorly grounded in a concrete reality. Over time, begin to be assimilated as technology, policies, and specific strategies related to technology. Later, the concept is landed on tools of innovation or technology that will improve everyday life of the citizens. This definition already gives a clear guide in the concrete

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Figure 10.2 The hybridizations. The evolution of governance policies has provoked different hybridizations along time, from the isolated citizen participation to United Nations Sustainable Development Goals (SDGs).

application of smart-cities strategies and a connection with citizens who can see more clearly the fruits of this. Second hybridization is therefore between the world of open government and that of smart cities, creating what is known as smart governance or smart citizens. From then on, open government, apart from making sense as such, also becomes part of the smart cities ecosystem, through this hybridized concept, which in practice means technology and innovation in the service of citizens. There can be no open government without technology, at least in populations of thousands of inhabitants: How to apply transparency, open data, or citizen participation policies with thousands and hundreds of thousands of people, but with technology. Smart governance concept would have this logic, as well as its almost synonymous of smart citizens, which in turn means smart cities for citizens but also smart citizens, recognizing the power of citizen knowledge to incorporate it into the governance logics. Finally, the third hybridization comes with what is known as the United Nations (UN) Sustainable Development Goals (SDGs) [8]. Beyond world pacification and setting great principles for planetary governance, United Nations has, this time,

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produced a concrete tool that is transversely landing on the entire globe and is likely to be of great use. SDGs do not only refer to sustainability as a strict environmental policy; they are not 17 great generic principles, because thanks to the goals of each objective, we have a more concrete and greater guide for their implementation; also in governance, especially through the SDG16, where such policies are specifically included, but not only for this purpose. Finally, SDGs are an efficient and equal guide for the entire planet, in the implementation of objectives of sustainability, justice, innovation, and effectiveness that can come together many of the goals and policies of states. And like everything that we are dealing with in this chapter, they also have a clear effect on the private world. Beyond that they represent a logical improvement in the reputation and brand of the company that fulfills them, and beyond that they will end up being a partial obligation for any private company derived from the bankruptcy clauses of public administrations and the requirements of every day more customers and suppliers, the SDGs are a real revolution in Corporate Social Responsibility policies. Many of them now without a specific guide and represented by concrete social or charitable actions, now find guidance, meaning, and alignment in the direction of planetary governance policies, as well as improving companies brand reputation and enhancement policies.

10.10

Citizens in the city and urbanism in smart-cities world

In this chapter we are talking about the role of citizens in urban planning and smart cities. Changes in society, and as a consequence of public and private governance models we have seen so far, also have, logically, a direct effect on the governance of our cities, on smart-city strategies, and on urbanism and in concrete urban infrastructures. The principles we have now seen of transparency, proximity, pedagogy, openness, and above all, the practical level of recognizing the value of citizen knowledge, there exists a full effect; not only in the governability of a city, or in the implementation of smart-city strategies (let us not forget that they are aimed at improving everyday life of citizens), but also in urban planning. Town planning and infrastructure in a city are not the result of chance; they are made by citizens and for citizens as a result of specific needs, evolution and idiosyncrasies. In the 21st century, therefore, with the evolution and social changes that we have seen and analyzed, urbanism and infrastructures cannot be designed and done without citizens, but also “with” citizens. Someone may ask what citizens in general engineering or town planning know about how to count on the construction of concrete infrastructures. Before these questions there are two types of answer. The first is that, as we have mentioned, these infrastructures are not made by aliens or for engineering graduates, but for the use of all citizens, so their opinion is essential.

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The second is that when we talk about citizens in general, we put some contempt on what they can come to know and contribute, derived from historical atavisms when a high percentage of society did not have the intellectual capacity to comment on certain aspects (which might also be called into question but is not the specific subject of this chapter). If we go to the concrete reality, how many engineers must live in a specific district of a city where you want to make an urban infrastructure (a bridge, a tunnel, a train station, an avenue or a new square, for example)? How many town planners? How many users of that infrastructure? How many mobility experts? How many town planners work in companies related to some of the aspects of the work (engineering, environment, economics . . .)? But, when we talk about experts who do not have to relate exactly to someone who has their studies, we have “experts” for use and practice, such as taxi drivers or VTC drivers in mobility; Metro or bus drivers; grandparents who analyze the evolution of the works—who will be specific users. All of these people not only have the right to say and open up about the new infrastructure, but they can also provide real knowledge that will improve their entire implementation process. In addition, this improvement and contribution of knowledge, makes sense and can be carried out in the whole process of the infrastructure—from the generation of the need for it (usually precisely linked to a need or citizen demand); through the design phase; the construction; and finally the evaluation of use and maintenance of the infrastructure (see checklist: “An Agenda for Action for Citizen Contributions to Specific Infrastructures”): An Agenda for Action for Citizen Contributions to Specific Infrastructures Proven phases of citizen contribution to specific infrastructures include the following key activities (check all tasks completed): _____1. Need: An infrastructure that does not come out of nowhere, but comes either as a result of city planning, or from new ones arising from it, or from new needs arising and usually detected and demanded by citizens themselves. The role of the citizen here is clear enough, as a result of being the main players in the city and its urbanism, they are the main detectors of new needs. _____2. Design: Beyond very technical issues where only citizens of the branch can understand or opine (which is also the citizen’s participation in the design of the work), the fact that citizens, especially ones of that neighborhood or area, will be those who use or are affected by that particular infrastructure, which already gives them a significant role in the design of the work. Later we will look at specific examples of failed urban projects because the role of the citizen in the design phase of the work was not taken into account. _____3. Construction: Once a need is detected, all the circumstances are analyzed and the work is designed, the construction phase comes, who better than the neighbors who will see and enjoy it every day, the evolution of the work to evaluate this, detect possible deficiencies or even, in an orderly exercise of citizen empowerment, detect possible delays or malfunctions, either by exercising more or less direct control over the work or making monitoring in a coordinated way with the technical and political decision makers of this work.

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_____4. Evaluation and use of work: Who will make use of it, are citizens, or specific people, citizens or not of this city, for example in the case of airports, ports or other infrastructures, therefore who better can evaluate the final result of the work according to the their own originals needs than citizens. _____5. Maintenance: This is the most logical, simple and proven phase of citizens contribution to specific infrastructures. The citizen, as a user, is the first to detect any malfunctions, faults, or deficiencies in an infrastructure, and the first who, through normally technological tools available to them, can report or claim them. A clear example would be the numerous mobile applications that have proliferated and where citizens can geolocate defects, allowing a quick reaction of the local government services also connected to this application, because it is evident that the non-proceeding to repair it becomes a problem visualized publicly. All this world of citizen contributions in different stages of infrastructure development, are clearly amenable to creation of all kinds of tools, mainly technological, that facilitate this process by interconnecting citizens, governors and executors of work, in which is definitely a field for smart-city strategy. Face-to-face among all stakeholders, is the most qualitative way to contribute, but it lacks, especially in terms of efficiency and reach of citizens. In the other hand technological tools and electronic participation or e-participation, they are perhaps qualitatively weaker, but provide citizens with simple and quick tools to add their knowledge to the work.

10.11

Practical cases

We will look at three practical examples of cases of urban infrastructures with citizen involvement, the first two examples, probably marked a before and after in the administration-citizen relationship in my city, Barcelona. The first of these would be the one known as Lesseps Square.

10.11.1 Barcelona Lesseps Square example Lesseps Square is an important square in the northern part of Barcelona that was conceived, and has traditionally acted, as a connecting rod between various parts of the area. It was conceived directly, more as a mobility hub as a place of stay, more for vehicles than for pedestrians, and logically this has marked its use and debate over the years. From the reforms that took place throughout the 20th century, from the old traditional square called the Plac¸a de la Creu to the one known as Lesseps Square, in honor of Ferdinand Lesseps, the square was not only the subject of debate over its use of vehicles and not pedestrians (even for a time it was known as the “scalextric”), but became a symbol, during the Franco dictatorship, of neighbors resistance against the imposition of governments. In democratic period, and in particular in 2002, Barcelona local government of the moment began a process of reforming the Lesseps Square, which still dragged

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the mobility “scalextric” to the detriment of citizen’s living space, precisely because reverse this process and convert or recover the character of square understood as a citizen’s stay space. Local government action found, however, not only by citizen opposition, but also by a resistance movement that ended up demolishing the project and having to redo it. What was the mistake of local governors of that time? Impose a project without citizen consultation in a very sensitive space that had already been the protagonist of demands and symbolic neighborhood battles. Further we could say that government did not calculate the degree of social maturity and especially that is a symbolic space that had its history, people was more aware of themselves, of the role of citizens, and wanted not only to know but also to think, to participate, to be part of the project. It was an advanced space for the development of this conscious and active citizenry, which demands a role not only in voting, but also in the thought, design, and execution of projects. Presentation of project without consulting neighborhood, provoked, not only the rejection of it, but also a genuine citizen reaction that was organized around the movement known as “Another Lesseps Square is Possible” and which basically defended the recovery of the original square, from when it was called Plac¸a de la Creu, and that was a place for citizens and not for cars. As a result of the emergence of this organized neighborhood movement and the agreement reached with the City Council, then it gives way to an exemplary process of citizen participation, led by the architect Itziar Gonzalez, where the locals were able to give their opinion, with necessary technique help about the project, which was jointly designed by local architects and neighbors, giving way to a Lesseps Square, which ended up being a combination of living space and vehicle traffic, and which by some locals this is not yet the definitive way they would like the square to end, the fight is not over for many of the locals. This project is in a pre smart-city phase, where the concept did not yet exist, and where technological tools did not proliferate. The tools of presentation and work of the project were rather classic and face-to-face, and the subsequent process of citizen participation was a very smart city from an innovative, but not technological, point of view, because it was completely analog, with installation of a huge physical model in an emblematic space of the square, where citizens had to go in situ to witness it and give their opinions and comments. What would have happened if this participatory process had taken place 10 years later? Well, we probably would have had an excellent Smart Governance technology scenario where all sorts of digital tools had allowed the project to be displayed to the neighbors, and they could make their contributions by capturing and leveraging their knowledge.

10.11.2 The Diagonal Avenue referendum in Barcelona The second case study is the Diagonal Avenue, for those who have not been to Barcelona, Avinguda Diagonal is a large street that crosses diagonally (hence the name) the entire city of Barcelona, it is a wide avenue, with six center lanes, walkway on both sides, and two side lanes on each side in addition to side sidewalks.

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Conceived as a vehicle connector between end to end of the city, it is an infrastructure that debates with the evolution of cities, increasing environmental awareness, and the increasing role of pedestrians in detriment of vehicles. At one point, local government decides to make a popular inquiry into the future of Avinguda Diagonal, responding to this long-standing citizen and technician debate, specifically talking about the years 2008 10. It is apparently a good solution because citizens are consulted about a basic and symbolic artery of their city. With a total budget of 3.1 million euros, apparently all the steps of the participatory process are carried out correctly, with a phase of information and communication to the citizens, an orderly phase of citizen contributions to the project (capture of knowledge), a correct phase of return of citizen contributions, a public debate on the alternatives, which were two, Rambla or Boulevard, and finally the consultation to citizens (see Fig. 10.3). When consultation arrives, the end result is apparently surprising. The winning option is predicted, but a virtually unannounced option, called Option C (which wins with 79.8% of the vote), means that people disagree neither with the proposal of Rambla, nor with the proposal of Boulevard; thus, returning to zero point with all of the process and the project. What happened, that a seemingly well-conducted process that met its phases perfectly, ended in a citizen disqualification of this size? Beyond gathering the other

Figure 10.3 Bulletin board of Diagonal Avenue referendum in Barcelona. All citizens of Barcelona received this information about referendum [9].

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citizen upsets and more or less the tactical maneuvers from the political opposition, it is clear now that citizens expressed a rejection of the consultation and the previous participatory process. We now analyze their causes. However could we summarize them with more of a political interested operation than a real participatory consultation, as shown in the following text: G

G

G

G

G

G

G

Long duration: More than a year of process and consultation, it was interpreted more as a will to lengthen shine and political publicity of a project, than a real will to involve and consult the public about a key urban project for city development. High budget: A budget of 3.1 million euros may or may not be high depending on the use made. If it is a budget set aside for a world-class project and world-class pioneer and consultation process in many aspects, it may be correct, but if it is interpreted primarily as a political advertising operation in favor of the government of the moment, and not to initial theoretical goals, then it can become a huge public expense with dubious fate. Political use of consultation: Was there a real desire to consult citizens and take their opinion into a strategic infrastructure for the city, or was it simply a political marketing operation to rescue a government that had a project crisis? Citizens interpreted this second. The media focus: When a government focuses all its political action and puts all media focus on a specific operation, if the operation goes well it will be a success but if all the public sources go wrong, prematurely put into operation will cause multiplication of failure. Voting options: The similarity between the two official voting options, La Rambla or Boulevard, led to the conclusion that the final decision was the least and that what was important for local government was the whole media and propagandistic “show” that could generate with all the operation of the query of the Diagonal. This interpretation and upset crystallized in the victory of the curious Option C, which was an amendment to the entire project. Hide Option C: Official propaganda emphasized the two options for urban planning for the Diagonal, Rambla or Boulevard, and deliberately hid Option C, in a show of disdain popular intelligence, reaction, and the decision-making capacity of citizenry, that reacted precisely by exercising its power and knowledge, and by winning Option C, which in practice meant, 1 year later, the fall of government in the following local elections. Computer mistakes: The query is at a time when the smart-city concept was just beginning and has not yet reached the cities in a real way or influenced its policies sufficiently. But well done, the query on diagonal could have been pioneering experience in smart governance in a city that for years had pointed to technological leadership with the existence of the technological district of Barcelona, 22 @, because the consultation was electronic for the whole city. However this also failed, and significant problems in the operation of the electronic consultation challenged this, being the iconic image that has remained of the consultation for history, the one of the Mayor of Barcelona, showing that he was voting electronically at a terminal, which failed exactly at the time of the Mayor’s vote.

In the end, the summary and message of the consultation process on the Diagonal of Barcelona, which connects perfectly with everything we have seen in this chapter. Barcelona government designed the operation, believing that in front of it had a passive population, accustomed to participate little, little involved in political issues beyond voting every 4 years, and no, citizenship had already

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changed, it had matured, it had been democratized, there was a generational change, it was asking for a change in the way from governing and politics and digital revolution was already taking place. The summary and result was that the operation was aimed at a citizen profile that was no longer, it had evolved.

10.11.3 Planning cases: Yinchuan, Dubai, and Neom Let us now turn to radically different examples of urban planning and construction, different not only from a technical but also a cultural and political point of view. They would be examples that we could classify as planning. First of these is Yinchuan [10], a Chinese city near the Mongolian border that was happy to visit twice as an example of a smart city. The peculiarity is that it is made from almost zero, where there was a small rural city, in a few years there is already a city of 2 million inhabitants and growing with its infrastructure and needs covered. The advantage of Yinchuan is that it is a city that could be planned from scratch and is already a smart city. This has allowed governors to take into account all the details. In addition, it has been able to do so with technology by adapting urban planning and infrastructure to technology, and not vice versa. Yinchuan is not an example of the role of citizens in the development of the city, a governing mind on the sidelines, basically because there were no citizens. If that is an example of urban planning from scratch, one should consider all of the smart-city elements. A city, however, which is only stone and technology has no soul, it needs soul, this soul is the citizen, and not only from point of view of inhabiting it and giving it life, but from the point of view in view of having them. Chinese government would do well, and there has already been some interest in this regard, if start to consider this citizen’s view, both from the point of view of simple maintenance or needs, and from the design point of view. If they incorporate citizen knowledge they would be advantageous over other cities because of the freshness and lack of mortgages with which they could do so. Another case, with similar distances, would be Dubai. Dubai is not so much a result of planning but a vision, as it is well explained in the United Arab Emirates, the Shaikh Mohammad’s and his environment vision, out of nowhere, from desert, making it a world-class pioneer city in many ways. We can debate and question the lack of citizen role in the development of Dubai. In addition, one should take into account the more or less democratic nature of governments in the United Arab Emirates, or the role and rights of the normally immigrant labor force, which carries out the infrastructure in Dubai. However we have to admire the example of that, from absolute nothing, to literally the wilderness. From where nomadic people barely survived fishing, they have made a rich, pioneer city in many ways. With many economic and touristic attractions, they have made it a symbol in many ways worldwide. A symbol as well as an opening for what the Arab world represents, as Dubai is a space with massive presence of visitors and also inhabitants of all the world, many of them western, where they can

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live with an important degree of freedom and comfort. And contrary to what many people think, although this project was initially possible thanks to oil, the potential of the city has managed to reverse its initial economic dependence, and today 95% of the city’s resources come from its own capacities, and only 5% of the city’s GDP comes from oil. It is, therefore, an example, in the economic field, of sustainability and economic development beyond oil, of overcoming the dependence that has allowed it to be born, and which would do well to copy many countries and cities in the area, as in fact already done. Dubai has been planned without citizens, beyond the political culture of the country because there were no citizens initially. If Dubai is already a world example city in terms of economic and urban development, imagine what it could be like if it incorporates, as it does, elements of smart city, and if it has the strength of opinion and knowledge that it gives it their natives and their citizens from other parts. If Dubai coordinated these two elements, it could become a world pioneer city in many ways, as well as the exploration and implementation of pioneering smart-city tools and especially smart governance. It has all conditions to do so. In the same line as Dubai would be the Saudi city of Neom [11], planned from scratch by a group of professionals, in this case not only native but from all over the world. Neom is the ideal city from scratch, looking for the best possible location and planning with the advantage of doing it from scratch. Is it an ideal city planned from scratch one that does not incorporate the collective intelligence of its citizens or future citizens? Is smart a city without smart governance?

10.12

Corruption and urbanism

Citizens place the urban environment as the most likely to have corruption practices, or directly the most corrupt. In addition, it is certainly in this area where, in many countries, there have been more cases and more volume of bad practices related to corruption. This gives a new dimension to citizen’s role in urban planning or infrastructure in a city, which is the control of corruption. It is clear that this function directly, and in first instance, corresponds to the judiciary, but with citizens, with tools of information, monitoring and control of the works or urban development of the city, they can play a fundamental and complementary role or as a denunciation.

10.13

Transparency and citizen role in urbanism and infrastructures

There are two major principles and paths through which citizens, in addition to providing knowledge of urban planning or a work of a concrete infrastructure, can control that the work is in accordance with the law and does not deviate from it, they are transparency and participation. We have analyzed the participation in previous

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sections, we see in which and in what processes of an infrastructure citizens can and must have the necessary tools to guarantee the transparency of the processes, transparency that will guarantee us at the same time the arrival of citizen knowledge and control over excesses or deviations from the law. From the outset, it is a proven question that transparency is a tool that fights directly with corruption, the simple publication of numbers, processes, and monitoring of a project already avoids deviations, as well as being basic and necessary information for so that citizens can voice their opinions and capture and leverage their knowledge. All these processes are one of the branches that any smart-city project must have and work on, not only from a theoretical point of view, but also from a practical one. The publication of all data of a project (open data) for monitoring, consultation (transparency) and opinion of citizens (citizen participation), is impossible without deep legal and technological planning. The presentation of data and the technological mechanisms through which citizens can express their opinions give rise to the creation of tools that allow one to combine all of these elements; apps; technological platforms for participation and knowledge management; artificial intelligence that allows us the reading, interpretation and organization of citizen information; and response process, accountability. Therefore we are clearly in this exciting field, at the same time of knowledge and guarantor, and of smart governance. Therefore which principles guarantee access to information and the subsequent action of citizens (see checklist: “An Agenda for Action by Citizens for Access to Information”)? An Agenda for Action by Citizens for Access to Information The principles that are supposed to guarantee access to information include the following key activities (check all tasks completed): _____1. Principle of publicity: This is the principle through which the public administration is obliged to make public the work plans or management plans, the management instruments, and all the agreements that are signed in order to make specific work possible. They are the basic elements of advertising that guarantee transparency and at the same time are the basic data that can allow citizens to control or monitor the project. The principle of publicity affects all the processes of the project, such as the publication of agreements, the publication of the rule, the publication of plans, guaranteeing the telematic access, and the right of access to the projects and help to understand them. _____2. Right to access public information: It is the right that allows citizens to carry out these tasks of monitoring, control, and contribution on a project, the legal principle on which they are subject. It is not enough to have the principle and publish some data, as we have seen before the administration has to create the channels and conditions necessary to capture, in positive, this citizen knowledge, it must be proactive, not only reactive as previous citizen participation policies of open government were. (Continued)

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(cont’d) _____3. Transparency principle: That guarantees the publicity of all processes of elaboration of a project or infrastructure and that it avoids unforeseen operations and guarantees the citizen control. _____4. Principle of open government: Public administrations must take necessary measures to guarantee a two-way administration-citizen dialogue while defining and implementing urban planning projects. _____5. Principle of good governance: Authorities and staff at the service of public administrations must exercise public policies, in this case urban planning, with maximum transparency, quality, and guarantee of accountability. _____6. Governance principle: Public administrations must seek, through coordination, and collaboration mechanisms, the coordination of public policies with each other and the involvement of social and economic agents in order to achieve effective and efficient management. Therefore based on the preceding principles, the public administration must guarantee information in the affected urban planning regulations, urban planning, geographical information, territorial plans, and environmental and landscape impact studies. In addition, citizens can monitor and contribute through the tools of urban planning, participation in the development of plans, substantial modifications of the project, and public action or citizen legitimacy for compliance with regulations.

10.14

Superation of citizen participation topics

When the term “citizen participation” appears, which is in fact what we are talking about applied to the role of the citizen in urban infrastructures in the world of smart cities, and beyond the positive connotations (citizen involvement), there is also a nebula of doubts like what will be the real value of the contributions received, if this will slow the project, if the expense in money and people will be worth it, etc. . . . In part they are caused by the denostation and wear of the term “citizen participation” certainly outdated and linked to obsolete partial strategies, out-of-date and very academic, which have costly intertwined with the effectiveness of government management, except in specific cases of success. Citizen participation linked to open government and smart-city strategies has little to do with isolated and ancient citizen participation, which is why the term should be updated. The academy has not yet been able to find the update, but “citizen involvement” is a term that better reflects the current moment of the citizen’s role in public (and private) governance. These negative cliche´s of a misunderstood citizen participation must be overcome, and the reality has overcome them:

The role of citizens in smart cities and urban infrastructures G

G

G

G

G

G

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“People do not participate”: When a public institution opens a participation process or conducts a citizen consultation, the levels of participation are low compared to the participation, for example, in a normal kind of election. Mistake here is to make this comparison, the right and importance we all have to the electoral participation is not the same, choosing our governments and/or public representatives, in comparison with participation in a specific city theme. It is clear that people will only participate in what interests them, if not they will not do. Only affected citizens will participate, for example, in a participatory process or popular consultation on the renovation of a square or a street, only, for example, its inhabitants or at most the people who use it. In addition, maybe the subject attracts some professionals or fans of urbanism or of environment, but nothing more. Therefore the turnout will be low compared to traditional election appointments. In addition, the root mistake is to confuse quantity with quality, quantity, being a value, is not so important in participatory processes, but quality yes, the conclusions drawn from it. It is much more important to draw three or four well-worked conclusions that can influence or improve a particular project, than if 50 or 2,000 people have participated in the meetings. “Citizen participation paralyzes and slows down”: The process of citizen participation may require extra time in the project, of course, but the wealth, social peace, and symbiosis of the citizens with the project are well worth it. In this chapter we have seen how some projects had to be stopped, turned back, and started again, this time with the involvement of citizens, but now with the consequent waste of time and economic overhead. “Dedication to these topics distracts from other important parts of the project”: It is all about assessing whether or not citizen knowledge is important and what can bring to the project. In this chapter we have argued how important it is. “It is impossible to answer all citizens”: The process of citizen response is fundamental, there is nothing more discouraging for a citizen who has spent an X time he does not have, than to receive absolutely no feedback from anyone where he has contributed his ideas and which may have influenced the project. If we never answer we will not have this citizen motivated never more. Internal citizen response processes are perfectly manageable by structure, first because they are not massive, second because we can use artificial intelligence processes to help answer them, and thirdly because if we do analysis internally of dedications and needs, we will quickly find the formula, workers, and spaces to meet this need, which is far more important than most of the bureaucratic processes to which a large number of workers are dedicated. “It is a fashion”: To despise citizen knowledge is a recklessness and a luxury that we cannot afford. The times when four people decided everything in an office without having the general knowledge and the knowledge that citizens and workers can bring, have passed to better time. When universal suffrage did not exist, the reasons given were that the people were not ready to voice opinions. We will now be in a second phase of this, will we despise citizens and their knowledge because we consider that they are not ready to do anything? “Transparency goes against the right to privacy”: In first term, the right to privacy is guaranteed by the same laws of transparency, and for example, as we enter in the world of open data, we move in parallel, and hand in hand in the world of data protection. Not to consider the side effects of a necessary reform we must stop doing it, that is, by protecting ourselves and minimizing them.

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“It is a way of removing the obligation to decide”: Nothing farther from the truth, opening up to citizens does not forget, but legitimizes the decision process that continues to be in hands of people we have chosen to do it or who that leads the company in private sector, but they will do so in a richer way, counting and integrating the entire team.

10.15

Summary

The summary of this chapter would be the evolution of citizen’s role in society, and also in the evolution of cities and more specifically of their infrastructures. Politics cannot be done ignoring citizens, cities cannot be done ignoring their inhabitants, and infrastructure cannot be made ignoring of those who will use them. Society and citizens have been changing, evolving over time. From that society without studies and rather passive, we move to a very well-educated society, conscious, and eager and able to get involved and participate. To use their knowledge is a duty, an obligation, but also a practical benefit in form of the enormous knowledge and great collective intelligence resident in citizens. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

10.16

Chapter review questions/exercises

10.16.1 True/false 1. True or false? The smart city is a concept that begins in the second decade of the current century as a fuzzy marketing principle, and without clear content beyond an appearance linked to a city strategy. 2. True or false? From the initial relationship between citizens and smart cities, comes a hybridized concept: smart citizens. 3. True or false? The “crisis of politics” would be a growing crisis of the confidence citizens have toward the institutions that theoretically represent them. 4. True or false? From passive citizens without tools, to active citizens that are more educated (already born in mature democracies), the adaptation of governments and public administrations are absolutely necessary and indisputable. 5. True or false? From theory to practice, the first formulas have already emerged through which the logic of citizen integration in public, or more recently in private governance, have already begun to be applied.

10.16.2 Multiple choice 1. ___________________ is where a citizen wants to know what is inside an administration, what is happening there and what is done with their taxes: a. Pedagogy b. Human centered c. Sufficient

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3.

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d. ICT enabled e. Transparency To understand the political and administrative language; what politicians have said; and the facilitation of understanding it, is known as: a. Openness b. Safety c. Pedagogy d. Economy e. All of the above The clearing away of structures, administration, attitudes, and policies in general is known as a. Economies b. Infrastructure systems c. Urbanization d. Autonomous systems e. Opening Where citizens want nearby public representatives at street level to talk and have a dialogue with them; as well as, get closer to them, is known as: a. Proximity b. Readiness c. Participation d. Involvement e. All of the above Open government is or is not: a. Closed b. Endorsed c. Homogeneous d. Transversal e. Innovative

10.16.3 Exercise 10.16.3.1 Problem What is the role of citizens in smart cities and urban infrastructures?

10.16.4 Hands-on projects 10.16.4.1 Project What is the role of citizen participation in the development of smart cities?

10.16.5 Case projects start here 10.16.5.1 Problem Do research on how to use a holistic approach in the assessment of governance and policy decision-making in the context of smart and sustainable cities.

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10.16.6 Optional team case project 10.16.6.1 Problem How do cities engage with their communities in the process of making a city smarter?

References [1] I. Ivanko, Moskva News Agency. Russia bans sale of smartphones without Russian apps, The Moscow Times, December 2, 2019 ,https://www.themoscowtimes.com/ 2019/12/02/russia-bans-iphone-sale-without-russian-apps-a68313.. [2] L. Kuo, China brings in mandatory facial recognition for mobile phone users, The Guardian, December 2, 2019 ,https://www.theguardian.com/world/2019/dec/02/chinabrings-in-mandatoryfacial-recognition-for-mobile-phone-users.. [3] TikTok sorry for blocking teenager who disguised Xinjiang video as make-up tutorial, The Guardian, December 2, 2019 ,https://www.theguardian.com/world/2019/dec/02/ china-brings-in-mandatory-facial-recognition-for-mobile-phone-users.. [4] J. Gehrke, Putin says Trump crackdown on Huawei constitutes the ‘first technological war,’ Washington Examiner, June 7, 2019 ,https://www.washingtonexaminer.com/ policy/defense-national-security/putin-says-trump-crackdown-on-huawei-constitutesthe-first-technological-war.. [5] O. Little. Spanish digital decree’ goes against European values, says Digital Policy Minister,. Catalan News, November 28, 2019 ,https://www.catalannews.com/politics/ item/spanish-digital-decree-goes-against-european-values-says-digital-policy-minister.. [6] Technical Office. A tool for digital rights and freedoms of Catalonia open to the participation of civil society, Punt Tic Catalan Government, July 10, 2019 ,http://punttic. gencat.cat/en/article/tool-digital-rights-and-freedoms-catalonia-open.. [7] The White House, Open government directive, December 8, 2009 ,https://obamawhitehouse.archives.gov/open/documents/open-government-directive.. [8] United Nations Department of Public Information Sustainable development goals, Knowledge Platform Sustainable Development Goals. ,https://sustainabledevelopment.un.org/?menu 5 1300., 2015. [9] Diagonal Barcelona Website. ,https://diagonalbarcelona.wordpress.com/altresdocuments/butlleta-participacio/.. [10] S.D. Chowdhury Smart cities in China: a short visit to YinChuan, TM Forum Website, December 29, 2105 ,https://www.tmforum.org/press-and-news/smart-cities-in-china-ashort-visit-to-yinchuan/.. [11] Neom Official Website. ,https://www.neom.com/en-us/..

Smart city and metropolitan governance

11

Mats Andersson Urban Management Consultant, San Francisco, United States

11.1

Introduction

As the world is becoming increasingly urban, it is also becoming increasingly metropolitan. Cities have expanded outward, and satellite cities and towns have over time become more closely connected to an urban center. Urban development changes the character of an area, but political boundaries tend to be quite stable. Many cities have over time become more economically interdependent with their neighboring cities (and peri-urban and rural areas), constituting a single economy and labor market, usually including various local government jurisdictions—a metropolitan (metro) area or city-region. The term metropolitan (metro) areas generally refer to cities with a large urban core plus adjacent urban and rural areas that are integrated socially and economically with the core [1]. It forms a community with common interests and opportunities for joint action. Transport and communications advances tend to extend such functional economic areas, facilitating people to live in one local jurisdiction, work in another, and possibly shop in a third. The economic links between the core and the area’s periphery can become so close, that one part cannot succeed without the other. Demarcation of such an area is usually either as: (1) a contiguous built-up area; (2) an area based on distance or traveling time from the core city center (often an area with 30 40 km radius or 1 hour travel time); or (3) an area based on significant functional relations, for example, defined by a proxy of at least 10% of daily commuting between the areas by the working population. A smart city is a technology-intensive city, with extensive use of sensors and interconnected devices to gather and analyze data in real time to deliver public services more efficiently and effectively. For example, trash cans with sensors that indicate when they are full, informing trash collectors on what routes to take. Or residents using a smartphone application or messaging service to report full trash cans. A city can create mechanisms to gather information and cultivate the relationship with its residents by encouraging feedback—leveraged by technology—to help improve service delivery.1 1

Other examples of the application of technology for improved public service management are: (1) electronic advance ticketing and single smart card for multiple travel and transport applications; (2) centralized traffic prediction and geographical tracking of service units and vehicles; (3) query system for

Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00011-5 © 2021 Elsevier Inc. All rights reserved.

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However, smart cities also need smart governance arrangements to make cost-effective use of the technology. Many challenges posed by the digital revolution and the role of information in urban environments, need to be addressed at a metropolitan scale. The digital transformation enables new ways to create, share, use, and access data. It brings new ways of working and managing; infrastructure changes related to security, cooperation, and interoperability; and a digital divide that can affect social cohesion and equality.

11.2

How can cities benefit from cooperation on the smart city subject in a metropolitan area?

The mismatch of economic integration and political fragmentation in metropolitan areas creates a need for collaboration among the local governments, to seize opportunities for efficiency/cost-effectiveness and prevent wasteful competition (see checklist: “An agenda for action for coordinating a collaboration effort among local governments with regards to smart cities”). An agenda for action for coordinating a collaboration effort among local governments with regards to smart cities Specifically, regarding smart cities, municipalities can benefit from coordination activities (check all tasks completed): _____1. Joint strategic planning of smart city applications to ensure: (i) harmonized policies and actions; (ii) compatible technologies (as required); and (iii) coherent evolution of the smart-city applications in the area. _____2. Metro-wide data capture to ensure adequate input for infrastructure and other planning to identify and inform potentials for joint initiatives at metropolitan scale; highlight possible duplications (waste) and gaps; and measure outcomes at the metro-area level. _____3. Capturing economies of scale for solutions and ongoing operations through joint initiatives by the local governments in the area. _____4. Implementing a pilot in one jurisdiction and assessing potential for metro-wide application, or piloting different technologies in different cities and measure impacts in a controlled manner. (Continued)

service requests; (4) electronical service provision in real time based on user requests (eGovernment); (5) ICT supported emergency services and disaster management/early-warning and response systems (e.g., early detection of floods and storms, or responding to environmental hazards and public service disruptions related to traffic, air, water, or heat issues); (6) remote reading of water and heat meters and prepaid utility charges; (7) automated sensor-based street lighting system. Smart government would also include, for example, collection efficiency through automated payments, optimization of schedules and management of service provision, and real-time access to government workflow using digital addresses for service provision.

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(cont’d) _____5. Creating a joint development unit or institute (a focal point) for research, training and joint planning, identifying high-value potentials for the area, driving coherent overall solutions, and possibly function as a “control center” for some implemented applications. To be stronger by acting together may simply translate to cost savings or lower transaction costs by joint procurement (anything from sensors to full ICT systems) and joint staff-training programs. It may also involve pooling of funds for a facility or equipment for shared use.

11.2.1 Intermunicipal coordination increases overall productivity The governance structure of agglomerations that include multiple municipalities is known to have a direct impact on the overall productivity. Work by OECD [2,3] shows that a metropolitan area of any given size with twice the number of municipalities is associated with around 6% lower productivity. The existence of a governance mechanism at the metropolitan level can cut this by almost half (to 3%). Networked public services, for example, power, transport, water supply, and sewerage service tend to be prime candidates for smart technologies, for example, with remotely controlled consumption meters, smart card readers, etc. Such network services are often also prime candidates for metropolitan-scale, coordinated solutions to gain efficiencies. Other services which lend themselves to metropolitan-scale approaches are disaster risk management (e.g., flood control), emergency services (e.g., addressing health epidemics), and air pollution control.

11.2.2 Difference in financial capacity among the cities is a common challenge Large differences may exist in the tax base, creating significant differences in the service provision. This can be addressed through harmonization of local taxes and fees or arranging some area-based revenue-sharing (beyond what is addressed through an inter-governmental fiscal transfer system in the country). Such solutions have, for example, been applied in the Twin Cities (Minneapolis and St. Paul) in the United States, and in the metropolitan areas of Marseilles and Lyon in France.

11.3

What metropolitan governance arrangement is needed?

As a minimum, a forum for periodic intermunicipal dialogue among local government executives in the metropolitan area is needed, either specifically set up to

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address smart city matters, or a cooperation arrangement with a broader scope. More comprehensive arrangements are also found internationally.

11.3.1 An Inter-Municipal Forum or Council An Inter-Municipal Forum or Council is a horizontal coordination arrangement among local governments in a one-tier fragmented local governance situation, usually established by the local governments in the area (bottom up). Such a light forum or council can be a low-risk arrangement for the local governments. Decisions sometimes need to be ratified by each participating local government council. The arrangement exists under names such as: committee, commission, partner agreement, working group, consortium (e.g., in Brazil), association of municipalities, mancomunidad (common across Latin America with legal agreement known as Convenio), Metropolitan Council or Council of Governments, common in the United States, and in France called communaute´ urbaine (urban community) or syndicats inter-communaux (syndicate). They can be established ad hoc for specific joint initiatives or with broader mandate for the longer term, for example, for ongoing development of the smart city concept in the metro area. The local governments would join forces when it clearly benefits them and their constituents, compared with acting independently. If one municipality in the area—usually a larger one—is having significantly more competence or facilities for a subject, the other municipalities may contract (outsource to) that municipality to address that subject for them, for example, developing and implementing (and possibly even operating) some smart city facilities or applications. In summary, advantages (1) and disadvantages (2) of these basic intermunicipal collaboration approaches are: G

G

G

Ad hoc cooperation among local governments/case-by-case joint initiatives: 1 Useful for areas where limited interdependencies exist among the local governments 1 Can be an initial stage to gain experience and build trust for joint efforts 1 Useful approach when more permanent and formal arrangements are constrained by politics or prohibited by legal frameworks 2 Usually limited in scope (e.g., for a specific technology application or an urgent issue) 2 No commitment to address smart city matters on a comprehensive or longer-term basis Committee, commission, working group, consortium, partnership, consultative platforms, etc.: 1 A flexible approach. It can be a temporary or permanent body and can have character of a network rather than an institutional body. 2 Usually with an advisory role only with approval of proposals by the participating governments. Contracting among local governments: 1 One local government can specialize in technology applications for a particular public service or function, for the benefit of all local governments in the metro area. 1 Useful when one of the local governments in the area dominates in terms of human and financial capacity.

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2 The contracting local government still needs to monitor the quality and coverage of the service provision (contracting out does not mean abdicating responsibility for the service or function). 2 Risks: access by residents to the service provider may be affected; and the accountability may be weakened or unclear to residents.

11.3.1.1 The process is as important as the outcome For a governance arrangement to be effective and sustainable, an extensive process of stakeholder consultation is required. While a cost-saving argument may be attractive to all, to achieve broad political support may still require significant efforts. Since proposals may create—at least perceived, if not real—winners and losers, factors other than economy, efficiency, and equity may determine the evolution of a metro area governance system.

11.3.1.1.1 Ensure strong support by the local governments

A prerequisite for effectiveness is that the forum or council has the active support and commitment of all local governments involved. Individual local governments may participate in only some parts of the metro-level arrangement, which may facilitate agreement. While cooperation among local governments may be encouraged by incentives from a regional government, through intergovernmental systems, legal frameworks, or specific financial incentives; international experience shows that no governance arrangement becomes effective and sustainable unless the local governments involved are actively supporting it [1].

11.3.1.1.2 Start simple and design for success

It is important that initial metropolitan coordination efforts are reasonably visible and become positive experiences to build on (have low risk of failure). The process may, for example, initially focus on noncontroversial items, for example, a joint training program; or a public service which has obvious cooperation benefits (e.g., flood protection, crime prevention, or air pollution).2

11.3.1.1.3 Agree on resourcing

Good intentions alone are not enough. Before launching a forum or council—particularly one that is intended to be permanent—required financing to make it successful needs to be agreed upon among the involved parties. This can, for example, include formula-based sharing of service expenditures, coordinated revenue mobilization through user charges, and/or a common budget for metropolitan-level initiatives and investments. 2

As another example, in 2010, the cities of the Helsinki Metropolitan Area began sharing public data for anyone to use freely through Helsinki Region Infoshare (HRI), a portal for public information about Helsinki and its surrounding municipalities. These open datasets, available through a web platform [4] has made it possible for citizens to develop applications such as “Blindsquare,” which helps blind people negotiate their way around the city, and “Recycling in Finland” where users can identify the closest recycling point for a particular product anywhere in Finland.

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11.3.1.1.4 Be clear on “Who does what”

This includes clarity on the role and authority that is vested with a new coordination body. In addition, this is not only important for the directly involved in a governance arrangement. It is also important to publicize so that the public at large will know who they can hold accountable for what. For example, although it may be effective to do strategic planning jointly for smart-city technology applications in the metro area, implementation of many applications may be most efficiently done locally by each local government.

11.3.2 More comprehensive arrangements Some institutional arrangements are established bottom up (i.e., through initiatives and agreements among the local governments in the metro area) and some top down (i.e., by a regional or national government). More comprehensive institutional models for metropolitan collaboration, within which smart city matters can be addressed, are: G

G

G

G

Metropolitan authority/is (sometimes called special purpose districts). A metropolitan government (a separate metropolitan-level government for some functions) A regional government (provincial or state government) fulfilling the metro coordination. A consolidated local government (by amalgamation of municipalities or land annexation).

International experience has shown that there is no one-size-fits-all solution because of local and national differences [5]. An effective governance arrangement should facilitate capturing economies of scale and service efficiencies, and address spillovers and regional disparities. It should also prevent negative impacts or risks that an arrangement may have on the access of citizens to their local governments, the degree of public participation in decision-making, and the responsiveness and accountability of the government entities in the area. The models are briefly explained below; details and global examples are found in [6]: G

G

Metropolitan authority/ies, for single sectors or one authority addressing multiple sectors. It can be a planning authority, a service delivery authority, or a more comprehensive planning and service delivery authority. Single sector authorities are common for infrastructure services, such as public transport, water supply, and sewerage services. An example of a multisector authority for selective regional services and policies is found in the Metro Vancouver Regional District in Canada, which is under the direction of 23 local governments. It provides a range of services, including human resource management services for many member governments. Separate metropolitan-level local government. This is a separate local government for certain functions, in parallel to other local governments in the area (e.g., as in Seoul, South Korea; Tokyo, Japan; and Quito, Ecuador). In a few countries, a true two-tier local government structure exists, with the lower tier governments reporting to a second-tier municipal government, for example, as applied across China, and partly in London, UK. An upper tier metro-level government (or separate local government, as called here) should be responsible for “services that provide region-wide benefits, generate externalities,

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G

241

entail some redistribution, and display economies of scale,” while lower tier governments should be responsible for services that “provide local benefits” [5]. Regional/provincial government. Metropolitan coordination needs can also be addressed —at least to some extent—by a (usually already existing) regional/provincial government, as is the case, for example, in Mexico, India, and Chile. Consolidated local government. This is a local government jurisdiction which covers its metropolitan area (or most thereof), usually created through amalgamation of local governments or annexation of land. While area-wide planning and coordination is in principle facilitated, coordination among local service offices may still be a challenge. The main international example is the eight large metropolitan municipalities created in South Africa in 1999 as part of redrawing the municipal map in that country at the time.

More than one model can exist in a metro area at the same time. For example, one or more sectoral authorities in parallel with any of the other models; or functional responsibilities may be divided between a regional government and another arrangement. Coordination may be needed at different scales for different purposes. The appropriate area for coordinated smart city policies and applications may be even larger than the commuting area of a large city (its metropolitan area).

11.4

What are the obstacles to collaboration across jurisdictions?

11.4.1 Parochialism is a common phenomenon “What is in it for us?” is an understandable reaction to suggestions for joint actions among local governments. Involved institutions may have divergent interests and political agendas, or simply protecting power. Inhibitors to greater collaboration may be reluctance on the part of elected officials to give up direct control or influence over matters related to their constituency—their voters.

11.4.2 The level of trust may not be strong enough To be effective, a metropolitan governance arrangement needs to have the support and commitment of all (or at least most) local governments involved. The rationale for collaboration at a metropolitan level may be financial, pointing to cost savings; or the motivation could come from equity concerns. It can also be triggered by pressure from the local civil society and private sector for actions at the metropolitan scale. However, if the government officials have insufficient trust in the process, proposals tend to fall on death ears.

11.4.3 The prerequisites for effective teamwork are not there This requires: (1) a common objective and clear understanding of the benefits of the cooperation; (2) a certain level of mutual trust among the participants (usually earned over time); and (3) a recognition that differing views constitute strength

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rather than weakness to arrive at the most effective overall solution. If the perception of a common objective, or the trust, is not strong enough at the local level, a higher level (regional or national) government tends to step in to take an active facilitating role, or simply arrange a resolution on the subject in question. Coordination on smart city may be addressed application by application if a joint strategic framework or plan would exist.

11.5

Application of the intermunicipal cooperation arrangement

Beyond the choice of arrangement, effective governance also depends on how an arrangement is implemented. This applies to both the basic intermunicipal forum or council; as well as, to a more comprehensive approach (see checklist: “An agenda for action for the application of a systematic approach”). An agenda for action for the application of a systematic approach A systematic approach may be applied along the lines of the smart city development framework outlined by the World Bank [7] for cities in developing countries that include the following key activities (check all tasks completed): _____1. Diagnostic. Carry out a forward-looking diagnosis to inform a strategic investment plan for the next 5 10 years. _____2. Prioritization. In parallel, interact with stakeholders and resource entities (civil society, universities, etc.) to define priority needs that may lend themselves to technology/smart city type solutions. _____3. Solutions. Generate solutions, for example, either by (a) developing specific applications directly; (b) partnering with academia and the private sector to create prototypes and concepts to test in the city; and/or (c) participating in events such as hackathons and application challenges to crowdsource solutions, spurring innovation, and entrepreneurship. This process may start a virtuous cycle of feedback from citizens and government responses to create new or improved services. _____4. A permanent space. To maintain the momentum of this process, a space such as an Innovation Lab may be needed that facilitates ongoing interaction between stakeholders and can test new ideas and solutions in a fail-safe environment. It may be combined with a joint operations center for management of selective activities at metropolitan scale.3 (Continued) 3

In 2010, following heavy storm, Rio de Janeiro decided to create a Rio Operations Center that operates 24 hours a day and is staffed by hundreds of officials from about 30 city departments. The responsibility of the Center is to control the city’s daily operations, integrating several departments involved; and to manage crisis and emergency situations. The model has had many benefits for the day-to-day

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(cont’d) _____5. Networking. Beyond cities of a metropolitan area going through this process together, they may join or create a larger network to share applications and practices and build on what they learn from others. Existing networks are, for example, the European Network of Living Labs and the Open Cities initiatives in the United States. At an early stage of metropolitan level coordination, emphasis can be on identifying a few initial joint initiatives with high probability of success, to build trust and momentum. Low-risk examples to start with can be joint procurement to save on cost, joint training programs for staff, establishing a smart city research entity, or marketing (branding) the area as a smart metro area. A strong advocate (champion) can play a pivotal role in steering change and creating or maintaining momentum for active cooperation. A case needs to be made for collaboration and joint efforts in each particular case. A clear financial/economic case is usually a powerful rationale for a joint initiative and hard to argue against. Active engagement by civil society and the local private sector on smart city matters, for example, through their associations or the local media, may also trigger demands for actions at the metropolitan level. As the participants create a longer term technology investment plan, they can start leveraging existing technologies (e.g., mobile devices, smartphones, and broadband access) to cocreate smart civic applications that will help improve public services and the overall quality of life for the residents in the area; a smart city or metro area where all stakeholders build what the European Network of Living Labs calls “Public-Private-People-Partnerships” [9], an ecosystem where government services and investments are continuously being improved through feedback from citizens, and where academia and the private sector create opportunities for new businesses. Emphasis should not only be placed on solutions that may come out of early iterations, but on the sustainability of the approach applied.

11.6

Summary

Cities in a metropolitan area can benefit from collaboration on their smart city developments. Opportunities that can be seized jointly for efficiency/cost-effectiveness for all include strategic planning; area-wide data collection for planning; capturing economies of scale through joint procurement, research and training; piloting management of the city. For example, data gathered enables the identification of neighborhoods with higher dengue fever infection rates. Traffic emergency time response has been reduced with citizens alerted about traffic situations and being redirected to the best routes. The Center has become a global model showing the benefits that can be derived from collaboration, alignment, and data sharing across city divisions. A similar approach can be applied across a metropolitan area [8].

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technologies; and creating a joint body for their smart city development (possibly also for operations of some applications). The coordination can be through an intermunicipal forum or council, or as part of a more comprehensive metropolitan governance arrangement. An effective collaborative approach can result in a better understanding of the potential of smart city applications and better outcomes for the cities. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

11.7

Chapter review questions/exercises

11.7.1 True/False 1. True or False? To be stronger by acting together, may simply translate to cost savings or higher transaction costs by joint procurement (anything from sensors to full ICT systems) and joint staff-training programs. 2. True or False? The governance structure of agglomerations that include municipalities is known to have an indirect impact on overall productivity. 3. True or False? Small differences may exist in the tax base, creating significant differences in the service provision. 4. True or False? As a maximum, a forum for periodic intermunicipal dialogue among local government executives in the metropolitan area is needed. 5. True or False? An Inter-Municipal Forum or Council is a vertical coordination arrangement among local governments in a two-tier fragmented local governance situation, usually established by the local governments in the area (top down).

11.7.2 Multiple choice 1. What approach can be a temporary or permanent body and can have character of a network rather than an institutional body? a. Flexible approach b. Useful approach c. Advisory approach d. Financial approach e. Preferred approach 2. What has shown that there is no one-size-fits-all solution because of local and national differences? a. Effective governance b. Responsiveness c. Accountability d. International experience e. All of the above 3. What can be a planning authority, a service delivery authority, or a more comprehensive planning and service delivery authority? a. Metropolitan authority

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b. Separate metropolitan-level local government c. Regional/provincial government d. Consolidated local government e. Parochialism 4. What is an obstacle to collaboration across jurisdictions? a. Systematic approach b. The level of trust may not be strong enough c. Infrastructure of cities d. Smart governance e. All of the above 5. Who can play a pivotal role in steering change and creating or maintaining momentum for active cooperation? a. Participant b. Stakeholder c. Government official d. Financial planner e. Strong advocate

11.7.3 Exercise 11.7.3.1 Problem Why is metropolitan governance needed?

11.7.4 Hands-on projects 11.7.4.1 Project Why is smart governance viewed as an emerging domain of study that attracts significant scientific and policy attention?

11.7.5 Case projects 11.7.5.1 Problem Do research: With regards to metropolitan governance, how would you develop a framework for future cooperation with metropolitan regions?

11.7.6 Optional team case project 11.7.6.1 Problem Do research: What is the impact of smart city technologies on city operations, service provision, quality of life, and local economic development?

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References [1] E. Slack, R. Chattopadhyay (Eds.), Governance and Finance of Metropolitan Areas in Federal Systems, Forum of Federations, Oxford University Press, 2013. [2] R. Ahrend, E. Farchy, I. Kaplanis, A. Lembke, OECD Regional Development Working Papers What Makes Cities More Productive? Evidence on the Role of Urban Governance from Five OECD Countries, OECD Publishing, Paris, 2014. [3] OECD, The Metropolitan Century: Understanding Urbanisation and Its Consequences, OECD Publishing, Paris, 2015. [4] ,www.hri.fi.. [5] E. Slack, Policy Research Working Paper Managing the Coordination of Service Delivery in Metropolitan Cities—the Role of Metropolitan Governance, The World Bank, 2007. [6] GIZ-UN Habitat, Unpacking Metropolitan Governance for Sustainable Development. Discussion Paper, 2015. [7] ,https://www.worldbank.org/en/topic/digitaldevelopment/brief/smart-cities.. [8] ,https://use.metropolis.org/case-studies/rio-operations-center#casestudydetail.. [9] ,http://www.openlivinglabs.eu/..

Distributed energy in smart cities and the infrastructure

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Essam E. Khalil Faculty of Engineering, Cairo University, Cairo, Egypt

12.1

Introduction

This introduction describes the main issue of energy storage in a smart built environment. It is followed by the basics of smart microgrids and how to balance smart and sustainable actions.

12.1.1 Energy storage As wind and solar become pioneering technologies and exhibit even more rapid adoption by publics and governments, one of the difficult hurdles that smart cities will need to overcome is the energy storage issue. This results from the fact that current grid has very little storage capacity, meaning that output fluctuations from wind or solar energy would necessarily increase the complexity of operating such systems. Today’s most prominent energy storage technology is the use of lithiumion battery, due to primarily its high energy density and low self-discharge rates. This type of batteries is used typically for short-term storage, but can also be found in some modern electric vehicles (EVs) as well as on smaller power grids. Newer types of batteries are expected to revolutionize the energy storage market not only because are they able to provide hundreds of megawatt hours at grid scale, but also they can maintain that supply for over 20 years without any loss in storage capacity. What is needed is to smooth out the power generated by intermittent renewable energy sources using these batteries to ensure that no energy is unnecessarily wasted.

12.1.2 Smart microgrids The Internet of Things (IoT-enabled) smart grids are powered by demand-response systems. In addition to reducing peak load and the need for larger grid infrastructure, smart grids; combined with smart meters; would allow energy derived from solar and wind sources to be better optimized. Another concept that has taken root and gathered a fair amount of support from eco-conscious homeowners is the concept of microgrids, a localized power grid that can operate either in conjunction with the main electrical grid or independently of it as an “island.” Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00012-7 © 2021 Elsevier Inc. All rights reserved.

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The basic concept behind microgrids is to break the hegemony of a centralized energy system, and make distributed energy resources infrastructure more resilient and reliable. Essentially, by making homeowners and businesses interactive collaborators with the grid, microgrids can put the power back in the hands of “prosumers” in that they can use as well as distribute and profit from the energy they generate amongst themselves. The final goal is to democratize the energy sector and create resilient, interconnected neighborhoods, or “smarthoods,” where all the connected components that make up an energy network are entirely self-sufficient.

12.1.3 Smart and sustainable balance Now it is clearer with adequate certainty, that if cities do not act now to address climate change, human settlements may find us in a far more precarious position in the future. As economies turn to transit to smart cities, reliability, and resilience are becoming increasingly prominent determinants of newer energy models. Governments that are able to streamline their core services using IoT, and show that sustainability is at the top of their agenda, will attract more people and businesses, thus gaining a competitive advantage over other economies.

12.2

Smart cities

Energy, water, transportation, public health, and safety are orchestrated in smart cities to provide a harmonized smooth operation of the critical infrastructure. This in turn would ultimately provide a clean, economic, and safe environment. The required logistics should be collected and provided to the public by all available means through, among others, social media networks enhancing efficiency, conservation, and safety of residents. A smart grid would alone provide three things. Firstly to modernize the current power systems through proper self-healing designs, automation, and remote monitor and control. Secondly, it would provide information to educate different consumers about their energy usage, costs and alternative options, enabling them to decide on how and when to use electricity and or fuels. Thirdly, it would provide safe, secure, and reliable integration of renewable energy and distributed resources. Energy, water, transportation, public health and safety, and other aspects of a smart city are managed in harmony to support smooth operation of critical infrastructure while providing for a clean, economic, and safe environment. The smart grid technologies which are utilized in smart cites include G

G

G

G

G

G

Distributed power generation Automatic distribution system Smarter homes Advanced metering systems architecture Energy storage with grid integration Electric vehicles

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12.2.1 Distributed power generation Distributed power generation sources include the use of solar, wind, biomass as well as fuel cells. Distributed power generation reduces the cost of transmission and distribution. Other benefits include mass production and flexibility, energy efficiency as well as emission reduction. In a smart city it will be possible that consumers can have their own renewable generation source to sell back the excess power generated to the utility. This will aid utilities to better manage the peak demand and also to reduce the need for building new transmission lines.

12.2.2 Automatic distribution system An automatic distribution system enables real-time observation; close monitoring and control of the entire distribution system, in order to attain stability in the grid through a centralized master control center. Automatic distribution system (ADS) includes substation automation system, feeder-level automation, and customer-level automation. Some of the ADS applications relevant to smart cities are outage time management system, voltage regulation, fault isolation and sectionalization, load management, demand side management, . . . etc.

12.2.2.1 Smarter home Smart homes are normally equipped with smart and intelligent appliances that can communicate with each other. These also enable remote control and monitoring of the appliances from anywhere using mobile phone or other Internet connected devices. Some of the features of a smart home are lighting: automatic light control based on a time cycle or based on occupancy sensor, brightness control, and remote control of lights through Wi-Fi or internet.

12.2.3 HVAC and audio visual Heating, ventilation, and air conditioning (HVAC) is concerned with the remote control of the building’s heating and air-conditioning systems through an Internetcontrolled thermostat. While audio visual is concerned with the security system that is integrated with the home automation system, it should provide remote surveillance of security cameras, central locking of all perimeter doors and windows, detection of unauthorized movement through motion detractors and notification alerts to the users via cell phone.

12.2.4 Advanced metering system infrastructure Advanced metering system infrastructure (AMSI) provides two-way communications between utilities and consumers through an integration of smart meters and Internet communication networks. Accurate measurement, automatic identification of unmetered connections, instant alarm in case of illegal tampering detection,

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reduced line losses due to reduced maximum demand are some of the features of AMSI in smart cities.

12.2.5 Energy storage with grid integration Renewable energy, coupled with energy storage, can provide reliable and quality power to a smart city. The excess energy that is generated from renewable sources, such as solar or wind is stored and used when the demand is higher thus reducing the maximum demand of the smart city. Battery storage is a well-proven technology that would be the most suitable for smart cities.

12.2.6 Electric vehicle EV derives all or part of the energy required from electric grid with electrical energy stored in battery for propulsion. Merits of EVs are simple construction, low maintenance, no emission, and thus protects environment, low noise, and more efficient. Thus electrification of personal vehicles and public transport is essential for attaining smart transportation.

12.3

Instrumental procedures in smart cities

Now, let us look at the main procedures to be followed by smart cities. This involves the incorporation of energy efficiency practices; smart grid and the main characteristics of the smart grid; and, smart governance, ending with the use of information and communication technologies (ICT).

12.3.1 Energy efficiency practices Energy concerns are also a key feature of “smart cities.” Energy-efficient practices are adopted in transportation systems, lighting as well as all other services that utilize energy. Tariffs mechanisms are structured to encourage conservation with incentives. Public awareness programs are expected to induce a culture of conservation. Efforts for improvement should focus on building material used, the transport system, sewerage and water supply systems, street lighting, air-conditioning systems, and energy consumption in buildings.

12.3.2 Smart grid A smart grid is an electricity network that utilizes digital technologies to monitor and manage the transport of electricity from the generation sources to meet the varying electricity demands of end-users. The needs and capabilities of all generators, grid operators, end-users, and electricity market stakeholders are coordinated by smart grids to efficiently operate all system components, thus minimizing costs and environmental impacts while maximizing system reliability, resilience, and stability. Smart grids would include electrical transmission and distribution systems

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and interfaces with power generation, storage, and end-users’ sides (see checklist: “An agenda for action for the implementation of the main characteristics of the smart grid”). An agenda for action for the implementation of the main characteristics of the smart grid Smart grid requirements include the following key activities (check all tasks completed): _____ 1. Rapid detection, and analyses of load behavior with quick response to restore loads. _____ 2. Supports and incorporates the consumer _____ 3. Characterize load behavior in grid design and operation. _____ 4. The grid should resist, mitigate physical/cyber attacks _____ 5. The grid should provide quality power in harmony with needs of consumers. _____ 6. The grid should also accommodate a variety of resources, including demand response, combined heat and power systems, wind turbines, photovoltaic cells, and end-use efficiency. _____ 7. Fully enabled to be supported by competitive electricity markets. _____ 8. Active participation of stakeholders

12.3.3 Demand management Smart cities would create incentives for savings and disincentives for excessive consumption and enhance supply to meet the demand. This could be achieved through rate structures that are affordable as well as low levels of consumption. For transport systems, the demand management efforts will promote the use of nonmotorized modes of travel or public transport and discourage personal motor vehicles.

12.3.4 Improved access to information A very important feature of all smart cities is good citizen access to information. Whether it is regarding city specific data or the measures being taken by municipal bodies or information relating to various service providers such as transport and similar information relevant for potential investors has to be conveniently available. This could be through multiple channels internet, mobile apps, radio, TV, printing media, etc.

12.3.5 Environmental sustainability Smart cities that are newly planned, should be environmentally sustainable to create a more liveable and healthy environment. This would mean not only to improve the air quality but also to reduce the waste of water, electricity, fuel, etc. Star rating is

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being done for most electrical appliances, air conditioners and in the building industry. All automobile vehicles should also be star rated to indicate their energy efficiency.

12.3.6 Application of Clean Technologies Application of clean technologies to overcome pollution in the world, eliminating any severe health hazards is drastically needed. In smart cities buildings, transport, and infrastructure should be energy efficient as well as being environmentally benign.

12.3.7 Use of ICT The extensive use of ICT is a must and only this can ensure information exchange and quick communication. Most services will need to be ICT enabled, and this often helps reduce the need for travel. The ability to shop online or book tickets online or converse online is very powerful ways of reducing the need for travel, thereby reducing congestion, pollutants, and energy use. An extensive use of ICTenabled services will need a sound communications backbone.

12.3.8 Citizen participation A Smart city would communicate well with its inhabitants and enlists their support in everything being done. The culture of closed environment working would need to end as people are often the biggest support base for any initiative a city takes up. Social pressure on other citizens can often dilute resistance and facilitate a greater degree of civic discipline.

12.3.9 Smart governance In many countries, current government setup maybe rather fragmented with each department working in isolated silos. The result of this is lack of coordination, which is reflected in form of poor services to the individual citizens. Therefore, for cities to become smart, it is an essential need that the governance structure is also made smart. Therefore, there is a need to make effective use of ICTs in public administration to connect and better coordinate different departments. Public service too citizens would greatly improve with this coordination combined with organizational change and new skills leading to strong support to public. This would entail the ability to look for, and obtain services in real time through online systems and with rigorous service level agreements with the service providers.

12.3.10 Identifying the smart cities In order to modernize our cities and make them internationally competitive, governments have to support the development of more smart cities. As it has been the experience worldwide over those developing smart cities a city can grow on a

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sustainable basis only if there are opportunities for economic activity, entertainment, education, healthcare, and a wide range of such services for citizens. However, some new cities need to be developed in the mountains, hills desert, and coastal areas. In view of these boundary conditions, satellite towns of cities with a 1 to 4 million populations would seem to be appropriate in size. Besides, mid-sized cities would also make very good candidates. Smaller cities, with great potentials can also need to be taken up in attempt to upgrade to smart cities. Additional cities to be developed as smart cities may be chosen from amongst the following: G

G

G

G

One satellite city of each of the cities with a population of 4 million people or more Most of the cities in the population range of 1 4 million people Cities of tourism, religious, and economic importance not included in the aforementioned text Cities in the 0.2 1.0 million population range

12.4

A selection of smart cities standards

Strategic-level standards are meant to provide guidance to local government leadership on how to develop a clear and effective overall smart cities strategy, identifying priorities, and developing a practical implementation roadmap and an effective approach to monitoring and evaluating progress till the goals are achieved. Continuous monitoring and assessment are a must.

12.4.1 Process-level standards Process-level standards would cover good practice in procuring and managing cross-organizational and cross-sectorial smart cities projects. This would include the proper guidance of appropriately financing this endeavor.

12.4.2 Technical-level standards Technical-level standards would cover practical requirements for products and services to ensure that they achieve the planned results. Strategic-level standards are most relevant to government leadership, while the process-level standards are relevant to management teams.

12.5

Energy strategy

Given that roughly 75% of Europe’s population lives in cities, according to Eurostat statistics, the EU’s urban areas are important contributors to Europe energy consumption and greenhouse gas emissions, which have a huge impact on climate change. At the same time cities are the main drivers of the European economy, opening effective pathways to growth and jobs for Europe. To aid solving the energy challenges in Europe, more attractive and competitive urban areas are to be

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developed with healthier and more sustainable places to live in. Several European policies, proposals, and initiatives are discussed at European level (see sidebar “European policies, proposals and initiatives”). European policies, proposals, and initiatives Solving the energy challenges 1. Guidelines of energy policy targeting transformation of European energy system into the most sustainable in the world. 2. Promoting better laws, easier access to funding and more knowledge sharing among member countries on issues relevant for cities, to aid the commission, national ministries, city governments, and other stakeholder collaborations. 3. The smart cities mandates aim to support the energy union and the Urban Agenda. 4. The Energy Performance of Buildings Directive developed recently to promote smart technologies in buildings to increase their energy efficiency. 5. The Strategic Energy Technology Plan promoting research and innovation efforts across Europe through supporting the technologies transformation to a low-carbon energy system. 6. The Smart Cities Information System that provides vital information on smart city projects and serves as a platform to exchange knowledge, experience, and know-how. Energy strategy and energy union 1. Governance of the energy union 2. Secured energy strategy 3. Clean energy provision 4. 2050 long-term strategy 5. 2030 energy strategy Markets and consumers 1. Single market progress 2. Rights of energy consumers 3. Smart grid metering 4. Government control 5. Market legislation 6. Wholesale market Energy security 1. Secured gas supplies 2. Cyber security 3. oil stocks 4. Diversification of gas sources and routes 5. Electricity provision security 6. Offshore oil and gas safety 7. Oil and gas licensing Renewable energy 1. Renewable energy mandates 2. National renewable energy action plans 2020 3. Support schemes

(Continued)

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(cont’d) 4. Biomass technologies 5. Advanced biofuels Energy efficiency 1. Energy efficiency directives 2. Energy performance of buildings 3. Energy efficient equipment 4. Cogeneration of heat and power 5. Energy efficiency financing 6. Heating, refrigerating, and air conditioning Oil, gas, and coal 1. Oil refining 2. Coal efficient utilization concepts 3. Carbon capture and storage 4. LNG Nuclear energy 1. Nuclear safety 2. Radioactive waste and spent fuel 3. Radiation protection 4. Decommissioning of nuclear plants 5. Precautions to avoid misuse Infrastructure 1. Trans-European networks for energy distribution 2. Common interest projects 3. Public acceptance of infrastructure projects 4. Energy infrastructure forum International cooperation 1. Overview 2. Intergovernmental energy agreements 3. Inter European cooperation 4. European cooperation with international organizations and initiatives Research, technology, and innovation 1. Energy storage 2. Strategic energy technology plan 3. ITER and fusion energy 4. Energy for smart cities

12.6

Factors affecting energy in smart city

Now, let us look at what kinds of factors affect smart cities. The factors include among others: global governance of energy, public exemplary plans, carbon-free mobility plans, energy refurbishment plans of buildings, and plans for new neighborhoods.

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12.6.1 Global governance of energy This governance must bring together the public decision makers and all the energy actors active on the managed perimeter: managers of networks of distribution of gas and electricity and district heating systems, producers of electricity and heat, producers and distributors of water, sewage and waste treatment operators, storage operators, local energy savings agency, leading energy service providers, etc. An energy efficiency master plan should be formulated to be valid for a minimum period of 15 20 year, consistent with the objectives set by the political authorities, and update it every 2 years. This last point is essential to follow technological and regulatory developments and consider the experience gained. A roadmap must also be defined giving visibility to each stakeholder on its own issues and facilitate coordination, many between actors. The progress of the projects should be fully supervised, on a regular basis, in order to correct any drifts in order to guarantee the achieving the objectives.

12.6.2 Public exemplary plan Unplanned city’s evolutions cannot be accepted nowadays in general form if it asks its inhabitants and its users to be “intelligent” and if it is not itself smart. An exemplary plan of the public actors is indispensable: it is not necessary to complete all actions at short notice but to plan them, and in a coherent way. Exemplary plans must basically cover the energy refurbishment of public buildings, the energy efficiency of public actors and activities. The production of renewable electricity, the mobilization of flexibility, a completely new mobility scheme of public actors, and their partners in the city, changing ways of working to reduce the need for travel, etc. are also covered.

12.6.3 Carbon-free mobility plan In the cities, transport is both energy intensive and highly carbon dioxide gas emitting. Our priority is to build a carbon-free and energy efficient mobility plan. This plan cannot ignore achieving several objectives: G

G

G

G

G

Decongest the city. Traditional solutions rely on public transport; easy-to-implement solutions include guidance applications; the promising solution is car sharing, which is more difficult to implement because it requires a profound change in the relationship with the automobile. Reallocate space. Densify the city; improve the living environment by reducing the ground footprint, very important, transport. Widen electrification plans to include also electric deliveries, electric buses, cable transport, bicycles, etc. as well as EVs. Properly manage the transition of urban transport by maintaining the economic, commercial, and cultural vitality of city centers. City officials should avoid taking brutal, unanticipated, unrepaired measures to initiate the transformation of transport, residents should be consulted to avoid creation a widespread

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feeling of rejection among the population and discredit for long, actions in favor of a more environmental-friendly society.

12.6.4 Energy refurbishment plan of buildings Energy efficiency is a vital component of a smart energy city; the energy renovation of existing buildings is the action tackling the biggest savings potential. The commitment of the owners in such work, the coordination of actions within buildings or, in some cases, neighborhoods are all issues to address successfully. Basic modes of financing such as owner investment plus subsidies are not efficient enough to guarantee a satisfactory speed of action. It is necessary to reduce the initial funds required through using mechanisms that introduce a leverage effect, such as contracting models. The development of such models at the scale of a city requires adapted financial partners, well-functioning operational actors and a guarantee of the main risks by the insurances.

12.6.5 Plan new neighborhoods The difficulty of changing the energy performance of existing neighborhoods is extremely important. The necessary work is expensive, potentially disruptive for the occupants, and therefore difficult to plan. Construction of a new district requires the proper engagement of the energy performance of the neighborhood until the next major refurbishment, that is, for a period of 30 50 years. Setting up these standards for a city, the city should be positioned as far ahead as possible, an attitude that is not always consistent with its habits. It should not be limited to current regulations but ahead of its evolution through making the most of new technologies available without hesitation.

12.7

Smart-city hacking

Now, let us look at a couple of key examples of the vulnerabilities that were uncovered in modern practices of smart cities: G

G

Manipulation of law-enforcement response The solution for smart cities

12.7.1 Manipulation of law-enforcement response Systems hackers could accomplish “simultaneous traffic tie-ups on key city roads by tampering with the traffic control infrastructure. That would be enough to create gridlock and delay law-enforcement teams from accessing the real scene of a crime.”

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12.7.2 The solution for smart cities Computer systems vendors argue that both vendors and smart city leaders need to prioritize security by reexamining the vendors’ security protocols, building proper frameworks for these systems. The following guidelines proved useful: 1. Implement IP address restrictions for who can connect to the smart-city devices, especially if networks rely on the public Internet system. 2. Scanning tools that can help identify vulnerabilities. 3. Application of strong network security rules to prevent illegal access to sensitive systems. 4. Disable unnecessary remote administration features and ports. 5. Scan network activity and identify suspicious Internet traffic.

12.8

Energy efficient designs of sustainable buildings

As the world becomes increasingly dependent on electrical appliances and equipment, energy consumption rapidly rises every year. Many programs have been established in various countries to increase end-use equipment energy efficiency. One of the most cost-effective and proven methods for increasing energy efficiency of electrical appliances and equipment is to establish energy efficiency standards and labels. Energy efficiency standards are a set of procedures and regulations that prescribe the energy performance of manufactured products, sometimes prohibiting the sale of products less energy efficient than the minimum standard. The term “standard” commonly encompasses two possible meanings: 1. A well-defined protocol (or laboratory test procedure) by which to obtain a sufficiently accurate estimate of the energy performance of a product in the way it is typically used, or at least a relative ranking of the energy performance compared to other models. 2. A target limit on energy performance (usually a maximum use or minimum efficiency) formally established by a government-based agency upon a specified test standard.

Energy efficiency labels are informative labels affixed to manufactured products indicating a product’s energy performance (usually in the form of energy use, efficiency, and/or cost) in order to provide consumers with the data necessary for making informed purchases. Energy labels serve as a complement to energy standards. They provide consumers information that allows those who care to select more efficient models. Labels also allow utility companies and government energy conservation agencies to offer incentive s to consumers to buy the most energy-efficient products. The effectiveness of energy labels is highly dependent on how information is presented to the consumer.

12.8.1 Literature review and background Energy efficiency in developed and developing countries plays an important role in achieving global sustainable development. Energy consumption is growing rapidly in these countries, yet energy efficiency remains far below levels in developed

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countries. Energy-efficiency improvements can slow the growth in energy consumption, save consumers money and reduce capital expenses for energy infrastructure, see references [1 15]. For most developing countries, the foreign exchange needed to finance energy sector expansion is a significant drain on reserves. Additionally, energy efficiency reduces local environmental impacts, such as water and air pollution from power plants, and mitigates greenhouse gas emissions. Standards and labeling programs provide enormous energy savings potential that can direct developing countries toward sustainable energy use. Improved enduse efficiency from Standards and Labeling programs can contribute significantly to developing economies. The main benefits are: 1. Less need to build new power plants. The cost of saving 1 kWh of energy through energy-efficiency programs has proven much less expensive than producing 1 kWh of energy by building a new power plant. 2. Reduced greenhouse gas emissions. Less energy production means less carbon dioxide emissions from power plants. This contributes to environmental benefits such as slowing down environmental pollution and global warming and preserving natural resources and the ecosystem. 3. Improved competitiveness for local manufacturers. Local companies that upgrade the efficiency of their products can compete better with multinational companies, especially with lower production costs. 4. Higher consumer disposable income. Less spending on electric bills increases consumer purchasing power for other products, which helps local businesses. 5. Increased cash flow in the local economy. With higher disposable income, consumers are more willing to spend, thus, injecting money into the local economy. 6. Improved trade balance. Decrease in energy demand will reduce the consumption of indigenous resources (i.e., natural gas and oil), allowing more to be exported (for Lebanon, less to be imported). Increased export earnings (or less import spending) help alleviate trade deficit of Arabian countries. 7. Avoided future energy deficit as power demand rises. Energy exporting countries have become net importers due to dramatic increases in electricity demand. Energy-efficiency programs can help slow down the demand and prevent energy deficit in the future.

12.8.2 Holistic (overall) approach The assessment of the overall energy performance of a building, including the technical building systems, comprises a number of successive steps, which can be schematically visualized as a pyramid (Fig. 12.1). Sets of common terms, definitions, and symbols are essential for all segments from top to bottom. These cover terms such as energy needs, technical building systems, auxiliary energy use, recoverable system losses, primary energy, and renewable energy. The top segment of the pyramid is the main output: the energy performance and the energy performance certificate of the building. The second segment provides the inputs for the top segment: one or more numerical indicators expressing the energy performance (such as overall energy use per square meter conditioned floor

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Figure 12.1 Overall building energy performance [11].

area, EP), a classification and ways to express the minimum energy performance requirements (EPmax). The third segment describes the principles and procedures on the weighting of different energy carriers (such as electricity, gas, oil, or wood) when they are aggregated to overall amount of delivered (and exported) energy. For instance, this may be expressed as total primary energy (EP) or carbon dioxide emission (ECO2). The fourth segment specifies the categorization of building types (for example, office spaces, residential, or retail) and specification of the boundaries of the building. The fifth segment provides procedures on the breakdown of the building energy needs and system energy losses, aiming at gaining clear insights into where energy is used. The sixth segment provides the building energy needs and energy use for each application (heating, cooling, etc.) and interactions between them. The seventh segment provides the input data on components, such as thermal transmission properties, air infiltration, solar properties of windows, and energy performance of system components and efficiency of lighting. The standards that provide the procedures on boundary conditions comprise external climatic conditions, indoor environment conditions (thermal and visual comfort, indoor air quality, etc.), standard operating assumptions (occupation), and national legal restrictions.

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12.8.3 Energy-efficient buildings Depending on the purpose of the energy declaration, different procedures can be of interest. Different actors need different information. Therefore for benchmarking and for explaining the CO2 emission, it can be enough to read the total energy supply to the building and only adjust these figures to normal outdoor climate and to the heated area. For giving relevant advice, or to make an energy declaration to the property owner on which measures are cost effective, a very careful examination and calculation of the building’s energy balance is necessary. Thus, the primary use of energy declarations in buildings is to: 1. Create consciousness of energy efficiency in buildings and also improve the knowledge of energy use in buildings. 2. Use the information to determine if the building works as well as possible with regard to its technical design. 3. Use the information for benchmarking. 4. Use the information for suggesting measures and recommendations for reducing the energy use. 5. Provide the information necessary to make calculations of the environmental impact due to the energy use, for example, CO2 emission. 6. Describe selected energy properties of the building. 7. Give the basis for a common energy performance certification of a building.

One way to proceed is to make the energy calculation in different steps for existing buildings. The first is to collect measured energy-use (e.g., from energy bills, and make a benchmarking to decide if the actual building is better or worse compared to similar buildings). If the energy-use seems to be higher than the average for a comparable grouping of buildings a second step is to make a careful energy calculation that can be compared to the measured energy use. This has to be done for identifying what kind of measures can be recommended in order to reduce the energy use in the building. For benchmarking, it can perhaps also be of interest to compare the measured energy use in the building examined with the estimated energy use in a building that is built with the best available technology. Alternatively, compared with a building that meets the requirement in the existing building codes. Some important aspects necessary to take into consideration when developing a common tool for energy declaration of buildings is discussed [12,13]. The discussion is here focused on residential buildings but similar principles are relevant for other types of buildings.

12.8.4 Energy declaration of existing buildings For most existing buildings the energy use usually is well known via the energy bills. The construction details are on the other hand not very well documented. Calculations of the energy use will thus in most cases be very uncertain and difficulties will occur when giving relevant recommendations of cost-effective energy conservation measures. The energy declaration needs a combination of tools for calculations based on the information from the energy bills. For existing buildings the

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energy declarations can be based on both measurements and calculations in order to fulfill the purposes mentioned above. Normally the heating bills are based on measured heat delivered to the building. In most cases, the energy for domestic hot water is included in the heating bill. To get the total energy use in a building, the electricity to run the building and household electricity have to be added. In electrically heated houses (common in Sweden), the house-owner just got one bill covering the total energy use. To make the measured values objective and comparable several corrections and calculations are necessary: G

G

G

It is necessary to check that the indoor thermal comfort and air quality meet agreed requirements. Corrections of the heat use to normal outdoor climate—primarily outdoor temperature (maybe also solar heat gain). Necessary corrections for internal heat gains, for example, differences in household electricity.

12.8.5 Energy declaration of new buildings The energy declaration of a new building has to be based on calculations. In comparison with existing buildings, the knowledge of the building construction is very good. The most critical part for the outcome of calculations is the choice of input data. To achieve good comparability, a common procedure to determine input data like energy for domestic hot water, household electricity or electricity for the activity in the building, choice of indoor temperature, electricity for operating the building, energy for lighting, etc. has to be developed. In many countries many new buildings have very low energy demand for heating (see checklist: “An Agenda for Action for International Collaboration Issues”). The solar heat gain, internal gains and energy losses from equipment, etc., cover the major part of the heating demand. In several buildings, the internal gains, etc. are so large that cooling is necessary even in temperate climate. For buildings with large glassed areas and/or large internal gains, the energy calculations need to be done on hourly basis. Many modern apartment blocks, offices, education buildings, and restaurants need very little heat supply from the heating system and need very often air-conditioning to get an acceptable thermal comfort. An example of the energy efficiency indication in buildings is highlighted in ISO 23045. An agenda for action for international collaboration issues Issues for international collaboration include the following key activities (check all tasks completed): _____ 1. Develop standardized tools for the calculation of the energy performance of buildings taking into account the aspects outlined in ISO 13790 that cover many aspects but still has to be completed. (Continued)

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(cont’d) _____ 2. Define system boundaries for the different building categories and different heating systems. _____ 3. Prepare models for expressing requirements on indoor air quality, thermal comfort in winter and when appropriate in summer, visual comfort, etc. _____ 4. Develop transparent systems to determine necessary input data for the calculations, including default values on internal gains. _____ 5. Provide transparent information regarding output data (reference values, benchmarks, etc.). _____ 6. Define comparable energy related key values (kWh/m2, kWh per person, kWh per apartment, kWh per produced unit, etc.) The areas/volumes need to be defined. _____ 7. Develop a method to translate net energy, used in the building, to primary energy and CO2 emissions. _____ 8. Develop a common procedure for an “energy performance certificate.” _____ 9. Develop and compile relevant standards applicable for each individual building category.

12.9

Summary

This chapter presents the important factors affecting the energy efficiency in built environment through reviewing the issues of energy storage and related problems and the need for smart microgrids and how to keep smart and sustainable balance. Smart cities and its definitions are described next with instrumental procedure to be followed in smart cities in terms of energy efficient practices, demand management, and improved access to information. Environmental sustainability and applications of clean technologies were also discussed. The chapter addresses the citizens’ participation, ICT applications, smart governance, and smart cities identifications. Naturally a set of standards are needed to govern the smart city designs. Energy strategy follows with market constraints, energy security and availability of renewable sources, international collaboration research and innovations, global governance, and carbon-free mobility were discussed in addition to possible smart city hacking and how to secure smart cities. The chapter highlighted the value of holistic approach for energy assessment and energy efficient buildings. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

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Chapter review questions/exercises

12.10.1 True/False 1. True or False? As wind and solar become pioneering technologies and exhibit even more rapid adoption by publics and governments, one of the difficult hurdles that smart cities will need to overcome is the energy storage issue. 2. True or False? The Internet of Things (IoT-enabled) smart grids are powered by demandresponse systems. 3. True or False? Governments that are able to streamline their core services using IoT, and show that sustainability is at the top of their agenda, will attract less people and businesses, thus gaining a competitive advantage over other economies. 4. True or False? Energy, water, transportation, public health, and safety are orchestrated in smart cities to provide a harmonized smooth operation of the critical infrastructure. 5. True or False? Distributed power generation sources include the use of solar, wind, biomass as well as fuel cells.

12.10.2 Multiple choice 1. What enables real-time observation, close monitoring, and control of the entire distribution system, in order to attain stability in the grid through a centralized Master control center? a. Transparent distribution system b. Human-centered distribution system c. Sufficient distribution system d. ICT-enabled distribution system e. Automatic distribution system 2. What are normally equipped with smart and intelligent appliances that can communicate with each other? a. Smart cities b. Smart energy c. Smart homes d. Smart phones e. All of the above 3. What is concerned with the remote control of the building’s heating and air-conditioning systems through an Internet-controlled thermostat? a. SVUAC b. Audio visual c. AMSI d. ESGI e. HVAC 4. What provides two-way communications between utilities and consumers through an integration of smart meters and Internet communication networks? a. HVAC b. SUVA c. SVUAC d. ESGI e. AMSI

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5. Renewable energy, coupled with energy storage, can provide reliable and quality power to a: a. Electric vehicle b. ICT c. Smart grid d. Smart city e. Smart economy

12.10.3 Exercise 12.10.3.1 Problem Create a methodology for developing an improved energy model in the smart-city context, along with some additional final recommendations.

12.10.4 Hands-on projects 12.10.4.1 Project Do research: Create an active grid interaction by using smart grids that aim to dramatically change residential area energy systems.

12.10.5 Case projects 12.10.5.1 Problem Create an optimal planning and operation model of distributed energy resources in a district, taking into account the mobility of consumers using conventional fuel vehicles or EVs.

12.10.6 Optional team case project 12.10.6.1 Problem Create a linear programming model to evaluate the most common distributed generation technologies, with and without storage systems and under different electricity pricing scenarios.

References [1] E.E. Khalil, Energy performance of buildings directive in Egypt: a new direction, HBRC J. 1 (2005). [2] A.A. Medhat, E.E. Khalil, Thermal comfort meets human acclimatization in Egypt, Proc. Healthy Build. 2 (2006) 25. [3] E.E. Khalil Energy performance of commercial buildings in Egypt: a new direction, in: Proceedings, Energy 2030, Abu Dhabi, November 2006.

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[4] R. Kosonen, Displacement ventilation for room air moisture control in hot and humid climate, Roomvent 2002 (2002) 241 244. [5] B.C.C. Leite, A. Tribess, Analysis of under floor air distribution system: thermal comfort and energy consumption, Roomvent 2002 (2002) 245 248. [6] R. Kameel, E.E. Khalil, Prediction of turbulence behavior using k-ε model in operating theatres, Roomvent 2002 (2002) 73 76. [7] E.E. Khalil, Arab-air conditioning and refrigeration code for energy-efficient buildings, Arab. Constr. World 28 (8) (2008) 24 26. [8] E.E. Khalil, Air conditioning and refrigeration code for energy-efficient buildings in the Arab World, J. Kuwait Soc. Eng. 100 (2008) 94 95. [9] ISO publications ISO 23045_2009, January 2009. [10] Federal Register / Vol. 72, No. 245 / Friday, December 21, 2007 / Rules and Regulations 72565. [11] D. Van Dijk, E.E. Khalil, Future cities building on energy efficiency, ISO Focus. (2011) 25 27. [12] E.E. Khalil, Holistic approach to smart buildings from construction material to services, Open. J. Energy Effic 1 (3) (2012) 48 56. [13] E.E. Khalil Design of energy efficient built environment, in: CHRVI Middle East 2013 Seminar, Doha, Qatar, June 2013. [14] Building Energy Efficiency in Cold Climates, Encyclopedia of Sustainable Technologies, 2017, pp. 149 157. [15] IEA EBC, Annexes 53: Total energy use in buildings—analysis and evaluation methods, Energy Build. 152 (2017) 124 136.

Energy efficient automated warehouse design

13

Melis Ku¨c¸u¨kya¸sar1, Banu Yetkin Ekren1 and Tone Lerher2 1 Department of Industrial Engineering, Yasar University, 2Faculty of Mechanical Engineering, University of Maribor

13.1

Introduction

Automated storage and retrieval technologies are widely used in large warehouses to deal with high transaction rate. In today’s business environment, competition among companies increases aggressively by creating radical differences in their marketing strategies. Quick response to customer orders is one of the challenging strategies in recent strategies. For instance, Amazon is an amazing leading company for the “same day delivery strategy” in creating such a challenging marketing strategy for its customers. Through such an ambitious strategy, the company invested on an automation technology for their warehouses in 2015, that is the Kiva robots [1]. One of the recent automated storage and retrieval technologies, whose order statistics has recently increased dramatically is, shuttle-based storage and retrieval system (SBS/RS). As shown in a business trend report of European Materials Handling Federation [2] in Fig. 13.1, orders for “shuttles for boxes” nearly quadrupled compared to the year of 2015. Note that the statistics for intra-logistic machinery (S/R machines and mini-loads) recovered have reached their highest level since the statistics started. Hence, it can be concluded that investment on automated storage and retrieval systems is increasing drastically and, one of them is the SBS/RS technology. A typical design of an SBS/RS is shown in Fig. 13.2A. According to that figure there is a dedicated tier-captive shuttle in each tier of an aisle providing horizontal travel for loads. A lifting mechanism is installed at each aisle providing vertical travel for loads. Loads and shuttles match at the buffer location of their designated tier. Based on the process type, the shuttle performs either a storage or a retrieval process. In Fig. 13.2B, the studied SBS/RS design with tier-to-tier shuttle system is illustrated. In that system, shuttles are not tier-captive and can travel between tiers within an aisle. In that system, two separate lifting mechanisms are installed in either end side of an aisle. One (see, Lift 1 in Fig. 13.2B) is providing vertical travel for loads and the other (see, Lift 2 in Fig. 13.2B) is providing vertical travel for shuttles for their movement between tiers. The advantage of the Fig. 13.2B SBS/RS compared to the Fig. 13.2A SBS/RS is that, since the shuttles are not tier-captive, there can be less number of shuttles operating in the system and hence it may result with decreased investment cost compared to the Fig. 13.2A Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00013-9 © 2021 Elsevier Inc. All rights reserved.

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Solving Urban Infrastructure Problems Using Smart City Technologies Statistics for S/R Machines Results - Total (Indexes) 733

165 119 132 117 118

145151 100 82

103 93

121117

100 87 78

121 132 127 111 98

128 97

135 111107

77 27

2

35 27 6

Miniload Machines

198194

133

100

100 46

S/R Machines without operator

number of orders, Index 2011 = 100

number of orders, Indexes 2005

486

6 0

0

S/R Machines with operator

0

39

0

Shuttle for boxes

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Source: FEM PG IS

Figure 13.1 FEM statistics report for the year of 2017. Source: This source is obtained by European Materials Handling Federation Business Trend Report. Received from: ,https://www.fem-eur.com/wp-content/uploads/2019/02/IS-AnnualFactsheet-2017.pdf., 2017 [2].

system. In addition, based on the number of shuttles in the system, the average utilization values of them may become as higher as the lifting mechanism. However, a disadvantage of that 13.2b system design may be increased cycle time and/or energy consumption compared to the Fig. 13.2A design. In this work, our aim is also to explore such advantageous conditions. Namely, we believe that it is worth to explore how the warehouse design would be optimal based on the factors such as number of tiers, aisles and bays as well as shuttles in the system, based on some important system performance metrics. Specifically, in this work, our aim is to study a Fig. 13.2B design, tier-to-tier SBS/RS, by exploring how these important performance metrics: average cycle time per transaction, average energy consumption per transaction, etc. are affected by some warehouse design factors in the system. We also consider that there is regeneration mechanism in the system where slowing down shuttles and lifts can produce electricity that can be stored in batteries for their future usage in accelerating. As the design factors, we consider number of tiers, aisles, bays, shuttles as well as acceleration/deceleration of lifts and shuttles in the system. In the literature, most of the studies about SBS/RS are based on tier-captive shuttles (see Section 13.2). However, in this work, we focus on tier-to-tier SBS/RS, where there are two separate lifting mechanisms providing vertical travels for loads and shuttles, separately. Different from the existing few tier-to-tier SBS/RS papers, we consider a separate lifting mechanism dedicated solely for travel of shuttles. By considering simultaneous travel policy of these separate lifting systems and shuttles, we also provide advantageous compared to an aisle-captive system with single

Energy efficient automated warehouse design

Figure 13.2 (A) Tier-captive SBS/RS. (B) Tier-to-tier SBS/RS.

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lifting mechanism. A detailed literature analysis along with our work’s difference is provided in Section 13.2.

13.2

Literature review

In literature, mostly SBS/RS with tier-captive design is studied. We present those studies as well as some few studies on tier-to-tier SBS/RSs. Marchet et al. [3] provided analytical models to calculate performance metrics (e.g., waiting time and cycle time) for tier-captive SBS/RS. The models were developed on an open queuing network approach and validated via simulation. Then, Marchet et al. [4] studied design trades-offs for tier-captive SBS/RS via simulation. They compared a few performance metrics including initial investment cost in the system. The other technological designs on SBS/RSs have been adapted by Carlo and Vis [5]. They suggested a heuristic approach for scheduling of lifts in the warehouse consisting of a conveyor, two nonpassing lifts, and multiple shuttles. Two functions are suggested for sequencing of the requests. Lehrer et al. [6] provided advantages of the tier-captive SBS/RSs in terms of high throughput rate and low cycle time by comparing with the other automated storage and retrieval systems. Different rack configurations and velocity profiles for lifts and shuttles are considered to calculate the desired performance metrics. Later, Lehrer [7] conducted a study evaluating the similar performance metrics as his previous work. Differently in that work, because it provides higher utilization of space, he considers double-deep storage compartments in the system. Lehrer et al. [8] developed analytical travel time models by using features of the lifting table and the shuttle carriers (e.g., changeable acceleration/deceleration and the maximum velocity) for single and dual command cycle of tier-captive SBS/RS. Ekren [9] focused simulation-based approach for the tier-captive SBS/RS. A graph-based solution is suggested to calculate performance metrics by considering different tier-captive design configurations. Later, Ekren et al. [10] conducted an analytical model-based tool that can calculate mean and variance of travel time of the shuttles and lifts per transaction. In addition, this calculator can estimate the amount of energy consumption and regeneration per transaction for different design parameters (e.g., discrete travel lengths, velocity of shuttles/lifts, acceleration/deceleration of velocities, number of tiers and bays, etc.). Wang et al. [11] depicted a time-based algorithm for sequencing the tasks by using a mathematical modeling approach in a tier-captive SBS/RS. Nondominated sorting algorithm is considered to calculate a multiobjective optimal solution. Tappia et al. [12] forecasted some performance measurements in tier-captive SBS/ RS by using a queuing network model. One of recent works of the tier-captive SBS/RS is provided by Eder [13]. This research conducted an analytical-based model to find out some performance metrics by using a continuous time open queuing network with limited capacity.

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Ekren [14] presented a recent work on tier-captive SBS/RS. She developed a statistical experimental design study to investigate factors affecting the performance metrics in tier-captive SBS/RS. This study concluded that increasing the number of aisles affects the system performance significantly. As mentioned previously, the existing studies mostly focused on tier-captive SBS/RS by using analytical or simulation-based approaches. In this chapter, we study a new design for SBS/RS where shuttles can travel between tiers. The first study on the tier-to-tier SBS/RS is published by Ha and Chae [15]. They discoursed on collisions between shuttles. A free-balancing approach is proposed for this and compared with nonfree balancing approach. This system includes one lifting mechanism that can carry shuttles and transactions. Later, Ha and Chae [16] introduced a study to determine the best number of shuttles in the tier-to-tier SBS/RS by considering several parameters such as acceleration, velocity, physical configurations, etc. Different from those existing two studies on tier-to-tier SBS/RS, in this chapter we also focus on energy efficient design of the system. For instance, in an effort to reduce the energy consumption in the system, we include acceleration/deceleration values of shuttles and lifts as design parameters. We also tried different mean arrival rate scenarios to show the advantages of higher vehicle utilizations. A very recent work on tier-to-tier SBS/RS is studied by Zhao et al. [17]. In that work, they presented a scheduling optimization of solely retrieval transactions based on an integer programming. Different from their SBS/RS design, our SBS/RS has two separate lifting mechanisms where one performs vertical travel for loads and the other performs for transfer of shuttles among tiers. Differently, we also consider both storage and retrieval processes in the system. Once again in this chapter, we propose a novel design concept for SBS/RS design, namely tier-to-tier SBS/RS design, and investigate how its performance change in terms of energy consumption and cycle time per transaction under different warehouse design metrics such as rack design, number of shuttles, and velocity profiles of shuttles and lifts. We utilize simulation for the modeling approach. Different acceleration/deceleration values are also experimented to observe how they affect the energy related performance metrics for the system designs. We also consider that there is regeneration mechanism in the system where slowing down shuttles and lifts can produce electricity for their later usage. To be able to observe how the throughput capacity of the system changes, we also increased the mean arrival rate scenarios to the system.

13.3

System description and model assumptions in the system

We study an SBS/RS design with tier-to-tier shuttles where shuttles can move between tiers by using a separate lifting mechanism located at the end of its aisle. Two types of views of the studied system are illustrated by Fig. 13.3A and B. Fig. 13.3A and B show side and top views of the studied system, respectively.

274

Solving Urban Infrastructure Problems Using Smart City Technologies Bay

I/O Point Tote Conveyors

Life for totes (Lift1)

Buffers

Shuttle Life for Shuttle (Lift2)

(A) Side View of an aisle

(B) Top view of an aisle

Bay

Figure 13.3 Side (A) and top (B) views of the tier-to-tier SBS/RS.

Lift 1 is the lifting mechanism providing vertical travel for the arriving loads (i.e., totes). Lift 2 is the lifting mechanism providing tier-to-tier activity for shuttles. Namely, Lift 2 provides vertical movements for shuttles (also see Fig. 13.2A and B). The SBS/RS warehouse is divided by two storage sides in an aisle. Therefore, totes can be stored in either side of a bay within a tier. It is assumed that each bay can hold a single tote.

13.3.1 Operations and assumptions in the system In this section, we detail how the SBS/RS operates and the assumptions that are used in the system, as follows: G

G

G

G

G

Arriving loads for storage transactions are transferred by conveyors in totes. There is a Lift 1 system in each aisle connected by a conveyor system at the first tier. Since, storage transactions arrive and retrieval transactions end at that point, these points are referred as input/output (I/O) locations throughout the chapter (see Figs. 13.2A and B, 13.3A). A storage process is a process where the arriving tote is stored in a bay of a tier in an aisle. A retrieval process is a process where the tote is retrieved from its storage address by shuttles and dropped off at the I/O point by lifts. In a storage process, an arriving tote first enters the shuttle’s common queue and is processed based on first-in-first-out scheduling rule. However, when a shuttle becomes available, it first searches whether or not there is a waiting transaction to be processed at its current tier. If there is, then the shuttle seizes it. After a shuttle seizes a transaction, an entity also enters the regarding lifting systems’ queue instantly and simultaneous travel may take place. The operating details can also be seen in the simulation flowcharts, in Figs. 13.4 and 13.5.

Energy efficient automated warehouse design

275

Figure 13.4 Simulation flow chart for storage process.

G

G

G

Lift 1 has two lifting tables that can process independently. Each lifting table of Lift 1 can carry a single tote. Lift 2 and a shuttle have a single tote capacity. At each tier, there are two separate buffer areas one of whose capacity is three totes. Totes are dropped off and picked up by lifts/shuttles from those areas.

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Solving Urban Infrastructure Problems Using Smart City Technologies

Figure 13.5 Simulation flow chart for retrieval process. G

Shuttles and lifts are assumed to stay at the point where they complete their last processes (dwell point policy).

Besides the above operating policies, to be able to prevent collision of shuttles, no shuttle is assigned for a transaction if there is already a shuttle in that tier.

Energy efficient automated warehouse design

13.4

277

Simulation modeling of the system

To be able to complete an analysis on how the performance metrics are affected in tier-to-tier SBS/RS design, we must first simulate the studied system. The simulation model is completed by the ARENA 16.0 commercial software. The flowcharts of the simulation models are illustrated by Figs. 13.4 and 13.5 for the storage and retrieval processes, separately. The verification and validation of the simulation models are done by animating the model and by comparing an output from the system (i.e., average cycle time/transaction) with a practical one by the experts. Namely, since there was not a real system, the validation of the simulation models is done by the help of experts in these systems. Besides the system assumptions given in Section 13.3.1, in the simulation models, we also consider the following assumptions: G

G

G

G

G

G

G

Acceleration and deceleration delays of shuttles and lifts are considered in the system. Mean arrival of rate for storage and retrieval transactions follows Poisson distribution with equal rate. A pure random storage policy is considered for assigning the storage addresses for transactions. The load and unload times of the totes are ignored. Distance between two adjacent bays is assumed to be equal and 0.5 m in each tier. Distance between the buffer area and the first bay is same with the distance between two adjacent bays. The weight of a tote, shuttle, Lift 1 and Lift 2 are considered to be 20, 40, 60, and 60 kg, respectively. Distance between two adjacent tiers is equal and 0.35 m.

The simulation models are run for five independent replications. The common random variance reduction technique is used in the models. We complete a steadystate analysis hence, we determine the warm-up periods for simulation runs. According to that, each experiment is run for 100 days with 10 days warm up periods. Note that the aim of this study is also to explore a good warehouse design for tier-to-tier SBS/RS in terms of both energy related performance metrics as well average cycle time per transactions. Therefore, we conduct several experiments based on the predefined design factors detailed in the following subsection.

13.4.1 Design scenarios for experiments Before explaining the design scenarios, Table 13.1 is provided to show the parameters used in the study. Table 13.2 shows the design scenarios for the conducted experiments. According to that, there are fifteen designs based on five number of tiers (i.e., 10, 12, 15, 17, and, 20) and three number of bays (e.g., 50, 80, and, 100). It is assumed that there is 12,000 number of storage capacity in the warehouse. The number of aisle is computed by dividing the warehouse capacity by T 3 B 3 2 sides. Hence, increased number of tiers may tend to have a narrower footprint while

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Table 13.1 Description of the utilized parameters. Parameter

Description

T B

Number of tiers in each aisle Total number of bays in both sides of each tier of an aisle Number of aisles in the warehouse Number of total storage compartments Acceleration value Deceleration value Mean hourly arrival rate at the warehouse Mean hourly arrival rate at an aisle Net energy consumption per transaction (EC
ER) Energy consumption per transaction Energy regeneration per transaction Average cycle time per transaction Average utilization of shuttles Average utilization of Lift 1 Average utilization of Lift 2 Number of shuttles in an aisle

A W a d λ λA E EC ER t U1 U2 U3 ns

Unit

m=s2 m=s2 Transaction/h Transaction/h kWh/transaction kWh/transaction kWh/transaction s/transaction

Table 13.2 Design scenarios for experiments. Design no.

T

B

A

W

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

10 10 10 12 12 12 15 15 15 17 17 17 20 20 20

100 80 50 100 80 50 100 80 50 100 80 50 100 80 50

12 15 24 10 13 20 8 10 16 8 9 15 6 8 12

12,000 12,000 12,000 12,000 12,480 12,000 12,000 12,000 12,000 13,600 12,240 12,750 12,000 12,800 12,000

decreased one may tend to have a larger footprint warehouse to meet the required number of storage capacity (i.e., 12,000). We run the Table 13.2 designs for four different number of shuttles per aisle (ns ) scenarios that are: two, three, four, and five shuttles. In addition, two different

Energy efficient automated warehouse design

279

acceleration/deceleration values are also experimented for shuttles and lifts to analyze their effects on energy consumption performance metric.

13.5

Results and discussion

Remember that the simulation models are run based on the Table 13.2 designs with five independent replications. The results are summarized in Table 13.3, Table 13.4 and Table 13.5. Furthermore, the results are given for averages of five replications along with their 95% confidence intervals. Although mainly, we study the average energy consumption and average cycle time per transaction performance metrics; the results are given with more performance metrics in the appendix tables because they are already provided by the simulation software. For instance, in the appendix tables, average utilization values for shuttles, lifts, average energy consumption per transaction (kWh), average cycle time per transaction (seconds), average energy regeneration per transaction (kWh), etc. performance results, can be seen. Note, that since there is a regeneration mechanism in the system, we also compute a “net energy consumption per transaction”—E—performance metric by (1). It shows the difference between energy consumption per transaction and energy regeneration per transaction: E 5 EC 2 ER

(13.1)

Note that, the details of the energy consumption and energy regeneration calculations can be found in Ekren et al. [10]. Hence, we do not repeat the calculations here. Mean arrival rate of transactions at the warehouse is considered to be 2400 transaction/hour for each scenario where mean arrival rates for storage and retrieval transactions are equally likely. To facilitate the modeling, we simulate a single aisle by considering that the mean arrival rate at this aisle (λA) follows Poisson distribution. The mean arrival rate at an aisle is calculated by dividing the mean arrival rate at the warehouse by the total number of aisles in the system as in (2): λA 5 λ=A

(13.2)

13.5.1 Graphical results and comments Fig. 13.6A
D shows the averages of five simulation replications of the performance metrics: average cycle and average energy consumption per transaction for the conducted experiments of Table 13.2 designs. For instance, Fig. 13.6A shows the experiment results for two number of shuttles; Fig. 13.6B shows the results for three number of shuttles, so on. Note that some of design results do not exist in Fig. 13.6A and B. For instance, in Fig. 13.6A, designs 7, 10, 13, 14, and, in Fig. 13.6B, design 13 do not exist. This is because in these scenarios, there are few

Table 13.3 Results for designs with 5 2 m/s2, d 5 2 m/s2, and λ 5 2400. Scenario no. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Design no. 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 8 8 8 8

T

B

A

W

nS

tðsÞ

u1 ð%Þ

u2 ð%Þ

u3 ð%Þ

EC kWh=transaction

10 10 10 10 10 10 10 10 10 10 10 10 12 12 12 12 12 12 12 12 12 12 12 12 15 15 15 15 15 15 15 15

100 100 100 100 80 80 80 80 50 50 50 50 100 100 100 100 80 80 80 80 50 50 50 50 100 100 100 100 80 80 80 80

12 12 12 12 15 15 15 15 24 24 24 24 10 10 10 10 13 13 13 13 20 20 20 20 8 8 8 8 10 10 10 10

12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,480 12,480 12,480 12,480 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000 12,000

2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5

41.55 6 0.10 29.26 6 0.02 26.13 6 0.02 24.06 6 0.02 27.06 6 0.04 22.79 6 0.02 20.97 6 0.02 19.41 6 0.03 16.49 6 0.02 15.20 6 0.02 14.20 6 0.01 13.22 6 0.02 57.56 6 0.22 32.37 6 0.06 28.18 6 0.03 26.20 6 0.02 29.78 6 0.04 24.10 6 0.01 22.29 6 0.01 20.96 6 0.02 17.29 6 0.02 15.97 6 0.01 15.10 6 0.02 14.27 6 0.01 n.a. 39.85 6 0.08 31.35 6 0.03 28.86 6 0.02 39.09 6 0.11 26.61 6 0.03 24.18 6 0.02 22.94 6 0.01

72 6 0.07 46 6 0.09 32 6 0.09 24 6 0.11 48 6 0.03 30 6 0.04 21 6 0.04 16 6 0.04 21 6 0.04 13 6 0.04 9 6 0.03 7 6 0.04 86 6 0.03 57 6 0.05 41 6 0.03 31 6 0.03 57 6 0.07 37 6 0.07 26 6 0.07 20 6 0.06 26 6 0.02 16 6 0.03 12 6 0.02 9 6 0.03 n.a. 74 6 0.09 55 6 0.08 42 6 0.09 76 6 0.05 50 6 0.05 36 6 0.05 28 6 0.05

33 6 0.04 33 6 0.05 32 6 0.07 30 6 0.07 24 6 0.06 23 6 0.05 22 6 0.06 21 6 0.06 11 6 0.04 11 6 0.03 10 6 0.04 10 6 0.04 40 6 0.05 41 6 0.07 40 6 0.08 38 6 0.06 28 6 0.05 28 6 0.04 27 6 0.04 26 6 0.04 14 6 0.02 14 6 0.02 13 6 0.02 13 6 0.02 n.a. 51 6 0.05 51 6 0.07 50 6 0.07 38 6 0.05 38 6 0.08 37 6 0.07 36 6 0.07

44 6 0.13 39 6 0.09 33 6 0.08 28 6 0.06 32 6 0.06 27 6 0.04 24 6 0.04 20 6 0.03 15 6 0.06 13 6 0.04 11 6 0.03 9 6 0.03 51 6 0.10 48 6 0.08 43 6 0.06 38 6 0.05 38 6 0.12 33 6 0.08 30 6 0.05 26 6 0.05 19 6 0.04 17 6 0.03 15 6 0.02 13 6 0.02 n.a. 61 6 0.08 56 6 0.08 51 6 0.06 49 6 0.11 45 6 0.08 41 6 0.06 38 6 0.04

2.9E-03 6 3.1E-06 2.8E-03 6 4.5E-06 2.6E-03 6 2.9E-06 2.5E-03 6 3.3E-06 2.9E-03 6 3.1E-06 2.8E-03 6 3.8E-06 2.6E-03 6 2.4E-06 2.4E-03 6 4.0E-06 2.8E-03 6 4.3E-06 2.7E-03 6 4.1E-06 2.6E-03 6 3.8E-06 2.4E-03 6 4.1E-06 3.2E-03 6 1.8E-06 3.2E-03 6 3.3E-06 3.1E-03 6 2.5E-06 2.9E-03 6 1.2E-06 3.3E-03 6 1.6E-06 3.2E-03 6 2.9E-06 3.1E-03 6 2.4E-06 2.9E-03 6 2.5E-06 3.2E-03 6 5.5E-06 3.1E-03 6 4.2E-06 3.0E-03 6 4.9E-06 2.9E-03 6 4.3E-06 n.a. 3.8E-03 6 3.0E-06 3.7E-03 6 3.3E-06 3.5E-03 6 3.2E-06 3.8E-03 6 1.4E-06 3.8E-03 6 3.2E-06 3.7E-03 6 2.9E-06 3.5E-03 6 2.6E-06




ER ðkWh=transactionÞ

EðkWh=transactionÞ

5.7E-04 6 5.8E-07 5.6E-04 6 7.9E-07 5.2E-04 6 5.8E-07 4.9E-04 6 5.8E-07 5.8E-04 6 5.6E-07 5.5E-04 6 6.7E-07 5.2E-04 6 4.5E-07 4.9E-04 6 7.6E-07 5.6E-04 6 7.8E-07 5.4E-04 6 6.7E-07 5.1E-04 6 6.1E-07 4.8E-04 6 8.2E-07 6.1E-04 6 3.5E-07 6.2E-04 6 5.4E-07 5.9E-04 6 4.5E-07 5.6E-04 6 2.6E-07 6.4E-04 6 3.0E-07 6.2E-04 6 4.9E-07 5.9E-04 6 4.1E-07 5.6E-04 6 4.9E-07 6.3E-04 6 9.2E-07 6.1E-04 6 7.2E-07 5.8E-04 6 8.3E-07 5.5E-04 6 6.8E-07 n.a. 6.9E-04 6 3.4E-07 6.7E-04 6 3.9E-07 6.4E-04 6 3.9E-07 7.0E-04 6 2.7E-07 6.9E-04 6 5.4E-07 6.7E-04 6 5.4E-07 6.4E-04 6 4.9E-07

2.3E-03 6 2.6E-06 2.2E-03 6 3.7E-06 2.1E-03 6 2.3E-06 2.0E-03 6 2.7E-06 2.3E-03 6 2.6E-06 2.2E-03 6 3.2E-06 2.1E-03 6 2.0E-06 1.9E-03 6 3.2E-06 2.2E-03 6 3.5E-06 2.2E-03 6 3.5E-06 2.0E-03 6 3.2E-06 1.9E-03 6 3.3E-06 2.6E-03 6 1.5E-06 2.6E-03 6 2.8E-06 2.5E-03 6 2.0E-06 2.4E-03 6 9.9E-07 2.7E-03 6 1.3E-06 2.6E-03 6 2.4E-06 2.5E-03 6 2.0E-06 2.3E-03 6 2.0E-06 2.6E-03 6 4.6E-06 2.5E-03 6 3.5E-06 2.4E-03 6 4.1E-06 2.3E-03 6 3.6E-06 n.a. 3.1E-03 6 2.7E-06 3.0E-03 6 2.9E-06 2.9E-03 6 2.8E-06 3.1E-03 6 1.1E-06 3.1E-03 6 2.7E-06 3.0E-03 6 2.4E-06 2.9E-03 6 2.1E-06

33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

9 9 9 9 10 10 10 10 11 11 11 11 12 12 12 12 13 13 13 13 14 14 14 14 15 15 15 15

15 15 15 15 17 17 17 17 17 17 17 17 17 17 17 17 20 20 20 20 20 20 20 20 20 20 20 20

50 50 50 50 100 100 100 100 80 80 80 80 50 50 50 50 100 100 100 100 80 80 80 80 50 50 50 50

16 16 16 16 8 8 8 8 9 9 9 9 15 15 15 15 6 6 6 6 8 8 8 8 12 12 12 12

12,000 12,000 12,000 12,000 13,600 13,600 13,600 13,600 12,240 12,240 12,240 12,240 12,750 12,750 12,750 12,750 12,000 12,000 12,000 12,000 12,800 12,800 12,800 12,800 12,000 12,000 12,000 12,000

Note: “n.a.” signifies that the system blows up due to the insufficient service rate.

2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5 2 3 4 5

18.48 6 0.01 16.95 6 0.01 16.19 6 0.01 15.51 6 0.01 n.a. 41.46 6 0.10 32.25 6 0.03 29.73 6 0.02 48.61 6 0.23 28.34 6 0.03 25.27 6 0.02 23.98 6 0.01 19.10 6 0.01 17.47 6 0.01 16.76 6 0.01 16.15 6 0.01 n.a. n.a. 40.53 6 0.07 33.59 6 0.03 n.a. 31.31 6 0.06 26.81 6 0.02 25.37 6 0.01 20.81 6 0.01 18.42 6 0.01 17.69 6 0.01 17.14 6 0.01

34 6 0.03 22 6 0.03 16 6 0.03 12 6 0.04 n.a. 76 6 0.08 56 6 0.11 43 6 0.11 84 6 0.06 57 6 0.07 41 6 0.05 32 6 0.05 36 6 0.05 24 6 0.05 17 6 0.05 13 6 0.06 n.a. n.a. 77 6 0.02 61 6 0.04 n.a. 66 6 0.06 48 6 0.06 38 6 0.09 47 6 0.08 31 6 0.08 22 6 0.09 17 6 0.08

19 6 0.03 18 6 0.02 18 6 0.02 17 6 0.02 n.a. 53 6 0.07 53 6 0.07 52 6 0.08 42 6 0.07 43 6 0.08 42 6 0.08 41 6 0.07 21 6 0.05 21 6 0.06 20 6 0.05 20 6 0.06 n.a. n.a. 67 6 0.06 67 6 0.04 n.a. 49 6 0.04 49 6 0.05 48 6 0.06 27 6 0.06 27 6 0.06 27 6 0.06 26 6 0.05

25 6 0.03 23 6 0.02 21 6 0.01 19 6 0.01 n.a. 63 6 0.08 58 6 0.08 54 6 0.06 54 6 0.14 51 6 0.11 47 6 0.07 44 6 0.06 27 6 0.05 25 6 0.03 23 6 0.02 22 6 0.02 n.a. n.a. 74 6 0.05 70 6 0.03 n.a. 59 6 0.07 54 6 0.06 51 6 0.05 35 6 0.10 32 6 0.07 30 6 0.06 29 6 0.04

3.8E-03 6 5.1E-06 3.7E-03 6 5.1E-06 3.6E-03 6 2.3E-06 3.5E-03 6 5.3E-06 n.a. 4.1E-03 6 2.7E-06 4.0E-03 6 3.7E-06 3.9E-03 6 3.9E-06 4.1E-03 6 2.5E-06 4.1E-03 6 2.7E-06 4.0E-03 6 1.2E-06 3.9E-03 6 1.3E-06 4.1E-03 6 3.9E-06 4.0E-03 6 4.9E-06 3.9E-03 6 3.7E-06 3.8E-03 6 3.6E-06 n.a. n.a. 4.4E-03 6 1.5E-06 4.4E-03 6 1.9E-06 n.a. 4.5E-03 6 3.5E-06 4.5E-03 6 2.5E-06 4.3E-03 6 3.4E-06 4.5E-03 6 4.3E-06 4.5E-03 6 4.0E-06 4.4E-03 6 3.6E-06 4.3E-03 6 4.0E-06

6.9E-04 6 8.6E-07 6.8E-04 6 8.0E-07 6.6E-04 6 3.7E-07 6.3E-04 6 7.7E-07 n.a. 7.2E-04 6 3.3E-07 7.1E-04 6 4.5E-07 6.9E-04 6 5.1E-07 7.2E-04 6 4.7E-07 7.3E-04 6 4.9E-07 7.1E-04 6 3.3E-07 6.8E-04 6 3.1E-07 7.3E-04 6 6.1E-07 7.2E-04 6 7.6E-07 7.0E-04 6 6.3E-07 6.7E-04 6 5.7E-07 n.a. n.a. 7.5E-04 6 2.8E-07 7.3E-04 6 2.9E-07 n.a. 7.7E-04 6 3.7E-07 7.5E-04 6 2.8E-07 7.3E-04 6 4.0E-07 7.7E-04 6 5.5E-07 7.6E-04 6 5.3E-07 7.4E-04 6 4.6E-07 7.2E-04 6 6.6E-07

3.1E-03 6 4.3E-06 3.0E-03 6 4.3E-06 2.9E-03 6 2.0E-06 2.8E-03 6 4.5E-06 n.a. 3.4E-03 6 2.5E-06 3.3E-03 6 3.3E-06 3.2E-03 6 3.4E-06 3.3E-03 6 2.1E-06 3.4E-03 6 2.2E-06 3.3E-03 6 9.1E-07 3.2E-03 6 1.0E-06 3.4E-03 6 3.3E-06 3.3E-03 6 4.1E-06 3.2E-03 6 3.1E-06 3.1E-03 6 3.1E-06 n.a. n.a. 3.7E-03 6 1.3E-06 3.6E-03 6 1.6E-06 n.a. 3.8E-03 6 3.2E-06 3.7E-03 6 2.3E-06 3.6E-03 6 3.1E-06 3.8E-03 6 3.8E-06 3.7E-03 6 3.5E-06 3.6E-03 6 3.1E-06 3.5E-03 6 3.4E-06

Table 13.4 Results for design 3 with 5 2 m/s2, d 5 2 m/s2, and ns 5 2 by changing arrival rate (λ). Scenario no.

λ

Design no.

T

B

A

W

tðsÞ

u1 ð%Þ

u2 ð%Þ

u3 ð%Þ

EC ðkWh=transactionÞ

ER ðkWh=transactionÞ

EðkWh=transactionÞ

61 62 63 64 65 66

5400 6180 7200 8640 10,800 12,400

3

10

50

24

12,000

19 6 0.01 20 6 0.01 22 6 0.04 25 6 0.05 36 6 0.09 54 6 0.06

47 6 0.08 54 6 0.04 63 6 0.07 74 6 0.04 89 6 0.04 96 6 0.02

25 6 0.08 28 6 0.04 32 6 0.07 38 6 0.04 44 6 0.04 48 6 0.02

32 6 0.04 36 6 0.08 41 6 0.04 48 6 0.04 53 6 0.06 53 6 0.07

2.85E-03 6 2.97E-06 2.85E-03 6 1.96E-06 2.84E-03 6 3.85E-06 2.81E-03 6 1.19E-06 2.69E-03 6 1.56E-06 2.52E-03 6 1.08E-06

5.74E-04 6 5.49E-07 5.74E-04 6 4.17E-07 5.73E-04 6 6.81E-07 5.66E-04 6 2.07E-07 5.41E-04 6 3.43E-07 5.07E-04 6 2.15E-07

2.28E-03 6 2.42E-06 2.28E-03 6 1.55E-06 2.27E-03 6 3.17E-06 2.25E-03 6 1.00E-06 2.15E-03 6 1.23E-06 2.01E-03 6 8.72E-07

Table 13.5 Results for design 3 with 5 1 m/s2, d 5 1 m/s2, and ns 5 2 by changing arrival rate (λ). Scenario no.

λ

Design no.

T

B

A

W

tðsÞ

u1 ð%Þ

u2 ð%Þ

u3 ð%Þ

EC ðkWh=transactionÞ

ER ðkWh=transactionÞ

EðkWh=transactionÞ

67 68 69 70 71 72

5400 6180 7200 8640 10,800 12,400

3

10

50

24

12,000

24.39 6 0.38 26.43 6 0.12 30.36 6 0.09 40.09 6 0.01 80.50 6 0.03 n.a.

57 6 0.07 64 6 0.10 74 6 0.09 87 6 0.04 98 6 0.07 n.a.

30 6 0.05 34 6 0.04 39 6 0.07 45 6 0.05 51 6 0.08 n.a.

38 6 0.06 43 6 0.05 48 6 0.05 53 6 0.09 52 6 0.04 n.a.

2.7E-03 6 2.0E-06 2.7E-03 6 8.0E-07 2.6E-03 6 4.2E-06 2.6E-03 6 2.1E-06 2.3E-03 6 2.2E-06 n.a.

5.8E-04 6 4.5E-07 5.8E-04 6 1.8E-07 5.7E-04 6 9.4E-07 5.5E-04 6 4.7E-07 5.0E-04 6 5.0E-07 n.a.

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numbers of shuttles (i.e., two or three) in the system, and the system blows up due to the insufficient service rate. We excluded those scenarios from the analysis. The observations from the Fig. 13.6 are summarized as follows: G

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D, it can be observed that energy consumption is very sensitive on the number of tiers. Note that in Table 13.2, every three following designs have the same number of tiers in the system. In Fig. 13.6A
D, although every three following experiments are almost at the same row (e.g., having very close energy consumption values), when the number of tiers scenario changes (for the following next three-groups) they are usually placed at a higher level in the graph. This means that when the number of tiers increases in the system, the average energy consumption per transaction also increases. Note that in Fig. 13.6A
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has the highest value, and Experiment 6 has the least value, and so on. This pattern is correct for all number of vehicles scenarios. This is probably because, in every three following experiments of Table 13.2 designs, the number of bays decreases while the number of tiers is fixed. Hence, the travel time of shuttle decreases resulting with decreased average cycle time per transaction performance metric. The average cycle time per transaction performance metric increases with the number of tiers increase in the system design. Note, that in Table 13.2, we change the number of aisle scenario when we increase the number of tiers. Hence, in every following threegroup designs, the number of aisles tends to decrease to meet the required storage capacity. As a result, it is observed that when the number of tiers increases and number of aisles decreases in the system, this affects both energy consumption and cycle time performance metrics negatively. When we look at the Fig. 13.6 graphs from a multiobjective perspective namely, when one would like to minimize both E and t performance metrics simultaneously, the experiment closest to the origin would be the best one. This is because the minimum values can be obtained

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at the origin area. Hence, Design 3 seems the best one having the least E and t in overall experiments. Note that Design 3 has 10 numbers of tiers, 50 numbers of bays, and 24 numbers of aisles. This may mean that having a small number of tiers and a large number of aisles in the system, improves both performance metrics. One may prefer focusing on such designs.

13.5.1.1 Effect of number of shuttles on average energy consumption per transaction From Design 3, it is understood that having decreased number of tiers and bays with increased number aisles in the warehouse works better. This is probably because by that, the mean arrival rate at each aisle decreases and this performs more efficiently. In Fig. 13.7, we focus on the decreased number of bays designs (i.e., B 5 50) resulting with increased number of aisles in the system. Fig. 13.7 shows how E changes based on the number of shuttles (nS) in the system. We also show the average utilization values of shuttles (u1) under each design. From Fig. 13.7, it is observed that the net average energy consumption per transaction—E—value decreases with the increase of number of shuttles, nS. Hence, one may focus on the increased number of shuttles per aisle, while decreasing the number of tiers in the system, to decrease the E value.

13.5.1.2 Effect of arrival rate on the both performance metrics Once again, it is found to be the Design 3 that has the least E in the system. Since this design also has the least t in the system, it also has the lowest u1 value (e.g., 21%, 13%, 9%, and 7% u1 values for the number of shuttles 2, 3, 4, and 5, respectively, see Fig. 13.7). Since we would like to have decreased number of shuttles in the system to decrease the initial investment cost, we focus on the two number of shuttles scenario T=10, A=24

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for Design 3. By focusing on this design, we increase the arrival rate at the system to increase the u1 value and hence the throughput rate in the system. For that we draw Fig. 13.8 showing E versus λ and t graph based on the u1 values when nS 5 2. From Fig. 13.8 it is observed that after a certain point of arrival rate or the u1 value, the E tends to decrease drastically. Therefore, one should focus on working with high utilization values in such systems, to decrease the E in the system. This decrease is probably due to completing less vertical travel of lifts. When there is high number of transactions in the system, the process scheduling in queue of the shuttles may be operated more efficiently, so that the lifts complete a less number of vertical travels. For instance, when arrival rate is high, a shuttle may find a transaction at its current tier more often and this results with less vertical travel and decreased energy consumption in the system.

13.5.1.3 Effects of acceleration/deceleration values on both performance metrics Because it has a significant effect on energy consumption and regeneration calculations as well as on the time of reaching the maximum velocity of shuttles, acceleration/deceleration values of shuttles are evaluated at this time. Namely, E versus λ values are drawn based on two velocity and acceleration/deceleration scenarios as 1 m/s, 2 m/s; 1 m/s2 and 2 m/s2. Fig. 13.9 shows those results. Note that those experiments are run for Design 3 with two shuttles. In those graphs, the average utilization values of shuttles are also shown. As seen in Fig. 13.9, low acceleration and deceleration values generate decreased E with higher average shuttle utilization. In an effort to reduce the

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Figure 13.9 Average net energy consumption versus average cycle time per transaction by hourly arrival rate and acceleration/deceleration values.

energy consumption in the system, one should focus on the decreased velocity profiles in the system. Note, that the analyzed figures are drawn from the Table 13.3, Table 13.4, and Table 13.5 values. For instance, Table 13.3 shows the results for experiments with high velocity profiles; Table 13.4 shows that results for Design 3 with two number of shuttles by also changed arrival rate scenarios under high velocity profiles and; Table 13.5 shows that results for Design 3 with two number of shuttles by also changed arrival rate scenarios under low-velocity profiles.

13.6

Suggested future works

This study can be extended in many directions. One may include more warehouse design scenarios in terms of number of aisles, tiers, bays, and velocity profiles in the experimentation. Another might be including a cost analysis to show the benefit of tier-to-tier SBS/RS design in terms of decreased investment cost. A multiobjective optimization by drawing a Pareto-optimal solution between energy consumption and average cycle time would also be a promising work.

13.7

Summary

In this work, a novel automated warehousing design, SBS/RS design with tier-totier shuttles, is studied. Our aim is to search a good warehouse design in terms of

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number of tiers, aisles, bays as well as shuttles in the studied tier-to-tier SBS/RS. Fifteen different warehouse designs are developed and run for 4 different number of shuttle scenarios. The system performance is evaluated mainly for average energy consumption and average cycle time per transaction in the system. After running the predefined 15 experiments, by using the knowledge of initial results, the analyses are extended and more experiments are conducted for instance for different velocity and acceleration/deceleration values. Results show that increased velocity profiles increases the average energy consumption per transaction in the system. In addition, increasing the number of tiers and decreasing the number of aisles increase the energy consumption in the system. It is also noted, that an increased number of shuttles tend to decrease the average energy consumption in the system. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

13.8

Chapter review questions/exercises

13.8.1 True/false 1. True or false? The same rack configurations and velocity profiles for lifts and shuttles are considered to calculate the desired performance metrics. 2. True or false? The SBS/RS warehouse is divided by three storage sides in an aisle. 3. True or false? Arriving loads for storage transactions are transferred by conveyors in totes. 4. True or false? The verification and validation of the simulation models are done by animating the model and by comparing an input from the system (i.e., average cycle time/ transaction) with a practical one by the experts. 5. True or false? To facilitate the modeling, two aisle are simulated by considering that the mean arrival rate at these aisles (λA) follows the Poisson distribution.

13.8.2 Multiple choice 1. The average cycle time per transaction performance metric increases, while the number of tiers increase in the: a. System design b. Human-centered design c. Sufficient design d. ICT-enabled design e. Preferred design 2. Having a small number of tiers and a large number of aisles in the system, improves both: a. Health metrics b. Safety metrics c. Housing metrics d. Performance metrics e. All of the above

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3. One could focus on the increased number of shuttles per aisle, while decreasing the number of tiers in the system, to decrease the: a. E value b. I value c. U value d. A value e. T value 4. When there is high number of transactions in the system, the process scheduling in queue of the shuttles may be operated more efficiently, so that the lifts complete a less number of: a. Vertical travels b. Horizontal travels c. Diagonal travels d. Linear travels e. All of the above 5. In an effort to reduce the energy consumption in the system, one should focus on the __________ velocity profiles in the system. a. Analyzed b. Enhanced c. Deteriorated d. Increased e. Decreased

13.8.3 Exercise 13.8.3.1 Problem Design an automated warehouse that stores goods and materials; as well as, allowing for the regular circulation of occupants, vehicles, and machinery, that are typically associated with the handling of these goods and materials.

13.8.4 Hands-on projects 13.8.4.1 Project Develop: Create an energy efficient automated warehouse management software, that should be simple to integrate and easy to use, and be effortless to upkeep and scale—as business priorities change.

13.8.5 Case projects 13.8.5.1 Problem Design an energy efficient automated warehousing operation that moves from the traditional time-based perspective to an energy-based one.

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13.8.6 Optional team case project 13.8.6.1 Problem How does the integration of rooftop photovoltaics affect the design and performance of refrigerated energy efficient automated warehouses, which are becoming the preferred choice for frozen food storage facilities?

Acknowledgment This work was supported by The Scientific and Technological Research Council of Turkey and Slovenian Research Agency: ARRS [grant number: 118M180].

References [1] ,www.amazonrobotics.com., 2019 (accessed 11.10.19). [2] European Materials Handling Federation Business Trend Report. Received from: ,https://www.fem-eur.com/wp-content/uploads/2019/02/IS-Annual-Factsheet-2017. pdf., 2017. [3] G. Marchet, M. Melacini, S. Perotti, E. Tappia, Analytical model to estimate performances of autonomous vehicle storage and retrieval systems for product totes, Int. J. Prod. Res. 50 (24) (2012) 7134
7148. [4] G. Marchet, M. Melacini, S. Perotti, E. Tappia, Development of a framework for the design of autonomous vehicle storage and retrieval systems, Int. J. Prod. Res. 51 (14) (2013) 4365
4387. [5] H.J. Carlo, I.F. Vis, Sequencing dynamic storage systems with multiple lifts and shuttles, Int. J. Prod. Econ. 140 (2) (2012) 844
853. [6] T. Lehrer, Y.B. Ekren, Z. Sari, B. Rosi, Simulation analysis of shuttle based storage and retrieval systems, Int. J. Simul. Model. 14 (1) (2015) 48
59 (2015). [7] T. Lerher, Travel time model for double-deep shuttle-based storage and retrieval systems, Int. J. Prod. Res. 54 (9) (2016) 2519
2540. [8] T. Lerher, B.Y. Ekren, G. Dukic, B. Rosi, Travel time model for shuttle-based storage and retrieval systems, Int. J. Adv. Manuf. Technol. 78 (9-12) (2015) 1705
1725. [9] B. Ekren, Graph-based solution for performance evaluation of shuttle-based storage and retrieval system, Int. J. Prod. Res. 55 (21) (2017) 6516
6526. [10] B.Y. Ekren, A. Akpunar, Z. Sari, T. Lerher, A tool for time, variance and energy related performance estimations in a shuttle-based storage and retrieval system, Appl. Math. Model. 63 (2018) 109
127. [11] Y. Wang, S. Mou, Y. Wu, Task scheduling for multi-tier shuttle warehousing systems, Int. J. Prod. Res. 53 (19) (2015) 5884
5895. [12] E. Tappia, D. Roy, R. De Koster, M. Melacini, Modeling, analysis, and design insights for shuttle-based compact storage systems, Transportation Sci. 51 (1) (2016) 269
295. [13] M. Eder, An analytical approach for a performance calculation of shuttle-based storage and retrieval systems, Prod. Manuf. Res. 7 (1) (2019) 255
270.

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[14] B.Y. Ekren, A Simulation-based experimental design for SBS/RS warehouse design by considering energy related performance metrics, Simul. Model. Pract. Theory (2020). in press. Available from: https://doi.org/10.1016/j.simpat.2019.101991. [15] Y. Ha, J. Chae, Free balancing for a shuttle-based storage and retrieval system, Simul. Model. Pract. Theory 82 (2018) 12
31. [16] Y. Ha, J. Chae, A decision model to determine the number of shuttles in a tier- to-tier SBS/RS, Int. J. Prod. Res. 57 (4) (2018) 963
984. [17] X. Zhao, Y. Wang, Y. Wang, K. Huang, Integer programming scheduling model for tier-to-tier shuttle-based storage and retrieval systems, Processes 7 (4) (2019) 223.

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Tuncay Ercan and Mahir Kutay Faculty of Engineering Universite cad., School of Applied Sciences, Yasar University, Izmir, Turkey

14.1

Introduction

The biggest danger awaiting smart utilities is the depletion of limited resources or the inability to meet the current demand, due to the rapidly growing population and economic growth. Smart-city identity is always prominent in investments and digital applications to ensure sustainability throughout the world, especially in big cities. Intelligent city designs focused on the effective use of resources, also provide better service to the people of the city and protect the environment. However, the opposite situation negatively affects the economic and social life of the cities and decreases the quality of life of urban residents and decreases the brands and competitiveness of cities as well. At this point, the potential of producing rational solutions for different smart services such as electricity, natural gas, water and waste water, public transportation, which are integrated with the people of the city, started to come to the fore in the country’s policies. However, our local administrations within the government and companies try to adapt to some technological developments in the area of digital technologies, Internet and data communication infrastructure, Internet of Things (IoT), mobile systems, and cloud computing in order to find reasonable and effective solutions. With this approach based on the logic of self-management of urban infrastructures and networks without the need for human intervention, especially for water and energy, it is aimed to achieve a significant improvement in people’s living standards. This means the smart services approach should only be seen as an integrated approach aiming to increase the quality of life of citizens rather than different applications of information and communication technologies (ICTs). Fig. 14.1, “ScottMadden Management Consultants” company, summarizes the objectives of different smart utilities and corresponding technologies to employ and integrate within the smart city [1]. In this context, the following urban development phases complement each other: G

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Increasing the efficiency of urban service systems, especially water and energy Increasing efficiency in these services by meeting the expectations of citizens Development of transportation and other urban services

Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00014-0 © 2021 Elsevier Inc. All rights reserved.

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Figure 14.1 Smart utilities and underlined technologies [1].

With the support of smart-city technologies and infrastructures for energy and water management, transportation, and environmental issues brought by the crowded population in cities, a fast, sustainable, and safe solution can be provided by central management that is citizen-management intertwined. Intelligent environmental services cover the solutions such as electrical energy, smart grids (SG), microgrids, energy-efficient smart street lighting, smart meters, advanced air pollution monitoring systems, waste management, smart water management systems, and public transport systems. With the determination of smart-city standards and regulations, the establishment and expansion of cities, countries will be able to use all their resources more efficiently. Existing management models will give more sustainable and faster decisions with the smart decision support systems and investments can become more long-term and planned. Although the population growth of cities is the main driving force in the adoption of smart services, another important responsibility of government agencies is to provide effective solutions in city management, especially in smart homes, smart transportation, smart energy management, and other smart services [2]. With the growth of cities, some side effects are also revealed. These are the hours in traffic, air pollution, and lack of clean water, waste management problems, overflow of the population, and consequently increase in crime rates and the threat of human security [3]. However, while utilizing smart technologies, smart utilities do not focus on not only a single reason or benefit but also attempt to handle many different positive initiatives, such as adapting their own technologies to individual customers and different organizations [4]. In this chapter, we survey how the requirements of different utility services offered to the public in a city for their usage and how public or private service providers effectively manage their systems. The chapter is organized as follows. First, we present the importance of utilities and utility management for people and

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organizations. Section 14.2 surveys how the most advanced systems fulfill present-day requirements. We will also discuss the state-of-the-art technologies from the point of utility service management with a comprehensive literature survey in each related section. In Sections 14.3 14.6, we cover electricity, water, natural gas, and other smart utility systems in detail and give examples from the worldwide applications. Section 14.7 gives a summary of the chapter.

14.2

Smart solutions

14.2.1 Overview In spite of the rapidly growing urban populations, the hope of city administrations to build livable cities is indispensable in order to create a sustainable world. The answer to the question “What makes a city so livable?” is that a livable and therefore sustainable city is primarily a city where people can reach where they want without having to travel a lot or spend a lot of time in traffic. In addition, water and energy consumption should be evaluated in order to determine how sustainable a city is. If we put transportation, water, and energy aside and look through the eyes of individuals, a livable city should first be safe. In reality there are some other questions that need to be answered for livable cities like “How many kids are on the streets?,” “How many of them are cycling?,” “Can they ride the bus alone?,” “How many older people can easily handle their work in the city?” On the security side for smart living applications such as live broadcast cameras, security cameras system, vehicle tracking system are available in almost all developed and developing cities. On the health side, there are applications that will facilitate the participation of Alzheimer’s and mentally disabled citizens in urban life. On the tourism side, live broadcast cameras, audio guide systems for museums, and mobile tourism atlas services are provided on the mobile platform. There are intelligent signalized intersections, green wave system, detector intersections, and interchangeable message signs applications regarding smart transportation. In this part of the book, we will focus on solutions to how smart services like electricity, water, and natural gas are provided by state and private organizations while leaving others out of scope for now. The energy, which is mostly both the source and the solution of the problems in the cities, it also refers to the production power and viability of the city. While almost all cities have been included in the global network of relationships with their original identities all over the world or at least with their border neighbors, energy has become the main carrier in both the formation of this network and in the establishment of cities. The cities that have owed all their life force to energy since the day they were founded, have become the prisoner of energy today. However, the human mind has to use energy again to solve all these problems. The only solution for this energy dependency is the correct and effective use of energy resources. Therefore, in addition to the right energy policies, expansion and growth of cities should be planned accordingly.

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In this section, we define what we mean by smart utilities. First, we will summarize what customers’ needs and expectations are about smart services and their use. Second, we will describe the need for energy and the balance of energy supply and consumption for cities. Thirdly, we will provide information about what needs to be done for intelligent energy infrastructures and smart metering and pricing about the existing systems all over the world.

14.2.2 Consumer requirements and expectations Knowing the expectations of the citizens as the customers are very important to catch the quality in the services since the city utilities like electricity, water, and natural gas are some of the important services given to the citizens. The way you know the expectation of the customer will allow you to win in the long term as long as you experience a successful business partnership. However, expectations are not enough to know. Adopting the win-win philosophy by giving them more in the direction of customer expectations is also an important factor in the relationship between the service provider and the citizens. You can also have a positive image for your services while customers whose expectations have been compensated continue to prefer you. Regardless of what service is provided, setting up an effective customer relationship management with the ongoing technological developments is a must for all service providers. A multimedia gateway for users to communicate with their service provider in any way they wish such as mobile applications, websites, SMS messages, and phone calls will provide the advantages listed as follows [5]: G

G

G

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A centralized customer service call center A platform to bring citizens together for community engagement of common interest A platform for service providers to listen to citizen complaints A rich source of open data that can inform residents about service-related issues A data-powered tool for monitoring the status of individual user services

Increasing population density due to urbanization and economic developments increases the need for energy usage day by day. However, environmental problems may also arise due to energy use. In this context, government and service provider institutions should work on providing clean and renewable energy in cities. Producing the energy needed in the most accurate, the most efficient and the most compatible with nature, without risking the needs of future generations should be interpreted under the concept of sustainability. It will be easy to manage the economic and natural consequences of this dependence to the extent that we can prioritize saving sensitivity from the point of social and individual consumption habits. As a result, since there is no unlimited resource, savings or efficiency will be the most basic energy solution for cities. Since the issue of efficiency is not a one-time saving, because it is a culture, an unchanged correct use is very important as it creates a continuous saving opportunity. Therefore, a change in our understanding of production is required to cope with increased energy demand as in the understanding of consumption. Although the

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possibilities of nature are processed with the most advanced technology to meet the huge energy needs of cities, there are no longer big or small companies in energy production. There are also systems in which everyone, every building, every business can generate a small amount of energy that can be shared by the whole city through smart grids.

14.2.3 Energy need Throughout history, there has been a natural relationship between cities and energy. In the same way, it is appropriate to say that energy is an important element in all urbanizations that arise as a result of the simple necessities such as water and heating. Therefore, we can easily say that energy is very important in the construction of modern life. Every innovation, every development in our era brings with it the energy need. As there is an economic cost in every new technological development or infrastructure investment, there is also an energy cost. Especially for the last 200 years, different forms and models of production and consumption have been changing at a dizzying pace. Naturally, the energy need and necessary infrastructure for this change continue to keep pace with this speed. In this context, when we consider the changing social consumption habits and the modern city structure, we witness a nonstop dynamism. To put it more clearly, the fact that production is based largely on the energy infrastructure brings greater responsibility for its management. The production mechanism that never stops, in this respect, needs a continuous and high-quality energy supply. This side of the business is also the responsibility of the governments than the service providers. These management units should ensure to meet the energy needs of both manufacturers and residents of the city with a visionary strategy, correct planning, and perfect practice. The right management of this process will be of great benefit to keeping the relationship between city life and energy in a secure infrastructure relationship rather than dependency. The biggest buyers of increasing energy production are undoubtedly cities that are growing every day. Thanks to their advanced infrastructure facilities, cities are now the locomotive of economic growth. The cities where the industry is concentrated are also among the regions where electricity consumption increases rapidly. In order to meet this need, the on-site production of electricity is very important. Otherwise, electricity is produced in remote areas and transported to industrial intensive areas causes huge cost losses. Since the electrical infrastructure is: (1) affected by all-weather; (2) affected by long line losses; this increases the investment required for continuous and high-quality energy supply. As long as there is no on-site production, you can not minimize the risk and sustain such a large cost.

14.2.4 National energy plans Clear, well-defined results that can provide reliable, cost-effective, and environmentally sensitive energy in all planning activities, must meet expectations in order to achieve a national energy policy. Realizing such a plan requires both the use of

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new technologies and detailed planning and cost control, as well as project-based work and the coordination of all responsible stakeholders. Critical service providers and contractors should be prepared for major projects in the following areas for the clean use of fossil fuels without environmental pollution and for the development of renewable energy sources: G

G

G

G

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Wind and solar power Electricity transmission and storage, electric vehicles New nuclear reactor design and installation Other renewable energy sources Nonpolluting use of coal and natural gas Environmental protection

14.2.5 Resource availability In order to meet the increasing energy demand, new primary energy sources are being supplied and the number and capacity of the cycle power plants where energy conversion is required. Primary energy sources (coal, natural gas, wind, solar, hydro, fuel oil, etc.) are mainly used by industry, housing and services, transportation, cycle power plants (electricity generation), agriculture, and other subsectors. In every country, the production and consumption sectors have to use energy resources in order to meet the demands of the increasing population both in quality and quantity. In this context, the increasing urban population, environmental concerns, especially climate change and air pollution, brought about the efficient use of energy supply and consumption. When we look at the distribution of electricity used in cities, a large part of it is caused by the use of heating/cooling, transportation, lighting, and electrical machinery equipment and household appliances.

14.2.6 Smart infrastructure The purpose of making the cities more livable can be called smart-city solutions as the same equivalent meaning with technological developments in the city infrastructure. In urban life, which is complicated by its ever-increasing population; efficient use of resources in meeting vital needs such as energy, health, transportation, and communication is very important. The complete integration of these infrastructures to each other and working effectively is also another important matter for being smarter. The information collected from the smart meters and devices of these different services will be processed together to create the opportunity for better decisions in city management through accurate business analysis [6]. In order to respond to the unlimited needs within the framework of sustainable development in the urban life, it is necessary to establish an infrastructure equipped with intelligent solutions where the change itself and the problems it brings increase steadily. The IoT evolution brings the capabilities of open systems and standards through the existing communication technologies to collect real-time data from the infrastructures and enables them to extend both customer and government value

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propositions. Facing the energy sector, SG systems stand out for the construction of modern and integrated infrastructure. One of the most important elements of continuous and high-quality energy supply to the consumer is to use the resources in the most efficient way. An energy infrastructure based on efficiency from production to distribution, from the transmission to system software, namely, the SG system will contribute to sustainable city life by providing advantages such as efficient use of resources, further integration of green energy into the system and energy saving.

14.2.7 Virtual utility Virtual controlled critical services can be defined as a new energy infrastructure model that integrates different types of distributed production utilities into the energy generation network controlled by a central energy management system (EMS). This explains the need for an intelligent network to establish digital communications and data paths between critical systems and provides information flow for power generation, transport, and use. Consumer requirements shape the market for real demand responses (DRs) with environmental benefits. They also better understand and control their energy usage and become more interactive participants with VU. If this is for the seamless integration of electricity and heat energy sharing, VU will participate in the creation of user-friendly Internet solutions through the effective use of smart meters, intelligent grid, and distributed generation [7]. Electricity generation in SGs depends on the heat levels that users need. Electricity is generated in various production facilities in different regions and is again distributed to users in different regions. Such a system includes EMS, different production facilities, and different heat storage tanks if necessary. Each of these separate systems is controlled by the local management station (LMS). Each LMS has the information for the heat and electrical requirements of the users connected to their cluster, as well as the storage tanks and water levels present in the cluster. EMS receives the information it needs about the distributed systems from regional LMS and can adjust the electrical input or output of each cluster in the network. LMS sets the utilities in its cluster to run or wait with information that is managed or supplied by EMS. In addition, each LMS can operate independently of EMS.

14.2.8 Benefits of VU model Power generation systems consist of one or more large power plants connected to consumers through a global distribution network (DN) (central configuration). In case of failure of the power plant or distribution system, all or part of the demand cannot be met. However, in a VU configuration, failure of one of the elements or one of the distribution systems does not affect the function of the whole system. The distribution infrastructure of the VU does not need to transport large amounts of energy from the point of production to the point of demand, because they are more likely to meet regional needs. Since the amount of electricity generated will be less, fuel consumption and emissions are lower. This distributed generation structure and features of the VU network allow the use of renewable energy

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resources (RES) to be more used and incorporated into the main grid. Because the network can be configured over and over again, for example, the integration of solar collectors to the VU system from time to time can be easily managed. In such a case, the solar collectors can transfer the energy to the VU cluster as soon as they collect sufficient thermal energy. “Virtual Power Plants” use solar panels, batteries and software to create that store excess power and release it to grid system when needed [8]. One of the advantages of VU is that it can react to changes in energy demand or prices due to the large number of small units that make up the distributed energy network. When the energy demand of a VU cluster suddenly changes, the system can meet this demand quickly. As soon as EMS receives the first notification of the change, it orders some of the other clusters to come online to take over this new demand. The need for more flexible, resilient grids in the face of increasing distributed energy resources (DERs) has made distribution automation (DA) the more critical. DA brings together digital sensors and switches with advanced communication and software to automate activities on the distribution grid, thus providing increased visibility across the system. As utilities are increasingly faced with requirements for consumer capacity analyses for distributed resources, DA has become a fundamental building block for the utility management of the future [9].

14.3

Electricity

14.3.1 Overview The cities have to use energy in the most efficient way for today’s more and more diminishing energy resources. If this efficiency is not achieved, power outages, and high prices will be unavoidable. The first step in the process of transforming energy systems into intelligent structures is planning. Thanks to the smart meters installed in the house, it is possible to monitor the use of electricity at every point of the house. This data is collected in a centralized system and provides electricity producers with the opportunity to plan on how much electricity should be produced for a specific time of the day. For example, when urgent energy demand from a region is received, the system will be able to detect this and give an alert to increase the capacity of the power plant or perform this process automatically within the framework of the protocols. With the help of information systems that control the network from end to end, the losses and leaks will be minimized. The increase in the rate of urbanization and the increase in the population increased the demand for electricity. Although electricity production in countries varies, it is mainly carried out from two main sources: Fossil fuels and renewable energy sources. In recent years, electricity generation from renewable energy sources has increased significantly in almost all countries. Therefore, countries have reviewed the electricity production regulations from renewable energy sources. Thus, by increasing tariffs in-unit electricity generation through diversified

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tariffs for wind, solar, hydro, geothermal, and biomass, producers were further encouraged for additional investment. In addition, each country paved the way for additional support to power plants using domestic renewable energy technology and equipment as part of its main strategies of reducing foreign dependency in energy. Especially with the support of the state in this field, it has become easier for the domestic industry to produce national energy technologies. With the direct use of the energy produced from the sun in city life, the losses and leaks in electricity transmission and distribution will be minimized, and power plants that more economic, esthetic, and suitable for urban architecture without emission, will be ensured. It is necessary to expand the solar panels in the city in accordance with the city architecture in order to make more use of solar energy in electricity generation. The stadium, parks, building tops and surfaces, conference centers, and public buildings with large surface areas must be identified as areas of priority for the solar panel. In this way, the economic sustainability of the facilities is ensured and the fight against climate change is provided. In recent years, energy efficiency applications (insulation, new lighting technologies, efficient household appliances, etc.) are among the factors that reduce the energy consumption per unit house. Building energy efficient homes and new construction techniques recently has become a new industrial market. A home is built with modern materials and appliances to conserve resources in order to prevent cracks and seams [10]. Today’s power systems were established in 1883 according to Tesla’s design principles. Although central production, demand control, and one-way transmission systems are reasonable in time, they are now expressed as obsolete according to current needs. It is stated in many sources that the existing networks need a complete renovation with careful engineering. With the help of the smart meters which are developed by the developing electronic industry, the smart network structure has become a data collection and management system extending to the end-user. In this context, the EU member states and candidate countries will be able to achieve the 20-20-20 target set by the European Union (20% of energy will be produced from renewable sources, 20% CO2 emissions will be reduced and energy consumption will be reduced by 20% in 2020) have started to undertake the necessary infrastructure works. To reduce the electricity bill, discounted electricity companies offer discounted or fixed-price tariffs per unit energy cost. To take advantage of the green tariff, some suppliers offer green tariffs where they sell electricity generated from fully renewable energy sources. For better customer service, the new electricity companies entering the market try to be more easily available to compete and accelerate the customer’s transactions with technological applications. Energy efficiency in cities can be achieved by reducing the energy consumption used for basic needs such as transportation, heating, and so on, and meeting them with the most efficient method. Municipalities are very important to adopt energy efficiency to the public and to take effective measures in buildings and urban transport. It should not be forgotten that energy efficiency is not only a technical issue but also a behavioral issue. Municipalities can reduce their energy consumption by reducing energy consumption costs in the buildings and equipment they have, along

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with the transportation, cleaning, water supply services they perform, and by including the measures taken in land use plans. The following strategies come to the fore for the cities to use energy effectively and efficiently; G

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Environmentally sensitive structuring: Structuring suitable to geographical environment, placement of buildings according to the heat and light factors, and low energy consumption material preference Use of energy technologies: Installation of renewable energy systems in suitable areas, SG infrastructure, and district heating Provide energy efficient service and awareness: energy efficiency awareness-raising activities and development of energy-efficient applications in services

14.3.2 Infrastructure Electricity generated by power plants includes a complex infrastructure (stations, transformers, and power lines) that connects all electricity producers and consumers, and is called a grid. The majority of local networks are interconnected for reliability and commercial purposes and larger electricity networks have been established that improve the coordination and planning of electricity supply at the entire regional/nation level [11]. The entire electricity grid across the country includes the DN and high/low-voltage power lines that connect thousands of power plants to millions of electricity customers. Fig. 14.2 shows the main spots in this infrastructure. Electricity produced in power plants reaches the regional consumer target by following the high-voltage transmission lines consisting of electrical metal towers. First, the voltage adjustment is made in the transformers and then connected to the customers via city poles or underground systems [11]. Countries’ electricity transmission and distribution infrastructures should aim not only to meet current or future expectations but also to integrate effectively with other alternative renewable energy sources such as wind power. Governments or

Figure 14.2 Electricity generation, transmission, and distribution [11].

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responsible service provider private organizations apply changes in existing laws or policies from time to time due to the changing technological conditions or increasing costs. This naturally causes infrastructure changes. Investment needs for SG modernization projects that enable reductions in electricity bills, improve system reliability, and increase fuel and system efficiency [12]. Smart electricity infrastructure systems include the following requirements [13]: G

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Improve electricity reliability and higher levels of system efficiency Increase energy conservation and support smart meters Integrate usage data into centralized data systems Monitor circuits to better service restoration

A unified structure for distributed and different energy systems provides interoperability in many different devices for the required utility operations beyond smart meters. Such a structure allows communication and processing for all different data if it has sufficient real-time monitoring and bandwidth. Real-time monitoring helps that the future energy supply networks should be able to handle with grid outages (like an increase of short circuit current) and instantaneously disconnect the section where the outage occurs.

14.3.3 Regulations and standards The standards will support DA applications and the integration of all equipment. The construction and the characteristics, and performances to be carried out on HV, MV, and LV (HV: high voltage; V $ 60 kV. MV: medium voltage; 1 kV , V , 60 kV. LV: low voltage; V # 1 kV) installations, as well as the types of equipment used, are subjected to national and international technical standards and regulations. Manual operation of existing equipment in the system, maintenance or network restructuring, obligations of operating personnel, procedures to be followed, security measures to be applied are regulated according to national and international standards and national laws [14]. Standards also play an important role in electrical installations as they provide common rules that can be applied to all components involved in different phases of any project. Standards are also organized into a number of topic areas as electrical and power appliances. For certain applications, additional standards and application codes are often required. The most important issue in determining these standards is whether the standards are still valid. Consumer electricity services are regulated by national and/or local agencies. These organizations manage usage fees, service conditions, their own budgets and new infrastructure plans, programs for energy efficiency and other services. Two basic principles justify state control of the public service sector. First, a utility is an industrial sector for both individuals and businesses, as it provides basic services for the welfare of society. Second, economic regulation is a market-open public or government intervention required to regulate public benefits that small or large local or national firms operating in the same sector cannot achieve on their own due to competition [15].

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14.3.4 Ongoing failures of existing networks The challenge faced by many governments and politicians in the country is to provide safe and reliable electrical energy to industry and society continuously despite population growth, economic growth and demand for modern technology [16]. When we look at the current network system in general, we can see that large and various power plants are connected with long transmission lines and operated with alternating current. In the event of a failure at any point in these lines, the entire network is in danger of collapse. In fact, these failures can pass from one country to another. Other shortcomings of existing networks are listed as follows: G

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Difficulty in reactive power control due to bidirectional energy flow Unwanted voltage changes due to changing active and reactive power Flicker and harmonic production is not within the required limits Short circuit current limits and thermal resistance capacities of existing network elements Increasing the effects of short circuit currents according to the connection groups of the transformers on the network and changing the selection criteria of the relay continuously Network stability is not within the limit values in temporary situations such as switching and instantaneous switching events

Recently DR programs have become an important tool to reduce excessive demands on regional power networks and to provide more reliable access to electrical energy. Many countries have tried DR applications and incorporated such permanent elements in the electricity sector and/or similar programs into their management programs [16].

14.3.5 Advanced control methods The main purpose of developing different control systems in electricity generation and distribution is to minimize energy consumption. It refers to a collection of devices and algorithms that analyze and estimate the state of the network. It automatically prevents or interferes with power failures and power quality problems by taking corrective actions. Naturally, different user interactions in a system include considerations to give each user the feeling that they control their environment on the system [17]. SGs have software and hardware components. Smart meters and smart home appliances stand out as hardware components. Considering that we spend about 70% of our energy consumption on heating-cooling, the necessity of smart thermostats that can be programmed, that are able to learn our usage habits and adapt dynamically is an indisputable fact. The software includes data infrastructure, Internet-based systems, and intuitive routing software for integrated communication systems. These systems, which are connected to the networks of GSM service providers in countries, can display instant consumptions as personal or institutional energy monitoring services by using different mobile applications developed by the software developers [18].

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14.3.6 Smart energy hub As countries implement policies that promote their energy efficiency, distributed generation and renewable energy sources, and the share of energy used by customers increases. The combination of different energy sources may be an appropriate solution to improve the performance of existing DR programs. By combining the storage of distributed power generation and DR opportunities, countries can reduce the problems associated with distributed generation and reduce or increase the different usage values in the electricity market according to customer demand [19]. The connections between the different energy carriers enable customers to participate in DR programs as integrated DR (IDR), not only by changing the load but also by changing the source of their consumed energy. IDR programs can be implemented in an energy hub called an intelligent smart energy (SE) center. This system requires a two-way communication network and information technologies to be established between customers and utility companies. Thus, while demand is reduced compared to the electricity distribution company, consumption from the customers’ point of view does not change. Because the electricity source is converted to natural gas by the energy hub. This time the natural gas distribution company is also benefiting from IDR by selling more gas to customers. With IDR, energy users not only change their energy consumption, but can also change the source of the energy consumed. Fig. 14.3 shows a sample IDR program [20]. The information technologies used in the SE centers provide customers with real-time information (cost for each consumption model). In particular, EMS can be used for real-time data exchange between companies and customers through this two-way communication in SE companies. In addition, the spread of technologies that can be used especially for the integration of heat and power systems has accelerated the integration of different energy sources into the energy centers. Here,

Figure 14.3 Integrated demand response [20].

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customers at SE centers can switch energy sources during peak hours, for example from electricity to natural gas [21].

14.3.7 Smart grid The network system that is obtained by integrating the computer and network technology of our age into the existing utility networks is called SG. The SG is basically the electricity DN, which is shaped by the integration of operation, information and communication systems. SGs provide a two-way, real-time transfer of information from energy production to consumption, providing a sustainable, safe and energy-efficient energy network. The basic components and technologies of a smart network are as follows: 1. 2. 3. 4. 5. 6.

Smart production Smart stations Smart distribution Smart meters Integrated communication Advanced control methods

Artificial intelligence (AI) can make SGs smarter because power generation, distribution, and transmission can be optimized automatically and the entire grid can be operated independently of human intervention. By using appropriate sensors and machine learning techniques, adjustments in wind turbines by adapting to changes in wind conditions, can be continuously updated to maximize production efficiency. With machine learning, supply, and demand peaks are envisaged, and renewable power resource use in the system can be maximized. Machine learning techniques, combined with intelligent cables, can optimize the entire system according to the current grid load and the portfolio of buildings, providing real-time power distribution. Modern technological products (drones and very small flying robots) can identify and predict errors by examining the entire system without interrupting production and operation. This means that on-site staff can receive real-time updates in less time for troubleshooting [22].

14.3.8 Advantages of smart grids The main advantages of the smart network can be listed as follows: G

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Smart networks can reduce the need for human resources by providing remote and instant monitoring and control of energy consumption will allow remote and instant monitoring and control of energy consumption. It will ensure the improvement and development of transmission and distribution infrastructure. It will be able to self-heal to detect and correct emergency situations before they occur or to prevent them from occurring. By comparing the electricity consumption rates in real-time at certain points, the electricity loss-leakage ratio can be reduced.

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SGs will allow the distribution of electricity generation and distribution structure. In this way, as in the case of classical networks, a problem that will arise at any point in the network related to production and distribution will generally prevent all users from affecting. It provides an increasing amount of network management to electricity distribution and transmission companies. Communication with subscribers in electronic environment will be provided and commercial losses will be reduced. Accrual—collection rates will increase, the system will operate more balanced, technical losses will be reduced, quality will increase. By enabling smart home automation projects (refrigerator, air conditioning, etc.) to be implemented, the consumer will be able to play their own role in the optimization of the operation in the electrical system. Consumers can purchase electricity with more dynamic pricing. About 20% 25% savings in electricity costs will be provided. Since it will generate as much electricity as the electricity to be used, it will be an important step for the target of red-using carbon emissions adopted in the Kyoto Protocol. It makes easier to integrate renewable energy sources into the distribution system. Energy investments can planned efficiently. It will create a solid infrastructure for electric vehicles. In addition to low usage costs, it will provide great facilities for production management system. Most importantly, the existing capacity will be used more effectively and accurately

14.3.9 Smart stations Increased use of renewable energy sources may require some decentralized technological solutions. Power supplies used in these energy systems are close to the end user. Thus, transmission and distribution losses to customers in a particular region can reduce economic and environmental costs [23]. In order to best support the individual needs in the regions, the smart technologies needed should be used in many places and the generated energy should be delivered to the customers’ homes with little loss. Smart stations offer innovative energy services from the monitoring of power factor performance, breaker, transformer, and battery status to critical and noncritical process control [24]. A released “Energy Systems: A view from 2035” report suggests that the trends for electricity transformations in Future will continue to become smarter with renewable and distributed generation. Electricity will be lower carbon and local in the coming years, and this will allow the consumer to produce almost at the level of distribution. Traditional gas-fired power plants will continue to help balance the system for electricity consumption across the country, but cuts will be largely overcome by battery storage at production points, networks, homes and workplaces. [25]. Distributed production facilities can be connected to the existing grid or serve a specific region on their own. The interconnection of distributed generation sources ensures that renewable energy sources can be used safely, especially to meet changing demands [23].

14.3.10 Smart distribution The competitive electricity market using the current technology and the different service requirements have led to different network operations (transmission/

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distribution system changes and tariff differences), especially in the DN. The main components that enable SG technologies are ICTs, control, detection and measurement, storage, automation, renewable production, and integration systems. The future’s DN is envisaged to be a complex structure consisting of interconnected distributed energy generation sources [26]. Smart distribution systems ensure the voltage stability, interconnected topology, reliability to consumers, and focus on advanced power distribution configuration in SG. Smart distribution has a selfhealing, stabilizing and optimizing structure. These systems are capable of predicting malfunctions depending on the weather and de-energizing history with automatic monitoring and analysis features. Energy management is important to increase the flexibility and reliability of the power grid for monitoring, controlling and optimizing distribution substations. The dynamic control and management system at all levels in the SG includes energy-efficient controllable equipment, distributed energy sources, advanced dynamic control architecture, and optimal operation of substations [27].

14.3.11 Smart metering Smart meters are embedded devices that measure consumption between the consumer and electricity providers by using a two-way communication infrastructure. It collects real-time payment data, power failure measurement, power quality, and consumption information. These devices allow the maintenance team to be directed to the right location without wasting time. Therefore, the more measuring and control devices placed at the endpoints, the easier the energy management. Fig. 14.4 shows some of the examples of commercial smart meters [28]. However, the most important point is that the data collected in such distributed networks should be reliable enough [29]. The Energy Independence and Security Act of 2007 (EISA) has been assigned to the National Institute of Standards and Technology (NIST), to coordinate the development of protocols and standards for information management to achieve SG framework [30]. One of these standards is advanced metering infrastructure (AMI) (including smart meters, collectors, transmission and distribution devices, and automated aggregation systems) provides real-time power consumption [31].

Figure 14.4 Single- and three-phase meters and communications module [28].

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Smart meters offer consumers advantages such as dynamic tariffs and real-time pricing. From smart meter monitors, feedback information such as the amount and cost of usage for home electricity can be learned in real time or retrospectively. Smart meters can be equipped with additional tools to detect unusual energy consumption, malfunction, and consumer leakage usage. Smart meters in buildings reduce the need for costly manual control, contributing positively to operating and maintenance costs. Smart meter technology contributes to energy efficiency and promotes sustainable development, providing a great social benefit. Globally, intelligent meters reduce unnecessary additional power generation demand. Smart metering is an important part of the transition to small-scale distributed energy systems and encourages customer engagement. It is an important step toward a complex and self-balancing SG system for the most demanding electrical uses. Fig. 14.5 gives a sample AMI network model [32]. At the macro-level, smart meters will have a significant impact on reducing carbon emissions as they provide good supply management. At the micro level, it will enable consumers to control their own consumption, thus reducing total energy demand and service costs. Studies on smart measurement are still in the beginning phase at the consumer level [33]. SG utilizing the advanced ICT infrastructure maximizes the energy efficiency of the entire system while ensuring optimal use of the distributed power generation system. As a result, the SG supports many power management devices to ensure efficient performance and is a seamless and flexible operational data communication network between different system components. Power system infrastructures

Figure 14.5 Smart grid/advanced metering infrastructure (AMI) [32].

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consist of all devices in the existing electricity networks and help decision support systems in data centers with intelligent meters and sensors distributed to the network to detect failures and measure critical performance metrics of the main power distribution system. Because the amount of data collected by smart meters is huge, and due to the importance of this data, the communication infrastructure needs to be scalable, providing high bandwidth capabilities and low latency [34]. The information gathered in the SGs helps planners and governments to decide the future expansion of the system. In addition, this information enables customers to regulate their energy use based on their personal economic conditions or to learn about their positive/ negative responses to government initiatives through forecasting tools. In order to meet changing economic and legal conditions, it is necessary to determine the extent to which electricity producers and distributors can meet the demand and coordinate with their customers. While conversion from traditional power grid to SG has many advantages, it is imperative to use forecasting tools to optimize the return on investment [35].

14.3.12 Integrated communication Control of all electrical systems is ensured through communication protocols and online systems. The integration of distributed production systems increases system efficiency and flexibility. This naturally improves reliability and efficiency, and provides a price advantage for customers [36]. A robust, secure distribution system should be established to integrate centralized and distributed electricity generation sources. Developed integrated system similarly can be used for different distribution systems like natural gas, water, waste water, and so on in the implementation of intelligent control systems. Although the requirements of these systems (sensors/ counters/switches) vary, they have something in common in terms of communication, data analysis and cyber security architectures. They can be made interoperable with the adaptation of data format and communication systems [36].

14.3.13 Review of state-of-the-art studies In the “smart-city” case studies, we can see that the following issues are examined as the key factors in new SGs [37]. G

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Resiliency, reliability, and security: Resilient to attacks and failures with rapid and even automatic restoration, and self-healing Integration generation and storage: Facility to integrate the many distributed energy sources (renewables) with “plug-and-play” as a supplement to the central stations Consumer engagement: Consumers are involved, well informed and have an active paper— DR and possibility to be “prosumers” Optimization and operations efficiency: Two-direction communication and flow; ability to reduce losses and use the full capacity of the system’s assets Market evolution: More mature, liberalization of the market lead to a growth of market and more options for the consumer

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The smart meter and AMI aggregate energy consumption at specific time intervals, informing the consumer of current consumption and price. Thus, consumers learn when and how much energy they consume. With existing monitors, they can manage their consumption and reach cost savings by accessing instant prices. Suppliers can read and bill meters in real time [37]. By 2020, the EU plans to replace at least 80% of electricity meters with smart meters. This change is expected to reduce household energy consumption by 9% [37]. Fig. 14.6 shows the adoption and rollout of smart meters until 2020. Smart metering is one of the new concepts to the consideration of a new technological application together with the IoT and embedded devices. Smart devices are built near the energy user and connect them to the central coordination center of the energy in use. Smart meters are the devices running with time or unit value to measure the resource consumption and specified by the utility provider. These devices can be used anywhere to analyze a specific consumption metric. There have been many different systems that have been developed and commercialized to automatically gather information since the use of distributed electricity networks [38]. Thus, with smart meters and future smart homes, homeowners’ participation in this system can create many additional possibilities. A typical smart meter network can have millions of metering endpoints reporting to a centralized end system. These networks can be deployed using different communication technologies such as wireless cellular, power-line communications, fiber-optical networks, and wireless mesh networks. In addition to the pricing information, smart meters can allow consumers to modify their consumption patterns

Figure 14.6 Overview of EU members’ targets for smart meter [37].

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about temporal fluctuations in consumption and time-of-day in synchronization with peak and off-peak demand-based pricing [39]. RFC 6550 specifies the IPv6 Routing Protocol for Low-Power and Lossy Networks, which provides a mechanism for multipoint-to-point traffic of devices in Low-Power and Lossy Networks toward a central control point and vice versa [40]. There are other popular routing protocols being deployed or are in consideration for smart utility networks such as LOAD (6LoWPAN Ad Hoc On-Demand Distance Vector Routing) [41], and Geographic routing [42] protocols. A significant part of the advanced measurement infrastructure uses wireless network architecture because of its low cost. The current drawbacks of wireless access, especially the distance from home to outside systems, and even in-house scenarios are tried to be corrected by algorithms in different network layers. However, the overall performance is dependent on the vital metrics like reliability and scalability to be applicable to smart utility networks [43]. The integration of renewable energy sources and energy storage systems necessitates the use of smart metering systems for the management and control of these resources [44]. The measurement side of the distribution system has become the main point of infrastructure investments. With automatic meter reading (AMR) customer records are kept error-free and regular, and consumption information can be tracked instantly and retrospectively [45]. However, AMR is limited to remote read and does not run additional applications. Nowadays, AMR, which is powered by intelligent sensors and control technologies equipped with advanced architecture, is called AMI and helps efficiently network control and management [46].

14.4

Water

14.4.1 Overview Water plays an important role in the protection of life and public health. Access to healthy water is a fundamental right for all people. Water is a public good and therefore water-related services need to be under the strict control of the public. Since there are many legal arrangements for water and waste water services, there are responsibilities given to administrations especially for different drinking water supply. The task of providing drinking water in metropolitan areas and building dams is given to metropolitan municipalities and state hydraulic works by law [47]. They provide end-to-end modern water management systems to manage the process from the source of water to the end-user in the city. There are also responsibilities of sewage services of water resources with used water and industrial waste to prevent contamination. The basic priority for water supplying organizations is to ensure clear and highquality water supply starting from the source to the end-users. Intelligent distribution of water can be implemented by the use of geographical database systems, determining losses and illegal use, waste water management, asset management, user assessment, and collection management systems utilization. For water services, from the point of digitization, recently coming up in every field, intelligent systems including data-based supervisory and control system

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(SCADA); geographical information systems (GIS) application; information, and communication technologies infrastructure; user management system application; and electronic document management system are in the focus of the water management systems in the cities [47]. Some IT companies providing services in the water sector offer smart water management solutions to water administrations and municipalities in order to use water which is the most important resource in the world in parallel with the population increase. End-to-end modern water management systems are offered to manage the process from the source of water to the end-user in the city. In this process, water distribution and network management based on geographic information systems, detection of losses and leaks, waste water management, asset management, subscriber accrual, and management of collection processes take place [48]. Fig. 14.7 shows a smart water network. Intelligent water distribution systems use sensors that measure water flow rate, pressure, conductivity, turbidity, and chlorine content. The sensors are mounted on the inner and outer surfaces of the pipes. These measurements enable field teams to learn about the condition of the pipes and water leaks [48]. In this way, it is possible to increase incomes of water administrations, decrease in operating costs, increase water quality, provide high standards of service to citizens, and increase satisfaction of subscribers and water administrations.

14.4.2 Infrastructure Drinking and potable water supply and distribution system supply drinking and potable water to users and includes one or more of the systems that include water intake structure, transmission line, treatment plant, pumping centers, storage, and

Figure 14.7 A smart water network [48].

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DN units. Water and sewage systems are managed by the municipalities or state water works. Business license is approved by the Ministry of Health, Labour and Welfare depending on the population served. They provide an effective water management system in order to prevent administrative and physical water losses in drinking and potable water supply and distribution systems [49]. They build the overall water system in accordance with the specifications and application projects. They provide the materials used in accordance with the standards, to create the main pressure zone and subzones in the system, and ensure the optimum operating conditions with effective pressure and flow management in the network. Fig. 14.8 shows the general water distribution system [50]. Water DN is used for the distribution of water from the transmission lines and carrier lines on the basis of neighborhood, street, and building. It also includes the branch lines that provide connection to the building and the segment up to the water meter of the subscriber. Water network is a DN consisting of pipes of different kinds and diameters such as polyvinyl chloride (PVC), high-density polyethylene (HDPE), and ductile font. On the water distribution infrastructure, there are production pumps that print water from production sources and promoted pumping stations that raise water to a higher level. In general, there are also pumps that suction and discharge from the line as well as promotion pumps that pump water from a tank. There are also water tanks for stocking, balancing purposes and distribution. Water distribution is made with these water tanks of variable capacities which are suitable for the feeding zone. With the compliance of the requirements of the act including facility standards, drinking water quality standards, etc. water utilities must supply water to their consumers at all times. Water utilities are also expected

Figure 14.8 Smart Water distribution system [50].

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to provide the consumers with information pertaining to the results of water quality inspections and related information as follows [49]: G

G

G

G

G

G

G

Plan/results of water quality inspections Implementation system of waterworks Cost of business/water charge Water supply equipment/facilities Sanitary management plan of water tank Results of extra water quality inspections Crisis management

14.4.3 Smart water grid Intelligent water systems, such as intelligent energy systems, use Internet-supported sensors to collect real-time data. This enables water facilities to be optimized by monitoring leaks or monitoring how water is distributed throughout the network, and allows people to make decisions based on more efficient information about water management. Sensor data are given a SCADA system that monitors and controls technical processes, stores the data and, if desired, transfers it to the online platform. Efficiency of infrastructure systems and to increase the scope, innovative, and local using conditions-compliant technologies manage water effectively is required. Smart water management is used to ensure water savings, reduction of infrastructural problems, and monitoring of water quality [51].

14.4.4 Smart meter Smart water devices are increasingly gaining popularity, allowing consumers to track their own water consumption, make decisions based on the data they see, and use water more sustainably as well as lower costs. In case of leakage, it informs consumers to solve the problem more quickly and prevent unnecessary waste of water. Smart water meters are similar to smart electricity and gas meters. Smart meter management covers the integration of the subscriber’s card and remote reading meter data into the central system and the integration of relevant solutions for the establishment of the necessary infrastructure. Smart meters transmit monthly or daily consumption totals to a central system via different communication technologies. Smart meters can be controlled from a central point and collect data intermittently. Operations such as interruption and reopening of the service can be done remotely. These devices measure the consumption at different time periods which can be adjusted later. For smart water meters, this time can be set from 1 hour to 1 day [52].

14.4.5 Management of water utility system Water utility system management is integral to enabling the system to achieve and maintain compliance with Safe Drinking Water Act (the federal law that protects public drinking water supplies in the United States) requirements. Official

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documents prepared by public institutions ensure that they can work with local authorities and that the whole system is legally audited with regard to the protection of public health through strategic planning [53]. In the light of these official documents that apply to almost all countries, the following examples can be given for some of the basic principles of water management: G

G

G

Pipes, tanks, and pumps that make up the system must have proper operating conditions The personnel working in all relevant levels of the system must have the appropriate competence Additional infrastructure needs and maintenance of the system should be planned

Smart water measurements allow real-time or near-real-time reading of water consumption. The use of IM technology is shaped by the support of water service providers (government water works and municipalities), consumers, social, economic, and technological actors. Intelligent metering is also a component of the intelligent urban water network and can be classified as AMR or AMI. Intelligent water usage systems use new technologies for the benefit of all stakeholders operating and using water and waste water systems, and provide a network management system for performance control of systems running to improve the effective distribution of water and waste water services, remote monitoring of material status, assessment of water availability, and real-time water consumption monitoring. Intelligent systems combining smart devices, services, and solutions enable an overall smart technology and provide a more efficient and sustainable management and delivery of urban water by joining with the consumers’ water consumption culture. For an effective water management system, it is important to have a water infrastructure that will meet consumer needs, to set effective process goals for a quality business, to establish rules and to perform management visually [54].

14.4.6 Inventory management Inventory management provides desired service levels and minimizes operating costs. Renewing and improving the water infrastructure of cities is a continuous activity. Inventory management is essential for planning maintenance and monitoring the economic life of the devices (pumps, motors, pipes, etc.). Many utilities use inventory management to monitor and achieve sustainable infrastructure. Inventory management provides managers and decision makers with critical information about the timing of investments. The main activities in inventory management are the inventory of critical devices, the evaluation of their performance, maintenance, and calculation of the financing required to change [55].

14.4.7 Subscriber management The Water Subscriber system allows suppliers to remotely read and bill consumers’ water consumption amounts. Some smart water meters can be prepaid via credit cards or smartphones. The counter automatically cuts off the water when the credit is finished. When the new payment is made, the meter automatically switches the

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water on again [56]. The system works in conjunction with online meter reading operations, providing real-time subscriber tracking capabilities to businesses by reference to accrual and collection transactions integrated with bank payments.

14.4.8 Geographical information system and infrastructure management Water management using GIS is beneficial for monitoring water resources. GIS also enables the geographic mapping of water sources, management of all assets that are used and within the physical responsibility area of an enterprise and the integration with other smart water management components.

14.4.9 SCADA-database based control surveillance system The most effective use of the supplied water is that it can be used with minimum water loss and leakage. SCADA systems provide the most effective management of data related to water and sewer infrastructure [47]. The components of SCADA can be categorized into three headings: G

G

G

Remote terminal unit: the device where all the measurements and inspections are needed in the field Central unit: the unit where information from the field is collected, monitored, evaluated, and all decisions related to process management are made Communication medium: the communication infrastructure between the field and the central unit. 3G modems, radios, and asymmetric digital subscriber line (ADSL) modems are in use.

SCADA and telemetry systems are key business tools in water industry. They provide remote monitoring and control of remote assets. SCADA provides the method to collect data from sewer pump stations, water reservoirs, and boreholes in the distributed water infrastructures and delivery to the end user. Central units are the management locations where SCADA monitors installed, and collected data are evaluated for efficient use of resources. Real-time data also allows for the current status and performance of the assets in the system [57,58].

14.4.10 Review of state-of-the-art studies In order to make smart cities a reality, we need to make the water smart. To take this first step toward smart water, it needs to be developed with the IoT technologies, which enable the updating of aged water infrastructures, some of which are more than a hundred years old, and communicate online with the system and other parts of the city. IoT solutions can be integrated into the water grid network to use real-time data/analysis more efficiently when managing its activities. ICT service providers help utility businesses manage the reliability of their network and improve the service they offer to their customers by taking advantage of cloud technology.

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Saving methods for existing water use aim to improve the system both to prevent leakages and to reduce unnecessary water use through economic incentives and training. Regional water supply programs should be prepared taking into account groundwater/surface water basins or external water resources. In addition, reduced water consumption will increase the reliability of the system.

14.5

Natural gas

14.5.1 Overview Natural gas is the largest source of fossil energy after oil. Natural gas can be difficult to find because it is often trapped in deep porous rocks underground. Natural gas can also be obtained from other sources such as shale gas. Natural gas, which has a wide range of usage from sites to hotels, factories to plants, can be configured to meet all energy needs from a single center. Nature-friendly, efficient, and safe natural gas services which offer a price advantage over the other alternative fuels, continue to reach not only big cities but also all settlements. Natural gas is the cleanest energy source compared with alternative hydrocarbon sources. Natural gas can be transported by road to any place where the pipeline goes. Natural gas can be produced far away from consumption centers. The most economical way of transporting this is pipelines. The powerful compressors at the starting point increase the pressure of the gas and allow it to move through the pipeline. The pressure in the pipelines is reduced due to the terrain structure and friction in the pipeline, and the pressure is brought to the desired level by additional compressor stations located between about every 50 100 miles. In some natural gas systems, large underground tanks filled in summer are used to meet increasing consumption in winter. The pressure of natural gas reaching the city is lowered before being sent to the users and odor is added for easy detection in case of leakage. Local gas companies use smaller diameter pipes to transport gas to consumers. The quantity used by the consumer is measured by a gas meter [59].

14.5.2 Infrastructure Industry uses a part of the natural gas mainly as a heat source to manufacture goods. Many of the items of synthetic rubber and manmade fibers like nylon could not be made without the chemicals derived from natural gas. Homes, businesses, and commercial sector consume natural gas for space and water heating. Overall demand of natural gas mainly depends on following sectors: G

G

G

G

Residential and commercial sector Industrial sector Electricity generation sector Transportation sector

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Demand for natural gas changes from season to season. The demand was demand was highest during the winter and lowest during the summer in the past. The reason for this cycle of natural gas was residential and commercial heating. The demand for natural gas was the highest in January and February, and the lowest in July and August. During the recent years natural gas consumption for the generation of electricity has the traditional demand cycle [60]. During the summer months, demand for electricity increases for space cooling. The increased electrical consumption increases the natural gas demand. The magnitude of the summer demand peak is expected to become more important in the feature.

14.5.3 Natural gas grid Natural gas extracted from the wells is pumped to a processing plant by field compressors. The processing plant removes impurities from the raw natural gas like “water, carbon dioxide, mercury or sulfur” which causes corrosion in pipelines and/or inert gases like “helium,” which reduce the energy value of the natural gas [61]. Processed natural gas transported by a main distribution pipeline system from production region to local distribution companies. To keep the gas pressure stable along the pipeline compressor stations are installed at every 80 100 km. Compressors are remotely monitored and controlled from a central control room. Pipeline is also equipped by remotely controlled shut-off valves for safety purposes [62]. Local distribution company draws the gas from the main pipeline through a “gate station.” Gate stations reduce the pressure from high transmission level pressure to low distribution level pressure, measure the amount of gas drawn from the main pipeline, and add an odorant so that a consumer can smell gas leakages. Local distribution company transports natural gas to the regional regulator stations by means of local main pipelines. The regulators are remotely controlled by a computer system and keep the gas pressure within desired range against the demand fluctuations. Natural gas is fed to smaller diameter service lines from the regulator for residential distribution. At the customer side the gas passes through another pressure regulator and a meter. Regulator drops the gas pressure to slightly higher than the air pressure, so the gas flowing through the burner is easily ignited and burns with a clean flame. In the residential area hand controlled and/or automatic shut-off valves are added against fire, earthquake and gas leakage accidents.

14.5.4 Management of natural gas system Gas management provides value-added support for production and customer support to reduce costs and optimize all devices used in the system. Although gas services in cities are provided by local and/or national agencies and/or companies, both service providers have their own management features. In a natural gas system, strategies should be developed to increase resource reliability, ensure price optimization, and minimize risks. Pipeline and supply bills are checked. Reports are

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prepared to meet customer needs without interruption. Planning is made to minimize costs [63].

14.5.5 Device maintenance Information such as maximum pressure, operating history, average pressure, and determination of design errors of the system should be continuously collected in order to deliver natural gas to consumers safely [64]. The user-side device is a boiler for natural gas. There are regular controls to ensure the efficient operation of the boilers and prolong the service life. Many companies working in the sector can avoid possible problems by performing burner cleaning and control, gas adjustment controls, heat exchanger cleaning, circuit elements control, filter cleaning, and safety equipment control. Experts point out that periodical maintenance prolongs the life of the device and emphasizes that the fuel consumption is reduced and energy saving is achieved through maintenance. Customers are warned from time to time that maintenance-free combi boilers are shortened, work inefficient and cause high invoices, and efforts are made to raise awareness.

14.5.6 Customer requirements and expectations Most of customers expect from the gas-distribution companies to provide fullservice, cost-effectiveness, and reliable natural gas supply and 24/7 communication. Pricing is still the most important factor for customer loyalty. In the recent years, developing digital technology shape customer expectations. Many natural gas utilities are not fast enough to take advantage of the many digital tools and techniques. The infrastructure ages by time, and cost pressures increase, utilities are forced to find new ways to reduce operational and maintenance spending without affecting the quality of their service delivery and customer satisfaction. Service providers that provide services to the people of the city for the distribution and operation of natural gas have to renew their corporate websites in accordance with the developing conditions. Companies that continually improve themselves by giving priority to the understanding of customer satisfaction, review the needs of consumers, and put their websites into service according to the conditions of the era. With the online transactions menu where the content is renewed and the membership system is introduced, consumers will be able to carry out their transactions directly on the website in a wide area.

14.5.7 Review of state-of-the-art studies Most recent scientific studies on natural gas relate to the technological level of both developed devices or other hardware components in the system. Clean, safe, reliable, and affordable energy is critical to nations’ economic and environmental well-being. Fortunately, many of the households and businesses can choose the type of energy that meets their specific needs. People shouldn’t have to choose between what’s good for the environment and what makes sense and luckily natural

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gas and renewable gas can do both, and easily meet the customer needs and protect the environment [65]. Combined heat and power (CHP) system coproduces from a single source of fuel, such as natural gas. A residential scale CHP is called as a micro-CHP that produces both electricity and heat. The electrical efficiency of the fuel cells is above 45%. This ratio is about 10% above the conventional electricity generation facilities. The efficiency in converting fuel to heat can approach 98%. By combining these fuel cell systems with renewable energy sources such as solar panels used in homes, carbon emissions can be significantly reduced. A connection to the grid is required to start up the system. A system that is not connected to the grid can use its own batteries for startup and energy storage [66]. Condensing boilers recover water vapor condensate at the gas outlet and increase efficiency. The condensing boilers also use a condensing heat exchanger, thus recovering the waste heat. This system is depicted in Fig. 14.9. Flue gas temperatures in condensing boilers are much lower than noncondensing boilers. Because the heat in the burnt gas is removed and the efficiency is increased [67].

14.6

Summary and business models for utility industry

The way to become a brand city is to operate and maintain an information system that uses digital technologies in all its services and can provide enough real data to its existing intelligent systems in order to solve all kinds of problems. In addition to technological advances in energy, new concepts such as distributed generation, SG infrastructures used in all utility services, energy storage, demand management, and electric vehicles have been included in the current opportunities and future projections of countries and governments. While anywhere anytime mobile computing is becoming true with the technological improvements and dense Internet usage, the choice of the management mechanisms for the smart utilities within the city should have a large impact on social, economic, business, and political aspects. When the living spaces constructed with the right planning and healthy urban modeling are combined with a strong energy infrastructure, the functioning of a modern city life can be ensured. We must remember that for a livable world and country, we have no choice but to save energy for a secure future. When the living spaces constructed with the right planning and healthy urban modeling are combined with a strong energy infrastructure, the functioning of a modern city life can be ensured. There are four main components in water management such as quality, quantity, continuity, and connectivity. ICT is naturally an enabler for smart water management used to optimize, monitor, and control the complete infrastructure. The technologies used today must meet business requirements. In drinking water supply systems, it is necessary to design a business model that can meet the problems such as water quantity, quality, and continuous service. Intelligent measurement system must be present as the basic technology in smart water management.

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Figure 14.9 Condensing boiler [67].

SCADA, GIS, have other new generation subscriber management applications, such as existing water resources management, healthy drinking, and domestic water supply services offered to citizens importance in terms of providing improvement bears. The more effective and efficient use of the resources in our world, which is the common usage area of all human beings and living things, should be the main word for smart cities and efficient utility services usage. The problems in areas such as infrastructure, environment, and energy in cities should be handled in integrity with urban transformation projects. In this context, housing, environment, energy and transportation infrastructures of cities should be handled within a specific plan and sustainable. In particular, the relationship between the transport infrastructure and the environment and energy needs to be assessed. Sample projects should be taken together with renewable energy and urban planning without disturbing the urban esthetics of cities. All water suppliers have to establish policies for production capacity, protection of watersheds, water saving, adequate financing for infrastructure installation, and maintenance with technological advancements. Mobile technologies, starting from smart meters and enabling consumers to control their own systems remotely, are becoming more and more important, and additionally the positioning systems in devices, environmental sensor updates create new methods of use [68].

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Recently, the adoption of the DERs concept, particularly in the area of electrical energy, has resulted in a more dynamic, decentralized, and energy efficient electricity system. Although this system has inherent benefits for shareholders and society, it is not surprising that the traditional benefit also gains importance as a business model. When applying different business models, the potential benefits of each need to be considered in comparison. While some models are evaluated at the traditional cost value, some may emphasize the integration of renewable energy sources into the grid environment while others are based on performance. There are also models that make customers stand out, allowing them to choose the energy source that best suits their needs [69]. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix K.

14.7

Chapter review questions/exercises

14.7.1 True/false 1. True or false? The biggest danger awaiting smart utilities is the depletion of limited resources or the inability to meet the current demand. 2. True or false? Plans for a national energy policy should be clear and identifiable outcome providing reliable, affordable, and environmentally sound energy. 3. True or false? Smart meters are the devices running with time or unit value to measure the resource consumption and specified by the utility provider. 4. True or false? The VU (virtual utility) can be defined as a new model of energy infrastructure integrating a single kind of distributed generation utilities in an energy (electricity and heat) generation network controlled by a central EMS. 5. True or false? SGs will not allow remote and instant monitoring and control of energy consumption.

14.7.2 Multiple choice 1. Which of the following strategies come to the fore for the cities to use energy effectively and efficiently? a. Environmentally sensitive structuring b. Use of energy technologies c. Energy efficiency awareness d. District heating e. All of the above 2. _______________can allow consumers to modify their consumption patterns about temporal fluctuations in consumption and time of day in synchronization with peak and offpeak demand-based pricing. a. Traditional meters b. Government c. Smart meters d. Local authorities e. All of the above

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3. Which system enables the geographic mapping, management of all assets that are used and within the physical responsibility area of an enterprise? a. Integrated communication system b. Demand management system c. Unique identity management system d. GIS e. Executive management system 4. Which of the following is a component of a SCADA system? a. RTU b. Central unit c. Communication system d. Field devices e. All of the above 5. Natural gas is considered a ________________like petroleum because natural gas was formed from the remains of tiny sea animals and plants that died 300 400 million years ago. a. Renewable energy source b. Liquid fuel c. Expensive fuel d. Fossil fuel e. All of the above

14.7.3 Exercise 14.7.3.1 Problem Create a number of exercises to evaluate and refine the engineering methodology of smart utility technologies.

14.7.4 Hands-on projects 14.7.4.1 Project Do research: Build a working smart power grid.

14.7.5 Case projects 14.7.5.1 Problem Develop strategies for a more equitable, sustainable, affordable, resilient, and innovative smart utility services.

14.7.6 Optional team case project 14.7.6.1 Problem Develop a new model for smart utility design, planning, and construction.

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Smart cities and infrastructure standardization requirements

15

Neena Pahuja ERNET India, Ministry of Electronics and Information Technology, New Delhi, India

15.1

Introduction

A smart city uses “technology, people, and processes” to improve outcomes across every aspect of city operation and enhance the services it offers to its residents. Technology “powers” the smart city, but it is the data that leads to insights and new services. To create these relevant services, cities must be able to innovate the right solutions, with the defined “processes” consumed by the “people” of city, which are scalable and replicable. To get the right outcomes that matter consistently and at scale, civic leaders must establish sensible technology and data policies. Finally, savvy cities use public private partnerships (PPPs) to maximize their resources, go faster, and scale effectively. A sustainable and well-functioning smart city is a tight orchestration of people, processes, policies, and technologies working together across the entire smartcity ecosystem. These architects unify teams across municipal departments. They create “tech bridges” to connect public and private organizations within the ecosystem, which builds consensus to cocreate the new smarter city. While connectivity is mission critical in smart city’s, today’s smart-city ecosystem architects are faced with several challenges of unequal access to basic connectivity, inadequacy of existing services, and a confusing array of emerging low power wide area network (LPWAN) options. In the smart city, connectivity is not an option but an essential basic requirement and vital to get the benefits of standardization. Smart-city architects must lead with new processes, policies, and PPPs. They must develop new innovative investment strategies, and create new connectivity ecosystems with city owned, service provider owned, and community owned infrastructure. Data is the lifeblood of the smart city. However, it is essential to be able to first capture the “clean” usable data, followed by extraction of knowledge from this data. Open data, generated by municipal organizations, is only one source of data. When supplemented with data created by businesses and private citizens, it yields richer insights and better outcomes. Smart-city ecosystem architects utilize the full extent of the ecosystem to create “city data.” They plan and build data marketplaces, robust data sharing and privacy policies, data analytics skills, and monetization models that facilitate the sourcing and usage of “city data.” In some smart cities, the citizens “willingly” provide their data, so that it can be used to provide better services in the city. Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00015-2 © 2021 Elsevier Inc. All rights reserved.

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Figure 15.1 Internet of Things framework.

This chapter brings out different needs of smart-city applications, and hence associated data and possible infra to collect the required data. The standardization of infrastructure starts from needs of city, which may vary from one city to the other, giving rise to need of applications and open data architecture to get benefits of replicability. Requirement of connectivity and secure data hub remain a constant in all the smart cities. This chapter also assumes a five-step Internet of Things (IoT) framework to yield the smartness described in Fig. 15.1 as described in Ref. [1], where IoT is defined as a seamless connected network system of embedded objects/ devices, with identifiers, in which communication without any human intervention is possible using standard and interoperable communication protocols.

15.2

Data monetization: open data to increase community engagement

The city as a platform and the data economy have the objective to guide cities on the process of data monetization using a platform approach. This chapter brings out a set of capabilities and their architecture to make such data monetization viable. Various data originators of smart city generate Peta Bytes of data on regular bases. It is also important to also handle and mange this large data while providing the benefits to the city dwellers. There are various data-monetization models suggested by various experts for city. The applicable models in this case may be: G

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Advertising based—Provide content or services for free in exchange for viewing advertisements, often customized to the personal behaviors, profiles, and locations. Revenue streams are generated by advertisers and not by users based on the views. Subscription (all you can eat)—Users pay a fixed amount per month in return for the right to consume digital content and services without limitation. Pay-per-use—Users consume digital content or services and pay a fee per consumed item. In a smart-city case, these could be, for example, a tourist guide in a language of choice. Many payment-collection services also get service fee per transaction or as a percentage of revenue collected.

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Data monetization—Digital businesses collect data on consumer behavior and preferences and on product usage. This data has value and can be monetized by selling raw data or derived insights to other players in the market. The following and more could be possible consumers of city data: Application aggregators, of various applications described in upcoming sections Insurance companies R and D organizations Municipality, police, and government itself Disaster-management teams City dwellers themselves G

Cities are also keen to organize and deliver their data as open data. However in a city, there are a great many private and public services; the technology and processes must be created for generating the required data in real time. With IoT becoming part of the citizen’s life, citizens themselves are generating lots of data, which can be used for smarter city operations. It is not enough to share static data. The city needs to share all the data and take this opportunity to provide new business models and innovations. This chapter also attempts in defining a conceptual platform architecture with the business logic to act as a “data hub” to be provided “by and for” a city. Technical report [2] details out a high-level architecture and usage of M2M and information and communication technologies for smart cities. Additionally, this “city” architecture needs to focus on the development of a digital ecosystem in and around the city’s digital infrastructure, creating new products/ services, businesses, and government revenue opportunities, which intern also provide the required services to the person’s living in the city. A smart city collects and uses open data to drive its decision-making, and creates networks of partners among governments, businesses, nonprofit groups, community groups, universities, and hospitals, to expand and improve its ability to serve its residents. Some more advanced smart cities have begun to move beyond infrastructure, to using big data. A true smart city example, leverages new found data to tap the wisdom of its residents and visitors and also the inferred data to help a better city management process. The digital infrastructure of a smart city allows real-time access to data that can unleash tremendous value, driving smarter decision-making by government, planners, community groups, and individual residents.

15.3

Smart-city technology architecture

Most smart cities have a four-layer technology architecture to capture and process data as shown in Fig. 15.2: 1. 2. 3. 4.

Application layer Application and data support layer and the associated processes Communication layer Data capture layer using sensors, CCTVs, citizens, news, social media and organizations, and processes

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Figure 15.2 Smart-city technology architecture.

The sensor layer may consist of actual sensors placed by the city authorities to capture data or even the mobile information of residents, or other sensors put on say E-buses/E-rickshaws/cycle, fitbits, etc. These sensors may also capture air quality or the rainfall or a water or a gas leakage that is happening anywhere in the city. The CCTV cameras may be put across the city to capture traffic, incidents, or even state of streets or even garbage collection in the city. The intelligent processing in the CCTV cameras can bring out alerts of the exception condition, for any immediate or safety action to be taken. Some crowded places or malls and banks have started installing sensors that can also sense gun shots. Data from such critical sensors can help in providing immediate relief in affected areas. M2M architecture report [3,4] also detail out this level as planned for India. The network or the communication layer connects the data collected by various agencies and others to a “cloud” at a data center, which helps in the decisionmaking process on the data. The data may be also be collected by satellite images or by the “low power” network. In some of the smart-grid applications implemented across in the society clusters of smart city, power usage peaks, and even power breakdowns can be proactively handled by these networks. Application and data support layer along with the processes can be country/city specific and can define rules of usage and storage of data. Based on the associated privacy and confidentiality tag with the data, the applications are allowed access to this data. The smart city standardization outcome framework is captured in Fig. 15.3. The applications can be specifically created for citizens, urban management, or supporting the government services. The smart-city infra standardization leads to innovations that help in improving services. The following sections will go into the details of these applications together with the need for security and privacy of data and with ways to monetize the city data.

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Figure 15.3 Smart-city standardization outcome.

15.4

Smart-city application architecture

Many applications can be created for community based on the need and availability of data. This section brings out a generic set of possible applications together with infrastructure required to capture the data for the applications, which may be required in a smart city.

15.4.1 Smart tourism Open data architecture is very effectively used by tourism groups and application providers, in order to give better services to tourist’s traveling to the city. To promote tourism in the city, smart applications with augmented reality and virtual reality (AR/VR) can also be created. These applications help persons to plan their trips better and have a view of the places of their interest, as they visit the city. These applications also provide the safety instructions to the tourists, coupled with eTicket solutions and details on E-bus and E-rickshaws for any requirements of last mile connectivity. Some of these applications also provide multiple language interface for helping persons traveling from different parts of the world. These applications also help travelers with any kind of physical disability to also request for facilities in advance. They may also inform the traveler on dos and don’ts for the place together with the travel advisory for children and elders.

15.4.2 Hygiene/cleanliness drive As part of smart city drive’s, sensors and CCTV cameras are installed at various city locations. The sensors can capture the air quality, water quality, any gas leakage, water logging, state of smart bins or at places, even breeding of insets or mosquitos. This sensed information together with the image capture from CCTVs can help in a lot of intelligent decision-making process. Other than safety and security

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of areas covered, these cameras can also bring-in the position of traffic, water logging, and any other information on the status of hygiene or cleanliness required.

15.4.3 Traffic and travel management The traffic can be monitoring using the intelligence built in the cameras and speed of moving traffic and traffic violations can be controlled with the help of the data. Special traffic advisory drives can be undertaken based on the information on areas getting maximum traffic violations. In addition, based on the need, the speed limits can be modified for the location and the time of the day. Even “green corridors” can be created for an ambulance or in interest of national security, based on any specific emergency requirement. In addition, this information can also be shared in real time with citizens for them to plan their travel. Traffic advisories may also be issued based on the location of schools and the time of the day. In ensure the safety of school children, parents can be given access to location and status of the school bus. In some cities, schools have already starting using city traffic data with of algorithm for managing the school buses, and in one of the published cases, the school managed to save over 5 M$ for the school by doing so. Smart cities have started using E-buses, E-rickshaws, shared bicycles, and travel cards for ease of their travel and a large number of innovative applications for traffic management and simplifying travel can be created.

15.4.4 E-buses The smart city plans also include running of electric or low-emission buses to manage the transport requirements of the city. The buses are further categorized into buses, which are elders or disabled friendly. The timing of such buses is intimated in advance for citizens to plan their travel in the city.

15.4.5 E-rickshaw To support the common connecting points such as metros and also to provide assistance to the disabled and elder persons, smart cities also plan the E-rickshaw for the last mile connectivity. They are also creating open information across it, which can be used by the public transport groups to provide the services. These are green and sustainable transports with no emission.

15.4.6 Public bicycle sharing With focus on clean environment and health in smart city, the bicycle sharing has become a very common application in the smart cities. This typically includes a public bicycle sharing system, bicycle parking facilities and strategy for awareness campaigns. Data of these bicycle usage coupled with location and time of the day information helps in better planning of these bicycle. Some of the private groups have created these bicycles with sensors. Therefore the user of the bicycle is also

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able to get some of his health information at the end of usage of bicycle. Even some insurance companies are tying up with these bicycle companies and offer a better health insurance package or inventive to these users of bicycles.

15.4.7 Passenger information system through mobile application and travel cards Some smart cities create a mobile application for booking of travel. This data can be effectively used for planning the transport assets in the city based on the realtime demand. Most cities have started issuing a single travel card to the persons for all their city needs. The anonymized data from these cards can be very effectively used for planning all the travel facilities in the city, which can be effectively monetized. It can be used to plan even the last mile connectivity using E-rickshaws or bicycles or number of bicycles at a particular location in the city at specific times of the day. It can also be used to plan for elder/disabled friendly buses/transport for specific times of day.

15.4.8 Intelligent transport management system The intelligent transport management system of city combines data of school locations, times, critical locations like hospitals, movement of school buses, ambulance, and then plans the traffic lights to support the movement across the city. The system also stores the data of breakdowns, if any to re-plan the traffic. Data on availability of self-driving cars available for car sharing can also be effectively used in the city.

15.4.9 Management of E-charging stations With need of electric vehicles (EVs) increasing to curb the air pollution, most countries are coming up with norms for EVs. With that also comes the need to be able to plan the charging stations on the roads, in the office complexes, in public areas, and also in the supermarkets. Data of usage and availably of these charging stations may be made available to the user.

15.4.10 Speed management, based on the time of the day Most smart cities define the speed limit for vehicles for the roads based on its proximity to school, hospitals or residential areas or any public places. However, these speed limits can also be modified based on the time of the day or any emergency. The data can be made available and used to help the city dwellers plan their city drives.

15.4.11 Management of traffic lights Intelligent programs may be created to manage the traffic lights based on the footfall and also the time of the day. This data again may be used by the city dwellers

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to plan their ride. This data may also be integrated to applications like maps, to guide on directions and travel paths to be followed.

15.4.12 Building management Smart buildings use large numbers of sensors to create fine-grained and real-time data about both the occupancy and the conditions in the building (e.g., temperature, humidity, and light). The data is used to optimize building systems like cooling, ventilation, and lighting with the objective to operate leaner when less people are using the building. On days when fewer people are expected, the system may even close entire sections, cutting costs for heating, cooling, lighting, and cleaning. Smart buildings can also be fitted with sensors to ensure just-in-time refilling of facilities like coffee machines or say towel dispensers in bathrooms. Smart buildings use sensors in these machines that are used to also detect the optimal time at which a refill should take place.

15.4.12.1 Usage-based cleaning Smart buildings use fine-grained sensor networks to detect the activity level during the day. This data can be used to instruct people and robots responsible for cleaning to focus on the areas that have been used most heavily.

15.4.12.2 Automated garage entry At arrival of the garage of a smart building, a camera detects the license plate of the car, matches it with the personnel records and the list of registered visitors, and raises the gate. For visitors, LED lights point out the route to the parking place that has been reserved for that visitor.

15.4.12.3 Renewable energy and smarter energy utilization Smart buildings use renewable energy like solar panels and thermal energy storage to decrease the net energy usage to a minimum, and in some cases, even to the levels where the building creates more energy than it consumes. Smart buildings are also capable of adjusting their power consumption to the real-time scarcity of electricity. If loads are high, the energy grid can send a request to smart buildings to reduce their energy consumption temporarily in order to lower peak load of the grid-as-a-whole. By doing this, the smart building ensures the lowest energy costs possible since energy prices are highest at peak times.

15.4.12.4 Water conservation/harvesting Water is an important natural resource and is the very basis of our life. Most smart buildings have started using techniques of water harvesting. Sensors as part of process can check on amounts and quality of water harvested for it to be reused effectively.

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15.4.13 Disease management Based on data of previous years and current information on location, persons with specific disease/viral, corrective action for controlling the disease can be taken. For example, if there are more malaria or dengue viral cases in a particular area, the citizens can be educated together with the spray of medicines to control the breading of mosquitos. Any area, which has a lot of cases of cancer, checks on any kind of radiations or food habits of inhabitants may be done to reduce the spread of disease. Again, different kind of sensors can be used to collect data, which can be used by the application developers.

15.4.14 Road and city cleanliness Most smart cities have a very high focus on cleanliness and road safety management. The cleanliness drive covers the public places including roads, drains, and also the housing areas. The roads are checked for closed drains, or open manholes together with quality of roads. Data may be collected using CCTV and/or sensors and analyzed to check the state of roads. Applications may also be developed to have citizens upload status of roads, which can be immediately acted upon.

15.4.15 Special care for elders Smart cities can create special cells to provide the desired extra care to elders without becoming intrusive in their day-to-day affairs (see checklist: “An agenda for action for special care for elders best practices”). An agenda for action for special care for elders best practices Eldercare requirement can be categorized into the following key activities (check all tasks completed): _____ 1. Care for people with walking disabilities _____ 2. Care for elders with disease like dementia to ensure that they are not lost on the roads _____ 3. Safety from thefts _____ 4. Facilities such as wheelchair, assistance for shopping _____ 5. Protection from falls together with urgent medical care, as the need arises _____ 6. Facility for homecare _____ 7. Special help for crossing the roads: Such applications can be designed so that such requests from senior citizens are sent to anyone closeby, including the cops on duty, who can come to support. This may require smart cities to create and store information of elders. In addition, based on the acceptable norms of privacy, smart watch/smart sensors/CCTV

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cameras and mobile applications can be provided for the care. The traffic application can also provide information on timings for easy accessibility of buses and other modes of transports for elders.

15.4.16 Care for physically disabled Starting from arrangements for physically disabled in smart transport, shopping areas, hospitals, and other city area, smart cities also need to have special areas/ help provided for road crossings and even jobs to make a difference in life’s of physically disabled persons and make them independent. Smart cities also have special care schools for such children.

15.4.17 Usage of data for safety In a connected city, the new age IoT devices can help in tracing a person, assets, detect falls, and together with the CCTV footage can predict most emergency situations. However, it is important to get acceptance from individuals who may want his data to be scanned, based on the country’s data privacy requirement. These features can be very effectively used by tourists, elders, and children, incase required. Some cities make it mandatory for children, elders, and persons with some specific type of disabilities to use this facility for their safety.

15.4.18 Fire safety With more and more cities with high-rise building, the smart cities must gear-up with new technologies to support them from fire. The new age equipment must be used for reducing loses because of fire and also help saving of lives. Information on fire cases with support of fire equipment’s, including drones and other suitable for high-rise buildings together with medical assistance, needs to be made available. City residents also need to be provided regular training on fire safety procedures and usage of in-house fire-safety equipment.

15.4.19 Smart contracts Globally, smart cities have started using blockchain for property and GIS location database. With blockchain providing authentic details across all the entities of the city, this also helps in ensuring the payment of city and municipal taxes. This technology also can be further extended to check the audits of fire safety carried out for various properties, to ensure the required level of safety.

15.4.20 Smart grid Smart grid is defined as electricity supply network that uses digital communications technology to detect and react to local changes in usage. Although data on “nousage” can be used in a wrong way also (no on in the house), data on usage can

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help in setting-up charges for the usage at various times of the day. In addition, it brings out the need for reusable sources of energy [5]. The grid can also provide proactive information on any power failure or any power leakage.

15.4.21 Smart water With water becoming a scarce resource, most smart cities now have a focused group working on smart water. These groups work on monitoring water usage, water treatment, and even rainwater harvesting. Quality of water is checked at public places and even in the residential areas and also the schools. In areas that are close to the Sea, but have a scarcity of drinking water, desalination plants are setup to ensure the availability of water. This data on water availability can be effectively used for the citizens. Wastewater treatment and rainwater harvesting has become part of most formal action plans of smart cities. Most cities have created bolt-on plants that can convert the waste into reusables such as biogas, electricity, and fertilizers. Some of group housing societies also have started planning it. Data on availability of harvested water can be effectively used by near-by housing locations or even the city authorities to for ensuring green corridor areas.

15.4.22 Smart homes G

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Smart homes may be connected with electronic devices such as smartphones, tablets, and laptops. Lights, heating, the television, the coffee machine, and other everyday appliances can be operated with an electronic device: Appliance control: Appliances are equipped with sensors to monitor the state of the appliance. They notify, if any appliance needs maintenance, or a refill. Security: Home monitoring and security appliances can be viewed and controlled from anywhere in the world by using the smartphone or tablet. Staring from entry control at the driveway to accessing in-home security footage, a range of security systems/processes can be used. Match energy use to occupancy: Smart homes use sensors to record real-time data about both the occupancy and the conditions in the home (e.g., temperature, humidity, and light). The data is used to optimize “home automation” systems like cooling, ventilation, and lighting with the objective to reduce costs. Landscape control: Landscape system measures and take cares of the optimal environment for plants and pets. The system waters the plants and/or gives food to pets at the optimal time and in the correct portions. Healthcare monitoring: Wireless sensing technology embedded in the walls can monitor breathing and heart rate in real time. This could benefit any person living in the house, and also observe elderly people or babies.

15.4.23 Smart working spaces The new age smart cities provide smart working spaces for small organizations and start-ups at nominal rates. The applications catering to this need allow for

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conference room bookings, working space for meetings or for any kind of investor meets. These spaces, together with smart sitting space also provide high-speed secure connectivity options together with any video conference facilities or projectors, as the need may be. Some of such applications also provide information on the relevant events and training or conference options based on their needs.

15.4.24 Smart waiting areas and smart advertisements Smart cities have started using the bus stands/rickshaw stands/railway stations/common waiting areas for smart advertisements and have started monetizing on the cost of location. Based on the travel or purchase behavior available for waiting passengers via their travel or other cards, these advertisements can also be customized.

15.4.25 Smart urban forests To improve sustainability and with focus on ecosystem creation, some of the smart cities have also planned smart urban forests. The information and visits to these urban forests can be monetized by the supporting groups, where they can additionally use the land for water harvesting, and also creating green houses to produce the rare and organic food.

15.4.26 Research, education, skilling, and reskilling institutes Education, training and reskilling for jobs is one of the major objectives of the smart cities. Open data on admission, places to stay for student, and course schedules with costs and related help can be made available as open data, which can be useful for students. This may also include vocational trainings and vocational jobs for students who may want to fund their own education.

15.4.27 Medical institutes and hospitals The data on medical institutes, their specializations together with hospitals needs to be available in application for any city emergency. Some cities are also coming up with health kiosk or health ATMs for self-checks for the locals. These are installed at shopping malls or even in the housing societies as part of their smart house project.

15.4.28 Start-up ecosystem and investor forums Start-ups ecosystem with investor forums has become part of every smart city. Open data about start-ups available as part of application can help in bringing-in investors, which can further help in city growth.

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Smart energy and light

Smart lighting with connected solar or renewable power can help in providing the required safety with the desired levels of conservation of energy. Some start-ups have created smart poles, which provide light, connectivity, and also cameras to capture any incidents around that place. Based on the need and the time-of-the-day, the lights also can be adjusted. There is need for applications, which are able to remotely control streetlights and also handle remote maintenance of these lights and poles. Energy data from both residential and commercial buildings in smart cities is collected and analyzed. Smart grids are part of the development of a smart city, and smart streetlights are an easy entry point for many cities, since LED lights save money and pay for themselves within a few years. Cities also plan sources of smart renewable energy to be self-sufficient in some areas. Overall energy usage is also part of a smart city, which begins with the installation of smart meters at their homes. However with the rise of home solar power systems and EVs, hardware and software technology will allow for the potential of better grid management, optimization of power production through different sources, and distributed energy production. Furthermore, buildings that monitor their energy usage actively and report this data to utilities can reduce their costs. This will ultimately lead to lower pollution and much better efficiency as cities become more urbanized. There are also smart grids and smart meters, which some of the cities have already started experimenting with. Smart-grid solutions play an important role in the development of smart cities. From prepaid energy applications to advanced metering infrastructure, there are several solutions to enhance energy services. With a smart grid, there can be improved outage detection, speed of data capture, continuing and disaster recovery, field service operations, and overall grid modernization techniques. Additionally, there can be analytical products rolled out which can bring out energy leakages, if any. Or, come-up with better charging models—based on need and time of day. To ensure the required security, these smart meters are created with embedded security so that a hacker cannot change its data.

15.6

Gearing-up for smart health in cities

The WHO defines a “smart healthy city” as one that is continually creating and improving the physical and social environments and expanding the community resources which enable people to mutually support each other in performing all the functions of life and in developing to their maximum potential. Proposed connected healthcare environment of smart cities not only has the territory and super specialty hospitals, it may also have the following: G

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Self-help health ATMs/kiosks covering basic self-tests Basic healthcare at retail centers (malls, like Wallmart/Wallgreen in the United States) Paramedic homecare service Emergency care and diagnostic centers in parts of city, which may be connected to hospitals Pharma outlets together with small pharma outlets with lifesaving drugs at petrol pumps Promotion of generic drugs Connected blood banks Stem cell and fertility centers with facility of in vitro fertilization and egg freezing Rehabilitation centers Old age center/homes Citizen health and awareness training centers SOS channel for medical help

It is also desired to have all of the preceding care providers go via a medical quality certification. Additionally, a standardized coding system for processes/ procedures should be used in all hospitals, so that patient data can be collated into an analyzable form.

15.6.1 Supported technology environment for smart healthcare The following standard systems and processes are proposed for handling the healthcare environment for the smart city (see sidebar: “Proposed Standard Systems and Processes for Smart Healthcare”). In other words, the proposed connected healthcare environment of smart cities is supported smart technology. Proposed standard systems and processes for smart healthcare The following proposed standard systems and processes could also be extended to the national level: 1. Central unique identification based eCard for every citizen of the smart city, which can store his personal health data. The diagnostic labs in city should have facility to upload the data to central patient database, which is secure. India has a concept of citizen digital locker, which can be used here. 2. Database of all health resources, such as doctors, emergency care, paramedics, blood banks, medicines, lifesaving drugs, diagnostics facilities, etc. and their availability. 3. Connectivity/Wi-Fi in hospitals/medical centers: a. So that patient can be reached for appointment, medicine, etc. b. While in the hospital, doctors can get the patient diagnostic data on his/her mobile phone for any emergency or review. 4. Technology-enabled medical market place enabling virtual collaboration between patients, insurance and care providers, and pharma outlets. 5. Healthcare cloud together with integration with mobile health monitoring: a. Mobile and wearable monitoring devices that capture physiological metrics, such as blood pressure, glucose level, pulse, blood oxygen level, and weight,

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and then transmit or stage the patient data for analysis, review, and intervention. b. Products such as cardio monitors, which are able to proactively sense the variations. c. Remote patient monitoring while the patient is in the ambulance. d. Exercise equipment, medical and fitness sensors, smart pharmaceutical containers, wearable healthcare sensors for health monitoring. Video visits: A video visit is the use of videoconferencing technology for remote consultations between clinicians and patients. Video visits can be used in conjunction with devices such as digital stethoscopes, digital cameras, and connected devices that enable the remotely located physician access and control. Most video visits are scheduled in advance by coordinators. These may be used in case of: a. Rehabilitation and mental health patients. b. For triage purposes including pre- and postsurgical evaluations to determine whether a face-to-face visit is needed. c. Dermatology and psychiatry. d. For follow-up care in their homes. e. Second option from a specialist at an emergency center. f. Video visits in offices or retail centers: Offices can create a clinic in office with a paramedic and video visits by doctors. Home healthcare and cloud hospitals: a. Homecare facility for diagnosis. b. Homecare facility for chronic old patients for regular procedures such as dialysis, which require them to currently visit hospital. c. Support for pre- and postoperative care together special care of physically and mentally challenged patients. d. Connecting the pharmacy and other healthcare resources to the patients. Special care and services: a. Technology-enabled safety bands to enable safety of dementia patients. b. Fall detection for old persons at home. c. Vaccination reminders. d. SMS on various diseases. Preventive checks for patient care: As the patient record builds by the standard processes, the basic preventive checks and guidelines for his wellness can be followed. Community health: a. Using the environment sensing data to appropriately identify alarm on the new diseases and symptoms. b. Knowledge sharing and education on genetic health and outcomes. c. Based on knowledge of viral and dengue outbreak facility, preventive action to ensure it is not spread further. d. With the data coming out to cloud from inhalers of asthma patients, quality of air is checked, and preventive action, if required is taken. e. Low-level public transport (with connectors to road) to enable persons on wheelchair to manage on their own and be independent.

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(cont’d) f. Early-warning sensing systems for infectious diseases—next generation smartphone test and tracking systems for serious infections including new strains of influenza and HIV. g. Smart garbage collection, cleaner sewerage, and clean drinking water, to ensure clean community environment. h. Defined processes to manage medical waste of different types. i. Community training centers on health and support for managing a chronic health condition using processes and mobile applications. 11. Home health monitoring: Home health monitoring is the use of technology and telecommunications to monitor the health of patients at home. Patients are provided monitoring devices that capture states, such as fetal heart of baby, blood pressure, glucose level, pulse, blood oxygen level, fluid discharge, and weight, and then transmit or stage the data for clinical review. Other devices are used for communications and messaging, gathering information from patients on their symptoms, cognitive state and behavior, and sending them information and advice. England, Italy, Germany, Spain, and Australia are already providing mainstream home health monitoring services to their populations.

15.6.2 Expected benefits of these applications in smart city Most smart cities are prioritizing their actions on healthcare as part of their smartcity implementations. Aforementioned reusable applications across cities can provide the following benefits: G

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Reduce hospital admissions, readmissions, and bed days Reduce the environmental impact and cost due to patient and clinician travel Reduce emergency room visits and inpatient admission delay Responsible community living Knowledge increase of preventive control for diseases

15.7

City services’ architecture and assets management

Smart city data can be used to provide various services to the city dwellers. Applications and service centers can be created around these services, which can also help in creating jobs and new forms of revenues.

15.7.1 Asset management and data aggregation services The open data on “city assets” from sensors and even organizations can be very effectively analyzed or aggregated. This is used for giving better services to the persons living and visiting the city.

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15.7.2 Tourist spots and hotel management Information on tourist locations, guides, tickets, timings, images, and also the waiting time or the crowd status of the tourist spots can help the visiting tourists. These applications can also be coupled be advertisements of local products and souvenirs available, together with the places where they can be purchased. Some application developers have already started creating tools for language translation to help tourists from various global locations in addition to videos and AR and VR products to enable tourist to plan their trips better. Sensors and cameras can also be used to monitor status of the old tourists’ buildings to ensure timely preventive maintenance. Applications can also guide the tourist of safety process and emergency care in case of any mishap. In some cities, based on the privacy settings of the visitors, they can also be traced for their safety. These applications are very useful in remote area visits and jungle safaris. Even robots may be used to guide the tourists in some locations, which can be controlled remotely. Availability of hotels/homestay with facilities is another open data that can be used by local and hotel aggregation applications. As part of personalized marketing and virtual fitting, smart apps can be used to show customers how they look when they are wearing any local products that they are not actually wearing. The same technique can be used to visualize how a new locally made piece of furniture looks in the home environments. 3D printing also may be used to create some of the personalized products.

15.7.3 Streetlights Information on the number of persons, time of the day, and the season/weather may be used to control streetlights and save power. Renewable energy may also be used. The information here may be used to strengthen the governance applications.

15.7.4 CCTV across cities Controlling and monitoring of CCTV footage can be done based on privacy rules associated with the area for security parameters associated with the location. Some of the organizations have started using artificial intelligence (AI) for looking for exceptions in these CCTV footages, to ensure a better control on and terrorism or other attacks or thefts.

15.7.5 Manpower skill database Manpower and their skills is one of the most important assets of the city. A database of such assets can be used for improving city infrastructure and also dealing with any emergency situation.

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15.7.6 Smart entertainment In addition to tourist spots, places, and access to all the entertainment hubs of city needs to be handled and managed. Aggregator applications for such entertainment hubs is another useful application, which can be reused across cities.

15.7.7 Cloud kitchens Cloud kitchens and food aggregators are becoming the integral part of some of the newer smart cities. Again, data is collected in a standardized open format across cities for replication of application. Analytics on food habits coupled with other information on jobs, age group, and disease management can provide interesting insights on the city.

15.7.8 Connectivity of assets across the city and managing solar lights/energy storage City assets, the ambulance, fire brigade, and mobile X-ray vans are modes of transportation that need to be connected, so that they can be made available to consumers, as required. In addition, creating a city target for renewable energy and recognizing the citizens for usage of renewable energy, are part of the management of solar lights and energy storage.

15.7.9 Solid waste management and zero waste policy and green houses Data from sensor-enabled bins together with cameras can be used for more effective solid data management. In addition, green houses and air purifier towers are becoming a part of the smart city, which are controlled remotely with information collected via different types of sensors.

15.7.10 Disaster/emergency management and emergency response teams Most of the large cities across world are grown near river basin or near sea. In case of heavy rainfall or natural disaster like tsunami, disaster response management is required to save many lives and controlling damage to properties. A disaster planning and management system, enable a single-window real-time operational status across the complete city. Such systems can encourage collaborative and effective communication and intelligent information sharing between stakeholders and the key parties, by helping them to enable disaster preparedness. With availability of real-time data via sensors, CCTVs, and satellite images together with previous years’ history, preventive work may be done to save lives and property. In addition, work can also be done on sanitation and medication for people of flood effected areas, after the disaster. Data on availability and need of

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medication, food, and clothes can be shared with people in city and also with the government and NGOs. Training and readiness for disaster is a very important part of smart city. Fire and other drills together with online/offline trainings need to be part of smart-city open architecture, which may be done by the citizens of the city. Cities have started using blockchain in emergency management because of interoperability and transparency that it provides. In terms of interoperability, blockchain can be adopted as a universal system across organization, similar to the internet, and allow multiple parties across that system to coordinate resources in an emergency. In a disaster relief scenario, multiple parties are often contributing resources to aid an affected area. If all parties involved in this scenario were to adopt a blockchain-based shared system of record, they could coordinate more efficient disaster responses, ensuring resources were allocated to the areas where they are needed most. The central disaster control application could use this for public health data surveillance, where it can collect and communicate data to entities who treat patients in disaster relief scenarios, including local public health agencies, hospitals, and pharmacies.

15.7.11 Smart governance Smart cities require a smart government. A smart governance uses the disruptive potential of technology and data to innovate in all parts of the value chain in the city [6 8].

15.7.11.1 Analysis The government value chain starts with analysis of perceived societal problems, preferably in a fact-based way. The availability of big data combined with advanced data analytics techniques increases the predictive power of these analyses. Furthermore, due to proliferation of data, nongovernmental organizations become active in the analyses of societal problems, which creates competition in this domain.

15.7.11.2 Policy making The policy-making process becomes more complex due to increased transparency, competition in the analyses, combined with new types of digital democracy and cocreation. The result is however more effective policies due to relevant feedback and creative alternatives at earlier stages in the process.

15.7.11.3 Planning The use of digital technology allows a shift from public to private in the planning phase. Instead of defining a detailed solution, the government increasingly defines the high-level requirements, and lets the market define creative and innovative solutions.

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15.7.11.4 Execution The services of private companies are often used for the execution of policies, and helps in faster execution of policies. Due to all kinds of social innovation, however, new types of market parties, like social entrepreneurs, emerge. These parties distinguish themselves from traditional parties by accepting a different distribution of risks among partners and a different type of financial compensation.

15.7.11.5 Enforcement Policy enforcement and supervision on the proper execution of polices increasingly becomes data based and the responsibility remains with the government. Open data architecture smart governance brings-in citizens and organizations to work in collaborative ways.

15.8

Smart-city data democracy architecture

Gartner predicts that 20% of all local government organizations will generate revenue from value-added open data through data marketplaces by 2020. In addition, government will also be able to save on costs by providing applications for control access to various data.

15.8.1 Components of smart-city data The smart-city data captures the city information, assets, and metadata across security and privacy settings, which then can be used by application programmers to provide services in the city. There are three major sources of data for a smart city: 1. Physical form via sensors, CCTV cameras, or other data acquisition devices. 2. Organizations/government providing data, for example, health, vehicle availability, etc. 3. Analyzed information from social media, web, or provided by community.

The process of data sharing is being accelerated by the demand for efficiency and convenience. Thus, the smart-city data architecture consists of following layers at the high level: G

G

G

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Data Associated security/privacy tags Process and usage Associated training

For example, one of the major barriers for citizens interacting with government is the complexity of engagement via a variety of touchpoints. A simple question such as “how can I start a business?” can lead citizens through complex processes and rules and onto a variety of websites.

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“The way forward today is a community-driven, bottom-up approach where citizens are an integral part of designing and developing smart cities, and not a topdown policy with city leaders focusing on technology platforms alone,” said Bettina Tratz-Ryan research vice president at Gartner. In some cases, the city dwellers, who become part of this approach, also are open to share their “not so confidential” data, so that better services can be provide in the city. For example, anyone open for blood donation may share his blood group. Even a system of volunteers for any emergency service, with their skills can be made available. The analyzed data helps companies to improve the quality of their existing services and look for opportunities to develop new services. The trend is not, however, limited to “open” government data. Businesses, also even some individuals too, open-up their data to help innovations for a smarter city. By releasing parts of their data, companies expect to ignite the creativity of the crowd, to ultimately generate new types of revenues. This represents a paradigm shift compared to the current practice of keeping all data proprietary.

15.8.2 Data infrastructure In a smart city, data is as important as the physical infrastructure. In the past centuries, cities developed carefully thought out mechanisms to manage the physical infrastructure. For data, such mechanisms are either lacking or in its infancy. Data infrastructure is required to maintain the data, share this data and has the following features: G

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Authority—The data infrastructure is a credible, authoritative source of data. Transparency—The data infrastructure is transparent about where the data comes from, how it has been collected, and how it has been processed. Openness—The data infrastructure is open for all users, making the data as accessible as possible. Real time—The value of data decreases with its age. The use of IoT generates massive volumes of real-time data, which can be made available through the data infrastructure. Agility—In addition to the previous aspect, agility to update data quickly, the data infrastructure should also be agile to encompass new data sets.

Based on the security and privacy policies and data distribution policies of the city/country, data may also be stored on clouds, in large authorized data centers.

15.8.3 Connectivity and data hub Data from various devices and data sources via different modes of connectivity is pushed to secure clouds in the reliable data centers, where data analysis can be done. Connectivity may be provided via mobile 2G/3G/4G/5G, broadband, Wi-Fi, LoRaWAN, light, satellite, or other technologies that may be used for connectivity. Most cities ideally should use a combination of all these technologies to get the best return on their investments. Some smart cities have started creating partially free Wi-Fi hotspots for citizens in public areas to provide them better connectivity.

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15.8.4 Smart city metadata model This section provides recommendation for a metadata model for the cities, as in Fig. 15.4, which can lead to desired standardization across cities. Metadata models are discussed in Refs. [9 11]. The model has been kept generic and at a high level so that it can be expanded easily. The metadata model views are shown as follows: G

Information hub view: This further consists of: Data hub view: This gives access to the data hub where the data exchange for city is done. This view is created based on roles again. Application view: Application developers participate in this view to create different views of data of smart city, which can be converted to applications and monetized. Infrastructure view: Most smart city start with a base of connectivity, smart grid, sensors or CCTVs, travel cards, etc. to capture the data. Capability view: This is an abstract representation of any capability/feature of city. For example, a city may be known for its handicrafts, handloom, tourist places, education hub, or even specialized food. Participation view: This view covers information and data related to participants, policy makers and the utilities and services, for with data is required. Application designers, developers, and testers collaborate to create the applications. Place view: Place view stores data on major places covering tourist destinations, schools, hospitals, major markets, and major landmark buildings. It will also have the GPS coordinates of these locations. Service view: This view provides the open API/services to the developers based on his role or the contract and the security policies associated with the data. G

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Figure 15.4 Smart-city metadata model.

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Business process view: Smart cities will have disparate business processes and applications run of the data provided by the city. Analytics view: This view makes data available for analytics after taking care of the rules laid for data privacy as per the government and country guidelines. Data anonymization is done as per the security and privacy guidelines [8]. For example, for health data, name, and address may be anonymized and only the sex of patient and age profile of persons with health data may be given for the desired analysis.

15.8.5 AI for smarter decisions in smarter cities Augmented intelligence and analytics is the integral part of smartness of the smart cities. Most applications described in the previous sections need analytics or even machine learning algorithms in a lot of cases. Following are some more use cases where AI is already being used in some of the smart cities: G

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AI powered chatbots can contextualize and personalize government services, improve service delivery and augment municipal employees’ effectiveness. There may be “bots,” which deal with frequent and routine tasks such as filing applications for hospital checks, childcare or vet-care support, or housing assistance. Bots guide applicants through the process, help prevent mistakes, and assess the chance of success, saving time for both applicants and government employees. AI for predicting disaster/rain falls or even environment condition: Based on the previous year’s data the metrological data available, predictions for heavy rain or water clogging or even bad air can be made. AI can also be used for predicting and monitoring “exceptions” in CCTV footage to provide extra safety for residents of the city or even city assets. Researchers in China and Australia developed models to predicting intersection traffic using tree models. By combining the historic and recurring events with “real-time spatiotemporal information related to the nonrecurring events” like construction or accidents, they can predict and manage better control on traffic and interactions.

15.8.6 The need for new operational requirements, skills, and expertise With the data hub for cities, comes the requirement of Network Operation Control Centre (NOCs) with build-in Security processes and infrastructure to monitor the sources of data and their availability. Mostly these NOCs need to be monitored 24 7 and can be in city or can be created for cluster of cities. They require the skilled manpower for their operations. Additionally, the applications and the embedding AI in smart city solutions requires changes in city operations, technology platforms and data privacy policies. While an embedded and interoperable AI improves the range of applications, the complexity of information, and data flows increases and raises new questions on algorithmic business flows and even on intellectual property rights of product. Technology team should oversee the necessary technology operational changes to manage this complexity. They must not only align city operations and management platforms, but also optimize data and analytics governance, data orchestration

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and predictive analytics to realize the full value of conversational AI. They also need to create policies and standards for information governance, privacy and information security for platforms, their algorithms, and the information accessed and used by their intelligent applications.

15.9

Security, privacy, and business continuity concerns of data hub

The metadata created for the smart city needs to have data privacy concept associated with it as per the norms of the country. For example, in case of eldercare, to view their data of a possible fall, the person concerned or his family or the clinician must authorize the application to view his home images/or sensor data that can indicate a fall. Again, it may be defined, who can see the data. Can only family or government agencies or hospitals view that data, or anyone can view that data? Data hub needs to have role-based authorizations to connect to the data, which may be administrators, public, or developers. The semantic or the knowledge hub created for these cities enables data integration from heterogeneous urban sectors and sources, irrespective of the different qualities, speeds, and scales. An additional innovative aspect of this ontology refers to the integration of concepts for human-generated data, coming from smart devices and social media platforms, being increasingly important sources of knowledge for the domains of urban analytics and decision-making. Wireless sensor networks across cities have increasingly become contributors of very large amounts of data. The recent deployment of wireless sensor networks in smart-city infrastructures has led to this data being generated each day across a variety of domains, with applications including environmental monitoring, healthcare monitoring, transport monitoring, and others. To take advantage of the increasing amounts of data there is a need for new methods and techniques for effective data management and analysis to generate information that can assist in managing the utilization of resources intelligently and dynamically. Through this research, a multilevel smart-city architecture is proposed based on semantic web technologies. This multilevel architecture should ensure storage of data in a meaningful way. Based on the storage capacity and associated data protection policy and associated data weening policy, this multilevel modular smart-city architecture will have another field associated with it which will be “life” of this data. City data provided by heterogeneous sources need to be appropriately interpreted, aggregated, filtered, annotated, and combined with other data sources in order to be queried or analyzed. Some research papers have proposed different semantic data platform to provide an interoperable representation of data and achieve the mentioned goals. Implementation of intrusion detection and protection devices together with security algorithms needs to be done in data hubs as part of infrastructure planning. Business continuity planning is another very important aspect of infrastructure planning of smart cities. The data center should be minimum of Level 3 data center and should have a disaster recovery site in a different geographic zone.

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355

Summary

Smart cities present an opportunity for rendering web of Things-enabled services. The anonymized data may be used for bringing out the required statistical reports for the city, for better planning and utilization of city assets. Standardization of infrastructure, processes together with open data frameworks helps in faster scaling of applications across cities. Most smart city technology implementations are supported by technology companies, researchers, and international research bodies. Stakeholder consultation is a very methodology to improve and add to the smart-city operations and facilities. While prioritizing the investment in applications and infrastructure, a social view of smart cities must be taken. This view may include improving ease-of-life to job creation and cover city sustainability goals. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

15.11

Chapter review questions/exercises

15.11.1 True/False 1. True or False? Only government is responsible for converting a city to a smart city. 2. True or False? Standardization of infrastructure in smart cities helps in faster replication of environment. 3. True or False? Privacy of city dwellers cannot be compromised, while picking their data for analysis. 4. True or False? Connectivity in a city is not essential for making it smarter. 5. True or False? In some case, some city dwellers may willingly provide some of their data.

15.11.2 Multiple choice 1. Data in city may not be collected via (sources of data) a. Sensors b. People c. CCTVs d. System administrators e. Social media 2. ________________ is very important to ensure meaningful output of data collected from various sources of smart city? a. Centrally managed repositories b. Information system auditors c. IT personnel d. Data analytics e. All of the above

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3. A relatively simple way to bring in standardization is to store information with its____________. a. User data b. Source c. Unique identity management d. Metadata e. Boundaries 4. Smart cities as per of their smart health initiative provide: a. Tele-consult facilities b. Homecare facilities c. Health education to citizens d. Ambulance service e. All of the above 5. Why is open data and data monetization important in smart city? a. Sustenance b. Bring-in innovation c. Replication with scale d. Creates jobs e. All of above

15.11.3 Exercise 15.11.3.1 Problem What kinds of data aggregation services are required in a city?

15.11.4 Hands-on projects 15.11.4.1 Projects Create a list of sources of data, data types, associated data security and propose data weening policy for these data types.

15.11.5 Case projects 15.11.5.1 Problem How can a tourist feel safer in a smart city? Define hardware, software, and processes to cover his various use cases.

15.11.6 Optional team case project 15.11.6.1 Problem How can we convert smart city technology services group to a revenue generator?

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References [1] Draft Policy of Internet of Things for India, Ministry of Electronics and Information Technology, Delhi, India. ,https://meity.gov.in/content/revised-draft-internet-thingsiotpolicy-0.. [2] Technical Report enablement of M2M and ICT in Smart Cities, Department of Telecommunication, India. ,http://tec.gov.in/pdf/M2M/ICT%20deployment%20and% 20strategies%20for%20%20Smart%20Cities.pdf., November 2015. [3] M2M Communication guidelines, Ministry of Communications, India. ,http://dot.gov. in/machine-machine-communications.. [4] National Telecom M2M Roadmap, Department of Telecommunication, India. ,http:// dot.gov.in/sites/default/files/National%20Telecom%20M2M%20Roadmap.pdf., April, 2015. [5] India Smart Grid. ,http://www.indiasmartgrid.org/.. [6] Connected Cities. ,https://www.cisco.com/c/en_in/solutions/industries/smart-connectedcommunities.html.. [7] ITU (International Telecommunication Union), Geneva. ,http://www.itu.org/.. [8] Role of Big Data in Smart Cities. ,https://www.sciencedirect.com/science/article/pii/ S0268401216302778.. [9] India’s Smart City Plan. ,http://smartcities.gov.in/content/.. [10] Data Driven Reference Architecture for Smart City Ecosystem by Mohammad and John Davies. ,https://www.researchgate.net/publication/317617860_Data_Driven_ Reference_Architecture_for_Smart_City_Ecosystems.. [11] Mapping Smart City Standards. ,https://www.bsigroup.com/LocalFiles/en-GB/smartcities/resources/BSI-smart-cities-report-Mapping-Smart-City-Standards-UK-EN.pdf..

Securing smart-grid infrastructure against emerging threats

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Daisuke Mashima Advanced Digital Sciences Center, Illinois at Singapore Pte Ltd, Singapore, Singapore

16.1

Introduction

Reliable delivery of electricity is the crucial building block for today’s and future smart society. In order to improve the efficiency and effectiveness of electricity services and also to enhance security and safety of power grid operation, remote management, and automation of power grid systems attracted high demand. In this direction, modernizations of power grid systems, by means of intelligent devices, including programmable logic controllers (PLCs) and intelligent electronic devices (IEDs) that have capability of communication and computation have been promoted and a number of standard communication specifications have been established by International Electrotechnical Commission (also known as IEC). For instance, IEC 60870-5-104 is used for remote control and monitoring of field substations over wide-area network (WAN) over TCP/IP, a network protocol used for the Internet [1]. On the other hand, IEC 61850 is used for communication within each substation local area network for the sake of automation [2]. Information model defined in IEC 61850 is mapped onto different transport protocols, such as MMS (Manufacturing Message Specification), GOOSE (Generic Object Oriented Substation Events), and SV (Sampled Value). MMS is a protocol over TCP/IP and utilized for communication among local HMI (human machine interface), PLC, and IEDs. GOOSE and SV are link-layer multicast communication used to enable high-speed exchange of real-time status/measurement exchange among IEDs and merging units. While the modernization of power grid benefits the improvement of our critical infrastructure, at the same time increased connectivity not only has expanded the attack surface but also make it complicated. While traditionally the control system of power grid was completely isolated from the rest of the world, in modernized power grid systems, the control system is often connected to the enterprise IT system and even to the public network such as the Internet or cellular network. For example, cellular communication channel is often used for remotely monitoring a large number of distribution-level (low-voltage) substation in a cost-efficient manner, and VPN (virtual private network) interface connected to the Internet is becoming common for enabling remote maintenance of device vendors as well as for the use as a backup SCADA communication channel. Thus, “security by Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00016-4 © 2021 Elsevier Inc. All rights reserved.

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air-gap” no longer holds, which was unfortunately demonstrated by a number of real-world incidents in the past years. In this chapter, we first discuss real-world cyber-security incidents in the past years, such as the Stuxnet case [3] and Ukraine power plant attacks [4], and discuss existing security mechanisms to provide a context. Then, we move on to the discussion of state-of-the-art cyber-security measures available for protecting smart grid infrastructure along with their potential limitations, which leads us to the discussion of novel cyber-physical security technology that can effectively complement the existing security solutions to counter emerging threats.

16.2

Emerging cyber threats targeting smart grid

Traditionally, a smart grid system (and other types of industrial control systems) was considered secure, largely because of the “airgap” between the system and the rest of the world, including the Internet and the enterprise IT system of the corresponding company. However, Stuxnet malware, which was reported in 2010, successfully bypassed the airgap and penetrated the control system of a nuclear plant in Iran [3]. Unlike typical malware at that time, Stuxnet was a malware specifically targeting industrial control systems. Stuxnet utilized removable storage devices used for PCs (e.g., USB drives) as an initial infection method. Because of this strategy, Stuxnet was copied to a PC in the control system infrastructure via an employee’s USB drive, bypassing the airgap. After that, Stuxnet started lateral movement and propagated by exploiting network shares of Windows PCs, taking advantage of multiple zero-day vulnerabilities, to find PCs running software used for configuring Siemens PLCs. Eventually PLCs associated with centrifuge units of nuclear plants were compromised to change the rotation speed of the units, which might have caused a disastrous situation. At the same time, in order to lower the situational awareness, Stuxnet injected fake, normal-looking sensor measurements to deceive human operators.

16.2.1 Ukraine power plant attacks Arguably the most notorious cyber incident targeting power grid system is the incident in Ukraine in 2015 [4]. In this incident, the SCADA master workstation that was connected to power grid systems was remotely manipulated by an adversary to send out a large number of malicious control commands to open circuit breakers, deenergizing substations. This incident was caused by well-prepared attack and seen as a successful demonstration of so-called industrial control systems (ICS) Cyber Kill Chain [5]. Attackers started with sending phishing emails to targeted employees working for power grid operators in Ukraine, in order to get their PCs infected with a malware called BlackEnergy 3 [6]. After the successful infection, the malware collected information about system configuration and topology as well as identity credentials

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used in the system. Using such information, the attackers compromised a remote access interface, for example, VPN, which is increasingly used for remote monitoring, control, and maintenance by operators and vendors. After penetrating the control system infrastructure, the attackers hijacked the SCADA master system, which was connected to the field devices in the power grid system (e.g., circuit breakers), and abused it to cause the massive power outage. The following year, Ukraine power plants were attacked again. In the incident in 2016, a new malware called CrashOverride (also called Industroyer) was reported [7]. One of the advanced capabilities of this malware was support of standard communication protocols used in SCADA systems, including IEC 60870-5-104 and IEC 61850 that are globally employed in smart grid systems. This fact implies that, once CrashOverride malware infects any devices in the control system, the infected device can potentially impersonate a legitimate SCADA master system to inject malicious, but valid-looking, control commands under cyber attackers’ control. In more recent years, we have witnessed cyber attacks accessing control room of the electricity utility companies. For instance, in 2018, it was reported that Russian hackers intruded into a control room of power companies in the United States [8]. Moreover, malware attack by North-Korean hackers targeting Indian nuclear power plants was reported in 2019 [9]. Thus, attacks mounted from the trusted control center particularly require attention when designing and implementing cyber-security solutions for protecting smart grid infrastructure.

16.2.2 Aurora generator test It is also possible that cyber-originated attacks cause physical destruction of crucial power grid components. In 2007, researchers of Idaho National Laboratory performed experiment to demonstrate that such a risk is realistic [10]. In this experiment, researchers used a real diesel generator that can produce 2.25 MW of electricity. They emulated cyber attacks that abuse its remote control interface that open and close the circuit breaker connected to it repeatedly. The sequence of the commands was crafted in such a way that mechanical stress was caused on the generator. As the result, the increased physical stress on the generator caused smoke within just 3 minutes, and researchers warned that real cyber attackers could do the same within even shorter time. It is said that this vulnerability is related to the outof-sync closing of the protective relays. In many of the existing smart grid systems, commands from the control center are blindly trusted, and therefore once a persistent attacker or malware would succeed in injecting legitimate-looking control commands, attacks of this sort is realistic.

16.3

Security solutions for protecting smart grid

In order to ensure interoperability among multivendor devices or systems in substation, standardized technology has emerged. For example, IEC 60870-5-104 and

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DNP 3.0 (mainly in the United States) are created for telecontrol and monitoring of remote substations. On the other hand, communication within substation is done by using IEC 61850 MMS or GOOSE protocols. Unfortunately, these protocols were not secure by design because, in the power grid context, the highest priority is placed on availability of communication, and security comes next. In order to define standardized security implementation, IEC 62351 standards have been established to define security enhancements for these protocols [11,12]. For example, IEC 62351-3 defines use of TLS (Transport Layers Security) for encryption and authentication of messages for all TCP-based protocols (e.g., IEC 60870-5-104 and IEC 61850 MMS), and IEC 62351-6 is written about security for IEC 61850 protocols, including IEC 61850 GOOSE and SV. See Table 16.1 for more details about the standards. While implementation of IEC 62351 is considered effective to counter many of the cyber-security threats, its penetration in real systems is still low. The main reason is that its requirements are relatively heavy for embedded devices already deployed in smart grid infrastructure. For instance, typical RTUs (remote terminal units) or protocol translators are equipped with highly constrained computational power, which makes it difficult to handle computationally intensive security features like public-key cryptography under the stringent latency constraints. Moreover, since many components in smart grid infrastructure are usually used for decades once deployed, upgrading and replacing devices would be costly. Industrial firewall products and data diode devices are also available to enforce security policies on data transfer and communication in smart grid systems. Industrial firewall supports popular industrial control system protocols, including Table 16.1 Overview of the IEC 62351 standard. Description

Security mechanism

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Transport (T-)Profile— TLS Application (A-)Profile: Peer authentication using certificates Serial version— Challenge-response protocol Network version: TLS GOOSE and SV—Digital signature MMS—TLS Role-based Access Control (RBAC)

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those used in smart grid systems, such as IEC 60870-5-104, IEC 61850, DNP3, and Modbus, to enforce network traffic control policy defined in terms of combination of source and destination addresses, TCP and UDP ports, which correspond to network services provided, and message payload. On the other hand, data diode technologies can be regarded as a special type of firewall that enforces one-way data flow. While firewall works on or above link layer (OSI layer 2) and works based on software that enforces rules defined by human operators, data diode enforces the direction of traffic at the physical layer without requiring any software. This way, data diode is considered more robust (i.e., difficult to compromise or bypass) but its flexibility is limited compared to traditional firewall. Several intrusion detection technologies have been proposed for industrial control systems. While intrusion detection can be implemented in host-based and network-based manner, owing to the resource constraints on field devices, most of the efforts in industrial control systems domain are focused on network-based approach, which monitors network traffic among devices. For example, Ref. [13] tailored Bro intrusion detection system [14], which is one of the most widely-used open-source intrusion detection systems (IDS), for smart grid protocol, namely, DNP3. Similar efforts have been made by Ref. [15] to implement IEC 60870-5-104 protocol parser for Bro. These efforts not only allowed users to define intrusion/ anomaly detection rules based on network characteristics (e.g., source and destination, port numbers, etc.) and protocol-specific payloads but also have provided an effective building block for other intrusion detection systems. In Refs. [16,17], multilayer, multiattribute intrusion detection systems are proposed. Their systems utilize ensemble of different detection logics to make the decision. For instance, SCADA IDS proposed by SPARKS project in Europe [17] consists of three different detection mechanisms, namely whitelist, stateful analysis, and anomaly detection using machine learning. In their system, whitelist is defined based on network-level characteristics, such as MAC address, IP address, protocol used, and port number. The whitelist can be generated either manually or systematically based on configuration of devices in substations. For example, in IEC 61850-compliant substations, information of each device as well as connectivity of them is defined in standardized substation configuration language files, and therefore, by parsing those files, the list of authorized node and communication patterns can be automatically generated. The second layer of the detection is based on protocol specific information. For instance, IEC 61850 MMS has the request-response communication model, and each pair of request and response is coupled by “InvokeID.” If such a pattern or rule is violated, an alarm can be raised. This layer also involves behavior inspection, which investigates payload of each packet (e.g., power grid measurements such as voltage) and enforces rules in terms of such measurements to detect misbehavior of monitored power grid devices. The third layer of the proposed scheme employs anomaly/outlier detection based on aforementioned network-level and application-level (i.e., protocol-specific) characteristics using machine-learning technologies, such as one-class SVM. The advantage of this approach is that the system can detect novel intrusions or anomalies that are not yet coded into rules used in the previous layers.

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Because of infeasibility (and reluctance of power grid operators) in making major upgrade on the system infrastructure as well as devices, bump-in-the-wire (BITW) security appliances are often utilized for retrofitting advanced security technologies without requiring major changes on the existing infrastructure. BITW security solutions are implemented as an additional device that provides security in a manner transparent to the existing devices. For example, layer-2 encryptor devices can apply cryptographic protection for the network traffic [18]. Another solution offers end-to-end, provenance-aware SCADA message authentication [19]. At the high-level, such solutions introduce additional devices in front of all devices that need security, and the BITW device at the sender side intercepts and encrypts the outgoing message and/or attaches cryptographic metadata for message authentication while the counterpart at the receiver side is responsible for decryption and/or verification and removal of the cryptographic metadata before passing the original message to the target smart grid device. Since BITW devices are usually more resource-rich compared to PLCs and IEDs, BITW devices can implement strong cryptographic schemes (e.g., public-key cryptography), which is required by the IEC 62351 standards, as well as other security features. Commercial layer-2 encryptor devices typically cost in the order of thousand dollars or more per unit and thus it is not practical to deploy such devices for each IED or PLC because there can be hundreds of devices in a single substation. Thus they are usually deployed at the perimeter of each subsystem. As proposed by Ref. [19], lower-cost, embedded platform can be utilized instead, availability and possibility of false alarm, which blocks legitimate message, would be a remaining concern. There are other types of solutions as summarized in Ref. [20], including advanced intrusion detection systems using machine learning and/or power system physics, hardware-based or software-based remote attestation technologies that enables verification of system/software integrity remotely, and deception technologies such as honeypot that can be used to confuse or mislead attackers. However, these are not yet mature enough to be deployed in the real power grid systems.

16.3.1 Limitations of existing cyber-security solutions The security measures discussed in the earlier sections can counter attacks of certain types. For instance, if an attacker attempts to inject malformed packets into the system, it would be filtered out at the firewall. Likewise, packets injected from an unauthorized source (e.g., an attacker’s PC outside of the smart grid infrastructure or compromised IEDs in a substation) can be blocked by a firewall or flagged by intrusion detection systems. However, what if a legitimate SCADA master system or HMI in the control center system is compromised and manipulated by attackers? Besides the possibility of malicious insiders, the Ukraine case discussed earlier demonstrated that such an attack is possible. In addition, because of the fact that there is no end-to-end SCADA message authentication (even when IEC 62351 is deployed, the message authentication, and encryption are applied in hop-by-hop manner), man-in-themiddle (MITM) attacks on the multihop SCADA communication path, including

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the control center LAN, WAN, and substation LAN, is also a risk. For instance, as you may recall, CrashOverride malware has capability to emit SCADA messages that are compliant to standard SCADA protocols, including IEC 60870-5-104 and IEC 61850. Attacks of these types cannot be effectively countered by the aforementioned security schemes because the packet format is completely compliant to the standard and the sender of messages is a legitimate entity Note that, even if messages are forged by intermediate entities, downstream entities on the multihop communication path have no effective way to tell if the message is actually generated by the SCADA master or not, owing to the lack of end-to-end message deliverypath verifiability.

16.4

Supervisory control and data acquisition command authentication as additional line of defense

In order to effectively counter the attacks of this category, it is mandatory to implement an additional layer of security that is complementary to the existing cybersecurity technologies. In this direction, we discuss technologies called command authentication systems, which evaluate validity and/or legitimacy of SCADA commands based on the real-time cyber-physical status of the power grid and context. By deploying such a mechanism at the edge of smart grid communication infrastructure, that is, at the boundary of cyber and physical sides of the smart grid systems, we can effectively mitigate the damage caused by malicious control commands.

16.4.1 Trends in supervisory control and data acquisition command authentication SCADA command authentication has attracted attention in recent years. So, let us first discuss some representative examples. Meliopoulos et al. [21] proposed to utilize distributed state estimation and simulation for detecting malicious commands. Namely, the command authentication module that is deployed at each substation runs power flow simulation based on local power grid measurements; as well as, information collected from nearby substations to evaluate the legitimacy of incoming remote control commands. Moreover, in order to shorten the latency for simulation to meet real-time requirements, the authors proposed to use simplified power grid model for simulation. One drawback of the proposed scheme is that it requires intensive communication among peer substations in proximity, which may expand the attack surface to confuse or mislead the proposed security solution with fake data. Lin et al. [22] employs distributed sensors as well as a centralized command authentication system running power flow simulation. Specifically, an intrusion detection system deployed in each substation is responsible for reporting received remote control commands back to the central command authentication system. Then, the command authentication system runs power flow simulation based on the

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complete view of the power grid to evaluate the outcome of the command execution. If any stability violation is found in the simulation results, the central system sends out reversing control command to neutralize the attack. Their scheme exhibits high accuracy, but its mitigation strategy is reactive, which is not an ideal solution under certain scenarios. For instance, in the case of commands to stop or change set point of thermal generators, it may take long time to restore to the original state even if the reverse control is initiated very quickly. If the target of the command is a nuclear plant, the outcome could be disastrous. Moreover, if circuit breakers connected to loads are opened even for a short while, it would not only cause inconvenience on electricity customers owing to the service disruption but also negatively affect revenue and reputation of the power grid operator. One potential drawback that is shared in the both schemes is that they rely only on steady-state information. The primary reason for such a design decision is that steady-state power flow simulation can be done very quickly and therefore is suitable for online, real-time operation. Steady-state power flow simulation allows us to predict voltage magnitude and angle, current, and real and reactive power flow resulting from a control (e.g., opening or closing circuit breakers) in steady state. The calculation is basically done by solving a series of equations, which are derived and based on power system physics. The calculated power flow and/or voltage information allow us to evaluate the power grid stability by comparing them against power system stability criteria, for example, ones used by WECC (Western Electricity Coordinating Council) in the United States [23] or other threshold defined by each power grid operator. For instance, the attack detection in Ref. [22] is done based on transmission line overload (i.e., whether the power flow on each transmission line in the power grid is within its nominal capacity or not). However, the limitations of using only steady-state power flow information have been pointed out by Grigsby [23], and the necessity to take transient stability, frequency stability, and cascading effects is emphasized. One example on GSO 37-bus power grid model [24] that demonstrates the limitation is shown below. Fig. 16.1 shows the result of steady-state power flow simulation on PowerWorld simulator [25] where one of the generators (marked with a solid circle near the center) is disconnected. As can be seen in the figure, the only noticeable change in the steady-state power flow is increase in power flow on one of the transmission lines (highlighted with the dashed circle on the left). However, the power flow is still 81% of the capacity of the corresponding line, and it is not treated as an anomaly or attack in the command authentication using steady-state information. On the other hand, if we investigate the behavior in the transient state (i.e., power system dynamics) under the same scenario, the story is totally different. Fig. 16.2 shows the frequency swing during the transient state after the generator is disconnected. As can be seen, the electricity frequency (nominal value is 60 Hz in the United States) started dropping rapidly and goes as low as 58.6 Hz and stays below 59 Hz for nearly 10 seconds. According to the WECC criteria [23], this is considered as violation of Category C limit (below 59 Hz over 7 seconds), and therefore this should be considered as a nonnegligible stability problem.

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Figure 16.1 Steady-state simulation result after malicious circuit breaker control.

Figure 16.2 Power system dynamics simulation result (frequency) after malicious circuit breaker control.

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As seen earlier, there can be malicious commands that are overlooked by state-of-the-art command authentication schemes using steady-state power flow simulation but could harm power grid stability and connected devices. This observation motivates exploration of use of power system dynamics simulation, which incorporates transient-state behavior and cascading events, for protecting smart grid systems against malicious (or anomalous) control commands.

16.4.2 Command authentication using power flow dynamics simulation Based on this observation, we designed a command authentication system using onthe-fly power system dynamics simulation [26]. The algorithm of the command authentication is formulated in Fig. 16.3. At a high level, the command authentication system runs two simulations simultaneously when a remote control command is received by a substation in the field. More specifically, the system evaluates if the simulation with the command execution causes any (additional) violation of power grid stability conditions or whether the command execution would make the situation worse, compared to the case without the command execution. The command authentication module, which is assumed to be centrally deployed (e.g., in the control center), is invoked whenever remote control commands (cmdnew) are reported by field systems. PG represents power grid topology along with up-to-date snapshot of power grid status required to run power system dynamics simulation (DynSim()). If there are preceding command(s) or event(s) to be jointly simulated under PG, eventpre should be set accordingly. In practice, PG can be updated once every few seconds or even in the order of minutes. Thus, for example, when multiple commands are reported within a short duration, commands reported between the last update of PG and receipt of cmdnew are supposed to be included in eventpre. Both eventpre and cmdnew contain timestamp relative to the latest system snapshot to be used for simulation (i.e., PG) so that they can be simulated at the appropriate time. If the power grid is under some contingency or disturbance, it should also be reflected in PG and/or eventpre. Then we compare (isWorse()) two simulation results, one with (Rescmd) and the other without (Res0) the command execution, to decide whether the command

Figure 16.3 Algorithm of command authentication using power system dynamic simulation.

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should be executed or not. Note that Res0 can be calculated in advance or in parallel to Rescmd. The decision criteria based on power system dynamics simulation includes, but not limited to: G

G

G

G

Whether any (additional) stability violation (i.e., in voltage, frequency, and/or line capacity) is observed. Whether a system dynamics simulation is aborted in the middle owing to blackout or islanding. Duration till blackout/islanding situation occurs (the longer, the better). Magnitude of frequency/voltage deviation from the nominal value and/or line overload

The command authentication system implementing the aforementioned logic showed promising results. We conducted simulation study using GSO 37-bus power grid model and PowerWorld simulator to evaluate both false positives and false positives. At the high level, in order to evaluate false negatives, we simulated contingency scenarios and evaluated if any legitimate recovery control command is flagged malicious. Under the same contingency scenarios, we also injected random control commands (other than the legitimate ones) to see whether they are flagged or not, in order to evaluate false negatives. Based on our study, we did not observe any false positive, which means that all legitimate control commands are not flagged and thus executed as expected while we see significant improvement in terms of false negatives compared to command authentication using steady-state power flow simulation. We refer interested readers to Ref. [26].

16.4.3 Active command mediation defense (A CMD) system and practical integration In order to integrate the command authentication system with power system dynamics simulation into real-world power grid operation, we need to address several technical challenges. In this section, we discuss them and provide practical solutions. The first challenge we must address is the latency for running power system dynamics simulation. As stated earlier, steady-state power flow simulation is very quick and on PowerWorld simulator [25], recalculation of power flow and voltages can be done almost instantly. On the other hand, power system dynamics simulation takes significantly longer time. Based on our measurements using the same PowerWorld simulator with Transient Stability add-on, a 30-second simulation on the GSO 37-bus model takes around 450 ms [27]. In addition to this simulation time, it takes time for initializing the simulator as well as for retrieving and analyzing the simulation results. Thus, based on our measurements, we should expect around 0.9 1 second in total including some safety margin [27]. In order to block malicious control commands before they are executed on the physical power grid system, it is necessary to put incoming remote control commands on hold until the command authentication is done. In order to implement such a command-delaying feature, we proposed a system architecture called active command mediation defense (A CMD for short) [28]. As can be seen in Fig. 16.4, A CMD module can be deployed at each substation in such a way that it can

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Figure 16.4 Architecture and deployment of A CMD System.

reliably mediate all communication to and from the control center. According to the reference model of modernized substations defined in Ref. [29], it is equipped with a device called proxy or gateway in Fig. 16.4, which is responsible for protocol translation. Specifically, the standardized protocol used for telecontrol of substations (i.e., communication between the control center and substations) is IEC 60870-5-104 while IEC 61850 MMS and/or GOOSE protocol is used for automated control and status update within each substation (i.e., among IEDs). Therefore, in order to enable endto-end connectivity between the control center and IEDs in substations, protocol translation is mandatory, which make the substation gateway (i.e., protocol translator) an ideal place to deploy additional security features like A CMD. The A CMD system on the substation gateway, when receiving incoming remote control commands, which might have been injected by a malicious entity at the control center or on the WAN, can add an artificial delay before forwarding the translated messages to the destination devices. During the added delay, the command authentication logic is executed to decide whether each command should be executed or not, for example based on power flow simulation as discussed in the previous section. The command authentication logic can be implemented in each A CMD module in a distributed manner, just as proposed in Ref. [21], or can be deployed in a centralized way, for instance at the control center. Given that devices deployed in the smart grid infrastructure is generally resource constrained and therefore it is not feasible to handle heavy computation. Another limitation of the distributed approach is that each instance lacks system-wide, global view about the power grid system. Because of these reasons, in the following text, we discuss such a centralized command authentication with A CMD.

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16.4.3.1 Artificial command-delaying Because, in general, delay or latency is not considered a positive thing in industrial control systems, in particular power grid systems, the configuration of artificial command-delaying requires careful design consideration. For instance, fault isolation, relay protection, etc., require very short latency (e.g., 10 ms or lower). However, each use case has different requirements and it may not be always a necessary condition. In particular, the substation remote control, which is of our particular interest, can tolerate longer latency. We here argue that, if there is a gap between the necessary condition (i.e., maximal delay allowed in the targeted context) and technical constraints (e.g., network latency), we can take advantage of the difference to accommodate latency for the advanced command authentication techniques. In the power grid domain, there are a number of publicly available guidelines for message delivery latency. One of the established documents is the one published by IEEE Power and Energy Society [30]. This document defines delivery latency requirement for many use cases of smart grid communication. For example, the message delivery for transfer switching should be done in 1 second, while messages related to load shedding is expected to be delivered in 10 seconds. Other guidelines can be found from academia. Ref. [31] states that communication latency requirements for the distribution automation (e.g., voltage/VAR control) are said to be less than 4 5 seconds, and even longer for many of other scenarios. Although there is no universal agreement yet, based on such observation, overall remote control is less latency stringent and can tolerate second-level delay. In addition, many of the remote control use cases do not have stringent timing constraints. Namely, since the purpose of topology control is economical optimization, circuit breaker control for this purpose may be delayed by seconds or even minutes without any negative consequences in grid stability. Regarding voltage regulation by controlling shunt reactors, according to our industry partner, controls are manually done by human operators usually in the morning and evening, which again is not considered sensitive to minor delay even when remote control is implemented for this purpose in the future. Having that said, each power grid model may have different tolerance to the message delivery delay, and to confidently configure command-delaying, simulation study would be demanded. Thus, we next discuss the systematic framework to find the delay tolerance by means of power flow simulations [28]. The procedure to find such a tolerable delay, D , can be formulated as in the algorithm in Fig. 16.5. The algorithm requires three inputs, PG, SC, and CTG. The PG input includes the grid topology, the configuration of each power system component, and status snapshots that are typically used for contingency analysis and power flow simulation. The SC input contains stability conditions in terms of frequency and voltage violation, etc. The CTG input is a set of contingencies that require (typically automated) remote control for recovery and can be defined based on N 2 1 (or more generally N 2 x) contingencies. Note that, N 2 1 contingencies are situations where 1 (x) out of N power grid components (e.g., generators) is lost or disabled. In the algorithm,

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Figure 16.5 Algorithm to find delay tolerance for power grid model of interest.

function named findRecoveryControl() invokes contingency analysis to find an appropriate set of recovery control commands. We should note that this step is typically done by power grid operators at the design phase. findTolerableDelay() function invokes iterative power flow simulations (in particular transient-state or power system dynamics simulation) with varying delays before the execution of recovery commands to find the maximum delay that can be introduced without causing violation of SC for the given contingency scenario and recovery control. D is selected as the minimum of all Delaycs, each of which represents delay tolerance for a certain contingency. The search space for Delayc can be narrowed down based on the available guidelines such as Refs. [30,31]. The initial value for D can also be set accordingly, for example, to around 2 seconds. Instead of defining a global D , we can also consider associating different delay tolerance with each individual power grid device (or device types), and the algorithm in Fig. 16.5 can be generalized accordingly. For example, let us see how D can be obtained in practice, by using GSO 37-bus power grid model. In smart grid systems, remote control is introduced and utilized for various purposes, such as power shedding to curtail overgeneration of renewables, load shedding for addressing generation-loss contingency, voltage regulation though shunt reactor control, topology control for economic optimization, and so forth. Out of these remote control scenarios, load shedding is considered not only the most time sensitive but also influential for customer experience as well as revenue of utility companies [27]. Thus, in this study, we focus on load-shedding control to maintain grid stability under generator-loss contingency, though different type of contingency and recovery control can be evaluated likewise. We simulated all N 2 1 contingencies focusing on generator loss. Because the GSO 37-bus model has nine generators, there are in total nine different settings. The procedure of our experiment is: 1. For each N 2 1 contingency case, run transient-state simulation to see if violation (in this case study, in terms of frequency) occurs. 2. For each contingency case that encounters violation, find a set of loads to be shed to avoid the violation (findRecoveryControl() in Fig. 16.5). 3. Apply the load shedding with different delay configurations and run power system dynamics simulations to find maximal delay that does not cause violation (findTolerableDelay() in Fig. 16.5).

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As the threshold for frequency violation, we used 1% (i.e., 0.6 Hz deviation in the case of the US power grid) from the nominal frequency, according to Ref. [32]. In the aforementioned Step 2, our strategy to find the appropriate load-shedding control set is to add loads one by one from the one nearest to the lost generator. Although we do not claim it is the optimal set, we believe our approach is reasonable from grid operators’ perspective. The development of a mechanism for finding a cost-optimal load-shedding strategy (or other types of recovery strategy) in a systematic and/or distributed way is outside of our scope, but it is possible, for example, by employing technology developed in Ref. [33]. The results of the above experiments are summarized in Table 16.2. As can be seen, recovery controls for the loss of bigger generators is less tolerable to delay. For the loss of the largest generator (150 MW), a maximum of 0.9 second delay can be introduced [28]. Hereafter, we consider D obtained in this way as the tolerable delay of the power grid model of interest. We also need to consider the mandatory latency to execute command authentication. This is largely determined by the specific authentication logic implemented. For example, in the case of the command authentication using power system dynamics simulation, it is around 1 second in the case of the GSO 37-bus model on PowerWorld. We call this latency D, and the command delaying strategy should be decided based on the relationship between D and D. If D . D, we can expect the ideal outcome by delaying all commands by D. In this case, the command authentication results will always be notified during the artificial delay, and therefore, if flagged malicious, the corresponding commands can be blocked before execution. Unfortunately, this is not necessarily the case, as seen in our case study using the GSO 37-bus model. In such a case, a grid operator would need to explore other solutions. For instance, the grid operator could implement probabilistic commanddelaying where each command is delayed with a certain probability [28]. Alternatively, the operator could configure priority of commands to be delayed, based on type of resources controlled, etc. However, in either case, the outcome would not always be the optimal. Therefore, we next discuss the formulation of the problem to find the command-delaying strategy that can attain the optimal security gain [27]. For contingencies like generator faults, one of the typical recovery control strategies is load shedding to balance supply and demand. Typically, utility companies carefully simulate and prepare for all expected contingencies (e.g., N 2 1 contingencies). In some cases, a set of loads is selected based on proximity to the source of Table 16.2 Simulation experiment on delay tolerance on GSO 37-bus model. Name of generator

Generation (MW)

# of Loads to be shed

Max delay (s)

JO345 #1 JO345 #2 LAUF69 BLT138 BLT69 ROGER69

150 150 150 140 75.23 38

5 5 5 3 2 1

0.9 0.9 1.0 1.2 2.5 3.0

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contingency (e.g., a lost generator). Alternatively, a more advanced scheme, such as in Ref. [33], may be used to optimize the number of loads to be shed based on the type of the contingency, the cost of the load changes and the curtailment charges. Because the planning is done in advance, we here assume that all contingencies to be taken into account, Cj (where j 5 1,2,3. . .m), and the set of loads to be shed for each contingency (Lj) are given. We further denote the superset (union) of Ljs as Lall, and its cardinality as |Lall|. We also denote each load included in Lall as li (where i 5 1,2,3,. . .,| Lall|). The control variable ki (where i 5 1,2,3,. . .,|Lall|) represents the amount of artificial delay to be added to load shedding control commands targeting each load in Lall. ki 5 0 means control for the corresponding load is not delayed, while ki . 0 means that the corresponding load-shedding control are delayed by ki. We consider either 0 or D (minimal delay required to wait command authentication results) for ki since, when ki , D, the command authentication results would not be notified in time, which means there is no difference from the case when ki 5 0, while otherwise the decision is enforced before command execution. Because artificial command-delaying is to be applied in a distributed, autonomous manner without requiring coordination, the kis need to be pre-programmed on A CMD devices in the field (e.g., substation gateways or protocol translators). Therefore, our goal is to find the optimal set of ki s, denoted by K, and then to configure K on A CMD devices before deployment. Intuitively, the objective is to maximize the security gain by adding delay to the maximal number of influential loads. Influence of loads [called impact factor si (where i 5 1,2,3. . .,|Lall|)] can be determined based on the size and/or criticality of the load, which are assumed to be decided in advance and given as input. For example, we can utilize the size of the load as the impact factor of each load since cutting larger loads would be more impactful on grid stability. More precisely, the objective is formulated as maximization of the security score as follows: Security score 5

X

j 5 1. . .m

X

  i 5 1. . .Ljsiki

Note that, when we delay control commands for more loads with high impact factor (and thereby protect them from malicious commands), the score becomes larger. Our goal is to find K that can maximize the security score. In other words, when Z is defined as a m 3 |Lall| matrix where an element in jth row, which corresponds to jth contingency Cj, zij is set to be ki when the ith load in Lall is included in Lj and zij 5 0 otherwise. This is equivalent to the maximization of product ZS where S is a |Lall|-dimensional vector consisting of si. This maximization must be done under the power grid stability constraints. Evaluation of the power grid stability can be done through power system dynamics simulation. We should note that, exhaustive search of all possible combination of K is needed to find truly optimal solution, and the computational cost would become prohibitive when working on large-scale power grid system. To address challenge, efficient, heuristic algorithm to find near-optimal solution has been explored, and we refer the interested reader

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Figure 16.6 Finding optimal command-delaying strategy.

to Ref. [27]. The overall procedure for finding the optimal command-delaying strategy is summarized in Fig. 16.6.

16.4.3.2 Overall A CMD system architecture and deployment options When a remote control command is received by a A CMD-enabled gateway in each substation (1), artificial time delay is added so that the command is held pending for a certain duration (2). Simultaneously, the receipt of the command is reported back to the command authentication system in the control center, which then evaluates the consequence of the command by means of system dynamics simulation (3). The result is sent to the A CMD-enabled gateway (4), and only when the command is not flagged as suspicious, then the command is sent to the destination IED in the substation LAN for execution (5). If the command is flagged as suspicious, the pending command is canceled before execution and is never seen by the IED. Alternatively, in order to avoid the risk of false positive (i.e., a legitimate command is flagged by mistake), A CMD could be configured to just log and report the event while letting the command through without blocking. Such a configuration is often preferred since availability of the communication is often of the highest importance for power grid operators. Note that, while the command authentication system is implemented at the control center, it should be securely isolated from the SCADA master to counter the cases where the SCADA master is compromised [4,6,7], or is manipulated by malicious insiders. Our recommendation is to deploy the command authentication

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Figure 16.7 Overall A CMD system architecture with centralized command authentication server equipped with power system dynamics simulator.

system on a physically isolated device, which is connected via the router or switch to the same LAN as the SCADA master through a trunk port. This way, besides receiving command information from distributed A CMD systems, the authentication system can passively overhear all SCADA communication including interrogation request and response to obtain real-time power grid status. Therefore the system can keep its power grid model for simulation up-to-date. Given the possibility of an attacker on the SCADA master, the command authentication module must collect information independently, instead of relying on the SCADA master. Another advantage of such a deployment is that the command authentication system is not on the critical SCADA communication path, and therefore it does not interfere with normal operation or lower overall system availability or throughput. The overall architecture is shown in Fig. 16.7. Regarding the practical implementation of A CMD-enabled substation gateway, we can consider two options: all-in-one type implementation and a bump-in-thewire approach. In the following text, we elaborate these options. Based on our observation [28], both deployment options offer satisfactory throughput and stability even when implemented on a low-cost, embedded platform.

16.4.3.3 Deployment option 1: All-in-one substation gateway In a real-world deployment, the role of a gateway in the reference model [29] is often implemented as a protocol translator (or protocol gateway) [34], and there are a number of commercial products in the market, such as in Ref. [35] that perform translation of protocols that are used in the smart grid context, including IEC 60870-5-104, IEC 61850, and DNP3. Therefore, one straightforward deployment option is to implement the A CMD module and other gateway functionality on a single box and replace an existing substation gateway or protocol translator device with it.

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An advantage of this approach is that no extra hardware is needed, and therefore degradation of reliability and availability of the entire infrastructure is minimal. On the other hand, one drawback is that this option requires implementation of equivalent features available on the existing gateway device or protocol translator to be replaced, which is often non-trivial without sufficient technical supports from device vendors. It is also possible to implement A CMD on the existing protocol translator (or RTUs) if the platform is extensible. In this case, A CMD could be introduced simply by updating firmware of such devices, which is highly beneficial for large-scale roll out. However, the implementation must be entirely device specific, which may require significant customization efforts especially if we need to support multiple models. In addition, protocol translators and RTUs are usually resourceconstrained, and therefore we may face extra technical challenges when porting the A CMD system to those devices.

16.4.3.4 Deployment option 2: Bump-in-the-wire approach There may be a situation where the all-in-one option is not desirable. For instance, as mentioned earlier, there may be a case where implementing equivalent features on the new gateway device is not feasible. In addition, depending on system configuration, there may be a situation where no protocol translation gateway is needed but additional security for just a single RTU is demanded. To meet such demands, another deployment option is to deploy the A CMD module as an add-on system component without requiring modification of an existing gateway or RTU. Furthermore, this option allows us to take advantage of the functionality of the existing gateway device or RTU for handling and interacting with IEDs or physical power system devices in a substation. Specifically, we can deploy the A CMD system as a separate box in “bump-inthe-wire” manner. Compared to the all-in-one option, this approach might suffer extra latency caused by communication between the A CMD box and the existing gateway/RTU. Another potential drawback is that adding an extra component into the communication path may increase failure rate of the system, which however can be addressed by redundancy. On the other hand, this option has a significant advantage in terms of broad applicability and feasibility of integration. Namely, this option does not require hardware/firmware customization on existing devices and can support any standard-compliant devices from various vendors. The resulting architecture is shown in Fig. 16.8B. Note that “Bump-in-the-wire A CMD” and “Existing RTU or GW” together offer the equivalent functionality to “All-in-one A CMD” in Fig. 16.8A. In addition, incoming and outgoing messages on “Bump-in-the-wire A CMD” are using the same protocol, and thus maintains compatibility with existing devices.

16.5

Summary

In this chapter, we have studied real-world cyber-security incidents targeting smart power grid infrastructure as well as state-of-the-art cyber-security solutions to

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Figure 16.8 Practical A CMD deployment options. (A) All-in-one option. (B) Bump-in-thewire option.

defend our critical infrastructure against them. However, they are not fully effective when trusted system components, such as a SCADA master workstation in a control center, are compromised, and thus an additional line of defense that complements existing solutions has been demanded. In this direction, we discussed design and practical integration of a SCADA command authentication system, named A CMD, that is deployed at field substations in a distributed manner to validate the legitimacy of incoming remote control commands. This way, A CMD is expected to effectively counter attacks even from the trusted devices in the upstream including the control center, such as the notorious Ukraine power plant attack [4], as well as emerging insider threats [36]. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

16.6

Chapter review questions/exercises

16.6.1 True/false 1. True or false? Traditionally, a smart grid system (and other types of industrial control systems) was considered secure, largely because of the “airgap” between the system and the rest of the world, including the Internet and the enterprise IT system of the corresponding company. 2. True or false? It is also possible that cyber-originated attacks cause physical destruction of crucial power grid components. 3. True or false? In order to ensure interoperability among multivendor devices or systems in substation, standardized technology has not emerged. 4. True or false? Packets injected from an unauthorized source can be blocked by a firewall or flagged by intrusion detection systems.

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5. True or false? The command authentication module that is deployed at each substation runs power flow simulation based on local power grid measurements as well as information collected from nearby substations to evaluate the legitimacy of outgoing remote control commands.

16.6.2 Multiple choice 1. The command authentication module, which is assumed to be centrally deployed (e.g., in the control center), is invoked whenever remote control commands (cmdnew) are reported by: a. Power systems b. Latest systems c. Dynamics simulation systems d. Command authentication systems e. Field systems 2. In order to block malicious control commands before they are executed on the physical power grid system, it is necessary to put incoming remote control commands on hold until the __________________ is done. a. Command authentication b. Malicious control authentication c. Protocol translation d. Substation gateway e. All of the above 3. Because, in general, delay or latency is not considered a positive thing in industrial control systems, in particular power grid systems, the configuration of _______________ requires careful design consideration. a. Fault isolation b. Relay protection c. Short latency d. Substation remote control e. Artificial command-delaying 4. When a remote control command is received by a ________________ in each substation (1), artificial time delay is added so that the command is held pending for a certain duration (2). a. A CMD-enabled gateway b. B CMD-enabled gateway c. C CMD-enabled gateway d. D CMD-enabled gateway e. All of the above 5. In a real-world deployment, the role of a gateway in the reference model is often implemented as a protocol translator (or protocol gateway), and there are a number of commercial products in the market, that perform translation of protocols that are used in the smart grid context, including: a. IEC 62880-6-105 b. IEC 60870-5-104 c. IEC 61850 d. DNP3 e. EOQ4

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16.6.3 Exercise 16.6.3.1 Problem Discuss the latest information on smart grid security.

16.6.4 Hands-on projects 16.6.4.1 Project Do research: What are the main goals for smart grid security?

16.6.5 Case projects 16.6.5.1 Problem Create security profiles for smart grid components.

16.6.6 Optional team case project 16.6.6.1 Problem Prepare a detailed survey of cyber-security issues for the smart grid.

References [1] Y. Zhao, Z.-J. Shen, Application of TCP/IP based IEC60870-5-104 telecontrol protocol in power system, Power Syst. Technol. 10 (2003). [2] R.E. Mackiewicz, Overview of IEC 61850 and benefits, in: 2006 IEEE Power Engineering Society General Meeting, IEEE, 2006. [3] R. Langner, Stuxnet: dissecting a cyberwarfare weapon, IEEE Secur. Priv. 9 (3) (2011) 49 51. [4] K. Zetter, Inside the cunning, unprecedented hack of Ukraine’s power grid, Wired, 2016. [5] M.J. Assante, M.L. Robert, The industrial control system cyber kill chain, THE SANS Institute Reading Room site. ,https://www.sans.org/reading-room/whitepapers/ICS/ industrial-control-system-cyber-kill-chain-36297. (2015). [6] Defense Use Case, Analysis of the cyber attack on the Ukrainian power grid, Electricity Information Sharing and Analysis Center (E-ISAC), 2016. [7] A. Greenberg, Crash override: the malware that took down a power grid, Wired Magazine. ,http://bit.ly/2raojOf., 2017 (accessed 20.09.17). [8] R. Smith, Russian hackers reach US utility control rooms, homeland security officials say, Wall Str. J. 23 (2018). [9] S. Datta, North Koreans behind Indian nuclear plant hack. Asia Times, 2019. [10] J. Weiss, Aurora generator test, Handbook of SCADA/Control Systems Security, CRC Press, 2016, pp. 107 114.

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[11] F. Cleveland, IEC TC57 security standards for the power system’s information infrastructure beyond simple encryption, in: Transmission and Distribution Conference and Exhibition, 2005, vol. 2006. [12] F. Hohlbaum, M. Braendle, F. Alvarez, Cyber security practical considerations for implementing IEC 62351, in: PAC World Conference, 2010. [13] H. Lin, et al. Adapting Bro into SCADA: building a specification-based intrusion detection system for the dnp3 protocol, in: Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop, ACM, 2013. [14] V. Paxson, S. Campbell, J. Lee, Bro intrusion detection system. No. Bro; 001905IBMPC00, Lawrence Berkeley National Laboratory, 2006. [15] R. Udd, et al. Exploiting Bro for intrusion detection in a SCADA system, in: Proceedings of the Second ACM International Workshop on Cyber-Physical System Security, ACM, 2016. [16] W. Ren, T. Yardley, K. Nahrstedt, EDMAND: edge-based multi-level anomaly detection for SCADA networks, in: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), IEEE, 2018. [17] B.J. Kang, K. McLaughlin, High-level design documentation and deployment architecture, Eur. Workshop Syst. Secur 1 (2014). [18] C. Jaggi, Layer 2 encryptors for metro and carrier ethernet WANs and MANs, 2017. [19] Ertem Esiner et al., F-Pro: a fast and flexible provenance-aware message authentication scheme for smart grid, in: 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), IEEE, 2019. [20] H.C. Tan, et al., Tabulating cybersecurity solutions for substations: towards pragmatic design and planning, in: 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), IEEE, 2019. [21] S. Meliopoulos, et al., Command authentication via faster than real time simulation, in: 2016 IEEE Power and Energy Society General Meeting (PESGM), IEEE, 2016. [22] H. Lin, Z. Kalbarczyk, R.K. Iyer, RAINCOAT: randomization of network communication in power grid cyber infrastructure to mislead attackers. IEEE Trans. Smart Grid 10 (2018). [23] L.L. Grigsby, Electric Power Generation, Transmission, and Distribution, CRC Press, 2007. [24] J.D. Glover, M.S. Sarma, T.J. Overbye, Power System Analysis and Design, Thomson Learning, Wadsworth, 2002. [25] PowerWorld. ,https://www.powerworld.com.. [26] D. Mashima, et al., Securing substations through command authentication using on-thefly simulation of power system dynamics, in: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), IEEE, 2018. [27] D. Mashima, et al., On optimization of command-delaying for advanced command authentication in smart grid systems, in: 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), IEEE, 2019. [28] D. Mashima, P. Gunathilaka, B. Chen, Artificial command delaying for secure substation remote control: design and implementation, IEEE Trans. Smart Grid 10 (1) (2017) 471 482. [29] IEC TC57, IEC 61850: communication networks and systems for power utility automation, Int. Electrotechnical Comm. Std 53 (2010) 54.

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[30] IEEE, IEEE standard communication delivery time performance requirements for electric power substation automation, IEEE Std. (2005) 1 24. [31] M. Kuzlu, M. Pipattanasomporn, S. Rahman, Communication network requirements for major smart grid applications in HAN, NAN and WAN, Computer Netw. 67 (2014) 74 88. [32] nationalgridESO. Frequency response services. ,https://www.nationalgrideso.com/balancing-services/frequency-response-services.. [33] X. Lou, et al., Profit-optimal and stability-aware load curtailment in smart grids, IEEE Trans. Smart Grid 4 (3) (2013) 1411 1420. [34] P. Gopalakrishnan, J. Thomas, F. Ka, Introducing Protocol Converter in a Sub-Station Communication Environment for IEC 61850 Compatibility, Kalka Communication Technologies Private Limited, India, 2008. [35] ABB, Communication gateway. ,https://library.e.abb.com/public/9d37bb56b86d31afc 125746d004b534f/COM610_tob_755425_ENf.pdf.. [36] J. Griffiths, China can shut off the Philippines’ power grid at any time, leaked report warns. ,https://edition.cnn.com/2019/11/25/asia/philippines-china-power-grid-intl-hnk/ index.html..

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Baseem Khan1, Habtamu Getachew1 and Hassan Haes Alhelou2 1 Hawassa University, Awassa, Ethiopia, 2Tishreen University, Latakia, Syria

17.1

Introduction

The term smart grid is first utilized in the year of 2005, which represents the 21st century technique of the electricity generation, transmission, and distribution to the end users. The term “grid” represents the electricity network, which supplies the power to the end users. On the other hand the term “smart” represents the object that has an inbuilt operating system accompanied with advanced metering and computing capacities [1 5]. Therefore, an electricity grid, integrated with digital technologies, that provides the energy to the end users through two-way communication is called the smart grid. It initiates the incorporation of the different market-related processes and systems for calculating the actual measurable data throughout the energy supply network. This futuristic electricity system links all the generation, transmission, and demands components of the power system in an intelligent manner via a communication network. For improving the efficiency of the system, minimizing energy utilization and price, and maximizing the reliability and transparency in the electricity supply system, smart-grid system offers improved monitoring, control, and communication inside the network [6 8]. For enhancing the energy productivity and system reliability along with allowing customers to control their usage and costs via real-time monitoring, smart-grid technologies provide various solutions to the electric utilities. All the sectors of the electric power system such as generation, transmission, and distribution are greatly affected by the smart-grid technologies [9 12].

17.2

Components of smart grid

Basically, smart-grid components combine intelligent appliances, along with heavy equipment that are mainly associated with the electricity generation, as mentioned in the preceding. These intelligent appliances operate according to the predefined codes. These smart appliances are able to understand the input power supply and the way to use it [1,13 16]. The main components of smart grid include. G

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smart meter; smart substation; distributed generation; phasor measure units; integrated communications; and sensing and measurement.

17.2.1 Smart appliances To perform functions faster, cheaper and in a more energy efficient manner, smart appliances utilize recent computer and communication techniques. The advantage of an energy smart grid that is developed by the utilities nationwide can be taken by these appliances. Appliances such as refrigerators, washing machines, toasters, dishwashers, and electric vehicles can be tapped into the smart-grid generation sources after the implementation of the smart-grid technology [4,17 24]. A predefined preference level is set by these appliances for the consumers to provide an idea on when to utilize electricity and on what level. To understand energy generation status and minimize the peak demands factors, these smart appliances have a vital impact on the utility generations.

17.2.1.1 Energy use For optimizing the energy utilization at the opportune instants of the day, smart appliances can be accessed by the utility’s energy sources. For example, energy will only be provided to the washing machine in the night while for coffee maker in the morning. Several electricity markets are testing smart-grid technologies, even though these technologies have not yet been implemented in different parts of the world.

17.2.1.2 Communication: connectivity and home savings For regulating and optimizing the utilization of energy at the community level, smart appliances have the ability to communicate with other neighboring appliances; as well as, the nearby smart grid. Furthermore, an Internet connection is required to connect smart appliances to the smart grid. Thus, these appliances can be accessed and controlled by any Internet-connected computer and mobile devices. Finally, the data-processing software utilized in the smart-grid technology anticipated around 30% 50% minimization in the electricity utilization per smart appliances [25].

17.2.2 Electric vehicles An electric vehicle (EV) is a device that utilizes one or more electric or traction motors for the purpose of propulsion. There are various methods, which are utilized

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to energize EVs. Some of them are as follows: 1. 2. 3. 4.

collector system that supplies electricity from off-vehicle sources; self-contained battery system; solar panels; and an electric generator that converts fuel to electricity.

Different categories that include, but are not limited to EV technology, are as follows: road, rail, surface, underwater vessels, electric aircraft, and electric spacecraft [22].

17.2.2.1 Smart charging of electric vehicles Changes at the infrastructure level involve technical and communication devices to manage the charging process, particularly at the low voltage level. Smart charging essentially consists of controlling time and rate at which the car is charged according to signals from the grid operator, enabling the car to stop charging at peak times. It is crucial that Distribution System Operators’ Association (DSOs) have a communication and control system in place to manage the charging process. This enables the DSO to handle charging according to the grid constraints and customers’ needs. Another viable option is enabling vehicle-to-grid (V2G) charging. This technology can be an essential tool for smart EV charging, turning the car into a temporary storage system to supply power to the grid at peak demand and charging the vehicle when overall demand is reduced. Projects utilizing V2G technology are getting substantial financial incentives to take off, making V2G a point of interest for utilities [22]. This element ties into the need for interoperable ICT and data standards. According to the association, interoperability is critical for smart charging to be reliable and practical. Interoperable interfaces should coordinate data between the grid, the charging point, and the EV. In fact, interoperability between systems and networks is an essential feature for utilities, allowing them to better adapt to the changing patterns of energy generation and consumption. Another significant element that can contribute towards more efficient smart charging is the integration of distributed energy resources (DER). Smart charging can be a medium-term solution to optimize local DER integration—it can adjust the charging profiles to the supply from renewable energy generation. Incentivizing local DER optimization can help DSOs with grid congestion issues, and brings the option to reverse the energy flow and enable V2G and vehicle-to-home charging [23]. Fig. 17.1 presented the schematic diagram of charging station of EV to grid system. Fig. 17.2 presented the schematic diagram of charging station of EV to grid and home system.

17.2.3 Smart meters For developing a channel between the electricity providers and the end users, smart meter technology provides a two-way communication. A secure wireless network is

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Figure 17.1 Schematic diagram of charging station of EV to grid system.

Figure 17.2 Schematic diagram of charging station of EV to grid and home system.

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utilized to develop this communication system. It permitted the users and the electric utilities to communicate in the case of any service failure or any other hazard that may or may not happened [2,4,26 29]. Smart meter technology has numerous advantages such as it collects the billing data in very fast manner, sensed failures of the systems and informs maintenance team much faster than the manual system because whenever there is a failure, utilities are reported instantaneously. Further, these utilized data for collecting revenue, detects failures in the system and sends out repair teams to the exact location more rapidly; a close link, is then developed by the smart meters between the smart substation and distribution. The additional features, which make smart meters different from the conventional energy meters, are utilizing real-time sensors, notification of the power failures, and monitoring of the power quality. Time of usage pricing can be documented in the data and transmitted to the utility for permitting them to find out amount of energy consumption during the day and charge users accordingly. For providing the interfacing between users and utilities, smart home energy management system is usually utilized along with smart meters. Further, digitally operated smart meters permitted the automatic and complex transfers of information available between utilities and users. The data transfer between utility and users can be linked to the home energy management system that permits users to view their energy consumption in an easy way. Furthermore, the data transfer can be utilized by the users to follow their energy utilization in detail. Therefore, by observing the energy management system users and see the effect of different appliances on energy usage pattern. To observe real time data and pricing signals from utilities, the energy management system can be utilized by users to help them reduce energy utilization at peak demand. Further, some specific setting of the smart appliances turns off them without user intervention when a huge energy load threatens to create the failure. For managing and recording the energy utilization and performance of the appliances in the home, smart meters can be utilized. The capability of these meters of providing detailed and exact analytics on energy utilization in real time or predefined time instants without the requirement of technician makes them smart. The broad spectrum of collected data of energy utilization by smart meters with quick and accurate measurements eliminates the monthly estimated meter readings without home visits. Although smart meters are useful for managing smart grid in energy efficient and profitable manner there are some issues which are related to the data collected by the smart meters on real-time basis. This collected data of hourly electricity utilization may be some time contained unnecessary information. Further, this collection some time violates the user privacy also. There are various advantages and disadvantages of smart meters for both users; as well as, for electric utilities. Some of them are as follows: G

For users advantages: Large and detailed feedback regarding the electricity utilization Capability of adjusting habits of consumers to minimize energy bills Minimize the number of blackouts and system-wide energy outages Disadvantages: Extra investment for installing the smart meter Privacy concerns related to the collected personal data and its utilization Users face more responsibility of maintenance G

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For electric utilities advantages: Monthly manual meter readings eliminates Real time monitoring of the electric system Supports efficient utilization of the generated energy To balance demands while minimizing the blackouts by supplying responsive data Supports dynamic pricing Minimized the cost of capital investment for constructing generation facilities Supports for optimizing the revenue with the available resources Disadvantages: Extra investment cost to train employees, construct system and realize new procedures to store data Supervising response and feedbacks of users related to new meters Develop a long-term financial contracts related to the new system Guarantee the safety and privacy of the metered data G

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The disadvantages of the smart meters’ may seem for short term. These issues will be delayed the adoption rate of smart technologies in the rural and isolated areas.

17.2.3.1 Working principle of smart meters Smart meters are the next level instruments that are utilized for both the energy and gas markets. These meters replaced the conventional energy meters to record and track the energy consumption of the users and transmit that information to the utility for accurate energy billing. Smart meters utilized the secure communication network for automatically and wirelessly transmit exact energy utilization to the service provider. Smart meters utilized the two-way communication to transmit the recorded data. Smart meters are available with an in-home display screen. This display provides the user real time information of the energy utilized and its respective cost [7]. Smart meters generally display the following: G

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a budget market, battery status, time, text area, touch buttons, light indicators, costs and consumption, fuel view, energy display dial, and wireless signal strength.

17.2.4 Smart substation The electricity industry around the world is going to be digital. The traditional electricity grid utilized devices without any digital controllers. For example, the conventional relays are simple electro-mechanical elements without any communication interfaces, firmware, or multitasking. Supplying electricity is always a

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challenging issue but the integration of smart devices makes this task more complex. Around the world, utilities are trying to minimize the gap between analog and digital technologies. By embedding the digital technology the different components of the substation has been enhanced, enriched, and augmented to make them function better at higher ratings with enhanced reliability as compare to before. The main challenge is to integrate these entire components into a completely digital substation and making them to operate in a demanding scenario. The digitalization of the electrical substation is encouraged by various issues. In most of the industrialized nations, the utility grid is operated mainly at maximum capacity because the users required more energy with better quality. Thus, whenever fault occurred in the system, it must be cleared as fast as possible. This is one of the advantages provided by the recent digital technology. At the costumer’s side of meters, digital technology is integrated with the Internet of Things (IoT). IoT is the system of devices, buildings, vehicles, and various types of physical objects those are integrated with sensors, coupled by the networks and controlled and monitored through the computer-based systems [1].

17.2.5 Distributed generation The utilization of small-level energy production techniques at the consumer end, is called distributed generation. It has the capability to reduce costs, enhance reliability, and minimize emissions and expanding generation alternatives. Energy production is performed near to demand that minimizes the transmission line development cost, as well as, transmission losses, therefore, efficiency is improved. The basic concept utilized in all types of industries is related to the amount of supply and demand. This is the area in which the current electricity grid is struggled, because the instant energy produced, must be utilized at the same time instant. To deal with the any contingency at any instant in the system, it is important to have the correct supply availability. If the amount of energy produced did not meet the required load at peak demand instants, stability and reliability issues are raised in the system. Thus, for meeting the required load (without knowing when the peak load occurs), utilities bring the production resources, namely peal load plants for ensuring what the requisite load will meet. Peak load power plants are highly expensive and require more fuels for operating [12 15]. The sum of energy generated from utilities can be minimized with the help of distributed generation. These renewable distributed generation can be supplied the similar surplus amount of energy that peak plants supplied. Thus, it reduced the cost of utilities for meeting peak loads. As large range of different generation sources connected to the grid, reliability of the system is improved. These DGs can be eliminated the utilization of the peak load supplying plants that saves money and protect the environment. DG can be utilized various types of renewable energy generations such as solar, wind, biomass, etc.

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17.2.6 Phasor measurement unit The devices which measure the voltages and currents at predefined points in the utility grid and use the global positioning system (GPS) radio clock for synchronization is called Phasor measurement units (PMUs) or synchrophasors. PMU can be a sophisticated device, which is often integrated into other electric devices, such as protective relays. Synchrophasors are placed at different locations, that is, substations and are synchronized with the GPS clock so that synchrophasor can be utilized for permitting power flow till to a line’s dynamic limit rather than its worst case limit, which depends on the weather and load. The transmission line’s actual capability of carrying power at any time instant is provided by its dynamic rating while satisfying its design limits. This technology provides the novel way of controlling the power flow through the utility grid and enhancing security and the transmission congestion management during over loading condition [30]. Generally the alternating current waveform should be identical and sinusoidal throughout the grid. PMUs are associated in the grid for permitting information to be extracted related to a particular waveform in the grid. PMUs are generally termed as the “health meters” of the power system, as they are capable of gathering sample voltages and currents at various time instants; and, perform the function to minimize congestion, bottleneck of the electricity grid and minimize or completely remove the blackouts from the system.

17.2.7 Integrated communication system The basic element that is required to implement the smart grid is reliable and highspeed integrated communication system. It links various elements to an open architecture, which is utilized to collect real-time information, control, and exchange of data for optimizing the security and reliability of the system and utilizing of the assets. With the help of integrated communication system, collected data can be rapidly transmitted between different transmission substations from system control center. The design of the communication system must be such that so it is able to cope up with the present as well as future applications of the power system [6]. Integration communication system is said to be the element of the power system that joins various other technologies together. The different integrated communication technologies are fiber optics, wireless mesh networks, and supervisory control and data acquisition (SCADA) system. These communication technologies required to incorporate the two-way communication characteristic into the home application. This process incorporates the sending of data containing information from source to demand. Various protocols like Wi-Fi, ZigBee, Bluetooth, and infrared are the most utilized protocols. These are the technologies those are compatible to each other in the case of smart-grid system applications [6].

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17.2.8 Sensing and measurements For the management of the power system in the better way, the advanced sensing and measurement technologies collected the data and altered them. To evaluate and monitor the equipment health, prevent the energy theft and control the strategies support, these technologies are utilized. Further for removing the energy bill estimations, assessing the grid stability, and obstructing and supporting the frequent meter readings, these technologies are utilized. By supplying useful information related to the daily demands of users, they help users for enhancing their energy utilization. The emerging sensing and measurement technologies will also be promoted the electricity markets and use the energy in better way. This will help users and utility to save their capitals [30].

17.3

Summary

Smart grid is the electricity grid that utilized the digital and various advanced technologies for monitoring, control, and manage the transmission of power from all the generating sources to the varying demands of end users. The different components of the smart-grid system are the combination of various intelligent appliances and heavy equipments, which provide the vital role in the generation, transmission, and distribution along with the efficient utilization of the energy. This chapter discussed the various components of the power system such as smart appliances, smart meters, smart substations, distributed generations, integrated communication, and sensing and measurement components in detail. The smart components are operated in predefined levels and they have the capabilities to understand the flow of incoming power as well as its optimal control and utilization. Different smart-grid components are working in the coordinate way, which requires the capabilities of all the generators, utilities, end consumers, and electric market stakeholders for operating in different sections of power system as efficiently as possible to reduce the costs and environmental impacts while enhancing the reliability, security, resiliency, and stability of the system. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

17.4

Chapter review questions/exercises

17.4.1 True/false 1. True or false? Smart-grid components, combine intelligent appliances, along with heavy equipment, that are mainly associated with the electricity generation.

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2. True or false? To perform functions faster, cheaper, and in a more energy efficient manner, smart appliances utilize old computer and communication techniques. 3. True or false? For optimizing the energy utilization at the opportune instants of the day, smart appliances can be accessed by the utility’s energy sources. 4. True or false? For regulating and optimizing the utilization of energy at the government level, smart appliances have the ability to communicate with other neighboring appliances; as well as, the nearby smart grid. 5. True or false? An EV is a device that utilizes one or more electric or traction motors for the purpose of propulsion.

17.4.2 Multiple choice 1. Changes at the infrastructure level involve technical and communication devices to manage the charging process, particularly at the: a. Low voltage level b. High voltage level c. Medium voltage level d. Critical voltage level e. Normal voltage level 2. For developing a channel between the electricity providers and the end users, smart meter technology provides a: a. Three-way communication b. Two-way communication c. Four-way communication d. One-way communication e. All of the above 3. Smart meters are the next level instruments that are utilized for both the: a. Gas markets b. Oil markets c. Energy markets d. Wind markets e. Nuclear energy markets 4. The electricity industry around the world is going to be digital: a. Wireless b. Digital c. Mobil d. Smart e. All of the above 5. The utilization of small level energy production techniques at the consumer end, is called distributed generation: a. Distributed generation b. Expanded generation c. Contracted generation d. Utilized generation e. None of the above

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17.4.3 Exercise 17.4.3.1 Problem What are the communication components of a smart grid?

17.4.4 Hands-on projects 17.4.4.1 Project Do research: Design a smart-grid components project that requires classic power systems knowledge, that is combined with communication, computing, electrical and computer engineering, and control.

17.4.5 Case projects 17.4.5.1 Problem Provide a comprehensive case project overview of the state-of-the-art and related work for the theory, distribution, and use of a smart-grid architectural model.

17.4.6 Optional team case project 17.4.6.1 Problem What would an optional extended-detailed smart-grid distribution system model component include?

References [1] T. Molla, B. Khan, B. Moges, H.H. Alhelou, R. Zamani, P. Siano, Integrated optimization of smart home appliances with cost-effective energy management system, CSEE J. Power Energy Syst. 5 (2) (2019) 249 258. [2] Z. Zhao, W. Lee, Y. Shin, K. Song, An optimal power scheduling method for demand response in home energy management system, IEEE Trans. Smart Grid 4 (3) (2013). [3] Z. Dogaheh, M. Dogaheh, Optimizing the performance of smart grids in relation with residential energy centers equipping with solar power units (PV), Sindhologic. Stud. 1 (2017) 14 22. [4] S. Mohammadi, M. Momtazpour and E. Sanaei, Optimization-based home energy management in the presence of solar energy and storage, in: 21st Iranian Conference on Electrical Engineering (ICEE), Mashhad, 2013, pp. 1 6. [5] F.A. Qayyum, M. Naeem, A.S. Khwaja, A. Anpalagan, L. Guan, B. Venkatesh, Appliance scheduling optimization in smart home networks, Special section on Smart Grids, IEEE, October 29, 2015.

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[6] M. Kuzlu, M. Pipattanasomporn, S. Rahman, Communication network requirements for major smart grid applications in HAN, NAN and WAN, Comput. Netw. 67 (2014) 74 88. [7] B. Khan, H.H. Alhelou, F. Mebrahtu, A holistic analysis of distribution system reliability assessment methods with conventional and renewable energy sources, AIMS Energy 7 (4) (2019) 413 429. [8] M. Arikiez, F. Grasso, M. Zito, Heuristics for the cost-effective management of a temperature controlled environment, in: Conference on IEEE Innovative Smart Grid Technologies-Asia (ISGT ASIA), Bangkok, 2015, pp. 1 6. [9] F.Y. Melhem, O. Grunder, Z. Hammoudan, N. Moubayed, Optimal residential load scheduling model in smart grid environment, in: EEEIC/I&CPS Europe 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Milan, 2017, pp. 1 6. [10] Pawan Singh, Baseem Khan, Smart microgrid energy management using a novel artificial shark optimization, Complexity 2017 (2017). Article ID 2158926, 22 pp. [11] F. De Angelis, M. Boaro, D. Fuselli, S. Squartini, F. Piazza, Q. Wei, Optimal home energy management under dynamic electrical and thermal constraints, IEEE Trans. Ind. Inf. 9 (3) (August 2013) 1518 1527. [12] L. Yao, Z. Damiran, W.H. Lim, Energy management optimization scheme for smart home considering different types of appliances, in: EEEIC/I&CPS Europe 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), Milan, 2017. [13] Seung-Jun Kim, G.B. Giannakis, Efficient and scalable demand response for the smart power grid, in: 4th IEEE International Workshop on Computational Advances in MultiSensor Adaptive Processing, San Juan, 2011, pp. 109 112. [14] M. Arora, S. Chanana, Residential Demand response from PV panel and energy storage device, in: IEEE 6th India International Conference on Power Electronics (IICPE), Kurukshetra, 2014, pp. 1 6. [15] K. Paridari, A. Parisio, H. Sandberg, K.H. Johansson, Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries, in: IEEE International Conference on Automation Science And Engineering (CASE) Taipei, Taiwan, August 18 22, 2014. [16] K. Paridari, A. Parisio, H. Sandberg, K.H. Johansson, Robust scheduling of smart appliances in active apartments with user behavior uncertainty, in IEEE Transactions on Automation Science and Engineering, 13, 1, pp. 247 259, January 2016. [17] T. Molla, B. Khan, P. Singh, A comprehensive analysis of smart home energy management system optimization techniques, J. Autonomous Intell. 1 (1) (2018) 15 21. [18] M.H.K. Tushar, C. Assi, M. Maier, M.F. Uddin, Smart microgrids: optimal joint scheduling for electric vehicles and home appliances, IEEE Trans. Smart Grid 5 (1) (January 2014) 239 250. [19] H. Wang, K. Meng, Z.Y. Dong, Z. Xu, F. Luo, K.P. Wong, Efficient real-time residential energy management through MILP based rolling horizon optimization, in: IEEE Power and Energy Society General Meeting - Denver, CO, 2015, pp. 1 6. [20] A.D. Giorgio, L. Pimpinella, A. Quaresima, S. Curti, An event driven smart home controller enabling cost effective use of electric energy and automated demand side management, in: 19th Mediterranean Conference on Control and Automation, Corfu, Greece, June 20 23, 2011.

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[21] S. Shah, R. Khalid, A. Zafar, S.M. Hussain, H. Rahim, N. Javaid, An optimized priority enabled energy management system for smart homes, in: IEEE 31st International Conference on Advanced Information Networking Application (AINA), Taipei, 2017, pp. 1035 1041. [22] Z. Chen, R. Xiong, J. Cao, Particle swarm optimization-based optimal power management of plug-in hybrid electric vehicles considering uncertain driving conditions, Energy. 96 (2016) 197 208. [23] F.-L. Meng, X.-J. Zeng, An optimal real-time pricing for demand-side management: a Stackelberg game and genetic algorithm approach, in: International Joint Conference on Neural Networks (IJCNN) July 6 11, 2014, Beijing, China. [24] H. Li, A.T. Eseye, J. Zhang, D. Zheng, Optimal energy management for industrial microgrids with high-penetration renewable, Prot. Control Mod. Power Syst. 2 (2017) 12. [25] S. Rahim et al., Ant colony optimization based energy management controller for smart grid, in: IEEE 30th International Conference on Advanced Information on Networking Application (AINA), Crans-Montana, 2016, pp. 1154 1159. [26] B. Ruan, Q. Yang, X. Fang, W. Yan, Demand response under real-time pricing for domestic energy system with DGs, in: International Conference on Power System Technology 2014, (POWERCON 2014), Chengdu, 20 22 October. [27] A.K. Shukla, K. Sudhakar, P. Baredar, Design, simulation and economic analysis of standalone roof top solar PV system in India, Sol. Energy, 136 (2016) 437 449. [28] A.R. Abul’Wafa, Energy storage sizing for rooftop grid-connected PV system, Electr. Power Compon. Syst. 45 (3) (2017) 331 343. [29] C. Dan, The home owner’s guide to renewable energy, Achieving Energy Independence Through Solar Wind, Biomass and Hydropower, New Society Publishers, Gabriola Island, Canada, 2006. [30] K. Negash, B. Khan, E. Yohannes, Artificial intelligence versus conventional mathematical techniques: a review for optimal placement of Phasor measurement units, J. Technol. Econ. Smart Grids Sustain. Energy 1 (2016) 10.

Introduction to energy management in smart grids

18

Essam E. Khalil Faculty of Engineering, Cairo University, Cairo, Egypt

18.1

Introduction

Wind and solar become mainstream energy providers’ technologies and with forecasting even more rapid adoption, one of the major hurdles facing cities would be the necessity to overcome the problem of deficient energy storage capacity. This implies that output fluctuations from wind or solar energy sources increase the complexity of proper utilization reliably. The concept of “energy storage” in this context can be defined as “the act of keeping and storing an amount of the energy that was generated to the moment of use, either as a final energy or converted into another form of energy,” which simply means saving electricity for later use. The dominant energy storage technology today is the lithium-ion battery, mainly due to its energy density and minimal discharge rate. These batteries are used typically for short-term storage, and can be traditionally found in electric vehicles and on power grids. However, if energy storage capacities become scalable up, it would become much easier to balance power fluctuations and mitigate peaks in grid demand. Recently known flow batteries, have emerged on the market as a solution for largerscale, long-term energy storage. These batteries are expected to revolutionize the energy storage market. They have a longer life span of 20 years and large storage capacities. Unfortunately, large-scale energy storage solutions, including modern batteries, are still in their infant primarily stages, which mean that these technologies are still very expensive and unviable. Cheaper energy storage would also open up a number of other opportunities in smart cities’ transition to a carbon-free future, the most important one perhaps being transportation. For energy storage solutions in smart cities, another vital energy system includes application of smart grids, Internet of Things (IoT)-enabled smart grids that are derived by demand-response systems. In addition to reducing peak load and the need for larger grid infrastructure, smart grids—in combination with smart meters—allow energy derived from solar and wind sources to be optimized. Along the same lines microgrids had emerged as a concept that gained a lot of support from eco-conscious homeowners, that is a localized power grid that can operate independently or in conjunction with the main electrical grid. The microgrids concept is based on the idea to break the hegemony of a centralized energy system, and make distributed energy resources infrastructure more resilient and reliable. Essentially, microgrids put the Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00018-8 © 2021 Elsevier Inc. All rights reserved.

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power back in the hands of the prosumers, so that these can be used as well as to distribute and profit more from the energy generated amongst the prosumers. Reliability and resilience are becoming increasingly prominent determinants of newer energy models. Cities can play an important role in the transition to a carbon-free sustainable world. National governments are expected to attempt to ultimately enable the delivery of carbon-free initiatives and provide them the support necessary to efficiently use the available financial, natural, and human resources. Governments would endeavor to streamline their core services using IoT and indicate that sustainability is at the top of their agenda will not only attract more people, businesses, and to gain competitive advantage over other economies. In smart grid, energy management is considered as a vital part to improve the renewable energy consumption and energy efficiency. The load fluctuations and output wind power fluctuations can be overcome through jointly dispatch the energy resources and demand-side resources. A smart grid is an electric operated network that can integrate the variations, behavior, and reactions of different users connected to the grid. This includes generators, consumers to ensure economically efficient, sustainable power system with lower losses and higher quality levels and secure supply. Smart-grid technology is applied as smart-grid devices that transmit information to enable common users, operators, and automated devices to promptly respond to changes in smart-grid condition systems. Smart grids are consequentially equally advantageous for enterprises, retail stores, hospitals, universities, and multinational corporations. The entire smart-grid system is automated for monitoring and controlling the electricity consumption at all the locations. Electricity tariffs would increase along with demand. A modern smart-grid system has the following capabilities: 1. 2. 3. 4. 5.

It can self-heal itself. Encourages consumer involvement in grid operations Provision of high-quality power supply with minimum power leakage Growing electricity markets and business Improved operation efficiency

A smart grid’s key features include, but are not limited to: G

G

G

Load management: As the total loads on the power grid load are normally varying with time, a smart grid can handle that variation as in case of heavy load, consumers are advised to temporarily minimize their connected consumption. Demand-response support: When rates are low, the users are provided through an automated way on how to reduce their electricity bills through the utilization of low-priority electronic devices. Decentralized power generation: Individual users are allowed to use renewable sources of energy at their discretion through the application of distributed or decentralized grid systems.

Research endeavors are made in order to enhance the energy efficiency of home appliances in terms of energy usage. Various techniques to control the power demand and supply were devised. This chapter contains some of the relevant reviews on a wide range of energy management techniques adapted for smart homes with the goal of increasing the efficiency and reducing wasted energy.

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18.2

401

Elements of the smart grid

Asset Management Systems would help to optimize the operational expenses and capital expenses spending of utilities. Condition-based maintenance, for example, would allow the reduction of maintenance costs without sacrificing its reliability. Additional benefits would be the full utilization of transport capacity due to a better cooling of primary equipment. Therefore with the preceding in mind, the following are smart-grid elements: G

G

G

G

G

G

G

Building Automation and Control System are important devices that monitor, control, and operate complicated energy consuming systems such as HVAC. . . and other building systems, generation plants, and other equipment amenable to automation. Decision Support and Integrity Protections are provided to better protect the primary equipment (e.g., boilers, generators, and transformers) from fatal fault currents, and power systems from instabilities and blackouts. However, System Integrity Protection Schemes would endeavor to better enhance the performance of protection devices, and to guard primary equipment (e.g., transformers) from fatal fault currents. In this way it is used to avoid uncontrollable chain reactions that may be initiated by protective actions. Distribution Automation and Protection: The current automated operation and remote control are state of the art for the transmission grid on the other hand; mass deployment of distribution automation has just started in recent years. Such concept is particularly useful in countries where overhead lines are commonly used. Advanced distribution automation concepts promote automatic self-configuration features, thus reducing the expected outage times to a bare minimum identified as “self-healing grids.” Distributed energy resources would be able to create self-contained cells “MicroGrids,” which in turn help to assure energy supply in distribution grids even when the transmission grid has a blackout. Distribution Management System (DMS): This concept is the counterpart to the Energy Management System (EMS) and is therefore the control center for the distribution grid. In countries where outages are a repeated problem, the Outage Management System would act as an important component of the DMS. EMS is known as the control center for the Transmission Grid. Today customers require an open architecture that enables an easy IT integration and a better support to avoid blackouts problems such as offering visualization of the grid status and, dynamic network stability analyses. Information and Communication Technology throughout the Smart Grid with the increased use of IT technologies would naturally allow better improvement of the interaction and integration of formerly separated systems. Buildings should respond to users’ requests and not vice versa. The ability of the utilities would increase to identify and rectify systems’ problems leading to more energy savings and reduced costs. Smart Generation would utilize power electronics to monitor and control harmonics, faults, and expected fluctuating generation from renewables. It helps to enhance the flexibility of conventional fossil fuel power plants to interact with the renewable intermittent power generation.

18.3

Energy management

Energy management includes planning and operation of energy production through power plants and energy consumption units. Objectives are the conservation and rationalization of resources, climate protection, and cost savings, while maintain permanent access of users to the needed energy levels.

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18.3.1 Base line of energy assessment One of the initial steps for an effective energy cost control program is the base line energy assessment that examines the pattern of existing energy use by governmental authorities or any subentity of the government or private organization. This program sets the reference base level for improvements in energy efficiency endeavors. Energy efficiency programs can improve the existing energy use and benchmarking of every individual section such as area, subarea and the industry, etc.

18.3.2 Organizational integration Energy management should be integrated in the organizational structure, so that its features can be implemented. Responsibilities and the interactions of the decision makers should be regulated. The responsible functions delegation and competencies would be extended from the top management to the executive worker. Furthermore, a comprehensive coordination can necessarily ensure the fulfillment of the tasks. It would be advisable to establish a separate organizational unit for energy management in large or energy-intensive companies. Such unit is aimed to support the senior management and to keep track of the activities. It depends on the basic form of the organizational structure, where this unit is connected. In a divisional organization, there should be a central and several sector-specific energy management units. So the diverse needs of the individual sectors and the coordination between the branches and the head office can be better fulfilled. In a matrix organization the energy management unit should be included as a matrix function to approach most functions directly [1].

18.4

Energy management in operational functions

This section describes the facility management in smart cities and identifies the Passive House and its definitions. Facility management is an important part of energy management. Facility management can be broadly defined as “a profession that encompasses multiple disciplines to ensure functionality of the built environment by integrating people, place, processes, and technology.” The central task of energy management is to reduce costs for the provision of energy in buildings and facilities without compromising work processes. Especially the availability and service life of the equipment and the ease of use should remain the same [2]. In this topic, the facility manager has to deal with economic, ecological, risk-based, and quality-based targets. This manager should also try to minimize the total cost of the energy-related processes (supply, distribution, and use) [3]. The Passive House utilizes a combination of low-energy building techniques and technologies to reduce carbon footprint. The most important key feature figure in this context is kilowatt-hours per square meter per year (kWh/m2 a). Based on this key figure, properties can be classified according to their energy consumption:

Introduction to energy management in smart grids G

G

403

In Europe: A low-energy house can have a maximum energy consumption of 70 kWh/m2 a as per the energy performance of buildings directive agency (EPBDA). In North America: Particularly in the United States, the ENERGY STAR program is the largest program defining low-energy homes. Homes earning ENERGY STAR certification use at least 15% less energy than standard new homes built to the International Residential Code, although homes typically achieve 20% 30% savings [4].

In comparison, the Passive House (Passivhaus in German) ultralow-energy standard, currently undergoing adoption in some other European countries, has a maximum space heating requirement of 15 kWh/m2 a. A Passive House is designed to be a very well-insulated and virtually air-tight building with no conventional heating system requirements. It is heated by solar gain and internal gains from people. Energy losses are minimized [5]. Another category of buildings would eventually produce more energy (e.g., by solar water heating or photovoltaic systems) over the course of a year than it imports from external sources (the grid). These buildings are called energy-plushouses [6]. Additionally, net zero energy houses become widely spread and countries are endeavoring to design energy producing buildings that can put back electricity into the national grid as a group of buildings or community. These take into account the diverse use and occupancy of buildings and their mixed use. Regulation would help to avoid the risked liability [7].

18.5

Energy management challenges

Through the energy efficient use and management of systems, the application in industrial companies and environment, would require more efforts to harness the renewable energy sources for the industrial user worldwide [8 16]. Therefore in order to achieve the energy management goal for the governments or industry, the efficiency of water and energy resources, play a vital role and should be preserved (see checklist: “An Agenda for Action for Energy Management Savings and Rationalization Best Practices”). An Agenda for Action for Energy Management Savings and Rationalization Best Practices. Examples of possible energy saving and rationalization, can be arrived at with the help of following proper maintenance key activities (check all tasks completed): _____1. Refrigerators defrosting. _____2. Check the pressures in cars and trucks. _____3. Adding proper thermal insulation in energy systems. (Continued)

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(cont’d) _____4. Proper sealing of buildings to prevent any leaks in building envelopes or at least minimize it. _____5. Reorientation of buildings to reduce cooling/heating requirements.

18.5.1 Energy strategies It is recommended that every company should have a dynamically changing, sound long-term energy strategy as part of the overall strategy (see checklist: “An Agenda for Action for Potential Energy Strategies Best Practices”). This strategy should be based on gradual application of renewable energies. Furthermore, criteria for decisions on energy investments, such as yield expectations, are determined [17], through sound formulation of an energy strategy; stakeholders; companies that have the opportunity to avoid risks; and, to assure a competitive advance against their business rivals [18]. An Agenda for Action for Potential Energy Strategies Best Practices In reality, one usually finds hybrid combinations of different energy strategies. According to the work of Kales [11,17], see the following energy strategies key activities (check all tasks completed): _____1. Passive strategy: Meaning no strategy to follow, such as the issue of energy and environmental management, is not perceived by the company as an independent field of action. The organization is blindfolded to such issue. _____2. Strategy of short-term profit maximization: The management is concentrating exclusively on measures that have a relatively short payback period and a high return. Measures with low profitability are not considered. _____3. Strategy of long-term profit maximization: such solution implies that the company has a high knowledge and awareness of the energy price and technology development. The relevant measures (e.g., heat exchangers or power stations) can have durations of several decades. Moreover, these measures can help to improve the image and increase the motivation of the employees. _____4. Realization of all financially attractive energy measures: This strategy has the goal and desire to implement all measures that have a positive return on investment. _____5. Maximum strategy: For the climate protection, the company is willing to change even the object of the company.

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18.5.2 Energy strategies of companies Many industries and stakeholders are endeavoring to promote its image and time protecting the climate through a proactive and public energy strategy [19 21]. For example, a company such as General Motors has a strategy that is based on continuous improvement. Furthermore, they have six major principles: 1. 2. 3. 4. 5. 6.

Restoring the environment Preserving the environment Reducing waste Reducing the environmental pollutants Educating the public about environmental conservation Collaboration for the development of environmental laws and regulations

Other countries had created their own strategy such as Nokia that tries to evaluate the energy consumption and greenhouse gas emissions of products and operations and devises emission reduction targets accordingly [21]. Furthermore, their environmental efforts are based on four key issues: substance management, energy efficiency, recycling, and promoting environmental sustainability [21]. The energy strategy of auto manufacturers Volkswagen is based on environmentally friendly products and a resource-efficient production according to the “Group Strategy 2018” [22]. Almost all locations of the Group are certified to the international standard ISO 14001 for environmental management systems [23]. Looking at the energy strategies of different companies it is important to witness the desire and actions for topical green washing in mind, may be clearly illustrated in a form of propaganda for green strategies used to promote the opinion that an organization’s aims are environmentally friendly [24].

18.5.3 Political energy strategies Countries formulate their energy strategy to reflect their needs and expectations for the future. The Swiss Federal Council decided to refrain from using the nuclear energy option. Most nuclear power plants will be shut down at the end of life and will not be replaced. To combat this decision, the focus was directed to energy efficiency, renewable energies, fossil energy sources and the development of water power [25]. The European Union has clear instructions for its members: The “20-20-20-targets” include: That the Member States have to reduce greenhouse gas emissions by 20% below 1990 levels; increase energy efficiency by 20%; and, achieve a 20% share of renewable energy in total energy consumption by 2020 [26].

18.5.4 Ethical and normative basis of the energy strategies The basis of every energy strategy is the corporate culture and the related ethical standards being applied in the company [27]. Ethics, in the sense of business ethics, examines ethical principles and moral or ethical issues that arise in a business

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environment. Ethical standards can appear in company guidelines, energy and environmental policies, or other documents. The most relevant ethical ideas for the energy management are: G

G

G

Utilitarianism: This form of ethics has acts that are good or right, and whose consequences are optimal for the welfare of all those affected by the action (principle of maximum happiness). In terms of energy management, the existence of external costs should be considered. They do not directly affect those who profit from the economic activity but nonparticipants like future generations. This error in the market mechanism can be solved by the internalization of external costs [28]. Argumentation ethics: This fundamental ethical idea says that everyone who is affected by the decision must be involved in decision making. This is done in a fair dialog; the result is completely uncertain [29]. Deontological ethics: The deontological ethics assigns individuals and organizations certain obligations. A general example is the golden rule: “One should treat others as one would like others to treat oneself.” Therefore everyone should manage their duties and make an energy economic contribution [29].

18.6

Energy management standards

ISO 50001 Energy management systems: Requirements with guidance for use is a specification created by the International Organization for Standardization (ISO) for an energy management system. The standard specifies the requirements for establishing, implementing, maintaining and improving an energy management system, whose purpose is to enable an organization to follow a systematic approach in achieving continual improvement of energy performance, including energy efficiency, energy security, energy use, and consumption [1]. The standard aims to help organizations continually reduce their energy use, and therefore their energy costs and their greenhouse gas emissions. ISO 50001 was originally released by ISO in June 2011 and is suitable for any organization, whatever its size, sector, or geographical location. The second edition, ISO 50001:2018, was released in August of 2018. The system is modeled after the ISO 9001 Quality Management System and the ISO 14001 Environmental Management System (EMS). Eccleston describes the procedural details of the ISO Energy Management System (EnMS) and compares its procedures with those of the ISO 14001 EMS. A significant feature in ISO 50001 is the requirement to “improve the EnMS and the resulting energy performance” (clause 4.2.1 c). The other standards mentioned here (ISO 9001 and ISO 14001) both require improvement to the effectiveness of the Management System but not to the quality of the product/service (ISO 9001) or to environmental performance (ISO 14001). It is anticipated that by implementing ISO 9001 and 14001 together an organization would improve quality and environmental performance, but the standards do not currently specify this as a requirement.

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ISO 50001, therefore, has made a major leap forward in “raising the bar” for energy management by requiring an organization to demonstrate that they have improved their energy performance. There are no quantitative targets specified; an organization may choose its own, then it creates an action plan to reach the targets. With this structured approach, an organization is more likely to gain some tangible financial benefits.

18.7

Summary

Wind and solar become mainstream energy providers’ technologies and with forecasting even more rapid adoption, one of the major hurdles facing cities would be the necessity to overcome the problem of deficient energy storage capacity. this chapter summaries the main elements of smart grid, including, building automation, decision support and integrity protections, distribution automation and protection., distribution management system, energy management system ems, information, and communication and smart generation. This is followed by energy management and organizational integration. Energy management in operational functions included facility management and highlighted the various energy management challenges were discussed in terms of energy strategies and political issues. The chapter also briefly described the energy management standard published by ISO. Finally, let us move on to the real interactive part of this Chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

18.8

Chapter review questions/exercises

18.8.1 True/false 1. True or false? Asset management systems would help to optimize the operational expenses and capital expenses spending of buildings. 2. True or false? Energy management includes planning and operation of energy production through power plants and energy consumption units. 3. True or false? Many of the initial steps for an effective energy cost control program, is the base line energy assessment that examines the pattern of existing energy use by governmental authorities or any subentity of the government or private organization. 4. Energy management should be integrated in the organizational structure, so that its features can be implemented. 5. True or false? Facility management is an important part of energy management.

18.8.2 Multiple choice 1. Examples of possible energy saving and rationalization, can be arrived at with the help of proper maintenance such as:

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2.

3.

4.

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a. Refrigerators defrosting b. Check the pressures in cars and trucks c. Adding proper thermal Insulation in energy systems d. Adding proper thermal Insulation in energy systems e. All of the above Meaning no strategy to follow, such as the issue of energy and environmental management and is not perceived by the company as an independent field of action, is known as: a. Strategy of short-term profit maximization b. Strategy of long-term profit maximization c. Passive strategy d. Realization of all financially attractive energy measures e. All of the above Many industries and stakeholders are endeavoring to promote their image and time protecting the climate through a: a. Proactive energy strategy b. Energy consumption strategy c. Greenhouse energy strategy d. Public energy strategy e. Energy efficiency strategy What form of ethics has acts that are good or right; and, whose consequences are optimal for the welfare of all those affected by the action (principle of maximum happiness)? a. Argumentation ethics b. Deontological ethics c. Utilitarianism d. None of the above e. All of the above What standard specifies the requirements for establishing, implementing, maintaining, and improving an energy management system, whose purpose is to enable an organization to follow a systematic approach in achieving continual improvement of energy performance, including energy efficiency, energy security, energy use, and consumption? a. ISO 50011 b. ISO 50001 c. ISO 50221 d. ISO 53451 e. ISO 56231

18.8.3 Exercise 18.8.3.1 Problem What are the potential benefits and technical problems of smart grids?

18.8.4 Hands-on projects 18.8.4.1 Project Do research: What is the meaning of a smart grid, its significance and goals, and its development?

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18.8.5 Case projects 18.8.5.1 Problem Provide recommendations on how to use energy effectively, and how to manage energy production and consumption by using smart grids.

18.8.6 Optional team case project 18.8.6.1 Problem Develop a case study that shows the role of energy storage in the effective management of smart grid energy demand and supply.

References [1] VDI-Guideline VDI 4602, page 3, Beuth Verlag, Berlin, October 1, 2007. [2] GEFMA: Energiemanagement Grundlagen und Leistungsbild (PDF), 2016 (accessed 14.04.16). [3] Viewed 10 November 2012. Energy20.net. 2010-02-03. Archived from original on 2015-09-24. Retrieved 2013-12-31. [4] Features of ENERGY STAR qualified new homes. ,EnergyStar.gov., 2008 (accessed 07.03.08). [5] Retrieved 8 December 2012. Passiv.de. Retrieved 2013-12-31. [6] Retrieved 3 December 2012. Plusenergiehaus.de. Retrieved 2013-12-31. [7] J. Kales, Betriebliches Energiemanagement - Eine Einfu¨hrung, Kohlhammer, Stuttgart, 2010, pp. 75 77. ISBN 978-3-17-021133-9. [8] Retrieved 10 November 2012. Iml.fraunhofer.de. 2013-12-20. Archived from the original on 2014-01-01. Retrieved 2013-12-31. [9] C ¸ . Iris, J.S.L. Lam, A review of energy efficiency in ports: operational strategies, technologies and energy management systems, Renew. Sustain. Energy Rev. 112 (2019) 170 182. [10] T. Bekta¸s, J.F. Ehmke, H.N. Psaraftis, J. Puchinger, The role of operational research in green freight transportation, Eur. J. Operat. Res. 274 (3) (2019) 807 823. [11] J. Kales, Betriebliches Energiemanagement - Eine Einfu¨hrung, Kohlhammer, Stuttgart, 2010, , ISBN: 978-3-17-021133-9, pp. 103 105. [12] Retrieved 10 November 2012. Energieagentur.nrw.de. Retrieved 2013-12-31. [13] P. Kotler, G. Armstrong, L. Brown, S. Adam, Marketing, 7th Ed, Pearson Education Australia/Prentice Hall, 2006. [14] Retrieved 6 December 2012 (in German). Bmwi.de. 2012-04-24. Retrieved 2013-12-31. [15] British Standard Glossary of Terms, 1993, vol. 3811. [16] Abgerufen am 12 November 2012. Ps-consulting.de. 2013-11-21. Retrieved 2013-12-31. [17] J. Kales, K. Wu¨rtenberger, IT-unterstu¨tztes Energiemanagement, in: HMD - Praxis der Wirtschaftsinformatik HMD, Heft 285/2012, S. 73 81. [18] J. Kales, Betriebliches Energiemanagement - Eine Einfu¨hrung, Kohlhammer, Stuttgart, 2010, , ISBN: 978-3-17-021133-9, p. 181.

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[19] J. Kales, Betriebliches Energiemanagement - Eine Einfu¨hrung, Kohlhammer, Stuttgart, 2010, , ISBN: 978-3-17-021133-9, pp. 182 184. [20] Retrieved 21 December 2012. Gm.com. 2012-01-13. Retrieved 2013-12-31. [21] Global change country. Retrieved 22 December 2012. Nokia.com. Retrieved 2013-12-31. [22] Retrieved 22 December 2012. Volkswagenag.com. Archived from the original on 201401-01. Retrieved 2013-12-31. [23] Retrieved 22 December 2012. Archived November 14, 2012, at the Way back Machine. [24] Retrieved 16 January 2013. Greenwashingindex.com. Retrieved 2013-12-31. [25] Retrieved 14 December 2012. Bfe.admin.ch. 2013-12-12. Archived from the original on 2013-12-31. Retrieved 2013-12-31. [26] Retrieved 14 December 2012 (in German). Bmwi.de. 2012-07-04. Archived from the original on 2014-01-01. Retrieved 2013-12-31. [27] J. Kales, K. Wu¨rtenberger, IT-unterstu¨tztes Energiemanagement. in: HMD - Praxis der Wirtschaftsinformatik HMD, Heft 285/2012, p. 73. [28] J. Kales, Betriebliches Energiemanagement - Eine Einfu¨hrung, Kohlhammer, Stuttgart, 2010, , ISBN: 978-3-17-021133-9, p. 200. [29] J. Kales, Business ethics and corporate energy management, in: L. Karczewski, H. Kretek (Eds.), Odpowiedzialny biznes i konsumerysm wyzwaniem XXI Wieku (Responsible Business and Responsible Consumerism as a Challenge of the 21st Century), Polen, Raciborz, 2012, p. 6.

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Satyam Bheemarasetti and Ravi Prasad Patruni NeoSilica Technologies Pvt. Ltd. Cyber Towers, Hi-Tech City, Hyderabad, India

19.1

Introduction

The world’s population is moving from 7.8 billion in 2019 to 10 billion by 2050, and 68% of these 10 billion people are going to be living in cities. Of this urban growth, 90% of it is going to happen in Asia and Africa. As of 2019, United States and Canada lead urbanization with 82%, Latin America and Australia follow with 81%, and Europe has 74%. Asia has only 50% and Africa is at 43% [1]. As more people swarm to cities, city management (municipalities) is increasingly in a morass of failing and outdated infrastructure (energy, water, transport, and sanitation), and the numerous dated information technologies (IT) and network systems in different organizations (utilities—public and private) that do not talk to each other. Based on evolution, this stage is also known as predigital era. As new enterprise system are highly focused toward fulfilling the “outcome” of the “final stakeholders,” city management reprioritized to give highest priority to the “primary stakeholder—the citizen,” and reorient and digitize all systems toward a single outcome of “providing seamless and reliable services.” Some highly evolved smart cities, such as Singapore, went further to ensure citizen happiness. Digitization and smart systems are playing an increasing role in digital transformation. This role involves end devices to consumer premises and networks, and to utilities who actively increase the level of integration, automation, and intelligent ways, in order to achieve customer goals (consumer, utility, and city). Utilities are actively deploying smart-grid systems for AMI (automated metering infrastructure), Distribution management to digital utility systems and analytics to modernize, and prepare for the changing role of utilities with active proliferation of distributed energy resources (DER). Implementation of the smart grid is mandatory for smart cities that are duly accounting for DER, microgrids, and demand response (DR)—with customers in different phases of transformation, from legacy to the future generation of energy systems. It is a challenge to plan OT 1 IT (operational and information technologies) systems at smart city and grid levels and the overall control, communication, and cloud systems architecture should be closely developed along with the field developments. Consumers have many smart [e.g., electric vehicle (EV)] and DER options available for local generation, and the scale depends on size of the premise and energy Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00019-X © 2021 Elsevier Inc. All rights reserved.

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needs, and business case to invest locally—than simply depend on the grid. On the load side, smart devices and appliances capable of interacting with electrical grid and consumer preferences to autonomously decide best time to operate are proliferating. With the advent of Internet of Things (IoT), 5G, and various other wireless technologies, secure cloud systems, Machine learning (ML) and artificial intelligence (AI), and blockchain, distribution, delivery, and trading of power are going through enormous transformation paving way to transactive energy network (TEN, as defined originally by GridWise Architecture Council, GWAC of US Department of Energy, [2]) that empower all stakeholders to achieve a sustainable and resilient energy future and perfect power [3] (coined by Motorola Chairman Robert Galvin). This chapter presents an overview and snapshot of various subsystems and technologies enabling TEN for smart cities and is organized as follows. First, we identify key stakeholders and market forces driving the need for transactive energy and key technologies that are enabling TENs for smart cities in Section 19.2. Sections 19.3 and 19.4 outline evolution of key subsystems of (1) DER on generation side and (2) customer premise systems on demand side such as building management system (BMS), building energy management system (BEMS), and interactive appliances. Digital systems and components enabling TEN are discussed in Section 19.5. Section 19.6 describes smart microgrid with TE features, starting with architecture and various features. Markets and operators are described in Section 19.7 and transactive energy approach, strategy, and challenges in Section 19.8.

19.2

TEN for smart cities—stakeholders, market forces, and technologies

An energy equation for a city is fairly complex. It involves interconnecting decades old regulatory and utility organizations and systems; new-age renewable (RE) and efficiency technologies with increasing digitization; AI and real intelligence; and customers (individual, commercial, and industrial)—with push and pull and iterative advancements over several touch points, with different degrees of advancement across the world (see Fig. 19.1).

19.2.1 Customers and stakeholders Customers and stakeholders represent city management (across different government and private organizations); utilities (electric, water, gas, and transportation); regulators (representing the government policy); service providers (public/private); end customers across commercial (malls and stores, office buildings, and parks); residential (townships of houses/apartments, and individual buildings); industrial (workshops, factories, and warehouses); and agriculture (across vast tracts of lands).

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Figure 19.1 New energy paradigm for smart city.

19.2.2 Digitization and smart systems Across the smart city, utilities, infra providers, different types of customers, and newer service providers are looking for ways to perform toward sustainable outcomes. As the world is looking for stronger cyber-physical integration, each device, system, and process (technical or manual, automated to physical) is going through iterative advancement for higher efficiency, lesser human intervention, and eventual goal of sustainable living. With advanced sensor and IoT technologies and appliances incorporating them becoming highly affordable, and mobile networks all pervasive, it is becoming easier for every device and system to add more electronic and software components and extensive insight using data sciences and AI—in the cloud or data center. Enterprises and individuals will increasingly manage the underlying systems using higher levels of automation toward the “outcome!”

19.2.3 Markets and operators With the proliferation of DER, storage, and EV, consumers are looking for ways to “export” the unused power to those in the neighborhood who need it, thus making them prosumers (consumers as well as producers). Proliferation of controllable smart appliances enables consumers to trade for best “value”—either price or comfort in operating them. As prosumers and operators expand, regulators and utilities will be required to facilitate markets for “buy and sell,” paving way to providing increased economic value than simply a fair price to meet the demand.

19.2.4 Transactive energy networks Gridwise Architecture Council defines: “Transactive energy systems, are systems of economic and control mechanisms that allow the dynamic balance of supply and demand across the entire electrical infrastructure, by using value as a key

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operational parameter.” Existing systems and infrastructure for bulk energy transactions between large producers and operators are evolving into full-fledged implementation of TEN enabling “price-to-devices” transactions. Several flagship projects implemented in the United States and Europe demonstrate the feasibility of peer-to-peer energy transactions and transactive energy controls in residential and commercial establishments. For example, Pacific Northwest National Laboratory’s (PNNL) Clean Energy and Transactive Campus project [4], launched in 2015 successfully tested the concept of creating individualized energy markets for buildings, further extending down to actual building zones and devices. In Germany the “Peer Energy Cloud” project [5], funded by the Federal Ministry of Economics and Technology developed a cloud based platform for local energy trading and smart homes.

19.3

DER: distributed energy resources

REs at customer locations are of tens of watts to kilowatts of capacity and the popular options are: solar on the rooftop as panels or shingles; on the fac¸ade of large multistoried buildings; on campus in gardens or parking lots; built into street and garden lights; water heaters; one or more small wind turbines; hybrid power with solar, wind and storage to provide supply at the time of need; tubular skylights bringing day light inside the house; micro hydro using water wheels where there is a source of flowing water; and geothermal heat pumps to help with heating and cooling. Therefore with the preceding in mind, Negawatt Sources are active Demand Response in order to meet peak demand on site, neighborhood or for the utility. Since heating, ventilation, and air conditioning (HVAC) is the largest load in a home, smart thermostats such as Google Nest negotiate and participate in DR programs. This program can further be expanded with home energy management (HEM) systems to comprehensively address HVAC, lighting, washing, kitchen, and other loads, along with integrating and managing the DER. Negawatt sources in a commercial or industrial environment will require active interface and integration with local BMS, BEMS, or any specific control systems, in order to control variable loads such as HVAC as part of DR programs aggregated and run by service providers (ESCO). Thus, battery storage is used to store RE energy and provide reliable power at the time of need. So far, most storage devices are not smart, and require extensions to link up with energy management system (EMS), BMS, or HEM. Diesel generators are popular choice, in fact the only choice for long, and are still present in most large customer locations. Early RE use cases evolve from eliminating or limiting the usage of these DG sets, as customers strive to limit spending carbon fuels. EV charging stations will be omnipresent with the proliferation of EV, two and four wheelers, in populous areas such as malls, office parks, and residential neighborhoods. A typical EV station is designed to work for two/four wheelers, with

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multiple charging points supporting local standards, and using power from grid, REs, battery or DG. In cases where battery recharging takes longer time, busy places can also provide battery swapping. EVs: when an EV is in the parking lot, the stored energy in the battery can also be used as a power source (DER), based on customer consent. With higher proliferation, tens/hundreds of EV can collaborate through a local operator/aggregator to meet partial requirements of peak demand in a premise. This tapped power is paid by the operator directly or accrued as future credit.

19.4

Evolution of key subsystems for transactive energy

This section describes the evolution of major subsystems that are revolutionizing the way electric power is generated, delivered and transacted; thus, paving way for the new-age Transactive Energy. The evolution of key subsystems in generation, distribution/delivery, and load/demand side are also discussed.

19.4.1 Building management systems Starting as the control systems for mechanical and electrical systems such as heating, ventilation, and air conditioning in a building several decades ago, today’s BMS/ BEMS systems, have evolved to integrate and control a whole lot of other functions, such as lighting, access control, surveillance, elevator operations, fire alarms and power/energy usage, that are generally referred to as integrated building management systems. Large commercial buildings incorporated an extended scope by encompassing an entire campus or facility with multiple buildings, whereas BMS controllers of individual buildings are integrated into a continuous emission monitoring system (CEMS) or factory energy management system (FEMS) system. All monitoring and management systems however are largely confined to internal or intra campus systems without any connectivity to or interactions with external systems such as the utility grid. With advancements in smart grid and DER (e.g., rooftop solar), need for grid interactive systems is increasing to achieve twin goals of sustainability and efficiency across the city’s energy infrastructure (see Fig. 19.2). With 75% of the electricity consumption and 80% of the peak demand coming from buildings (see Fig. 19.2), it is imperative that the highest level of efficiency and conservation measures are implemented using advanced technologies. While incorporating the green building technologies such as passive solar, energy efficient lighting, and windows and use of RE energy (rooftop solar/wind turbines) reduce the electricity needs of a building, operational systems such as BMS/BEMS need to support seamless integration and management of energy sources (grid, DER, DG sets, EV, and storage systems) and a building’s energy loads including plugged loads and smart appliances.

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Figure 19.2 Energy use in US building sector [6].

19.4.2 Grid interactive BMS/BEMS The majority of power systems today are one-way systems with power flowing from large centralized power plants to homes and buildings through utilities transmission and distribution systems. To meet the peak demand requirements, there are separate peaking plants which supply electricity during peak demand periods only at prices an order of magnitude higher than what the utility pays for normal usage times. Utilities cover these costs through time of day pricing where per unit rates are higher during peak hours. With increasing power demand from all types of consumers (residential, commercial, industrial, and agricultural), meeting the peak demand through large, centralized peaking plants is not a viable solution in present times. While distributed energy resources such as rooftop solar, mini/micro wind turbines are enabling local generation at customer premises, the vagaries of RE energy generation (frequent variations in output power as irradiance or wind speed vary randomly) cause grid instabilities and moreover they may still not meet peak demand requirements at the utility scale, there is a strong need to make homes and buildings responsive to grid in near real time to manage their peak loads and smoothen or even shift the peaks in demand patterns. Automated demand response (ADR), wherein the utility sends pricing signals to participating customers’ BMS/ BEMS facilitates interactions with the building and industrial control systems, which are preprogrammed to act on the utilities’ DR signal. With an ADR, while the power flow is still in one direction only, the whole building or campus responds to dynamic pricing and demand management of the utility without any human intervention through a two-way communication system with the utilities’ systems.

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Today’s BMS/BEMS systems support open ADR or other standards as per the local utilities’ ADR implementation. Green buildings and grid interactive BEMS systems contribute significantly to the flexibility and sustainability of an energy future by: 1. Reducing energy load on the system—through efficient equipment and building design 2. Changing operating load based on consumer needs and price—energy conservation through smart usage controls 3. Optimized building operations as per occupant needs and DER availability—to reduce, shift, or flatten building loads 4. Two-way communication flow between buildings and external systems—enabling demand response and power export

19.4.3 Levels of operation Depending on the usage of different customers at various times of the day, week, and season in the year (and concurrency in terms of time of use), load characteristics are estimated, monitored, and eventually provided by the key stakeholders. With increasing share of DER and role of several related management systems, secure, and real-time interoperation is most critical and essential. Depending on the hours of operation of the entire facility or larger loads, and the overall purpose, demand pattern of a customer facility can be segregated into base and peak loads (Fig. 19.3). Base load is minimum that needs to be serviced, that may vary depending on business and holidays, and working hours. Consumers typically plan for the utility to supply the base load, since the requirement is fairly constant and critical. Peak load is created from large loads, simultaneous initiation of multiple loads based on a schedule, or in response to severe weather conditions. From a shopping mall operating from 11 am to 11 pm (in a city such as Dubai, India), where the differential temperature (between outdoor and indoor) is fairly high ( . 20 C) during the day, even HVAC becomes a core part of the base load. Since the storage costs are still high and not yet at god parity, local RE is used to supplement the regular consumption without a plan to store. In case the current RE generation exceeds required load, excess power can be supplied to the grid using a

Figure 19.3 Load pattern with base and peak loads.

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scheme of net metering where the supplied units can be compensated in the monthly bill with consumption units, or paid at preset/dynamic price.

19.5

Digital systems and components—10 enablers

The Internet of Things, popularly known as IoT, is an emerging technology allowing things to connect over the Internet, and communicate with one another—similar to how people connect over web. IoT enables things, systems, and sensors to exchange data and control information to accomplish application specific tasks.

19.5.1 IoT and sensors Over the years, IoT has become ubiquitous with many home devices, appliances, sensors, personal wearables, and industrial equipment all incorporating the technology along with integrated intelligence to execute complex applications. IoT solution platforms are comprised of IoT devices performing sensing, monitoring, or actuating tasks; a heterogeneous network to connect the devices and computers or cloud platforms; and application software to collect, store, analyze, and present data to users over web-based dashboards. These IoT solutions span a wide range of application such as smart homes, smart cities, healthcare, transportation, energy systems, and industrial automation.

19.5.2 IoT for home and building automation IOT devices are being used in homes and buildings to monitor and control electronic, electrical, and mechanical systems. While there are many tasks done by these IoT devices at home for comfort and security, the following are the key tasks where IoT is enabling smart energy management including transactive energy: G

G

Smart HVAC controls—Allowing precooling or preheating and automated temperature settings based on ambient conditions, occupancy, customer preferences, and time of day energy prices or even DR signals from the local utility. Smart appliance management—Appliances like washing machines autonomously deciding best time to operate based on customer preferences and time of day energy prices or even DR signals from the local utility.

19.5.3 IoT for energy IoT is the major contributor to advancement of smart grid beyond the monitoring and automation being done by the utilities. Key tasks performed by IoT-enabled devices in the field of electrical energy include: G

AMI—IoT-enabled smart meters and communication systems enable advanced monitoring up to the end consumer.

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SCADA (supervisory control and data acquisition)—IoT with AI and ML takes SCADA beyond control, enabling several advanced functions like multisite integration, predictive maintenance, and fault prevention. Smart inverters—IoT enables solar- or battery-based inverters to manage power flows and respond to grid stability requirements in real time. Rooftop solar inverters have a potentially major role to play when they are integrated directly with smart-grid applications of the utility, since they have potential to extend their smart functions for multiple purposes. As per California Rule 21 [2], smart inverters will require the following standards—IEEE 2030.5 [7] for Smart Inverter Profile; IEEE 1815/DNP3 for SCADA Real-time Monitoring and IEC 61850 for integration with grid infrastructure. Remote operation of energy devices: Major energy consuming devices like lighting and HVAC systems are IoT-enabled to respond to grid requirements and utility pricing signals.

19.5.4 IoT Communication Technologies for TEN Several communication technologies have developed to enable IoT applications in residential, commercial, and industrial sectors. Here we outline four key communication technologies that enable IoT for energy including transactive energy.

19.5.4.1 Bluetooth Bluetooth low energy (BLE) is a low-power, short-range, secure wireless technology used in battery-operated IoT devices such as wearables and smart home devices, which can be monitored or controlled through mobile phone handsets. It is widely used in home lighting controls, smart thermostats, computer, and audio peripherals at home enabling consumers to set and control their appliances through their mobile phones. Since the BLE range is limited to 10 20 m, the number of devices in a network is limited to 7. With these limitations BLE is more commonly used for “within the room” wireless operation.

19.5.4.2 Zigbee Zigbee is a popular wireless mesh technology used in industrial control applications. It uses IEEE802.15.4 personal area network standard to communicate with other Zigbee devices within 75 100 m in indoor settings. With clear line of site Zigbee devices can communicate up to 300 m (in outdoor and industrial settings). Zigbee creates a mesh where each interoperable device becomes wireless node passing information to next device (hop) till a gateway is reached. A Zigbee network, in theory can accommodate up to 65,536 Zigbee devices. In practice up to 1,000 Zigbee devices can be operated in an industrial setting, making it more popular in home and industrial automation applications. Zigbee Smart Energy (Zigbee SE) is the world’s leading standard for interoperable devices used for monitoring, controlling, and automation in energy and water industry. This protocol enables real-time tracking of energy, power, and flow

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parameters in energy, gas, and water meters besides enabling multiple control methods such as emergency signals and duty cycling. Zigbee Home Automation (Zigbee HA) is a global standard for smart homes and enables home users to manage energy and security.

19.5.4.3 LoRa and LoRaWAN LoRa (Long Range) is a low-power wireless technology for wide area networks. It enables long-range ( . 10 km) transmissions with low-power consumption. LoRaWAN is one of the widely used low-power WAN solutions using LoRa technology, enabling data communication with thousands of devices deployed kilometers away. LoRaWAN features low-power operation (10 years of battery life), low data rates (0.3 50 kbps), and long-range communication (2 5 km in urban areas and up to 15 km in rural) with gateway nodes relaying messages from end devices and a central network server. LoRaWAN is an appropriate technology for some of the smart city applications such as smart street lighting and smart parking, which require thousands of devices to send short messages with more tolerance for delay. LoRa Alliance was created in 2015 as a nonprofit association in charge of the LoRaWAN network protocol specification and rules of certification. DLMS User Association, a nonprofit association founded in 1997 by utilities and meter manufacturers develops, supports and maintains the DLMS/COSEM specification for data exchange for smart metering, smart energy management and related fields. To help adoption of LoRaWAN for smart grid/AMI and energy management applications, a liaison was created between LoRa Alliance and DLMS UA. The following is a nonexhaustive list of applications that benefit from the DLMS LoRaWAN profile: G

G

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Utility revenue metering for electricity, water, gas, and thermal energy Demand response Energy management in buildings and smart cities Management of DER EV charging Public lighting

19.5.4.4 Cellular networks 5G/4G/3G Smart-grid applications such as AMI that require operations over long distances can take advantage of cellular 3G/4G networks capable of large amounts of bidirectional data transfer. Many smart metering installations across the world still use 2G/3G and 4G-LTE connectivity. However the latency and power consumption of these technologies limits their use to monitoring applications with more tolerance for delay. Proliferation of RE energy such as wind and solar, particularly rooftop solar throw additional challenges in stabilizing the electric grid in real-time against wide variations in generation. Responding to such events from hundreds or thousands of DER installations across a vast utility area requires high bandwidth, low latency and very low-power wireless technologies with reliable signal reception in

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both indoor (e.g., a meter or sensor on a pipe in an inaccessible corner of a building) and outdoor settings. The upcoming 5G (fifth-generation) cellular technology paves the way for very high bandwidth and low latency networks—facilitating smart city wide IoT device networks enabling smart grids become smarter. 5G uses AI for traffic management, network planning, and address changing customer needs cost effectively. Smartgrid applications running on a 5G can bring the following benefits to the utility and consumers: G

G

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Reduced metering and billing costs to utility, allowing supply and demand modeling and dynamic pricing Smoother integration of DER, DR, and grid stability Grid infrastructure responding well to RE mix (reactive power), and adapting quickly to energy markets Two-way power and data transfers between utility and end consumer systems Transactive energy—enabling BMS, HES, and smart appliances to operate autonomously responding to price and availability considerations to maximize value across the electric system value chain

19.5.5 Cloud systems During the past 3 years, we have witnessed the rapid rise of the cloud as the default option for enterprise applications—providing scalable and flexible server and storage infrastructure; advanced options for HA (high availability); DR (disaster recovery, with 2/4 copies); application stacks and platform services for rapid development and customization; and, prices falling down for initial adaption. Customers are already using multiple clouds and fast looking for optimization and cut down costs. As standards for interoperability emerge and more parties implement, key DER, microgrid, and TE functions can be encapsulated into a TE service platform that the field implementations can draw upon. Market price integration, local operations, grid adoption outside, and behind the utility meter—is a complex subject and related functions can be implemented using AI and MI and offered on the TE service platform that can be subscribed by utilities microgrid EMS and emerging distributed service operators (DSO).

19.5.6 Cyber security and federation With the increasing need for multiple stakeholders, higher levels of integration, interoperability, and distributed processing, cyber security should be integral to all systems, individually and when integrated. This includes security at multiple levels of—device, interface, data, server, and network, along with IAM (identity and access management) and federated identity (IAM across different systems from different operators and providers), across access, and operational needs. Here, a reference is made to the cyber security strategy and standards as defined by National Institute of Standards and Technology, US [8], in order to secure smart-grid applications.

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19.5.7 Big data, analytics Data from IoT networks from DER and smart-grid systems will be quite large. In addition, the data architecture should include a data hierarchy across—realtime, application, analytical, and predictive, and combine the best of distributed processing of edge gateways, and centralized applications on the cloud/data center.

19.5.7.1 Distributed centralized AI and ML and blockchain AI and ML functions can be offered from the cloud as well as within EMS and IoT networks in the field to facilitate iterative adaption. The technology that popularized crypto currency is also available for securely connecting multiple stakeholders, customers to disparate systems, to participate in the energy markets.

19.5.8 Interoperability and standards With the proliferation of smart home appliances, DER, grid interactive BEMS, and other smart-grid infrastructure, it is imperative that all the subsystems seamlessly interact and integrate with each other to provide the end-to-end functionality for the intended outcome. In addition, various control and communication devices in smart buildings and smart homes shall be interoperable across suppliers. Such interoperability can be ensured only through adaption of open standards ratified by appropriate international standards organizations such as ANSI, IEEE, or ETSI. The Smart Energy Profile 2.0 (IEEE standard P2030.5) application protocols intended to provide the interoperability across smart grid and the end-user equipment. It enables management of the end-user energy environment including demand response, load control, price communication, distributed generation, electric storage, and EVs as well as the support for additional commodities including water, gas, and steam. This standard focuses on a variety of possible architectures and usage models including direct communications between a service provider and consumers/prosumers, communications within a premises or home area network (HAN), and communications between a service provider and an aggregator. It uses TCP/IP for providing transport and network layer functions while supporting a variety of wireless (Zigbee, WLAN, and other personal area and HANs) and wired (e.g., Ethernet LAN, power line communications PLCC, and serial RS485) protocols at the media access and link levels, ensuring interoperability across various subsystems with disparate technologies (see checklist: “An Agenda for Action for the Interoperability Standard Best Practices”).

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An Agenda for Action for the Interoperability Standard Best Practices Function sets that are addressed by this interoperability standard include but not limited to the following key activities (check all tasks completed): _____1. Smart metering/AMI _____2. Prepaid metering _____3. Pricing _____4. Demand response _____5. Grid interactive buildings—BEMS _____6. Distributed energy resources—generation monitoring and control _____7. Energy storage _____8. Billing and customer information systems (for utility) _____9. EVs _____10. Smart home appliances—autonomous interactions with grid An interoperability scenario across HEM and all related networks is illustrated in Fig. 19.4. As interoperability improves over time with standards and established “trust” relationships through an active federation, a “loosely coupled and robust” architecture evolves around the building of a much needed—power system of systems: G

G

Utility scale smart-grid systems integrating across the grid such as AMI, distribution management system, outage management Energy service providers such as ESCO aggregating DR and any other microgrid customers

Figure 19.4 HEM with market transactions.

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Energy infra companies managing EV charging stations across a neighborhood or city Customer systems such as BMS, BEMS, facility management system, EMS, energy network management system

19.6

Smart TE microgrids

A smart microgrid, is a small scale power grid, operating at a low voltage, consisting of key components of DER, battery storage, electric loads that can be controlled (variable or on/off), grid supply (if connected)—managed by EMS, BESS, BMS, and other control systems networked together for singular purpose of providing reliable, quality and increasingly independent power to the customer. While all microgrids may not transact energy, as part of this chapter, we consider only those with transactional features. In a smart city, majority of microgrids are connected to the grid, while some of them such as an EV station can be designed to be independent. Microgrids are selfmanaged and can offer stability during any grid disturbances or maintenance. The blackout of North East (US) in 2003 for 14 days in August (Aug 14 28) [9], affected 45 millions in US and 10 millions in Canada, and prompted widespread awareness to build alternatives to traditional grid operations. Motorola Chairman, Robert Galvin, envisioned a network of microgrids and DER as the only solution to build a perfect power for the future [3]. At the same time, the onus of providing a highly reliable and resilient local grid falls on the Microgrid, imbibing smart design, system, and maintenance elements from a traditional grid. Economic value is quite critical in terms of return on investment (RoI) and total cost of operation. While RE sources have reached grid parity, storage is still quite expensive and needs to be justified. The design undergoes multiple rounds of optimization across minimal period of operation (few hours a day to 24/7), load profiles, available DER, grid pricing (ToD and dynamic prices, and charges), and energy markets (short and long term at transactional level) within the available budget. A sustainability goal can be strategic to a customer and choose to design a complete net zero premise, which would result in required upfront capital costs into the design. Quite often green building ratings focus on static components such as architecture, localized material, greenery, recycling, layers of insulation, star-rated appliances, and not adequately address the operational efficiency and costs of the facility. A traditional BMS addresses basic automation of large loads and monitoring, and need to expand through IoT and EMS extensions to participate as a microgrid. Resilience is the ability to work reliably in grid connected and islanded modes, and how well the energy sources and loads are synchronized to provide seamless operation (even during the transition) and management, under normal conditions as well as unexpected events. Events can range from unplanned peak loads, sudden change in weather conditions that impact the RE generation, emergency events (storms, floods, cyber, and physical attacks) and even breakdown of key equipment.

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Control schemes can be centralized, decentralized or a combination, where each has its distinct advantages. Centralized scheme is easier to implement but has a single point of failure and decentralized scheme is more resilient but more difficult to implement and coordinate. A hierarchical scheme integrates multiple decentralized schemes to adapt iteratively toward central settings of critical parameters such as frequency, voltage, and power (active and reactive). Hierarchical scheme involves at three levels—primary at individual smart device/subsystem, secondary at microgrid EMS across loads and DER, and tertiary at grid integration levels. A smart inverter will adapt to varying voltage and frequency in the local grid automatically (using latest droop algorithm) by reducing or increasing generation. Controllers of chiller and lift can account for voltage sag and compensate through internal power electronics and restart or transition to backup quickly for smooth transition, using industry standards SEMI F47 [10] and IEC 61000-4-11. This architecture of microgrid TE EMS, as shown in Fig. 19.5, is the principle of Industrial IoT where multiple OT, IT, and AI systems are integrated for common purpose, instead of point solutions. Distributed AI and ML features are embedded into the IoT gateway and the EMS management server in order to adapt to varying field conditions (within the acceptable limits). Key components of microgrid EMS will consist of EMS controller that provides real-time control across the premise, IoT edge gateways to acquire data across all deices and subsystems, and TE EMS management server software that collects the data and offers key functions such as energy market integration for finding and transacting for best prices, DER modeling, forecasting and scheduling, and AI-based analytics on the collected data across the microgrid. IoT edge gateways provide a two-way communication system for monitoring as well as control for specific systems. Integrated SCADA system will include multiple interfaces integrating different subsystems such as—BMS (building management system), solar SCADA, wind SCADA, and battery BMS (battery management system). For a green field

Figure 19.5 Architecture of microgrid TE EMS for legacy and future requirements.

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project, it is good to design an integrated TE system from the ground up! Microgrid TE EMS will achieve the following: 1. Model, make, and manage energy transactions, with neighbors or through markets, for best economic value while maintaining microgrid and grid stability. AI and ML can be utilized for continuous optimization of the economic model. 2. Automation under different modes of the microgrid—normal grid connected, islanding and extreme emergency, and smooth transitioning between different modes—directly from EMS controller, or through BMS, IoT, and SCADA. 3. Controlling the loads for peak shaving and demand shifting with first preference to local generation and best power quality and at the same time optimizing continuously for best economic value using transactional features and energy markets. 4. Interfacing all loads and DER and integrate for a seamless smart microgrid operation, directly or through individual SCADA and automation systems for BMS, solar, wind, battery BMS. 5. Analyze device and system performance to continuously to look for outliers and maintenance issues, and help build strong predictive maintenance practice. 6. Model load patterns and DER availability and forecast complete energy schedule (at 15/ 5 minute blocks) of the premise, in real time, day and week ahead, and share the schedule with the utility/operator. The schedule will also consider dynamic rates of the energy markets to recommend required local changes, in order to achieve best economic value.

Standards are critical to follow for the equipment, for interconnection (within the microgrid, with the distribution grid and markets) and management interfaces (for data acquisition and control). Legacy integration is critical if the microgrid project is not green field and there is requirement to utilize already existing energy sources such as diesel generator. Smart-grid integration is critical for grid connected TE microgrids where there is a two-way exchange of data, control commands, and power in real time. While utilities play these roles today, local operators (DSO) may emerge who would specialize and offer dedicated services to neighborhood.

19.7

Markets and operators (short and long term)

In United States, PJM is an independent systems operator in the North East, planning wholesale markets, working behind the scene to operate the transmission and distribution grid reliably, and making real-time decisions to balance supply and demand. When it comes to wholesale markets, the operator will work with multiple power producers, small and big, local DER or larger central plants, and set up power purchase agreements (PPA) with constant or variable pricing at various times of the day. Once in operation, the power producers send their generation forecast to the operator, at 5/15 minute block and hourly-daily-weekly-monthly levels, in prescribed format and system interface. The operator will also get demand forecast from the utilities and large smart consumers, and combine demand and generation forecasts to prepare a model for reliable operation of the grid. This model will help in infrastructure planning of the grid, at transmission and distribution levels.

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The operator will monitor the grid in real time, and send adjustment signals to the power producers and consumers, upward or back down, to adapt to the power supply and demand. While larger producers go for the wholesale PPA, smaller producers like to negotiate for maximum economic value. A solar generator may use battery storage during off-peak hours, and supply during peak periods for peak pricing. Short-term markets such as spot markets are coming up for producers to seek peak periods in near real time (hours ahead) and participate for better pricing. The same market will also be efficient for the consumers also to look for favorable pricing from producer of choice. For smart cities to evolve neighborhood and city level markets are required, the markets needs to be created and facilitated by reliable operators, so as to allow DER to meet a higher percentage of the peak needs. Rate discovery is a crucial part of these markets, and significant work is going on across the world. One significant pilot project is—Olympic Peninsula Demonstration Project in Olympic Peninsula, Washington, US, led by PNNL (Pacific Northwest National Lab), explored real-time pricing methods across critical peaks, and time-of-use intervals. The project deployed “price-flexible energy technologies,” such as washing machines that learn best time to initiate the washing cycle, based on this real-time pricing. These smart appliances can also synchronize with other similar appliances located on the same network, to manage peaks and loads based on the above real-time pricing of DER and utility. Energy market operators such as PJM uses LMP—locational margin pricing to set energy prices between buyers and sellers, and manage grid congestion to protect grid infrastructure. Similar to airlines, the charges go up when the demand to supply ratio is higher. The LMP prices can vary in sending and receiving areas, based on higher demand (congestion). At steady state, LMP in all areas of the grid is at the same price, and in times of congestion in certain areas, the LMP prices go up in the congestion area and LMP from the sending area will come down. Based on the dynamic price levels for instantaneous, short, and long terms, across different areas, a heat map can show stress areas in the grid that helps in planning for grid operations and upgrades in infrastructure.

19.8

Transactive energy strategy and challenges

REs changed the entire scenario of the traditional utilities and new paradigm of energy transactions is possible between customers in a neighborhood, through direct negotiation or through a market. The above-discussed smart microgrids with transactive energy features and underlying components take over the responsibility and investments of a typical utility and the customers are going to foot the bill for all capital and operational costs. This brings a shift of electric assets from utilityowned and operated to customer-owned and operated that will be behind the meter. It is to be seen how the regulators are going to evolve to play in this type of decentralized markets with distributed systems and components. In case of any change in

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regulations, since the involved parties are many, the underlying software and integration should be updated for compliance. Utilities will likely evolve to be operators of the customer assets and play a large relevant role. The transactive energy framework (TE1.1) is defined by the GridWise Architecture Council and US Department of Energy, as a guide for several pilots and standards. In order to address the growing use cases, the following topics are addressed: G

G

G

G

G

G

G

G

Wholesale markets and participation by microgrids and DERs Increased intelligence and coordination at interchange points of transmission and distribution, and distribution and customer microgrid Peak load management across neighborhoods and city Resource management to ramp up to sudden spike in demand Facilitation of new service operators to maintain assets in buildings and homes Minimization of transmission and distribution capacity as electric flows change from large central plants and utilities Management of congestion and related costs Manage market supply and demand to ensure price overrun

In transactive energy, the stakeholders are organized in a hierarchical model in order to provide a reliable functioning of the electric system, and in a distributed and centralized model, to provide better flexibility, reliability, and efficiency compared to the present grid.

19.8.1 Challenges In order for transaction energy and smart grid to be implemented across the smart city, there are quite a number of challenges as utilities across the world need to transform. Regulators will find it hard to create new rules of the game when they need to deal with several parties (with DER) to maintain compliance and grid stability. Compared to dealing with a few large players, regulators will need to find new ways to set up, tweak, and stabilize rules. When it comes to end devices, the manufacturers still do not have a roadmap for major use cases, so they are delivering for separate use cases—typical or special case. Since the standards for interoperability are not yet final, manufacturers offer their own methods, built internally, with external device or cloud. Integrating these variations along with standalone legacy—will present challenges. Interoperability requires standards to be finalized and tested across varieties of use cases that will vary across different parts of the world. Until then, manufacturers will not be able to adapt and offer supplies in scale. Until the devices reach a scale, the cost of implementation will still be high making the adoption slow. While investing in smart-grid systems, utilities are caught in a dichotomy as they lose revenues from their HT customers who are moving faster with DER. At the same time, advanced distribution management and AMI are going to make the grid future proof. Since energy systems are going through a rapid transformation, there will be severe shortage of qualified people who can take charge and deliver what it takes.

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The new workforce will require extensive knowledge across OT and IT systems, with expertise, experience, and knowledge across functional, electric, electronics, software, and analytics.

19.9

Summary

Digitization and smart systems are playing increasing role of digital transformation, from end devices at consumer premises, and networks to utilities and actively increasing the level of integration, automation, and intelligent ways to achieve customer goals. Across smart city, utilities, infra providers, different types of customers, and newer service providers are looking for ways to perform toward sustainable outcomes. Proliferation of distributed energy resources, energy storage, electrical vehicles, and smart home appliances are enabling consumers to buy or sell energy based on price and need (comfort). Technology is evolving to enable full-fledged TENs that facilitate “price-to-devices” transactions. At the smart city level, several enabling technologies and infrastructure need to be in place to enable TEN implementations. This chapter provides an overview of the key systems such as distributed energy resources, microgrids, and grid interactive building energy management systems that participate in these energy transactions. IoTs and latest developments in wireless technologies and secure cloud systems that can enable millions of transactions on a TEN are discussed in detail. While several pilots and flagship implementations, particularly in US and Europe have been successful, there are no large-scale implementations yet owing to lack of infrastructure, interoperability standards, and large-scale market/operator systems. With rapid development on all these fronts, while addressing the strategy and challenges, commercial microgrids and transactive energy are going to redefine the way energy is going to be generated, distributed and transacted for a better energy future on the planet. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

19.10

Chapter review questions/exercises

19.10.1 True/false 1. True or false? Across the smart city, utilities, infra providers, different types of customers, and newer service providers are looking for ways to perform toward sustainable outcomes. 2. True or false? With the proliferation of DER, storage, and EV, consumers are looking for ways to “import” the unused power to those in the neighborhood who need it, thus making them prosumers (consumers as well as producers).

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3. True or false? Transactive energy systems are systems of economic and control mechanisms that allow the dynamic balance of supply and demand across the entire electrical infrastructure by using value as a key operational parameter. 4. True or false? Since HVAC is the largest load in a home, smart thermostats such as Google Nest negotiate and participate in DR programs. 5. True or false? So far, most storage devices are smart, and require extensions to link up with EMS, BMS, or HEM.

19.10.2 Multiple choice 1. Large commercial buildings incorporated an extended scope by encompassing an entire campus or facility with multiple buildings, whereas BMS controllers of individual buildings are integrated into a: a. CEMS system b. BMS system c. FEMS system d. BEMS system e. Grid interactive system 2. With 75% of the electricity consumption and 80% of the peak demand coming from buildings, it is imperative that the highest level of efficiency and conservation measures are implemented using: a. Passive solar b. Energy efficient lighting c. RE energy d. Advanced technologies e. All of the above 3. The majority of power systems today are one-way systems with power flowing from large centralized power plants to homes and buildings through: a. Electrical systems b. Utilities transmission systems c. Urbanization systems d. Autonomous systems e. Distribution systems 4. Green buildings and grid interactive BEMS systems contribute significantly to the flexibility and sustainability of an energy future by: a. Reducing energy load on the system—through efficient equipment and building design b. Changing operating load based on consumer needs and price—energy conservation through smart usage controls c. Optimized building operations as per occupant needs and DER availability—to reduce, shift, or flatten building loads d. Two-way communication flow between buildings and external systems—enabling demand response and power export e. All of the above 5. Depending on the usage of different customers at various times of the day, week, and season in the year (and concurrency in terms of time of use), load characteristics are estimated, monitored and eventually provided by the: a. Customer facility b. HVAC

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c. Key stakeholders d. IoT solutions e. Smart economies

19.10.3 Exercise 19.10.3.1 Problem What would justify the establishment of a transactive energy system?

19.10.4 Hands-on projects 19.10.4.1 Project Do research: Why/how should countries consider transactive energy as a pathway for grid modernization?

19.10.5 Case projects 19.10.5.1 Problem How can smart home microgrids collaborate with each other in a multiple smart home microgrid system, by forming coalitions for gaining competitiveness in the market, through the presentation of a smart transactive energy framework?

19.10.6 Optional team case project 19.10.6.1 Problem Develop a comprehensive simulation study that reveals the effectiveness of a proposed method in lowering the market clearing price of energy time intervals, by increasing smart home microgrid responsive load consumption, and promoting the local generation of energy.

References [1] World urbanization prospects: 2018, United Nations, Department of Social and Economic Affairs (2018). [2] The GridWise transactive energy framework is a work of GridWise Architecture Council, US Department of Energy. ,http://www.gridwiseac.org/., January 19, 2015. [3] Perfect power by Motorola Chairman Robert Galvin, Galvin Electricity Initiative. ,http://www.galvinpower.org/., May 20, 2010. [4] Clean energy and transactive campus, Project, Pacific Northwest National Laboratories, US. ,https://bgintegration.pnnl.gov/connectedcampus.asp., January 7, 2020.

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[5] Peer energy cloud, funded by Federal Ministry of Economics and Technology, Software Cluster, Germany. ,http://software-cluster.org/projects/peer-energy-cloud/., October 19, 2011. [6] Annual energy outlook 2017, US Energy Information Administration (US EIA) 2017. [7] 2030.5-2018 IEEE standard for smart energy profile application protocol. ,https://standards.ieee.org/standard/2030_5-2018.html., May 13, 2018. [8] Cyber security framework for smart grid profile, NIST Technical Note 2051, National Institute of Standards and Technology, US Dept of Commerce. ,https://nvlpubs.nist. gov/nistpubs/TechnicalNotes/NIST.TN.2051.pdf., July 9, 2019. [9] Technical analysis of the August 14, 2003, blackout, North American Reliability Council. ,https://www.nerc.com/docs/docs/blackout/NERC_Final_Blackout_Report_ 07_13_04.pdf., September 15, 2005. [10] SEMI F47 industry standard for voltage sag immunity. ,http://www.semi.org., August 1, 2007.

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Baseem Khan1, Esayas Gidey1, Habtamu Getachew1 and Hassan Haes Alhelou2 1 Hawassa University, Awassa, Ethiopia, 2Tishreen University, Lattakia, Syria

20.1

Introduction

Energy is a very important aspect for any household, industries, and agriculture. Conventional energy sources are in limited amount. Further, these conventional sources are declining day by day. Therefore there is a necessity to enhance new sources of energy along with their efficient utilization. For the social and economic development of any country, energy is the important factor. It is the major requirement of the infrastructure development as well as it decide the development level of any country also. Electrical energy generation, transmission, and distribution required economical and secure operation to meet the demand [1,2]. Table 20.1 presented the world energy consumption. The forecast of the future load demand for the development of any country on the basis of historical data is performed to develop the prediction of the generation capacity as well as generation planning of the system on the long-term basis and to enhance the reliability of the energy supply. Furthermore, planning of the various electrical sectors should be adequately design to incorporate various renewable energy sources in available in the system. Real time control systems are utilized to interact with the consumers in the new energy management systems [3]. Optimal utilization of the energy for maximizing the profits and minimize the cost is come under the problem of the energy management. Energy management enhances the economic competitiveness of the energy sources. The utilization of the energy must be efficient, economical, and optimal. For enhancing the productivity, social welfare, and comfort levels as well as to minimize the cost of energy, energy management can be utilized. Further, energy management can also be utilized to plan, direct, and control the supply and demand of the energy. Therefore to utilize the energy into more conscious, judicious, and effective manner, smart-grid network is implemented in various parts of the world. Integration of the innovative and superior communication, information, and networking techniques in the conventional utility grid for making it more reliable, stable, and faster to make decisions is the main characteristic of the smart grid [4]. The development of the smart grid will enhance the reliability of the electrical Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00020-6 © 2021 Elsevier Inc. All rights reserved.

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Table 20.1 World energy consuption. Year

Electricity consumption in (TWh)

1990 1995 2000 2005 2010 2015 2017

10,901 12,193 14,163 16,744 19,838 22,471 23,696

services along with the improvement in the safety of electrical instruments with the integration of more automation devices in the system. Therefore, the comfort level of the consumers will increase. Various innovative techniques, algorithms, and technologies are developed in the past years for the implantation of the smart-grid system. Some of these technologies are smart meters, smart energy management system, Phasor measurement units, home area networks, etc. Smart-grid technologies have been utilized in different sectors of the power system such as generation, transmission, distribution, and energy market. Further, the characteristic of the smart grid, that is, is the integration of the renewable energy generation sources is performed in the system with the help of microgrid system and distributed generation. In these technologies energy generation and utilization is performed at local level. Therefore, energy will be saved with help of smart energy management system utilized with such technologies. In the smart-grid system, the state of the power system is maintained in steady state by taking the intelligent decisions, which are depend on the information obtained from the smart technologies integrated in the smart-grid system. The smart-grid system can be easily defined with the help of its characteristics, which are as follows: G

G

G

G

G

G

G

Self-healing from power disturbance events Enabling active participation by consumers in demand response Operating resiliently against physical/cyber attack Providing power quality for 21st century needs Accommodating all generation and storage options Enabling new products, services, and markets Optimizing assets and operating efficiently

For improving the renewable energy utilization and efficiency, energy management system is the main component of the smart-grid system. The balance between generation and demand is the main criteria of power system operation. For any change in the demand and generation balance, a continuous monitoring and fast response are required to manage these changes. Slower response to the variation in the power demand balance may lead the system toward blackout in the whole system. Further, intermittency of the renewable energy generation also added complexity in the in the operation and control of the smart-grid system. With the help of

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recent advance communication and sensing technologies, smart-grid control with earlier discussed issue is easier as compare to conventional grid system. The integration of the highly fluctuated distributed generations (such as photovoltaic (PV)s, wind turbines, electric vehicles, and energy storage systems) threatens the stability of the power and distribution systems. The main cause is that the power ratio between the supply and demand may not be balanced. An excess/shortage in the generation or consumption of power may perturb the network and create severe problems such as voltage drop/rise and in severe conditions, blackouts. To increase the balance between the supply and the demand in an efficient way, and to reduce the peak load during unexpected periods, energy management systems are utilized [5]. The transition of the traditional power grid toward the smart-grid structure globally, can be justified for satisfying the requirement of ever-increasing energy demand. Further, smart-grid structure guaranteed the secure and reliable power supply to the consumers. The most vital approach utilized around the world to develop the smart-grid structure consists of renewable energy sources integration such as solar, wind, etc. Further, approaches such as intelligent management system, optimization algorithms, concepts, and techniques at the consumer end also very important for the implementation of smart-grid system along with smart generation technologies. This will be supplied the future supply demand reliably.

20.1.1 Importance of energy management In a world where the energy demand is on the rise, the power generation should also increase to satisfy the users’ needs and improve their daily life. However, because the number of consumers are rising and also because of the unpredictability nature of the electric load, power demand may cause challenges to the electric utilities and system operators. High peak demands have a great probability to occur in many periods and may be a threat to the system functionality. To resolve this issue, the electric utility and system operators have two choices available [6]: G

G

Increase the size and dimension of the network which is costly and requires time to implement Utilize energy management in order to reduce the possibility of high peak demand during peak hours

The second solution sounds more reasonable; however, it requires sophisticated algorithms and methods to be capable of managing energy. Energy management is considered a must for a smarter grid for many reasons: G

G

G

G

G

It is automated and does not require direct intervention from human beings It gives accurate results and predictions It helps the electric utility to better optimize the functionality of its generation units and reduce the generation cost It helps the system operator in reducing the energy losses on the network and lines, which may reduce drastically the indirect distribution electricity cost It helps the end-users to better manage their load demand and reduce their electricity bill

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G

G

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It increases the load factor, in which the power profile becomes smoother and less fluctuating It increases energy efficiency It conserves the resources It reduces pollution and protects the climate

20.2

Energy management techniques in smart grid

The smart energy management system can be developed to monitor the power quality and control the distribution of the power system by the advanced technology based wireless communication networks like: Bluetooth; ZigBee network interfaced with microcontroller; ZigBee network interfaced with field programmable gate array (FPGA); global system for mobile communication (GSM) interfaced with embedded controller; and supervisory control and data acquisition (SCADA) interfaced with programmable logic controller (PLC) techniques. By implementing energy management system, consumers can reduce their energy bill, reduce peak demand, and also they can know the information about electricity utilization.

20.2.1 ZigBee network interfaced with field programmable gate array The smart energy management system is designed for managing as well as improving the efficiency of the photovoltaic energy generation system and grid generation [7]. For this purpose Xilinx ISE utilizing Spartan 3AN FPGA and LAB VIEW software is utilized for the system design. By utilizing the energy management system, consumers can be easily monitored and managed their consumption as per their requirements. This system also stored the information related to their daily energy consumption. Further, daily consumption data is also available to the consumers. The efficiency of the smart energy management system is the main criteria of this whole technique and the utilization of the photovoltaic generation and utility sources are optimized by this system. The different information collected by the smart energy management system consists of the amount of supply required from utility, photovoltaic system battery status and the status of current, and potential transformers. Energy management center of smart energy management system received all of this information through the ZigBee network. With the help of this information the energy consumption is checked and compared with the available energy sources. This collected data is transformed into the some specific factors with the help of sensors of the photovoltaic energy system and grid generation sources. The decision of power utilization from the available sources such as photovoltaic and grid generation is made by the smart energy management system. Fig. 20.1 presented the block diagram for smart energy management system using FPGA.

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Figure 20.1 Block diagram for smart energy management system using FPGA.

20.2.2 Global system for mobile communication The energy utilized by the every consumer, is monitored by the energy management system with respect to time. Whenever the energy consumption made by the consumers is greater than the nominal energy utilization, the energy management system will send an alert signal via an alarm circuit. After this warning signal, consumers take necessary action to take off the excess supply from the electrical system for turning off the alarm. If excess supply will not cut from the system, circuit breaker comes into effect and tripped off the supply. The information related to the energy consumption pattern of the various consumers is also sent to the energy management center through the GSM. To restore the supply at normal condition consumer will send a request to center for bring the circuit breaker back into the normal state with the utilization of microcontroller. This microcontroller is programmed with parameters of electrical energy to monitor the system. This energy management system is very much useful to prevent any illegal use of electricity along with monitoring of the power consumption and data management on tariff [8]. Fig. 20.2 presented the Block diagram for GSM-based automatic trip control system.

20.2.3 Supervisory control and data acquisition SCADA is a technique that is utilized in the smart grid for the management as well as the collection of data utilized in the energy management system development. The energy information can achieve by the SCADA techniques [9].

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The SCADA system consists of remote terminal unit (RTU). In addition, RTU consists of programmable logic converters [9], so that the system will get programmable control. The SCADA is functioning to collect the information and transferring it back to the central dispatch center. Dispatch center performed the various important analyses and control the system according to the analyzed values and then presenting the information on various operator sensors as shown in the Fig. 20.3. The main feature of the SCADA system is its ability of monitoring the whole system in the real-time scenario [10]. This feature is performed by facilitating the data acquisition from smart meters, sensors status, etc. that are communicated at predefined time duration depending on the requirement of the system.

Figure 20.2 Block diagram for GSM-based automatic trip control system.

Figure 20.3 Block diagram for SCADA control system.

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20.2.4 Remote energy management system using smart meter The smart meter technology is the latest advancement in the traditional Ferrariswheel, electronic, or digital meters. It has two-way communication capabilities for receiving data as well as transfers the data. The smart meters have different communication tools like ZigBee, HAN (home area network), and WiMax. New concept of the remote energy management system is implemented using smart metering, which provide the public users power of knowing the specific energy consumption information with the ability to handle and control the energy utilization. This will depend on the data collection with the help of smart metering technology. The collected data is very helpful to the owner for maintaining the energy consumption; thus, to minimize the energy cost. Fig. 20.4 presented the block diagram for remote energy management system.

20.3

Smart energy management system

Smart energy management can be divided into two main categories. The first one is on the side of the supplier such as electric utility, in which some generators are turned ON or OFF to follow the fluctuation of the load demand. The second category is on the consumer side and it is called demand-side management.

20.3.1 Supplier-side management The electricity supplier (such as electric utility, power plant operators, and production units) can use the energy management to control its generation units in an efficient way. For example, to meet a certain power demand of the consumers, using energy management, the electric utility can turn on some generators, which may have the least operation cost, while the generators with high operation cost are left

Figure 20.4 Block diagram for remote energy management system.

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to supply extra load demand in specific peak periods. In this way, the electric utility is trying to minimize the operation cost of its generation units The system operator (such as transmission and distribution systems) can use energy management to regulate the power flow in a way to minimize the energy losses on the network and increase the penetration level of renewable energy sources (such as PV and wind farms) in an efficient way. Generally demand-side management is focused on energy saving while supply-side management related to the selection of the energy generation sources and coordinate them in such a manner so than most cost effective operation is obtained.

20.3.2 Demand response Demand response is a technique in which end-users are involved in demand-side management of electrical power consumption based on electrical pricing signal received from electric power utility company. When end-users are creating awareness about their energy consumption, they tend to manage their total usage. The demand response program in traditional grid system mostly applied for large-scale consumers such as commercial buildings and industrial plants; however, such mechanism does not exist for residential users mainly due to two reasons. The first reason is it is too difficult to handle a large number of home appliances without using automation technology, sensors, and communication system. The second reason is, compared to their implementation cost the impact of demand response program is relatively small [6]. Studies have suggested that by employing automated energy management strategies, it is possible to let the users to participate in demand response program and control their load consumption pattern based on the pricing information. In order to implement this strategy, different techniques can be adopted, for example, by using internet and controlling the energy consumption via software installed on PC. Demand response can be categorized into two. The first demand response program is pricebased demand response such as time-of-use pricing, critical peak pricing, and realtime pricing, which provides time-varying rates of electricity consumption at different periods of time. This encourages customers to use less electricity when the price of electricity is high and they tend to shift their loads to nonpeak hours when electricity pricing is low. The second type of demand response programs are incentive-based demand response program in which the utility company pays the customers who are participating in the program to reduce their loads in the time requested by the utility company or program sponsor, which is triggered by reliability problem in the grid system or highest electricity prices. Demand response techniques uses smart appliances, sensors, actuators, smart meters and two-way communication. Therefore it is considered to be part of smart-grid technologies.

20.3.3 Demand-side management Demand-side management techniques are a group of solutions that are required for enhancing the efficiency of the energy system at the consumer side. It incorporate techniques started from energy efficiency improvement techniques by utilizing good quality material, intelligent energy tariffs with the provision of incentives to

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some demand patterns, to adequate control of distributed generation sources on the real-time basis. Demand-side management techniques motivate consumer to control their energy demand for minimizing the demand of electricity instead of increasing the generation to meet the electricity demand at every time state. Demand-side management techniques are helpful to meet the demand by minimizing the load, instead of investing extra capital to develop extra capacity to supply the daily increasing electricity demand. This objective can be achieved by efficiently utilizing existing energy. Thus demand-side management programs are implemented by the utilization of different techniques for managing the energy utilization of the consumers. The most critical objectives of the demand-side management programs are the minimization of the electricity cost through management of the energy utilization, improving reliability, minimizing the grid related issues, and the development of environment and society. Demand-side management program incorporated the diverse programs related to the various energy policies such as: G

G

G

Energy efficiency policy: It is related to the utilization of the less power for offering same or better levels of energy services to the consumers in an efficient manner with respect to economy and reliability Demand response policy: This policy is related to the different procedures, which are utilized by the consumers to fulfill their demand. Consumers load management policy: In this policy for the residential consumers, utility aims to minimize the consumer’s energy utilization and with the help of this minimization, the peak loading also minimized on the system.

There are six different techniques, which are utilized by the utility for performing the demand-side management. Fig. 20.5 presented the demand-side management techniques. These techniques are as follows: 1. 2. 3. 4. 5. 6.

Peak clipping Valley filling Load shifting Strategy conservation Strategic load growth Flexible load shape

20.3.4 Peak clipping Inside the peak clipping technique, measures such as load cutting and demand minimization, are utilized at the time of a heavy load condition. The peak loading time duration can be minimized with the help of a load controller, shutdown of customer equipment and by distributed generation.

20.3.5 Valley filling In the valley filling demand-side management technique, the utility encourages the consumers to utilize the electricity at off-peak hours. Due to this, consumption of the electricity in the nonpeak hours is increased which is helpful in the reduction of

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Figure 20.5 Demand side management techniques.

the generation cost, averaging the price of electricity, and improving the efficiency of the system. To encourage consumer for the utilization of electricity at nonpeak hours, different incentive like discounts are provided to motivate consumers.

20.3.6 Load shifting The load shifting demand-side management technique shifts the workload time duration of largest loading, that is, the peak period to off peak period and transfer the load without varying the total utilization. Distributed generation can also be utilized for this purpose.

20.3.7 Strategic conservation This demand-side management technique minimized the seasonal consumption of the energy with the help of improving the efficiency of the consumption and minimizing the wastage of energy. Various incentives are utilized under this program for the technological changes, which makes this program more comprehensive.

20.3.8 Strategic load growth This technique is utilized to controls the increase in the seasonal energy utilization. Various intelligent system and processes, highly efficient equipments, and costeffective energy sources are utilized by the utility to perform the demand-side management.

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20.3.9 Flexible load shape This method of demand-side management utilized the set of actions and integrated planning among the concessionary and consumer, which is subjected to the requirement of the time moment. The modeling of customer demand is performed without affecting the actual security conditions, restricting the power and energy that the individual costumer can utilized at definite time duration by incorporating loadlimiting devices.

20.4

Summary

Energy management plays a central role in increasing the efficiency and the reliability of the power and distribution systems. To do so, smart energy management and advanced control systems are used to optimize and schedule the load demand in an efficient way. Smart grid, energy management is regarded as a core part to improve the renewable energy consumption and energy efficiency. The maximum range of advanced technology was used to develop the energy management system for the smart grid. Even though to improve the reliability, efficiency, and planning in the power system the real time smart energy management system is required. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

20.5

Chapter review questions/exercises

20.5.1 True/false 1. True or false? In a world where the energy demand is on the decline, the power generation should also decrease to satisfy the users’ needs and improve their daily life. 2. True or false? The smart energy management system can be developed to monitor the power quality and control the distribution of the power system by the advanced technology-based wireless communication networks like: Bluetooth; ZigBee network interfaced with microcontroller; ZigBee network interfaced with FPGA; GSM interfaced with embedded controller; and SCADA interfaced with PLC techniques. 3. True or false? The smart energy management system is designed for managing; as well as, improving the efficiency of the photovoltaic energy generation system and grid generation. 4. True or false? The energy utilized by a few consumers is monitored by the energy management system with respect to time. 5. True or false? SCADA is a technique, which is utilized, in the smart grid for the management as well as the collection of data utilized in the energy management system development.

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20.5.2 Multiple choice 1. Smart meters have different communication tools like: a. ZigBee b. HAN c. WiMax d. All of the above e. None of the above 2. The electricity supplier (such as electric utility, power plant operators, and production units) can use the energy management to control its ___________ in an efficient way. a. Production units b. Operational units c. Electrical units d. Distributed units e. Generation units 3. Demand-side management techniques are a group of solutions that are required for enhancing the efficiency of the energy system at the: a. Consumer side b. Infrastructure side c. Intelligent side d. Material side e. Quality side 4. The peak loading time duration can be minimized with the help of a load controller, shutdown of customer equipment and by: a. Distributed generation b. Mobile services generation c. Infrastructure generation d. Demand minimization generation e. All of the above 5. In the valley filling demand-side management technique, the utility encourages the consumers to utilize the electricity at: a. Nonpeak hours b. Peak hours c. Peak period d. Off-peak hours e. Off peak period

20.5.3 Exercise 20.5.3.1 Problem Is the smart grid an enabler or a result of change?

20.5.4 Hands-on projects 20.5.4.1 Project What are the enabling technologies for the smart grid?

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20.5.5 Case projects 20.5.5.1 Problem Develop an assessment framework for the smart grid, which addresses the major challenges and issues for smart-grid implementation.

20.5.6 Optional team case project 20.5.6.1 Problem Address the challenges that are facing smart-grid technologies and provide the solutions.

References [1] International Energy Agency, World Energy Outlook 2019, 2019. [2] M.A. Akanca, S. Ta¸skın, Akıllı sebeke uygulanabilirli˘gi ac¸ısından Tu¨rkiye elektrik enerji sisteminin incelenmesi, Elektrik Mu¨hendisleri Odası Dergisi, 2011. [3] A.S. Massoud, Toward a smart grid: power delivery for the 21st century, in: Wollenberg B.F., IEEE Power and Energy Magazine, 2005. [4] A. Khan, A. Mahmood, S. Razzaq, Home energy management systems in future smart grids, Nadeem Javaid, COMSATS Institute of IT, Islamabad, 2013. [5] F.A. Qayyum, M. Naeem, A.S. Khwaja, A. Anpalagan, L. Guan, B. Venkatesh, Appliance scheduling optimization in smart home networks, Special section on smart grids, IEEE, October 29, 2015. [6] Z. Zhao, W. Lee, Y. Shin, K. Song, An optimal power scheduling method for demand response in home energy management system, IEEE Trans. Smart Grid 4 (3) (2013). [7] Y.H. Khattak, T. Mahmood, I. Ullah, H. Ullah, Smart energy management system for utility source and photovoltaic power system using FPGA and ZigBee, Am. J. Electr. Power Energy Syst. 3 (5) (2014) 86 94. [8] S. Sukhumar, P. Mukesh Aravind, L. Manivannan, GSM based automatic trip control system for energy management, Int. J. Innovat. Res. Sci., Eng. Technol. 2 (12) (2013) 7690 7695. [9] S. Aman, Y. Simmhan, V.K. Prasanna, Energy management systems: state of the art and emerging trends, IEEE Commun. Mag. (2013) 114119. [10] M. Macedo, J. Galo, L. de Almeida, Ad.C. Lima, Demand side management using artificial neural networks in a smart grid environment, Renew. Sustain. Energy 41 (2015) 128 133.

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P. Lazzeroni1, M. Repetto2 and H. Gabbar 3 1 LINKS Foundation, via Pier Carlo Boggio, Torino, Italy, 2Politecnico di Torino Dipartimento Energia “Galileo Ferraris,” Corso Duca degli Abruzzi, Torino, Italy, 3Energy Systems and Nuclear Science Research Centre (ERC), North Oshawa, Ontario, Canada

21.1

Introduction

The concept of hybrid energy networks is considered one of the most promising paradigm to decarbonize our society and to increase energy efficiency of many processes and conversions. As for now, each energy network (electrical, gas, heating, cooling, hydrogen, etc.) has been studied and optimized as a standalone object. As a matter of fact, many advantages can be gained by considering the integration of different networks, for instance, the conversion of electrical power in other forms of energy can act as energy storage leading to the power-to-gas and power-to-heat processes. As the interconnection of different energy vectors requires coordination, the smartness of new energy systems is needed, in first place an energy management system (EMS) has to be devised and implemented. This topic is treated by different organisms at the international level. Among other initiatives, International Energy Agency is addressing this opportunity by means of a working group on the interaction of different energy grids in [1]. Research at the European level is also facing this task within different initiatives, as for instance the renewable heating and cooling platform [2]. Research is also active on the cross coupling among different energy vectors, especially on the technologies that can enable the transition of the energy sector toward a system that can host larger shares of renewable energy sources (RES). Recent scientific papers have been devoted to this topic, as for instance, a special section in the IEEE Transactions on Industrial Electronics. In this line, the very concept of Energy Hub as a way of interconnecting in a smart way different energy vectors is cited as one of the most important topic in nowadays research [3]. The use of hybrid energy networks, also called polygeneration, is very promising for the increase of renewable energy share in the final energy use as the integrated combination of different energy sources can accommodate RES, that are often intermittent and noncontrolled, matching their contributes with user demand. In this way, conventional energy generation can serve as backup to the RES while energy storage acts as a buffer to balance the different time of power production and usage as well described in [4]. Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00021-8 © 2021 Elsevier Inc. All rights reserved.

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As polygeneration is made by the integration of different energy sources, its control is more difficult than that of conventional energy plants. In fact, with a single energy source the control strategy is usually defined by imposing the satisfaction of the user demand. This target is reached by adjusting few control parameters with respect to set points. With more than one power generation available, the satisfaction of the user request can be met in different ways. Provided that they fulfill its requirements, all possible production mixes are equivalent to the end-user but they are different for the owner of the system. They are in fact characterized by different performance as economic cost, RES exploitation, efficiency, greenhouse gases emissions, etc. In addition, the presence at the same time of different energy vectors, for instance, heating and electricity, makes the production choice more and more complex and the integration of all production sources more needed. On the economic side, the interaction between the owner/manager of the system and the end-user is usually ruled by bilateral contracts that require the satisfaction of energy demand, but this is not the only boundary of the system across which energy vectors or energy related products are exchanged. For instance in the production of combined heat and power (CHP), the polygeneration is often exchanging electrical energy with a grid at a price that is changing on the hour basis. Selling electrical power to the grid when it is economically convenient is a way of decreasing the overall cost of generation and to increase the efficiency in the use of fossil fuel. Beyond the electrical grid, other boundaries of interaction of the system can be defined. The environment can be seen both as a source of renewable energy and as a dump for gaseous emissions due to fuel combustion. A complete model of the energy system should take into account all these exchanges. The simulation of complex energy systems, as the one earlier introduced, can be made at different levels and can meet different targets. A thermodynamical and hydraulic model of a district heating and cooling (DHC) network is of sure interest for the regulation of its physical parameters but can be cumbersome for the evaluation of its environmental and economical performances. A physical model must be defined on a time scale comparable with the dynamic behavior of the underlying phenomena which is often much smaller than the one of the user demand or of the energy price variation, see for instance [5]. On the other hand, a model made on a monthly or yearly scale can give an answer to the average satisfaction of the user request but it is unable to take into account the dynamic of renewable sources which are often varying during one single day, as for instance by using a planning software procedure as [6]. As a matter of fact, the time scale that matches the most of the technical and economical performance is the hour basis. On the hour basis the model is able to catch the variations of the user requests, the modifications of the renewable input and their matching by means of a daily energy storage. At the same time, the prices of the electrical market are defined at each hour of the day and thus possible opportunities in energy trading are contained in the model. This our based model is then set as the starting point of the optimization of the system performances. As a research topic, optimization of the profile of production of energy sources has always been important but has become crucial when dynamics in price variation has been imposed by the rule of the market. Started with the optimization of

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hydropower generation [7], the research on the topic has gained interest also in the conventional power generation [8]. In the field of distributed generation the definition of an optimization tool based on multiple energy carrier has been presented in [9], while a hour-based techno-economical model of the polygeneration system has been proposed in [10,11]. The last model, based on a simplified mixed-integer-linearprogramming (MILP), has been implemented in a procedure able to simulate different energy systems both made up of conventional and RES energy sources [12,13]. In the following sections a description of the formulation of the optimization procedure will be given while afterward some examples of application of the procedure will be outlined.

21.2

Energy management system: the optimization procedure XEMS13

The optimization of the energy management for a polygeneration node needs an energy model of the system and a target performance to be reached. The optimization process searches the production profiles of all controllable power sources that minimize the cost function while fulfilling all the technical constraints of the structure. A procedure based on this approach has been developed and is called XEMS13. In order to describe the energy model some hypotheses must be stated: G

G

G

G

The model of the polygeneration node is implemented through phenomenological equations that describe the input/output relations of energy conversion modules. These equations are based on power flows. Thermodynamic constraints are embedded in the constitutive equations of the modules. The system is considered to be in thermodynamic steady-state, transient phenomena are considered to be negligible on the minimum time frame Δt which is of the order of one hour. The optimization is carried out on a limited time horizon, which is the scheduling period, discretized in Nist interval of amplitude Δt. Each variable is considered to be constant through the interval and in most cases it is expressed in terms of an exchanged energy as P Δt being P the average power in the interval. Dynamic phenomena are taken into accounts in some components that are related either to energy storage or that are characterized by ramp limits.

21.2.1 Components Each component in the model is described by one or more than one constitutive equation, as: Pout 5 f ðPin Þ

(21.1)

if the module is handling more than one energy vector, multiple equations are defined. This happens, for instance, in the case of an absorption chiller: it creates

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cooling power by converting heat but the process requires also an electric power to drive all the pumping system. The interaction of three energy vectors: heat, cooling, and electricity, is thus obtained. Since the output quantity of the power module is the one of interest to match the user demand, often the constitutive equation is formulated using the output variable as the independent one. Often the generic function f referred in Eq. (21.1) is nonlinear and thus it is represented by a piecewise linear approximation to match the requirements of the optimization algorithm (Fig. 21.1). Constitutive equations are usually static, they define thus a link between input and output power flows at the same instants. Whenever energy storage is present, the module equations become dynamic because the energy state of the component is defined as: Pst 5

dS dt

(21.2)

where Pst is the power exchanged by the energy storage and S is its energy content. By expressing Eq. (21.2) in a discretized form on a time step Δt 5 tk11 2 tk, it becomes (Fig. 21.2): Sðtk11 Þ 5 Sðtk Þ 1 Pst ðtk ÞΔt

(21.3)

The components can be either controllable or dispatchable if one of their variables can be defined by the optimizer. A CHP module is dispatchable since

Figure 21.1 Schematic layout of a generic power conversion module.

Figure 21.2 Piecewise linear approximation of a nonlinear characteristic.

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its power production can be defined by the optimization strategy. Some of the power modules are considered and non-dispatchable if their power flows cannot be changed by the optimizer, as for instance, in a photovoltaic (PV) panel whose electric power output is defined on the basis of the sun irradiance that is an environmental datum. Besides nonlinearity in the constitutive equation, the power modules can be characterized by other nonlinear or logical parameters that express some technical constraints. Referring to a CHP module, the first nonlinearity is related to the limited variation of power output: even if the constitutive equation is linear, its existence interval is usually limited between 50% and 100% of its nominal power. If Pek is the electrical power produced by the generic kth CHP present in the system, its variation limits are expressed as: max δk Pmin ek # Pek # δk Pek

(21.4)

max where Pmin ek and Pek are the limits of variation range and δk is a logical variable that expresses the on/off status of the CHP. At the generic kth time interval, δk can be expressed as a binary variable that is a control variable itself. It is in fact choice of the algorithm to switch on or off the CHP. In this way the optimization variables are not only real valued but can be also take integer 0/1 values. Binary values are also needed to select a particular working interval within the discretization of the piecewise linear characteristic of one module. The choice of the particular working point is in fact decided by the optimization algorithm, as it will be explained later. Other technical constraints can be expressed by means of binary variables, for instance a priority in the switching on of machines. In the case of two CHP machines the first one can be used to cover the base load while the second one balances the peak request. The variation limits of the second CHP can be expressed as: pri max min δpri 1 Pe2 # Pe2 # δ 1 Pe2

(21.5)

max δpri 1 # Pe1 =Pe1

(21.6)

where the variable δpri 1 assumes value 1 only when the first machine has reached the full power. In this way a priority constraint on the transition from off to on is set. Several other technical constraints can be defined by means of binary variables and most of them can be found in [10].

21.2.2 Energy vector balance equations Each energy vector that is present inside the polygeneration node is subject to a balance constraint where all contributes of the same energy vector can be summed up. For their nature, balance equations are linear: each contribute can appear there only once with a 1 or 2 sign depending on the direction of the power flow.

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In analogy with the usual Kirchhoff current law applied in electrical circuits, this balance equation is written taking into account a convention for the orientation of the power flow. For the electrical node shown in Fig. 21.3, the balance equation at the generic time interval tk becomes: PPV ðtk ÞΔt 1 Phydro ðtk ÞΔt 1 Pgrid ðtk ÞΔt 2 Ue ðtk ÞΔt 5 0

(21.7)

and Pgrid can take both positive or negative sign: if its sign is positive it is considered that the power is purchased by the grid Pp 5 Pgrid, if its sign is negative it is considered that it is sold to the grid Ps 5 2Pgrid. The two variables Pp and Ps are needed because different prices are used for purchasing/selling energy to the grid. Purchasing energy is in fact higher than the selling one because of grid cost and taxes. In the present implementation, the energy vectors that are defined are: G

G

G

G

G

G

Electricity, exchanged among the nodes and with external grid Heating, or power flow carried by hot water Cooling, or power flow carried by refrigerated water Low enthalpy heating, defined as a power flow carried by water at a temperature level lower than the heating one Steam, power flow carried by steam Condensing power, power needed to cool down the refrigerating fluids of cooling modules

Other energy vectors that interact with the system, for instance natural gas, are considered in the simulation with their economic counterpart but, unless their availability is limited, their flows are not used as control variables.

Figure 21.3 Example of an electric node where power flows from PV generator, hydro turbine, electrical grid, and end-user are balanced.

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21.2.3 Cost function The operating cost needed to cover the expenses for running the system through the time horizon is given by the sum of the cost on each time interval. The sum must take into account: G

G

G

G

Fuel cost of conventional modules defined as the cost of fuel per unit energy, multiplied by the energy produced in the time interval Cost of energy purchased by external grids, for instance the electrical one (Pp as previously defined) Revenues obtained by the selling of energy to external grid, for instance the electrical one (Ps as previously defined). Possible incentive schemes like Feed in Tariffs can be taken into account. Revenues are expressed by negative costs. Costs related to maintenance that can be expressed as unit cost per produced energy of for every running hour.

In the case of one system made up of one natural gas fired CHP producing electrical energy, the cost function can be expressed as: C5

Nist X

cf PeCHP ðtk ÞΔt 1 cp ðtk ÞPp ðtk ÞΔt 2 cs ðtk ÞPs ðtk ÞΔt

(21.8)

k51

where cf is the unit cost for the production of electrical energy expressed in h/kWh, since this is related to the cost of natural gas it is assumed to be constant through the time horizon. cs(tk) and cp(tk) are respectively the selling or purchasing unit cost of electrical energy. These values are time-dependent since electricity market price is varying on the hour basis. Notwithstanding the possible time variation of unit costs, the cost function is expressed by a linear function.

21.2.4 Optimization The cost function defined in Eq. (21.8) can be minimized by changing the production profiles of all the modules present in the polygeneration system. This minimization process is constrained by all other equations previously defined and particularly: G

G

balance equations, one for each energy vector constitutive equations, at least one for each module

While balance equations are linear, as already mentioned, constitutive equations can be expressed by piecewise linear functions where binary variables are used to select a particular working interval. As a result, the minimization of cost function (8) can be approached by a MILP [14]. The set of cost function, constitutive equations and constrains are written in a standard file “.mps” where the information is written and delivered to an external MILP solver such as solving constraint integer programs [15], MatLab solver or

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other solvers that are able to solve the problem and return the optimum solution along with the individual values for the variables in the problem.

21.3

Case study

The case study introduced here represents an example of the application of the optimization tool XEMS13. As EMSs, XEMS13 is adopted to perform a feasibility study for the implementation of a polygeneration system supplying an existing DHC network located in the North-West of Italy [16]. The study is focused on the design of the main units composing the multienergy facility to fulfill hot and chilled water demand in the DHC network. The XEMS13 output, that is, the optimal scheduling of the energy sources to minimize the operational cost of the polygeneration system, is used here to evaluate the yearly cash flows and the corresponding economic indicators of different proposed configurations. As a results, a comparison of the proposed solutions from the economic and energy point of view allows to evaluate the sustainability of RES integration within the polygeneration system. The analyzed network presently supply an area with different building typologies connected to a DHC network to cover space heating/cooling and domestic hot water (DHW) energy demands. Table 21.1 summarizes the yearly energy demands for the buildings connected to the DHC network as measured by the energy manager in 2016. It is noticeable that buildings of tertiary sector are the larger energy consumers in the area, since they account for 78% and 70% of the whole demand for space heating/DHW and space cooling, respectively. The DH network is operated with a supply temperature of 80 C and a return temperature of 65 C, while supply and return temperatures for the DC network are 5 C and 12 C, respectively. These, temperatures have been assumed as fixed within the feasibility study, even if different levels could be potentially considered for increasing energy performance of the network. This constraint is due to a Table 21.1 Yearly energy demands of the buildings connected to the DHC network. Building ID

Building typology

Space heating and DHW (MWh)

Space cooling (MWh)

A1 A2 C1 C2 E V M W Z Q

Residential Residential Commercial Commercial Tertiary Tertiary Commercial Tertiary Tertiary Residential

111.75 108.98 110.53 366.71 630.98 1761.00 119.94 128.93 553.90 48.21

29.80 31.37 35.12 211.03 370.22 239.10 45.82 91.91 170.70 21.68

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pre-existing contractual agreement between the manager of the DHC network and the customers and it cannot be presently modified. A simplified layout of the DHC network supplying the buildings presented in Table 21.1 is shown in Fig. 21.4, where G is the proposed location for the installation of the generation units part of the polygeneration system. The space cooling energy demand of the buildings currently connected to the DC network is met by the production of chilled water locally supplied through a generation plant consisting of two compression chillers with the following main characteristics: G

G

a unit with 1750 kW of cooling capacity and a seasonal COP of approximately 4.5 a unit with 550 kW of cooling capacity and a seasonal COP of approximately 4.5

The compression chillers are supplied by electricity from the local distribution grid through a medium voltage connection also used to provide electricity to the pumping systems of the DHC network as well as the cooling towers. On the contrary, hot water supplying the DH network is not produced locally, but it is purchased through a supply contract from third party. In this case, the generation plant of hot water is only represented by the pumping system capable to

Figure 21.4 Layout of the DHC network for the case study.

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pressurize and move the hot water in the DH network. Fig. 21.5 summarizes the present layout of the generation plant considered in this case study. The DHC network of Fig. 21.4 is presently formed by preinsulated double pipes that connect the generation plant with the different end-users typology. A simplified mathematical modeling was defined for calculating the thermodynamic quantities that describe performance of the system. In particular, the calculation of the heat losses in the DHC was performed by a simplified evaluation of the water flow rate and the temperature drops in each pipe. This assessment was carried out considering two different operating conditions during a day: 1. A stationary condition when the set-point temperatures of the DHC networks are reached 2. A transient condition when temperatures decrease/increase by shutting down/up the plants

The condition (a) is substantially reached in the late morning and maintained approximately for 8 hours until the plants shut down. In this case, the water flow rate in the pipes is based on the network topology and on the calculation of an average daily power consumption, which is derived from the energy consumption of Table 21.1. For this stationary condition, the temperature drop of a pipe and consequently the heat losses are approximated through a inversely proportional function of the water flow rate (i.e., obtained as a first order Taylor’s series approximation of the exponential function [17] for the evaluation of the temperature drop of a pipe in stationary condition). The condition (b) is instead approximately maintained for 16 hours. In this case the evolution of the temperature in the network is calculated

Figure 21.5 Present configuration of the generation units.

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considering the water flow rate close to zero. As a consequence the temperature drop in pipe is calculated as ones for a storage tank through exponential function (i.e., as obtained from the solution of the differential form of the Fourier’s law). Under these operating conditions, the calculated yearly heat losses of the DH network are approximately close to 20% of the demanded energy, while losses of DC network are around 5% of the supplied energy (see Fig. 21.6). Clearly, energy losses of the DH network appear higher than ones in DC network since the gap between the water and ground temperature is greater in the DH network compared to the DC one.

21.3.1 Optimal scheduling The current configuration of the area presented in Figs. 21.4 and 21.5 is particularly stressed from economic point of view. The increasing energy supply costs of the hot water provision for the DH network purchased by third party forced the energy manager of the DHC network to an upgrade of the present configuration of the energy production plant, including the introduction of RES. Configurations adopting energy production unit with a reduced levelized cost of energy are the possible solutions investigated in the feasibility study to cover hot water demand. Hence, the study evaluates the technical and economic aspect of the new possible polygeneration configurations. The study was performed through the XEMS13 optimization tool described in the previous sections. The tool developed by the Energy Department of the Politecnico di

Figure 21.6 Yearly demand and losses of the DHC network.

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Torino and LINKS [12,1820] simulates polygeneration systems by means of an optimized management of the sources minimizing operational costs and considering technical and operational constraints. According to the aforementioned characteristics of the optimization tool, the objective function is the one defined by Eq. (21.8).

21.3.2 Hourly load profiles As already observed, the time profiles of the energy demand for the whole area are needed to simulate the optimal management of the different energy sources in the upgraded configurations of the production plant. The heating and cooling demand of the area can be defined as the sum of the energy needs of the buildings and the heat losses of the DHC network. The hourly load profiles of each building supplied by the DHC network were identified from daily normalized load profiles present in literature or derived from measurement in similar climatic zones. These normalized load profiles are classified by building typology and period of the year. In fact, it is worth nothing that space heating and cooling demand change for different season and type of end-user. Then, under the hypothesis that all the days in a given season have the same profile, the normalized load profiles were opportunely rescaled by means of a correction factor fc, to ensure that the energy annually required by each building coincides with the measured data of Table 21.1. In this way, the yearly energy Ey absorbed by a building can be calculated as follows: Ey 5 fcU

8760  X  Pp:u: ðti Þ  Δt

(21.9)

i51

where Pp.u. is the value of the normalized load profile in a given time interval and Δt is the length of the time interval (i.e., 1 hour in this case). Later, the profiles of the energy demand for the whole area were obtained by summing up each building load profile and the heat losses of the DHC network, under the approximation that the load profile of network losses is flat. The yearly aggregated load profiles for the heating and cooling demand were finally subdivided in 14 representative weekly profiles, since the heating season for the area starts at October 15th and stops at April 15th. Thus, 12 weeks were defined to represent each month of the year, but two additional weeks were used to consider the no-heating period in the first half of October and in the last half of April. Fig. 21.7 shows two of the representative weekly load profiles of the area. These weeks refer to the periods in which the peak of heating/DHW demand and the peak of cooling needs are reached, respectively. In particular, Fig. 21.7A shows how the peak for space heating and DHW presently can reach approximately 4 MW, while Fig. 21.7B shows how the peak for space cooling can potentially reach 2 MW. The latter condition evidences how the cooling demand is close to the maximum capacity of the present configuration. Hence, critical operation could be potentially observed in summer during adverse environmental condition.

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Figure 21.7 Aggregated weekly load profiles of the area for: (a) space heating and DHW in January and (b) space cooling in July.

The electric load profiles for the pumping systems of DHC network were instead derived from the heating and cooling one, assuming that electric profiles follow the thermal one and the electricity consumption of the pumping systems is equal to 3.5% of the corresponding thermal demand, as resulting from electricity bills.

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21.3.3 Energy prices As in the analysis for defining the load profiles of the different energy vectors, the assessment of the present energy prices was performed to individuate the unit price for each energy carriers of the area. The electricity currently purchased by the grid for feeding the compression chillers and the pumping systems is subjected to a time-of-use (ToU) Italian tariff. The electricity prices presented in Table 21.2 include the variable access grid costs, variable general system costs, and the excises. Other fixed costs are not considered since this quota does not change in the upgraded scenario when compared to the reference present scenario. The hot water for supplying the buildings connected to the DH network is instead currently purchased by third parties at a price that can be considered approximately close to 65 h/MWh. For this reason, the upgraded scenarios proposed in this paper were compared with this current value considering also other fixed costs to be paid to the third parties which account for around 33kh per year. Since in the proposed new scenario electricity generation systems could also be introduced, the prices for the electricity sold to the grid were also identified. These prices refer to the historical data provided by the Italian Energy Market Operator Gestore dei Mercati Energetici S.p.A. [21] for the year 2015. Fig. 21.8 shows an example of these time profiles for some periods of the year. Finally, the unit price of the natural gas for supplying the heat generation systems to be introduced in the upgraded scenarios was estimated at approximately 0.37 h/Nm3. This value, that does not include excises, is derived from the natural gas price database of the Italian Energy Authority (ARERA) [22]. The price used refers to an estimated demand of around 1 Mm3/year obtained for polygeneration plants with an installed capacity similar to the existing one. The natural gas price was later increased by adding the excises value, which depend on how the use of natural gas is classified in each new configuration according to the definition introduced by ARERA.

21.3.4 Proposed configurations As already described, the current energy supply costs of the hot water provision purchased by third party are forcing to an upgrade of the present configuration (see Fig. 21.5) of the energy production plant. In this section, four different new configurations are presented in Table 21.3 and Figs. 21.9 and 21.10 for producing hot and Table 21.2 Electricity ToU tariff of the case study. Day

On-peak

Mid-peak

Off-peak

Mon-Fri Sat Sun Price (h/MWh)

819   151

78; 1923 723  146

237 237 024 136

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Figure 21.8 Hourly selling electricity price for different periods of the year in Italy.

cold water by systems with incremental complexity where also RES are involved. In the proposed configurations, all the generation facilities are located and connected in the same point of the network (node G of Fig. 21.4) due to the fact that the network is spread over a small area.

21.3.5 Scenario 1: adding a local boiler In the first scenario presented in Fig. 21.9, the production of hot water for feeding the DH is obtained by means of a boilers unit supplied by natural gas. The size selected for the boilers group was 6 MW with an estimated efficiency of 92%, since the peak of the heat demand is approximately close to 4 MW as already shown in Fig. 21.7A. In this scenario, the excises to be applied in addition to the cost for natural gas presented in Section 3 are equal to 0.2118 h/Nm3 according to the Italian regulations [23]. This is due to the classification introduced by the Italian Energy Authority which classify as “civil use” the natural gas used to supply the boilers in this configuration.

21.3.6 Scenario 2: further addition of a CHP, absorption chiller, and storage Scenario 2 (see Fig. 21.9) represents an evolution of the Scenario 1 where a cogeneration unit (CHP) is added together to an absorption unit for recovering heat produced by CHP and a thermal storage unit to increase the flexibility and the

Table 21.3 Installed power capacities for the different scenarios. Technical characteristics Unit Electric chiller #1 Electric chiller #2 Boilers CHP Absorption chiller Thermal storage Solar thermal Heat pump

Scenario 1

Scenario 2

Scenario 3

Scenario 4

Pn 5 1750 kWf

COP 5 4.5

Pn 5 1750 kWf

COP 5 4.5

Pn 5 1750 kWf

COP 5 4.5

Pn 5 1750 kWf

COP 5 4.5

Pn 5 550 kWf

COP 5 4.5

Pn 5 550 kWf

COP 5 4.5

Pn 5 550 kWf

COP 5 4.5

Pn 5 550 kWf

COP 5 4.5

Pn 5 6000 kWt  

η 5 0.92  

Pn 5 5000 kWt Pe 5 635 kWe Pt 5 766 kWt

Pn 5 5000 kWt Pe 5 635 kWe

η 5 0.92 ηe 5 0.395

Pn 5 500 kWf

COP 5 0.7

Pn 5 5000 kWt Pe 5 635 kWe ηt 5 0.476 Pt 5 766 kWt COP 5 0.7

η 5 0.92 ηe 5 0.395 ηt 5 0.476



η 5 0.92 ηe 5 0.395 ηt 5 0.476 Pt 5 766 kWt Pn 5 500 kWf

Pn 5 500 kWf

COP 5 0.7



E 5 3.5 MWht

V 5 180m3

E 5 3.5 MWht

V 5 180 m3

E 5 3.5 MWht

V 5 180 m3

 

 

 

 

Pn 5 180 kWp 

S 5 500 m2 

Pn 5 180 kWp Pn 5 390 kWt

S 5 500 m2 COP 5 2.5

Introduction to energy management in smart grids

Figure 21.9 Proposed upgraded scenarios 1 (A) and 2 (B).

463

Figure 21.10 Proposed upgraded scenarios 3 (A) and 4 (D).

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efficiency of the overall system. The installation of a CHP unit benefits of reduced excises for the natural gas used to supply both boilers and the CHP, if the following conditions are met: G

G

The ratio between rated thermal power of CHP and total installed thermal power (CHP 1 boilers) must be $ 0.1 The yearly electricity production of CHP must be $ 10% of the thermal energy produced by the polygeneration system.

In this case, the natural gas used to supply the polygeneration system is subjected to excises for “industrial use” equal to 0.018 h/Nm3 [23]. However, part of the gas feeding the CHP, that is calculated as 22% of the electricity produced by the CHP, is subjected to reduced excises for “electricity production” equal to 0.0004433 h/Nm3 [23]. Scenario 2 can benefit of a further incentive related to the qualification as high-efficiency cogeneration (CAR) unit [24]. The CAR qualification is achieved when cogeneration respects the following limits [25]: G

The global efficiency ηg of the CHP must be $ 0.75 for CHP consisting of internal combustion engines fed by natural gas: ηg 5

G

E1H F

(21.10)

where E is the gross electricity yearly generated, H is the thermal energy yearly produced, and F is the annual total energy of the natural gas used to fed the CHP. The primary energy saving (PES) must be positive for small cogeneration units (i.e., size # 1 MWe):

PES 5 1 2

!

1 CHPHη RefHη

1

(21.11)

CHPEη RefEη

where CHPHη and CHPEη are the annual thermal and electric efficiency of the CHP, while Ref Hη and Ref Eη are the reference value of the efficiency for separate production of heat and electricity [26]. The CAR qualification allows to obtain energy efficiency certificates (TEE or white certificates) proportionally to the savings calculated as follows: ! TEE 5 0:086UKU

E ηe;rif

H 1 2F ηt;rif

(21.12)

where K is a factor based on the CHP size, while ηt,rif and ηe,rif represent the average thermal efficiency of the Italian heat production systems and the average electric efficiency of the Italian electricity production systems, respectively. Presently the average value of each energy efficiency certificate in the Italian market is close to 220h [21], but a peak of more than 250h was also recently reached. However, a more prudent value of 150h is used here.

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21.3.7 Scenario 3: further addition of solar heating Scenario 3 (see Fig. 21.10) integrates RES production within the Scenario 2. In particular, heat production from solar thermal collectors was introduced to cover part of the heating demand of the DH network. For this reason, hot water production from solar collectors is supposed to be at the supply temperature of the network (i.e., 80 C), with a tilt angle of 50 and azimuth equal to 0 to ensure production also in mid-season. The total gross area of solar field was chosen so that the daily production meet approximately 50% of the daily heat losses of the DH network during the worst operating condition (i.e., summer period in July). This choice avoids large plant size of the solar field, unable to be feasibly realized. A gross surface of the modules equal to around 500 m2 was calculated for generating the required energy by means of an analysis of the solar irradiation [12,27] of the area considering the tilt angle, the azimuth angle and the supply temperature of the water. Moreover, the Scenario 3 benefits of an additional incentive for the installation of solar thermal collector according to the Italian scheme named “Conto Termico” [28]. The yearly incentive I is proportional to the annual energy production of a single module calculated as follows: I 5 Ci  Qu  Sl

(21.13)

where Ci is the coefficient to economically valorize the thermal energy produced Qu and Sl is the gross area of the of the solar field.

21.3.8 Scenario 4: further addition of heat pump The last scenario improves the Scenario 3 where the high set point (i.e., 80 C) of the supply temperature for the solar collector reduces the heat production during winter. The proposed solution is a reduction of the supply temperature, during the heating season (October 15th to April 15th), down to 55 C and then use a water-towater heat pump to warm-up the water up to the DH supply temperature of 80 C. Instead, the solar collectors have a set point of 80 C for the supply temperature outside the heating season. In this new configuration, low enthalpy heat (at 55 C) can be also recovered from the cooling system of the CHP, which otherwise should be wasted in the environment. This low enthalpy heat feeds the same water-to-water heat pump coupled by the solar collectors.

21.3.9 Results The proposed scenarios were implemented in the XEMS13 optimization tool to evaluate the optimal scheduling of the difference sources in the four proposed configurations and the corresponding yearly operational costs, considering technical, and operational constraints of each components of the polygeneration system. These results were compared to one obtained for the reference configuration of Fig. 21.5 to highlight the corresponding costs saving of the different scenarios as

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shown in Table 21.4. Fig. 21.11 shows an example of the XMES13 solutions concerning the scheduling of the hot water production for supplying the DH network in summer for Scenario 4. It is noticeable that the TES unit reduces CHP production (Ptle) by storing its daytime overproduction (PSttin) and using it during nighttime (PSttout). Moreover, the effect of the heat produced by the solar field (Psh) contributes to cover the heat demand (Ut) especially during daytime of the weekend. An economic analysis identifying the main economic indicators was also performed to evaluate the investment profitability of the different proposed scenarios. In particular, the net present value (NPV), the internal rate of return (IRR), and the pay back time (PBT) were used to compare the different solutions. A discount rate of 4% was considered for the definition of the NPV, while a technical lifetime of 20 years was used for the evaluation of the IRR. Investment and the yearly operations and maintenance (O&M) costs for the technologies proposed in the different scenarios derive from [26]. The former were used to evaluate the installation cost of the proposed upgrade in each scenarios, while the latter were added to the operational costs estimated by XEMS13 for calculating the yearly cash flows in the NPV and IRR. O&M costs are generally considered as a percentage of the investment cost, but in some cases (e.g., CHP) this costs refer to the energy generated (i.e., expressed as h/kWh), so they are directly added in the

Table 21.4 Economic results obtained for the different configurations.

CAPEX (kh) O&M (kh/y) Costs savings (%/y) PBT (years) NPV (kh) IRR (%)

Scenario 1

Scenario 2

Scenario 3

Scenario 4

600 12 3.63 . 20 2 305.3 26

1385 29.6 34.9 9.5 1830.9 10.7

1560 31.3 35.9 9.85 1808.9 9.8

1638 35.2 36.1 11.2 1827.7 9.6

Figure 21.11 Optimal scheduling of the different sources in the Scenario 4 by XEMS13.

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objective function. Finally, savings of operational costs were also evaluated considering the costs of the present configuration as reference. Table 21.4 shows the results carried out by the economic analysis. In particular, Scenario 1 is economically unsustainable because of the impact of the excises on the natural gas used to feed the boilers, since this scenario is classified as civil use, according to the ARERA classification [22]. On the other hand, Scenario 2 is more economically attractive thanks to the introduction of a CHP system combined with the boilers unit, which greatly reduces the excises on the natural gas. In fact, the electricity produced in this Scenario represents 38.3% of the heat produced by the whole systems and the ratio between rated thermal power of CHP and total installed thermal power is equal to 0.15. Consequently, reduced excises are paid by Scenario 2 according to the condition presented in Section 3. Moreover, the whole system could be qualified as highefficiency cogeneration unit (CAR), since PES and the global efficiency are equal to 23.9% and 87.1%, respectively. Energy Efficiency Certificates can also be obtained to further support the investment. Scenario 3 introduces hot water production from solar thermal collectors starting from the configuration of Scenario 2. The investment cost for the installation of the solar field can be partially recovered thanks to the additional Italian incentive named “Conto Termico” [29]. However, the economic indicators obtained for this configuration are slightly worse than ones of Scenario 2, due to the reduced heat production from the solar field during winter. Reduced excises, CAR qualification, and energy efficiency certificates can be also obtained for this configuration. In fact, the electricity produced in this scenario is equal to 33.3% of the heat produced by the whole systems, the PES is equal to 23% and the global efficiency is equal to 87%. Scenario 4 modifies the configuration of Scenario 3 by reducing the set point of the supply temperature from 80 C to 55 C during the heating season (October 15th to April 15th). Furthermore, low-temperature water (i.e., at 55 C) is also recovered from the cooling system of the CHP in order to supply a water-to-water heat pump and to increase the overall efficiency of the plant. In this configuration, the economic indicators improve if compared to Scenario 3, thanks to the increase of both heat production of the solar field and plant efficiency. Again, reduced excises, CAR qualification, and energy efficiency certificates can be also obtained for this configuration. In fact, the electricity produced in this scenario is equal to 35.9% of the heat produced by the whole systems, the PES is equal to 25.9%, and the global efficiency is equal to 91.5%. Scenario 2 and Scenario 4 could therefore represent the possible solutions to be adopted, taking into account that Scenario 4 could be reached at a later stage once Scenario 2 was previously completed. Finally, Fig. 21.8 shows the share of the different sources for covering of the load demand from end-users connected to the DHC network. These values define if each different scenario can be considered as an “efficient DHC” configuration following the definition introduced by the European Directive [30]: “efficient DHC” means a district heating or cooling system using at least 50% renewable energy, 50% waste heat, 75% cogenerated heat, or 50% of a combination of such energy and heat. In this context, all the scenarios can be defined as efficient district cooling since the production of cold water comes from electric or absorption chillers. On the other

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Figure 21.12 Yearly energy share in the different configurations as evaluated by XEMS13: (A) scenario 2, (B) scenario 3, and (C) scenario 4.

hand, district heating can be defined as efficient only for the Scenario 4 where more than 50% of the demand is covered by a combination of heat produced by cogeneration and renewable sources (Fig. 21.12).

21.4

Summary

The use of the smart paradigm can be efficiently applied to energy production systems. The coordination and integration of different energy vectors is possible but it has to be supported by proper tools.

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The use of optimal EMSs has been shown in theory and applied to a particular case study showing the advantages of a high level of integration among different energy networks. As shown by presented results, the tool supporting this process must implement a good balance between accuracy and efficiency of the model: it must rely on a proper mathematical model of the system being close to the physical nature of the process avoiding the use of very detailed and complicated thermodynamic description of thermal systems. A system based on power flows balance on a time scale of one hour has been proved to be efficient to represent integration of heating and cooling vectors with electricity market. As it has been presented, the tool is efficient in the planning phase of a new energy system allowing to assess quantitative its technical and economic parameters. A new challenge is to implement the same scheme in the online management of the energy hubs. As soon as reliable forecasts of loads and energy prices for a time horizon will be provided the model will implement a real strategy toward a higher value of energy efficiency and a reduction of the environmental footprint of energy production. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

21.5

Chapter review questions/exercises

21.5.1 True/false 1. True or false? The optimization of the energy management for a polygeneration node needs an energy model of the system and a target performance to be reached. 2. True or false? Since the output quantity of the power module is the one of interest to match the user demand, often the constitutive equation is formulated using the output variable as the independent one. 3. True or false? Each energy vector that is present inside the polygeneration node is subject to a balance constraint, where all contributions of a different energy vector can be summed up. 4. True or false? The operating cost needed to cover the expenses for running the system through the time horizon, is given by the sum of the cost on each time interval. 5. True or false? While balance equations are linear, constitutive equations can be expressed by piecewise linear functions, where singular variables are used to select a particular working interval.

21.5.2 Multiple choice 1. The concept of __________________ is considered one of the most promising paradigms to decarbonize our society and to increase the energy efficiency of many processes and conversions.

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2.

3.

4.

5.

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a. Wireless energy networks b. Microgrid energy networks c. Smart-grid energy networks d. Storage energy networks e. Hybrid energy networks The optimization procedure is called: a. XEMS13 b. XEMS14 c. XEMS15 d. XEMS16 e. All of the above Constitutive equations are usually ____; they define a link between input and output power flows at the same instants. a. Variable b. Static c. Active d. Autonomous e. Changed In an analogy with the usual Kirchhoff current law applied in electrical circuits, a balance equation is written, taking into account a convention for the orientation of the: a. Power vector b. Power flow c. Infrastructure cities d. Power surge e. All of the above The use of the ________ can be efficiently applied to energy production systems. a. Smart grid b. Smart microgrid c. Smart energy d. Smart optimal EMS e. Smart paradigm

21.5.3 Exercise 21.5.3.1 Problem Provide a comprehensive and critical overview of the latest models and assessment techniques that are currently available to analyze multienergy and hybrid energy networks in smart grids, and in particular distributed multigeneration systems.

21.5.4 Hands-on projects 21.5.4.1 Project Do research: Present a number of interactions between electricity, heat, gas, hydrogen, and the transport sector, as they relate to the different levels of the energy chain for the smart multienergy grid.

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21.5.5 Case projects 21.5.5.1 Problem Develop an efficient EMS scheme, with an effective control strategy to integrate with the smart utility grid.

21.5.6 Optional team case project 21.5.6.1 Problem How do you make optimal use of smart-grid technologies for the integration of renewables into the grid?

References [1] ,https://www.iea-dhc.org/the-research/annexes/2017-2021-annex-ts3-draft.html., July 5, 2005. [2] ,https://www.rhc-platform.org., October 24, 2019. [3] Y. Ding, T. Strasser, P. Siano, Methods and systems for a smart energy city, IEEE Trans Ind Electron 66 (2) (2019) 13631367. [4] Common implementation roadmap for renewable heating and cooling technologies. Technical report, European Technology Platform on Renewable Heating and Cooling (2014). [5] S. Cao, A. Mohamed, A. Hasan, K. Sire´n, Energy matching analysis of on-site microcogeneration for a single-family house with thermal and electrical tracking strategies, Energy Build 68 (Part A) (2014) 351363. [6] ,http://www.retscreen.net/., December 18, 2019. [7] T.W. Archibald, K.I.M. McKinnon, L.C. Thomas, An aggregate stochastic dynamic programming model of multireservoir systems, Water Resour Res 33 (2) (1997) 333340. [8] J.M. Arroyo, A.J. Conejo, Optimal response of a thermal unit to an electricity spot market, IEEE Trans Power Syst 15 (3) (2000) 10981104. [9] M. Geidl, G. Andersson, Optimal power flow of multiple energy carriers, IEEE Trans Power Syst 22 (1) (2007) 145155. [10] E. Carpaneto, C. Cavallero, F. Freschi, M. Repetto, Immune Procedure for Optimal Scheduling of Complex Energy Systems, Springer Berlin Heidelberg, Berlin, Heidelberg, 2006, pp. 309320. [11] A. Canova, C. Cavallero, F. Freschi, L. Giaccone, M. Repetto, M. Tartaglia, Optimal energy management, IEEE Ind Appl Mag 15 (2) (2009) 6265. [12] E. Carpaneto, P. Lazzeroni, M. Repetto, Optimal integration of solar energy in a district heating network, Renew Energy 75 (0) (2015) 714721. [13] F. D’Urso, A. Giarratana, P. Lazzeroni, E. Pons, M. Repetto, L. Spairani, et al. An optimization and management tool for complex multi-generation systems, in: 16th IEEE International Conference on Environment and Electrical Engineering, June 710, 2016 Florence, Italy, 2016. [14] L.A. Wolsey, G.L. Nemhauser, Integer and Combinatorial Optimization, Wiley, 1999.

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[15] SCIP optimization web page. Available online at: ,http://scip.zib.de., July 2, 2018. [16] P. Lazzeroni, S. Olivero, M. Repetto, F. Stirano, V. Verda, Design of a polygeneration system with optimal management for a district heating and cooling network, Int J Sustain Energy Plan Manag 22 (2019) 8194. [17] X. Liu, J. Wu, N. Jenkins, A. Bagdanavicius, Combined analysis of electricity and heat networks, Appl Energy 162 (2016) 12381250. [18] M. Repetto N. Perez Mora, P. Lazzeroni. XEMS13: an hybrid-energy generation management system, in: IEEE International Conference on Smart Grid Communications (SmartGridComm): Workshop 2: Efficient, Intelligent and Economic District Heating and Cooling Systems, November 69, 2016. Sydney, Australia, 2016. [19] N. Perez-Mora, P. Lazzeroni, V. Martinez-Moll, M. Repetto, Optimal management of a complex DHC plant, Energy Convers Manag 145 (2017) 386397. [20] N. Perez-Mora, P. Lazzeroni, V. Martinez-Moll, M. Repetto, Optimal DHC energy supply harnessing its thermal mass, Appl Therm Eng 133 (2018) 520531. [21] GME - Gestore dei Mercati Energetici. Available online at: ,http://www.mercatoelettrico.org/It/Default.aspx., June 19, 2018. [22] ARERA - Prezzi medi di vendita sul mercato finale al netto delle imposte. Available online at: ,https://www.arera.it/it/dati/gp35.htm., July 1, 2019. [23] Decreto 26 ottobre 1995 n. 504 e s.m.i. - Testo unico delle disposizioni legislative concernenti le imposte sulla produzione e sui consumi e relative sanzioni penali e amministrative. [24] Decreto 4 agosto 2011 del Ministero dello Sviluppo Economico, Integrazioni al decreto legislativo 8 febbraio 2007, n. 20, di attuazione della direttiva 2004/8/CE sulla promozione della cogenerazione basata su una domanda di calore utile sul mercato interno dell’energia, e modificativa della direttiva 92/42/CE. [25] Ministero dello Sviuluppo Economico, Linee guida per l’applicazione del Decreto del Ministero dello Sviluppo Economico 5 settembre 2011 - Cogenerazione ad Alto Rendimento (CAR). [26] A. Duffy, M. Rogers, L. Ayompe, Renewable Energy and Energy Efficiency Assessment of Projects and Policies, Wiley, 2015. [27] Joint Research Center - JRC, Photovoltaic Geographical Information System (PVGIS). Available online at: ,https://re.jrc.ec.europa.eu/pvgtools/en/tools.html., December 2, 2019. [28] Ministero dello Sviluppo Economico, Decreto interministeriale 16 febbraio 2016 Aggiornamento Conto termico. [29] ,https://www.gse.it/en., 2020. [30] Directive 2012/27/EU of the European Parliament and of the Council of 25 October 2012 on energy efficiency, amending Directives 2009/125/EC and 2010/30/EU and repealing Directives 2004/8/EC and 2006/32/EC Available online at: ,https://eur-lex. europa.eu/legal-content/EN/TXT/?uri 5 celex%3A32012L0027., October 25, 2012.

Hybrid renewable energy systems, load and generation forecasting, new grids structure, and smart technologies

22

Aliona Dreglea1, Aoife Foley2, Ulf Hager ¨ 3, Denis Sidorov4 and Nikita Tomin5 1 Energy Systems Institute, Russian Academy of Sciences, Irkutsk National Research Technical University, Irkutsk, Russia, 2Queens University Belfast, Belfast, United Kingdom, 3Institute of Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund, Germany, 4Institute of Energy Systems Russian Academy of Sciences (SB), Irkutsk, Russia, 5Energy Systems Institute SB RAS, Irkutsk, Russia

22.1

Introduction

The evolution of the modern electric power systems (EPSs) management during the recent decades can be compared with the stages of growing up a child. Energy systems are becoming more autonomous, intelligent, and require less human involvement, provided that their reliability should remain high and efficiency should increase. In other words, there is an evolution of the traditional EPS in the direction of a fullfledged smart grid, which has such properties as continuous self-monitoring of the state and self-healing of network components, wide integration of renewable energy sources, the participation of active consumers, increased physical and cybersecurity, etc. Such an intelligent transformation of EPSs is largely due to the introduction of new smart data-driven technologies and introduction of the new grids structures.

22.1.1 Smart grid: smart technologies and new grids structures The development of the smart grids is based on an advanced mathematical theory application [including artificial intelligence (AI) and machine learning (ML)], the improvement of information collection and processing systems (phasor measurement unit (PMU), wide area monitoring system/wide area protection system (WAMS/WAPS) technologies, and intelligent supervisory control and data acquisition/energy management systems/distribution management systems (SCADA/EMS/ DMS) systems) as well as the emergence of new grid structures (hybrid AC-DC networks, integrated systems, and microgrids), adaptive control, and regulation devices. The classification of major smart-grid systems is illustrated in Table 22.1. Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00022-X © 2021 Elsevier Inc. All rights reserved.

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Table 22.1 The detailed classification of the smart infrastructure system and the smart management system. Smart management systems

Management objective Management methods and tools

Smart infrastructure

Smart energy subsystems

Smart information subsystem

Smart communications subsystem

Energy efficiency and demand profile Utility, cost, and price Emission Optimization ML Game theory Multiagent systems Power generation Transmission grid Distribution grid New grid paradigm: microgrids, multienergy systems, hybrid renewables energy systems, and vehicle-to-grid Information metering and measurement (smart meter, sensor, and PMU) Information management (data modeling, information analysis, integration, and optimization) Wireless Wired End-to-end communication management

Let us consider in more detail on some triggers of such a transformation. The penetration of renewable energy and converting technologies as well as the need to transmit and distribute different energy carriers, facilitates the creation of hybrid renewable energy systems (HRES) that include traditional AC networks, multiterminal DC networks, and gas transmission infrastructure, with traditional and renewable energy sources. The adoption of hybrid networks reduces the use of fossil fuels (oil and gas), cuts the power production and transmission costs, and enhances the efficiency of all types of control (online, automatic operation, and emergency control). This in turn leads to positive effects in socioeconomic sphere (energy supply to geographically remote areas, reduction in electricity costs), enhances the efficiency of some key technologies (ship building, autonomous military, and civil energy systems), increases reliability and survivability of key infrastructure facilities (combined power transmission, pipeline systems), solves environmental problems (reduction in carbon dioxide emissions), etc. A distinctive feature of these systems is a strong interconnection among all its components. The AC networks power the gas pumping stations. At the same time, power in the AC networks is generated at gas turbine plants. The multiterminal DC networks are suitable for the integration of renewable energy sources. However, the presence of multiterminal constituent, on the one hand, increases the flexibility of control, but on the other hand increases the interaction of various components, which makes it impossible to control DC network separately from AC network and

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477

from gas transmission infrastructure. In the nearest future, hybrid networks with an analogous set of components will be created at all the levels of hierarchy, starting with large-scale intersystem power interconnections and finishing with distribution networks of consumers (gas 1 power 1 renewable energy sources) and off-grid power systems (networks of ships, autonomous power systems of deposits, microgrids, etc.). Furthermore, the accelerated development of HRES, poses a number of complex engineering problems, among which three key ones can be distinguished: modeling, forecasting and control. Currently, there is an increase in the number of works devoted to the joint modeling of various engineering infrastructures (AC 1 gas, AC 1 DC with multiterminal DC grid, AC networks with renewable energy sources, etc.), which indicates the relevance of this subject. Throughout the world, the main problem of HRES is the extremely volatile power generation from RES. In addition, the trend toward the introduction of smart-grid technologies in transmission and distribution networks has led not only to the complication of monitoring tasks, but also necessitated more accurate forecasting when solving problems of accumulation and redistribution of consumption between different resources (electricity, gas, and renewable energy sources). Effective management of HRES in the context of continuous changes in external and internal factors is an urgent task in modern world energy, the solution of which is probably difficult to achieve without the use of AI technologies (e.g., multiagent systems and deep ML) and new methods of nonlinear mathematical programming [1,2]. Considering the current development processes noted in the preceding, the modern power systems are expected to undergo principal changes in their internal structure and properties, which will considerably decrease the level of self-adaptability, self-healing, and hence flexibility of these systems. The internal factors are related to the mass use of power electronics and rectifiers/inverters to connect highfrequency small gas turbine plants and wind turbines, photovoltaic plants, power storage systems, DC lines and links, variable frequency drive loads, and local rectifiers of many loads to EPS. This considerably reduces the preceding mentioned voltage and frequency regulating effect of load, and the inertia in the EPS. On the other hand, the anticipated soaring number of generators with randomly fluctuating power output, first of all from wind units, will considerably increase the negative impact of such fluctuations on the self-adaptive capability of the EPSs, and correspondingly reduce their flexibility. At the same time the control systems of many prospective devices, based on power electronics (FACTS, power storage systems, DC lines and links, etc.) are highly effective, and their wide use will essentially increase the controllability of the future EPSs [3]. Thus, the prevailing negative factors and insufficient consideration of positive factors in the course of development and operation of EPSs, will lead to an inadmissible decrease in the flexibility of these systems, increase in their failure rate; and, reduction in the reliability of the power supply to consumers and power quality. Mitigation of the negative factors requires comprehensive, in-depth studies. In this regard, a promising solution is the development of autonomous intelligent control systems that will allow combining the operational and automatic control of the regimes of modern power systems with minimal involvement of operational

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dispatching personnel. For example, according to the Concept of Network Digitalization for 2018 2030 [4], one of the main and priority tasks for the development of the energy management system (EMS) of the largest Russian energy company PJSC Rosseti is the centralization of EMS, and the task of creating intelligent EMS tools for the network management centers. Over the past few years, similar projects to create intelligent autonomous EMS for power grids have been carried out by various energy companies, for example, the Grid Mind system (GEIRI North America, USA) [5], “Mimic of Human Operator Decision” (French Transmission Service Operator “RTE”, France) [6] and scientific institutions, for example, the intelligent decision-support system “Artificial Power Systems Operator” (Melentiev Energy Systems Institute SB RAS, Russia) [7]. The main technology of these projects is deep neural networks. Siemens also already uses deep neural networks in various projects: improving relay protection, optimizing the operation of gas turbines, intelligent regulation of wind turbines [8 10].

22.1.2 Load and generation forecasting Electric load forecasts play a key role in the electric power industry of smart cities, because it provides the primary information for power systems planning and operations; revenue planning; and for energy trading. Apart from the electric utilities companies, load forecasts are widely used by regulatory commissions. Moreover, load forecasts are used by the industrial, commercial, and insurance companies-to name a few. The time ranges of the load forecasting, is normally classified into several categories: very short term and short term, medium term, and long-term load forecasting. These intervals correspond to one day (24 hours), 2 weeks, and 3 years. According to the computer science terminology, the load forecasting belongs to the ML set of problems and its efficiency heavily relies on not only the specific ML regression algorithms, but also on the input data employed to train these ML algorithms. Such input retrospective datasets, can involve, not only the load time series itself, but also weather parameters, social activities, time, day of the week, and other information. Electric load forecasts accuracy heavily depends on such retrospective datasets. Moreover, the different datasets may influence the forecasts of different time range, that is, forecasting models parameters must be tuned when one change the forecast horizon. The load forecasts’ output format can be considered as point or interval. It is to be noted that the massive deployment of the smart meters provided the electric utilities companies and industry with spatio-temporal big data. Such data can be used for various problems solution in smart cities, not only for load forecasting. For comprehensive review of the load forecasting algorithms, readers may refer to [11]. One of the emerging problems is such recordings analysis is anomalies detection. Anomalies may refer to different problems, for example, the equipment failure, communication problems, and different types of intrusion. Each of these anomalies must be detected and properly classified in smart cities in order to proceed for higher-level decision making.

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During the last decades, the anomalies detection problem has been attacked in various sectors of human life, such as medicine, finance, and cybersecurity [12,13]. The largest IT companies in the world (Google, Facebook, and Yandex) develop their own algorithms and frameworks for detecting social data anomalies. In addition, there are many papers on the search for anomalies in industrial data as part Internet of Things (so-called Energy Internet) framework. The ML algorithms that are used to detect anomalies include the k-means algorithm [13], random forest [14], and the support vector machine [15]. The wind speed forecasting models may be categorized into time series-based models, weather condition-based models, and mixed type models. The time seriesbased methods employ the retrospective weather records including the wind speed data to build the data-driven models using advanced ML, see, for example, [16]. Weather condition-based approaches, on the other hand, use hydrodynamic atmospheric models, which incorporate physical phenomena such as frictional, thermal, and convective effects [17,18]. The latter are advantageous in long-term prediction whereas the former perform well in short-term prediction. Contemporary intelligent methods are widely used for a variety of prediction and classification problems in various energy systems for phase transition monitoring [19], combustion regimes monitoring [20], transportation systems [21], power system’s operational stability and efficiency [21 25], pollution problems [26], energy storage control, load leveling [27], and many other applications. In comparison with classical methods, ML methods can be faster and more accurate, when it comes to energy management in a smart city. The significant research has been undertaken with regard to forecasting wind power or wind speed using contemporary ML methods; for example, the support vector regression is combined with Elman recurrent neural work and seasonal index adjustment as a hybrid model to forecast medium-term wind power in [28]. On the basis of the autoregressive integrated moving average, a hybrid of Kalman filtering-artificial neural network (KF-ANN) model is used for wind power forecasting and to improve the accuracy of wind power forecasting in [29]. The ANN model with meteorological data is applied to predict of the mean, maximum, and minimum hourly wind power eight hours ahead in [30] using the conventional multilevel perceptron. A self-adapting forecasting model based on extreme learning machine is employed for ultrashort-term wind power time series forecasting in [31]. A detailed comprehensive comparative analysis of three different ANNs in 1-hour-ahead wind power prediction, including adaptive linear element, radial basis function, and back-propagation network can be found in [32]. A combined forecasting approach is proposed in [33], which builds forecasting model with self-adjusting parameters of low computational complexity. The hybrid model, based on Hilbert-Huang transform and neural networks for time series forecasting, is proposed in [13]. Other common methods like spatial correlation method, genetic algorithm, support vector machine, KF method, autoregressive moving average method, continuous method, gray forecasting method, and various combinations of these methods have been employed for wind power or wind speed forecast in multiple studies [34 38].

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Summary

As a footnote of this section, let us outline how many advanced forecasting methods have not been covered here, because this field is currently under rapid development. Moreover, energy management in smart grids involves various interdisciplinary studies concerning smart integration of electric vehicle, microgrids, and storage systems. Some of these problems will be discussed in Chapter 26, “Resilient future energy systems: smart grids, vehicle-to-grid, and microgrids.”

22.3

Conclusions

Application of new data-driven methods to energy management paves a new avenues to novel innovative smart grids design and development. Present chapter provided the brief introduction to this field focusing on smart technologies development and new grids structures design. First, the classification of new smart grids systems is introduced with focus on the main triggers of the HRES development. Then the new methods for forecasting of the electric load and renewable energy (wind and solar) generation are briefly discussed. Anomalies and novelty detection methods are also discussed. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

22.4

Chapter review questions/exercises

22.4.1 True/false 1. True or false? The development of the smart grids is based on an advanced mathematical theory application (including AI and ML); the improvement of information collection and processing systems (PMU, WAMS/WAPS technologies, and intelligent SCADA/EMS/ DMS systems); as well as, the emergence of new grid structures (hybrid AC-DC networks, integrated systems, and microgrids), adaptive control and regulation devices. 2. True or false? The penetration of renewable energy and converting technologies as well as the need to transmit and distribute the same energy carriers, facilitates the creation of HRES that include traditional AC networks, multiterminal DC networks, and gas transmission infrastructure, with traditional and renewable energy sources. 3. True or false? The multiterminal DC networks are suitable for the integration of renewable energy sources. 4. True or false? Furthermore, the accelerated development of HRES, poses a number of complex engineering solutions, among which three key ones can be distinguished: modeling, forecasting, and control. 5. True or false? Considering the current development processes, the modern power systems are expected to undergo principal changes in their internal structure and properties, which will considerably decrease the level of self-adaptability, self-healing, and hence flexibility of these systems.

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22.4.2 Multiple choice 1. The prevailing negative factors and insufficient consideration of positive factors in the course of development and operation of EPSs, will lead to an inadmissible decrease in the flexibility of these systems; increase in their failure rate; and reduction in the reliability of the power supply to consumers and: a. Power quality b. Power systems c. Energy management system d. Grid mind system e. Deep neural networks 2. Electric load forecasts play a key role in the electric power industry of smart cities, because it provides the primary information for power systems planning and operations; revenue planning; and for: a. Machine trading b. Energy trading c. Grid trading d. Load trading e. All of the above 3. Load forecasting belongs to the ML set of problems and its efficiency heavily relies on not only the specific ML regression algorithms, but also on the input data employed to train these: a. ML regression algorithms b. ML set of problems c. ML algorithms d. Spatio-temporal big data e. Load forecasting algorithms 4. Anomalies must be detected and properly classified in smart cities, in order to proceed for decision making. a. Lower level b. Medium level c. Higher level d. None of the above e. All of the above 5. The wind speed forecasting models may be categorized into: a. Time series-based models b. Hydrodynamic atmospheric models c. Weather condition-based models d. Prediction models e. Mixed type models

22.4.3 Exercise 22.4.3.1 Problem How does the high variability of HRES generation (up to 100% of capacity), make forecasting critical for maintaining the reliability of the smart grid?

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22.4.4 Hands-on projects 22.4.4.1 Project Do research: What does it mean for electricity systems to be flexible and smart?

22.4.5 Case projects 22.4.5.1 Problem Create a hybrid smart-grid integrating wind, photovoltaic, and batteries into an alternate current bus.

22.4.6 Optional team case project 22.4.6.1 Problem What are the implications on the risk and return profile of investments in smart energy assets in the future? Should small smart-grid edge transactions be aggregated to facilitate financing? Will new smart energy assets have access to low-cost institutional capital?

References [1] R. Arghandeh, Yu Zhou, Big Data Application in Power Systems, first ed., Elsevier, Oxford, UK, 2017. [2] M. Glavic, et al., Reinforcement learning for electric power system decision and control: past considerations and perspectives, IFAC-PapersOnLine 50 (1) (2017) 6918 6927. [3] N. Voropai, C. Rehtanz, et al., The development of a joint modelling framework for operational flexibility in power systems, in: Proceedings of ELMA 2019, Varna, Bulgaria, 2019. [4] Concept of Russian Grids Digitization on 2018 2030, Moscow, JSC «Rosseti». ,http:// www.rosseti.ru/investment/sovet/doc/Pr_7.pdf., February 14, 2018. [5] R. Diao, Z. Wang, D. Shi, Q. Chang, J. Duan and X. Zhang, Autonomous voltage control for grid operation using deep reinforcement learning, arXiv:1904.10597,10, 2019. [6] B. Donnot, I. Guyon, M. Schoenauer, P. Panciatici and A. Marot, Introducing machine learning for power system operation support, arXiv:1709.09527, 7, 2017. [7] N. Tomin, et al., Development a partially observable Markov decision processes-based intelligent assistant for power grids using Monte Carlo tree search, in: Proceedings of the 10th International Scientific Symposium on Electrical Power Engineering, ELEKTROENERGETIKA 2019, Stara Lesna, Slovakia, pp. 389 393, 2019. [8] I. Kogan et al., Introduction of advanced machine learning technologies in protection relays, Proceedings of the International Scientific and Technical Conference and Exhibition on Relay Protection and Automation of Power Systems 2017, St. Petersburg, Russia, 2017.

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[9] R. Busch, The future of manufacturing, artif. intelligence: optimizing ind. operations, Siemens. ,https://www.siemens.com/innovation/en/home/pictures-of-the-future/industry-and-automation/the-future-of-manufacturing-ai-in-industry.html., May 31, 2018. [10] S. Webel, K. Nikolaus and A. Pease, Autonomous systems. Getting machines to mimic intuition, Siemens. ,https://www.siemens.com/innovation/en/home/pictures-of-thefuture/digitalization-and-software/autonomous-systems-machine-learning.html., March 01, 2016. [11] C. Deb, et al., A review on time series forecasting techniques for building energy consumption, Renew. Sustain. Energy Rev. 74 (2017) 902 924. [12] S. Hawkins, H. He, G.J. Williams and R.A. Baxter, Outlier detection using replicatorneural networks, Fourth International Conference on Data Warehousing and Knowledge Discovery. Springer-Verlag, pp. 170 180, 2002. [13] M. Hayes, M. Capretz, Contextual anomaly detection framework for big sensor data, J. Big Data 2 (2) (2015). [14] A.V. Zhukov, D.N. Sidorov, A.M. Foley, Random forest based approach for concept drift handling, Commun. Comput. Inf. Sci. 661 (2017) 69 77. [15] T. Kanungo, D.M. Mount, An efficient k-means clustering algorithm: analysis and implementation, IEEE Trans. Pattern Anal. And. Mach. Intell. 24 (7) (2002). [16] F. Liu, R. Li, A. Dreglea, Wind speed and power ultra short-term robust forecasting based on Takagi Sugeno fuzzy model, Energies 12 (18) (2019) 3551. Available from: https://doi.org/10.3390/en12183551 (accessed 30.12.19). [17] G. Kariniotakis, P. Pinson, N. Siebert, G. Giebel and R. Barthelmie, The state of the art in short-term prediction of windpower from an offshore perspective, in: Proceedings of Sea Tech Week, NEW YORK, NY, USA, pp. 1 13, 2004. [18] A. Costa, et al., A review on the young history of wind power short-term prediction, Renew. Sustain. Energ. Rev. 12 (6) (1998) 1725 1744. [19] H.T. Nguyen, T.H. Nguyen, A.I. Dreglea, Robust approach to detection of bubbles based on images analysis, Int. J. Artif. Intell. 16 (2018) 167 177. [20] M.P. Tokarev, et al., Monitoring of combustion regimes based on the visualization of the flame and machine learning, J. Phys. Conf. Ser. 1128 (2018) 012138. [21] H.T. Nguyen, et al., Machine learning algorithms application to road defects classification, Intell. Decis. Technol 12 (2018) 59 66. [22] F. Liu, et al., Takagi Sugeno fuzzy model-based approach considering multiple weather factors for the photovoltaic power short-term forecasting, IET Renew. Power Gener 10 (2017) 1281 1287. [23] Q. Liu, et al., Power quality management of PV power plant with transformer integrated filtering method, IEEE Trans. Power Deliv. 34 (2019) 941 949. [24] N.V. Tomin, et al., Machine learning techniques for power system security assessment, IFAC PapersOnLine 49 (2016) 445 450. [25] N.I. Voropai, et al., A suite of intelligent tools for early detection and prevention of blackouts in power interconnections, Autom. Remote. Control. 79 (2018) 1741. [26] Q. Tao, et al., Air pollution forecasting using a deep learning model based on 1D convnets and bidirectional GRU, IEEE Access. 7 (2019) 76690 76698. [27] D.N. Sidorov, et al., A dynamic analysis of energy storage with renewable and diesel generation using Volterra equations, IEEE T. Ind. Inform 8 (2019) (accessed 04.08.19). [28] J. Wang, et al., Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China, Renew. Energy 76 (2014) 91 101. [29] C.N. Babu, et al., A moving-average filter based hybrid Arima Ann model for forecasting time series data, Appl. Soft Comput. J. 23 (2014) 27 38.

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[30] K.P. Moustris et al., Wind power forecasting using historical data and artificial neural networks modeling, in: Proceedings of the Mediterranean Conference on Power Generation, vol. 9, Belgrade, Serbia, 6 9 November 2017. [31] Y. Zhao, et al., A novel bidirectional mechanism based on time series model for wind power forecasting, Appl. Energy 177 (2016) 793 803. [32] L. Gong, S. Jing, On comparing three artificial neural networks for wind speed forecasting, Appl. Energy 87 (2010) 2313 2320. [33] Y. Li, et al., A combined forecasting approach with model self-adjustment for renewable generations and energy loads in smart community, Energy 129 (2017) 216 227. [34] J. Yan, et al., Reviews on uncertainty analysis of wind power forecasting, Renew. Sustain. Energy Rev. 52 (2015) 1322 1330. [35] Z. Men, et al., Short-term wind speed and power forecasting using an ensemble of mixture density neural networks, Renew. Energy 87 (2016) 203 211. [36] T. Mahmoud, et al., An advanced approach for optimal wind power generation prediction intervals by using self-adaptive evolutionary extreme learning machine, Renew. Energy 126 (2018) 254 269. [37] Z. Liang, et al., Short-term wind power combined forecasting based on error forecast correction, Energy Convers. Manag. 119 (2016) 215 226. [38] H. Chitsaz, N. Amjady, H. Zareipour, Wind power forecast using wavelet neural network trained by improved clonal selection algorithm, Energy Convers. Manag 89 (2015) 588 598.

Smart lighting for smart cities

23

Matthew Palmer and Ronald Gibbons Virginia Tech Transportation Institute, Center for Infrastructure Based Safety Systems, Blacksburg, VA, United States

23.1

Introduction

The concept of smart cities is relatively new. However “smart lighting” has been around for a decade or more. Smart lighting allows a “precious balance” of lighting to be applied at the location it is needed, when it is needed and only in the correct amount. Smart lighting makes the urban environment safe for humans at night while improving quality of life both night and day while enabling a more harmonious existence of technology, humans, flora, and fauna that cannot be achieved with traditional technology. Finally, smart lighting provides the power and control networks that can be the initial backbone for smart-city services and technologies.

23.2

Smart lighting basics

Smart lighting is comprised of several required components. These include the luminaire, light emitting diodes (LEDs), dimmable drivers, wireless control nodes, control network, interface and node controller, and control methodologies, which may incorporate occupancy and ambient lighting detectors.

23.2.1 Luminaires A luminaire is a device that is comprised by a light producing object; optics designed to direct the light in a needed direction and distribution; any electrical components required to power or control the light producer and/or the optics; any heat dissipation devices; a structure to hold all of the components; and provide a means of mounting the object (Fig. 23.1). Luminaires come in a variety of shapes and sizes designed for different applications (Fig. 23.2). In order to enable smart lighting, there must be a control interface to the luminaire being utilized. Typically, this is a NEMA 3, 5, or 7 pin connector located on the top of the luminaire, which can be specified when ordering. A NEMA 7 pin female and male connector is shown in Fig. 23.3. The NEMA 7 connectors are based on the ANSI C136.41 standard. Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00023-1 © 2021 Elsevier Inc. All rights reserved.

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Structure and heatsink

Light-producing object (LEDs) and optics

Driver

Figure 23.1 Luminaire and components.

Figure 23.2 Luminaires come in a variety of shapes and sizes.

The NEMA 3 pin connector was developed earlier in time to enable on/off control of roadway luminaires with a photocontrol and is specified in ANSI C136.10. The three pins allowed the photocontrol to be powered continuously while providing for interruption of the luminaire ballast power during the day. The three connections are assigned to:

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Figure 23.3 NEMA 7 female connector found on luminaires (left) and example of a light controller with NEMA 7 male plug (right). 1. Power in 2. Luminaire power 3. Neutral

The NEMA 7 connector (Fig. 23.3, left) replaces the NEMA 3 connector. The matching twist lock connector found on lighting controls is shown in Fig. 23.3 on the right. The NEMA 7 connectors are designed to provide luminaire-dimming controls through the additional four connections. The NEMA 5 connector has only two dimming connections. The standardization of the NEMA style control connections, has allowed the enablement and development of a large variety of controls, including some very intelligent Devices (which are detailed in Section 23.3 (More advanced concepts) of this chapter). The NEMA 7 receptacle is also available with rotation capability to enable aiming of the controllers that have integrated sensors. The NEMA 5 and 7 connectors are backward compatible allowing sensors or controls that were designed to work with three pin NEMA connectors to function correctly. While the NEMA 7 connector is intended to be the primary interface to control the luminaire, a luminaire may include additional interfaces to enable controlling the lighting output by means of sensors or internal components. Additional sensor interfaces are specified by ANSI C136.58 and ANSI C136.54.

23.2.2 LEDs Solid-state (LED) technologies have improved vastly in recent years, and are now one of the best options available for roadway, parking-garage, and parking-lot lighting. LEDs are robust and have a long-life reducing maintenance costs. Single LEDs are small and allow for excellent optical control especially when compared to other technologies (Fig. 23.4). They are powered by digital controller circuits called drivers that can also enable dimming of the LEDs. LEDs produce light with a broad white light available in a wide range of correlated color temperature (CCT) from 2000 to 6000K.

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Figure 23.4 Single LED with individual optic shown 8 mm screw head for scale.

LEDs are also an energy-efficient lighting option, especially when dimmed to take advantage of the technology capabilities. High-pressure sodium (HPS) lighting is the most prevalent lighting in cities and on roadways. This is primarily due to the combination of high efficiency, low lumen loss over time, and low cost. LEDs have reached a combination of price point and efficiency that rivals HPS especially when including the cost of lane closures and bucket truck crews for bulb replacement with HPS lighting. LEDs are solid-state semiconductor devices that produce light from electrical current very efficiently. They are capable of turning on and off in millisecond time frame and at high repetition rates. In comparison, HPS lighting is similarly efficient, but cannot be turned on or off very quickly. HPS lighting needs 5 10 min to reach full light output and once turned off, cannot be turned back on for several minutes. While dimming ballasts exist for HPS lighting, they are considerably more expensive and again cannot change the output of the lighting faster than about once per 5 10 min so the usefulness is limited. While HPS lighting can be dimmed by about 30% 50% of their lighting output, LED lighting can be dimmed to 5% or less output. LEDs lighting output can be adjusted almost instantaneously. Finally, HPS lighting is limited in color reproduction, which affects the visual performance of drivers with respect to color contrast that is critical to safe operation (the color of the HPS luminaire will also change during dimming operations). It is the capability to quickly dim and turn the LED luminaire on and off with controls that enables smart lighting. When used in combination with smart controllers and dimmers, already efficient LED lighting can used provide to even more energy savings. For example, if a lighting system could be dimmed to 50% brightness for at least 50% of the system burn time (night hours), a 25% energy savings would result. This is adaptive lighting. In 2001, one estimate [1] put the cost of outdoor lighting in the United States at $5.9 billion. Therefore a smart LED lighting system operating under the aforementioned conditions could save $1.49 billion per year if implemented widely in the United States. Smart lighting, when adaptive lighting is implemented, can reduce lighting energy usage by as much as 50% [2] while providing higher-quality light for improved safety.

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23.2.3 Controls The intelligence in smart lighting comes from the controls. A control is a device added to the luminaire that allows the lighting to be controlled by means other than a person turning a switch on or off. The least smart lighting control consists of photocontrol enabled on-off control of the luminaire power in response to the presence or absence of sunlight. This can be performed at the switching station, which controls groups of 100s 1000s of luminaires. This works fine with HPS lighting as well as others with magnetic ballasts. Magnetic ballasts act as a low-pass filter, which limits current draw during start-up which in-turn controls the total current transient at the switching station. Another method of photocontrol is to place a photocontrol on each luminaire. This allows the end users to adjust the amount of light needed to turn on each luminaire enabling staging of the luminaire switching times to further reduce lighting transients. However roadway lighting levels needed are not constant throughout the night [3]. Nighttime to daytime accident rate ratios has been researched by fusing crash rate data with measured lighting levels over 2000 lane miles of roadways in a variety of areas throughout the United States. Lighting was found to be dependent on many factors including lighting level, speed, traffic volume, pedestrian volume, type of roadway, and geometry of the roadway as well as other factors. An important finding was that there were diminishing reductions in crash rate ratios beyond a certain lighting level for each road type. The important finding for smart lighting was that traffic volume and pedestrian volume had a significant effect on required lighting levels. Since traffic and pedestrian volumes vary through the night, controls that enable control of the luminaire lighting level could be useful. Wireless roadway lighting control systems that can dim luminaires are becoming more prevalent on the market and in the field [2]. These control systems allow wireless dimming and on-off control of individual luminaires. A base station communicates and controls each luminaire through a wireless transceiver connected to the electronics, which controls the amount of light that each luminaire produces. The luminaire transceivers can form an ad-hoc network where commands are repeated from one luminaire to another, allowing low-power, low-cost wireless devices to access luminaires many kilometers from the home base. For LED luminaires, this allows dimming of the lighting from 100% output down to about 5% 10% output depending upon the luminaire design.

23.2.4 Drivers and dimming A dimmable driver is typically available standard with any LED luminaire, but may be optional or special order, depending on the specific luminaire design and manufacturer. A dimmable driver is a requirement for smart lighting. As each luminaire has varying requirements, it is recommended that a dimmable driver option be selected or requested when ordering the luminaries, so that, they can be provided by luminaire manufacturers.

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23.2.5 Networks Most lighting controls are on either cellular networks or IEEE 802.11b at 2.4 GHz—an early Wi-Fi standard. A few lighting controls use other Wi-Fi standards, some use proprietary licensed bands, and there is some interest from DOTs in LoRa or Long Range communication standard which operates at 433, 868 (Europe), and 915 MHz. As the name implies, LoRa enables communication over a longer distance than 802.11 standards and may be more appropriate for more rural areas. There is also a new IEEE 802.11ah Wi-Fi HaLow at 900 MHz, again for longer-range communication.

23.2.6 Interface and controller Most smart lighting control systems utilize a network with a luminaire node controller (sometimes called a gateway) that acts as a single access point. The luminaire node controller is an electronic device between the lighting control network and the interface with the end-user. Multiple lighting node controllers can also interface with each other or with an overall lighting management system as illustrated in Fig. 23.5. Ambient condition, occupancy, and/or traffic volume sensors can be networked in as needed through interface to the individual controller nodes on the luminaires or directly to the luminaire node controllers. The actual node topology, whether mesh, point to multipoint (star), or point to point will depend on the geometry of the lighting system infrastructure and line-of-sight between wireless nodes as well as signal quality and latency. The interface is typically a through a webpage or custom software with graphical user interface running on a personal computer but some systems allow control through a smart phone. Some gateways can host the interface software locally, some are hosted on remote servers, while other systems are hosted in a cloud environment. Each interface is unique, but in general the interface enables individual addressing of each luminaire through the attached node for dimming, and enables on-off control. The interface enables manual controls, sensor controls, and enables programming of various lighting schedules. Most interfaces also provide power usage calculations or measurement, as well as self-monitoring of node and luminaire health including last communication with the nodes, voltage and current measurement, temperature measurement, and luminaire fault (no current draw). Finally, faults and alarms can be programmed to automatically notify specific users with emails, and typically various reports scan be setup including automatic generation of work orders to address luminaire and controller faults.

23.2.7 Control methodologies There are several control methodologies for smart lighting already available and several undergoing research and development. As mentioned previously, the least smart control is photocontrol of the lighting. As this is of least interest to smart cities, nothing further will be discussed regarding photocontrol. This section will focus on the more advanced control algorithms enabled by smart lighting controls.

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Figure 23.5 Smart lighting control network topology concept.

Figure 23.6 Example luminaire-dimming controller illustrating translucent cover for photocontrol.

Recently, guidelines [2] were published on how to design roadway lighting for adaptive lighting, which has the potential for dramatically reducing energy usage at night when traffic and pedestrian volumes are low, without decreasing the safety benefits. Adaptive lighting is defined as adjusting lighting levels to the current conditions on a schedule or utilizing sensors. A schedule-based system can be used to adapt lighting to vehicle volumes, based on traffic and pedestrian counts. Those surveys would only be generally applicable and would need to be used conservatively in order to insure sufficient light levels are available. Most lighting control systems allow schedules that vary by day of the week and adjust for sunset and sunrise changes through the year. The lighting system, also allows manual control for special events. Most controllers include photocontrol sensor behind a clear or translucent cover (Fig. 23.6) and global positioning system (GPS) sensors.

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Alternatively, there exist multiple control systems that can utilize an occupancy sensor(s) to increase lighting levels from scheduled dimming when the traffic or pedestrian presence demands. Occupation sensors are based on either radar or infrared light. Sensors can be integrated into the controllers or designed to interface with the controller system network and monitor. As the sensor market is expanding rapidly, detailing all of the sensors is beyond the scope of this chapter.

23.3

More advanced concepts

Once deployed, a smart lighting system can provide the backbone for other smartcity applications due to its ubiquitous features. In addition to freeing up power over older technology luminaires, the smart lighting system can provide an initial data network and infrastructure to support other services and devices for smart cities such as Wi-Fi hotspots, charging stations, and automated refuse pickup monitors.

23.3.1 Ubiquitous network and infrastructure For smart cities, the most important aspect of smart roadway lighting system is the fact that its features are relatively standard and ubiquitous. These features: power wiring, electric power, control network, and poles (infrastructure), are important for smart-city development. Switching from HPS to LED lighting at the correct RP-8 18 [4] light levels frees up 30% 50% of the power previously utilized to light the roadway. This is due to overall peak light level reduction, LED efficiency, and light level reduction or adaptation with controls. Most roadways are over lighted when compared to RP-8 18. The over lighting is due to several factors including sizing the luminaires for the maximum lighting levels needed, increasing lighting levels in accident or crime “hotspots,” or due to oversizing of the luminaire for dirt depreciation and lumen depreciation and then not being able to dim the oversized luminaire down to the correct lighting levels. LED luminaires are more efficient at providing illumination using the lumens produced. LED luminaires distribute the light more evenly because LED luminaires are made up of dozens of LED chips, which can be aimed individually and typically require only one lens or reflector. This allows RP-8 18 light levels to be reached with a smaller lumen package than can be achieved with other lighting technologies resulting in a lower current draw for the required lighting levels. Finally, LEDs can be dimmed for different conditions and users, which lowers current draw. All of these factors add up to a savings of 30% 50% in power usage, freeing up power for other smart-city devices and technologies that can be directly connected to the lighting power feed. If smart lighting controls are deployed, there are multiple ubiquitous communication networks available to the smart city for other data: (1) the lighting control network, (2) the power supply wiring, and (3) potentially a fiber cable network depending the location relative to major intersections. The lighting control network is the most likely network available and there are a plethora of options available

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that are wireless as described above. These wireless networks are typically limited to 11 MB/s. There are controller systems that utilize the power lines to transmit high frequency communication data although these are typically utilized for indoor building lighting such as the ZigBee. Finally, some smart lighting controller systems are anticipating installation of additional optical fiber cables in parallel or along with upgrades to the lighting luminaires and controllers. These controllers include built in optical fiber interfaces enabling significantly higher bandwidths potentially up to 1 GB/s at each node. Lighting poles are a hot topic in smart-city discussions because of the real estate available beneath or alongside the luminaire. There is significant space available for mounting of a variety of smart-city technologies and devices. Besides occupancy sensors that increase the lighting level with pedestrians or vehicle traffic increases, services such as Wi-Fi hotspots, traffic cameras, trash-container monitor wireless relays, or electric personal mobility (scooters) checkout locations could be mounted on the “smart poles.” Finally, with access to power and wireless communication available between the NEMA 7 connector on the luminaire and the attached control node, there exist opportunity to add intelligence for other applications. Edge computing is a term that describes a computer that processes a large amount of data from a sensor at the location of the sensor and then only provides the desired aggregate or summary data along with the metadata through the wireless network to the user or control system. An example of this would be a pedestrian tracking and counting system that utilizes machine vision running on an edge computer to process video and report back accurate and precise pedestrian counts to the signal phase and timing systems as well as the roadway lighting control system on a regular interval such as 1/15 minutes or 1/4 hour. The edge computing reduces the high volume of video data to the pedestrian volume in two or three different velocities at each intersection or cross walk in this example. Many control manufactures have already developed small computing modules that attach to the NEMA 7 receptacle on the luminaire and have additional NEMA 7 receptacles for the controller node and which provide pass through and controlled connections between the luminaire and the control node. The computing module provides additional input and output connectors that vary by manufacture that enable connection to other sensors or devices. These edge computer modules can run custom software provided by third parties expanding the available data to and capability of the smart lighting system.

23.3.2 Color Another smart lighting concept that is of potential interest to municipalities is that of changing the color of the lighting depending on the time of night. This would be done to reduce the impact on human, flora, and fauna health. There is interest in dual or tunable color luminaires to enable the luminaire to produce a warmer white light during normal sleep hours when traffic is reduced. There exists data that shows impact of both dose (photons-cm22-s21) and color on human melatonin levels [5], which seems to support warmer light for human health. At the writing of this chapter, Virginia Tech Transportation Institute (VTTI) and Thomas Jefferson University are performing a US

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Table 23.1 Relative human retinal photo pigment complement calculated utilizing the Lucas et al. workbook [6] from spectra measured from roadway luminaires at identical illuminances.

Department of Energy funded study to measure the impact of lighting dose absorbed on melatonin levels during typical human activities. These experiments were performed using naturalistic roadway lighting levels, which are much lower lighting levels than those previously studies. Melatonin is the hormone responsible for initiation of sleep in humans and other animals. However, shifting from a 4000 K CCT to 3000 K CCT may change the melanopic action by only 15% (Table 23.1) when at the same illuminance level. Therefore it is likely that a color shift will have a smaller affect than a 50% reduction in lighting level which is possible under certain conditions during low traffic hours in early hours. Since human beings illuminance or lighting levels on a logarithmic scale, a 50% reduction in lighting appears as only a 30% reduction in lighting and is difficult to see.

23.4

Smart lighting example

Smart lighting can be a as simple as a timed dimming schedule controlling LED luminaires which provides one light level from dusk until midnight and a dimmer light level from midnight until dawn. However, occupancy or traffic sensors can provide even more capability by enabling the lighting to dim to a very low level until traffic demands the lighting. This concept was investigated by VTTI.

23.4.1 On-demand roadway lighting Researchers and engineers at the VTTI designed an on-demand roadway lighting system on the Virginia Smart Road. They used a combination of available technology and resources, along with custom electronics and algorithms.

23.4.1.1 General architecture An on-demand roadway lighting system would require a vehicle to pass its speed and heading information to an on-demand lighting processor, and the roadway lighting system to pass its status to the same processor. The processor would then decide which luminaires are in the vicinity of the vehicle, if they should be turned on or off depending on their status, and the location, speed, and heading of the vehicle.

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Figure 23.7 On-demand roadway lighting system.

Then the processor would interface with a luminaire controller that would turn the luminaires on or off as needed. Fig. 23.7 shows a schematic of such a system. Depending on the system, luminaire status could be fed directly to a processor, and/ or the processor and lighting control system could be a single unit. Calculations for determining how far ahead of the vehicle to illuminate must take stopping sight distance and decision sight distance into consideration. Stopping sight distance is the distance drivers need to come to a complete stop, and decision sight distance is the distance drivers need to perform evasive maneuvers [7]. Calculations would take place inside either the processor or the luminaire controller.

23.4.1.2 Results and lessons learned VTTI developed and researched a rudimentary version of such an on-demand system as described above [8]. The system utilized commercial off-the-shelf (COTS) Direct Short Range Communication V2X equipment to sense the vehicle position and custom lighting controller system based on COTS wireless transceivers. The system operated successfully and repeatably at speeds up to 60 mph. The most significant challenge with the system was latency in the wireless systems, which required network tuning to reduce. The research showed positive public acceptance of the system and limited if any impact on driver visual performance under most conditions.

23.5

Potential challenges

Smart lighting challenges include legal implications, public opinion on the LED luminaires, lighting levels, and cost. These challenges can be addressed through careful planning and execution.

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Others have discussed legal implications [3], which are complex. In summary, a narrative documentation of the calculations and design decisions as well as the standards or basis used in the calculations and decisions will likely be accepted as reasonable effort in protection of the public from harm. However this is not to be construed as legal advice in any form. Public opinion can be addressed through informational meetings designed to educate the public on the reasons for deploying smart lighting and smart-city services and devices. Once informed that the system reduces cost, reduces impact on human health, reduces impact on the environment, and impact on flora and fauna, the change is usually embraced. Informational meetings, especially where public opinion is officially collected, recorded, and incorporated into the final design demonstrates to the public that their opinions are valuable and heard. Finally, increased cost of smart lighting deployment can be addressed in a variety of manners. Several private studies have shown the payback period ranges from 6 to 10 years depending on initial costs. There are public private partnerships where the municipality and corporate entity divide initial costs and cost benefits of the installed systems over a long period of time. In addition, there is privatization of services such as illumination whereby lighting becomes a service the municipality pays for, which in some cases is no different than luminaires and pole currently owned and operated by power companies. Lastly, due to the modular nature of the smart lighting system, the municipality can stage the deployment of a smart lighting system. In that case, the municipality can start by installing LED luminaires with NEMA7 receptacles, but does not deploy a control system. The receptacles are filled with shorting caps (always on) which are usually provided by the manufacturer and the luminaires continue to be controlled by the power switching stations on a time schedule or dusk to dawn basis. Later on control nodes could be deployed in sections or by street type as funds are made available. In a final phase, all of the lighting is tied together with an automation system operated from city offices with a varied collection of control schemes, sensors, and timers.

23.6

Summary

Smart lighting allows a “precious balance” of lighting to be applied at the location it is needed, when it is needed and only in the correct amount. Smart lighting makes the urban environment safe for humans at night while improving quality of life both night and day while enabling a more harmonious existence of technology, humans, flora, and fauna that cannot be achieved with traditional technology. Smart lighting provides the ubiquitous power and control networks that can be the initial backbone for smart-city services and technologies. The basics and some advanced concepts of “smart lighting” were reviewed as well as the benefits of such as system. Smart lighting consists of dimmable LED luminaires with sensor and controller interfaces, a controlling system, and support infrastructure. Smart lighting, when adaptive lighting is implemented, can reduce

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lighting energy usage by as much as 50% while providing higher-quality light for improved safety. Utilizing sensors, a smart lighting system can reduce light levels significantly until needed by users, which can significantly reduce negative impacts on human health and the environment. Lastly, the usage of smart lighting infrastructure as a jumping off point for smart-city devices and services was introduced. Excess power is made available in the lighting power lines by smart lighting and the smart lighting controller network has extra bandwidth for additional smart-city services or data collection and transmission. Smart lighting is available now and offers significant potential benefits to cities. Smart lighting seems to be the logical starting point of any smart-city plan. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

23.7

Chapter review questions/exercises

23.7.1 True/false 1. True or false? A luminaire is a device that is comprised by a light producing object; optics designed to direct the light in a needed direction and distribution; any electrical components required to power or control the light producer and/or the optics; any heat dissipation devices; a structure to hold all of the components; and provide a means of mounting the object. 2. True or false? Solid-state (LED) technologies have improved vastly in recent years, and are now one of the best options available for roadway, parking-garage, and parking-lot lighting. 3. True or false? The intelligence in smart lighting comes from the controls. 4. True or false? A dimmable driver is typically available standard with any LED luminaire, but may be optional or special order, depending on the specific luminaire design and manufacturer. 5. True or false? A dimmable driver is typically available standard with any LED luminaire, but may be optional or special order, depending on the specific luminaire design and manufacturer.

23.7.2 Multiple choice 1. Most lighting controls are ______ on either cellular networks or IEEE 802.11b at 2.4 GHz—an early Wi-Fi standard: a. Transparent b. Wireless based c. Sufficient d. ICT-enabled e. Preferred 2. Most smart lighting control systems utilize a network with a luminaire node controller (sometimes called a gateway) that acts as a:

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a. Gateway b. Network c. Single access point d. Interface e. All of the above 3. Adaptive lighting is defined as adjusting lighting levels to the current conditions on a schedule or: a. A schedule-based system b. Lighting control system c. Sufficient light levels d. Utilizing sensors e. Translucent cover 4. Once deployed, a smart lighting system can provide the backbone for other smart-city applications, due to its: a. Freeing up power b. Mobile services readiness c. Infrastructure d. Ubiquitous features e. All of the above 5. For smart cities, the most important aspect of smart roadway lighting system is the fact that its features are relatively standard and: a. Efficient b. Ubiquitous c. Important d. Utilized e. Adapted

23.7.3 Exercise 23.7.3.1 Problem How can you reach an interoperable smart lighting solution over the emerging machine-to-machine protocols, such as the constrained application protocol built over the representational state transfer architecture?

23.7.4 Hands-on projects 23.7.4.1 Project Do research: Look at smart lighting systems and the different Internet-of-Thingsenabled communication protocols, which can be used to realize the smart lighting systems in the context of a smart city.

23.7.5 Case projects 23.7.5.1 Problem How are smart streetlights enabling smart cities?

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23.7.6 Optional team case project 23.7.6.1 Problem How do smart traffic lights connected to a cloud management platform, allow for the monitoring of green light timings that automatically alter the lights based on current traffic situations to prevent congestion?

References [1] J. Bullough, Introduction: assessing the benefits of adaptive roadway lighting. ,onlinepubs.trb.org., June 2001. [2] R. Gibbons, F. Guo, A. Medina, T. Terry, J. Du, P. Lutkevich, et al., Design criteria for adaptive roadway lighting, McLean, VA (August 12, 2014). [3] R. Gibbons, F. Guo, A. Medina, T. Terry, J. Du, P. Lutkevich, et al., Guidelines for the Implementation of Reduced Lighting on Roadways, FHWA, Washington, DC, 2014. [4] ANSI/IES, RP-8-18 recommended practice for design and maintenance of roadway and parking facility lighting, in: ANSI/IES RP-8-18, Illuminating Engineering Society (IES), 2018. [5] G. Brainard, et al., Sensitivity of the human circadian system to short wavelength (420nm) light, J. Biol. Rythm. 4 (2008) 1 8. [6] R.J. Lucas, et al. Measuring melanopic illuminance. Available from: ,http://lucasgroup. lab.manchester.ac.uk/research/measuringmelanopicilluminance/., 2014 (accessed 2017), July 22, 2011. [7] AASHTO, Geometric Designing of Highways and Streets, American Association of State Highway and Transportation Officials, 2004. [8] M. Palmer, R. Gibbons, and A. Jahangiri. On-demand roadway-lighting system effect on visual performance and public impressions, in: TRB Annual Meeting, Washington, DC: The Transportation Research Board, 2016.

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Tuncay Ercan and Mahir Kutay Faculty of Engineering Universite cad., School of Applied Sciences, Yasar University, Izmir, Turkey

24.1

Introduction

Data have become common information for ideal city management. Data sharing and compilation across the city has increased and gained depth, at least at the level of critical services. However, in the 21st century, all traditional services and computer networks that make information and data from other sources into a single architecture are at the forefront of city life. During the 20th century, while electricity, water, and heating services were the head of the digitalization of these services; today, the consumption and efficiency standards of all used resources should be especially shaped for the megacities. This brings us to the concept of smart cities. In this way, innovation capacity will be increased for all services, productivity increase will surely be provided and technological development will be provided in all services. In addition, current information technologies will be integrated into the process of doing business and providing services. The use of digital technology should, in fact, appear as a public service, and all systems, particularly critical services, should be able to serve both residents and managers. This will be achieved by adopting an understanding of smart services rather than smart products. In compact cities, service users should be balanced and support the disadvantaged disabled and elderly population. Therefore while developing policies to keep the population density at a level appropriate to the resources of the city, it should not forget the difference in services of disadvantaged groups. Critical situations are determined by the location of any asset in the system to which it belongs and its relationship with other assets there. Critical infrastructures are the essential systems that their continued operation is required for the security, economy, and the public’s safety and health for a country. They are similar in all nations but their importance changes according to a nation’s needs, resources, and development level. Department of Homeland Security in the United States identifies 16 different sectors for critical infrastructures like energy, communications, electrical equipment, transportation, dams, defense industry, emergency services, health, water, and waste water systems [1]. Local administrations, which are responsible for the majority of the technical infrastructure of the city, have the authority in the construction, supervision, and coordination of the services related to the technical Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00024-3 © 2021 Elsevier Inc. All rights reserved.

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infrastructures. Necessary permissions for all of the facilities that can pass through the underground (like freshwater and wastewater canal projects of the city, electricity, natural gas, geothermal, telephone, TV connection lines projects, metro system, subway, energy-supply projects, central heating channels, and so on) are under the responsibility of Infrastructure Coordination Center in cities [2]. The chapter is organized as follows. Section 24.2 gives additional information for critical infrastructures in cities and summarizes the reliability and vulnerability terms in this context. Section 24.3 begins with the critical communication systems in our scope. Sections 24.4 24.7 discusses energy, water, public transportation, and emergency services in turn gives with recommendations and solutions for the future for each section. Section 24.8 summarizes the chapter.

24.2

Critical city infrastructures

24.2.1 Overview Critical infrastructure describes the physical and cyber systems that are so vital to the nations. However, as the population of cities increases, the importance of critical systems increases. Moreover, as the urban populations of cities increase, the role of infrastructures for city services has become even more important. The protection of critical systems and assets should be carried out not only by the state but also by private companies that own many critical enterprises with the utmost importance. The quality of everyday life in cities depends on the reliable operation and intelligent management of all critical services like electricity, water, communications, transportation, and emergency systems [3]. The consequences of failure of critical infrastructures can lead to major social, health, and economic problems, and this is in turn the reason why developed countries are working hard to protect and improve their critical infrastructures [1,4]. As the design, size, complexity, and interactions of critical systems are increasing, management, control, and monitoring of errors that may occur are becoming increasingly difficult. This has made human-centered control tasks and automated process management systems even more modern to improve the reliability and fault tolerance of critical services. It is increasingly necessary to find effective methods to estimate the reliability of all existing critical infrastructure networks and to identify cost-effective strategies through interdisciplinary efforts to increase their durability [5]. Fig. 24.1 shows the main critical infrastructures and their related functions and services in a city [6].

24.2.2 Identifying critical infrastructures As we already know that the identification of critical infrastructures is one of the main components of the complete risk-management process. When you think about the point of probable concerns like terrorism and natural disaster threats, it is important that the service providers and governments figure out the critical assets

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Health Financial Transport

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Figure 24.1 Critical infrastructures [6].

for national security in order to prioritize risk-management efforts. There is no doubt that this task is not easy while deciding which assets are critical even if while comparing them among many different infrastructures or industrial sectors. This section reviews the protection policy of the critical infrastructures in most of the countries and analyzes the key requirements and methodologies. Critical infrastructures may, by definition, concern more than one country, but different countries’ definitions of different critical sectors bring about other differences in the protection of these systems. Adopting an integrated network view of critical infrastructures will be of great help in predicting difficulties in finding effective solutions, especially for failures. Reliability, which is one of the characteristics of an assessment scale, is an indicator of the stability of the measured values obtained in repeated measurements under the same conditions as a measurement tool. It is necessary to trust that the information provided with the scale has a stable feature and the same results will be obtained in a second measurement for the same purpose [7]. Networks of critical infrastructures should ensure the functioning of our society to provide us with the services critical for everyday life, like water and energy [5]. As urbanization increases, the number of critical facilities increases, indicating that the dependence on these critical infrastructures increases continuously. This also requires the examination of communication networks of critical structures, their consistency, reliability, and the continuous reduction of potential problems and failure rates with modern technology and engineering. The integration of natural gas pipelines and

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electricity networks means that the pipelines supply fuel to electrical generators, and cyclically the compressor and control systems in the gas network use this electricity [5]. Since smart cities are regarded as a reflection of the information age and information society, they naturally include the advanced hardware and software capabilities of the latest technologies like industrial control systems, Internet of things (IoT), supervisory control and data acquisition (SCADA) systems [8]. Therefore cyber security of all existing critical infrastructures in smart cities has become a vital issue for both regional and national securities. At the same time, critical infrastructures in smart cities are vital in the provision of community-oriented public services by central and local governments. Concepts like risk, threats, and security gaps are sensitive terms for national security and have been included in the cyber-security literature. While weaknesses in critical systems or in the utilities provided to the community bring vulnerabilities, these vulnerabilities in the system cause risks and threats. Therefore it is important for governments to produce and implement public policies to avoid threats to these services and critical infrastructures. A threat mitigation, risk assessment, and detailed management plan, including physical, logical, and methodical cyber security measures, should be drawn up among different critical infrastructures that are related to each other in order to prevent vulnerabilities. Intelligently, functionalized information and communication technology (ICT) infrastructures are required to ensure sustainability and efficiency in the critical utilities, and they also include integrated infrastructures and services that can be monitored and controlled by smart devices [9]. Fig. 24.2 shows the interdependencies among critical infrastructures in a smart city [4]. Perhaps the most important of the challenges in assessing the reliability and flexibility of critical infrastructure networks is that all networks are strongly interconnected, dependent, and include complex feedback loops. The use of ICT depends on the availability of available resources in the systems, accessibility of the relevant infrastructures

Interdependencies: x Physical x Cyber x Logical x Geographic

Transportation

Water Emergency services Electricity

Government

Financial Communications

Figure 24.2 Critical infrastructure interdependencies [4].

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and user preferences. The connection authority of these systems to each other can be changed as required when it is important for cyber security. Therefore different security levels and user accessibility for different functions in intelligent systems are important to identify the available options. There is a lot of administrative action that needs to be formally completed when an excavation is necessary for any of the critical infrastructures like water, electric, and natural gas. Public institutions and organizations that will carry out excavation work within the metropolitan areas are required to obtain an excavation license from the Infrastructure Coordination Directorate within the municipality. Illegal excavation is applied to all excavations without a license and a criminal procedure is applied. Examples of infrastructural dependencies of critical systems are given in Fig. 24.3 [5]. In this way, the institutions responsible for the existing infrastructures (electricity, telecom, fresh and wastewater organizations, natural gas, and geothermal) are also informed. The existing facilities are processed by the infrastructure organizations on the given sketch and the approval is given as “observer is required or observer is not required.” Although interdisciplinary research is supported, interdisciplinary cooperation in the field of critical infrastructure networks is still in its infancy [3].

24.2.3 Protection of critical infrastructures It is a well-known fact that one of the challenges in assessing the reliability of critical infrastructure networks is their being strongly interconnected and mutually dependent. Different types of interdependencies in infrastructures, including, physical, cyber, geographic, and logical interdependency have been studied [10]. A systematic framework is necessary to assess the vulnerability of critical infrastructures to cyber, physical, or social attacks [11]. Cyber networks, critical infrastructures integrated with hardware

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and software are now the core components of smart cities. Public institutions and/or private ICT service providers are responsible for the establishment, operation, and management of all information systems used in smart cities and critical infrastructures [9]. Any poor performance in one of the interoperated networks can have a negative effect on other systems like measuring the sensitivity of a system with the weakest component, which may result in a serious problem or even a disaster in the global economy. The coordination between public and private centers is the most important issue in providing cyber security in the smart cities. Interdisciplinary collaboration is probably the easiest way to understand how to assess the reliability of critical infrastructure networks and how to make them more flexible. Some nongovernmental organizations and government agencies are conducting courses and framework programs designed for people who have emergency-management responsibilities [12]. With these programs, they are trying to train all stakeholders like city, town administrations, critical infrastructure owners and operators, and private sector partners, in the critical infrastructure community to support the implementation of the National Infrastructure Protection Plans.

24.3

Communications

24.3.1 Overview The communications sector is one of the critical infrastructures for nations and enables operations of all businesses and governments across all other critical infrastructure sectors. It provides the interconnection among the national and global entities by using different types of medium like wired, terrestrial, satellite, and wireless transmission systems. While faster and more efficient processing of information provides businesses with the competitive advantage necessary for today’s market, direct access to key business values, intelligent communication platforms, and strong management potential depend on the current capacity of the systems. International and national communications services to service providers depend on each other to carry the traffic flowing on them and terminate. The private sector has the majority of communications infrastructure and mainly responsible for protecting sector infrastructure and assets during outages and times of crisis and handle recovery efforts. The term “mission-critical-communications” is the ability to deliver necessary communication assets where traditional networks cannot meet demands. Currently, public safety organizations and critical utility infrastructures are frustrated by the limitations of their data-transfer capability over their dedicated networks. However, new technological developments provide higher advantages than conventional fixed broadband systems and help utility providers set new standards to provide wireless and mobile broadband systems for network connectivity with technologies like 3G, 4G, and LTE. As a result, the demand for high-speed wireless broadband services required for both commercial use and for some communications in critical systems is constantly increasing. The communications sector is closely linked to the energy

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sector, which operates base stations, head offices, and other critical facilities and also needs communication to monitor and control electricity distribution. In addition, in the event of an emergency, it is linked to the emergency services sector to direct assistance resources, coordinate responses, operate public alarm and alert systems, and most importantly receive emergency 911 calls. Monitoring and controlling the flows of land, sea, and air traffic of transportation services, which provide the necessary fuel to generators that will generate electricity with petroleum or other energy source, are also realized through communication [13].

24.3.2 Channels used for communications Communication between public institutions and of course citizens is important for the political, economic, and social structure of the country, and disruption of critical services can lead to state-citizen communication problems and may also lead to instability in society [14]. The increasing use of different social media elements has changed the relationship between government and citizens. These new forms of communication represent an interactive communication channel that allows citizens to freely express their views on government policies or governance. However, governments can sometimes overcontrol these channels to increase their governance impact, or on the contrary, a small group of dissident citizens may influence the public by proposing different views to influence the government’s decision-making process. Therefore governments sometimes compare virtual public spaces to other physical public spaces where regulation is necessary [15]. (Non)governmentcommunication channels are used as traditional communication tools and official news sites used by the public to disseminate by official organizations/governments and to get the information by citizens about the critical infrastructures. An example of these news sites is the citizen communication center, which is run by municipalities in most cities and allows citizens living in the city to communicate directly and easily with the municipality services like water and public transportation. If the solution to the subject you require time, you will be given a registration number and your transaction will be tracked.

24.3.2.1 The flexibility of communication systems The fact that we all know very well is that almost all communication services were initially established by state institutions, commercial organizations, and educational institutions to serve the interests of the public. Global connectivity is the current degree of telecommunications today in which people and services everywhere are connected, independently of location. This brings us the potential of interconnectivity and accessibility of different information systems being used by critical infrastructures. Flexible information communication infrastructures for smart electricity grids or control systems for water and natural gas systems should be run for monitoring, operation, customer and supplier side management, and quality of service control. Wireless sensor networks and radio frequency identification (RFID) are the essential technologies in focus to support the critical infrastructures in the city and

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they help information reliability, flexible network reconstruction, quality of service, and security analysis. For the network, these applications are critical and provide end-to-end communication. This makes it necessary to research and invest to achieve a reliable communication infrastructure.

24.3.3 Safety and security of communication systems Telecommunications is a key factor for community, business, and government operations, and many factors are taken into account when designing or modifying these systems, especially on the trust and reliability issues [16]. Different types of security services in the field of communications should be provided no matter the range covers simple or complex systems like a home or enterprise security systems. Security systems can be observed in two areas where how you use the existing security technologies and what are the existing security tools. However, the focus should stay in that additions and modifications to the system (different utility constructions like natural gas, electricity, water, as so on) are simple enough to implement and reliable. The best way of designing supporting structures for the safety and security of communication systems in critical utilities is to combine the experiences of technical and management people in an innovative and cost-efficient methodology to easily build up a solution-oriented and flexible control system.

24.3.4 Recommendations and solutions The communication technologies already used by critical systems especially should closely follow all current developments in their field. Developments should be monitored not only for the management systems of the relevant sector or service but also for the coordination of critical systems that are integrated. Modernization of communities depends on the quality of existing infrastructure facilities and their efficient operation. Physical infrastructures like transportation systems, water and energy supply, prevention of waste problems, and communication systems ensure that everyone in the society can maintain an effective city life. Technological developments and service-oriented economy have brought telecommunication and information infrastructure to the foreground especially in urban life [17]. Some of the emerging technologies like fifth-generation wireless mobile communications systems, augmented reality, the IoT, and big data analytics that those critical infrastructures may use, are expected to make a significant impact on public safety and critical business applications. Fig. 24.4 explains the view of state-of-the-art studies for the communication environment in critical infrastructures [18]. The number of critical systems increases in proportion to both the population in the region and the number of service providers in this sector. In this case, all systems operating naturally require updating from time to time. There are two main factors for mission-critical-communications: (1) the natural demand for developments in mobile device capabilities for information transfer and flexible communications in the field. (2) A greater and more flexible capability for public safety within the focus of governments and municipalities standard interoperability, integration into legacy systems, is

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Figure 24.4 Communication environment for critical infrastructures [18].

crucial for the transition to mesh and hybrid-based solutions for future critical communications [19]. In the near future, there is likely to be an increasing demand for communication of critical services, and therefore all suppliers need to be ready to offer the highest levels of reliability, scope, flexibility, and functionality. In the future, the interconnectivity of computer networks will increase not only the access to information, but also the chance that people can access it from their location. The “IoT” has come into the scope of utility service providers in a short amount of time. The smart gadgets can easily be connected by this concept and enable providers to control them to manage energy costs from anywhere. It is expected that new patterns of interpersonal communication for customers and service providers will emerge from the widespread use of this technology and help to estimate the reliability of critical infrastructures. Of course, realistic, site-specific models are required to address failures. Examples include cross-sectoral interdependence modeling, feedback loops, modeling human error, and interaction with online social networks. By combining the field knowledge and expertise of many engineering disciplines (system analysis, applied mathematics, statistical physics, and computer science), the challenges outlined must be successfully tackled [5]. The OECD Council’s proposal for the Protection of Critical Information Infrastructure (2008) provides a high-level policy framework for the protection of national policy and critical infrastructure information protection (CIIP). In 2019 the recommendation was revised in order to align with the 2015 Recommendation on Digital Security Risk Management [20]. This report includes current riskmanagement practices, strategies to monitor the roles and responsibilities of different stakeholders, public private partnerships, and information sharing. Smart city infrastructure has been described in the context of sustainable development including smart digital infrastructure, smart buildings, smart mobility, transportation, utilities (energy, water, and waste), healthcare, and ICT for smart digital infrastructures [21]. It also provides an overview of digital urbanization in the context of global urbanization trends and smart cities. The importance of an integrated approach to the smart city infrastructure is highlighted in this reference. The authors presented some key challenges when implementing smart city projects, and explained how to be strong with numerous case studies from all over the world to overcome these challenges.

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Solving Urban Infrastructure Problems Using Smart City Technologies

Energy (electricity, gas, and oil)

24.4.1 Overview The energy sector, which enables it to function in almost all critical infrastructure sectors, is crucial. Thus it can be integrated to growth and production throughout the country [22]. The energy infrastructure is divided into three main categories: electricity, oil, and natural gas. They include power plants (coal, nuclear, hydroelectric, oil, and renewable sources) to produce electricity.

24.4.2 Smart grid infrastructure We are in a period in which technology is increasingly taking place in our world and making life easier. With developing communication and Internet technology, all utility service networks can be remotely commanded. Smart grids are the intelligent systems obtained by integrating the 20th-century electrical networks with the developing 21st-century computer and network technology. With an increasing number of subscribers, like increasing populations, increasing energy needs to be controlled. Electrical networks are a service provider and user network operated by one or more control centers connected by transmission and distribution lines. Most people refer to electricity transmission systems by the term “grid or network” [23]. Fig. 24.5 shows a complete smart grid infrastructure [24].

Smart factory Smart grid

Smart warehouse Smart community

Smart healthcare

Smart transportation

Figure 24.5 Smart grid infrastructure [24].

Smart hospitality

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As the need for all kinds of information from the electricity networks increases, the intelligent network initiatives enable the network components to communicate with each other by automating all processes on the part of the end user and the service provider, and also assist in maintenance and future planning. Electrical energy is transmitted through a system called electricity distribution network from the power plant where it is produced to the end users in residential areas. These power lines can easily be seen if you live in a suburban or rural area. Upgrades in the technology allow the electricity generated by end users to use solar panels or wind generators to connect to the public grid and even to be paid to ourselves. Governments are also investing in intelligent network infrastructures that use digital technology to manage energy resources more efficiently. Smart grid projects help to increase the total capacity by accessing other renewable energy sources like geothermal energy and wind power plants [25]. The potential to generate energy in today’s production facilities is obvious. This has led to the emergence of new forms of energy production to meet the growing need for energy. These systems should be monitored and controlled remotely and technical problems that may occur at the points where they are connected to the network should be managed [26]. Smart grid is a holistic solution to reduce losses and energy costs of existing and/or new power lines by using information technology resources. Smart grid technologies have numerous applications that are capable of accessing variable and distributed energy sources depending on the demand and availability of smart meters in the end user. Smart meters encourage electricity consumers to use energy at affordable and different price rates. Smart meters both create a balanced demand and reduce expensive power usage in the existing grid system. Consumers can see real-time price information through in-house indicators.

24.4.3 Smart grid system usage in the world The term smart grid is used in addition to the expression of a new technological solution for future grids. The main issue in smart grids is that it can collect and analyze data from all parts of the electricity grid in use and present these to both service providers and end users to solve the problems in the electricity source. This information and the reactions shown cover the entire electricity transmission and distribution system from electricity generation to consumption. It is considered the replacement or the natural evolution of the century-old power grid. Countries like the United States rely on power grids, but are concerned about power outages and problems from small parts of the grid. Most interruptions are also due to a lack of automatic analysis and slow response times for toggle switches [27]. The European continent has taken care to develop and use smart grid technology as it gives importance to renewable energy sources. However, the most important problem of this continent is, of course, its geographical conditions. Because the solar, wind, and wave energies of this continent are from different regions rather than a single region, smart grid applications are preferred to increase efficiency rather than the static grid. However, the usage of smart meters, which are the basic materials of smart grid applications, is also increasing. As a result of the studies

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carried out, predictions say that by 2020, 80% of European consumers will switch to smart meters. In India, this system is needed more than in other countries. Because India has the weakest network infrastructure in the world. As a result, energy losses are much higher than in other countries. Due to this situation, the first major breakthrough was made in 2008. In the near future, with big investments, the transition to regional smart networks has started. In China, new productions and new lines are being created very quickly. Therefore it is one of the countries that need the most need of a smart and developing network system [26].

24.4.4 Microgrids A microgrid is a small-scale power grid that either operates independently or is connected to the main grid in the region. A grid is defined as a microgrid, if it has its own electricity generation, resources, loads, and definable limits. A microgrid can act as a back-up and buffer during interruptions or high demand periods affecting the main grid. The microgrid is microgrid automation that enables a group of distributed renewable energy sources connected to each other to be integrated into the main grid and operate synchronously. Microgrid’s group includes renewable energy sources like wind, solar, gas turbines, small hydropower, geothermal energy, biomass, biogas, and battery. Microgrid technology can operate independently of the smart grid network or connected to the public network. Microgrids use distributed renewable energy sources for not only electricity generation and but also store energy. However, it may adversely affect the network in bad weather and power outages. Microgrids are used to create a grid structure with sufficient power generation and balance sources during the interruptions to enable automatic operation, independent of the grid, by forming a safe and reliable supply line by balancing the power quality (voltage and frequency) with the required energy transition. The microgrid network must be connected to the local network to prevent consumers from being affected by power outages [28]. Microgrid application is known as distributed, distributed, decentralized, regional, or built-in power generation. Fig. 24.6 shows an infrastructure of microgrid [29]. This intelligent energy automation connects the energy sources using the IoT and a networked control system and provides the following advantages: G

G

G

G

In the event of power outages or disconnection from the central grid, generators and/or batteries of the microgrid can serve microgrid customers until electricity is available from the grid [30]. Microgrids reduce energy costs for consumers and businesses and also generate revenue by selling the generated energy to consumers. Microgrids use a wide variety of renewable energy types. These resources provide clean energy without damaging the environment. Microgrids serve as an auxiliary source network during peak demand periods of central networks and this strengthens the central network.

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Smart digital infrastructure

Smart health

Helps monitor differernt parameterst of the city: analyze the data collected

Smart buildings Improve comfort of users ; optimize usage of utilities,

Shift in focus to prevention: remote access to healthcare and personalized healthcare solutions Smart mobility

Smart infrastructure Smart weste management Improve efficiency of waste collection, pickup, separation, reuse and recycle

Smart water Reduce cost and leakage; increase reliabiliy and transparency of water distribution

Optimize traffic conditions; customize traffice solutions; reduce environmental footprint Smart energy Optimize energy distribution and usage; enable communitybased enegy monitoring

Figure 24.6 Microgrid [29].

24.4.5 Natural gas Providing people more energy is one of the biggest challenges of the 21st century. Natural gas can help with this situation by replacing coal and diesel and thus improving air quality by reducing emissions. Gas is a reliable partner for renewable energy sources, helping to balance electricity supply and demand, providing support for other renewable sources like wind, solar, and hydropower. Natural gas is vital in some areas where the economy needs electricity and energy, like industrial processes and freight transport. For example, the use of gas instead of coal in the textile industry makes a significant contribution to reducing costs, improving greenhouse gas emissions, and improving air quality. In heavy industries like iron, steel, cement, and chemicals, the use of gas instead of coal will also reduce hazardous emissions to provide the high heat required for furnaces. Natural gas is also a key component for sectors like plastics and fertilizer production [31]. Natural gas replaces wood and coal in heating and cooking in homes and businesses, helping to improve health conditions. Combined heat and power systems reduce greenhouse gas emissions and are extremely effective for heating. The integration of natural gas and electricity will provide great savings for consumers. Combined and interconnected heat and power units for industrial, governmental, and private facilities are examples of a smart city application [32]. DTE Energy, one of the best operated energy companies in North America, strives to be a power for social growth and prosperity in the production and transfer

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of different energy types by targeting innovation and economic development dimensions [33]. They also make every effort to ensure the smooth and safe operation of natural gas systems, and also provide information on how to recognize and report natural gas leaks in an emergency through their own websites. Natural gas leaks are extremely dangerous, but since natural gas is odorless and colorless, it can be difficult to detect. Therefore in order to easily identify natural gas leaks, a harmless substance is added to the natural gas, which allows leaks to smell like rotten eggs. The same is true for almost all national gas service companies.

24.4.6 Renewable energy resources With the rapid growth of the world’s population, the demand for energy is increasing. Although the availability of renewable energy sources is limited, the benefits of protecting the ecological environment and providing economic advantages are extremely important. Because the use of fossil fuels for energy needs causes greenhouse gas emissions that cause global warming. However, even considering the life cycle of renewable energy sources, it is very important for public health that it does not cause little or no emissions and air pollution [34]. Renewable energy sources can offer fixed energy prices at lower costs. It can also create opportunities for the development of local industry and increased job opportunities. Renewables increase the reliability and flexibility of the energy system and energy supply in the eyes of the society and the users [35]. In order to meet the energy needs of future generations and to minimize the damage to the environment, we need to focus on sustainable energy sources. Sustainable energy sources are experimenting with the energy produced to meet the required need without risking energy sources. Renewable energy sources also play the most important role in sustainability and meeting the need. Electricity production from renewable energy sources is increasing. As an example for production of electricity from renewable energy sources in Turkey. There is a 90,458 MW of installed generation capacity in Turkey, 43,333 MW of installed capacity of renewable energy power plants [36]. Despite these figures in the area of total wind, geothermal, and solar energy and hydraulic installed power, the renewable energy ratio among the energy sources used in Turkey is at very low levels. However, Turkey has very significant potential in many other renewable energy sources. Renewable energy sources can create many opportunities for use in services like heating, cooling, and transportation. Solar thermal water heaters, biomass boilers, and heat pumps can meet the heating demands of end users in buildings. Reducing energy demand in buildings and different industrial sectors is the key to a renewable-based energy system, and therefore a national policy approach to the efficiency of renewable energy will be important. Solar energy can be used in industrial heating and cooling industry like food processing, pulp preparation, and paper. The hydrogen produced by the electricity generated through the use of renewable energy can meet the needs of industrial processes requiring high heat in the iron, steel, and chemical industries. Reducing fuel demand in the transportation sector is critical, which can be achieved through national policies that promote energy efficiency [34].

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24.4.7 Recommendations and solutions Pipeline companies use lots of methods to monitor the overall system. Visual inspections should be done regularly (by walking, by using drones, or by electronic monitoring). Because operators need to safeguard this infrastructure against vandalism and damage as well as ensuring safety and environmental compliance. Micronetworks also use local energy sources to regulate their local power and resource requirements and contribute to improving the efficiency of the entire energy system, thus they are automated by intelligent technology and microgrid control system, in order to anticipate problems and potential negativity. This intelligent energy automation combines sensors and electronic systems that connect energy sources, microgrid, and cloud-based storage of real-time data, by using the IoT and a networked control system. System software uses the data to control energy sources. It determines the right energy mix to meet the microgrid operator’s objectives by continuously analyzing energy demand and weather conditions. For example, the software can be programmed to switch from the sun to the battery when it receives weather forecasts indicating an impending rainstorm [28].

24.4.7.1 Advanced heating, ventilation, and air-conditioning systems Heating, ventilation, and air-conditioning (HVAC) systems are critical to the (inter) national-wide economies with the cost of diminishing natural energy resources. Therefore smarter cooling and heating systems, which are more energy efficient have become a necessary investment. Especially, in the case of more efficient HVAC systems are demanded in most government regulations, the use of intelligent systems and sensors to automate instantaneous performance values and maintenance needs in these systems is very important. Therefore while the high-efficiency systems naturally provide greater comfort and energy savings, the most advanced heating and airconditioning units will have intelligent controls and sensors to keep homes and offices cool in summer and warmer in winter [37,38]. HVAC building air-conditioning automation systems are divided into two as central and individual air conditioners. In the central air-conditioning system, the heat source in a single location uses it to exchange heat to cool or heat each room to the specified temperature while circulating air, water, or steam to various rooms. The only cooler in the system cools the water, circulates in various rooms. The coolant heats up slowly during this circulation. Water is cooled by contact with air and is then reused. Pumps are used for water circulation. Heat sources can work with different products like gas, oil, or electricity and ultimately heat the water in the boiler to produce hot water or steam. The resulting hot water or steam circulates inside the building and provides heating. The coolers also cool the water first and then distribute the cold water to the various rooms and exchange heat. After the cooling water slowly heats up with the heat exchange, the water is brought into contact with the air in the cooling tower to be cooled again. Pumps are used to circulate water. Although heating and cooling are not performed simultaneously, if the cooling and heating coils have their own outlet and inlet pipes, simultaneous heating and cooling may be possible in the same building.

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HVAC systems use air, water, or refrigerant for heat exchange. Some central air-conditioning systems use a method called variable air volume. In a water-cooled system, cold or hot water is circulated through the pipes and the fan coil units change heat to adjust the temperature of each room. The growing concern and demand for more effective smart storage grids motivated and helped to realize new and better energy storage capabilities to prevent the requirement for new power plants. The storage of energy can quickly respond to instant increases in demand. This reduces the need to build additional power plants by making smart grids more responsive. The efficiency of these plants is measured by how fast they can respond to changes in demand and how fast they can store energy again [39]. Pump storage (PSH) is a type of hydroelectric energy storage. There are two water reservoirs that can generate power as the water moves down from a turbine, consuming power when pumped up. Fig. 24.7 explains how PSH works [40]. The PSH system is defined as an open loop with a connection to a natural water body or a closed loop where the reservoirs are not connected to an external water body. Although there is widespread use of pumped-storage facilities, technological advances are mainly aimed at battery storage. However, battery storage systems can only store energy for approximately 4 hours or less and are unfortunately far from the goal of replacing traditional energy networks. Battery systems are therefore mainly used to integrate renewable energies into the grid and provide relief to the grid during peak hours. Over the last decade, the cost of energy storage for solar and wind energy has been steadily reduced due to the low costs of lithium-ion batteries, and has triggered renewable energy sources to provide additional solutions for dual storage [39]. Energy storage is the most important requirement for electric vehicles (EVs). As the use of EVs increases, the need for night charging will also increase the demand for electricity. EVs also have the chance to provide energy back to the energy grid. Therefore old EV batteries can be used as second-hand energy storage [39].

The smart grid

The smart home

Operation centers

Distribution intelligence

Renewable energy

Consumer engagement

Plug-in electric vehicles

Figure 24.7 Open/closed loop pumped-storage hydropower [40].

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24.4.7.2 District heating and cooling District heating networks provide flexibility in fuel selection, making it possible to switch to renewable sources. Thus water heated by any fuel can be distributed to users throughout the region. District heating consists of a heating plant and a pipe network filled with hot water. The hot water is circulated from the heating plant to the customer and the reheating plant with pumps. The heat exchanger in the customer building transfers the heat from the district heating network to the building’s own heating and hot water systems. The water used for heating is pumped back to the plant where it is reheated from the return pipe. The method commonly used in district heating systems includes waste water, heat pump, combustion process, and electric boiler. Regional heating and cooling is independent of scale according to the current biofuel source. District heating and cooling provide significant environmental benefits for the community in the environment and allow the economic use of natural resources [41]. The energy sector is aware of its risks when considering its available resources and therefore continuously increases its planning and preparation. Collaborations between different industry sectors have led to the sharing of best technological practices among themselves. Many sector owners and operators have recently focused their attention on the protection of their infrastructure on cyber-security efforts in energy services [22]. An intelligent energy consumption usage model that can be analyzed in ideal conditions is possible with complex systems analysis. With complex system analysis that is larger than the sum of its individual parts, all aspects of the scientific capabilities possible to develop future energy system scenarios and to analyze aspects of cost, operability, and sustainability can be integrated. In smart cities, there can be many different models of analysis that can be created regarding energy consumption. It is very important to monitor every process through different levels like the storage, power cycles, and communication infrastructure of the energy obtained from different renewable energy sources [42].

24.4.7.3 Sector coupling The use of renewable energy sources in heating, transportation, and industry instead of fossil fuels naturally requires new technology and rules. Therefore electrification of the whole economy cannot be shaped due to the different solutions offered by all stakeholders at national and international level. The sectoral integration and coupling will at least help the industrial units in the same sector to make a joint decision [43]. While modern buildings are expected to cause minimal damage to the environment in which they are located, they are planned to be energy efficient and provide a sufficiently full, usable interior. Because people typically spend most of their daily lives indoors and rely on the lighting and air conditioning provided to them. This has led the construction industry to become the largest component of energy consumption worldwide. To give an example for the United States, building energy consumption has increased by 8% in the last 20 years. In 2016 the majority of the total electricity consumed by residential and commercial buildings in the United States was used in HVAC and artificial lighting applications. Integrated building

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management, including HVAC, solid state lighting, and automatic shading systems, has been critical, as environmental, economic, and political considerations make it necessary to reduce energy consumption in buildings. The following figures show different components available in a typical building management system and the possible interactions and sensor couplings among them [44]. Smart grids are a critical system for integrating renewable energy sources into the electricity grid. Since renewable energy sources like solar and wind are variable, it is very important to have electricity networks that use energy efficiently and respond to different demands. Due to the need for smart grids, policy makers at all levels have begun to look for ways to increase energy efficiency in electricity generation and use in homes, businesses, and public institutions. Smart grids have become a critical basis for reducing greenhouse gas emissions and moving to a low-carbon economy, especially since they can be more easily integrated into renewable energy sources [45]. Policy makers should provide smart network practitioners with the necessary physical and financial incentives to promote development across the country through their active roles in the development of smart grids. In addition, smart grid technologies are infrastructure projects that promote both sectoral growth and new business opportunities. In addition to providing power generation through renewable and green energy, smart grids are an effort to modernize the entire grid by providing better control and flexibility in terms of management.

24.5

Water

In almost all countries, water supply systems are critical infrastructures responsible for providing uninterrupted and quality water to people. The water systems used are water transmission and water distribution networks. The water transmission system is responsible for transporting water from natural or artificial sources to water treatment plants to improve water quality. Safe drinking water is a prerequisite for protecting public health and all humanitarian activities. Properly treated wastewater prevents disease and protects the environment. Therefore drinking water and wastewater treatment and water transmission and distribution services are essential for the modern life and economy. Limited water resources can pose risks to national economies. According to the estimates of gross product and population growth, in 2050, one-quarter of the world gross product is expected to be produced in these certain locations. They are almost river basins and home to almost a quarter of the total world population. Rational use and good management of water resources in developing economies can directly affect the national and world economy [46].

24.5.1 Overview The water utility systems nationwide include drinking water and wastewater systems. The availability of sufficient and high-quality water for the people living in the area

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is a necessary condition for the diversity and sustainable development of the food as well as for the future of all humanity and freshwater ecosystems. These systems are vulnerable to malicious activities like pollution, physical attacks like the release of chemicals and even cyber attacks on infrastructure. These conditions can cause a large number of diseases and/or casualties, and problems that can affect economic viability. Many other adverse effects may occur in other sectors like firefighting and health services, energy, food, agriculture, and transportation systems. The pressure on this vital value is increasing day by day. One of the main reasons for the increase in demand for water is the diversification of water usage areas. Today it is one of the most important inputs for many economic activities, including water, energy and food production. Water is used extensively not only in hydroelectric production but also in the production processes of new energy sources like fossil fuels or shale gas.

24.5.2 Infrastructures for water systems It is a well-known fact that water systems are facing serious difficulties due to population growth, socioeconomic development, security problems, urbanization, and environmental destruction. In all academic and political studies, formal decisions can be taken at dialog meetings for the evaluation of common water resources and recommendations are made to all countries of the world. These recommendations include the need for more technology and research, greater support for international cooperation agreements, the development of further education on the water as a resource, and the implementation of significant reforms in economic sectors like agriculture. The water supply system consists of water storage facilities and water distribution networks in all areas receiving quality water from the nearest pump station in the region. Fig. 24.8 shows a general infrastructure for water systems shown in a fictional city “Highlake” that have two residential areas and an industrial area, as well as a water supply system for the city’s water needs [47]. It is estimated that by 2050, energy demand will increase by two times, while food and water demand will increase by 50%. It is necessary to understand the dynamics and connections between these three sectors in order to understand potential opportunities, some of the options and synergies that should be waived, and to develop integrated solutions that can meet the growing demand for resources.

24.5.2.1 Leakage detection and control Water supply systems may have problems due to failures that could compromise their correct operation and reduce their reliability and performance. These failures may be of structural or hydraulic origin, in particular water supply systems, pipe failures, pump and valve failures, tank aging, and illegal connections. The effects of the failures are water leaks and pressure loss, followed by water outage. The aim of water demand management is to provide the same service level with less water. Thus the water supply process is provided more economically without developing new resources. There are a number of demand management measures in the literature, like measuring water used, price policies, the use of water-saving instruments,

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Controlle

On

r

Microgrid Off

Other microgrids

Energy markets Weather forecast

Figure 24.8 Water systems infrastructure [47].

changing water use regulations, consumption restrictions, leakage control, and training. For some developed countries where urban water distribution systems are rather outdated, this is a serious and very difficult measure to implement. Water leaks can occur both in the network and in installations in buildings. The first one finds a very large proportion and water administrations should determine the amount and location with a systematic program and then reduce it. Almost all 50% leakages in drinking water networks show how important the issue is. Leaks control time and because it is a process that requires welding, the savings at the tap will mean a much greater saving in welding when all losses are considered. Although not as much as network leakage, there can be significant losses in homes or workplaces. Their rapid repair will result in significant savings. The location and amount of leaks are important. The following procedures are used for effective leak detection. G

G

G

G

Installing regional counters Analysis of night currents Research with sound correlator devices SCADA system

SCADA system consists of establishing a common control system by equipping the whole network with regional meters and sensors measuring various characteristics of water (flow rate, pressure, speed, and so on) and transferring the obtained information to a control center [48].

24.5.2.2 Water efficiency via smart metering As a result of rapid urbanization, cities are struggling to supply water efficiently as well as to meet the maximum amount of water demand. In order to manage limited

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water resources efficiently, city governments have turned to ICTs. The smart ICT solutions needed to ensure the efficient use of valuable and limited resources can both reduce water losses in the system and can be used to develop demand management strategies. Advanced metering infrastructure and/or smart meters are systems that provide support for both the supplier and the consumer, which should be included in this ICT infrastructure. Smart meters provide early warning of customers’ past consumption data, identification of usage differences, determination of water expenditure efficiency in homes, setting targets for water savings, and possible leaks [49].

24.5.2.3 Water quality monitoring Water is an important natural resource that must be monitored by the quality of the entire system used continuously to ensure reliable use. This is because water resources are particularly vulnerable to pollution threats from industrial activities. Traditionally, water quality determination is a manual process in which water samples are collected and taken to laboratories for analysis. This, of course, is a significant challenge in terms of implementation, especially due to the constraints on manpower, appropriate plant, and equipment costs [50]. Water supply monitoring and control systems (SCADA) used for management and control purposes may be subject to problems that may significantly or lessen system reliability and performance from time to time due to hardware/software errors, cyber attacks, and power outages. Another alternative method to monitor the current state of water resources is to use multiple sensor systems to control water quality. In such a system, sensors capable of reading the chemicals, conductivity, dissolved oxygen content, pH value, and turbidity can be used to monitor the general quality level of water [50].

24.5.3 Recommendations and solutions Especially among countries that are bound to natural water resources, even at local and regional level, sometimes water use can pose problems among stakeholders. Water itself is both a renewable natural resource and can clean itself repeatedly in natural cycles. Water use problems in our world are mainly caused by various human and natural factors. These problems can normally be divided into water quality, water quantity, and environmental ecosystem problems. IoT can offer a great solution to improve water management and ensure efficient use of this valuable resource. While reducing the costs associated with the maintenance of water systems, it provides information on real-time water-level status in different storage areas, holds values like oxygen, chlorine, and salinity in the water, thereby increasing the amount of usable water [51]. Although water is the main driving force of both economic and social developments, it has a fundamental function in protecting the integrity of the natural environment. The fact that water is a vital natural resource requires unity and cooperation among stakeholders in all water-related issues. All managers,

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whether in the government or in the private sector, must make an honest and fair decision on the allocation of water. Since demographic and climatic changes further aggravate the need for problems on water resources, it is more accurate to look at water management in a holistic approach. Water solutions should be flexible enough to meet the dynamic water demand of the population and maintain sustainability. This was the beginning of an internationally recognized integrated water resources management for efficient, fair, and sustainable management of all water resources around the world [52]. Fig. 24.9 explains the stages of this plan. The most intelligent allocation of water resources means the development, use, protection, and management of these resources in the most fair way. Ecological protection of water resources means controlling the time-space distribution of water resources through engineering and nonengineering measures like environmental control, new resource development, a systematic decision-making method, and the use of computer technologies [53]. Water solutions should naturally be flexible to meet the dynamic water demands of the population to maintain continuity. Therefore life, agriculture, infrastructure, and energy requirements should be supported with a durable and sustainable water cycle in order to use the limited water source at hand [54]. All agricultural businesses require a dynamic and sustainable water strategy that balances agricultural production and commercial imperatives with environmental and social responsibilities in the region. The IoT and remote sensing techniques, which are used in almost every industrial field today, have been successfully used in the field of agriculture to collect and analyze data on different subjects like control of water resources used, soil quality, monitoring of product status, and aerial control of crops. The availability of quality water is crucial to improving the quality of life as well as preventing the spread of diseases and even infectious diseases from the use of contaminated water [55]. It is possible to continuously monitor the water quality with a wireless sensor NATURAL GAS SUPPLY CHAIN Gas field

Processing

Oil and gas wells Gas processing gas wells to specification coal seams odorization compression metering

Production

Transmission

Gateway

Distribution

Pressure reduction and regulation flow metering Liquified Large Gas-powered natural gas industrial generation Transmission

Figure 24.9 Stages in IWRM planning and implementation [52].

Residential Distribution

Commercial

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network to be used on the basis of IoT. In such a network, data are collected instantly from sensors placed in pumping stations, and the water transmission system in the usage areas, even in the other industrial facilities like energy and chemistry, or in the areas of agricultural use, then sent to the central units over the Internet. According to the types of sensors used in the system, data collection, processing, and analysis are designed for monitoring the quality, pH, conductivity, and temperature of the water [56].

24.6

Public transportation

24.6.1 Overview The quality of life in a smart city rises and falls with the public transportation that is available. Decreasing traffic congestion and increasing the mobility of the people of the city is the biggest challenge facing crowded cities today. Traffic congestion deeply impacts the daily activities of the people, decreases the efficiency of business life. To solve these big problems, city planners are trying to develop smart transportation for optimizing public transportation. The “intelligent integrated public transport systems” offers the most efficient transportation system for the evaluation of the smart cities [57]. Smart cities need uninterrupted, at high speed and frequency smart public transport services. It should provide service quality better than that of private vehicles. Smart public transportation can totally change the way people commute in metros and smart cities. It provides novel transportation models, highly advanced infrastructure, traffic, and mobility management solutions. Also, integration into other services like connected infrastructure (e.g., traffic light management, congestion monitoring, and parking) should be provided [58]. Important features of intelligent transportation network can be summarized as follows: G

G

G

G

G

Public transportation management Route information Electronic payment system and single fare card Traveler information system Safety and vehicle control

Benefits of smart public transportation are listed as follows: G

G

G

G

G

G

Improved traffic safety, decrease in fatal traffic crashes Reduced traffic congestion Shorter travel times and increased mobility Increase in work efficiency Less infrastructure damage Low-carbon emissions and healthy urban space

The electricity generated by renewable energy sources can give a great impetus to the fleets of EVs that are increasingly used. Vehicle batteries can be used as electrical storage

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units due to their structure. Thus the electricity in a charged car can then be used for home usage. Such renewable source energy can also be used to produce fuels like hydrogen, which is used for long-distance transportation, aviation, and transportation [34].

24.6.2 Integration via information and communication technology applications In smart cities, ICT is considered as an integral part of public transportation. ICT allows integration of different public transportation systems, their operational processes, and citizen engagement [59]. It encourages greater use of public transport and enables a change in people’s travel behaviors. During the last decade, tremendous development in the availability of smartphone ICT applications has been observed. Mobile applications have profoundly changed citizen’s perception of public transport systems. Innovative ICT applications can provide highly important information for passengers and users, like departure and arrival times, current location information, costs, delay status, nearest departure point, and transfer facilities of different transportation systems [60]. For example, in the concept of smart city and smart transportation systems, all components have maximum use of existing ICT systems. Examples of such a modern transportation system are GPS-supported mobile networks, systems that provide pedestrian and vehicle communication, vehicle and sensor networks that use sensors for road and environment information, and vehicle-to-vehicle communication systems that enable communication between vehicles even during movement [61]. GPS modules are installed on the public to track the bus lines and regulate public transport in real time. Data collected from bus GPS network enables route planners to optimize the bus fleet operation and decrease the cost. Passengers waiting on bus stops can monitor the arrival times of the buses at the bus stop displays or by using smartphone ICT applications. The development of ticketing ICT solutions is very similar to the developments in travel information. A means of payment which is becoming more integrated with public transport is the use of smart cards. Today smart cards have an integrated RFID chip, which does not require physical contact. By presenting the card near to a card reader while entering or leaving a public transport vehicle passengers can easily pay. Near-field communication (NFC) technology in mobile phones has some advantages over the smart cards. A major advantage is that passengers using need a vending machine to load credit to their cards. NFC-enabled phones have great benefits over RFID cards. NFC-enabled phones can hold multiple payment applications, like credit card, debit card, travel pass, or prepaid ticket allowing the passenger to select the payment method [62].

24.6.2.1 Electrification of motorized public transportation Electric bus usage in public transport bus fleet is growing all over the world. Electric buses have higher costs compared to fossil fuel busses, but they also provide significant cost reduction because of reduced maintenance and fuel in

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high-mileage use cases. Today, most of the public transportation buses that are used all over the world use diesel fuel completely. As a result of this usage, the amount of carbon dioxide added to the air by a single bus is around 100 tons in a year [63]. Pollution from the emissions of diesel engines is an important problem for local air quality in cities around the world. Therefore EVs have received unprecedented attention from a large number of users and investors. So in the 21st century, EVs are now an attractive solution to replace traditional transport as energy efficient and environmentally friendly. Electricity powered buses are safe, emission-free, and silent but to build-out electric bus charging infrastructure and providing enough electric power is required. EVs have brought new opportunities for electricity networks. Some infrastructures like charging stations, a communication link and a control interface and control system are needed to provide the electrical charging of the EVs. The biggest obstacle to increasing number of electric buses is the state of the electricity supply networks. As much as the architecture of these structures, which require a physical infrastructure, the charging power and voltage of the EVs, and the reduction of charging times should be high enough to provide the owners with sufficient advantages [64].

24.6.2.2 Integration of parking and public transportation system As the public transportation system improves, private car use reduces, traffic congestion minimizes and living conditions in urban areas enhances. This target can be achieved by the integration of private car parking and public transportation systems. Integrated parking management should ensure rational use of the available parking spaces near the metro/train stations and central public transport bus stations. Therefore the park-and-ride concept could be seen as a solution to relocate the mass parking areas from the most valuable city areas to the peripheral zones [65]. Smart parking systems use automated parking which operates like robotic valet parking. The driver drives the car into an entry station, by inserting a ticket/card into an automated terminal the car is lifted to its parking space and delivered to an exit area when demanded [66]. Smart cities should provide drivers, online/offline payment, information on parking availability, and an e-receipt through mobile applications as a technological improvement. Intelligent car parking systems increase the ease of use, security, and efficiency of public car parks. The main features of this system are to reduce traffic congestion in the parking lot, to have fast entry and exit facilities, to detect parking spaces with the help of mobile applications, ease of payment, and to identify violations within the parking lot [67].

24.6.3 Recommendations and solutions Although intelligent transportation systems are increasingly part of daily life, the provision of public transport is a difficult city service to fulfill due to different factors that make it difficult for regular lines to operate in traffic congestion and

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tariffs. Public transport networks in cities and central settlements provide a relatively good opportunity for the public to reach their desired destinations within the city. However, most tourist sites in rural areas are not integrated into public transport systems. Flexible transportation system (FTS) services, which are on the agenda especially for touristic regions, are a flexible approach to the problems related to the public offering of public transport services in rural areas with low population density. In this sense, the FTS is a solution to cover the last kilometer of tourists’ travels and offers an alternative means of transportation to the people living in the area [68]. While comparing public and private transportation systems under the concept of smart cities, public transportation always stands out for reasons like less air pollution, less traffic jams, relatively determined travel time, and availability [69]. Because the transition to public transportation will provide these qualities at all times with both easy-to-use features and a wide network spread all over the city. New technologies like traffic management automation, new smartphone applications, integration with GPS systems, and navigation can be brought to a more rational and flexible position for public transport or private vehicle owners. It should be noted that the use of EVs will save a lot of energy not only in individual vehicles, but also in transport systems like public transport or logistic transportation. New battery technologies will not only increase the range that vehicles can drive at full charge, but also reduce charging time, and help balance electricity supply and demand everywhere [70]. EVs also have the potential to become a large-scale storage system, enabling more integration of renewable energy systems into existing electricity networks. The unused batteries of individual vehicles can return the stored energy as an alternative electricity source to the system during high consumption times in the electricity grid. Such a situation can offer great advantages in terms of basic load balancing and variable power generation throughout the entire electrical system. Intelligent transport system (ITS) aims to gather and analyze public transport information, allows bus operators to take advantage of the data for efficient operation and management to provide the users of public transit with the necessary information, and thus to enhance the service quality. Bus management system (BMS) for the operators and bus information system for the users are used separately. But we should not forget that there are some limitations for public transport to overcome in order to ensure competitiveness against cars like taking more time [71]. ITS aims to improve the overall transport system with positive impacts like efficiency, information dissemination, road safety, traffic conditions, and energy consumption. Quality in transportation is achieved through three main functions: improving road safety, reducing pollutants and energy consumption, and achieving consumer standards. Road safety can be easily enhanced, even with a training program for drivers in public transport and logistics transport services, which enables drivers to understand the use of smart card, BMS, and GPS technologies. The assessment of driver training should be carried out not only by the reduction in bus-related traffic accidents, but also by the timing of bus journeys and the rearrangement of bus routes [71].

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Emergency services

24.7.1 Overview Emergency services must be delivered with accurate real-time data from any connected device. Obtained data should provide the first responder’s potentially life-saving information like accurate location, the health situation of the victim by any means of communication. It is very important that all critical resources can be intelligently detected and managed with modern ICT technologies using IoT during emergencies and disasters in the city. IoT devices and sensors collect and share crucial information for emergency responders. An effective data exchange system integrated with IoT provides better response times, better resource allocation, lower casualties, and decrease errors [72].

24.7.2 Fire detection and prevention Fires have always been scary, wherever they may be, and their consequences should not be underestimated. People should raise awareness about fire and have knowledge of firefighting in order to minimize losses and damages during fire. Smoke detectors and even flame detection systems are technological systems that provide us with the first information during a fire. However, these systems should be designed to meet firefighting and firefighting requirements to provide information to property owners, security guards, or firefighters and should be integrated into intelligent systems [73]. NB-IoT-based intelligent smoke detection systems will be used in place of traditional smoke detectors by integrating with other intelligent systems and meeting these requirements. Fig. 24.10 shows such an architecture of the smart smoke alarm

Wind

Solar

Hydro

Biomass

Geothermal

Figure 24.10 NB-IoT smart smoke alarm system [74].

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system [74]. Smart sensors, integrated with this fire detection systems improve fire safety within apartment buildings. Fire detection systems are capable to communicate emergencies and impacted occupants. Building codes require smoke alarms to be installed in each apartment unit. They provide a local sounder alarm to alert the occupants of smoke or fire. Modern fire alarm systems replace traditional smoke alarms with smart smoke sensors. These sensors can be connected to the buildingwide fire alarm system, to notify building managers and other residents in the event of an emergency. These smart sensors can also identify highly lethal carbon monoxide (CO) gas. CO is invisible, tasteless, and odorless, it cannot be recognized easily. When CO is detected in an apartment, the fire alarm system notifies occupants and building management, to take necessary actions to resolve the problem. When emergencies occur, integrated fire systems communicate to all systems of the building, including fire alarm sounders, mass notification systems, emergency lighting, and HVAC control [75].

24.7.3 First-aid alerts Public safety services in cities collect information through active emergency calls and direct it to the relevant emergency services. However, for first-aid calls, the initial shared information may not be complete and the person receiving the call may not be able to provide full information to the relief teams. That’s where intelligent systems come in. Intelligent sensors in the IoT system can provide real-time and detailed information to public safety personnel, like better assessing emergencies, entering data into relevant distributed information systems, implementing appropriate services immediately, and reducing response time. Smart sensors and smart city technologies supported by IoT enable public security institutions to use these systems. Many cities around the world use a large sensor network that captures critical data for first-time responders. When emergency managers are notified by their own staff, they can use public safety communications and information systems to contact other emergency services and refer their teams to designated crime scenes [76]. Fig. 24.11 explains IoT-based emergency care delivery process [77].

24.7.4 Emergency response optimization Current dispatcher systems do not consider the consequence of their allocation decision. To increase the effectiveness of the emergency services, the following questions should be answered: G

G

How long will it take for the first team to reach the target location? How many teams will be ready on the emergency response centers during a time interval? [78]

All kinds of resource planning and allocation that can be used in emergencies is very important. Because new information technologies provide real-time management of emergency events. In emergency response systems in smart cities, all citycritical resources can be intelligently detected with ICT capabilities, and systems

Smart cities critical infrastructure recommendations and solutions

Cooling tower RR-1

Ventilation duct

Outdoor-air RR-2 processing unit

VAV controller

Ventilation duct

FCU controller

VAV

Window

Intake opening

Outflow opening

AHU

531

FCU

2-pipe system

Chiller

Cooling water pumps

2-pipe system

Heat storage tank

Heat source (boiler)

Machine room

Feed water pump

Figure 24.11 IoT-based emergency care delivery process [77].

can be automatically controlled and managed as part of a larger network. Finding the right or closest locations when an emergency call is received is possible with advanced geographic software analysis. Of course, these determinations are also based on the experience of previous analyzes, especially on the abundance of call data in the past. Therefore the location of ambulance waiting points for ambulance access times in relation to first aid was decided as a result of these analyzes [79].

24.7.5 Recommendations and solutions When firefighters are called to a burning building, it’s critical that they understand who might be trapped inside the blaze. To quickly identify victims, IoT sensors, including Bluetooth low-energy beacons, can be placed within homes and other structures to provide indoor positioning information. Proximity sensors can determine an individual’s location to first responders, and way finding applications can guide responders to people inside [76].

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A patient with an emergency case is provided with a wearable device that collects the necessary physical data from the body and transmits information to the emergency department located at the nearest location. Thus an ambulance is sent to the patient who receives emergency information. Fig. 24.12 illustrates the IoT scenario in smart hospitals [80]. In an emergency situation, you never want to be alone. Therefore in the context of smart cities, perhaps the most important for human life is the immediate assistance needed in any emergency. This emergency service covers to receive accurate emergency information in a fully integrated communication system, access to information about people in need of assistance, directing the teams to the scene in the fastest way, and monitoring and controlling all processes. These solutions should also be kept in a big data platform to help the government or private emergency services make critical decisions and eliminate disasters and individual accidents. Panic buttons are used in many different industries for different purposes, especially safety because of their simple usage. These buttons are designed to collect immediate assistance in an emergency and are usually fixed devices connected to monitoring stations or emergency services. However, with the advent of intelligent security systems, the functionality, flexibility, and mobility of panic buttons have been further improved [81]. Smart panic buttons are really a turning point for emergency support. Smart panic systems have access to any emergency room you may need in an emergency, and to your own physical security response companies, medical information, and other useful connections. When you call your crisis managers to which you are connected in an emergency, they will call you back and access the most appropriate support you need. The Smart911 is an exemplary service that you can use from your mobile phone. With this system, citizens will be reached faster

OPEN-LOOP PUMPED-STORAGE HYDROPOWER

CLOSED-LOOP PUMPED-STORAGE HYDROPOWER

Projects that are continuously connected to a naturally flowing water feature

Projects that are not continuously connected to a naturally flowing water feature

Upper reservoir

Penstock/tunnel Powerhouse Generator/motor Turbine/pump

Upper reservoir

Penstock/tunnel Powerhouse Generator/motor Turbine/pump

Lower reservoir

Not to scale

Figure 24.12 IoT scenario in smart hospitals [80].

Lower reservoir Not to scale

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in case of emergencies. Because with this system, direct contact with the relevant rescue units will be established in any emergency events that may be exposed to air, traffic, or society. If necessary, coordinate between different institutions will be initiated. Along with the personal information, home, location, health, and other private information that is allowed to be shared will be transferred automatically to the relevant units from the moment we are defined in this Smart911 call [82]. Smartphones also provide medical indicators that can be accessed from the emergency call screen, which may be important in emergencies, like allergies and other medical information, and may also allow you to create a medical ID [83].

24.7.5.1 Crime prediction The most successful smart cities are those that use data collected from all available systems to predict and prevent crime and terrorism. Along the way, the key to building a safe urban environment is to modernize the existing infrastructure to provide intelligent information. In doing so, smart cities increase their security features by investing in all technologies that improve artificial intelligence, public transport, and city security. In addition to the many data obtained in smart cities, all the information systems used are data and problem oriented and accelerate the decisionmaking process [84].

24.7.5.2 Smart surveillance Applications within this scope may include video recordings focused on specific gathering areas, systems to analyze the behavior of human communities that may suddenly occur in different regions at different times, and various purpose sensors and their management mechanisms placed at certain points called hot spots. For example, in the United States, there is a service that will help fight all kinds of crime using advanced digital surveillance systems. In this system, the cameras are equipped with sound sensors to automatically direct them to the place where a sound is heard. Cameras and sensors are so sensitive that even in firearm use, even technical information about the gun can be transmitted to the relevant information systems before the police arrive at the scene [85].

24.7.5.3 Disaster early warning systems Alert, alarm, and early warning news must be communicated in a timely manner to at least all citizens living in the area. The technological infrastructure established for this purpose should be bidirectional, not only for informing the public, but also for gathering information for emergency situations in the region. Integrated alert and alarm systems must ensure that the nation’s own warning and alarm news and the disaster and emergency threat news in the region to be received from the news source institutions and are transmitted online to the provincial disaster and emergency management centers established in the regions against any threats and dangers that may endanger the life of the community. Thus the warning of the people in the areas that can be threatened is provided. For example, IoT for All is a

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technology media platform dedicated to providing high-quality, unbiased content, resources, and news focused on the IoT and many related industrial sectors. Central early warning systems empower communities to be prepared for and deal with natural hazards. However, the effectiveness of such systems should be measured in terms of Saved Lives and reduction of losses. This is directly related to the implementation of a response expected by people and institutions after the natural warning is given. Early warning systems traditionally consist of three stages: monitoring of the first events, forecasting of unsuitable events, and warning notification in case of events in catastrophic rates [86].

24.8

Summary

Services like water, electricity, natural gas, public transportation, and health, which constitute the critical infrastructures in cities, can lead to large-scale economic damage, disruption of public order, and even loss of life when their integrity or accessibility is impaired. Critical infrastructures generally consist of three layers as physical systems, human resources, information system, and assets. Each city has critical facilities that require further security measures. Facilities like power plants, telecommunication power stations, and water plants are important components of a city’s infrastructure. The deterioration of these systems can create a mass impact on society, leading to threats to the city and its people, from economic losses to social unrest and even to major vital disasters. Therefore it is very important to ensure that critical facilities are well protected. While some of the critical infrastructures use traditional information systems, the other part is monitored or managed by special information systems called industrial control systems. SCADA system as being the one of the industrial control systems, constitutes the basic information system in many critical infrastructures. Because SCADA systems are the systems used to centrally monitor and control the components of a geographically widespread system. Technology spreads into almost all areas of life, consciously or unconsciously surround us. Technological developments also cause a technological transformation in the lives of the people, so that cities and city administrations take their share from this transformation. Cities have always been home to growth, production, innovation, reason, and knowledge with their dynamic structures. Therefore urbanization and economic development are two inseparable processes. At the point where we come today. Our cities, which are focused on production, innovation, and technology, are on the way to smart searches and applications in order to increase productivity and improve the quality of life. Looking at the current literature and practices, it would be correct to understand the term “smart city” as an effort to modernize the cities to use their resources more effectively and provide better service to the city dwellers. Because, in smart cities, which are basically equipped with computer network infrastructure and Internet, the data received from the sensors used in the whole system are transferred

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to the Internet and the applications realized with these data facilitate both the management of the cities and the lives of the people. In this context, in the case of integrated critical facilities that complement each other; G

G

G

G

Ensuring continuity in water and wastewater services Increasing the efficiency of urban systems, especially transportation and energy Improvements in living spaces like reducing air and noise pollution Increasing the effectiveness of services like health and emergency services to citizens

Intelligent transportation includes integrated transportation systems supported by information and communication technologies. Primarily, it is aimed to provide comprehensive transportation solutions for environmentally friendly and especially disadvantaged groups. Within this component, real-time traffic information is produced and shared with passengers, drivers, and operators. The smart environment includes renewable energy, smart grids, microgrids, smart meters, advanced air pollution monitoring systems, environmentally friendly buildings and urban planning, energy efficient smart street lighting, and smart water management systems. With smart life information and communication technologies make life easier for people and provide a healthier and more reliable environment for city residents. Since these components are applications that feed and develop each other, a holistic approach with a system approach will increase the effectiveness of the applications. The negative effects of global growth and the rapid depletion of ecological resources with increasing population try to reduce the carbon footprint in many cities and to reduce the sustainability of investments through digital applications. It is necessary to identify the issues that cities need especially in the critical services provided to citizens, and to plan and organize all the issues that are expected to be solved (e.g., energy, infrastructure, transportation, buildings, and so on). Rather than reducing operating costs and turning the city into a technological laboratory, the aim should be to improve the quality of urban life with technological assistance at points that are insufficient in current practices, to save on natural resources and energy, and to reduce negative environmental externalities. It is necessary to make investments in the IT infrastructure at the city and even the whole country level. Establishment of technological infrastructure, data collection, purpose-oriented processing, and development of the services provided are the most basic steps toward smart city process in the management of critical infrastructures. The issue of how cities can fully benefit from investments in ICT should be addressed from a “total value chain perspective.” The types of information obtained for this purpose are applications for different urban services, urban dashboards, or optimization algorithms. The acquisition of these can also be done at the end of this value chain with identifiable inputs like suitable devices, sensors, and raw data. If this value chain is sufficiently understood and defined, cities can begin to manage this value chain to promote positive, economic, and social development. The most emphasized technological solutions are water management, clean and renewable energy, intelligent traffic control, e-government, health and emergency services, and waste management. But what is important here is not the technology itself, but the use of technology for the real needs and benefits of citizens.

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The most important issue today in the control of critical systems is the IoT. It is possible to define the IoT as an infrastructure that enables advanced services by linking physical and virtual things/objects based on interoperable information and communication technologies. From this point of view, a series of devices, sensors, communication network infrastructures, cloud systems, and software for the disruptive services of cities should be developed and problems should be solved and sustainability should be targeted. Finally, let’s move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

24.9

Chapter review questions/exercises

24.9.1 True/false 1. True or false? Critical infrastructures are the essential systems that their continued operation is required for the security, economy, and the public’s safety and health for a country. True 2. True or false? Definitions of critical infrastructure and/or related critical infrastructure sectors may vary for countries, which may change the definition of systems used in critical infrastructure. True 3. True or false? One of the challenges in assessing the reliability of critical infrastructure networks is not their being strongly interconnected and mutually dependent. False 4. True or false? The term “mission-critical-communications” is the ability to deliver necessary communication assets where traditional networks can meet the required demands. False 5. True or false? The energy infrastructure is divided into three categories: electricity, oil, and natural gas. True

24.9.2 Multiple choice 1. Which of the following is a power source of the microgrid? a. PV panel b. Wind turbine c. Biogas d. Power storage unit e. All of the above 2. ________________ are the intelligent systems obtained by integrating the 20th-century electrical networks with the developing 21st-century computer and network technology. a. Coal power plants b. Hydraulic power plants c. Smart grids d. Solar power generation plants e. All of the above 3. ____________ system consists of establishing a common control system by equipping the whole network with regional meters and sensors measuring various characteristics of water.

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a. SCADA b. Wastewater treatment c. Stormwater d. Water consumption billing e. Park garden irrigation 4. These smart sensors can also identify highly lethal ______________ gas. a. Carbon dioxide b. Hydrogen c. Helium d. Nitrogen e. Carbon monoxide 5. Smart city technologies, powered by smart sensors and ____________ allow public safety agencies to do just that. a. IoT b. Fire department c. Ambulance services d. Police department e. Public transportation

24.9.3 Exercise 24.9.3.1 Problem What needs to be done to ensure that critical infrastructures are protected and ensure that their continued operation will be an important part of future smart-city ecosystems?

24.9.4 Hands-on projects 24.9.4.1 Project How can the sustainability of a smart city be guaranteed only through ubiquitous communication and decentralized information exchange between optimization and computational models for the operation, visibility, and control of each constituent network?

24.9.5 Case projects 24.9.4.1 Problem What factors are driving or blocking the development of smart cities, as enabled by the application of the IoTs?

24.9.6 Optional team case project 24.9.6.1 Problem Can artificial intelligence be used to develop the many applications that will be needed for smart cities to solve real-world problems?

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[73] HUAWEI, Smart smoke detection. ,https://www.huawei.com/minisite/iot/en/smartsmoke-detector.html.. [74] Pioneer NB-IoT smart smoke alarm system. ,http://pioneeriot.com/?page_id 5 1030.. [75] REMI Network, Smart, life-saving fire safety solutions. ,https://www.reminetwork. com/articles/smart-life-saving-fire-safety-solutions/.. [76] StateTech, How IoT and FirstNet can deliver emergency response in smart cities. ,https:// statetechmagazine.com/article/2019/01/how-iot-and-firstnet-can-deliver-emergencyresponse-smart-cities.. [77] H. Farhadi, Medical Internet of Things (m-IoT), enabling technologies and emerging applications, Royal Institute of Technology, Sweden. ,https://www.intechopen.com/ books/medical-internet-of-things-m-iot-enabling-echnologies-and-emerging-applications/ internet-of-things-in-emergency-medical-care-and-services.. [78] B. Berhault, Limkedin. ,https://benjaminberhault.com//project/post/2018/06/13/reachingthe-optimal-dispatch-for-an-emergency-dispatch-system.html.. [79] ,https://www.iise.org/ISEMagazine/details.aspx?id 5 43713.. [80] Dauwed, M., Meri, A. (2019). IOT service utilisation in healthcare. Available at: ,https:// www.intechopen.com/online-first/iot-service-utilisation-in-healthcare.. [81] S. Moxey, Barry Bros Security, Panic buttons: the future is smart. ,https://www.barrybros.com/2018/12/panic-buttons-the-future-is-smart/.. [82] Smart911, Plan ahead for any emergency. ,https://www.smart911.com/.. [83] Daily News, 11 apps that can save your life in case of an emergency. ,https://www. nydailynews.com/news/world/10-apps-save-life-case-emergency-article-1.2438105., 2017. [84] Smartcity Press, Data-gathering technology is now used to predict crime and terrorism. ,https://www.smartcity.press/ai-for-crime-prevention/., 2019. [85] Smart cities emergency services. ,https://eena.org/wp-content/uploads/2018/11/Smartcitiesemergency-services.pdf., 2016. [86] Early warning systems in the context of disaster risk management. ,https://www.eird. org/cd/indm/documentos/46fad12d0a62e5.38742613.pdf?id 5 281..

The city as a commons: the concept of common goods

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Marco Buemi Turin, Italy

25.1

Introduction

The term commons dates to Mediaeval England and has assumed during history different names and statuses. In mid-19th century W. F. Lloyd underlined [1] that under lack of regulations over a common good exploitation due to self-interest of individuals may lead to depletion of the good itself; his work put the basis for ecology, environmental science, and analyzing issues related to demographic growth. Nowadays the idea of Commons encompass a variety of fields like culture, technology, education, creativity, and knowledge as shared social-ecological system. According to Bollier and Helfrich commons “it is a paradigm that embodies its own logic and patterns of behavior, functioning as a different kind of operating system for society” [2]. If we restrict the topic to urban commons, the practice remains under a wide umbrella touching different geographic and administrative scales going from resources at micro level to cities, and regions. Depending on the level in which the term applies, the results may sensitively differ. The efforts to establish common guidelines and to give concrete contributions at EU level have been several. In November 2016 the first European Commons Assembly was launched gathering activists, researchers, makers, and people active in the movement of commons to share their experience and explore ways to upscale the debate beyond the local sphere. At EU level, a Commons Intergroup was formed as subgroup of the European Parliamentary intergroup on Common Goods and Public Services and its representatives are part of the European Assembly of the Commons. Inter groups are constituted as official forums of the European Parliament to enhance dialog with civil societies and organizations and to raise attention of the Parliament toward specific topics. Even if they are not granted legislative power in the European Parliament, their main challenge remain advancing a Commons Agenda to the political parliamentary stage. The central event in their activity was represented by the crucial meeting with the EU MPs where they had the chance to present something completely new to them, coming straight from the streets of the European cities by doers coming from very different contexts whose main common interest is to foster urban regeneration, housing, service provision, research, education and training, art, mapping, land regulation and consumption, political campaigns, open source technology, food, energy, and climate change. Several other international meetings, and conferences were organized since the Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00025-5 © 2021 Elsevier Inc. All rights reserved.

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movement started having political relevance and influence over law makers to promote the dialogue among activists, academics, and public institutions, and to serve as meeting point with neighborhoods and citizens to propose their own projects for city spaces (gardens, parks, kindergartens, and graffiti cleanup) and showcasing a variety of commons innovators from around the world.

25.2

Defining the topic

The commons and its related concepts have been on the spot of international studies for decades, but they have come to global attention recently, thus, posing challenging questions on both the role of citizens, the third sector in the provision of public services and the structure of public administrations [3]. According to accepted definitions provided by the literature [4], coproduction can be defined as “the mix of activities that public service agents and citizens contribute to the provision of public services. The former are involved as professionals, or regular producers, while citizen production is based on voluntary efforts by individual and groups to enhance the quality and/or quantity of the services they use” [5]. At the basis of the involvement of citizens in the service production process is not only the choice to contribute time and efforts for a common cause but to do so for services people themselves use and enjoy [3]. This new paradigm in service provision makes traditional service planning and management outdated and requires them to be revised and to integrate coproduction into the system so to incentive resources mobilization [6]. According to Alford [7], the reasons why people commit to coproduction range from specifically economic interests or a reward they claim in exchange of their efforts (either monetary or nonmonetary). Other motives are closely related to individual’s values or believes which act as drivers for donations to charities, signing of petitions, or volunteering. This view highlight not only the material interest an individual might have in doing a certain action but also the social value any citizen confer to his/her actions. Another important purpose contributing to coproduction is the normative one, pushing people to participate in the name of values like participation, influence, and democracy [8]. To quote Victor Pestoff, one of the most prominent author and researchers in modern social and political studies in the field: [8] “Citizens’ motivation to become involved as a co-producer will, in turn, depend on the importance or salience of the service provided. Is it a very important service for them, their family, loved-ones, a relative, a friend, or not? This will reflect how the service affects them, their life and life chances. Does it make a direct impact on their life and/or life chances or does it only have an indirect effect? If and when a person feels that a service is very important for them and/or their loved-ones or vital to their life chances, they will be more highly motivated to get involved in the coproduction of services. It is, therefore, necessary to make a distinction between enduring and non-enduring services. Many social services belong to the former category, and therefore have an immediate impact on the life, life chances and quality of life of the persons and/or families receiving them. The importance and impact of such services guarantees high client interest in the development of such services, especially in

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service quality. Enduring social services include childcare or preschool services, basic and higher education, elder care, handicap care and housing as well as preventive and long-term health care. Users of such services are locked into them for a longer period of time and can therefore not normally rely on exit to provide them with influence or redress. The transaction costs of exit are often prohibitive [9] so voice, rather than exit, provides clients with influence and redress.” According to him: [8] “citizen involvement is more than just a question of facilitating greater citizen participation or developing techniques to motivate them. It is a combination of the ease of involvement and individual motivation. In other words, citizens are not like a ‘jackin-the-box’, just waiting for someone to push a lever that will immediately release their energies and result in their engagement in social service coproduction. They need to be motivated to do so, but the greater the effort required of them to overcome hurdles to participation, the greater their motivation must be. However, the greater the effort required of them to become involved in co-producing a public service, the more the service provided by a public agency must be both relevant and salient for them personally. Thus, less ease of involvement may thwart greater citizen participation, even in highly salient services, thereby limiting their participation to ad hoc, spontaneous and individual involvement.” According to Elinor Ostrom [10] several conditions linked to boundaries of the action (territory and group of people, adaptation of rules to local circumstances, involvement of coproducers, role and noninclusive structure of local authorities, and conflicts management mechanism) have the power to determine effective coproduction systems and successful management of common goods and services. Alford [7] also highlights the link between the match between the needs and the mission/vision of the organization in defining a common successful strategy. That means that public administrations have to be aware of what is needed by the population/actors involved and coproducers, paying much attention to the balance between adding value for users and the community. At the same time they need to develop the more appropriate structure for facilitating coproduction. Other conditions contributing to the effectiveness of coproduction are recognized as: specific skills to coproducers motivations [11], new technologies [12], integrative structures and relation capital [13], and organization flexibility and shared responsibility in the services provision [14]. Another interesting issue concerns the effects of coproduction and it also represents the less developed part of the studies in the field [3]. Nevertheless literature has started questioning about it already in the 80s [15] claiming that among the effects of coproduction one can list: cost reduction, higher service quality and increase in citizens’ participation. At the same time coproduction helps in creating better relationships between citizens and the state based on trust, ethical values, and accountability [16]. On the other side it would be a mistake to think about coproduction without taking into accounts its side effects. Actually coproduction can in certain cases be accessible to specific social groups only thus strengthening inside/outside dynamics [17]. Another important issue is that coproduction is generally fostered by wealthier, nonminority citizens thus excluding those part of the population who need the services produced the most [18]. Last but not least, the concept of accountability by itself has to be analyzed as the main actors (i.e., citizens or users) of the process, as would be at the same time for those to held accountable.

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The commons and the OECD

A study published by the OECD in 2011 [19] analyses the partnerships between public bodies, citizens, and civil society organizations (CSOs) to provide better services and face fiscal constraints. The study first identifies tight budgetary environments, constraints to public service delivery; ageing populations, climate change, and the spread of chronic illnesses as some of the most relevant issues governments and national, regional, and local bodies need to face that oblige them to change their perspective in service delivery, and in their relationship toward the market and the society as a whole [19]. According to this perspective, citizens represent a new source of innovation through the coproduction mechanism, which transforms them into service providers themselves (and not only users), thus ensuring control, ownership, greater satisfaction and eventually cost reductions. At the same time coproduction implies some challenges and risks concerning accountability, and training for public sector staff. The definitions of coproduction in literature are several. The OECD study lists those that identify citizens as a resource. Actually citizens are considered not only as volunteers but they become contributors working either together or at the place of professionals [20] to generate value through cooperation [21,22]. This requires the creation of long-term relationships, and the direct involvement of citizens in the service production (input) Bovaird [23], Lo¨ffler and Watt [24]. According to the OECD [19] coproduction is “a way of planning, designing, delivering, and evaluating public services which draws on direct input from citizens, service users and civil society organizations.” According to this definition the benefits derived from coproduction are several: cost reduction as already mentioned, and consequent increase of service efficiency, identification of possible service failures or underperformance, enhancement of societal and individual wellbeing, strengthening of existing tools and mechanisms, improvement of democratic governance, and public trust, creation of social capital. The analysis conducted by the OECD in 2011, in more than 50 countries, also identifies success paths to design effective coproduction schemes, based on factors like attitude and culture; systems and processes; collaboration and partnerships; management and leadership; learning and communication; and resources. The mix between these factors may vary depending on the field and from the change one wants to obtain.

25.4

The commons and the European Union

A technical report of the EU Commission dated 2018 [25], recognizes the importance of coproduction in current public service, and provides study cases from EU countries. Due to the recent socioeconomic crisis the interest European public authorities have shown has been increasing leading the European Commission to state that “social innovation represents an important option to be enhanced at different levels and sector as its purpose is to innovate in a different way (through the active engagement of society itself) and to generate primarily social value” [26].

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The study goes further in the explanation of how coproduction may interact with European social fund (ESF) and it also makes some important terminology differences between coproduction and other trends often used as synonyms. The report adapts the outlines provided by Osborne and Strokosch [27] and Voorberg et al. [28] for the definition of three stages of coproduction depending on the involvement of users and their degree of control and ownership over the process: consumer coproduction (citizens as coimplementer); participative coproduction (citizens as codesigners); and enhanced coproduction (citizens as initiators). Other terms are used often as synonyms of coproduction that need to be clarified. Among them: first ranks cocreation whose origin are found in the private sector to increase exchanges between businesses and customers through a process which has been described by Prahalad and Ramaswamy [29] as dialogue, access, risk assessment, and transparency. This approach entails a better communication with customers, sharing information, and providing full disclosure about risks, prices, costs, and profit margins. Another important concept in social innovation is codesign where all relevant stakeholders are involved directly in the decision making process following, according to Szebeko and Tan [30], six phases: analysis of the issue; involvement of the right people; sharing of findings and consequent decision on priority areas; development and testing of ideas; review and categorization of ideas and opportunities; monitor and evaluation of impacts on individuals, communities and organizations. Coresponsibility is an approach focusing on cooperation among civic associations and citizens aimed at social well-being [31]. The steps leading to coresponsibility are identified in: cogovernance (consultation), comanagement (increased involvement), coproduction, and finally coresponsibility which is reached when citizens are actively and equally involved [31]. The last term analyzed by the European Commission report is coconstruction in the definition provided by Hargreaves [32] as a process aimed at full involvement of beneficiaries (the case concerns student in the learning process) in the design, implementation, and evaluation of the service provided to them. For Hargreaves [32] the coconstruction process is composed of the following elements: engagement, responsibility, independence, confidence, and maturity. All the terms described above share with coproduction several aspects. The main difference lays in the role of public authorities in the process. In this sense Bourgon [33] suggests a framework in which public authorities accomplish both their traditional role to steward society, and promote the development of new abilities to support societies thus integrating cocreation and codesign in the coproduction process.

25.5

Coproduction and the European Social Fund

Before analyzing some of the most relevant Italian best practices, it is useful to outline a general framework of coproduction at the European level to better understand which guidelines are provided by the EU Commission (European executive body) and how it grants national and local authorities more funding chances to enhance

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coproduction and the commons. Most specifically, as explained by the 2018 EU Commission report [25] coproduction shares some of its key figures with the ESF (European Social Fund) and its focus on fostering people participation and partnerships between different social actors from regional and local communities. Such approach is concretely translated into the so-called: Community Led Local Development (CLLD). The origin of CLLD is identified into the LEADER (Liason Entre Actions de De´veloppement de l’e´conomie rurale, that is, link between the rural economy and development actions), a method tested in European rural areas in cofunding with the European Agricultural Fund for Rural Development and soon adopted by the European Maritime and Fisheries Fund that have helped out the creation of some 2600 Local Action Groups. In this context CLLD represents a concrete opportunity to support a single action under different EU Funds; thus, enabling local action groups to cowork and cooperate without overlapping. The main aim of CLLD is to enhance the development of local partnerships for integrated development and it is based on seven principles: an area-based approach; a bottom-up approach; an integrated approach; partnerships; innovative approach, cooperation, and networking (i.e., peer-to-peer learning exchanges) [25]. The report suggests that this method might be used together with coproduction and the two approaches can reciprocally reinforce their power. The growing interest of European authorities in coproduction has been concretely translated into the 2014 2020 programming and the trend seems to have been reconfirmed for the 2021 2027 period. This is shown by the application of coproduction in several context around the EU testifying its power to act as catalyst of citizens participation, to enhance tailored service options for users, and reinforcing the partnership principle.

25.6

The Bologna regulation on public collaboration for urban commons: theoretical basis

The present subchapter is based on the research in urban development of the working group that drafted the Bologna regulation on public collaboration for urban commons [34] chaired by Prof. Christian Iaione who is the author, together with Prof. Sheila R. Foster, of “The City as Commons” (Yale Law & Politics Review) [35]. The following text is based on the findings of Ms. Foster and Mr. Iaione as described earlier. City space has recently come to the attention of many urban movements and policy debates [36] leading social movements to reclaim control over decision making in urban development, and greater access to urban spaces for all inhabitants. The theoretical basis [35] of the contestation is the critique to contemporary urban development as promoter of powerful economic interests instead of supporter of poor or socially vulnerable population in creating more revitalized and inclusive cities. Neighborhood streets, parks, gardens, open spaces, business improvement districts (BIDs), and community improvement districts (CIDs), constitute concrete evidence of how civil society is looking beyond the state to sublocal

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forms of organization; thus, claiming urban resources as “commons.” In this sense “commons” are not only conceived as a right but also as a common stake without need to exercise monopolistic public regulatory control over them. This concept clearly identifies a new paradigm in distributing and managing common urban assets with minimal involvement by the state on the basis of three main principles (horizontal subsidiarity, collaboration, and polycentrism [37]) that contribute to reorienting public authorities away from a monopoly position in using and managing common goods toward a shared collaborative governance approach treating all actors as decision makers, and copartners of a shared “commons.” Despite a lack of attention on the way public spaces are being tackled, it is possible to transform them into a resource for community development thanks to what is recognized as grassroots initiatives. Iaione and Cannavo` [37] refer to grassroots initiatives as those based on citizens getting together to address the issues left unsolved by public administrations. The concept of urban commons shares with grassroots initiatives the focus on collective management of public spaces, and are generally composed of four underlying elements: repurposed public spaces, collective governance, hands-on action, and resulting benefits supporting community and urban development. Benefits of both grassroots initiatives and urban commons emerge from the action of collectively repurposing underused public spaces as a resource for community development, and result in social, economic, and environmental benefits. The debate on urban development has traditionally taken into account the action of three main actors: public institutions, education institutions (i.e., universities and academics), and companies cooperating to generate new models for economic growth. This is the so-called triple helix model [38] where interactions between the actors lead to technology transfer, cooperation, conflict moderation, collaborative leadership, substitution, and networking. The triple helix model is founded on institutional and productive eco systems working together to generate top-down urban development, and the raise of new socio-institutional formats in the production, transfer, and application of knowledge through the cooperation of between enterprises, public institutions, and universities. One of the best examples of the triple helix model is represented by the Silicon Valley and the birth of the “Joint Venture Silicon Valley” in mid 90s. The model has represented and still represent one of the most relevant success cases in this field nevertheless this is not enough to satisfy the new needs expressed by social and urban movements currently in search of an evolution of the model toward innovative spaces and living labs. Such new creative spaces would nowadays serve as tools for local innovation at social and economic level and provide even more effective results if structured to be part of an institutional context of local urban governance aimed at producing knowledge in an open and collaborative city environment. This idea represents the conceptual basis of the cocity (or collaborative city) model [37] which is founded on a three-level urban cogovernance: sharing, collaboration, and polycentrism thus embodying the idea of the city as space for material and immaterial production as per the definition provided by Nobel Prize winner Elinor Ostrom [39]. According to this approach the emphasis of the process is put on creating an institutional and productive ecosystem within cities composed of

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cogovernance platforms to effectively manage common goods. Actually it is clear that, in order to foster more inclusive and sustainable institutions and companies, it is nowadays necessary to include into the process actors from the civil society and the so-called third sector, defined by Carol Rose as “the non-organized public”: [40] social innovators, active citizens, city makers, just to quote a few. Cities do need to reaffirm the idea that reaching concrete cultural and environmental innovation requires to conceive the state as a common and collective space, and the debate concerns all those actors taking action in the creation of new paradigms of cooperation within cities and local communities. This means evolving from the triple helix model toward a five helix [37] one on the basis of the assumption that social innovation represents the catalyst for technological, institutional, and economic innovation. This assumption implies and introduces into the debate on cities, urban and economic development, and public spaces a bottom-up approach. This assumption does also find recognition at EU level as testified by the Pact of Amsterdam signed in May 2016: “In order to address the increasingly complex challenges in Urban Areas, it is important that Urban Authorities cooperate with local communities, civil society, businesses and knowledge institutions. Together they are the main drivers in shaping sustainable development with the aim of enhancing the environmental, economic, social, and cultural progress of Urban Areas. EU, national, regional and local policies should set the necessary framework in which citizens, NGOs, businesses and Urban Authorities, with the contribution of knowledge institutions, can tackle their most pressing challenges” [41]. The pact clearly shows that EU institutions recognize that innovation is generated within and by the society, and it answers social needs first. This idea implies that institutions and companies are not only requested to analyze social needs but to adopt a more sympathetic approach, and to share the production process with citizens and social innovators. The mentioned approach requires as well consistent and effective cooperation between public authorities, private organizations and the whole community at a large, and looks particularly suitable for the improvement of urban welfare states based on integration and economic development. Given the relevance of the role of civil society and active citizens, it is clear how grassroots movements and city of commons concretely enhance social change through new and innovative social aggregations or institutions based on cooperation, mutual help, and reciprocity. In this sense, they serve every day as incubators proactively acting to protect and manage a common good in the sole interest of the community. From an operational point of view when a society pass from shared governance to polycentric governance it has to face the fact that cooperating is no longer enough. It is instead necessary to coproduce new rules together with new, autonomous players. Polycentric governance [37] implies leaving behind traditional administrative models to switch into one considering the public as a collective body entitled to start, implement, and manage decision processes in the interest of the community they represent. Such principle has formed the theoretical axiom to design a methodological protocol aimed at building a collaborative city, the so-called “cocity protocol” [42 which is currently being testing in several contexts and divided into the following phases: knowledge, mapping/codesign,

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trial, prototyping, evaluation, and model design. For each phase, specific operational tools have been designed as well. Following this approach communities get together to provide quasi-public solutions that governmental authorities would not have found alone while specific projects build on the relationship between citizens and existing institutions [43]. In this sense, cogovernance allows citizens and civil society to rethink and reshape their neighborhood and to coproduce a new common together with local institutions [43]. According to the OECD [19] coproduction occurs as a way of planning, designing, delivering, and evaluating public services which draw on direct input from citizens, service users, and CSOs. In this sense, coproduction and the commons lay on the motivation to work in the interest of the community rather than of the single individual/company, and they are likely to be successful if four conditions are met: input and competences are owned by different entities; legal option is available for both parties; participants are able to build a credible commitment to one another, incentives help to encourage input sharing from both public officials and citizens [44].

25.7

Italy and the commons

In Italy the idea of “city of commons” has been implemented in the last decade. Among the first examples we can describe the “Cantiere Barca in Turin” launched in 2011. Barca is located in the North Eastern part of the city of Turin. This neighborhood was built in the 70s to provide immigrants looking for employment in the automobile industry with housing. Its main features are typical of modern urban planning: foresight errors, housing piled up in blocks, and separated by excessive and inhospitable public space; difficult to maintain; lack of commercial establishments, like most of the dormitory suburbs it represented a symbol of inertness for the whole community. In 2011, two anthropologists conducted a series of interviews to map the neighborhood social situation. The results of in situ research were used by some activists groups who used them to launch a project to empower local young generations. Together with some institutional and private partners (Turin City Council, Piedmont Regional Authority, The Goethe Institut; the Foundation de France; and the Compagnia di San Paolo) they raised a grant to organize the workshops currently named under the umbrella of “Cantiere Barca” aimed at training the people participating the carpentry workshops and showing them how to use the tools thus strengthening social ties in Barca and demonstrating its residents how to change their neighborhoods by themselves. The joint effort of the neighborhood residents brought the whole community to turn empty buildings in lively selfmanaged social centers where participants were asked to take common decisions on the developments of the whole area and express their own construction language. Their choice was to use recycled materials and to improve the general environs in the neighborhood through the inclusion of a basketball backboards, football goal posts, a platform serving as a stage, structures to support hanging gardens and a

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wooden construction named “Stella” where children could play. The project and its results were so spectacular to lead the Turin City council to recognize them as “pieces of art” thus nourishing the hopes that the workshops would become a longterm project to be maintained and consolidated as a permanent program. Today, Barca’s carpentry workshop is a place where local people work together with students and young professionals in architecture and design; the former butcher’s shop (closed long before the beginning of the project) is a community facility managed by a group of women from the neighborhood. Some costs are currently shared with Turin City Council who is in charge of paying electricity, water and heating bills but users are fully conscious of their responsibility in keeping and managing the space they have built together. Another prominent example was developed in Bologna by the residents of via Fondazza, who gave birth to one of the first (and most successful) experiments of social street. The idea of a “social street” (www.socialstreet.it) was born in September 2013 thanks to the Facebook group “Residenti in via Fondazza, Bologna” created to promote and enhance social relationships thus facing a sense of loneliness caused by the depletion in social interactions, and to take over control on common urban spaces. The main goals of this residents group were to foster cooperation among neighbors living in the same street, and to exchange knowledge and professional skills to reach common shared goals. The group set itself as an informal one, based on the use of Facebook (wide and free) as a tool to pass from virtual reality to reality with explicit the choice of using a closed group to avoid any commercial or political influence and to limit single groups to a limited territory thus fostering the deconstruction of other identity categories like social classes, interests, age, political or religious beliefs, and geographical origin; a free of charge service promoted a culture of giving without any immediate counteraction and the independence of the model while the absence of a structured hierarchy granted that every individual belonging to the group can take action if in compliance with general guidelines. Last but not least the group and its initiatives focus on what is relevant for people and what can aggregate them and avoid discriminatory language and actions. Excluding any economic, political, and legal structure showed to be very effective and resulted in being the real innovative feature of Social Streets that differentiate it from any other experiences promoted by associations, committees and other structured bodies. Today more than 450 groups started similar experience both in Italy and abroad, showing the need to develop social interactions free from any political or economic aspect.

25.8

The Bologna regulation on public collaboration for urban commons

The preceding examples represent important steps in creating a favorable environment for grassroots initiatives and for the commons in general. Nevertheless the turning point was in 2012 when bottom-up initiatives were officially recognized, and institutionalized. The process started in 2012 thanks to an initiative launched in

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the city of Bologna by Fondazione del Monte di Bologna and Ravenna acknowledging the constitutional right of citizens (Article 118(4) of the Italian Constitution) to represent a powerful and reliable ally to public administrations in putting new stimulus, energy, talents, resources, capabilities, skills, and ideas to improve the quality of life of a community thus contributing to its survival. The initiative is based on a “City of Commons” background study presented in Imola during a workshop in December 2011. After the workshop the idea was presented to the city of Bologna whose Mayor decided to run an administrative experimentation program. A research unit first collected and analyzed cases carrying at least some collaborative governance features in Bologna and other cities to demonstrate how they might represent an effective tool in updating the traditional paradigm of government. The research unit together with an ad hoc task force created a steering committee with the aim to design experimentation to get a prototype of governance and regulatory tool based on the principles of horizontal subsidiarity and collaborative governance mechanisms. Local residents were facilitated in managing three urban commons by city officials and a local partner to test experimental partnerships between the City and its inhabitants. On the basis of the results obtained and best practices from this test the Mayor of Bologna appointed three City Officials and two external experts to draft an innovative piece of local regulation to submit it to public consultation and review by some of the most prominent Italian administrative law scholars. At the end of February 2014 the draft was presented in Bologna and successfully submitted for final approval to the City Council in May 2014. The project was awarded the medal of representation of the President of the Italian Republic, and made available to all Italian cities and Mayors.

25.9

From the commons to the city as a commons

The Bologna regulation on the urban commons offered the chance to Prof. Iaione and Foster to put into practice their theoretical basis, to give birth to further researches and analysis of what is referred to as cocity, and to lay down the foundation not only of the cocity protocol but also to several research hubs distributed in different continents. The main aim of the cocity protocol [45] and the work of Lab. gov.city (a research platform codirected by Professor Sheila Foster and Cristian Iaione) is to serve as an international network of theoretical, empirical, and applied research aimed at exploring and developing methods, policies, and projects on shared and collaborative management of urban spaces and resources, and to build a global community engaged in enhancing innovative urban project supporting more inclusive, sustainable, equitable, and collaborative cities. The vision of Lab.gov.city is not only to promote innovative urban policies to cope with large-scale urbanization processes, social and economic inequalities, socio-spatial polarization, equitable access to technology and CO2 emissions in accordance with sustainable development goals and the new urban agenda, but also to shift from single commons to the idea of cities themselves as commons [46]. In its search for innovative urban solution Lab.gov.city coordinated the publication of the cocity open book, a

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joint effort [47] by several scholars, researchers, public institutions, universities, students, and CSOs that provides a common general framework for urban transitions, and guidance for policy makers, researchers, and urban communities involved in cogovernance approaches. The research analyzed field experiments in several Italian cities together with more than 200 global case studies from different geopolitical contexts. The study conducted gave the chance to develop a protocol based on three elements: the principles, the processes and the tools, aimed to foster innovation through urban commons founded, as previously mentioned, on sharing, collaboration, and polycentrism. The protocol is composed of three main elements: the design principles (a set of basic design drawn from study cases that identify cocities, i.e., collective governance, enabling state, social and economic pooling, experimentation, and technological justice), the cycle, and the tools. According to the protocol, the cycle (also called as cocities process or policy cycle) involves six phases: cheap talking [48], mapping, practicing, prototyping, testing, and modeling. The phases of the process are structured so to grant a participatory process taking into account the identification of the common interest (existing or potential), fieldwork activities to map and visualize them through the help of digital technology so to better understand their specific urban contexts and proceed into the design and prototype phases accordingly. After the first phases, based on the analysis of the context, the next steps concerns experimental phases aimed at creating synergies between emerging commons projects and local authorities so to extract specific characteristics and needs from the direct involvement of various actors: institutions, nonprofit organizations, small and medium enterprises or CSR programs, and city residents. Finally during the modeling phase the solutions obtained are then tested through implementation and finally governance output is prototyped, evaluated, and adapted to the legal and institutional framework of the city so to ensure legal and institutional harmonization. In order to create, govern, and sustain cocities it is crucial to deploy institutional (policy innovation labs and collaborative working hubs, neighborhoods agencies) legal, economic, digital, and technological tools. Such tools will serve to make economic resources available to meet the needs of local communities, to attract funds from collaborative economy and support citizens and stakeholders in their joint efforts. Last but not least digital and technological tools serve as both instruments and strategies to transform urban commons into cocities as they can represent more effective means of social justice in terms of access to infrastructures and energy production, consumption, and distribution. After the first experiment in Bologna, the protocol has been applied in other Italian realities like Mantua, Reggio Emilia, Battipaglia, some cities of Tuscany, and Rome.

25.10

The cocity index

In order to measure the implementation of the EU and UN urban agenda, and to provide cities all over the world (with special attention to least developed countries) with best practices and fits of the collaborative city, Lab.gov.city has also

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developed a cocity index. While the report is the result of a 5-year-long research on groundbreaking experiments like the Bologna one, and others from Italy (Milan, Rome, Palermo, Bari among the others), and worldwide (Seoul, San Francisco, Barcelona, and Amsterdam), the index has been created through the survey of sixty-seven cities over 18 months providing 74 study cases in urban commons and public policies from different geopolitical contexts. In order to measure the impact of both community-led and institutionalized solutions cities have been studied according to common standards, and data were collected through direct interviews to the representatives of each case study. The study itself is not currently completed as data have not yet been compared. At this stage the cases can just be listed and they can provide the ground to identify relevant aspects and to build classification criteria. All cities have been collected into a dataset that is going to constitute, together with the interviews, the basis for further research. Last but not least, the results of this first phase of the research have been published on the platform https://commoning.city/ The platform was launched in August 2018 with the aim of serving as an international mapping platform for the urban commons and for cities interested into the transition toward the commons paradigm. The index thus represents the first standard to evaluate the state of the art of sustainable development goals and the new urban agenda, and the European urban agenda through a concrete measuring instrument able to classify cities on the basis of a gradient. The function of the index will also be to act as a powerful tool for global cities and administrations to measure the implementation of the measures undertaken in urban sustainability and governance. The Protocol, together with the index ultimately represents a crucial contribution to sustainable urban development and to local communities. The report on cocities also demonstrate that the commons paradigm enhance institutional capacity building and promote active inclusion of stakeholders thus fostering collaboration among civil society, universities, public authorities, enterprises to achieve cooperative management of urban resources.

25.11

Urban innovative action in the city of Turin

With a population of over 359 million people (over 72% of EU residents) living in cities, towns, and suburbs, the EU has been working consistently to provide its member states, regions, and cities, with resources to address emerging challenges concerning the environment, migration, demography, water, and soil pollution. Among the possible resources, article 8 of the ERDF (European regional development fund) provides authorities with legal ground to fund the urban innovative action (UIA)—an initiative whose goal is to support urban areas in their process to test new and unproven solutions. Actually the need of a grant to foster urban innovative solutions has been recognized as priority in consideration of urban authorities’ reluctance in allocating financial resources for what they feel as “risky” ideas. The projects selected for funding need to match the following criteria: innovation, participation, high quality, measurability, and transferability. The UIA contributes

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to the urban agenda; is aligned with the topics of the urban agenda; and, gives urban authorities the chance to deploy and test their potential and creative innovative bottom-up solutions. The tests funded by UIA are shared and disseminated, and made available for practitioners and policy makers around the EU thus constituting the basis for further discussion and analysis in the framework of the EU urban agenda. The city of Turin took advantage of the UIA to enhance the adoption of the cocity paradigm and to experiment an innovative approach to find a solution to the problem of urban poverty through the commons [49]. Following the example of the city of Bologna, the Turin city council approved the regulation for collaboration between citizens and administration for the care and regeneration of the urban commons at the beginning of 2016 [50] to respond to citizens solicitation to propose the adoption of the so-called “pacts of collaborations,” that is, a set of nonauthoritative administrative legal tools based on participatory approach. The main differences with the Bologna Regulation are: more types of interventions allowed with no limit on range or policy goals of the actions to be undertaken; empowerment of citizens in taking direct economic responsibility; creation of an internal infrastructure serving as coordination point within the city administration to harmonize and foster the work of the departments engaged in the process. The aforementioned infrastructure, is managed by a working group, which works closely with the council committee to provide guidance in drafting and enhancing collaboration pacts with citizens. Another innovative aspect of the working group, is that it is composed by civil servants from different sectors (depending on the projects), which are selected and appointed to accomplish specific tasks and project activities. The project enjoyed from the partnership of many stakeholders: not only the Turin City Council, CSOs, and citizens, but the Computer Science Department and Law School of the University of Turin, the National Association of Municipalities (ANCI), and the Cascina Roccafranca Foundation, already leader of the Neighborhood Houses Network, a policy and network implemented by the city of Turin since 2006 [51]. The cocity project was launched in March 2017 and its first step was to publish a public call [52] of proposals directed to citizens wishing to participate or getting their ideas and proposals funded. The call granted a participatory approach as citizens were acting as promoter of the pact of collaborations they would benefit from as target beneficiaries. To be taken into consideration the collaboration proposals should imply specific objectives connected to sustainable urban development (territorial monitoring and community development activities; urban cultural production; job opportunities; social innovation, and social enterprises, social inclusion, cultural diversity, dialogue, equal opportunities, sustainability, urban agriculture, circulate economy, spaces, services, and public initiatives availability), and relate to three types of actions: peripheries and urban cultures; underutilized infrastructure for public services; care of public spaces. The mentioned types were selected to promote the regeneration of abandoned buildings, appreciation, and further development of existing infrastructure, and comanagement of public spaces. The response to the call was pretty positive with most actions focusing on care of public spaces showing the effectiveness of the participatory approach in engaging a wide network of stakeholders. The project enhanced in Turin also represents a milestone in facing some of the main challenges of coproduction: leadership for implementation, public

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procurement, integrated cross-departmental working, adopting participatory approach, communicating with target beneficiaries. Some of the instruments that showed to be effective in going beyond these challenges are represented by the internal infrastructure created by the city of Turin acting as coordinator and catalyst for synergies and, most of all, the collaborative and teamwork atmosphere created by the initiative. Other important success factors are represented by applying a coordination principle in the selection of members of the Working group, and the aforementioned participatory approach. From the public procurement point of view the project, represent a concrete novelty as it created procedure based on collaborative dialogue, that is, a collaborative and not competitive environment founded on partnerships. Furthermore the project approach involves a sharing of risks among participants instead of a simple transfer of risks thus contributing to the creation of a more collaborative working environment. The institutional framework created by the city with its links to the European Commission, with the policy-making community and the urban partnership on innovative and responsible procurement, and a workshop with administrative courts for feedback and fixes in due time contributed to lower the risks connected to the action. The process initiated by the City of Turin represent a further evolution of the experiments carried out in other Italian cities as in this case the adoption of a regulation over the commons and coproduction activities represents a starting point of a “multi layered policy strategy for the urban commons as a leverage for the implementation of a horizontal collaboration model of governing the city” [53].

25.12

The city of Verona and subsidiarity pacts with active citizens

The experiences described are both part of a wider network comprising dozens of cities around the world. Nevertheless other cities outside of the Lab.gov.city network are following the pioneering example of the city of Bologna. The city of Verona that adopted its own regulation on the commons in 2017 [54] after a path started in 2015 when the city council voted to start a process to manage coproduction initiatives. The Verona regulation provides some relevant definition of terms commonly used when referring to the commons topic. More specifically it defines: [55] G

G

G

Active citizens: Any subject, single individual, association or social group, and entrepreneur, that is legally recognized and takes the initiative for the cure and appreciation of a city’s common goods Collaboration proposal: a manifestation of interest coming from active citizens aimed to propose appreciation interventions toward city common goods. The collaboration proposal can be spontaneous or answer a call from the city council Subsidiarity pact: the agreement signed between citizens and the city authorities that describe the topic and main characteristics of the collaboration to enhance the intervention on the city common goods. The proposal presented by active citizens is published on the city website to collect suggestions and recommendations before signing the agreement.

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Interventions can focus on both material and immaterial goods and proposals (when admissible), are presented to the public, and the department in charge according to the issues they deal with. The agreement signed make explicit reference to city laws so to give them not only a concrete legal framework but also continuity and stability within public administration. The process leading to the adoption of the regulation of Verona has been based on participation and a bottom-up approach where actions are proposed by the citizens, and evaluated by the city council according to internal guidelines and regulations. The project was structured in five steps: [56] listening, testing, draft, evaluation, definition of contents, and framework. The first phase (listening) was structured as a need-assessment analysis, collecting ideas, and suggestions from citizens through online semistructured and multiple choice surveys; the surveys provided ground to propose pilot project to test new collaboration forms and contribute to the definition of the subsidiary regulation. After the collection of all the answers a first regulation draft were published on the city of Verona website to get contribution from citizens. The evaluation phase gave the chance to measure the concrete effects and results of the pilot projects previously enhanced and to test the efficacy of the draft while the last phase is represented by the signature and entrance into force of the regulation, adopted by the City Council of Verona in 2017. The example of the city of Verona represents shows the effectiveness of involving citizens from the very first steps, and into the definition not only of the projects but also of the framework ruling the coproduction initiatives.

25.13

The commons and civic crowdfunding

Another powerful instrument for enhancing public private collaborations is represented by the possibility to match public funding with private ones through new technologies. It is the case of civic crowdfunding. Even if it is difficult to provide a definition of civic crowdfunding due to the definition of civic itself and the wide literature on the topic, we can take as a point of reference the definition provided by Charbit and Desmoulins in 2017 [43] describing the phenomenon as a “significant opportunity for citizens, civil society organizations, and subnational governments to leverage funds for public interest projects, more broadly for projects aiming to improve people’s wellbeing.” Civic crowdfunding thus represents an emerging field, and a key tool to achieve a wide range of public interest projects, from social and environmental innovation to urban commons [43]. To date crowdfunding for urban commons has produced a number of territory mutations and communities’ projects (distressed areas turned into public parks, local facilities, and community centers). Studies on civic crowdfunding [57] agree in attributing to it the following characteristics: G

G

G

G

Inspiration from community fundraising models, and resource pooling Small in scale Specific geographical funding area, tackling neighborhood issues Connection with nonprofit organizations (generally)

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According to Rodrigo Davies [58] local government can participate in four main ways: G

G

G

G

Curate citizen-initiated projects by choosing those to endorse and promote Start local government-run campaigns for specific new projects Use an existing platform for small-scale projects’ procurement Build an in-house crowdfunding platform on their own

Data collected by Davies also show that projects’ success rates of campaigns related to public goods are shown to be double, compared to private sector initiatives. The author also stresses the role of civic crowdfunding in: G

G

G

G

G

G

G

Promoting civic engagement and a sense of community Enhancing local development in time of fiscal constraints for subnational governments Acting as catalyst among people who have a common stake Granting more visibility to grassroots campaigns that would have not been put in the radar of local governments Providing small-scale pilot project that serve as test for larger ones Facilitating transparency Potentially matching diverse resources

The main civic crowdfunding platforms are currently located in the United States and in Europe. The platforms represent a concrete chance for citizens to take an active part in financing public activities and projects, and to induce municipalities and public authorities to create innovative collaborations and match opportunities.

25.14

Best Italian practices in matching public funds with private ones: the city of Milan and Turin

The state of the art of the application of civic crowdfunding initiatives in Europe has been investigated by research promoted in the framework of the “Crowd Fund Port Project”—a transnational EU-funded initiative aimed at “improving the skills and competencies of all relevant stakeholder groups; and, to prepare them to take advantage of the phenomenon” [59]. The research was based on structured interviews to representatives of the countries taking part into the project to analyze their knowledge and provide a need-assessment analysis as well as present best practices and success cases. The institutions chosen for the structured interviews in Italy were the Politecnico of Milan, the City of Milan, and the City of Turin. All of them have concrete experience in Civic Crowdfunding and are involved in some Civic Crowdfunding initiatives: the Politecnico of Milan engaged in a Crowdfunding campaign to finance the refurbishment of some facilities in the campus, alongside its own resources; the City of Milan is a real pioneer in the field and is engaged in creating social projects through cofinancing aimed at economic growth and granting an immediate social result to improve living conditions in specific areas of the city; the City of Turin started a research and training project, namely “European Crowdfunding Center,” to enhance the knowledge about Crowdfunding and help the development of successful campaigns.

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In particular, the city of Milan launched a matching fund project in 2015 within the framework of its smart-city specialization strategy. The idea at the basis of the project was very simple: to start innovative projects through the help of small contributions collected via an experimental crowdfunding platform. The platform was aimed at enhancing social innovation and shared networks projects ranging from disability to the elderly to families in order to make the city more accessible for all. The objectives of the first test of civic crowdfunding in the city of Milan had two main objectives: to promote and develop a new conception of both the city and participation based on the idea of “smart city,” where technology concretely improve life conditions, and to stimulate the creation of social enterprises thanks to alternative finance tools. In their vision, civic crowdfunding was an instrument to create and develop new enterprises, and to double administrative and EU funds. The city decided to invest 400,000 Euro for crowdfunding projects, and to collect funds through the platform Eppela, used to present the selected projects one by one. Projects were required to raise at least 50% of their target to receive public funds. The area of the projects concerned different fields, and most of them were focused on territorial solidarity. In their opinion, crowdfunding can serve public goals and institutions as it can play different roles for public institutions: increasing the awareness of local communities, allowing them to select the best projects and be involved in the project governance; leveraging on public resources to raise also capital from businesses, citizens and member of the network; tapping the crowd for ideas and contributions to increase the quality of the project. Furthermore, it gives the chance to launch shared projects and to develop grassroots initiatives coming from citizens. The nonrepayable nature of the investment also grants high level of entrepreneurship. As mentioned before, the city of Milan is not the only Italian city engaged in civic crowdfunding. Another relevant example is represented by the city of Turin, which is strongly committed in providing civil society with training and capacity building in this field. Within the framework of provision 3.3.1 B of the PON Metro Torino, the city promoted the first Italian Crowdfunding district, namely the “European Crowdfunding Center.” In particular, the City of Turin launched a tender to support third sector organizations in promoting Crowdfunding campaigns to raise money for social innovation projects. The tender is divided into two main parts: the first is represented by the application of the projects that wishes to participate to the smart-city specialization strategy academy training and capacity building courses; the second part of the call is the application to get support in the enhancement of a crowdfunding support by experts in the field. The organizations are eligible is they belong to the third sector and if they promote innovative social projects in the fields of new poverties, social vulnerability, unemployment, cultural integration, and social cohesion, citizens well-being. The projects selected have to target specific groups either officially residing or consistently frequenting target areas of the city of Turin in order to add value to the material and immaterial heritage of the city itself and to foster regeneration, restoring, revitalization socioeconomic, and environmental projects.

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The role of institutions in promoting civic crowdfunding

The interviews conducted in the framework of the research on civic crowdfunding provide stimulus on the role of public authorities in promoting and enhancing innovative instruments and tools in the field. More specifically, according to the Italian institutions, the EU can help in creating capacity building and reciprocal understanding through the dissemination of knowledge and best practices, training on how to perform a civic crowdfunding campaigns and cofinancing. In addition, EU funds would represent a further stimulus, so it would be recommended to promote specific tenders for crowdfunding projects. The same role is recognized for local authorities that might also guarantee the projects at both public and crowd level, and give a crucial contribution in creating the crowd, granting transparency, and budget control. All institutions agree on the fact that crowdfunding should not be used to cover costs, which are not covered by public funds, but as a complementary tool. The opinions on the role of crowdfunding as a participatory tool for deciding public budgets allocations are different: while the city of Turin sees it as a threat, the city of Milan think it might represents an opportunity to both increase shared projects and invest public funds. In addition, crowdfunding gives an immediate feedback on how funds are invested and it can also give key contribution; it gives citizens a double power to both chose and control what to implement. The answer is totally positive on the importance of receiving public support as a chance to receive more funds from the crowd.

25.16

Summary

The examples provided clearly show how cities around the world have started developing innovative solutions to face critical issues related to urban commons, common goods management, and citizens participation. Finding new cooperative paths and enhancing innovative solution has nowadays become one of the main issues at global level. The model developed by the city of Bologna and exported in Italy and around the world as well as the research by the Georgetown and Rome laboratories will constitute the basis for further developments in this sense. Meanwhile, it is necessary to disseminate the data collected and to share knowledge at public level so to identify best practices and best fits. It is also crucial for public institutions to provide active citizens with punctual and efficient tools and frameworks. Within the framework of the European Union coproduction and the commons have consistently shown their potential not only when exploiting local resources but also (and mainly) when matched with structural funds. Civic crowdfunding and the use of new technologies may also represent key factors as resource multipliers. Even if at an early stage the results in terms of efficiency and increase in participation are impressive. More data and the possibility to monitor and evaluate the state

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of the art and further development will constitute powerful tools in reducing the risks and improve the models. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

25.17

Chapter review questions/exercises

25.17.1 True/false 1. True or false? The commons and its related concepts have been on the spot of international studies for decades, but they have come to global attention recently, thus, posing challenging questions on both the role of citizens, the fourth sector in the provision of public services, and the structure of public administrations. 2. True or false? The analysis conducted by the OECD in 2020, in more than 40 countries, also identifies success paths to design effective coproduction schemes, based on factors like attitude and culture; systems and processes; collaboration and partnerships; management and leadership; learning and communication; and resources. 3. True or false? Due to the recent socioeconomic crisis, the interest European public authorities have shown, has been increasing; thus, leading the European Commission to state that: “social innovation represents an important option to be enhanced at different levels, and sector as its purpose, is to innovate in a different way (through the active engagement of society itself) in order to generate a primarily social value.” 4. True or false? CLLD represents a concrete opportunity to support a single action under different EU Funds; thus, enabling local action groups to cowork and cooperate without overlapping. 5. True or false? Neighborhood streets, parks, gardens, open spaces, BIDs, and CIDs, constitute concrete evidence of how civil society is looking behind the state to sublocal forms of organization; thus, claiming urban resources as “commons.”

25.17.2 Multiple choice 1. In order to measure the implementation of the EU and UN urban agenda, and to provide cities all over the world (with special attention to least developed countries) with best practices and fits of the collaborative city, Lab.gov.city has also developed a: a. Cocity index b. Cocountry index c. Sufficient index d. ICT-enabled index e. Preferred index 2. The _____ contributes to the urban agenda is aligned with the topics of the urban agenda, and gives urban authorities the chance to deploy and test their potential and creative innovative bottom-up solutions. a. ERDF b. EU c. WG d. UIA e. All of the above

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3. Any subject, single individual, association or social group, and entrepreneur, that is legally recognized and takes the initiative for the cure and appreciation of a city’s common goods, is known as: a. Collaboration proposal b. Active citizens c. Subsidiarity pact d. Autonomous systems e. Transport sharing 4. Another powerful instrument for enhancing public private collaborations is represented by the possibility of matching public funding with private ones (through new technologies), such as: a. Civic crowdfunding b. Commons c. CSOs d. Subnational governments e. All of the above 5. The state of the art of the application of civic crowdfunding initiatives in Europe has been investigated by research promoted in the framework of the “__________”—a transnational EU-funded initiative aimed at “improving the skills and competencies of all relevant stakeholder groups, and to prepare them to take advantage of the phenomenon.” a. Civic crowdfunding project b. Crowd fund port project c. European crowdfunding center project d. Smart-city specialization strategy project e. Social specialization strategy project

25.17.3 Exercise 25.17.3.1 Problem Is the urban commons framework more than a legal tool to make proprietary claims on particular urban goods and resources?

25.17.4 Hands-on projects 25.17.4.1 Project Do research: What are the alternatives beyond privatization of urban common resources or monopolistic public regulatory control over them?

25.17.5 Case projects 25.17.5.1 Problem Can designing a smart city as a commons help address issues such as urban poverty, gentrification, climate change, and migration, among others?

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25.17.6 Optional team case project 25.17.6.1 Problem Can smart-city design principles be applied to cities to rethink the governance of smart cities and the management of their resources?

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[16] A. Calabro, Co-production: an alternative to the partial privatization processes in Italy and Norway, in: V. Pestoff, T. Brandsen, B. Verschuere (Eds.), New Public Governance. The Third Sector and Co-production, Routledge, New York, 2012. [17] T. Brandsen, J. Helderman, The conditions for successful co-production in housing: a case study of German housing cooperatives, in: V. Pestoff, T. Brandsen, B. Verschuere (Eds.), New Public Governance. The Third Sector and Co-production, Routledge, New York, 2012. [18] M.S. Rosentraub, E.B. Sharp, Consumers and producers of social services: coproduction and the level of social services, South. Rev. Public. Adm. 4 (1981) 502 539. March. [19] OECD, Together for better public services: partnering with citizens and civil society, OECD Public Governance Review, OECD Publishing. Available from: ,https://doi. org/10.1787/9789264118843-en., Aug. 31, 2011. [20] R. Norman, A local government approach to world order, Peace Change 10 (1) (1984). quoted in E. Lo¨ffler, P. Watts (2009), Understanding the efficiency implications of coproduction, unpublished paper, November; D. Boyle, S. Clark, S. Burns (2006), Hiddenwork. Co-production outside paid employment, Joseph Rowntree Foundation, 2009. [21] J. Alford, Engaging Public Sector Clients From Service Delivery to Co-production, Palgrave Macmillan, 2009. [22] E. Loeffler, S. Parrado, T. Bovaird, G. Van Ryzin. If you want to go fast, walk alone: if you want to go far, walk together: citizens and the co-production of public services. Paris: French Ministry of the Treasury, Public Accounts and Civil Service, on behalf of the Presidency of the EU, 2008. [23] T. Bovaird, “Breaking new ground in public service improvement: the role of codesign, co-commissioning, co-managing and co-delivery, presentation to Governance International seminar (June 2009). [24] E. Lo¨ffler, P. Watts Understanding the efficiency implications of co-production, unpublished paper (November 2009). [25] European Union, Leda Scott, Co-production: enhancing the role of citizens in governance and service delivery, ESF Transnational Platform, Technical Dossier no. 4 (May 2018). [26] European Commission, Empowering People, Driving Change: Social Innovation in the European Union, Publications of the European Union, Luxembourg, 2011. [27] S. Osborne, K. Strokosch, It takes two to tango? Understanding the co-production of public services by integrating the services management and public administration perspectives, Br. J. Manag. 24 (2013). [28] W.H. Voorberg, V.J.J.M. Bekkers, L.G. Tummers, A systematic review of co-creation and co-production: embarking on the social innovation journey, Public. Manag. Rev. 17 (2014). [29] Prahalad, C. & Ramaswamy, V. Co-opting customer competence, Harv. Bus. Rev., 78, 2000; Prahalad, C. & Ramaswamy; V. Co-creating unique value with customers, Strat. Leader., 32, 2004. [30] D. Szebeko, L. Tan, Co-designing for society, Australas. Med. J. 3 (2010). [31] J. Bloomfield, Available from: http://www.forumdascidades.pt/sites/default/files/Projetos/ together_final_report_rev.pdf TOGETHER final report, EU, Urbact, 2012. [32] D. Hargreaves, A new shape for schooling?, SSAT, the Schools, Students and Teachers network. ,www.ssatuk.co.uk., 2006.

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[33] J. Bourgon, A New Synthesis of Public Administration: Serving in the 21st Century, Queen’s Policy Studies: McGill-Queen’s University Press, June 12, 2011. See also. Available from: http://www.pgionline.com/. [34] Bologna Regulation on Public Collaboration for Urban Commons, LABGOV. ,http://www. labgov.it/2014/12/18/bologna-regulation-on-public-collaboration-for-urban-commons/., 2014 (accessed 18.12.14). [35] S.R. Foster, C. Iaione, The city as commons, Yale Law Policy Rev. (YLPR) 34 (2) (2016). [36] M. Buemi, Who invites who? The cities as a new actor in collaboration, Case Study for the CHANGE! network. ,https://urbact.eu/sites/default/files/media/case_study_aarhus_ad_ hoc_expert_1.pdf., 2017. [37] Christian Iaione & Paola Cannavo`, The collaborative and polycentric governance of the urban and local commons, 5 URB. PAMPHLETEER 29 (2015). Bologna Regulation on Public Collaboration for Urban Commons, LABGOV, Dec. 18, 2014, , http://www.labgov.it/2014/12/18/bologna-regulation-on-public-collaboration-for-urban-commons/ . . [38] H. Etzkowitz, L. Leydesdorff, The triple helix-university, industry, government relations: a laboratory for knowledge based economic development, EASST Rev. 14 (1) (1995). [39] E. Ostrom, Governing the Commons, Cambridge University Press, 1990. [40] C. Rose, The comedy of the commons: custom, commerce, and inherently public property, 53 U. Chi. L. Rev. 711, 1986; Carol M. Rose, The several futures of property: of cyberspace and folk tales, Emission Trades and Ecosystems, 83 Minn. L. Rev. 129, 155, 1988. [41] ,https://ec.europa.eu/regional_policy/sources/policy/themes/urban-development/agenda/ pact-of-amsterdam.pdf., May 30, 2016. [42] G. Arena, C. Iaione, L’Italia dei Beni Comuni, Carocci Editore, 2012. [43] D. Charbit, Civic crowdfunding: a collective option for local public goods?, in: OECD Regional Development Working Papers, 2017/02, OECD Publishing, Paris, 2017. [44] E. Ostrom, Crossing the great divide: coproduction, synergy, and development, World Dev. 24/6 (1996). [45] Veronica Olivotto, The beginning of the first co-city: Co-Bologna, in critical turning points-database, TRANSIT 4 (2016). Available from: http://www.transitsocialinnovation.eu/sii/ctp/ctp4-the-beginning-of-the-first-co-city-co-bologna. July 25, 2016. [46] According to the “Co-City Open Book” the main findings come from a combination of research on methodological approaches on the commons and may be generally identified in the studies conducted by A. Poteete, M. Jannsen, E. Ostrom, Working together: collective action, the commons, and multiple methods in practice, 2010; A. Poteete, E. Ostrom, In pursuit of comparable concepts and data about collective action, Agric. Syst. 82 (2004), 215 232. Chicago School of Urban Sociology to Contemporary Urban Research, T. May, B. Perry, L. G. Patrick, S. S. Saskia, M. Savage, The future of urban sociology. Sociology, 39 (2005), 343; C. Wu, Moving from urban sociology to the sociology of the city, Am. Sociol., 47, 1 (2016) 102 114. [47] The report benefited from the collaboration of Sheila Foster, Christian Iaione, and Elena De Nictolis with the P2P Foundation; the Transformative Actions Interdisciplinary Laboratory (TrailLab) of the Catholic University of Milan, in particular Professor Ivana Pais and Michela Bolis; the International Association for the Study of the Commons (IASC). Michel Bauwens and Vasilis Niaros for data selection and collection during the exploratory phase. An analysis on the findings from the first 30 relevant case studies provided by Michel Bauwens will be made available

The city as a commons: the concept of common goods

[48]

[49] [50] [51] [52] [53] [54] [55] [56] [57]

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on the Co-Cities Open Book, forthcoming on ,www.commoning.city.. Constant supervision and guidance for the theoretical framework and the methodological approach by Sheila Foster and Leonardo Morlino. For case studies in Latin America: Thamy Pogrebinschi and the team on LATINNO, Innovations for democracy in Latin America. For case studies on sharing cities worldwide: “Shareable Sharing Cities: Activating the Urban Commons” and Neal Gorenflo. The theoretical background and literature of the project, and the conceptual pillars of the Co-city are based on the analytical framework developed in the following publications: S. Foster, The city as an ecological space: social capital and urban land use, 82 Notre Dame L. Rev. 527 (2006 2007); S. Foster, Collective action and the urban commons, 58 Notre Dame L. Rev. 57; C. Iaione, Governing the urban commons, 1 IT. J. Pub. L. 170 (2015); C. Iaione, The co-city, 75 Am. J. Econ. Sociol., 2 (2016); S. Foster, C. Iaione, The city as a commons, 34 Yale L. Poly Rev. 81 (2016); C. Iaione, The law and policy of pooling in the city, Fordham Urban L. J. 34:2 (2016); and S. Foster, C. Iaione, Ostrom in the city: design principles for the urban commons, Nat. Cities, 2017. ,https://www.thenatureofcities.com/2017/08/20/ostrom-city-designprinciples-urban-commons/., 2017 (accessed 20.08.17). First emerged in game theory see J. Farrell, M. Rabin, Cheap talk, 10 J. Econ. Perspect., 3, 1996, 103 118, and adopted in the research on common pool resources see A. Poteete, M. Janssen, E. Ostrom, Working Together: Collective Action, the Commons, and Multiple Methods in Practice, 2010, vol. 29. Cristian Iaione, UIA Expert, The co-city project. Journal N 1, Project led by the city of Turin. ,https://www.uia-initiative.eu/sites/default/files/2018-03/Turin_CO-City_UIA ExpertJournal1%28Jan2018%29.pdf., January 28, 2018. Regulation of the city of Turin no 375/2016 on the urban commons was approved through the deliberation of the City Council on January 11, 2016 (mecc. 2015 01778/ 070) and entered into force on January 25, 2016. G. Ferrero, Welfare urbano e case del quartiere, Urbanistica Informazioni, 242, 2012. ,http://www.comune.torino.it/benicomuni/bmBdoc/determina-approv-avvisi-atti.pdf., 2019. Cristian Iaione, UIA Expert, The co-city project. Journal N 1, Project led by the city of Turin, ,https://www.uia-initiative.eu/sites/default/files/2018-03/Turin_CO-City_UIA ExpertJournal1%28Jan2018%29.pdf., 2018. For the complete text of the regulation in Italia visit: ,https://portale.comune.verona.it/ media//_ComVR/Cdr/SegreteriaConsiglio/Allegati/sussidiarieta/DCC_10_2017.pdf., March 8, 2017. ,https://intranet.comune.verona.it/nqcontent.cfm?a_id 5 55920., 2019. ,https://portale.comune.verona.it/nqcontent.cfm?a_id 5 52312., July 30, 2019. Baeck P., Bone J., Mitchell S. “Matching the Crowd: combining crowd funding and institutional funding to get ideas off the ground”, Nesta October 2017 , https://media. nesta.org.uk/documents/matching_the_crowd_main_report_0.pdf . ; Bone J., Baeck P. “Crowdfunding good causes: opportunities and challenges for charities, community groups and social entrepreneurs”, Nesta, June 2016 , https://media.nesta.org.uk/documents/ crowdfunding_good_causes-2016.pdf . ; Ezrah Bakker and Frank Jan de Graaf, “Civic crowdfunding: not just a game for the self-reliant”, November 2017 , https://www.civictools.nl/en/artikel/civic-crowdfunding-is-niet-alleen-een-speeltje-van-zelfredzame-burgers/ . ; Davies R. “Civic Crowdfunding: Participatory Communities, Entrepreneurs and the Political

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Economy of Place”, B.A. Oxford University (2003) Submitted to the Department of comparative Media Studies in partial fulfilment of the requirements for the degree of Master in Science in Comparative Media Studies at the Massachussetts Institute of Technology, June 2014; C. Charbit, G. Desmoulins, Civic crowdfunding: a collective option for local public goods?, in: OECD Regional Development Working Papers, 2017/02, OECD Publishing, Paris, 2017. [58] R. Davies, Civic crowdfunding: participatory communities, entrepreneurs, and the political economy of Place, MIT (May 9, 2014). [59] ,https://www.interreg-central.eu/Content.Node/CROWD-FUND-PORT.html.; ,https:// www.crowdfundport.eu/., January 27, 2020.

Resilient future energy systems: smart grids, vehicle-to-grid, and microgrids

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Alexander Domyshev1, Ulf Hager ¨ 2, Daniil Panasetsky1, Denis Sidorov1,3 and Pantelis Sopasakis4 1 Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences (ESI SB RAS), Irkutsk, Russia, 2Institute of Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund, Germany, 3Irkutsk National Research Technical University, Irkutsk, Russia, 4Queen’s University Belfast, School of Electronics, Electrical Engineering and Computer Science and i-AMS Centre, Belfast, United Kingdom

26.1

Introduction

According to [1], the share of renewable energy sources, such as wind and solar power sources, reached 17% in 2016 with Sweden at the top with 54%, while the target is that the average penetration exceeds 27% by 2030. The need for action against the ongoing climate change can be expected to accelerate the replacement of conventional thermal generators by wind, solar, wave and other renewable sources of energy.

26.1.1 The changing face of energy networks The use of renewable sources effects a shift from a centralized production scheme to a spatially distributed network that may involve several production and storage sites. Such large networks often tend to be organized into smaller entities known as microgrids [2]. In certain cases, microgrids need to operate autonomously, in “islanded” mode, in which case they become responsible for both frequency regulation as well as demand management via appropriate online production planning and storage to avoid shortages [3
5]. Power networks become complex cyber-physical systems of systems that operate at a wide spectrum of spatial and temporal scales and call for a hierarchy of control and monitoring systems [6
9]. Typically, one can identify three main control layers. The lower/faster control layer of primary control runs at a sampling rate up to a few seconds and is responsible for regulating the voltage and frequency [10]. The secondary control layer runs at a rate of several seconds and is responsible for regulating frequency fluctuations by providing appropriate set points to the primary control layer [4]. The tertiary control layer, often referred to as the energy management layer, orchestrates the generation and storage Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00026-7 © 2021 Elsevier Inc. All rights reserved.

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of energy by dispatching power set points to the various producers in the network aiming at meeting the demand of consumers [2,11]. As conventional thermal generation gives its place to renewable energy sources, power networks become all the more exposed to uncertainty as energy production depends heavily on weather conditions (e.g., solar irradiation and wind speed) and renders energy generation highly volatile and intermittent [12
15]. Renewable power time series are, more often than not, difficult to model and can exert a strong impact on the network’s operation [16]. Energy demand is also uncertain and despite the significant research attention that this topic has attracted, it remains a challenge to produce accurate short-term demand predictions. Lastly, in deregulated energy markets, energy prices can have their fair share of contribution to the uncertain operation of the network. As a result, power networks are, and are expected to be, ever so exposed to high uncertainty, both at production and demand sides, whose impact should not be underestimated. The operation of such networks calls for operational control paradigms that can make the best out of the available resources, lead to an uninterrupted power supply, minimize the environmental footprint of energy production, respect the battery operating limits, and overall operate the network at a low economic cost.

26.1.1.1 Control-oriented stochastic modeling The computation of forecasts of the upcoming wind speeds, solar irradiation, and demand is essential for the network to respond proactively to expected changes in those values. In fact, forecasting is an indispensable component of most operation control approaches. An overview of common methodologies for load forecasting is given in [17] and methodologies for wind forecasting are discussed in [12]. Predictions of future energy and load rely on previously obtained values of these time series, as well as external time series (such as weather data) [18]. When it comes to modeling a time series for control purposes, we may identify four main classes of models, which lead to four control formulations: (1) deterministic models, (2) bounded uncertainty, (3) stochastic processes, and (4) distributionally robust or risk-averse approaches. Each of these broad categories makes use of different assumptions regarding the uncertainty that is associated with the model predictions. The certainty equivalent, or deterministic, models produce single forecast values without information about the reliability of that forecast, or other statistical information. Such models have been used in a number of publications [19
22]. Such models can be used to provide an indication of future values of unknown (demand/ load) time series; however, when used for the design of controllers can lead to poor performance and violations of the prescribed constraints [13,23,24] the reason being that wrong predictions will advise suboptimal or even unsafe decisions regarding the allocation of resources, the use of storage and dispatch of energy. Deterministic models, when used in controller design, can clearly jeopardize the stability, safety, and performance of the controlled system. In order to protect systems from inaccurate predictions, one may use the worst-case robust approach

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(see Fig. 26.1B) where predictions are sequences of (compact) sets. This approach was followed in [24
26] where uncertain future load/wind/irradiation forecasts, as well as unknown system parameters, are treated as unknown-but-bounded quantities. The main limitation of this approach is that it disregards the statistical information that is typically available (via observations) and can lead to an overly conservative designs that will seek to accommodate the worst-case load and weather conditions simultaneously—a possible, but not very likely outcome—therefore, when such models are used for the design of controllers they lead to a safe operation, yet poor performance with limited participation of renewable sources, increased use of thermal generators and an excessive number of switching of thermal generators [23]. Stochastic models offer probabilistic information about the predicted variables by modeling future loads, wind speeds, and solar irradiation values as stochastic processes—sequences of typically dependent random variables. Roughly speaking, stochastic models provide a sequence of future probability distributions alongside time-covariance information about these future predictions (see Fig. 26.1C). There exist two approaches in regard to modeling such stochastic processes. The first class of approaches models uncertain quantities by means of normal distributions [27
30] and the additional assumption of independence. For instance, future wind power can be modeled as wt1j 5 w^ t1jjt 1 εj , where wt1j is the future, unknown, wind energy value, w^ t1jjt is a prediction of that value using a time-series model and εj is the j-step ahead prediction error, which is assumed to be normally distributed, independent of all εj0 for j0 6¼ j. This approach allows to formulate chanceconstrained formulations as in [31,32]. In fact, hard constraints cannot be imposed since normal distributions are unbounded. However, in reality probability distributions are all but normal. For example, even under the assumption that wind speed prediction errors are normally distributed, the generated wind power follows a saturated cubic normal distribution. The normality assumption can be dropped by means of polynomial chaos expansions as in [33]. There exists a second approach that does not require the independence assumption and account for the covariance between variables εj, but requires the assumption that at every time j, the random variable εj is finitely supported. This assumption, alongside the filtered structure of εj (the random process εj lives in a

Figure 26.1 Different types of predictive models: (1) deterministic: predictions are values, (2) worst case: predictions are set-valued, (3) stochastic: predictions define a stochastic process such as a Gaussian process or a Markov chain, and (4) distributionally robust modeling: predictions are collections of stochastic processes.

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filtered probability space), gives rise to the structure of a scenario tree [23,34]. Scenario trees are becoming popular in microgrids and power networks [20,23
25,35
37] and can be constructed directly from data [38,39]; therefore, they have the potential to provide a more realistic approximation of the actual (but unknown) probability distribution. Stochastic modeling approaches, such as the aforementioned ones based on normal distributions and scenario trees, are approximations of the actual unknown probability distribution. However, such probability distributions are likely to be inaccurate, especially in lack of a large number of data points. Additionally, the underlying distribution may be time varying. For example, it is known that in the simple case of an independent finitely supported random process with timeinvariant  pffiffiffiprobabilities, the empirical distribution converges to the true one at a rate of 1= k , therefore a large number of data is required to achieve a highly accurate estimate of the distribution [40]. Sopasakis et al. [41] showed that misestimating the probability distribution can have a destabilizing effect on the controlled system, it is therefore important that the controller designer takes into consideration this “uncertainty in uncertainty,” that is, the inexactness in the knowledge of probability distributions. A good account of stochastic model predictive control (MPC) methodologies is available in the review paper [31], while the review paper [42] offers a more recent take on robust MPC (including worst-case, stochastic, and risk-averse approaches).

26.1.2 Model predictive operation control It is evident that the operation of power grids is subject to a number of conflicting objectives. This gives rise to the formulation of optimization-based control methodologies such as the popular MPC approach [43]. MPC is an optimization-based discrete-time control approach, where at every time instant the control action is determined by solving an open-loop optimal control problem. At every time instant, the controller determines an optimal sequence of control actions along a finite horizon that optimizes a performance index that encodes the operating objectives. The optimization is carried out subject to the state and actuation constraints of the system—for example, these can be power generation, energy storage, transmission, or switching rate constraints. The optimization problem is also solved taking into account the system dynamics, therefore, for example, the dynamics of storage units. There exist two widely known approaches to deal with multistage decision making under uncertainty. In the stochastic approach we minimize the expectation of the uncertain cost with respect to a reference probability measure, whereas, in the worst-case approach we minimize the maximum (worst-case) cost. The first approach is naive in assuming a perfect knowledge of the underlying distribution, while the second one is pessimistic and disregards any probabilistic information, which is typically available. The risk-averse approach seeks to remedy the shortcomings of the two conventional approaches by using risk measures. These allow to interpolate between these two optimal control paradigms. The resulting optimal control problems are termed “risk averse” because they lead to decisions which are less sensitive to high-effect low-probability events. Additional constraints on the

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risk of a random function may also be imposed, often as surrogates of intractable probabilistic constraints. Overall, in multistage risk-averse formulations, the cost function is the composition of several (typically nonsmooth) mappings, yielding numerically challenging optimization problems. The aforementioned MPC formulations are accompanied by certain stability notions. Deterministic and worstcase stability notions are discussed in the classic textbook [43]. In Stochastic MPC, mean square stability is the most common stability definition and several Lyapunov-type results are available; a comprehensive overview of the recent theoretical developments in this field is provided in the review paper [31]. Risk-averse stability for Markovian switching systems is studied in [41]. In power networks, as well as in a variety of other systems, stability is not the main concern. Instead, one is mostly interested in a safe and economic operation of the system. Recently, the research community has turned their attention to economic model predictive control (EMPC) [44
48]. EMPC is concerned with the economic operation of dynamical systems, the satisfaction of state and input constraints, and the attainment of a low (bounded) asymptotic average operating cost. A great attention has been given to the derivation of conditions under which economic formulations lead to stable closed loops. To that end, dissipativity seems to be a property of central importance. We may say that dissipativity is an open-loop counterpart of Lyapunov-type decrease conditions. Economic MPC formulations can be extended to stochastic systems and stability can be studied using a stochastic variant of the dissipativity notion [49].

26.1.3 Flexible future smart-grid systems In classical power systems, load and generation was balanced by controllable power plants mostly located on the transmission system level. In modern power systems with fewer controllable power plants, energy management on distribution system level can be used to provide flexibility. Future smart distribution systems will consist of various assets that are not directly owned or controlled by the grid operator but are still able to adapt their generation or consumption behavior in a controllable manner. The potential range from certain distributed assets can be aggregated to a joint flexibility potential. The aggregation can be done for local grid nodes or also in general for the whole power system depending on the use case for the flexibility. There exist various use cases for active power flexibility: G

G

G

G

G

G

G

Trade on energy markets Trade on control reserve markets Congestion management on TSO level Congestion management on DSO level Prevention of thermal overloads Prevention of voltage band violations Local balancing of active power feed-in and consumption (e.g., island operation, etc.)

The following sections give insight to different types of energy management. Aspects of different use cases for flexibility, such as island operation, will be discussed in the following chapter.

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26.2

Solving Urban Infrastructure Problems Using Smart City Technologies

Optimization of urban electric grids with EV charging load and V2G generation

For more than a decade, the concept of so-called smart grids has been developing in many countries [50]. This concept includes consideration of issues such as: G

G

G

G

G

The use of power elements, incorporating computer (digital) control devices, can be used for the production, storage, transmission, distribution, and consumption of electricity. Application of modern information and communication technologies in the grid control. New methods of controlling, using complex computational algorithms and machine learning. The use of active grid elements that provide smart consumer behavior to manage their energy consumption. Use of renewable, small, and distributed generation.

This concept is especially relevant in large cities when electric vehicles (EVs) are added to the above properties of electric grids. In the future, the growth in the share of electric cars will only increase, for example, during the climate conference in Paris in 2015, where the joint initiative “Paris Declaration on Electromobility and Climate Change and a Call to Action” was adopted. To achieve the goals set by this declaration, EVs should represent 35% of global car sales by 2030 [51]. To generally assess the potential impact of EVs on the behavior of an electric grid, the share of EVs in the total load of electric grids was estimated based on the following open statistics: (1) data on the number of road transport per capita [52], (2) statistics and population forecasts by country [53], statistics and forecast of electricity consumption by country [54]. The growth in electric car sales was also extrapolated [55], taking into account the current trend and the declared share of 35% of total car sales. As a result, using the example of electricity consumption in countries such as Russia, the United States, France, and Germany (Fig. 26.2), the share of the forecast for electric car consumption is significant and reaches 25% (Fig. 26.3). The data given do not take into account the possible saturation of the car market, but for a qualitative assessment, this approach is acceptable. EVs add an indeterminate component to the behavior of an electric power system, which negatively affects its modeling and control. When electric cars are connected to the electric grid inconsistently and at the full power required to charge them, such uncoordinated behavior leads to local problems with the power system, such as additional losses of electricity, voltage deviations, and thus to a deterioration in the quality of electricity and a potential decrease in stability of whole power system.

26.2.1 Statement of the optimization problem The urban electric grid is considered; which is characterized by a large stochastic load, the presence of alternative generation, and the presence of EVs. The optimization goals for the grid company may include: (1) minimization of power losses,

Resilient future energy systems: smart grids, vehicle-to-grid, and microgrids

Figure 26.2 Power consumption forecast.

Figure 26.3 Growth in the share of EVs in the load of electric grids as a percentage.

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(2) providing the required voltage levels, and (3) optimization of the cost of electricity generation. For EV users, it is important to optimize the EV charging processes according to certain economic criteria taking into account EV charging during minimum tariffs and possibly using their own generation resources (so-called prosumer behavior). Such a comprehensive statement of the problem entails a partial contradiction in the interests of the participants of the process (grid companies and EV owners). EV owners would like to be able to charge their electric car at any convenient time and in any convenient place at the lowest prices. For a grid company, it is important to minimize their costs of electricity transmission. At the same time, the reliability of power supply is important to all participants in the process. Working with a single model representing the city electric grid and each EV is not possible because of its complexity. Therefore, the two-level dynamic optimization seems to be the best option for solving the complex task of optimizing a city grid with EV. The upper level is a stochastic model of the urban electric grid. The lower level—these are group of EV charge controllers that optimizes the charge process at the level of local microgrids or charging aggregators. The two-level optimization algorithm is presented in Fig. 26.4. The implementation of this algorithm in cyclic mode allows us to effectively perform optimization of the urban electric network with the presence of EVs without complicating the optimization algorithm itself.

26.2.2 Lower level of optimization The objective function at the lower level of optimization takes into account the economic efficiency of the charge and EV power output (in the case of connecting EV using vehicle-to-grid (V2G) technology). The minimized objective function can be determined as follows:   f (pg ðtÞÞ 5 ce ðpev ðtÞÞ 1 ci ðpev ðtÞÞ 1 cpev ðtÞ 2 pd ðtÞ

(26.1)

The first two terms of this equation determines the cost of the electricity received from the external grid (ce ) and the cost of the electric energy generated inside the microgrid (ci ). Also in the optimization function, there is a term determining the deviation of the EV power from the required one. Observation of the power changing pev ðtÞ represents both the load power and the generation power.

Figure 26.4 Two-level optimization algorithm.

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The required power schedule EV (pd ðtÞ) is calculated as a result of the optimization of the entire city electric grid and transmitted from the upper-level control system. Lower level optimization should take into account the stochastic nature of EV charging load behavior. Methods for solving this problem are usually dynamic programming options, such as approximate dynamic programming, taking into account the stochastic nature of the source data [56,57]. Adaptive dynamic programming methods are also used, which use the reinforcement learning approach as an adaptation of the system’s transition from state to state strategy [58]. To reduce the dimension of the problem being solved, methods such as the support vector method are used. In addition to the classical solution to the optimization problem using dynamic programming, heuristic methods of machine learning can also be applied, such as deep Q-networks, genetic algorithms, particle swarm method, etc.

26.2.3 High-level model description Optimization at the level of the electric grid is a multipurpose optimization, which can be solved by various methods, such as a Pareto optimum [59], minimizing the distance to the utopia point [60], and methods of unifying into a single objective function. Among the unifying methods that are distinguished, includes the following: the weighted sum method [61,62], the lexicographic method [63], the Pareto optimum [64], the exponential weighted criterion [65], the weighted product method [66], target programming [67], and physical programming [68]. The simplest and most effective way is the method of unifying different objective functions with the help of weighted sum when individual objective functions are summed into one using the appropriate weights. fc ðxÞ 5

n X

wi fi ðxÞ; gðxÞ # 0

(26.2)

i51

Here fi ðxÞ is the objective function according to one of the considered criteria; wi is the weight coefficient corresponding to the subproblem of the objective function; x is the vector of control parameters; and gðxÞ are constraints containing both the boundary values of the control parameters and system constraints. The boundary values of the control parameters are calculated, including at the level of aggregators controlling the charging of EV. The method of hierarchy analysis can help in determining weights of optimizing subproblems [69]. Components of the objective function included in the task of optimizing the upper level of the city electric grid with EVs: Minimization of the cost of generation. In this task, it includes not only the cost of energy production in the urban energy system but also the minimization of the cost of purchasing electricity from generating companies.    X F g pg 5 ci2 p2gi 1 ci1 pgi 1 ci0 iAG

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Solving Urban Infrastructure Problems Using Smart City Technologies

Control parameters of the optimization are the following: pg is the generation of the active power within the grid or injection of power into the grid from an external supply network; G is the set of generator buses; and ci2 , ci1 , and ci0 are constants that scale the generation cost.

26.2.4 Minimization of losses in the electric grid The minimization of power losses in the smart electric grid, and the improving voltage profile in distribution systems by the optimal allocation of distributed generation, results in the optimal allocation of size and location, which are determined to achieve the highest benefit in terms of improving the bus voltages. Thus, the minimization of losses in the smart electric grid is determined by the following equation: FWp ðV Þ 5

X

Wpij ðVi ; Vj Þ

fi;jgAB

Wpij are the loses in the branch i-j; Vi ; Vj are the voltages at buses i and j; and B is the set of buses indexes for every branch in the bus-branch model.

26.2.5 Minimization of voltage deviations Voltage regulation or the minimization of voltage deviations, are important tasks in electrical engineering for controlling node voltages in a power network. Thus, the minimization of voltage deviations in the power network is determined by the following equation: FWV ðV Þ 5

X

jWVi j

iAN

WVi are the voltage deviations from permissible range and N is the set of buses with voltage control.

26.2.6 Reducing environmental impact The pollution emission function can be expressed as the polynomial function of the generator output active power as follows:   X FPol pg 5 ei0 1 ei1 pgi 1 ei2 p2gi 1 . . . 1 eik pkgi iAG

where ei are the pollution factors and k is the order of the polynomial. The constraints on the objective function (2) are: constraints on the injection of reactive power in generation buses, constraints on the range of control parameters, as well as constraints on the total power balance in the network, defined as: SG 2 SL 2 WS 5 0

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Which in turn is calculated by solving the system of power balance equations SN 5 VWYWV t where SN is the vector of active and reactive power injections, V is the vector of components of complexes of buses voltages, and Y is the conductivity complex matrix. The injection parameters of EV (load power when charging EV and generating power when EV acts as an energy storage device) also act as control parameters in a power system with EV. The available volume of such power is an uncertain value and can be estimated with some probability. The share of EV in the load of the bus of the electric grid can be estimated by monitoring on EV aggregating charge controllers. It is also possible to identify the share of EV by analyzing the change in load over time and identifying distinctive patterns [70]. The probability distribution of the charging load can be estimated based on statistical data on the charging of EVs, as well as on the assessment of their traffic [71
73]. Although in estimating the probability distribution in the context of time, different distribution models can be used (Weibull distribution [71] or lognormal [72]), but for each moment in time, the normal probability distribution of the injection of power EV can be obtained. This will make it possible to universalize the probabilistic calculation of optimal flow distribution at the network company level.

26.2.7 Probabilistic statement of the problem In a probabilistic formulation, the objective function Eq. (26.2) can be rewritten as: pðfc ðxÞÞ 5

n X

wi pi ðfi ðxÞÞ

(26.3)

i51

Instead of the deterministic components of the objective function fi ðxÞ, there are probability distributions of these functions pðfi ðxÞÞ. The boundary conditions are also not deterministic but are given by a probability distribution. As already shown in the preceding, the values of the components of the generalized objective function are calculated based on the state vector of the system, which is the voltage at each node of the electric network, as well as the generation power. The probability distribution of the generation power of PQ generation buses can be specified a priori in the form of a normal distribution. Thus, the entire complexity of calculating the components of the objective function reduces to calculating the probability distribution of voltages, which, in turn, can be obtained from the equations of power balance in the electric grid. In a probabilistic formulation, the balance of electric power in the grid Eq. (26.3) can be written as following: pðSN Þ 5 pðVÞYpðVÞt

(26.4)

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pðSN Þ is the injection probability distributions vector and p(V) is the vector of probability distributions of the system states to be determined. In the literature, such a formulation is known as the probabilistic power flow calculation and was first proposed in [74]. However, an assumption is made that the system is linear, power losses are neglected, and there is no relationship between active and reactive power. Such an approach is permissible only for an approximate calculation of power balances in the electric grid. The development of the method of probabilistic calculation of power flow distribution has since developed in many works, such as [75
77]. The essence of the probabilistic calculation of power flow distribution is to present the equation of the balance of electric power in the probabilistic formulation Eq. (26.4) in a linearized form: pðSN Þ 5 J 21 pðVÞ

(26.5)

where J is the Jacobi matrix of the current state of the system. New works in this direction [15,16] solve the problem of computational complexity of the convolution operation, which may not be applicable for large systems. This problem is solved by approximating the convolution by cumulants of the characteristic function of a random variable. However, these works are also based on the admissibility of the linearity of the problem being solved. Thus, this approach can be applied either in planning the power system modes, when the model can be simplified to linear or the approximation should be performed at each iteration of the solution of the nonlinear system of equations by Newton’s method using updated values of matrix J. In general, the probability distributions of power injection can be different for different buses. The model of the wind power plant uses the Weibull distribution [78] to determine the probability of wind speed, based on which the generation distribution of the wind power plant is calculated. The power distribution of the solar power plant is calculated using the beta-distribution function describing solar insolation [79,80]. The load model is usually given by a normal distribution with an average value and a standard deviation. As for the EV charging load, it can also be represented by a normal distribution for each point in time. At the same time, its mathematical expectation and variance change during the day. It is much easier to calculate the probabilistic power flow distribution if all injec tions in the network are represented by normal distributions pðSN Þ 5 N SN ; σ2s . The probability distribution of the objective function for each point in time, in this case, will also be normal. In this case, it seems reasonable to use the methods of interval analysis [81] to estimate the probability distribution of the state vector of the system pðVÞ and, as a consequence, the probability distribution of the objective function. When using interval arithmetic, the normal probability distribution of power injections is represented as the interval si 5 s0i 2 σ2si ; s0i 1 σ2si . The system of

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equations of balance of electric power (4) is then written in the form of an interval system of equations: s 5 vYv0

(26.6)

s is the box of active and reactive power injections and v is the desired box of system state variables. The solution to this problem can be performed using an external estimation of the solution sets by the Newton interval method [82].

26.2.8 Dynamic optimization Before this, we considered separate states for each moment in time. The task of optimizing on the level of the urban electric network is the optimization for a certain time horizon ahead to form the desired load schedule for the lower level control system. This problem can be represented as a problem of stochastic dynamic programming (SDP). Originally introduced by Richard E. Bellman, SDP is a technique for modeling and solving problems of decision making under uncertainty. Mathematically, we can describe multistage stochastic optimization problems as an iterated expectation

Minimize E x0 AX0

inf

x1 AX1 ðx0 ;ξ1 Þ



F1 x1 ; ξ 1





1E ...1E

inf

xT AXT ðxT21:0 ;ξ T Þ



FT xT ; ξT





Here T is the number of the discrete-time moments in timeslot; xi is the control actions on time i; ξi is a random component at time t; xT is a control actions set that depends on actions previously made; and Fi is a cost function for time period i. The objective function should take into account the cost of control actions, which depends not only on the state vector of the system but also on time.   Fi 5 Fbi xi ; ξ i 1 Ci ðxi ; xi21 ; iÞ Here Fbi is the base value of the objective function for each moment and Ci is the term taking into account the cost of control actions. Solving the dynamic optimization problem for the entire forecast time horizon is a computationally difficult task. A popular approach for solving such problems is the stochastic dual dynamic programming. The SDDP (stochastic dual dynamic programming) algorithm was firstly proposed in 1991 in [83]. Since, the algorithm has undergone many upgrades and specifications. Currently, the acronym SDDP encompasses a large family of algorithms. SDDP solves a large-scale complex problem by partitioning it into a set of smaller and simpler subproblems [84]. The solution to the original problem is constructed by solving and combining the solutions of subproblems in a forward or backward manner. In contrast to a brute-force algorithm, SDP can greatly reduce computation and save storage.

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Alternative dynamic methods for finding solutions under uncertainty are also widespread today, for example, methods that work on the principles of constructing a tree of possible controls, or methods that work on the principles of control rules. However, methods that work on the principle of constructing a tree inevitably encounter the well-known “curse of dimensionality,” and methods based on the principles of control rules, as a rule, require serious restrictions on the type of control rules, as well as on the properties of stochastic ones task parameters. Besides, in the problems of dynamic control, there is a problem of time-consistency solution.

26.3

Resilient operational control of microgrids

Optimization formulations for the operational management of microgrids typically impose the following objectives: (1) an economic operation with minimum utilization of conventional thermal generators, (2) a low switching rate of thermal generators (which is particularly important given that thermal generators may take several minutes to start, they consume more power and produce more emissions at start up and will require more maintenance), (3) a high penetration of renewable energy sources and a high utilization thereof, (4) adequate storage within the best operating limits of the storage units, as well as potentially other objectives. Additionally, the operation of a microgrid needs to take into account (1) the storage dynamics and the various technical requirements and constraints such as (2) the fact that the power that the network can request from renewable sources is bounded, and the maximum available energy depends on uncertain weather conditions, (3) the fact that thermal generators have a certain capacity, (4) the switching nature of thermal generators, in the sense that they cannot provide less than a certain minimum power, so they often need to be switched off, (5) the power sharing conditions across the network, which is controlled by the lower control layers, and (6) the power balance between generated and demanded energy and the associated optimal power flow problem.

26.3.1 Risk-averse multistage optimization and risk-averse MPC The mathematical formalization of the concept of risk traces back to publications in the field of operations research and mathematical finance with the seminal paper of Artzner et al. in 1999 who postulated a set of desiderata that are nowadays widely used to define well-behaving measures of risk [85]. Such risk measures are called coherent. Roughly speaking, a risk measure is a measure of the extent and size of the right tail of a distribution of losses/costs and lies between the expectation and the maximum (essential supremum) of such a random cost and is used to guide informed decisions that involve this cost. A risk measure attempts to extract a characteristic cost value out of a cost distribution that best describes the fixed price that corresponds to that uncertain cost.

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Risk measures are used in optimization formulations to suppress the effects of high-effect low-probability (HELP) effects and to mitigate the impact of inexactly known distributions. HELP effects may be associated with extreme weather conditions, unexpectedly low or high wind speeds, unexpected clouds, or similar conditions that are not foreseen by the stochastic model used by the controller, or their probability is underestimated. Formally, a coherent risk measure ρ is an operator that takes a random variable Z:Ω ! ℝ on a probability space ðΩ; F; PÞ and returns a scalar ρðZÞ and has the following properties which are known as coherence axioms [86]: (1) it is convex, in the sense that for all tA½0; 1 and random variables Z1 ; Z2 , it is ρðtZ1 1 ð1 2 tÞZ2 Þ # tρðZ1 Þ 1 ð1 2 tÞρðZ2 Þ, (2) it is monotone, in the sense that Z1 # Z2 implies ρðZ1 Þ # ρðZ2 Þ, (3) it is translation equi-variant, that is, for every constant c we have ρðZ 1 cÞ 5 c 1 ρðZ Þ, and (4) it is positive homogeneous, ρðaZ Þ 5 aρðZ Þ, whenever a $ 0, which practically means that we can change the units of measurement of the cost function (we can scale it and the risk measure will scale accordingly). It has been shown that coherent risk measures can be written in the following convenient form, which offers an alternative interpretation: ρðZ Þ 5 maxμAA Eμ ðZ Þ; where A is a (weakly- )-closed convex set of distributions. Set A is referred to as the ambiguity set of the risk measure. This representation of coherent risk measures offers the interpretation that they are worst-case expectations, when the underlying probability distribution, μ, draws from a set A of distributions. If A is a singleton—that is, if the probability is known—the risk measure reduces to the ordinary expectation operator. If instead A is the set of all distributions (A 5 D)—that is, if we have no information about the distribution—then, the risk measure becomes the (essential) supremum operator (see Fig. 26.5). This implies that the expectation and the (essential) supremum are trivial examples of risk measures. In practice, we are looking at cases where the available data can be used to construct nontrivial ambiguity sets. Risk-averse formulations are becoming popular in energy-related applications and, in particular, in energy management [23,87], unit commitment [88,89], scheduling [90], and optimal power flow [91
93]. The most popular risk measure used in practice is the average value-at-risk. The average value-at-risk, also known as the conditional value-at-risk or expected shortfall of a (integrable) random variable Z is given by

1 AV@Rα ðZ Þ 5 inf tAℝ t 1 EP maxf0; Z 2 tg : α For continuous random variables, the average value-at-risk at level α can be seen as the expectation of the α-right tail of the distribution.The average value-at risk is a coherent measure of risk with ambiguity set Aα 5 μAD:αμ # P which is illustrated in Fig. 26.6. The average value-at-risk includes the expectation and the

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Figure 26.5 A hierarchy of ambiguity sets for the average value-at-risk. This illustration refers to a three dimensional probability space (with Ω 5 {ω1, ω2, ω3} with corresponding probabilities π1, π2, π3). The large red triangle is the probability simplex, D, the set of all probability vectors. The orange and yellow subsets of D are the ambiguity sets of the average value-at-risk at level 0.6 and 0.9, respectively. Lastly, at α 5 1, the ambiguity set becomes a singleton.

Figure 26.6 The risk-averse concept: the average value-at-risk is a coherent risk measure that interpolates between the expectation and the (essential) supremum of a random cost. This leads to a continuum of optimization formulations that are “between” the conservative worst-case formulation and more cautious than the naı¨ve expectation-based formulation.

essential supremum as special cases. Indeed, AV@R0 ðZÞ 5 ZN and AV@R1 ðZÞ 5 EP ½Z. As parameter α goes from 0 to 1, we have a collection of risk measures: from conservative ones, which are closed to the worst-case risk measure, toward the expectation. This multitude of risk measures gives rise to a multitude of associated risk-averse MPC formulations. Other coherent risk measures involve the entropic value-at-risk and the meanupper semideviation. One possible approach toward the formulation of risk-averse MPC problems would be to simply replace the expectation operator in stochastic MPC (or the maximum operator in worst-case MPC) with a risk measure. However this ostensibly meaningful approach comes with severe limitations: firstly, it does not measure how the risk propagates in time, and second, and most important, it is

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not amenable to a dynamic programming formulation, therefore, it is not possible to design stabilizing risk-averse model predictive controllers. The remedy is to formulate a multistage risk-averse problem with a nested sequence of conditional risk mapping [86,94,95]. A conditional risk mapping is the risk-averse counterpart of the conditional expectation and it is a random variable [94]. When the uncertainty is described using scenario trees, the conditional risk mappings at a stage of the tree reduce to a collection of risk mappings on the spaces of children nodes for each node at that  stage as shown  in Fig. 26.7. A risk mapping at a stage k becomes a vector ρk 5 ρ1k ; ρ2k ; . . .; ρnk k , where nk is the number of nodes at stage k. A nested multistage risk measure is a risk on the  measure   probability space of nodes at a stage N defined as ρN ðZ Þ 5 ρ0 ρ1 ρ2 . . .ρN21 ðZ Þ . Such risk measures are used to construct appropriate multistage risk-averse formulations. Indeed, such risk measures are coherent; they reflect the way uncertainty propagates across stages and are amenable to dynamic programming formulations—an essential requirement to prove various risk-averse stability properties. In case of Markovian switching systems, such multistage measures can be constructed using the concept of a Markov risk measure, which is a risk measure conditioned at the modes of the Markov chain that drives the stochastic system [41]. The overall multistage risk-averse problem using the above nested risk measure becomes  Minimizeu0 ρ0 ‘0 ðx0 ; u0 ; w0 Þ 1 inf u1 ρ1 ð‘1 ðx1 ; u1 ; w1 Þ 1 . . . 1 inf uN21 ρN21 ð‘N21 ðxN21 ; uN21 ; wN21 Þ 1 ‘N ðxN ÞÞÞÞ; where ‘k ðxk ; uk ; wk Þ is the (random) cost function at stage k, which is a function of the system state, the control action and the uncertain parameter at that stage, and

Figure 26.7 A scenario tree showing the propagation of states and associated decision variables. At stage k 5 2, the stage-2 risk mapping comprises three risk measures—one for each node at that stage. The risk measure on the node of the state x12 is a risk measure on the space of children nodes, chð2; 1Þ.

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‘N ðxN Þ is the terminal cost function. The preceding risk-inf minimization problem is called a nested multistage optimal control problem and is solved subject to the system dynamics, xk11 5 f ðxk ; uk ; wk Þ, and the state and input constraints (xk AXk ; uk AUk and ðxk ; uk ÞAYk ). In risk-averse MPC formulations, a problem of the above form needs to be solved at every discrete-time instant. For that, one obtains a sequence of control laws, or, equivalently, a set of control actions on the nodes of the scenario tree over a finite time horizon. This can be thought of as a contingency plan of upcoming actions. The first control action, u0 , of this optimal solution is applied to the system and the problem is solved again at the next time instant in a receding horizon fashion. Multistage risk-averse MPC has been shown in [23] to offer resilience against misestimations in the probability distributions of load and available energy from renewable sources. Additionally, AV@R-based risk-averse MPC equips the designer with an additional tuning knob: the level of risk aversion α, which can be used to strike the desired balance between worst-case and stochastic control. Riskaverse MPC has the potential to be more resilient than risk-neutral expectationbased stochastic MPC, yet less conservative than worst-case MPC. Risk-averse formulations can also accommodate risk measures in the constraints [95]. Risk-based constraints are constraints of the general form ρðϕðxk ; uk ; wk ÞÞ # 0, for some measurable function ϕ. Risk constraints can serve as (tight) convex approximations to chance constraints (known as probabilistic constraints), that is, constraints of the form P½xk AXk  $ 1 2 δ. The average value-at-risk can in fact be used for such tight approximations. Risk-based constraints can also be seen as robustified versions of expectation constraints. Indeed, for a risk measure with ambiguity set A, the risk constraint ρðϕðxk ; uk ; wk ÞÞ # 0 can be interpreted as Eμ ½ϕðxk ; uk ; wk Þ # 0 for all probability measures μAA. Risk constraints are highly relevant for the power management of microgrids: the extremely high uncertainty associated with renewables and load can lead to conservative designs when all constraints are imposed as hard constraints. The current practice is to impose constraints as soft constraints, that is, to enforce their satisfaction by penalizing their violation in the cost function. However, the soft constraints approach evades a proper analysis and makes it difficult to establish guarantees on the level of constraint satisfaction. In other words, it is desirable to relax the constraints by be able to control the quality of service. Risk-based constraints provide probabilistic guarantees regarding the satisfaction of constraints and offer flexibility in terms of how demanding their satisfaction must be.

26.3.2 Numerical optimization methods for multistage optimization Nested multistage risk-averse problems of the above form have been considered particularly hard to solve numerically as the cost function, albeit convex, is a composition of a number of nonsmooth functionals. Even the computation of a subgradient of the cost function is not an easy task. Multistage risk-averse optimal

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control problems have been identified by Rockafellar and Uryasev as particularly hard to solve [96]. A novel approach was presented in [41] that allows to write them as conic problems and then solve those using off-the-shelf numerical optimization methods and algorithms such as MOSEK [97] and Super SCS [98]. It turns out that all known coherent risk measures over finite-dimensional spaces  can be written in the convenient form ρðZ Þ 5 miny y0 b:E0 y 5 Z; F 0 y 5 0; y $ K 0 , where E and F are matrices of appropriate dimensions, K is a convex cone and K is its dual. This realization, alongside the property ρðinf xAX gðxÞÞ 5 inf xAX ρðgðxÞÞ allows us to decompose the nested cost function and write the original nested multistage problem in the form of a conic problem. In the case of AV@R-based formulations, the resulting conic problem is a second-order problem (SOCP) for which there exist numerous numerical optimization software. This approach leads to computation times, which are significantly superior to SDDP approaches and pave the way for the application of risk-averse MPC controllers to real applications. Lastly, the resulting problems possess a certain structure because of the scenario tree, which can be exploited to devise ad-hoc numerical algorithms to solve such problems very fast. Proximal-type numerical algorithms, such as ADMM and the proximal gradient method can be used and the involved operations can be parallelized to yield very fast solution times. Further acceleration can be achieved by parallelizable implementations on graphics processing units, which have been proposed for riskneutral expectation-based stochastic optimal control problems [99
101]. As a remark, a day-ahead optimization schedule for gas-electric integrated energy system based on SOCP is proposed in [102].

26.4

Smart grids and digital twins

A digital twin (DT) is a digital replica of a real physical entity [69]. The DT term was first coined by Dr. Michael Grieves in his course on “product lifecycle management (PLM)” [70]. The DT concept consists of three distinct parts: physical product, the digital/virtual product, and their connections. The connections between the physical product and the digital/virtual product, is data that flows from the physical product to the digital/virtual product and information that is available from the digital/virtual product to the physical environment. The enabling technologies of DTs experienced exponential growth since then. Fig. 26.8 illustrates the basic framework, in which, the virtual space is mapped to the physical space through the connection part that exchanges data and information [103]. DT is characterized by data-driven mode, real-time interaction, and closed-loop feedback. A wide review of the DT applications within the industry was presented in [104]. The DT approach represents the next wave of development in modeling, simulation, and optimization since it can describe the current and predict the future behavior of the object [39]. The growing complexity of EРS makes it appropriate to introduce the concept of DT. Taking into account the significant complexity growth

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Figure 26.8 The DT concept.

of the control object, the main goal of introducing the DT concept in EPS is the need to understand the situation in real time. In this case, some control elements of a virtual object can change from model-based to data-driven based. The introduction of distributed generations with the simultaneous development of monitoring and control technologies provides an understanding that the data-driven paradigm is more natural for smart grids. Data-driven approaches may include model-free concepts when we no longer heavily rely on physical models and can handle the scenarios where topologies and some parameters are unreliable or unavailable. Comparing data-driven results to model-based ones, we can obtain some insights for further analysis. From a practical point of view, it should be noted, that organizations often get a quick start of DT when they first build simple DTs and put them into operation. Then there is a targeted change in DTs over time with the accumulation of new operation data, practice feedbacks, and subjective experience. It is quite different from the procedure of building a physical model for global designing, with the conventional development cycle, when assumptions and simplifications are required in advance. This quick start makes DT much more accessible than conventional simulations.

26.5

Summary

The concept of resiliency is the backbone of modern technical systems including energy systems. Resilient systems are supposed to provide control actions that detect adverse events and conditions. Such systems must exhibit the higher level of robustness and rapidly respond to disturbances, and recover afterward. The design of such self-healing energy systems employs the advanced mathematical models and methods. The contemporary industrial mathematics and computer science provides the solid arsenal of methods to be applied and integrated to design the highly resilient future energy systems. Many of these methods are still waiting to be understood by the practitioners to succeed in their business. This chapter reviewed some of such methods and concepts with focus on smart grids, EVs, and renewable energy sources. It starts with introduction where the main challenges of energy networks modernization are listed including renewable generation integration into Grid and flexibility of future smart energy systems. Then optimization of urban electric

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grids with EV charging load and vehicle-to-grid generation is discussed. The latter subsection following by the paragraph where the risk-averse multistage optimization and risk-averse MPC is presented. The chapter is concluded by introduction to the concept of DT. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

26.6

Chapter review questions/exercises

26.6.1 True/false 1. True or false? The use of renewable sources, effects a shift from a centralized production scheme, to a spatially distributed network that may involve several production and storage sites. 2. True or false? The computation of forecasts of the upcoming wind speeds, solar irradiation and demand, is essential for the network to respond proactively to expected changes in those values. 3. True or false? It is evident that the operation of power grids is subject to a number of conflicting objectives. 4. True or false? In modern smart power systems with fewer controllable power plants, energy management on a distribution system level, can be used to provide a nonflexible environment. 5. True or false? The use of power elements, incorporating computer (digital) control devices, can be used for the production, storage, transmission, distribution, and consumption of electricity.

26.6.2 Multiple choice 1. The optimization goals for the grid company may include: a. Minimization of power losses b. Providing the required voltage levels c. Optimization of the cost of electricity generation d. None of the above e. All of the above 2. The objective function at the lower level of optimization, takes into account the economic efficiency of the charge and: a. V2G technology b. EV charging load behavior c. Deep Q-networks d. EV power output e. All of the above 3. Optimization at the level of the smart electric grid is a: a. Pareto optimum b. Weighted product method c. Multipurpose optimization

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d. Weighted sum method e. Lexicographic method 4. The minimization of power losses in the smart electric grid, and the improving voltage profile in distribution systems by the optimal allocation of distributed generation, results in the optimal allocation of size and location, which are determined to achieve the highest benefit in terms of improving the: a. Bus-branch model b. Bus voltages c. Power network d. Smart governance e. All of the above 5. Voltage regulation or the minimization of voltage deviations, are important tasks in electrical engineering for controlling node voltages in a: a. Generator output active power b. Generation bus c. Power network d. Control parameter e. Power balance

26.6.3 Exercise 26.6.3.1 Problem Develop a plan outlining an appropriate process for electric distribution companies to provide project developers with information identifying the most valuable locations for distributed generation and public purpose smart microgrid deployment.

26.6.4 Hands-on projects 26.6.4.1 Project Do research: Identify the current trends in smart-grid research, by exploring the work carried out in numerous smart-grid labs on a global scale.

26.6.5 Case projects 26.6.5.1 Problem How will energy storage, distributed generation, and smart microgrids technologies, increase the adoption of the smart grid, and spur new markets for software and systems, that integrate the preceding technologies into modern and future energy systems?

26.6.6 Optional team case project 26.6.6.1 Problem What are the major differences and advances of advanced smart microgrids?

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144.

Future of connected autonomous vehicles in smart cities

27

Hossam Gaber1, Ahmed M. Othman2 and Abul Hasan Fahad1 1 University of Ontario Institute of Technology (UOIT), Oshawa, ON, Canada, 2University of Ontario Institute of Technology, and Zagazig University, Oshawa, ON, Canada

27.1

Introduction

A report by the United Nations predicts 2.5 billion more people will live in urban areas by 2050. To accommodate these people, cities need to get smart in all possible aspects. Therefore worldwide smart-city visions are now getting increasing attention in order to prepare for the future. Electric mobility is getting more widely accepted and is considered to be the future reality of mobility. With more concern on emission reduction and secure environment for future generations, many cities are pushing forward the use of electric vehicle while phasing out fossil fuel-driven vehicles. Citizens are adopting ridesharing services increasingly, which has positive impact on emission reduction and energy efficiency of modern cities. These battery-driven vehicles can provide power to home and can sell power to the grid. All these possibilities are disrupting the energy and transportation sector in this very moment. These monumental changes are leading the cities toward a new reality in terms of mode of transport—connected and autonomous vehicles (CAV). To define the level of autonomy of a vehicle, the International Society of Automotive Engineers has published ranges from a baseline of no automation, up to five levels of increasing autonomy: G

G

G

G

G

Level one, driver assistance (e.g., adaptive cruise control) Level two, partial automation (e.g., Tesla’s autopilot) Level three, conditional automation (e.g., human drivers serve as backup for an autonomous system that operates under certain conditions) Level four, high automation (e.g., Google/Waymo test cars) Level five, full automation (e.g., no steering wheel in the vehicle)

Hence the goal of this chapter is to present the CAV in the context of smart city. Efforts were made to present the interaction and integration of CAV with important smart-city components. Lastly a communication and verification platform for CAV in the University of Ontario Institute of Technology (UOIT) has been presented.

Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00027-9 © 2021 Elsevier Inc. All rights reserved.

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27.2

Components of smart city

According to the IEEE Smart Cities Technical Community, smart city can be defined as: A smart city brings together technology, government, and society to enable the following characteristics: a smart economy, smart mobility, a smart environment, smart people, smart living, and smart governance

In the keynote speech “Helping to Make Smarter Cities a Reality” at 2018 International Smart Cities Conference (ISC2) [1], IEEE PES President Saifur Rahman mentioned: There is no single consensus definition of a smart city, but there is some agreement that a smart city is one in which information and communication technology (ICT) facilitates improved insight into and control over the various systems that affect the lives of residents. A connected city is one where all relevant city systems—transportation, utilities, employment, health care, public safety, education, and others—are capable of communicating with each other to allow coordination and reduce waste. A smart city is an urban development vision to integrate information and communication technology (ICT) and Internet of things (IoT) technology in a secure fashion to manage a city’s assets.

The “United for Smart Sustainable Cities” (U4SSC) is a UN initiative coordinated by ITU, UNECE and UN-Habitat, and supported by CBD, ECLAC, FAO, ITU, UNDP, UNECA, UNECE, UNESCO, UN Environment, UNEP-FI, UNFCCC, UNIDO, UNU-EGOV, UN-Women, and WMO, in order to achieve Sustainable Development Goal 11: “Make cities and human settlements inclusive, safe, resilient and sustainable.” U4SSC serves as the global platform to advocate for public policy; and, to encourage the use of ICTs to facilitate and ease the transition to smart sustainable cities. UNECE and ITU have defined smart city as follows [2]: A smart sustainable city is an innovative city that uses information and communication technologies (ICTs) and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social, environmental as well as cultural aspects.

Fig. 27.1 shows the UNECE vision of smart-city components. The USDOT (see Fig. 27.2) has several vision elements for a smart city. In its smart-city challenge, it has mentioned: to identify an urbanized area where advanced technologies are integrated into the aspects of a city and play a critical role in helping cities and their citizens address

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Figure 27.1 One-UN approach to smart city. challenges in safety, mobility, sustainability, economic vitality, and address climate change.

From the preceding definitions, it can be easily seen how vital CAV are to the vision of developing a smart city. It is imperative to understand the functional model of CAV before the discussion of CAV interaction with other smart-city constituents. The next section will focus on it.

27.3

Connected and autonomous vehicle functional architecture

A CAV has four functional components [3]: 1. 2. 3. 4.

Localization Perception Path Planning Control

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Figure 27.2 USDOT vision elements for smart-city development.

Each function has multiple inputs from various sensors. Functional algorithm takes input from associated sensors, performs sensor-fusion, and provides multiple output to associated functional blocks. Fig. 27.3 describes the functional diagram of a CAV with associated inputs. The following sections will describe each function in detail:

27.3.1 Localization Localization is the task of knowing the actual position at any driving condition. To perform this function, CAV takes input from its onboard global positioning system device, telematics service (map), vehicle-to-infrastructure (V2I), and vehicle-tovehicle (V2V) commutation service to calculate its current location. Fig. 27.4 shows the localization process of a CAV. Many advanced Localization algorithms are proposed in the literature. They are termed as SLAM (simultaneous localization and mapping).

27.3.2 Perception Perception is a combined task of detection, classification and finally a virtual 3D model creation of CAV’s surrounding (see Fig. 27.5). In this task, CAV, is assisted by many onboard sensors, such as distributed cameras, RADAR, LIDAR, LASER, SONAR, etc. In addition, output from Localization is used in this step.

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Figure 27.3 CAV functional diagram.

Figure 27.4 Localization process.

27.3.3 Path planning According to recent literature, the path planning function (see Fig. 27.6) of a CAV is composed of three separate function: mission planning, behavioral planning, and motion planning. The typical task of each function is outlined as follows: G

The mission planner (or route planner): high-level decision such as determination of pickup-destination locations and road selections achieve the target mission

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Figure 27.5 Perception process.

Figure 27.6 Planning process. G

G

The behavioral planner (or decision maker): dynamic ad-hoc decisions such as lane change, intersection crossing, overtake, etc. The motion planner (or local planning): collision avoidance, obstacle avoidance, alarm generation, etc.

27.3.4 Control The control functions of CAV (see Fig. 27.7) is a complex one. In this task, there are inputs from localization, perception, and path planning process in addition to

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Figure 27.7 Control process.

sensor inputs monitoring road conditions, passenger and driver behavior and comfort, vehicle dynamics, energy management systems, etc. Sensor and information fusion from all these sources lead to trajectory generation and tracking, path tracking, speed control, cooperative control for platooning, etc.

27.4

CAV and smart mobility

Authors in [4] have identified nine key areas of smart mobility, which is depicted in Fig. 27.8. With its functionalities, the CAV will become a core part of the smart mobility ecosystem. With intelligent transportation system integration, V2V, and V2I communication services, CAVs can interact with smart mobility elements and help the management of such services in the operation of a smart city.

27.5

CAV and smart energy

CAV can be easily integrated into the smart grid with vehicle-to-grid technology (see Fig. 27.9) [5]. The following diagram illustrates a tentative integration method. Most of the CAV in future will be electric. So charging infrastructure will be developed all over the smart city. The price of electricity today is dynamic in nature. Therefore intelligent transportation infrastructure nodes can receive this dynamic pricing signal and relay to charging point and CAVs. Intelligent charging management software inside a CAV will then decide the most optimum amount

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Figure 27.8 Smart mobility areas.

Figure 27.9 A method of CAV integration with smart grid.

of charge, place and time. In this way, CAV can act as energy-responsive nodes in smart-city context.

27.6

CAV and smart home

A smart city will consist of Smart Homes [6]. Many smart home devices are available in the market. Smart home devices allow all the home appliances and utility components to interact with each other based on the user requirement. Many electric vehicles today are integrated in respective owner’s home through the charging interface.

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Figure 27.10 CAV integration with smart home.

However there are many ways a CAV can transform this situation. Fig. 27.10 shows the connection between a smart home and a CAV through 5G cellular network. Smart home controller can send pickup-drop-off requests, parking request, passenger status, etc. to a CAV and with its capabilities, a CAV can execute such request in an efficient manner. Similarly, a CAV can transmit data such as real-time location, charging status, passenger-health, etc. to a smart home. Such interaction between Smart Home and CAV will surely change the dynamics of smart city.

27.7

CAV and smart health

CAV can significantly affect health of smart-city residents [7]. Fig. 27.11 shows some of the benefits that are impacted by CAV in a smart city. In a smart city, there will be less traffic accidents, due to CAV usage, as they have advanced functionalities and are integrated with an intelligent transportation management infrastructure. In addition, with CAV’s smart energy management and environment-aware driving modes, smart city will have improved air quality and environment due to CAV application. Smartcity citizens will be health-aware as CAVs monitor the passengers’ behavior and can alert them about tentative health risks. CAVs will also ensure improved urban quality of life with improved travel safety, less traffic congestion, less driving stress, etc.

27.8

CAV testing and verification platform

This section presents an integrated testing and verification platform of CAV and transportation electrification and (CAVTE) at automotive center of excellence (ACE) facility within UOIT. In collaboration with Canadian Standards Association

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(CSA), CAVTE will test, verify, certify, and lead the standardization activity of modern and innovative vehicular and electrification technologies, such as autonomous vehicles; wireless charging; energy storage systems; V2V and V2I connectivity; cyber-physical security, etc. CAVTE will support Auto manufacturers, infrastructure service providers, utilities, and government agencies with its

Figure 27.11 Health benefits of CAV usage in smart city.

Figure 27.12 Integrated test platform schematic.

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industry-leading facilities. Within the ACE at UOIT, CAVTE can facilitate testing in different operating and weather conditions, which will enable realistic and comprehensive results and will enable faster commercialization and adoption of innovative transportation technologies. The primary aim of CAVTE will be to support the research and innovation relating to the Development of Canadian Standards and Certification process on the basis of key performance indicators (KPIs) such as safety, reliability, cost, human interactions, and environmental impacts. CAVTE facility will enable CSA to evaluate different technologies and systems and conduct different tests accordingly. The target test facility will be connected via wireless sensor network and Internet of Things with layers of cybersecurity to monitor and control the target CAVTE setup at UOIT via remote access and operation by CSA team. Fig. 27.12 shows the layout of CAVTE setup.

27.9

Summary

CAVs are soon to become a part and parcel of our daily life. Smart-city vision is getting more popular all over the world; and, it will be unwise to not consider the impact of CAV on smart-city realizations. Keeping this idea on mind, this chapter has presented the relationship and impact of CAV with multiple components of a future smart city. CAVs will drastically change mobility, energy, homes, health, and environment of smart city. Tentative scenarios were presented in relevant sections describing the communication, integration, and impact of CAV on respective elements. It is of utmost importance to focus on research for testing and validation of CAV technology, which is already underway in advanced part of the globe. UOIT is taking initiative to establish an integrated testing and validation platform. Tentative design of this platform was presented. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

27.10

Chapter review questions/exercises

27.10.1 True/false 1. True or false? U4SSC serves as the global platform to advocate for public policy and to encourage the use of ICTs to facilitate and ease the transition to smart sustainable cities. 2. True or false? It is imperative to understand the functional model of CAV before the discussion of CAV interaction with other smart-city constituents. 3. True or false? Localization is the task of knowing the actual position at any driving condition. 4. True or false? Perception is a combined task of detection, classification, and finally a virtual 4D model creation of CAV’s surrounding. 5. True or false? With its functionalities, the CAV will become a core part of the smart mobility ecosystem.

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27.10.2 Multiple choice 1. CAV can be easily integrated into the smart grid with: a. Vehicle-to-grid technology b. Intelligent transportation infrastructure nodes c. Charging point d. Intelligent charging management e. Smart homes 2. Many electric vehicles today are integrated in respective owner’s home through the: a. Charging interface b. 5G cellular network c. CAV d. Smart home e. All of the above 3. In a smart city, there will be less traffic accidents, due to CAV usage, as they have advanced functionalities and are integrated with a: a. Smart energy management infrastructure b. Air quality and environment infrastructure c. Urban quality of life d. Intelligent transportation management infrastructure e. CAV and transportation electrification 4. Within the ACE at UOIT, CAVTE can facilitate testing in different operating and weather conditions, which will enable realistic and comprehensive results and will enable faster commercialization and adoption of: a. Wireless mobile technologies b. Key performance indicators c. Innovative transportation technologies d. Smart governance e. All of the above 5. Smart-city vision is getting more popular all over the world and it will be unwise to not consider the impact of CAV on: a. E-government b. E-governance c. Citizenry engagement d. Smart-city realizations e. Smart economy

27.10.3 Exercise 27.10.3.1 Problem What type of rapid urban developments and sustainable transportation solutions are required to meet the increasing demands for mobility, while mitigating the potentially negative social, economic, and environmental impacts?

27.10.4 Hands-on projects 27.10.4.1 Project Do research: What makes it possible to compile massive amounts of real-time data to optimize the smart urban infrastructure? In other words, what makes it possible

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to improve the efficiency of smart public transport services, from both user and service-provider perspectives?

27.10.5 Case projects 27.10.5.1 Problem Explain why vehicles that include interactive advanced driver-assistance systems and cooperative intelligent transport systems can be regarded as connected.

27.10.6 Optional team case project 27.10.6.1 Problem What are the solutions that are required to meet the increasing demands for smart mobility, while mitigating potentially negative social, economic, and environmental impacts?

References [1] ,https://www.un.org/development/desa/publications/2018-revision-of-world-urbanization-prospects.html., May 16, 2018. [2] ,http://www.saifurrahman.org/presentations/., September 22, 2019. ¨ .S. [3] O ¸ Ta¸s, F. Kuhnt, J.M. Zo¨llner and C. Stiller, Functional system architectures towards fully automated driving, in: 2016 IEEE Intelligent Vehicles Symposium (IV), Gothenburg, 2016, pp. 304 309. [4] R. Faria, L. Brito, K. Baras and J. Silva, Smart mobility: a survey, in: 2017 International Conference on Internet of Things for the Global Community (IoTGC), Funchal, 2017, pp. 1 8. [5] T. Strasser, P. Siano, Y. Ding, Methods and systems for a smart energy city, IEEE Trans Ind Electron 66 (2) (2019) 1363 1367. [6] E. Kim, Smart city service platform associated with smart home, in: 2017 International Conference on Information Networking (ICOIN), Da Nang, 2017, pp. 608 610. [7] M. Espinilla, J. Medina, G. Urzaiz, P. Singh, IEEE Access Special Section Editorial: ambient intelligence environments with wireless sensor networks from the point of view of Big Data and smart and sustainable cities, IEEE Access, vol. 6, 2018, pp. 72025 72027.

Future developments in vehicleto-grid technologies

28

Michela Longo1, Wahiba Yaici2 and Federica Foiadelli1 1 Politecnico di Milano, Milan, Italy, 2CanmetENERGY Research Centre, Ottawa, Canada

28.1

Introduction

Electricity is vital for economic and social well-being. Conversely, its nonavailability can have very dire effects; a power failure can interrupt or impede the supply of essential services (including transport, finance, communications, water supply, and especially healthcare) when there is no backup power available or the power recovery time exceeds the backup autonomy. So let us talk about critical infrastructure. The recent blackout in Caracas, Venezuela is a typical example of the devastating and even fatal effects that a power outage can inflict. In that city, some patients in a number of hospitals died when vital equipment shut down as a result of critical energy deprivation. Certain important systems within the electricity sector bear a special mention: G

G

G

G

Large classic thermal and hydroelectric generation plants Distributed hydroelectric generation systems Distributed renewable generation (wind, photovoltaic, etc.) Energy transmission and distribution systems (consisting of hundreds of primary cabins and tens of thousands of secondary cabins).

The growing use of renewable resources and polygeneration, that is, systems delivering more than one form of energy, has caused the electricity grid to become increasingly diffused/decentralized. The presence of subjects (prosumers) that produce energy on a small scale and transfer it to the network makes the energy flow bidirectional. The interconnected devices—from smart homes to electric vehicles (EVs)—are increasingly numerous and equipped with advanced functions and require increasingly complex management of smart grids. There is an increasing number of stakeholders involved in the process and a similar proliferation of smart devices connected to the network. The impact of digital transformation in the energy sector affects the entire energy chain: from procurement, to aggregators, to distribution and transportation, to sales, and relations ultimately the end-users. In spite of the intricacies described earlier, the complexity of the system is still inadequately represented. The electricity ecosystem has always been complex and strongly interconnected. Organizations, large and small within this environment rely on one another for critical business equipment and services. The introduction of digital technologies has amplified the level of interconnectivity/interconnection Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00028-0 © 2021 Elsevier Inc. All rights reserved.

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and introduced an additional dimension of risk, which all organizations within the ecosystem must manage together: this is known as cyber risk. The security of electrical systems changes dramatically because they transition from safe physical systems to cyber-physical secure systems. The separation between IT (information technology) and OT (operation technology) was traditional in the electricity grid and in its vision of security. The approach to the security of legacy supervisory control and data acquisition system/industrial control systems is premised on the idea of an impregnable castle. However the limitations of this approach are well known. IT and OT environments are fundamentally and functionally different: they have different priorities within commercial activities, disparate functional requirements, dissimilar work cultures, and different risk appetite. As a result, they often also have distinct security requirements. In summary, the fundamental differences consist in the fact that in IT the priority is confidentiality, while in OT primacy is usually accorded to availability. These two areas must interpenetrate and be addressed simultaneously. The need to increase security levels is also due to the progressive introduction of new technologies, both in the energy sector and in the telecommunications sector [e.g., cloud computing, wireless transmission systems, and industrial Internet of Things (IoT)]. The data generated in embedded systems, created by machine-to-machine and IoT devices, are growing exponentially in the electrical sector and their importance places them at the core of the system, hence the need to decide on a specific security strategy. IoT units installed globally by utilities grew by an average of 23% per year. Regrettably, as their use expanded, so did the attacks grow not only in numbers, but also in complexity. Without adequate cybersecurity measures, systems are vulnerable to violation, and power interruptions could occur, which could cascade down to interconnected systems and energy services, causing irreparable damage to equipment and people. A proactive approach is a design that incorporates security from the earliest stages of the life cycle of a solution, to guarantee the adoption of cybersecurity principles and to maintain them throughout the entire life cycle of IT/OT/IoT solutions and infrastructure. Leading energy companies increasingly view cyber attacks as a threat to business continuity. Despite acknowledging this profound problem, stakeholders still share very limited information about risks, experiences, and lessons learnt. Sharing “best practices” would contribute to a greater awareness of the impact of cyber risks in energy companies and in the energy sector as a whole. The sector must adopt a systemic approach and evaluate the problem through the entire “supply chain,” to improve the protection systems and limit any possible domino effect that could be caused by a failure in any aspect of the value chain. The public sector has sought to improve the cybersecurity levels of all organizations through Directives issued by regulatory institutions (NIS, NERC, and CIP). The Directives provided the basic safety guidelines/requirements; however, compliance with them does not necessarily assure safety. The rapid digitalization of the electricity ecosystem makes it important not to wait for standardization but to be

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proactive in facing imminent cyber attacks. Organizations must be resilient and adopt a strategic approach to managing cyber risks. However, the distributed nature of the electricity industry ecosystem can make it difficult for a single organization to efficiently identify a cyber attack. Overcoming this challenge requires a real-time transparent sharing of information in order to gain collective awareness of the situation. In addition, real-time sharing of information should take into account national security implications as information required to manage cyber risks may need to cross national and regional borders. A first approach could be development of a framework for real-time, coordinated, neutral, specific information-sharing for electricity at an international level. To effectively integrate cyber risk into the business strategy, progress must ultimately be measured. Monitoring cyber resilience efforts and measuring the effectiveness of investments in cyber resilience remains a challenge for stakeholders in the electricity ecosystem (both public and private). To overcome this challenge, robust cybersecurity metrics must also be expressed in business language.

28.2

Smart grid

As already expatiated, electric mobility represents a necessary transition to dispense with a mode of transportation that is overly dependent on harmful fossil fuels, with their deleterious effects on the environment which discharges make urban centers increasingly unlivable. Electric mobility, being one of the branches of “smart mobility,” is therefore connected to one of the pillars of the “smart cities”: cities with urban planning strategies and plans aimed at ensuring sustainable economic development and high quality of life through a skillful management of available resources (food, mining, energy, services, etc.). The fundamental pillars of a smart city are six as shown in Fig. 28.1 [1]. The pertinent pillar is “smart mobility.”

Figure 28.1 Evolution from a traditional grid to a smart grid.

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However it would be reductive to limit the import of “smart mobility” to merely switching from a type of transport with an internal combustion engine to one with an electric motor. In reality, “smart mobility” is a much broader concept involving different stakeholders (public administrations, private, public or mixed companies, end-users, etc.) and technologies/services (carsharing, autonomous drive, tripplanning app, etc.) but the full treatment is outside the scope of this paper. Rather, this chapter, will deal with the aforementioned concept of vehicle-to-grid (V2G). Nowadays, in reality, the perception of the EV is that it refers to the “passive” type, of the grid-to-vehicle (G2V) type, coincided to mere electric load. However, this notion could be destined to change in the immediate future. The idea of the V2G fits into the more general concept of the “smart grid.” A possible and exhaustive definition taken from [2,3] of smart grid is the following: “a smart grid is an electricity network based on digital technology that is used to supply electricity to consumers via two-way digital communication. This system allows for monitoring, analysis, control and communication within the supply chain to help improve efficiency, reduce energy consumption and cost, and maximize the transparency and reliability of the energy supply chain.” The current electrical system originated in at the start of the 20th century and was conceived as an exclusively unidirectional system [4,5]. It consisted of relatively few production centers and many users, and had all the limitations and disadvantages that this entailed, including: G

G

G

High Joule losses due to the long distances that connecting production centers and endusers; incomplete sentence Difficulties in managing energy flows caused by the high uncertainty of the distributed generation (wind, photovoltaic, etc.) and lack of protocols in dynamic energy management Overly long response times in cases of failures or malfunctions with consequential inefficiencies

Therefore, its evolution in the “smart grid” foreshadows the resolution of these limitations with the introduction in the electric network of real-time embedded sensors and automatic control systems in order to: G

G

G

G

Realize a real-time grid monitoring to have a permanent awareness of the network’s parameters, voltage and current measurements, grid events detection, etc. Detect any malfunctioning, reducing repair times and maintenance costs Optimize the energy consumption of the end-user who becomes more aware of his own consumption and act accordingly, even if remotely Exploit and better coordinate the various small, distributed production centers

28.3

Vehicle to grid

With the increasing number of EVs being integrated into the power system, the potential impact of EV on an electric utility could be substantial. In the aspects of generation side and transmission side, the effect is relatively small, but the impact on the distribution system cannot be ignored. From the view of the power system

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operator, the load fluctuations and the power losses during charging are the significant concerns that have to be minimized. Not only are load fluctuations essential, power quality (e.g., voltage profile, three-phase unbalances, harmonics, etc.) are also important to both the system operator and grid customers. In addition, a series of supervening problems must be addressed, including system planning, system efficiency, system reliability, EV user benefit, and EV user convenience. V2G concept was ignited by the aforementioned problems. V2G was first discovered in 1995 by Amory Lovins, and later developed by William Kempton. The primary concept of V2G is that EVs can provide energy to the power system when parked, and the battery of EVs can charge during low demand times and discharge when power is needed. In this way, the EV users buy electricity from the grid at low prices and sell electricity at high prices to obtain certain profits [6].

28.3.1 Architecture Fig. 28.2 shows a generic architectural design of a V2G system with interactions among power generation/transmission, power consumers, and plug-in electric vehicle (PEV) users. The power systems include convention generators, renewable sources, and transmission facility. The power systems supply energy to both consumers (e.g., residential, industrial, and business) and V2G systems. The V2G systems are composed of PEVs connected with the power grid through public and private charging stations and aggregators. An aggregator is a mediator controlling and optimizing energy flow between power grid and V2G systems. The V2G systems act as both energy storage and consumer. V2G communication provides data and information exchange among power systems, power consumers, and V2G systems, and it consists of communication

Figure 28.2 V2G architecture.

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infrastructure (e.g., wireless networks) and processing facilities (e.g., cloud computing and data center) [7].

28.3.2 Advantages In recent years, due to the widespread use of EV and battery, V2G has received considerable attention. V2G is still a relatively new concept, and as an important part of the smart grid, research on it is still in its infancy. V2G technology can potentially achieve the following benefits: G

G

G

G

G

Reduce environmental pollution: Being distinct from conventional vehicles using fossil fuel, PEVs can significantly reduce environmental pollution even when power generation emissions are concerned. It is estimated that by replacing a conventional car by a PEV, CO2 emissions can drop by 2.2 tonnes per year [8]. Enhancing ancillary services: In practice, many cars travel on the road only 4% 5% of the day, while they spend the rest of time parked. This implies that we can utilize such EVs to facilitate the ancillary services in V2G systems, for example, spinning reserves, reactive power support, frequency, and voltage regulation, to balance supply and demand for reactive power. These services can be used to reduce an overall cost of V2G systems, thereby decreasing energy prices for customers and improving load factors. Improving quality of services for PEV users: Due to the development of battery technologies, V2G systems enable very quick response time for energy supply in which the charging and discharging responses can be performed in milliseconds. Furthermore, there is no significant running cost for the unit’s committed operations. Therefore, quality of services for PEV users, for example, serving time, can be improved considerably. Supporting renewable energy: The power quality from renewable sources such as solar and wind generators can be greatly improved by using PEVs as storage and filter devices. The combination of PEVs and renewable energy sources can strengthen the power grid, making it more stable and reliable. Enhanced revenue to PEV users: PEV users can receive monetary reward for discharging energy or other support benefits from V2G operators in participating in the system. Thus, by adopting intelligent energy management solutions, the PEV users can balance their demands and charging/discharging processes, for example, charging during nonpeak hours and discharging during peak hours, to achieve more savings and thus earn more revenues.

28.4

State-of-the-art of the V2G

Up till the present time, V2G researchers have focused their research mainly on economic feasibility, global structure and implementation method. In 2005, Willett Kempton from University of Delaware studied primary V2G problems which include: capacity calculation and system profit. In the same year, he researched the V2G implementation problem of stabilizing the grid to support large-scale renewable energy. In 2009, Dirk Uwe Sauer from Germany, published articles which addressed the impacts from the mobile energy storage; and, the results showed that mobile storage systems consist of EVs and control systems THAT can partially replace the static

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storage systems [9]. In [10], it researches the V2G application that the EVs join the peak modulation and establishes the V2G system model which provides the reference for the future research [6]. In [11] studies the optimal load shifting problem via EVs with both G2V and V2G which is formulated as a mixed integer quadratic programming problem. A decentralized optimal algorithm based on alternating direction method of multipliers is proposed to solve the problem in a decentralized manner. In [12], load regulation through dynamic programming successive algorithm optimization method is employed to obtain the optimal charging strategies by minimizing the overall load variance of daily household load demand.

28.4.1 Classification Due to the diverse characteristics and different power supply functions of EVs, some research findings show that the V2G can be divided into two categories to achieve (see Table 28.1). PEV users can enter into a long-term agreement with the V2G operator to make charging and discharging more predictable. For example, the operator can offer battery maintenance service in exchange for PEV users agreeing Table 28.1 Advantages and disadvantages of centralized and decentralized control solutions. Type of solution

Advantages

Disadvantages

Centralized

Control energy and ancillary service efficiently Maximize revenue for the provider and PEVs

Decentralized

Preserve individual authority Able to adapt to a large number of PEVs Better fault tolerance. Fast and convenient services since decisions Less communication and infrastructure required

Privacy of the PEVs can be vulnerable Decisions of the PEVs are controlled by the provider Require a powerful central controller and a backup data storage Complex and expensive communication infrastructure Can be delayed or interrupted due to the system overload or cyber attacks Must be able to handle a large amount of data at the same time Require methods to predict demands of the PEVs for the provider Require efficient decentralized control solutions for the PEVs The PEVs must find approaches to protect themselves are made and controlled by them from cyber attacks

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to charge and discharge the battery to meet the requirements of the V2G systems. With this approach, centralized control of charging and discharging processes can be implemented to achieve the maximum efficiency. However, to achieve such a goal, status monitoring and information update are necessary for V2G systems. The V2G systems should be able to obtain the timely conditions of both moving and parking PEVs. The conditions can be PEVs’ locations, battery capacities, battery state-of-charge, and expected times of arrival and departure at/from charging stations. Using this information, the V2G system can estimate the amount of energy to charge and to receive from PEVs in certain areas. Alternatively, some PEVs can participate in V2G systems voluntarily without making long-term commitment with the V2G operator. For example, the operator can offer different incentives for charging and discharging energy by PEVs depending on current load and supply of the power grid. The PEV user individually considers the current location, that is, charging stations locations, the battery state-of-charge, and energy price to decide to charge (or discharge) its battery or not. With this approach, charging and discharging decisions are made by PEV users in a distributed fashion. Therefore, the V2G systems must provide information about the incentive to motivate the users in such a way that the system efficiency is maximized [7]. At present, with the development of V2G, the key issues are as follows: G

G

G

G

Intelligent dispatching from the grid view Smart charging management from the EV view Bidirectional charger Effect of V2G on battery

To solve two great problems of the harmonic’s pollution and the load fluctuations from EVs, the research studies focus on the bidirectional charger and the charging/discharging strategy [6].

28.4.2 Bidirectional charger Most of the conventional chargers are unidirectional, and they will create harmonics problems, which will not meet the requirements in the power system. To achieve the V2G, we need to equip a two-way smart charger between the power grid and the EV. Battery chargers play a critical role in the development of EV. The purpose is to ensure that they can improve the efficiency, reduce the cost and volume, and suppress total harmonic distortion under normal condition, and still have a good control performance when it is subjected to the external disturbance. From the literature, the research studies mainly focus on the charger topology and the control strategy. According to the different EV charger topology, it can be divided into the following three types [13]: 1. Consisting of uncontrolled rectifier and chopper. The features are: large volume, large current harmonics of grid side, and low efficiency. It is not suitable for access to the public grid. 2. Consisting of uncontrolled rectifier and DC DC converter. The features are: large current harmonics of grid side (about 30%), low efficiency, and low cost. It is the main charger on the market.

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3. Consisting of pulse width modulation (PWM) rectifier and DC DC converter. The features are: small harmonic, high power factor, and dual energy flow.

A typical bidirectional charger has two stages: an active grid-connected bidirectional AC DC converter that enforces power factor and a bidirectional DC DC converter to regulate battery current. Fig. 28.3 shows the general bidirectional charger topology.

28.4.3 Voltage source rectifier Currently, due to the preceding features, the PWM control applying in AC DC converter is the popular research topic, especially the voltage source rectifier (VSR). Depending on the grid AC signal, VSR can be divided into voltage control and current control. Because the current control method is simple and direct, it is more widely used. VSR current control scheme is usually dual-loop control: the outer-loop takes the voltage control to maintain stability of the DC bus voltage; and the inner-loop takes the current control (direct current and indirect current control), the direct power control and the time-optimal control. We can regard the output of the out-loop voltage as the instruction of the inner-loop, and then the inner-loop (current or power) rapidly and timely adjust the current of the AC side to suppress load disturbance, reduce harmonic, and achieve unity power factor control. The traditional modulation strategy: sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM). In SPWM, based on the three-phase AC power, it focuses on how to generate a three-phase sinusoidal power to adjust the voltage and frequency, and it is easy to use hardware circuit to achieve. In SVPWM, it uses eight basic voltage vectors to composite the desired voltage vector, and then establish the state of the converter switchers to achieve the regulation. The SVPWM has the better dynamic performance, high efficiency of the DC voltage. Meanwhile, compared with the SPWM, it can reduce the switching losses in the same waveform quality [14].

Figure 28.3 General bidirectional topology.

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28.4.4 DC DC converter Since bidirectional AC DC converter output voltage may not match the voltage of the DC energy storage unit, one might also need a bidirectional DC DC converter to ensure proper charging voltage. When the converter is operating in battery discharge mode, the process is just the opposite. In [15], comparing with several nonisolated bidirectional DC DC converters, it puts forward the variable frequency pulse width modulation (VFPWM) used in the three-level DC DC converter to improve the power efficiency of half bridge converter at lower battery pack voltage. In [16], the author analyses the isomorphic topology and suited applications of bidirectional DC DC series resonance converter (SRC) and adjusts the phase shift angle between different ports and bridge arm to the power flow and the output voltage.

28.4.5 Charger control method Bidirectional charging system is characterized by nonlinearity, varying time, and strong coupling, greatly challenging the control system design, especially when model inaccuracy and external disturbances are taken into account. So the control requirements are very high. At present, the control methods are many: traditional linear/nonlinear control, modern nonlinear control, and intelligent control. These include: proportional integral derivative (PID) control, active disturbance rejection control (ADRC) control, fuzzy control, adaptive control, neural network control, Lyapunov stability theory control, and so on. In [17], it proposes double closedloop PI control to achieve the charging and discharging, but current power quality is poor. The PID is famous for its “error is used to reduce error” principle, but it harbors the contradiction between overshoot and rapidity. In [18], a fuzzy-controlled active state-of-charge controller for improving the charging behavior of a lithium-ion (Li-ion) battery is proposed. But the fuzzy control rules are difficult to establish and the control accuracy is not high. In [19], a bidirectional current source converter topology is proposed as a grid interface for V2G application, and ADRC theory is proposed to manage the charging and discharging processes. ADRC is proposed by Jingqing Han and Zhiqiang Gao, who developed it. Fig. 28.4

Figure 28.4 ADRC-controlled charging model.

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shows the ADRC-controlled charging model. ADRC inherits from PID: the error driven, rather than model-based [20]. Comparing PID and ADRC, the advantages of ADRC as follows: G

G

G

Fast response, small overshoot At steady state, the fluctuation of voltage or current is minimal Strong resistance to external disturbances

But the drawback is that its parameters are relatively large, and it is hard to set parameters. As previously mentioned, there are many control methods and the control mode is complex. The technology of the traditional control method is mature and easy to realize. The intelligent control needs not set up a charger mathematics model, so it is introduced into the control of the charger. But the intelligent control is still very immature; it remains at simulation stage. In summary, the bidirectional charger for research mainly includes the following aspects: G

G

G

Charger structure Harmonic suppression from grid connection Charger operation efficiency

28.5

Charging/discharging strategy

This section provides an overview of charging/discharging strategy from the viewpoint of the grid and user. Then we will describe the time-of-use (TOU) electricity price and the TOU concepts.

28.5.1 Grid view The grid view approach consists of focusing on the system operation indicators and a series of subsequent influence factors, including voltage deviations, power losses, and system efficiency. The research of centralized control is based on various objectives, including lowering operating costs, reducing energy loss, or minimizing load variance. Therefore from the viewpoint of the grid, the EV store energy planning and scheduling are serious problems to solve. In these issues, solutions can be divided into two categories: G

G

Adopting intelligent algorithms to control each EV operation. Power systems directly dispatch each EV and other generating unit. Ahmed Yousuf Saber from Missouri University of Technology employed this approach [21]. However, this approach will complicate issues and it also does not take into account the EV user’s perspective. Adopting aggregator model [22]. Establishing an intermediate system between the grid and the EV group. The aggregator organizes some EVs within a certain area, and then dispatches them as a whole. So the grid is not required to have in-depth analysis of the status of each EV and merely needs to manage the aggregator. For the direct management of the EV, the aggregator can finish. Fig. 28.5 shows an aggregator scheme for dispatching EVs.

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Figure 28.5 An aggregator scheme for dispatching EVs.

28.5.2 User view In the current research into V2G technology, researchers seldom consider the main participants of the V2G. The problem is if the EV users are willing to participate. However, most of the V2G commercial operation programs that have been proposed require EV accepting system regulation. Through research and analysis, research teams suggest that V2G theoretical optimal control strategy is difficult for EV users to accept in practice. For each EV connected to the grid, on one hand it provides support services to grid through V2G; on the other hand, it also obtains energy from the power grid. However, whether it provides support services or obtains energy, the process is not free or unlimited. It needs to consider EV realtime and future status, such as battery SoC (state of charge), future travel plans, current position, current electricity prices, and other information. This is to ensure that EV users get the optimal benefits under normal driving conditions. Actually, those problems originate from the EV uncoordinated charging. The EV, as large loads, may lead to increasing the operation complexity of future power systems, taking its charging or discharging randomness and intermittency into account. To settle these problems, many scholars have conducted pilot studies on technical level, from analyzing the effects of the EV charging behavior, to measuring the system’s benefits when EVs discharge to power system through the V2G technology. Nevertheless, there are few systematic management studies on the above problems, and fewer studies on the discussion of the price setting of the EV charging and discharging electricity price. However one way to achieve V2G is to guide the user’s

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charging and discharging behavior by setting a reasonable charging and discharging price and applying some other stimulus measures.

28.5.3 Time-of-use electricity price The TOU electricity price is an important approach to cut peak loads and fill the valley to ensure stable operation of power systems. The TOU electricity pricing must consider the stakeholders of the government, the power companies and the EV users. The power company is allowed to adjust the electricity price under the price cap given by the government to regulate the power load.

28.5.4 Traditional TOU In [23], the Poisson distribution features of the EV users’ initial charging/ discharging time are considered. Discharging demand function of EV owners is proposed based on economic theory. An optimal formulation of peak-valley TOU tariff is proposed to minimize load fluctuations under the constraints of EV charging/ discharging time and energy demand. In [24], based on the demand side response theory, it adopts the peak and valley lime charging price strategy rather than the unified price strategy, coordinating the EV load as the target, to analyses the EV user’s market response and the respective revenue functions of the EV user and power company. At present, the traditional TOU has its shortcomings. These are: G

G

G

G

Not taking into account competition from the new energy Seldom factoring in the government’s pricing mechanism Lacking other stimulation method to influence user participation If EV user only consider their own interests, it may lead to a new peak

28.5.5 Game theory TOU In [25], based on the game theory, establishing the TOU electricity price model which indicates that the government determines the price level, the power company determines the detailed price, and the user determines the amount. In [26], it proposes an agents’ pricing game model, considering the response of EV charging policy on prices which can reduce the cost of ownership and achieve a win-win for agents and owners. And it transforms the game model into a mixed integer linear programming by Karush Kuhn Tucker conditions and duality theorem without considering any approximation. On one hand, the game theory applied in the TOU fully considers the user’s psychology and the actual situation, so it will attract more participants. On the other hand, it can decrease the scale of the algorithm. Due to limited research studies, the game model is not perfect and needs to be further improved. Fig. 28.6 presents the game theory TOU applied in the V2G. Fundamentally, the charging/discharging strategy is a multiobjective optimization. Multiobjective evolution algorithm is one

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Figure 28.6 Game theory framework.

of the most active research fields in recent years. Domestic and foreign scholars have proposed algorithms one after another, including: strength Pareto evolutionary algorithm, Pareto archived evolutionary strategy, indicator-based evolutionary algorithm, multiobjective particle swarm optimization, S-metric-selection evolutionary multiobjective optimization algorithm, and they have been applied in the optimization problems of power systems [6].

28.6

Summary

The electricity grid as we know it today is directed to change profoundly. After all, the structures linked to the world of electricity have never been static and steady over time: the innovations have followed one another, with new and decisive changes from time to time. But the changes that are about to come in the next few years will most likely be such as to bring a real electric revolution. They are called Smart Grids, or smart grids and they really will be smart, given that in the near future, they will save energy and protect the environment around us, in response to a production landscape that has radically changed compared to some year ago. In effect, if in the past we were faced with large electricity-producing centers and a network made up of a myriad of users, today many consumers have actually become producers in turn, as a result to photovoltaics and renewable energies; however, through the use of EVs in V2G mode there will be an additional pool of energy. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

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Chapter review questions/exercises

28.7.1 True/false 1. True or false? Electric mobility, being one of the branches of “smart mobility,” is therefore connected to one of the pillars of the “smart cities”: cities with urban planning strategies and plans aimed at ensuring sustainable economic development and high quality of life through a skillful management of available resources (food, mining, energy, services, etc.). 2. True or false? With the increasing number of EVs being integrated into the power system, the potential impact of EV on an electric utility could be substantial. 3. True or false? The power systems supply energy to both consumers (e.g., residential, industrial, and business) and V4G systems. 4. True or false? In recent years, due to the widespread use of EV and battery, V2G has received considerable attention. 5. True or false? Alternatively, some PEVs can participate in V2G systems voluntarily without making short-term commitment with the V2G operator.

28.7.2 Multiple choice 1. Most of the conventional chargers are unidirectional, and they will create harmonics problems, which will not meet the requirements in the: a. EV b. Power system c. V2G d. Battery charger e. DC DC converter 2. Depending on the grid AC signal, VSR can be divided into voltage control and: a. PWM control b. Current control c. Dual-loop control d. Time-optimal control e. All of the above 3. Since bidirectional AC DC converter output voltage may not match the voltage of the DC energy storage unit, one might also need a bidirectional DC DC converter to ensure proper: a. Battery pack voltage b. Output voltage c. Charger control voltage d. Bidirectional voltage e. Charging voltage 4. The grid view approach consists of focusing on the system operation indicators and a series of subsequent influence factors, including voltage deviations, power losses, and: a. Load variance b. Intelligent algorithms c. Aggregator models d. System efficiency e. All of the above

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5. In the current research into V2G technology, researchers seldom consider the main participants of the V2G: a. EV b. Battery SoC c. TOU d. Poisson distribution e. V2G

28.7.3 Exercise 28.7.3.1 Problem Develop a technology road-mapping process for smart electric V2G technologies.

28.7.4 Hands-on projects 28.7.4.1 Project Do research: What are the main features, opportunities, and requirements of V2G?

28.7.5 Case projects 28.7.5.1 Problem Why is V2G taking so long to happen?

28.7.6 Optional team case project 28.7.6.1 Problem Why would a transition to V2G enable vehicles to simultaneously improve the efficiency (and profitability) of electricity grids; reduce greenhouse gas emissions for transport; accommodate low-carbon sources of energy; and reap cost savings for owners, drivers, and other users?

References [1] S.V.F. Lewis, Optimal Control, Wiley-Interscience, 1995. [2] C. Xia, C. Shen, Optimal power split in a hybrid electric vehicle using, in: Asia-Pacific Power and Energy Engineering Conference (APPEEC’10), 2010, pp. 1 4. [3] Y. Guezennec, G. Rizzoni, A. Brahma, Optimal energy management in series hybrid electric vehicles, in: American Control Conference, 2000, pp. 60 64. [4] C. C. Lin, J. -M. Kang, J. W. Grizzle, H. Peng, Energy management strategy for a parallel hybrid electric truck, in: American Control Conference, 2001, pp. 2878 2883. [5] C. C. Lin, H. Peng, J. W. Grizzle, J. -M. Kang, Power management strategy for a parallel hybrid electric truck, IEEE Trans Control Syst Technol 11, 2003.

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[6] B. Zhang, X. Zhou, Z. Gao, Y. Wu, J. Yin, X. Xu, et al., An overview on V2G strategies to impacts from EV integration into power system, in: 2016 28th Chinese Control and Decision Conference (CCDC), 2016. [7] P. Wang, D. Niyato, E. Hossain, D.T.Hoang, Charging and discharging of plug-in electric vehicles (PEVs) in vehicle-to-grid (V2G) systems: a cyber insurance-based model, in: IEEE Transactions on Communications, 2017. [8] F.R. Islam, H.R. Pota, Integrating Smart PHEVs in Future Smart Grid in Renewable Energy Integration, Springer, 2014, pp. 239 258. [9] M. Kleimaier, W. Glaunsinger, D. U. Sauer, Relevance of energy storage in future distribution networks with high penetration of renewable energy sources, in: 20th International Conference and Exhibition on Electricity Distribution Part 1, 2009, pp. 1 4. [10] J. Yang, W. Wang, Y. Zhang, D. Wang, F. Ye, Applying power battery of electric vehicles for regulating peak in grid, East China Electric Power 38 (11) (2010) 1685 1687. [11] Z. Lin, M. Fu, H. Xing, A new decentralized algorithm for optimal load shifting via electric vehicles, in: 36th Chinese Control Conference, 2017. [12] P. Fajri, I.Husain, F. Hafiz, Load regulation of a smart household with PV-storage and electric vehicle by dynamic programming successive algorithm technique, in: 978-1-5090-41688/16/$31.00 Conference: 2016 IEEE Power and Energy Society General Meeting, 2016. [13] M.H.N. Li, Comparison among chargers of electric vehicle based on different rectifiers, North China Electric Power 1 (2011) 23 29. [14] X. Zhang, Study on the PWM rectifier and its control strategies, Doctoral Dissertation, 2003. [15] X.H.Z.S.Z.B.S.L.A.H.Y. Du, Review of non-isolated bi-directional DC-DC converters for plug-in hybrid electric vehicle charge station application at municipal parking electric vehicle charge station application at municipal parking, in: 25th Annual IEEE Applied Power Electronics Conference and Exposition (APEC), 2010, pp. 1145 1151. [16] C. Liu, Research on bi-directional DC/DC converter for small electric vehicles, Doctoral Dissertation, 2013. [17] B.-Y. Chen, Y.S. Lai, New digital-controlled technique for battery charger with constant current and voltage control without current feedback, IEEE T Ind Electron 59 (3) (2012) 1545 1553. [18] L.-R. Chen, K.-S. Huang, G.C. Hsieh, Fuzzy-controlled Li ion battery charge system with active state-of-charge controller, IEEE T Ind Electron 48 (3) (2001) 585 593. [19] W. Liu, M. Su, X. Li, H. Wang, J. Yang, Y. Sun, A unified modeling and control of a multi-functional current source-typed converter for V2G application, Electr Pow Syst Res 106 (2014) 12 20. [20] J.Q. Han, From PID to active disturbance rejection control, IEEE T Ind Electron 56 (3) (2009) 900 906. [21] G. K. Venayagamoorthy, A. Y. Saber, Unit commitment with vehicle-to-grid using particle swarm optimization, in: IEEE Bucharest in PowerTech, 2009, pp. 1 8. [22] S. Han, S. Han, K. Sezaki, Development of an optimal vehicle-to-grid aggregator for frequency regulation, IEEE T Smart Grid 1 (1) (2010) 65 72. [23] D. Xiang, Y. Song, Z. Hu, Z. Xu, Research on optimal time of use price for electric vehicle participating V2G, Proc CSEE 33 (31) (2013) 15 25. [24] L. F. Shi, Design for the electric vehicle charging and discharging price strategy from demand side management perspective, Doctoral Dissertation, 2012. [25] L. Zeng, Game based time-of-use electricity price models and relevant simulations, East China Electric Power 35 (8) (2007) 40 44. [26] W. Wei, Y. Chen, L. Feng, S. Mei, F. Tian, X. Zhang, Stackelberg game based retailer pricing scheme and EV charging management in smart residential area, Pow Sys Technol 39 (4) (2015) 939 945.

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Charru Malhotra1, Vinti Manchanda2, Anushka Bhilwar2 and Aniket Basu1 1 Indian Institute of Public Administration, New Delhi, India, 2Shallate Service Pvt. Ltd, New Delhi, India

29.1

Introduction

The United Nations in the year 2012 had established sustainable development goals (SDGs) to guide the development agenda to be achieved by the year 2030. Goal 11 of SDG aims to “make cities and human settlements inclusive, safe, resilient and sustainable” [1]. The overarching vision of SDG 11 could be understood as that of providing urban state services equitably without any differentiation of abilities (or disabilities). Creation of cities that are fair in their approach in terms of distribution of services for the coming decades is the need of the hour [2]. As per United Nations World Urbanization Prospects Report [3] the world is progressing toward an indicative process of rapid urbanization, where over 60% of the global population would be living in urban centers by the year 2030, which is expected to rise to over two-thirds by the year 2050. This rapid urbanization will consequently lead to a burgeoning pressure on the prevailing resources of the cities. These issues get further compounded due to economic, social and physical disparities existing amongst the city populace. The city populace is usually heterogeneous in nature as different communities migrate to a city in varied circumstances including a natural calamity or may be a war, or may be for finding better livelihood options. In the process of responding to the needs of all within constrained resource provisions, the needs and aspirations of several communities including the elderly, poor and disadvantaged communities, referred together in the chapter as “differently abled communities (DAC)” [DAC refers to people with disabilities, elderly (above the age of 60), poor, and disadvantaged] are often sidelined. A smart city is one that strives to enhance the quality and performance of urban services and utilities by employing emerging trends of information and communication technologies (ICT), including “Internet of Things (IoT),” “cloud computing,” “mobile computing,” “artificial intelligence (AI),” etc. A smart city therefore employs these digital technologies to facilitate all public services including transportation, education, health care, social facilities, and utilities. This is done to maximize the performance of public service delivery mechanisms with minimum wastage. However, liberal use of digital technologies might end up causing more problems of accessibility than solving it, especially for all those who are on the wrong side of digital divide. This is especially true for Solving Urban Infrastructure Problems Using Smart City Technologies. DOI: https://doi.org/10.1016/B978-0-12-816816-5.00029-2 © 2021 Elsevier Inc. All rights reserved.

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DAC, who might be reluctant in accepting these digital innovations, especially if those are not easily accessible, adaptable, and affordable for them. There is thus a need for these smart cities to be more inclusive to the demands and needs of this sensitive section of our population. The overall intent of the study is to suggest an inclusive paradigm for designing smart cities so that the emerging technologies could be employed more meaningfully to improve the “quality of life (QoL) for all” irrespective of the differences assailing DAC. With this aim, the authors try to propose a conceptual model in order to make a city an inclusive smart city with special reference to Indian context.

29.1.1 Need for the study: the Indian context India is a developing economy and the second most populous country in the world with a significant part of its population being differently abled. People with disabilities constitute about 2.1% of the country’s total population [4]. Even an increase is expected in its elderly population from 8% (in 2015) to 19% (in 2050) and finally to 34% by the end of the century [5]. Further, only around one-tenth of this elderly population has access to any kind of pension, including the paltry sum of INR.200 (US $ 2.81) per month that is provided under the Indira Gandhi National Old Age Pension Scheme, a Government of India (GoI) scheme. Urbanization is also growing with almost 34% of its population. To cope up with these mounting pressures on the Indian cities, GoI launched its Smart City Mission (SCM) in the year 2015 [6]. This mega project was initiated with the aim of drawing a strategy for Indian cities to retrofit, redevelop and achieve city extension and consequently achieve efficiency in the city administrative regime. The SCM emphasizes that smart cities are those that provide core infrastructure and give decent QoL to its citizens, a clean sustainable environment and application of “smart” solutions [7]. This initiative by the Indian government also resonates with various provisions of the Indian constitution with Article 14 providing that the “the state shall not deny person equality before law.” The Supreme Court of India on similar lines has also sanctioned the “right to adequate housing” as a fundamental right protected under Article 21 of the Indian Constitution. Indian cities cannot be called smart, till they are not accessible to all [8]. Technology-based “inclusive development” is being emphasized as a mandatory approach, even by the President of India [9]. The policymakers and designers in India would have to gradually expand their vision of smart cities so that technology could be seen as a tool for social equity in urban areas.

29.1.2 Flow of the chapter This section of the chapter introduces the topic as well as establishes the background of the study (Section 29.1). The following section deals with the review of literature, which tries to trace the origin of “smart cities” and explores its various definitions. It explains the various technological advances, which make up any city smart (Section 29.2). A separate section is devoted to list some of the global

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initiatives that have been adopted around the world to make a smart city more inclusive (Section 29.3) as well as to encapsulate the Indian context (Section 29.4). The main contribution of the chapter is the proposed conceptual model that strives to address the needs of the DAC, using digital technology as a tool (Section 29.5). The chapter concludes by providing a basic set of recommendations on revisualizing smart cities to be all-inclusive so as to improve the QoL for all irrespective of the differences assailing DAC (Section 29.6).

29.2

Review of literature

According to the United Nations [3], over 60% of the world would be living in urban centers by the year 2030 and this number is expected to expand to over twothird by the year 2050 [3]. This phenomenon of rapid urbanization demands a more careful and sustainable use of resources as well as services in the city. Escalating urbanization is goading cities around the world to look for ways in which resource optimization could be achieved without compromising on the development agenda of the city, which is possible only through prudent urban planning. It is under these circumstances that the concept of smart city becomes important that advocates newer approaches to urban planning using the urban data that is collected and harnessed using digital technologies including IoTs, AI, and so on [10]. The last few years have seen a meaningful rise in the concept of a “smart city,” where a city being ‘smart’ has been ascribed to a process of advancements involving processes such as digitalization in government, mobility, and sustainability [11]. This idea of a smart city is now being accepted as a standard blueprint for the municipalities around the world to deal with problems that usually assail urbanization and related population explosion in urban spaces [12]. However, despite the widespread use of the term, smart city, there is still no consistent representation of what a smart city constitutes. The term has been used globally with varying connotations in varying contexts [12]. Tracing its genesis, the term “smart city” was first scouted to have been used in mid 1990s by California Institute for Smart Communities; in this context the term “smart city” centered around the implementation of new ICTs-based technologies in addressing infrastructure challenges posed in the cities [13]. With the turn of the century, when it was deemed that for a city to be smart it should be able to provide various services contextually to its citizens, then the concept of smart city was realigned with the concept of urban planning [10]. A city, in any part of the world is made and grown by the people that inhabit it [11]. Therefore, there is a need to recognize the human element in this current equation of smart urban planning, which involves a heavy reliance on the use of ICTs. Based on this paradigm of thought, another relevant perspective on smart cities is that of citizens’; this perspective insists that since it is not technology but citizens who can make a city smart, therefore smart city essentially includes citizens’ participation in the processes of urban governance. A study, on these lines, defines smart city as a space “where investments in human and social and traditional (transport)

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and modern (ICT) communication infrastructure fuel sustainable economic growth and high QoL, with a wise management of natural resources, through participatory government” [14]. This is crucial, as the most important feature of this technology is not its ability “to automatically create smart communities, but its adaptability to be utilized socially in ways to empower people” [15]. There is another perspective to understanding of the term “smart cities”—it is industry perspective which is essentially (and understandably) technology driven. On this line of thought, the literature gleaned from industry sources, particularly an IBM journal describes a smart city as an “urban center that employs operational data and is an instrumented, interconnected, and intelligent city” [16]. “Instrumented” refers to a city’s ability to collect data from both physical and virtual sensors and to connect it with real world data. “Interconnected” refers to the integration of this data into a computing platform, which then facilitates the exchange of various services within the city through this medium. “Intelligent” in this context, relates to the inclusion of complex analytics, modeling, optimization, and visualization of these services to make better operational decisions [16]. It can be convincingly argued that this approach allows data-based planning of various public services, and helps to adapt urban services to the needs of its inhabitants thereby leading to an optimal use of available resources in the city. Albino et al. (2015) have converged these varied perspectives of “smart city” and have summarized that a set of four attributes could be identified as necessary and essential for any city to be regarded as “smart” [10]. These four characteristics include “networked infrastructure” (that enables political efficiency and social and cultural development), an emphasis on the “business-led urban development and creative activities” (for the promotion of urban growth), “social inclusion” of various urban residents (to enhance the social capital in urban development) and the “natural environment” as a strategic component of the future [10]. Majority of smart-city initiatives around the world have been imbuing these four characteristics for developing smart cities including Amsterdam, Barcelona, Copenhagen, Dubai, Singapore, and Shanghai. More specifically, The SCM launched by the Government of India (GoI) deserves a special mention. Launched in the year 2015 under the Union Ministry of Housing and Urban Affairs it aims to identify 100 eligible cities throughout the country that could be remodeled into smart cities through a process of area-based development involving retrofitting, green fielding, and redevelopment around the city [6]. This process would involve providing smart solutions by harnessing technology to improve various services such as e-governance and citizen services, waste management, water management, energy management, urban mobility, etc. The ultimate purpose of the SCM is to drive the process of economic growth in the country to offer a better QoL to its citizens. All these measures within the SCM and other smart-city initiatives around the world intend to mobilize technology for improving the lives of citizens, thereby making urban spaces smarter. As can be understood from the previous discussions, the underpinning strength of smart cities is social inclusion of various urban residents (to enhance the social capital in urban development). However, there still lies a significant section of

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urban population whose needs and demands are often not adequately represented in the cities—especially in developing countries like India. These are people with disabilities, poor and disadvantaged and the elderly, referred by one category titled “DAC” in this chapter. DAC forms an important part of our society but is often not consulted or considered when any new initiatives are being created or implemented. As a result, such initiatives end up creating more barriers and not conveniences for this segment of population. Before any such ICT-based initiative is started, there must be clear delineation of the intended impact of ICTs on the society as a whole, which is more often than not, missing. In the majority of the instances, not much tangible improvement in the QoL of people is sighted. To the contrary, there is definitely a possibility that widespread ICT implementation could inflate the digital divide [15] and consequently cause a social, economic, and cultural polarization [14]. Further, availability does not always ensure utilization; there is also a possibility of digital technologies not being utilized appropriately by all the sections of the society. There is thus a glaring need to bridge the gap that denies the DAC their rightful claim to the benefits emanating from the various technological advances in the world. Understanding what makes a city inclusive hence becomes important in this context. Pineda [17], in his seminal work on creating inclusive and accessible cities for the disabled, has proposed an urban centered capability model of disability (CMD), which highlights three key features for city and urban planning processes. This involves “rethinking the relationship between people with and their environment, a development-based framework for inclusive policy making along nine policy dimensions and the concept of salience to measure cultural coherence and likelihood for a society to adopt international human rights norms at the local level” [17]. He argues that this model can lead to positive results helping change an individual’s position in the society. These include creating favorable circumstances that allow the disabled to be at par with other sections of the society, a push for better social validation of the said section along with an increase in general rights and duties [17]. Being at par with other sections of the society will enable the DAC to participate in the society as at an equal level, whereas an increase in social validation will help alter the social perception toward this section of the society and also help create a better understanding of what the said section can do despite their abilities or disabilities. An increase in the general rights and duties will lead to more social inclusion for the differently abled as it comprises a more unified resolution toward health, rehabilitation, education, and employment as well as a more dedicated and inclusive approach toward mobility, accessibility, community, inclusion, political, and public participation of the same [17]. These principles of an accessible inclusive city by Pineda can be added to the present understanding of inclusive cities so that it is favorable for DAC. The foundation of CMD [17] can also be connected to the philosophy of Universal Design that calls for “the composition of all products and environments, to be usable to the greatest extent possible by people of all ages and abilities” [18] can be incorporated into the existing knowledge of how a smart city is imagined. This concept which was developed in 1997 by a group of architects, product

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designers and environment researchers led by Ronald Mace includes 7 principles of equitable use, flexible is use, simple and intuitive use, perceptible information, tolerance and error, low physical effort, size, and space for approach and use [18]. These fundamentals of a universal design can also be a guide to creating comprehensive smart cities, which are more inclusive to the wants of all its inhabitants. One of the simplest yet important examples of Universal Design in action are the automatic sensor doors, as compared to the usual door knobs and lever doors which could only be accessed by people who were capable and have enough physical strength [19]. These power-assisted doors are thus a necessity for providing access to people with some form of mobility impairment. Emerging technologies and advancements in the field can likewise play a crucial role and have a great potential in making these smart cities more inclusive. Many new and novel technologies within ICT like IoT, AI, and AT (assistive technology) can and have proven to be crucial in aiding the DAC in a variety of ways. The IoT is the communication of everyday devices among themselves. These devices are equipped with sensors, actuators, embedded computing, and cloud computing, which enables communications. To put it simply, the IoT enables devices (things) to interact and coordinate with each other, reducing human intervention in basic everyday tasks [20]. Since most of the new and emerging IoT applications are focused on facilitating comfort and security, they can enable a sense of independence among the DAC through its features that allow a user to control various things in their physical space such as control the temperature remotely, control door locks, activate alarm systems, and so on [21]. For a person with some form of physical disability and/or dexterity, IoT can prove to be immensely helpful by providing functionalities such as remote services at home; speech-activated devices and automated accessibility functions. Similarly, for a person with a hearing disability and IoT-enabled functionality can aid them by providing services such as visual cues regarding the status of home devices on mobile phones and captioning in glasses delivered by beacons [21]. AI has been defined as: a branch of computer science dealing with the simulation of intelligent behavior in computers and the capability of a machine to imitate intelligent human behavior [22], it is used to empower devices to perceive the surrounding environments using different tools available, leading to calculative decisions and performing efficient actions order to maximizing the chances of successfully accomplishing a task [23]. On the other hand, AT “are those whose primary purpose is to maintain or improve an individual’s functioning and independence to facilitate participation and to enhance overall wellbeing” [24]. The idea is to make citizen participation as the key. Therefore, the role of AT shall enhance the participation of the people by possessing certain technology products such as smart devices, for the citizens to carry out basic activities of life and equally enjoy their rights as citizens. Another important breakthrough of AT is the introduction of features like video-monitoring, electronic sensors, fall detectors, doors monitors, bed alerts, pressure mats, etc. can help in improving lifestyle of DAC in terms of security and ability to carry out various tasks [25]. Neto and Kofuji in their work propose, a “inclusive smart-city approach,” which brings together the concepts of the smart city, urban computing, accessibility, and

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universal design by creating a digital AT, based in an urban space that enables differently abled people to achieve a higher level of independence and autonomy to perform a range of activities which might seem ordinary to others [26]. The integration of these into the existing understanding of the smart cities can therefore help build an inclusive smart city, where not only are these services available but are also accessible by all. This will also ensure that this section of the society is also an active participant in the growth and development process of the state and that the needs and demands of the residents in these inclusive smart cities are reflected in the solutions that the city administration implements for the same.

29.3

Learning from existing global implementations

This section of the chapter talks about some of the global best practices that have been adapted by city administrations around the world, to make them more inclusive for the DAC. While increasing citizen participation and engagement are important factors, it is also important to recognize that challenges faced by the DAC are not homogenous. For instance, a person with a physical disability might face problems accessing their tangible space due to different issues such as buildings without elevators, closed-off wheelchair ramps, inaccessible toilets, shops, etc., the busy and crowded city space can prove to be a sensory nightmare for someone with a learning disability or on the autism spectrum. Similarly, an elderly person may face a completely different set of problems and challenges. There are numerous examples of countries and international organizations that have adopted schemes, legislatures, and protocols keeping these in mind. For instance, the Convention on the Rights of Persons with Disabilities and its Optional Protocol was adopted with the vision of human rights and social development for all. Under this, there are eight guiding principles that underlie the convention and each one has specific articles, as follows [27]; “Respect for the inherent dignity, individual autonomy including the freedom to make one’s own choices, and independence of persons, Non-discrimination, Full and effective participation and inclusion in society, Respect for difference and acceptance of persons with disabilities as part of human diversity and humanity, Equality of opportunity, Accessibility, Equality between men and women, Respect for the evolving capacities of children with disabilities and respect for the rights of children with disabilities to preserve their identities.” Different countries around the world have similarly responded to this demand of more inclusivity by initiating various smart-city projects such as those in Amsterdam, Barcelona, San Francisco, Shanghai, Singapore, etc. Although various disability laws around the world such as the Americans with Disabilities Act, Britain’s Equality Act, Australia’s Disability Discrimination Act, and India’s Rights of Persons with Disabilities Act seek to increase the rights and access of specially abled people, the ground reality is however often different. Despite these barriers, there are some examples around the world, of cities, which are creating

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and adopting strategies for inclusive and accessible smart cities. A few of which are as follows.

29.3.1 Seattle, USA The Taskar Centre for Accessible Technology, University of Washington came up with Access Map, a footpath mapping-based app, which allows pedestrians with limited mobility to plan approachable routes via custom made settings to avoid areas such as uphill or downhill areas. The app coordinates its data with from Seattle’s Department of Transportation and the US Geological Survey to provide the best possible route to people with limited accessibility [28].

29.3.2 Alexandria, USA Alexandria, in the United States, officially declared itself a dementia-friendly city after several years of developing a Strategic Plan on Aging, spurred by the White House’s 2015 Conference on Aging. The city will implement the plan, developed by the Alexandria Commission on Aging, until 2021. While a major part of the plan is training service workers to work with people with dementia and the elderly, the city hopes to implement technology that can help make some things easier. Taking a step in the right direction, the city enrolled in Smart911 last year, a free service where citizens or their caregivers can create profiles that make it easier for emergency service workers to locate them during a crisis [29].

29.3.3 European Union—City4Age City4Age (elderly friendly city services for active and healthy ageing) is a research and innovation project funded by the European Commission under the Horizon 2020 Programme. The first and core objective of City4Age is to enable ambientassisted cities or age-friendly cities. The project aims to create an innovative framework on ICT tools and services that can be deployed by European cities in order to: enhance early detection of risk related to frailty and mild cognitive impairments, and provide personalized intervention that can help the elderly population to improve their daily life and also promote positive behavior changes [30].

29.3.4 Sonoma, USA Autism Friendly Design in Sonoma, USA: this housing project in Sonoma California aims to address the sensory overload that people on the autism spectrum undergo in the messy and turbulent city life. The project created by Leddy Maytum Stacy Architects opened in 2013 and has been laid out according to autism specific principles, which were recommended by the Arizona State University to foster a sense of calm among its inhabitants.

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29.3.5 Korsør, Denmark Sports for all in Korsør, Denmark: The Mushlom sports, holiday and conference complex in Korsør is owned by the Danish Muscular Dystrophy Foundation. The center is a vast sports hall with an aerial ropeway and climbing wall for wheelchair users along with an integrated pulley system [31]. All the hotel rooms in the center have features such as ceiling hoists, electronic curtains, and beds with automatic raise and recline, sinks with adjustable heights and accessible toilets making it an all-inclusive center [31]. Denmark is also known for The House of Specially abled People’s Organization in Copenhagen, which has been recognized as the most accessible office building in the world.

29.3.6 Melbourne, Australia Bluetooth audio cues in Melbourne, Australia: the city of Melbourne in Australia had initiated an 8-month experimental study at Southern Cross station rail terminal, which could alter the way in which a person with a visual disability can access their public spaces. The project used an unpaid GPS app and bluetooth to develop a guide navigation system. The end user obtains audio signals through their smartphones that provide direction and real-time information related to different obstacles within a person’s tangible space. Outside, the app provides real-time directional information; inside, where GPS is unreliable, 20 wireless bluetooth beacons ensure that the users continue to receive information [31].

29.3.7 Global Initiative for Inclusive ICTs The Global Initiative for Inclusive ICTs (G3ict) and World Enabled in 2016, launched the ‘Smart Cities for All’ initiative, with the objective of underlining the unprecedented opportunities that inclusive technology will create in the future for cities [32]. This initiative in the same year surveyed more than 250 global experts of which over 60% claimed that the smart cities today are inclusive to people with disabilities as technology solutions within them are not designed to be accessible and inclusive [17]. The biggest challenge to a more inclusive and accessible smart cities according to the smart cities for all initiative has been the “lack of awareness of disability, accessibility, and inclusion”—including in the design and innovation process [32]. The project thus aims to provide cities and urban innovation ecosystems with tools to help overcome the barrier of this lack of awareness. Similarly, this initiative in September 2018 also announced “The Inclusive Innovation for Smarter Cities” project in partnership with AT&T and the cities of New York and Chicago. The project aims to help ensure the growing number of cities implementing smart-city strategies do so with inclusion as an essential part of it from the very inception of these plans [33]. This project sought to take on the understanding and wisdom of various prominent accessibility, innovation, and disability professionals to come up with resources for various global smart cities. This collaboration intended to bring about more comprehension about the ways in which urban

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innovation ecosystems can be more inclusive and provide guidelines to cities in ways they can make their innovation process more inclusive.

29.4

Understanding Indian context

Although basic demographic reality of Indian context had been encapsulated in the first section, this section of the chapter tries to evaluate the present policy structures of GoI including its SCM launched in the year 2015. Through the years, the GoI has launched various schemes and policies for DAC in order to promote their health, well-being, and independence around the country. The central government also introduced the—National Policy for Older Persons in the year 1999 to promote health and welfare of senior citizens in India. The aim of this policy was to encourage individuals to make provisions for their own and their spouse’s old age, encourage families to take care of their older family members, etc. The policy enables and supports voluntary and non-government organizations to supplement the care provided by the family along with providing care and protection to vulnerable elderly people by offering services such as health care, research, creation of awareness, and training facilities. The main objective of this policy is to make older people fully independent citizens. Under this policy, various schemes have been introduced as listed as follows: strengthening of primary healthcare system to enable it to meet the healthcare needs of older persons; training and orientation to medical and paramedical personnel in health care of the elderly; promotion of the concept of healthy ageing; assistance to societies for production and distribution of material on geriatric care; provision of separate queues and reservation of beds for elderly patients in hospitals; and extended coverage under the Antyodaya Scheme with emphasis on provision of food at subsidized rates for the benefit of older persons especially the destitute and marginalized sections. The Integrated Programme for Older Persons, 2007 is another scheme that provides up to 90% financial assistance to NGOs to establish, maintain, and provide services such as old-age homes, day care centers, and mobile healthcare units to the elderly. The Scheme of Assistance to Panchayati Raj Institutions, Voluntary Organizations, and Self Help Groups supplies a one-time construction grant for building old-age homes and multiservice centers for the elderly. In addition to these the Central Government Health Scheme provides central government offices pensioners the amenity to acquire medicines for a stretch for chronic illnesses. The National Mental Health Programme similarly deals with the needs of elderly persons affected by Alzheimer’s, dementia, Parkinson’s disease, depression, and psycho geriatric disorders. The GoI keeping in mind the needs of the differently abled brought out the Rehabilitation Council of India Act, 1992. It is the highest government body in the country that supervises the articulation of training and education programs and courses dealing with the information related to the differently abled. The National

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Trust for Welfare of Persons with Autism, Cerebral Palsy, Mental Retardation, and Multiple Disabilities Act, 1999 created a national trust to empower a differently abled person to live independently “by promoting measures for their protection measures for their protection in case of death of parents, evolving procedures for appointment of guardians and trustees and facilitating equal opportunities in society.” Besides these provisions The Rights of Persons with Disability Act, 2016 was the measure passed by the GoI to achieve its responsibility to the United Nations Convention on the Rights of Persons with Disabilities. The Mental Health Act, 2017 furthermore grants every mentally ill person the right to avail hood quality healthcare services, which are accessible, convenient, and affordable. This act also safeguards said persons from inhuman treatment and gives them free access to legal services and their medical records.

29.4.1 Existing smart India initiatives The Government of India initiated its Digital India program on July 1, 2015 with a vision to transform India into a digitally empowered society and knowledge economy. This program was a multifaceted project, which under its banner initiated various programs such as SCM launched on June 25, 2015 under the Union Ministry of Urban Development as well as the Accessible India Campaign under the Department of Empowerment of Persons with Disabilities of Ministry of Social Justice and Empowerment. The SCM was launched to ensure the inclusion and participation of all groups of citizens in the country in the new developments, hence ensuring that the needs of the special section of the population are met. This mission also works to bring together campaigns like Digital India under its umbrella. Technology nowadays is deeply rooted in the blend of design, electronics, and computer science. The Ministry of Electronics and Information Technology (MietY), following the same line of thought had released a Technical Report on Design and Planning Smart Cities with IoT/ICT. The report explores how “ICT deployment in smart cities in India lies within a broader context of institutional, physical, social and environmental factors amidst the complex needs of managing rapid urbanization, while ensuring QoL and economic opportunities for all citizens” [34]. Another feature to note is that people with disabilities that affect their mobility, vision, hearing and cognitive functions often move to cities to take advantage of its transit system, healthcare facilities and social services. These reports however paint a contrasting story, giving an insight into the making of a “smart city” but not specify how municipalities should design and implement digital services for specially abled people. “As a result, the cities sometimes adopt new technologies that end up causing problems of accessibility rather than solving it” [35]. The city of Kolkata illustrates this point very well. The city has a large slum population, which amounts to around 31% of the total population; their presence is mostly concentrated in central and north-eastern parts of the city [36]. So far the metropolitan city has seen various developmental schemes and plans to guide its development as an inclusive smart city in terms of Governance, Sustainability,

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Sustainable Urban Economy, Sustainable Resource Management, Safety and Resilience, and Urban Mobility under both national and state regimes. Yet, Kolkata is still far from being an inclusive city. While there has been progress in terms of IT, housing, and physical infrastructure to some extent, issues such as unregulated built-up growth, safety, restricted spatial mobility, unsafe public spaces, and exclusionary social practices against certain sections of the society still prevails [36]. The SCM likewise, also directly talks about promoting active participation of the communities. In the recent chain of events, it can however be observed that these smart-city initiatives have been forwarded to corporate houses. The Finance Minister of GoI, Nirmala Sitharaman was recently quoted saying, “India plans to invite multinational corporations to participate in various upcoming Greenfield and brownfield projects” [37]. The question that arises at this junction is “how does the government plan to make these cities inclusive?” Various corporate firms like Intel, Mckinsey, KPMG, etc. do talk about India’s growth under the smart-city regime. Yet this often sidelines the role local businesses can play owing to their extensive knowledge of the needs and demands of citizens at the regional level. The tendency to turn toward the corporate not only increases the discrepancy of intended benefits among the citizens but also widens the gap between what is expected out of the government and what it delivers. As a result, there is primarily a difference between what the government envisioned and what firms execute. This is related to the second point, as international or private firms often employ single use technology, which does not sit well with India’s unique and vast landscape where every city has its own unique requirements. Thirdly, most technological advancements or technology-based solutions are “force-fitted” by technology firms by negotiating with implementing authorities. This form of city development enhances a technocratic model of governance where corporate interests are upheld at the cost of citizen’s right to their city [38]. This phenomenon, as argued by Datta in his study creates “new urban colonialism,” which he illustrates through the example of that Dholera smart city in India. This smart city relies mostly on the technocratic model of governance, which caters to and is shaped by corporate interests [39]. The Government of Delhi, realizing the need to take small steps has initiated ways to increase engagement of differently abled people in the process of building a smart city. The Delhi government has taken steps such as the buildings of ramps, railings, and accessible washrooms, ramps in Delhi Transport Corporation (DTC) buses and support systems in the Delhi metro that have trained staff to assist the physically challenged. Other measures include installation of Braille systems in the elevators and modification of toilets for wheelchair users [8]. All these initiatives by the Delhi government however, are still limited to infrastructure and design aimed to improve the physical mobility among the DAC. The only exception is the government’s doorstep service delivery of government services like license, domicile and so on. The potential that the use of ICT offers to make the city as a whole more inclusive still remains untapped. The city of Varanasi under SCM in 2015 was similarly selected by the Ministry of Housing and Urban Affairs, GoI to be one of 100 cities under Phase 1 of the program. Following it, was Phase 2 of the program under which the city was selected

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to be one of the top 20 smart cities. The Mission was to enable the process to bring about a “Smart Kashi,” which was to be based on 6 pillars according to the proposal submitted to the government in the second phase of the mission. These were: Suramya (picturesque), Smmunat (improved), Nirmal (pure), Sanyojit (planned), Surakshit (safe), and Ekatrit (integrated) [40]. The project aimed at launching a process that enables the city to maintain its religious and heritage essence of the city along with efforts that would make the city cleaner; while on the other hand provide mobility for all, in the meantime utilizing ICT for the promotion of local entrepreneurship and smart services. In addition to this, the pan-city development highlights the interventions in the sector of urban mobility and E-governance. It also introduces several features like e-Kashi app, smart card, community engagement portals, digital wallet, e-bookings, and so on [41]. The SCM in Varanasi also plans to bring in a number of technological advancements like data centers, interoperable command and control centers, surveillance and traffic cameras, traffic control systems, and e-challans. In addition to these, facilities such as tracking of vehicles and bins for SWM, environment sensors; multilevel integrated parking; automated centrally regulated street lighting; e-governance integrated with portal and mobile app shall also be introduced. With regards to the redevelopment of old buildings and structures, the project primarily focuses on available individual plots, major roads are being redesigned within the existing “right of way” without any width extension and no demolition of adjacent properties [42]. The mission with its notion of inclusiveness and convergence, however, fails to integrate disability as a key issue in the smart-city proposal. In December 2015, the Prime Minister of India launched the Accessible India Campaign (AIC) for making India accessible for people with disabilities. Yet only after a year of its launch, the campaign seems like an isolated campaign of the Ministry of Social Justice and Empowerment (MSJE) with a very limited vision of making “x” number of buildings and websites accessible. Moreover, there has been little to no action to explicitly integrate accessibility in other campaigns and programs, like Swachh Bharat or Smart Cities Mission. The core infrastructure elements in a smart city still do not include accessibility for persons with disabilities [43]. While the projects have been subjected to repair, remodeling, and betterment of the spaces yet, there is no way to assess how friendly or accessible these measures are for the DAC within the country. Transport services, especially public ones such as buses do not have a provision for people who are above 60 years old or are differently abled. Further, this sector has no provisions for persons with disabilities for the diverse services it offers under various categories like skill development centers, smart bus shelters, heritage walks and so on [41]. The pan-city development highlights interventions in the sector of Urban Mobility and E-governance by introducing features like eKashi app, smart card, community engagement portals, digital wallet, e-bookings, etc. These however fail to integrate the aspects of accessibility, especially the digital inclusion of persons with disabilities and the elderly [43]. The proposal thus

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caters to some specially abled friendly interventions related to mobility but completely neglects the accessibility features for ICT-driven solutions [41]. While there have been amendments being made for inclusion to invite people from each and every class of the society by maintaining, reconstructing and remodeling the city, there have however been no provisions made for citizens with limited mobility—physical, visual, and hearing.

29.5

Proposed conceptual model of an inclusive smart city

The way governance was approached is being overhauled year by year by incorporating new advances in technology. This is especially true for specific policy and governance decisions regarding the DAC. The proposed model works on a collaborative and interdepartmental platform as it is a multilayer, multistakeholder model. The main objectives of the proposed conceptual model are: 1. To harness the available voluntary and involuntary data available to various stakeholders including government agencies, and other responsible actors. 2. To develop a control and command center that uses appropriate technology available for analysis. 3. Evolve support and intervention system for the DAC using the analysis and recommendations of the C&C center.

The preceding objectives give form to the basic design of the proposed model; irrespective of the number of layers or building blocks in each of these layers, the underlying system design principle weaving all of them remains the same. The proposed conceptual model (see Fig. 29.1) requires the collection of sensory data using IoT from public spaces as well as data being created by target specific applications in smart phones and wearable devices. The big data created from this network can then be stored in a cloud-based database management system, conventional databases, or Fog computing. This makes this data accessible to multiple stakeholders, especially the municipality of the urban space, which can use a command and control center to extract relevant data using AI tools, Big Data analytics, etc. This data can be analyzed to extract important insights needed for answering relevant questions. This relevant data can be visualized in the form of verticals, presented in layers using technologies such as GIS (geographic information systems) to be used for behavior analysis, risk detection, and prompt emergency response and intervention. For the creation of an effective network to collect, collate, and deliver data, it is necessary to have a hardware layer (sensors, smart phones, IoT devices, routers for communication, fiber, etc.), software layer, or middleware architecture (data storage, interface, application layer, etc.). It is the basis of the ability to connect a vast number of sensors and facilitate data delivery within the city. This will primarily

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Figure 29.1 Reference model for inclusive smart cities (developed by Aniket Basu and Charru Malhotra).

work to capture data produced by users, store it, process it, and make it available to be extracted. This contributes to a system that is using real-time data. It analyses the past and real-time data sets, which result in a predictive and need based governance model. Hence decision support systems that employ quantitative data superimposed on qualitative data based on citizen classification and local needs leads to a better understanding of the immediate and local needs. This results in not only the predictive measures but also a shorter response time in times of emergency. The analysis also sheds light on the areas needing intervention and attention in terms of assistance in day-to-day activities and services being provided to the DAC. Hence, the model works on evidence-based intervention model.

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29.5.1 Implementation of the proposed conceptual model As previously explained, the proposed conceptual model (see Fig. 29.1) requires the collection of sensory data, by using IoT from public spaces as well as data being created by target specific applications in smart phones and wearable devices. The conceptual model is composed of the following four blocks: G

G

G

G

Data capture block Data storage block Data analytics block Data-based decision block.

29.5.2 Data capture block As illustrated in the first block (see Fig. 29.1), the first and the foremost step for the implementation of the proposed conceptual model is the collection of voluntary and involuntary data [44]. For the collection of the same, smart wearable devices and smart phones can be used for capturing of voluntary data along with IoT sensors in the metropolitan environment for the capturing of involuntary data (using AI and facial recognition-based surveillance deployed through, drones, surveillance cameras, sensors in waste composition, pollution, etc.). The overall task of this data-capturing platform is the unobtrusive collection of raw data from heterogeneous sensing infrastructure. In order to realize this in a smart city, it is imperative to have an expansive access to fiber throughout the city including in buildings and open spaces so as to utilize IoT and 5G technologies. This will allow actors in a smart city to transmit information in different formats and according to different standards in real time. It is important to note the multitude of variation and purposes for which sensors are available in the market, hence it becomes important for the city to establish a consistent strategy for standards and protocols to maintain uniform data and smooth communication. Currently, different public service providers in the city are used to working in isolation and are departmentalized. Smart cities require a high level of interoperability so as to also enable data sharing with other stakeholders.

29.5.3 Data storage block This block illustrates the creation and maintenance of a data platform that can be cloud based or be operated and managed by the city. In the age of the IoT and AI, where devices are generating more data than ever before, deciding how to properly store all this data has become a critical consideration. The model proposes a data center, which can be cloud based, fog computing based, or conventional data centers. Looking at the fast-paced advancement data storage, it is not difficult to conclude that conventional data storage systems are no ideal for storing a continuous stream of data an entire city. Hence cloud-based/Fog-based systems are recommended so that there is access to the information stored in database without delays,

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it is cost effective, it offers scalability, and is the best option available to the larger organizations and companies who need to hold terabytes of data [45]. It is vital that the city be clear as to who owns the data as there can be potential privacy concerns that may rise from the same, as the city does not have a control over the location of data storage, it is imperative that it take precautionary measures to secure its data. At the same time online data storage assists in the smart cities responsibility to ensure that the cities stakeholders and citizens have access to the data thus creating an integrated data storage solution.

29.5.4 Data analytics block The third layer is the application layer that uses processes and derives value from the data generated. The data platform will be an expansive collection of Big Data. With the use of AI tools, machine learning, Big Data analytics, and information systems like GIS, the available data can be analyzed to find relevant answers. The smart city may choose to limit itself here and ensure access of different players including private actors for developing applications and act as a facilitator and follow a collaboration-based model. This layer translates into digital profiles; it is a means in which we can analyze and piece together a person’s interaction with this digital data network, add geographically relevant sensory data and produce the outputs of profiling, trend as well as behavioral analysis and apply all this data to the digital profile. This can be at a personal level, street level, locality level, or at the citywide level. This data can be collated into a centralized database for the DAC enabling specialized monitoring and response.

29.5.5 Data-based decision block Block 4 firstly comprises of the command and control center, where the relevant output from the application layer including the digital profile is reflected and a multidimensional assessment team can evaluate the possible interventions. Secondly, the relevant output is also set collated and can be used for predictive decision-making and initiating policy changes. The command and control center is supported by decision support algorithms employing quantitative data superimposed on qualitative understanding of local context, which aids in undertaking risk assessment and behavioral analysis. This control center is also responsible for forwarding relevant information to concerned stakeholders for preventive action as well as reducing emergency response time. The centralized database for the DAC will play a key role in facilitating the interventions as well as creating target group focused schemes. If intervention is seen to be critical and finalized then supporting response is initiated, if not then the data is anonymized and sent back to the data repository (Block 2). This step containing the human factor helps in keeping only necessary data, minimizing the risk of data leaks, and ensures privacy is not breached. If intervention is deemed fit, then the same is communicated to the relevant civic authority

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to take action. Keeping in mind the need for a mobile platform for facilitating these interventions as well as aiding the target group of citizens in critical response time, there is also a need for a network of mobile vans stationed at major interjections of the city as well as areas with a higher density of the target population, that is, differently abled and the elderly. This will not only shorten the response time for critical interventions, but will also allow multiple independent stakeholders in the city to facilitate services through these vans. The importance of a mobile kiosk able to reach citizens who are challenged with mobility and cannot travel to avail services and programs meant for them, may be the last straw to make the proposed smart city a responsive, inclusive smart city. This data-based decision block in the long term also provides a detailed insight into the critical behavioral patterns as well as general factors that can be used to improve service delivery and assistance to the DAC. While the same data can be used to develop new interventions both long term as well as short term in the form of policy changes, target group focused schemes, and evidence-based infrastructural changes. While drawing from this information, new applications that assist them in their day-to-day needs like health, cognitive abilities, nutrition, safety, localization of services, socialization, mobility, communication, etc. are also a possibility to be encouraged [46]. The overall outcome of these blocks can be said to be working in the direction of achieving the 3As, availability, adaptability, affordability. The interventions needed for general public sensitization toward the DAC can also be addressed using the learning’s from the processed data at this stage.

29.6

Recommendations

This section of the chapter proposes various recommendations and a way forward in order to overcome the limitations and challenges various stakeholders and policymakers face today when designing an Inclusive smart city. These recommendations broadly cover issues such as—implementation of existing initiatives by the GoI India, citing the likes of StartUp India, the factors that are important when making any new policy, that is, implementation of the 3As, using real-time apps, introduction of new features like—smart vans, visual, hearing and cognitive centric ICT solutions, and restructuring public infrastructure.

29.6.1 Initiatives taken by the Government of India The idea of more inclusive and accessible smart cities has taken some root in India; the state at the initial glance is becoming more sensitive to the needs of a fairly large section of our society. The Person with Disabilities Act was amended in 2016 to broaden its scope and reach. Similarly, the Accessible India campaign was launched with the aim of promoting more specially abled friendly buildings and resources policies. Over 1707 buildings were identified with the help of auditors across 57 Indian cities to be made more accessible as part of this campaign. Section 44 of the Persons with Disabilities Act, calls for these buildings to be fitted

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with ramps for greater access. Modification of toilets to more wheelchair friendly as well as installation of Braille symbols in elevators; the progress regarding these has however been lethargic at best. The Finance Ministry, GoI India in May this year made it necessary for all new projects to include accessibility costing in the total project cost proposals sent for approval. The national program to make public infrastructure more accessible and specially abled people friendly was to be halfway complete by July 2018, but according to the DEPwD only 3% of public buildings in the country have become fully accessible [8]. The public transport and roads in the country are also infamous for creating access barriers and being just plain hostile for the specially abled. The center’s target for making over 25% of the public transport specially abled accessible is however yet to be met [8].

29.6.2 Study of 3As In order to make smart cities inclusive, it is necessary for any state to demand stemming from the problems faced by its citizens into consideration. For that purpose, a study of the 3As is thus proposed, which facilitates an analysis of the problems and setbacks faced at the citizen level. Such hurdles can be eliminated via changes in implementation of policies and measures at the grass root level. This includes aspects of the 3As.

29.6.3 Accessibility Inclusivity is “for the people”; in a large and diverse country like India where the population is sizable, the issue of last mile connectivity stands as the first hurdle in the process of development. While a state may implement new frameworks and strategies there is still a need to focus on the impact that these measures have at the grassroots level as well.

29.6.4 Adaptability More emphasis should be levied on the citizen awareness and their capability to adapt to new changes. Policy and change makers need the support of the masses to bring new changes and developments as desired by the citizens. It is thus essential, to make systems that go through proper live processes in order to understand issues and challenges from top to bottom perspective, allowing the ecosystem to adapt to newer technologies.

29.6.5 Affordability—high Capex and Opex New policies and changes require more than just planning. An in-depth analysis of the expenditure in terms of the priority need and budget is required. Generally, in developing countries like India a lot of amount is spent only on investment without any said or less outcome possible [10].

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It is imperative that we recognize that the problem of inaccessibility and inclusivity today is not just about being a social duty but is a constitutional right for people. The lack of access to various facilities, deny a significant section of the population, various basic rights guaranteed to the citizens of India by the Indian Constitution. The government’s SCM thus offers a good opportunity to ensure inclusion and participation of persons with disabilities in the workplace, neighborhood activities and in social life. Beyond displaying its political will to create specially abled friendly buildings, the government will now have to hold the stakeholders culpable [47]. They will have to ensure that the targets charted at the offset of any policy implementation process are delivered. Hence, ensuring the QoL standards and the overall happiness index. There are numerous possible ways to achieve the aforementioned, for instance, accessible pedestrian signals can be one way of making the city more embracing toward needs of a specially abled person. This integrated audio device sends audio signals to facilitate safe, quick, and timely crossing of roads for people with disabilities, especially the ones with any kind of visual impairment [47].

29.6.6 Objective of inclusive smart cities Inspired by the Literature Review [48], these inclusive smart cities should delineate the following objectives—ensuring access to pathways, junctions, footpaths, bus shelters, crossings, and public transportation; creating accessible websites, applications, government portals, and community engagement platforms; create accessible digital technology for websites, mobile applications, products, and services; and design accessible buildings, parks, playgrounds, schools, colleges, hospitals, recreational areas, public toilets, and so on.

29.6.7 Use of real-time apps—SeenAb In terms of making these smart cities accessible and more citizen friendly, there is a need to address issues, which may or may not seem inconsequential. For example, in a case study conducted by ethnographic researchers Arnab Bose and Seema Sharma issues like height of the bus, wheelchair access ramp being blocked by advertisement boards, cross roads not having foot over bridges and even if they do it does not have elevators or ramps. In order to deal with these Bose and Sharma designed a community APP—SeenAb—through which they collect real-time data based on structured questionnaires on various issues faced by specially abled persons in the neighborhood while accessing public infrastructure [48]. The aim is to collect and analyze that data in order to prioritize the requirements of the government’s funding. Moreover, it shall also help product manufacturer companies and services to customize products for requirements of the DAC.

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29.6.8 Collaboration of Smart-City Mission and Startup India Another, major step could be alignment of smart-city initiative with the Startup India Initiative. Rather inviting global private players, the state should encourage local startup initiatives as these have a better chance of understanding the regional situations and demands as compared to private international companies. Cities identified under the “Accessible India” campaign can open and involve startups, which have specialization in ethnographic thinking, social awareness and empathy, thus, making a difference in the “inclusive smart city.”

29.6.9 Smart vans The popular measures surrounding the accessibility for persons with disability have been largely centered on the physical or mobility aspects in their environment such as ramps, disable friendly toilets, etc. but there has been hardly any focus on making various digital and ICT-driven services which are equally important to persons with disability [49]. Smart vans, those are equipped to be capable of providing emergency medical aid as well as delivering services and utilities at the doorstep of both the DAC that face mobility challenges. These smart vans can be stationed at crossroads throughout the city or at certain marked points near neighborhoods with a sizable target population (DAC). As part of India’s Smart City Challenge, the SCM has identified 24 key features that a city needs to have (see Fig. 29.2).

29.6.10 Visual, hearing, and cognitive ICT-based solutions Various ICT-based solutions if implemented in the cities can be of immense help to the DAC, addressing different problems in terms of—visual, hearing, and cognitive abilities. These can include initiatives such as—audible and vibro-tactile signals for pedestrian augmented with systems able to inform people with visual and hearing imparity their location, accessible shopping for visually impaired people through mobile technologies, navigation system, a product recognition system as well as assisted city apps adapted to visually challenged users. For people with hearing obstacles—speech to text machines can be quite useful, and can also be used to convert and reproduce sign language. For other problems in terms of navigation being faced, wristbands or devices can be created which can guide the DAC through their everyday tasks [46]. The GoI through various programs has taken initiatives to make the digital world more accessible to people with disability, these include “National Policy on Universal Electronic Accessibility” 2013 as well as the new amendment in the 2016 which calls for “all content available in audio, print and electronic media to be in an accessible format; electronic goods and equipment that are meant for everyday use to be made available in universal design and ensuring access to television programmes with sign language interpretation or subtitles. Additionally, all service

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Features of a smart city Sanitation Underground electric wiring Housing and inclusiveness Transportation and mobility Energy efficiency Air quality Water quality Waste water management Water supply Energy source Energy supply Intelligent government services IT connectivity Walkable Open spaces Compactness Mixed use Education Health Economy and employment Identity and culture

Figure 29.2 Features of a smart city.

providers whether government or private will have to provide accessible services within a period of two years from the notification of the law” [49]. The ground realities for all these initiatives however leave a lot to be desired. These measures instead of improving the QoL, have instead worked toward further marginalizing this community from the advances in the digital world and using them to their advantage. The digital inclusion as a whole will not only work to benefit persons with disabilities, but also for the elderly people and people with limited language skills. These services are also important because they allow this section of the society to have a much-needed sense of independence, autonomy, and safety.

29.6.11 Public infrastructure Lastly, policymakers must plan effectively and commence by creating public infrastructure to promote bottom-up interventions, wherein they take an active role in building the ecosystem [38]. This approach includes the creation of an accessibility cell within the said SCM under the Ministry of Urban Development, along with a core group/committee of experts on the need of DAC people to monitor the developments. The next step should involve the creation of a knowledge center, which would entail focusing a shift toward accessibility of information, by involving

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communities and groups. Steps should also be taken to provide awareness and training at different levels on making spaces friendlier for DAC, especially to the architects, IT officials, auditors etc. Furthermore, people could be hired and trained toward realizing the sensitivity of the issue and enable them to participate at the grassroots level by providing assistance at major spots in the cities to DAC. There is also a need to shift the focus toward enabling policies for citizen-led interventions, which enable the city to be inclusive to all its citizens. As discussed earlier, different policies could be recombined such as Make in India and SCM. In light of what SeenAb has done, the government can also support regional hubs and apps to encourage innovative ideas and develop them as ventures. Finally, smart cities should not be an exclusive space for people who are protechnology/tech-savvy, but should involve one’s own surroundings and environment inclusive of all for a better, sustainable future. Smart city in its truest sense does not mean to have a strong leader to dictate but rather entails having citizens who are aware and informed enough to ask for their rights, seek redressal of their grievances, and ultimately have them addressed. This can only be made possible by eliminating barriers that have currently resulted in arbitrary exclusion of CAD, from active participation in social and day-to-day spaces in urban spaces.

29.7

Summary

In this chapter, we tried to understand the concept of “smart cities” and how it is more than just a change in the infrastructural designing. In order to make a city more advanced there is a need for technological advancements, which are inclusive to all of its citizens. The study unfolded itself in parts, wherein we first understood the process of rapid urbanization which has given birth to various issues of affordability, availability, and adaptability of the resources in the city in terms of housing, sanitation, employment, health services, and other utilities and services. All of these demands are met by the government, with the help of making the city more inclusive to its citizens, and in order to do that, the state/government uses means such as new policies and technologies. One such policy is the SCM taken up by the Indian government. While the mission has been dedicatedly working toward making the city smart, it is lacking in terms of “inclusivity,” which in turn may be termed as its biggest drawback. The chapter also looks upon various best global practices that have been adapted around the world to make smart cities more inclusive. To understand the inclusivity of a smart city, the chapter relies on the 3A parameter, which are availability, affordability, and adaptability. Based on the aforementioned, various issues and challenges were then brought to light and similarly, a way forward was then provided with. The way forward provides various lucrative possible policies and examples of cases wherein inclusivity is being practiced in a successful way. The focus needs to shift more on the adaptability part, as the sections we are talking about for the city to be inclusive of the DAC. The aim is to make them independent by providing

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them best possible services to make the cities more adaptable. Services like setting up Accessibility Cell along with a core group/committee of experts on the need of DAC. Create knowledge centers provide awareness and training at different levels on making spaces friendlier for elderly and specially abled people especially to the architects, IT officials, auditors, etc. Apart from it, changes like introduction of sign language boards can also be quite beneficial for people with limited speech and hearing problems. At the end, we understand the need of a smart and inclusive city wherein everyone’s grievances are heard and acted upon, thus, upholding QoL standards and ensuring everyone’s right to life and equality. Finally, let us move on to the real interactive part of this chapter: review questions/exercises, hands-on projects, case projects, and optional team case project. The answers and/or solutions by chapter can be found in Appendix G.

29.8

Chapter review questions/exercises

29.8.1 True/false 1. True or false? The SCM emphasizes that smart cities are those that provide core infrastructure and give decent QoL to its citizens, a clean sustainable environment, and an application of “smart” solutions. 2. True or false? According to the United Nations (2014), over 70% of the world would be living in urban centers by the year 2040, and this number is expected to expand to over two-thirds by the year 2060. 3. True or false? While increasing citizen participation and engagement are important factors, it is also important to recognize that challenges faced by the DAC are not homogenous. 4. True or false? The Global Initiative for Inclusive JDUs (H4JDU) and World Enabled in 2016, launched the ‘Smart Cities for All’ initiative, with the objective of underlining the unprecedented opportunities that inclusive technology will create in the future for cities. 5. True or false? Through the years, the GoI has launched various schemes and policies for DAC, in order to promote their health, well-being, and independence around India.

29.8.2 Multiple choice 1. Technology nowadays is deeply rooted in the blend of design, electronics, and: a. IoT/ICT b. Governance c. Computer science d. ICT e. Sustainability 2. The way governance was approached is being overhauled year by year by incorporating new advances in: a. Health b. Safety c. Technology d. Economy e. All of the above

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3. The proposed conceptual model requires the collection of sensory data, by using IoT from public spaces as well as data being created by target specific applications in smart phones and: a. Wearable devices b. 5G technologies c. Stakeholders d. Autonomous systems e. Transport sharing 4. What block illustrates the creation and maintenance of a data platform that can be cloud based or be operated and managed by the city? a. Data storage block b. Data capture block c. Data analytics block d. Data-based decision block e. All of the above 5. What block is the application layer that uses processes and derives value from the data generated? a. Data analytics block b. Data storage block c. Data capture block d. Data-based decision block e. Data backup block

29.8.3 Exercise 29.8.3.1 Problem What is known as integrated approach encompassing sustainable, resilient, accessible, and affordable solutions, to the challenges faced by the urban poor and vulnerable groups, by enhancing their access to urban services and infrastructure through targeted investments?

29.8.4 Hands-on projects 29.8.4.1 Project Do research: How can the current process of designing smart urban equipment be improved?

29.8.5 Case projects 29.8.5.1 Problem What is needed to eradicate social inequities in smart urban design?

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29.8.6 Optional team case project 29.8.6.1 Problem How can digital solutions advance, rather than impede, inclusive smart urban design?

References [1] United Nations, Sustainable Development Goals, United Nations, 2012. [2] J. Abidi, Building inclusive and accessible cities the opportunities now. ,https://www. uclg.org/sites/default/files/inclusive_accessible_cities_policypaper.pdf., November 15, 2019. [3] United Nations, World Urbanization Prospects 2014, United Nations, New York, 2014. [4] Census of India. Retrieved from mospi.nic.in: ,http://mospi.nic.in/sites/default/files/ publication_reports/Disabled_persons_in_India_2016.pdf., 2016. [5] United Nations Population Fund, Caring for Our Elders: Early Responses - India Ageing Report, United Nations Population Fund, New Delhi, 2017. [6] What is Smart City. Retrieved from: ,http://smartcities.gov.in/upload/uploadfiles/files/ What%20is%20Smart%20City.pdf., 2016. [7] Ministry of Housing and Urban Affairs. What is smart city? Smart Cities Mission, Government of India. Retrieved from: ,http://mohua.gov.in/cms/smart-cities.php., May 4, 2017. [8] A. Sharma, Our cities cannot be smart, until they are accessible for everybody. Retrieved from hindustaantimes.com: ,https://www.hindustantimes.com/analysis/our-cities-cannot-besmart-until-they-are-accessible-for-everybody/story-RXiPRhqmFG4wHj59UrS6qO.html., October 23, 2018. [9] Technology for sustainable and inclusive growth is the need of the hour, says President. Retrieved from: ,https://pib.gov.in/newsite/PrintRelease.aspx?relid 5 161713., March 26, 2019. [10] V. Albino, U. Berardi, R.M. Dangelico, Smart cities: definitions, dimensions, performance, and initiatives, J Urban Technol. 22 (1) (2015) 3 21. [11] M. Cavada, D. V. Hunt, C. D. Rogers, Smart cities: contradicting definitions and unclear measures, in: World Sustainability Forum. MDPI AG, November 2014, pp. 1 12. [12] H. Chourabi, T. Nam, S. Walker, J. R. Gil-Garcia, S. Mellouli, K. Nahon, et al. Understanding smart cities: an integrative framework, in: 2012 45th Hawaii International Conference on System Sciences. IEEE, January 2012, pp. 2289 2297. [13] S. Alawadhi, A. Aldama-Nalda, H. Chourabi, J. R. Gil-Garcia, S. Leung, S. Mellouli, et al. Building understanding of smart city initiatives, in: International Conference on Electronic Government. Springer, Berlin, Heidelberg, September 2012, pp. 40 53. [14] A. Caragliu, C. B. Del, P. Nijkamp, Smart cities in Europe, in: Proceedings of the 3rd Central European Conference in Regional Science CERS, 2009, pp. 49 59. Retrieved from: ,https://www.scirp.org/(S(351jmbntvnsjt1aadkposzje))/reference/References Papers.aspx?ReferenceID 5 1239981.. [15] R.G. Hollands, Will the real smart city please stand up? Intelligent, progressive or entrepreneurial? City 12 (3) (2008) 303 320.

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[16] C. Harrison, B. Eckman, R. Hamilton, P. Hartswick, J. Kalagnanam, J. Paraszczak, et al., Foundations for smarter cities, IBM J Res Develop 54 (4) (2010) 1 16. [17] V.S. Pineda, What makes a city accessible and inclusive? in: V.S. Pineda (Ed.), Building the Inclusive City, Palgrave Macmillan, Berkeley, California, 2019, p. 50. Available from: https://doi.org/10.1007/978-3-030-32988-4. [18] M. F. Story, J. L. Mueller, R. L. Mace, The universal design file: designing for people of all ages and abilities (1998). [19] The Goals and Benefits of Universal Design. Retrieved from: ,http://www.buffalo. edu/access/help-and-support/topic3.html., 2019 (accessed 08.03.19). [20] S. Vashi, J. Ram, J. Modi, S. Verma, C. Prakash, Internet of Things (IoT): a vision, architectural elements, and security issues, in: 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE, February 2017, pp. 492 496. [21] Internet of Things: New Promises for Persons with Disabilities. Retrieved on 03.02.20, July. From g3ict.org: ,https://g3ict.org/upload/publication/internet-of-things-newpromises-for-persons-with-disabilities/IoT_new-promises-for-PWD.pdf., December 3, 2015. [22] Artificial Intelligence. Retrieved from: ,https://www.merriam-webster.com/dictionary/ artificial.intelligence., February 14, 2018. [23] S. Soomro, M. H. Miraz, A. Prasanth, M. Abdullah, Artificial intelligence enabled IoT: traffic congestion reduction in smart cities (2018). [24] Assistive devices and technologies. Retrieved from: ,https://www.who.int/disabilities/ technology/en/., 2017. [25] Role of AI, IoT and Blockchain in a Smart City. Retrieved from: ,https://www.infosysblogs.com/blockchain/2019/05/role_of_ai_iot_and_blockchain_.html., May, 2019. [26] J.S. de Oliveira Neto, S. T. Kofuji, Inclusive smart city: expanding design possibilities for persons with disabilities in the urban space, in: 2016 IEEE International Symposium on Consumer Electronics (ISCE). IEEE, September 2016, pp. 59 60. [27] UNCRPD, Convention on the rights of persons with disabilities, G.A. Res. 61/106. The text is available at: ,https://www.un.org/disabilities/documents/convention/convoptprot-e.pdf., January 24, 2007. [28] Engagement. Retrieved from: ,https://tcat.cs.washington.edu/activities/., January 1, 2019. [29] K. Barett, Alexandria, VA joins growing list of dementia-friendly cities, Alexandria, Virginia, USA. Retrieved from: ,https://www.smartcitiesdive.com/news/alexandria-vajoins-growing-list-of-dementia-friendly-cities/., August 5, 2019. [30] City4Age. City4Age. Retrieved from city4ageproject: ,http://www.city4ageproject.eu/., December, 2015. [31] S. Salman, Smart cities library. Retrieved 28.12.19 from smartcitieslibrary.com: ,https://www.smartcitieslibrary.com/what-would-a-truly-specially-abled-accessiblesmart-city-look-like/., 2018, (accessed 14.02.18). [32] The Global Initiative for Inclusive Information and Communication Technologies. The global initiative for inclusive information and communication technologies. Retrieved from g3ict.org: ,https://g3ict.org/news-releases/smart-cities-for-all-launches-projectto-define-more-inclusive-approach-to-innovation-for-smarter-cities., 2018 (accessed 19.08.18). [33] SmartCities World. Smart cities world. Retrieved 28.12.19 from samrtcitiesworld.net: ,https://www.smartcitiesworld.net/news/news/creating-inclusive-smart-cities-3367., September 19, 2018.

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[34] Telecommunication Engineering Centre, Department of Telecommunications. IoT/ICT enablement in smart cities design and planning smart cities with IoT/ICT, Ministry of Communications, Government of India (2019). [35] The Global Initiative for Inclusive ICTs. Smart cities must be accessible for persons with disabilities. Retrieved from g3ict.org: ,https://g3ict.org/headlines/smart-citiesmust-be-accessible-for-persons-with-disabilities., January 9, 2019. [36] I. Haque, S. Mehta, A. Kumar, Towards sustainable and inclusive cities: the case of Kolkata, ORF Special Report, Observer Research Foundation. Retrieved from: ,https://www.orfonline.org/research/towards-sustainable-and-inclusive-cities-the-caseof-kolkata-48992/., March 14, 2019. [37] Economic Times, India Times. Sitharaman invites Swedish businesses to build smart cities in India. Retrieved from ET Government: ,https://government.economictimes. indiatimes.com/news/smart-infra/sitharaman-invites-swedish-businesses-to-build-smartcities-in-india/72358448., 2019 (accessed 04.12.19). [38] R. K. Kummitha, What do our cities need to become inclusive smart cities?, Economic and Political Weekly Engage. Retrieved from: ,https://www.epw.in/node/154076/ pdf., March 29, 2019. [39] A. Datta, New urban utopias of postcolonial India: entrepreneurial urbanization in Dholera smart city, Gujarat, Dialogue in Human Geography. Retrieved from: ,https:// journals.sagepub.com/doi/abs/10.1177/2043820614565748., 2015. [40] Varanasi Municipal Corporation, Government of India. Proposal for the Indian smart cities challenge phase-II, Varanasi Municipal Corporation. Retrieved from: ,http:// smartcities.gov.in/upload/uploadfiles/files/Varanasi_SCP.pdf., July 11, 2016. [41] National Centre for Promotion of Employment for Specially-abled People. Varanasi smart city proposal analysis. Retrieved from ncpedp.org: ,https://www.ncpedp.org/ varanasi., March 11, 2019. [42] Financial Express. Varanasi smart city project: how PM Modi’s constituency is being transformed in a ‘unique’ way, New Delhi, New Delhi, India. Retrieved from: ,https://www.financialexpress.com/infrastructure/varanasi-smart-city-project-how-pmmodis-constituency-is-being-transformed-in-a-unique-way/1135889/., July 14, 2018. [43] FICCI, NCPEDP. Structural framework for accessible urban infrastructure in smart cities. Retrieved from: ,http://ficci.in/spdocument/22933/Smart_Cities%20new.pdf., August 9, 2017. [44] R. Mulero, A. Almeida, G. Azkune, P. Abril-Jime´nez, M.T. Waldmeyer, P.M. Castrillo, et al., An IoT-aware approach for elderly-friendly cities, IEEE Access (2018) 7941 7957. [45] S.B. Shende, P.P. Chapke, Cloud database management system (CDBMS), Compusoft 4 (1) (2015) 1462. [46] K. E. Skouby, A. Kivim¨aki, L. Haukipuro, P.Lynggaard, I. Windekilde, Smart cities and the ageing population, CMI center for Communication, Media and Information Technologies, Aalborg University Copenhagen, Denmark; International Business, University of Oulu, Finland; Center for Internet Excellence, University of Oulu, Finland, 2014. [47] K. Antony, Do not forget people with disability in smart city, Tiruchirapalli, Tamil Nadu, India. Retrieved from thehindu.com: ,https://www.thehindu.com/news/cities/ Tiruchirapalli/do-not-forget-people-with-disability-in-smart-city/article29975566.ece., November 14, 2019.

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[48] S. Dutta, S.K. Majumdar Working towards a specially-abled-friendly India, India. Retrieved from: ,https://www.thehindubusinessline.com/opinion/working-towards-adisabled-friendly-india/article25040700.ece., September 25, 2018. [49] D. Sharma, Why does mainstream Indian smart city discourse leave out disability and digital inclusion? Retrieved from: ,https://thewire.in/rights/mainstream-indian-discourse-digital-inclusion-leave-disability., May 9, 2017.

Appendix A: List of top smart cities and critical infrastructure implementation and deployment companies John R. Vacca

Organization

Description

URL

Navigant Consulting

Creates flexible transportation systems and new mobility options Creates UV powered glow in the dark road/pathway markings Provides a common data and content repository that connects systems that otherwise do not communicate; and, then provides an intelligent visual presentation layer that allows this information to be automatically delivered to any visual medium Assists clients with all phases of roads and highway projects, starting with planning and design and carrying through to operations and maintenance

http://www.navigant.com

Nevana Designs Omnivex Corporation

Parsons Transportation Group Pulse Larsen Antennas

Rostra Precision Controls SAFECHECKportal SenseOps, Inc.

Provides solutions that for antennas and RF technology; and, antennas covering 2G/3G/4G LTE, WLAN (Wi-Fi), Zigbee, Bluetooth, GPS/Glonass, Compass, ISM, VHF/UHF, NFC and custom applications Warns drivers of pedestrians’ activity or presence in and around the perimeter NHTSA danger zones Mobile human resource management tool Builds licenses and/or configures various software technologies to operate on edge devices and interoperates with larger cloud-based systems

http://www.nevanadesigns.com http://www.omnivex.com

https://www.dnb.com/businessdirectory/company-profiles. parsons_transportation_ group_inc.f5d5e7154ea 769d4.html https://www.pulselarsenantennas. com

https://www.summitracing.com/ search/brand/rostra-precisioncontrols http://www.safecheckportal.com/ http://www.senseops.com/

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Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

Strategic Innovation Partners LLC

Prepares internally for smart-city transition with particular focus on smart governance Anonymizes and aggregates runners and cyclists activities into a GIS format; and, partners with departments of transportation and planning groups to enable deep analyses of bicycling and pedestrian behavior, including activity counts by specific time of day and day of week across the entire network Delivers wireless experiences to millions of customers who are unwilling to compromise on quality and value Delivers actionable intelligence that drives and protects growth Provides government, utilities, and businesses with transportation demand management and electric vehicle program implementation and consulting services Monitors the fill levels and actual weights of all waste and recycling litter receptacles Helps cities not only TO aggregate and visualize real time data from parking garages and spaces, but then puts that data to work in a series of consumer facing applications that allow for better wayfinding Facilitates explicit permission-based data sharing between companies and consumers National distributor of Electric Vehicle Supply Equipment (EVSE) Provides secure broadband and intelligent infrastructure networks to a variety of industries Specializes in thermal printing solutions for transportation applications Provides a comprehensive suite of smartcity solutions that ranges from traffic management energy efficiency and smart healthcare to e-governance; intelligent lighting systems; and, home and building efficiency systems Technology partner with municipal public works departments

http://www.strategicinnovationpartners.com/

Strava Metro

T-Mobile US— Bellevue, WA Uptake Vermont Energy Investment Corporation Victor Stanley, Inc ZoomThru

Axon Vibe EV Charge Solutions eX2 Technology Microcom Corporation Mindteck, Inc.

MotionLink

http://www.metro.strava.com/

http://www.t-mobile.com/ http://www.uptake.com/ http://www.veic.org/

http://www.victorstanley.com http://www.zoomthru.co

http://www.axonvibe.com/ http://www.evchargesolutions. com/ http://www.ex2technology.com/ http://www.microcomcorp.com/ http://www.mindteck.com/

http://www.motionlink.com/

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665

(Continued) Organization

Description

URL

Organic Transit

Provides Urban Mobility Solutions: design, build, manufacture and solar hybrid designs Develops and manufactures parking guidance hardware and software systems with an integrated management reporting software and data analytics platform Connects to a network of video cameras, and analyzes pedestrian and vehicular movement, revealing hidden patterns and strategic opportunities Provider of full ITS solutions (parking, way finding, TMS) Rajant Kinetic Mesh technology enables municipalities to build private wireless networks to support the data, voice, and video demands driving smart-city communications initiatives Technology partner with over 600 transit agencies Moves passengers in a fast, safe, green, and economical manner Boosts infrastructure, increases investment, is sustainable, and improves the quality of life to meet the demands of the smart city Provider of cloud-based solutions that help improve government through democratizing access to data Provides program, project, and construction management services for large infrastructure projects nationwide Provides an ITS-based platform and related services to improve parking for commercial vehicles at governmentowned and private facilities on the highway network; as well as, at truck loading and unloading zones in urban centers 3D real-time LiDAR sensor provider Forecasts road trouble to reduce congestion, road accidents, and save lives FocusES on real-time, smart, and scalable modeling and optimization solutions; especially for sustainable multimodal transportation, smart cities, and Internet of Things (IoT), from basic research to industry transition and product development and support

http://www.organictransit.com/

Parking Sense USA

Placemeter

Q Free TCS Rajant Corporation

RouteMatch Software skyTran Smart Cities Summit Boston— Organized By Informa Socrata Triunity Engineering & Management, Inc. Truck Smart Parking Services, Inc. (TSPS)

Velodyne LiDAR way-CARe technologies ltd. WIOMAX LLC

http://www.parkingsenseusa. com/ http://www.placemeter.com/

http://www.qfree.com/ http://www.rajant.com/

http://www.rajant.com/ http://www.skytran.com/ http://www.smartcitiesevent.com/

http://www.socrata.com/ http://www.triunityeng.com/ http://www. trucksmartparkingservices.com/

http://www.velodynelidar.com/ http://www.waycare-smarthighway.com/ http://www.wiomax.com/

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Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

Bergkamp, Inc.

Pothole patching performance monitor and management system Manufacturer of electric buses

http://www.bergkampinc.com/

Utilizes a mobile phone application to dispatch rides using a fleet of fully electric low speed neighborhood electric vehicles Provides information, schedules, and payment portals; as well as, a portal for directions back to the parked car Provides the fabric for a modular solution set for smart transportation and smart cities Offers advanced electric vehicle fleet infrastructure and load management solutions; as well as, a global provider of open standards-based distributed energy resource solutions Delivers real time occupancy data to smart cities and its residents via a sensor Provides software development for Smart City IOT technology application development, using some of the industry’s highest quality certifications and standards, including CMMI Level 5, PCMM Level 5, ISO 27001:2013 and ISO 9001:2008 Provides EV charging stations, solar carports and pergolas, and LED lighting Provides data products for use in connected vehicle applications by utilizing existing public infrastructure and communication protocols Solves urban environment transportation, energy and water problems, with a systemic vision, a disruptive business model and developments that will revolutionize the way people are transported by using data, goods, water and energy Uses demand aggregation and real-time traffic information, to provide more efficient and accessible transportation; improve travel time reliability; and capture valuable data for future decision making

http://www.ridedowntowner. com/

BYD Heavy Industries Downtowner

EZR Mobile Glocol Networks Inc. Greenlots

Parkifi R Systems

Solar Power and Light Traffic Technology Services, Inc. ArqBravo Group

BRIDJ

http://www.byd.com/

http://www.ezrmobile.com/ http://www.glocol.com/ http://www.greenlots.com/

http://www.parkifi.com/ http://www.rsystems.com/

http://www.splsolar.com/ http://www.traffictechservices. com/ http://www.bravomotorcompany. com/

http://www.bridj.com/

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667

(Continued) Organization

Description

URL

Carmanah Technologies Corp. Cisco

Provides smart solar-powered LED traffic beacons and outdoor lighting

http://www.carmanah.com/

Securely connects disparate intelligent transportation systems to improve traffic flow, reduces roadside incidents, and provides a centralized view of highway systems Collects and analyzes millions of quantified self-data points throughout a city; develops proprietary wearable sensors and deploys them on multitudes of people every day; and then analyzes the data against existing geographic insights Creates Internet of Things enabled environments to bridge the gap between the digital and physical web Provides ITS master planning, scoping assessment studies, system definition analyses, agency coordination, ITS facilities design, and operations and maintenance, which are integral to the successful planning, development, and deployment of smart cities Looks at how technology can solve complex problems and enhance mobility in the world’s biggest smart cities Provides commuters and tourists a complete real-time snapshot of what their trip will be like and suggests the fastest, most comfortable routes; and how to ride public transit smarter around the world Manufacturer of instrumentation for autonomy, IoT, and vehicle electrification Provides transportation infrastructure, which aims to eliminate the problems of congestion, gridlock, and insufficient highway capacity Provides parking services to the automotive industry, by providing drivers with the information on location, pricing and real-time availability of off-street and on-street parking

http://www.cisco.com/

Multimer

EB Systems Michael Baker International

moovel

Moovit

National Instruments Overland ATS, LLC

Parkopedia

http://www.multimerdata.com/

http://www.ebsystems.com/ http://www.mbakerintl.com/

http://www.moovel.com/en_us

http://www.moovitapp.com/

http://www.ni.com/ http://www.overlandats.com/

http://www.parkopedia.com/

(Continued)

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Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

Q-Free

Global supplier and systems integrator for intelligent transportation systems, including tolling, traffic management, infomobility, and parking management Provides drones for citywide use in easing traffic congestion, speeding up construction on roads and picking up trash Enhances and accelerates coast-to-coast deployment of connected vehicle pilots; as a means to dedicated short range radio communications (DSRC); as the foundation for a ubiquitous vehicle-tovehicle and vehicle-to-infrastructure (V2X) system; leveraging the unique capabilities of SiriusXM’s existing network infrastructure exclusively licensed spectrum; and, in-vehicle hardware and software platform Provides an agnostic fleet management platform designed to connect, operate, and optimize any fleet of autonomous vehicles. Provides a multisensor data fusion behavioral analytics platform that includes video, time phase numerical data (SCADA, building management data sources), and cyber Uses open data to predict outcomes, help prioritize resources, and establish datadriven performance metrics Provides non-programmers with the ability to create, deliver, and track proximitybased experiences which contain rich targeted content, audio, video, HTML, and more Was created to help smart cities access a group of startup companies that work together to address the US DOT’s 12 Vision Elements Provides analytics and parking guidance to solve parking issues for smart cities A design studio that takes a human centered and research based approach to crafting spaces, strategies, and content A green incentive based digital directory, signage, and announcement system that displays real-time transit, shared ride, and bike information

http://www.q-free.com/

SICdrone SiriusXM

BestMile

Giant Gray, Inc.

Open Data Nation Place Global

Smart City Startup Consortium Streetline Think-Craft

TouchSource Inc.

http://www.sicdrone.com/ http://www.siriusxm.com/

http://www.bestmile.com/

http://www.giantgray.com/

http://www.opendatanation.com/ http://www.placeglobal.com/

http://www. smartcitystartupconsortium.org/ http://www.streetline.com/ http://www.thinkcraft.co/

http://www.touchsource.com/

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(Continued) Organization

Description

URL

Veniam

Enables vehicles with multinetwork capabilities, allowing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication Specializes in the deployment of energy, water, telecommunications, transportation, and smart-city infrastructure Delivers the infrastructure necessary for smart city/smart transportation technology companies to securely and unobtrusively house the placement of their antennae and electronics that is pervasive, manageable, and revenue producing Creates seamless solutions and platforms designed to enhance today’s smart cities Designs and deploys high-performance public structures that integrate Wi-Fi, mobile LTE, and smart sensor technologies. Provides a multistage research and recommendation project, which is focused on the economic, environmental, safety, and health impacts of emerging advancements in metropolitan transportation Combines RFID, magnetic locating, cloud data management, and geo-locating software to mark, locate, and manage infrastructure asset points Develops and deploys smart cities resource measurement systems that help smart cities make infrastructure and asset decisions more easily, as well as bringing crucial gas, water, electricity, and sensor data to provide real-time views of a smart cities resource utilization in cooperation with utilities and services departments Supplies production control systems in a variety of applications: electric and hybrid systems; alternative fuel engine control; hydraulics; autonomous systems; and overall vehicle control

http://www.veniam.com/

Black & Veatch

Brandbumps

CitiSite Corporation CIVIQ Smartscapes LLC Eno Center for Transportation

InfraMarker by Berntsen Itron Idea Labs

New Eagle - New “Energy”

http://www.bv.com/

http://www.brandbumps.com/

http://www.citisite.us/ http://www.civiqsmartscapes. com/ http://www.enotrans.org/

http://www.inframarker.com/

https://www.itron.com/na/ company/who-we-are/itronidea-labs

http://www.neweagle.net/

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Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

Nimble Consulting Inc.

Program and change consultancy that helps energy companies deploy transformational change initiatives and services like: governance and stakeholder management; change management; training; facilitation; and program management Deploys measurement technologies in the waste management industry to increase efficiency, improve recycling rates, reduce emissions, and save smart city costs A global consulting and engineering firm, that supports companies across the automotive, telecommunications, and aerospace industries to bring their products from the innovation stage to full implementation Provides software and professional services to smart cities and regions for optimizing the movement of people and goods for a sustainable and smart future Builds driving simulators for research needs Takes machine data and makes sense of it Creates data-driven software to improve urban mobility Provides GIS/GPS asset inventory auditing; design and engineering; installation; project management; controls integration; advanced analytics; system commissioning; utility billing analysis; warranty management; project financing; and utility rebate optimization Reduces unnecessary traffic by making carpooling fun and effective; saving parents time and money; while simultaneously decreasing emissions Develops and operates antenna facilities on governmental properties Provides energy storage and solar generation at a V2G bidirectional charging station Provides innovative technology solutions for the future of smart fleet management Implements autonomous behaviors and precise ( 6 2cm) accuracy for V2X solutions (indoors, outdoors, air, and ground vehicles)

http://www.nimbleconsulting.net/

OPTIMYS

P3 Communications Inc

PTV Group

Realtime Technologies Inc. Splunk, Inc. Swiftly, Inc. TEN - The Efficiency Network, Inc.

Time Lab, Inc. (Kid CarPool) Wireless EDGE XLR8SUN Zonar 5D Robotics

http://www.optimys.com/

http://www.p3-group.com/

http://www.ptvgroup.com/

http://www.simcreator.com/ http://www.splunk.com/ http://www.goswift.ly/ http://www.tensaves.com/

http://www.kidcarpool.com/

http://www.wirelessedge.com/ http://xlr8sun.com/ http://www.zonarsystems.com/ http://www.5drobotics.com/

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(Continued) Organization

Description

URL

Air Expertise Colorado

Provides expertise in applying US EPA models to determine the most fuelefficient and least carbon intensive transportation alternatives Provides great support in facilitating cooperation with European stakeholders (cities, industry, and research) for exchange of best practices and knowledge sharing. Integrates intelligence, controls, wireless connectivity, and smart sensors on street lighting infrastructures Provides a parcel-level affordable housing and traffic reduction model to aid in smart growth and sustainable development Provides IT services to public sector organizations across the country Provides cloud-based data analytics solution for fusing traffic data with WiFi sensor data; helping traffic engineers determine travel behavior; measuring travel and delay times; and monitoring congestion and signal performance of the road network Provides an application enablement platform that simplifies the deployment of M2M cloud services; robust device connectivity and communication suite; and security technology to protect everything from the data to the device to the entire network Provides software technologies and develops advanced analytical health management solutions for use in defense aviation, commercial aviation, energy, and ground transportation systems Manages congestion and safety at intersections by using technology that improves traffic signal operation, in order to reduce delays and optimize system efficiency Provides cameras designed for the collection of data from moving traffic, regardless of speed, or illumination A big data platform that enables the Internet of Things and smart technology solutions

http://www.airexpertisecolorado. com/

BLERVAQUE Sprl

Cimcon Lighting Inc. CourthouseUSA, LLC DatamanUSA FLIR Systems

Gemalto

Global Strategic Solutions LLC

GRIDSMART Technologies, Inc.

Hill & Smith Inc. Hortonworks

https://data.be/en/company/ Blervaque-SPRL-0474847662

http://www.cimconlighting.com/ http://www.courthouseusa.com/

http://www.datamanusa.com/ http://www.flir.com/traffic

http://www.gemalto.com/

http://www.gssllc.net/

http://www.gridsmart.com/

https://hillandsmith.com/ http://www.hortonworks.com/

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(Continued) Organization

Description

URL

LQD

Provides unified technology hubs, where anyone can engage with the community, the Internet, and local services at any time; as well as, a network of public information, safety, and emergency assistance Researches and investigates urbanization and the development of solutions for safer, cleaner, and more reliable transportation for future smart cities Provides proprietary software that is GPS enabled and allows you the ability to quickly push out messages for public safety; such as route changes and closures, emergency weather alerts, amber alerts, or other critical community information Provides distributed networks that deliver services where conventional networking techniques are not effective Provides smarter, cleaner solutions in energy, transportation, and the built environment Provides digitization of information at the source of an incident along with realtime data sharing, streamlined report generation, and data analytic tools for real-time insight into operations Provides software that allows cities to offer uber-style services, thereby investing in their own digital transportation infrastructure Provides smart-city solutions to customers related to the management of traffic, transport, logistics, and intelligent street lighting Specializes in providing engineering talent to complex projects in the transportation, infrastructure, aerospace, defense, science, and commercial sectors Provides end-to-end solutions and services in data warehousing, big data and analytics, and data science applications that enable cities to become data driven Provides intelligent solar powered traffic warning devices

http://www.lqdwifi.com/

Michelin Tire Corporation MultimediaLED

NetSteady Communications, Ltd. Prospect Silicon Valley Quicket Solutions

RideLeads

Siemens ITS

Stellar Solutions, Inc.

Teradata, Inc.

Traffic & Parking Control CO., Inc. (TAPCO)

http://www.michelinman.com/

http://www.multimedialed.com/

http://www.netsteady.com/ http://www.prospectsv.org/ http://www.quicketsolutions. com/

http://www.rideleads.com/

http://w3.usa.siemens.com/ mobility/ http://www.stellarsolutions.com/

http://www.teradata.com/

http://www.tapconet.com/

(Continued)

Appendix A: List of top smart cities and critical infrastructure implementation

673

(Continued) Organization

Description

URL

Transit Labs, Inc.

A transportation analytics company that helps smart cities move people and goods Real-time parking information services

http://www.transitlabs.com/ index.html http://www. trucksmartparkingservices.com/

Provides support to fleets to minimize the challenges associated with the operating characteristics and fueling requirements of medium- and heavy-duty zeroemission vehicles; helps organizations match propulsion and fuel technologies to the most appropriate fleet applications; and, provides independent, third party assessments to help organizations make informed zero-emission vehicle procurement and deployment decisions Provides intelligent mobility solutions and professional services focused on smartcity requirements, such as vehicle miles traveled; urban congestion; integrated corridor management; and connected vehicle and advanced traffic management systems Assists clients in understanding and implementing U.S. safety compliance regulations; as well as, completing research into autonomous and electric vehicle solutions Provides intelligent transportation hardware and software Converts current camera infrastructure into traffic sensors; and, publishes realtime, lane-level data for improved signal timing, driver safety, and transportation planning Supports the US Department of Transportation and Smart Cities with connected and autonomous vehicles; rideshare and bike share programs; and electric vehicle charging stations A parking payment service for commercial delivery and service vehicles Provides design and manufacturing of zero-emission, battery-electric transit vehicles, that enable bus fleet operators to significantly reduce operating costs, while delivering clean, quiet transportation to communities across North America

http://www.cte.com/

Truck Smart Parking services, Inc. (TSPS) Center for Transportation and the Environment

Kapsch TrafficCom

Kinetic Metrics LLC

McCain, Inc. MetroTech

Mobilitie

PayBySky, Inc. Proterra, Inc.

http://www.kapsch.com/

http://www.kineticmetrics.com/

http://www.mccain-inc.com/ http://www.metrotech-net.com/

http://www.mobilitie.com/

http://www.paybysky.com/ http://www.proterra.com/

(Continued)

674

Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

SGS Testcom

Provides inspection, verification, testing, and certification on the use of information technology and data analytics in the transportation industry Provides holistic data analytics platforms designed to get smart cities organized around their existing parking data, in order to implement smarter pricing; inventory allocation; planning decisions; and seamless growth into the connected age Manufactures self-powered, portable computing systems for outdoor intelligent security and industrial Internet applications Quantifies the energy-related benefits of advanced transportation solutions; and evaluates transportation programs at the state and local levels Analyzes the future of smart cities and new mobility, in terms of travel demand; energy and emissions; policy; data; equity; economics; and the built environment Provides real-time ridesharing, carsharing, and carpooling Provides the design, building, modification, and maintainability of wireless systems Provides a smart-city planning framework and services that include the how to on development of strategies; use cases; business cases; processes; and the use of best practices to create, deploy and manage the digitalization of energy, water, telecommunications, healthcare, transportation, education, public safety, public works, parks and recreation, economic development, legal, financial, and e-government services Deploys in the public space, contactless technologies (bluetooth low energy, NFC, QR code, Wi-Fi) that turn urban, passive physical assets (street furniture, bus stops, public lighting) into smart, connected objects, that are able to interact in the smart city with mobile users, in bringing contextualized, high added value information

http://sgs.com/

Smarking, Inc.

V5 Systems

American Council for an EnergyEfficient Economy Arup

Carma Centerline Solutions LLC CMG

Connecthings

http://www.smarking.net/

http://v5systems.us/

http://www.aceee.org/

http://www.arup.com/

http://www.gocarma.com/ http://www.centerlinesolutions. com/ https://512cmg.com/

http://www.connecthings.com/

(Continued)

Appendix A: List of top smart cities and critical infrastructure implementation

675

(Continued) Organization

Description

URL

Current powered by GE, Intelligent Cities

Enables smart cities to leverage their street lighting to be a data-collecting network that sees, hears, and harnesses the data that is everywhere Provides a platform through which data is exchanged between vehicles and infrastructure, specifically signalized intersections and roadside equipment (RSE) Develops applications to reduce friction for users in areas such as casual carpooling Provides long-range wireless Machine-toMachine communications devices; and, enables remote management and control of traffic control devices, video solutions, and Wi-Fi access Is a Wi-Fi-enabled garage controller that modernizes delivery logistics by turning garages into a personal delivery destination Provides solutions to move people through cities quicker, improves emergency vehicle safety, and reduces transportation emissions Designs every aspect of a truly integrated smart city for people to live, work, and play—from high-rises to industrial buildings; schools to state-of-the-art hospitals; transit stations to highways; airports to toll systems; and bike lanes to parks Provides traffic and parking information, connected car services, and smart-city analytics Provides transportation elements associated with smart cities, including intelligent, sensor-based infrastructure to collect and differentiate vehicle, pedestrian, and bicyclists at traffic signals, as well as enabling urban automation with mobility data aggregation and real-time analyses to improve safety, enhance the value of regional mobility and local accessibility, and ready the roadways for connected vehicle transportation

http://www.currentbyge.com/ ideas/intelligent-cities

Econolite Group, Inc.

Engage Mobile Solutions FreeWave Technologies, Inc.

Garageio

Global Traffic Technologies, LLC IBI Group

INRIX, Inc. Iteris, Inc.

http://www.econolitegroup.com/

http://www.engagemobile.com/ http://www.engagemobile.com/

http://garageio.com/

http://http/www.gtt.com/

http://www.ibigroup.com/

http://www.inrix.com/ http://www.iteris.com/

(Continued)

676

Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

LVL1 LLC

Provides support for smart cities and related solutions for network management, content development, content management, on-site technicians, and other services Provides driverless vehicle platforms and technologies under centimeter level accuracy in positioning and navigation Provides drivers access to more than 1000 fast charging locations, along with individual charging stations at homes, schools, offices, multifamily communities, and hospitals across the network Provides the platform for application specific vehicles that can be tailored for specific use, operating environment, and performance criteria Provides information on the availability of parking to mobile APPs for drivers, as well as helping parking management companies to monitor their spaces efficiently Provides hardware, software, and firmware to monitor and control ITS devices Provides unified security and management for IoT systems Provides predictions for the smart city and smart vehicle of the future and traffic data sets Provides an application and data management platform that enables centralized monitoring and control of smart city services regardless of the underlying technologies, vendors, or devices Provides a multilingual service, monetizes the Wi-Fi network, surface tourism, transport information, and a better understanding of the footfall Provides complicated multifaceted technical projects with an emphasis on design, development, and fielding of complex systems

http://www.mylvl1.com/

moovee innovations inc NRG EVgo

Pangea Motors LLC

Park Smart s.r.l.

Peek Traffic Corporation Phantom Iot Pivotal Software, Inc PLAT.ONE INC

Purple

RJ Vincent Enterprises LLC

http://www.mooveeinnovations. com/ http://https/www.nrgevgo.com/

http://www.pangeamotors.com/

http://www.buttiglieri.it/

http://www.peektraffic.com/ http://www.phantomiot.com/ http://pivotal.io/ http://www.plat.one/

http://www.purple.ai/

http://vincent-enterprises.com/ blog/

(Continued)

Appendix A: List of top smart cities and critical infrastructure implementation

677

(Continued) Organization

Description

URL

Smart City Results

Provides vehicle electrification; electrification infrastructure; wireless communications; vehicle automation; new forms of shared mobility; cost-benefit analysis; performance measurement; transportation economics and finance; community development; team building; process analysis; and preparation of funding and project proposals Provides residents and visitors with free charging for mobile devices, public WiFi, and pedestrian analytics Provides IoT-enabled, integrated IUX platform for big data; prebuilt IUX applications with domain-specific data models for transportation, water, and energy; and a set of APIs for thirdparty application development Provides smart-city consulting services Provides master planning, design, and development of smart cities Provides smart mobility solutions for electric vehicles, automated vehicles, ride-hailing, ride-splitting, first-last mile transit access solutions, shared ride, vehicle maintenance, taxi, paratransit, rail, and fixed-route bus operations Provides pavement and roadway asset management Manages the installation and deployment of a wide range of technology solutions for transportation, retail, distribution, manufacturing, education, healthcare, government, hospitality, restaurants, and public venues Provides smart data applications that make smart cities and communities safer and more connected; as well as, open standards, frameworks, and SDKs that bring new innovation to smart cities, and creates new markets for developers Provides high-resolution analytics and information at the arterial level Provides a transportation system that is like a tram; it rides on a pair of cables just like a tram, but that is where the similarities end—it drives itself along the pair of cables (self driven), where it can turn and travel any distance

http://www.smartcityresults.com/

Soofa TCS Digital Software & Solutions Group

Teknotraffic The Digit Group (TDG), Inc. Transdev North America

Transmap Corporation Velociti, Inc.

Xaqt

Acyclica Airbornway Corp.

http://www.soofa.co/ https://dss.tcs.com/

http://www.teknotraffic.com/ https://www.thedigitgroupinc. com/ http://transdevna.com/

http://www.transmap.com/ http://www.velociti.com/

https://www.xaqt.com/

http://www.acyclica.com/ http://airbornway.com/

(Continued)

678

Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

Bentley Systems

Provides users with a leverage on information mobility across many disciplines; and infrastructure project lifecycles, to deliver better-performing projects and assets Provides charging stations, mobile apps, and the network that allow people to charge their cars everywhere they go; as well as, transforming the energy industry by developing intelligent energy management solutions Provides a highly accurate, radar-based sensor that captures real-time, on-street parking occupancy and violation data; delivers guidance information to motorists; supports demand-based meter pricing; promotes parking program efficiency; reduces traffic congestion; and increases smart-city revenues Works with local governments, public transit agencies, taxi and transportation network companies, advanced vehicle developers, and transportation innovators, to prepare for the coming public and private markets for Transportation as a Service (TaaS), as well as planning and preparing for the development, marketing and growth shared-vehicle fleets, including autonomous public transit fleets, designed to become massive and pervasive over time Provides manufacturing, engineering, services, and self-service Kiosks Provides real-time traffic and bus data

https://www.bentley.com/

Provides public transit on demand, where the displacement of vehicles is managed by predictive algorithms Provides a modular, scalable, and personalized smart-city transportation system Provides smart IoT lighting solutions, ranging from energy efficient LED platforms; discretely integrated security cameras; sensors (gunshot, hazardous material, precipitation, etc.); electric car charging stations; Wi-Fi; kiosks; and back-end networking

http://www.mvmant.com/

ChargePoint

CivicSmart, Inc.

Grush Niles Strategic

KIOSK Information Systems Louisville Metro Advanced Planning MVMANT NEXT Future Transportation PennGlobe/ PennSMART

http://www.chargepoint.com/

http://www.civicsmart.com/

http://grushniles.com/

http://www.kiosk.com/ https://data.louisvilleky.gov/ group/advanced-planning

http://www.next-future-mobility. com/ http://www.pennsmart.com/

(Continued)

Appendix A: List of top smart cities and critical infrastructure implementation

679

(Continued) Organization

Description

URL

Ridesharing Institute

Provides technologies such as autonomous and connected vehicles; sensor-based infrastructure; smart parking; urban analytics; smart grid and EV’s; and multimodal transportation Deploys communication ecosystems in smart cities that enable vehicle-tovehicle, vehicle-to-smartphone, vehicleto-traffic light, and vehicle-toinfrastructure communication Provides analytics describing key mobility behavior with smart cities and run routing; origin/destination; before/after comparisons; and more in a matter of minutes, using billions of real-world trips sourced from mobile devices Provides free Wi-Fi Kiosks to smart cities supported by advertising revenues Links city dwellers to transportation hubs efficiently and effectively, while eliminating the need for parking, sitting in traffic, and paying for gas Provides a powerful, as well as, wired charging solution that is user-friendly, and safe to use to customers everywhere around the smart city Helps smart cities increase their resiliency against flooding and other natural hazards by using cloud computing, realtime mapping, and interactive graphics, which together save planners hundreds of hours in data collection, analysis, and visualization Provides a dispatch system that monitors vehicle positions, availability, waiting times, advanced reservations, and data relating to all trips (upcoming or completed) Uses technology to move people from multiple origins to multiple destinations, to seamlessly share rides in professionally driven vehicles—in real time Provides a mass notification system; as well as, a safety app, which uses an indoor positioning system (IPS) to help responders more accurately locate distressed individuals

http://www.bosch.us/

Savari

StreetLight Data

SYNC City LLC URB-E

Vim and Vigor Development LLC Vizonomy

iCabbi

Via Transportation, Inc.

911Cellular

http://www.savari.net/

http://www.streetlightdata.com/

http://www.sync.city/ http://www.urb-e.com/

http://www. vimvigordevelopment.com/ http://www.vizonomy.com/

http://www.icabbi.com/

http://platform.ridewithvia.com/

http://www.911cellular.com/

(Continued)

680

Appendix A: List of top smart cities and critical infrastructure implementation

(Continued) Organization

Description

URL

Citilabs

Provides software and data platforms for use in smart management, operation, and planning Provides a car with the footprint of a motorcycle, and the weight of a midsize sedan with more side impact protection Uses existing infrastructure to connect traffic signals to vehicles Provides ways to help smart cities provide their citizenry new and smart public benefits from their public agency data Specializes in mobility technologies and digital services to smart cities in several fields like mobile ticketing (lightweight solutions for public transportation); event management; construction site management (information for people, mobility tools for workers); and waste management Provides a SaaS platform that serves as both an open data portal and a smart city data hub that is natively designed for real-time sensor data, and includes built-in API generation and data visualization

http://www.citilabs.com/

Commuter Cars Corp

Connected Signals, Inc. Live Traffic Data (LTD), LLC NFC-Interactive

OpenDataSoft

http://www.commutercars.com/

http://www.connectedsignals.com/ http://www.livetrafficdata.com/ http://http/www.nfc-interactive.fr/

https://www.opendatasoft.com/

Appendix B: List of smart cities and critical infrastructure products/projects John R. Vacca

Product/project

Country/ region

City

URL

ALMANAC

Italy

Torino

https://almanacproject.github.io/

Amsterdam Smart Light

Netherlands

Amsterdam

https://www.luciassociation.org/ smart-lighting-for-amsterdamshoekenrodeplein-square/

Automatic Urban and Rural Network (AURN) Berliner Badewasserqualit¨at

UK

Not available (N/A)

https://uk-air.defra.gov.uk/networks/ network-info?view 5 aurn

Germany

Berlin

http://daten.berlin.de/datensaetze/liste-derbadestellen-badegew¨aA4sserqualit¨at

Bristol Air Quality Data Bristol is Open

UK

Bristol

http://www.bristol.airqualitydata.com/

UK

Bristol

https://www.wired.co.uk/news/archive/ 2015-03/17/bristol-smart-city

Building Smarter and Safer Communities

USA

Charleston

https://smartcitiescouncil.com/resources/ building-smarter-and-safer-communities

Chicago Array of Things Cities Unlocked

USA

Chicago

https://arrayofthings.github.io/

UK

N/A

http://www.citiesunlocked.org.uk/

City2Mobil2

Europe

N/A

https://cordis.europa.eu/result/rcn/ 191677_en.html

City of Chicago Data Portal Civic Hall NYC

USA

Chicago

https://data.cityofchicago.org/

USA

New York

http://civichall.org/

Connecting Cities

Global

N/A

http://connectingcities.net/

DIMIS

Germany

N/A

http://www.iis.fraunhofer.de/de/ff/lok/proj/ dimis.html

(Continued)

682

Appendix B: List of smart cities and critical infrastructure products/projects

(Continued) Product/project

Country/ region

City

URL

Eeneind Street Lighting

Netherlands

Eeneind

http://www.tvilight.com/projects/citynuenen/

EkoBus

Serbia

Belgrade, Pancevo

http://www.libelium.com/smart_ city_environmental_parameters_ public_transportation_waspmote/

EPIC European Platform for Intelligent Cities Express Park Program

Europe

N/A

http://www.epic-cities.eu/

USA

Los Angeles

http://www.laexpresspark.org/about-laexpresspark/

Forum Virium Helsinki

Finland

Helsinki

http://www.forumvirium.fi/en

Glasgow Future City

UK

Glasgow

https://futurecity.glasgow.gov.uk/

Greater Manchester Data Synchronisation Programme Hamburg Smart City

UK

Manchester

http://iyfsearch.com/?dn 5 gmdsp.org. uk&pid 5 9PO755G95

Germany

Hamburg

https://www.e-zigurat.com/blog/en/urbandevelopment-the-smart-city-hamburgproject/

Hamburg smartPORT

Germany

Hamburg

https://newsroom.cisco.com/press-releasecontent? type 5 webcontent&articleId 5 1414144

Helsinki Region Infoshare (HRI) iCity

Finland

Helsinki

http://www.hri.fi/en

Spain

Barcelona

http://www.icityproject.eu/

IssyGrid

France

Issy-LesMoulineaux

http://imaginationforpeople.org/ maintenance/maintenance.htm

Kalasatama Model District of Smart Urban Development La Garrotxa

Finland

Helsinki

http://en.uuttahelsinkia.fi/

Spain

La Garrotxa

http://www.libelium.com/smart-city-urbanresilience-smart-environment/

LinkNYC

USA

New York

http://www.link.nyc/

London Data Store

UK

London

http://data.london.gov.uk/

Los Angeles Synchronised Traffic Lights

USA

Los Angeles

https://www.pcworld.com/article/2032914/ los-angeles-synchronizes-all-its-trafficlights-lets-a-computer-control-the-roads. html

(Continued)

Appendix B: List of smart cities and critical infrastructure products/projects

683

(Continued) Product/project

Country/ region

City

URL

Madrid smart parking meters

Spain

Madrid

https://www.theguardian.com/world/2014/ apr/30/madrid-smart-parking-metrespolluting-cars

Milton Keynes’ Internet of Things Monaco 3.0

UK

Milton Keynes

http://www.mksmart.org/

Monaco

Monaco

http://blog.bosch-si.com/categories/ projects/2013/12/smart-city-monaco-30-bosch-technology/

NAPA

Germany

N/A

http://www.iis.fraunhofer.de/de/ff/lok/proj/ napa.html

Nijmegen Roadway Lighting

Netherlands

Nijmegen

http://www.tvilight.com/projects/ intelligent-roadway-lighting/

Open Data Hamburg

Germany

Hamburg

http://transparenz.hamburg.de/open-data/

PlanIT Valley

Portugal

Porto

http://www.living-planit.com/

RESCATAME

Spain

Salamanca

http://www.libelium.com/ smart_city_air_quality_urban_ traffic_waspmote/

Sensing London

UK

N/A

https://futurecities.catapult.org.uk/project/ sensing-london/

Smart Airport Experience

UK

London

http://www.airport-business.com/2015/06/ london-city-investing-smart-airportexperience-expedite-passenger-journey/

Smart Blocks

Australia

Melbourne

https://communicationscollective.com.au/ city-of-melbourne-smart-blocks/% 20target 5

Smart Cities Demo Aspern (SCDA) Smart City

Austria

Aspern

https://smartcity.wien.gv.at/site/en/

Sweden

N/A

https://international.stockholm.se/citydevelopment/the-smart-city/

Smart City Berlin

Germany

Berlin

http://www.berlin-partner.de/en/the-berlinlocation/smart-city-berlin/

Smart City Commission

UK

Birmingham

https://birminghamsmartcity.wordpress. com/

Smart London Initiative / Datastore Smart Santander

UK

London

http://data.london.gov.uk/

Spain

Santander

http://www.smartsantander.eu/

SMILE

Austria

Vienna

http://smile-einfachmobil.at/

Songdo International Business District

South Korea

Songdo

http://www.songdo.com/

(Continued)

684

Appendix B: List of smart cities and critical infrastructure products/projects

(Continued) Product/project

Country/ region

City

URL

Stockholm Royal Seaport Project

Sweden

Stockholm

http://www.environmentalleader.com/2012/ 07/11/smart-cities-stockholm-royalseaport-project-update/

Streetmix

USA

N/A

http://streetmix.net/

Trash Track

USA

N/A

http://senseable.mit.edu/trashtrack/

UK Air Pollution

UK

N/A

http://uk-air.defra.gov.uk/air-pollution/

Whereabouts London

UK

London

http://whereaboutslondon.org/#/about

WindyGrid

USA

Chicago

http://www.cityofchicago.org/city/en/narr/ foia/CityData.html

XALOC

Spain

Barcelona

http://www.uab.cat/web/latest-news/newsdetail/new-system-helps-locate-car-parkspaces-1096476786473.html? noticiaid 5 1278568901108

Yokohama Smart City Project

Japan

Yokohama

https://www.toshiba.co.jp/about/press/ 2011_12/pr1601.htm

Appendix C: List of smart cities and critical infrastructure standards John R. Vacca

Standard

Number

Type

URL

Services

03.080

https://www.standard.no/en/webshop/ productcatalog/productpresentation/ ?ProductID 5 247499

Transport

03.220

International Classification for Standards (ICS) ICS

Medical sciences and health care facilities in general

11.020

ICS

https://www.normadoc.com/english/ ics/11-health-care-technology/11020-medical-sciences-and-healthcare-facilities-in-general.html

Aids for disabled or handicapped persons Environmental protection Wastes

11.180

ICS

https://www.iso.org/ics/11.180.html

13.020

ICS

https://www.iso.org/ics/13.020.html

13.030

ICS

https://www.iso.org/ics/13.030.html

Air quality

13.040

ICS

https://www.iso.org/ics/13.040.html

Water quality

13.060

ICS

https://www.iso.org/ics/13.060.html

Accident and disaster control Alarm and warning systems Energy and heat transfer engineering in general Heat pumps

13.200

ICS

https://www.iso.org/ics/13.200.html

13.320

ICS

https://www.iso.org/ics/13.320.html

27.010

ICS

https://www.iso.org/ics/27.010.html

27.080

ICS

https://www.iso.org/ics/27.080.html

Solar energy engineering Electrical accessories

27.160

ICS

https://www.iso.org/ics/27.160.html

29.120

ICS

https://www.iso.org/ics/29.120.html

Switchgear and control gear

29.130

ICS

https://www.iso.org/ics/29.130.html

https://www.standard.no/en/webshop/ productcatalog/productpresentation/ ?ProductID 5 247524

(Continued)

686

Appendix C: List of smart cities and critical infrastructure standards

(Continued) Standard

Number

Type

URL

Power transmission and distribution networks Electronic display devices Electromechanical components for electronic and telecommunications equipment Telecommunications in general (including infrastructure) Telecommunication services. Applications (including supplementary services, service aspects and associated legal tracability aspects) Telecommunication systems [including network (system) aspects] Mobile services

29.240

ICS

https://www.iso.org/ics/29.240.html

31.120

ICS

https://www.iso.org/ics/31.120.html

31.220

ICS

https://www.iso.org/ics/31.220.html

33.020

ICS

https://www.iso.org/ics/33.020.html

33.030

ICS

https://www.iso.org/ics/33.030.html

33.040

ICS

https://www.iso.org/ics/33.040.html

33.070

ICS

https://www.iso.org/ics/33.070.html

Components and accessories for telecommunications equipment Telecontrol. Telemetering Information technology (IT) in general Software

33.120

ICS

https://www.iso.org/ics/33.120.html

33.200

ICS

https://www.iso.org/ics/33.200.html

35.020

ICS

https://www.iso.org/ics/35.020.html

35.080

ICS

https://www.iso.org/ics/35.080.html

Networking

35.110

ICS

https://www.iso.org/ics/35.110.html

Interface and interconnection equipment Applications of information technology Road vehicles in general Road vehicle systems

35.200

ICS

https://www.iso.org/ics/35.200.html

35.240

ICS

https://www.iso.org/ics/35.240.html

43.020

ICS

https://www.iso.org/ics/43.020.html

43.040

ICS

https://www.iso.org/ics/43.040.html

(Continued)

Appendix C: List of smart cities and critical infrastructure standards

687

(Continued) Standard

Number

Type

URL

Electrical and electronic equipment and control systems Commercial vehicles

43.060.50

ICS

https://www.iso.org/ics/43.060.50.html

43.080

ICS

https://www.iso.org/ics/43.080.html

Passenger cars. Caravans and light trailers Electric road vehicles

43.100

ICS

https://www.iso.org/ics/43.100.html

43.120

ICS

https://www.iso.org/ics/43.120.html

Special purpose vehicles Railway engineering in general Materials and components for railway engineering Rails and railway components Freight distribution of goods Distribution and vending machines Construction industry

43.160

ICS

https://www.iso.org/ics/43.160.html

45.020

ICS

https://www.iso.org/ics/45.020.html

45.040

ICS

https://www.iso.org/ics/45.040.html

45.080

ICS

https://www.iso.org/ics/45.080.html

55.180

ICS

https://www.iso.org/ics/55.180.html

55.230

ICS

https://www.iso.org/ics/55.230.html

91.010

ICS

https://www.iso.org/ics/91.010.html

Physical planning. Town planning Buildings

91.020

ICS

https://www.iso.org/ics/91.020.html

91.040

ICS

https://www.iso.org/ics/91.040.html

Installations in buildings Lighting

91.140

ICS

https://www.iso.org/ics/91.140.html

91.160

ICS

https://www.iso.org/ics/91.160.html

Building accessories

91.190

ICS

https://www.iso.org/ics/91.190.html

Civil engineering in general Road engineering

93.010

ICS

https://www.iso.org/ics/93.010.html

93.080

ICS

https://www.iso.org/ics/93.080.html

Construction of railways Construction of airports

93.100

ICS

https://www.iso.org/ics/93.100.html

93.120

ICS

https://www.iso.org/ics/93.120.html

Construction of waterways, ports and dykes Home economics in general Domestic electrical appliances in general Kitchen equipment

93.140

ICS

https://www.iso.org/ics/93.140.html

97.020

ICS

https://www.iso.org/ics/97.020.html

97.030

ICS

https://www.iso.org/ics/97.030.html

97.040

ICS

https://www.iso.org/ics/97.040.html

(Continued)

688

Appendix C: List of smart cities and critical infrastructure standards

(Continued) Standard

Number

Type

URL

Laundry appliances

97.060

ICS

https://www.iso.org/ics/97.060.html

Cleaning appliances

97.080

ICS

https://www.normadoc.com/english/ ics/97-domestic-and-commercialequipment-entertainment-sports/97080-cleaning-appliances.html

Domestic, commercial, and industrial heating appliances Automatic controls for household use Shop fittings

97.100

ICS

https://www.iso.org/ics/97.100.html

97.120

ICS

https://www.iso.org/ics/97.120.html

97.130

ICS

https://www.iso.org/ics/97.130.html

Miscellaneous domestic and commercial equipment Equipment for entertainment Systems Evaluation Group on Smart Cities—most of their activities seem to be working group reports Sustainable cities and communities— vocabulary

97.180

ICS

https://www.iso.org/ics/97.180.html

97.200

ICS

https://www.iso.org/ics/97.200.html

SEG 1

IEC

http://noderedguide.com/smart-citystandards-an-overview/

37100:2016

ISO

https://infostore.saiglobal.com/ en-us/Standards/ISO-371002016-607033_SAIG_ ISO_ISO_1391510/

Sustainable development and resilience of communities— management systems —general principles and requirements Sustainable development in communities— management system for sustainable development— requirements with guidance for use Sustainable development and resilience of communities— vocabulary

37101

ISO

https://pecb.com/en/education-andcertification-for-individuals/iso37101

37101:2016

ISO

https://infostore.saiglobal.com/ en-us/Standards/ISO-371012016-606594_SAIG_ISO_ ISO_1390363/

37102

ISO

https://global.ihs.com/doc_detail.cfm? document_ name 5 ISO%2037102& item_s_key 5 00674095

(Continued)

Appendix C: List of smart cities and critical infrastructure standards

689

(Continued) Standard

Number

Type

URL

Sustainable cities and communities— transforming our cities—guidance for practical local implementation of ISO 37101 Sustainable cities and communities— descriptive framework for cities and communities Sustainable cities and communities— guidance on establishing smart city operating models for sustainable communities Sustainable cities and communities— guidance on establishing smart city operating models for sustainable communities— Amendment 1 Sustainable development of communities— indicators for city services and quality of life Sustainable cities and communities— business districts— guidance for practical local implementation of ISO 37101 Sustainable development of communities— management systems —requirements with guidance for resilience and smartness

37104:2019

ISO

https://infostore.saiglobal.com/ en-au/standards/iso-371042019-1148043_saig_iso_iso_ 2722831/

37105:2019

ISO

https://infostore.saiglobal.com/ en-au/standards/iso-fdis37105-2019-1159394_ saig_iso_iso_2754465/

37106:2018

ISO

https://infostore.saiglobal.com/ en-au/standards/iso-371062018-1132896_saig_iso_iso_ 2674837/

37106:2018/ CD Amd 1

ISO

https://iso.ch/ru/standard/76545.html? browse 5 tc

37120:2014: 2014

ISO

https://www.iso.org/obp/ui/#iso:std: iso:37120:ed-1:v1:en

37108

ISO/AWI

https://www.iso.org/standard/62067. html

37101

ISO/DIS

https://ec.europa.eu/eip/ageing/ standards/city/smart-cities/isodis37101_en

(Continued)

690

Appendix C: List of smart cities and critical infrastructure standards

(Continued) Standard

Number

Type

URL

Inventory and review of existing indicators on sustainable development and resilience in cities Smart cities

37121

ISO/DTR

https://ec.europa.eu/eip/ageing/ standards/city/smart-cities/isodtr37121_en

JTC 1

ISO IEC

https://www.iso.org/iso/ smart_cities_report-jtc1.pdf

Sustainable development in communities— indicators for smart cities Inventory and review of existing indicators on sustainable development and resilience in cities Smart community infrastructures— review of existing activities relevant to metrics Smart community infrastructures— common framework for development and operation Sustainable cities and communities— maturity model for smart sustainable communities Smart community infrastructures— principles and requirements for performance metrics Sustainable development and communities— practical guidance for project developers—meeting ISO 37101 framework principles

37122

ISO/NP

https://ec.europa.eu/eip/ageing/ standards/city/smart-cities/isonp37122_en

37121

ISO/TR

https://www.iso.org/obp/ui/#iso:std: iso:tr:37121:ed-1:v1:en:sec:5

37150

ISO/TR

https://standards.globalspec.com/std/ 1663072/iso-tr-37150

37152

ISO/TR

https://standards.globalspec.com/std/ 10034071/iso-tr-37152

37107:2019

ISO/TS

https://shop.belgiss.by/en/ mezhdunarodnye-standarty-iso/isots-37107:2019

37151:2015: 2015

ISO/TS

https://www.iso.org/obp/ui/fr/#iso:std: iso:ts:37151:en

37109

ISO/WD

https://www.iso.org/standard/62068. html

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Appendix C: List of smart cities and critical infrastructure standards

691

(Continued) Standard

Number

Type

URL

Sustainable cities and communities— management guidelines of open data for smart cities and communities— Part 1: Overview and general principles Sustainable development of communities— indicators for city services and quality of life Focus group on smart sustainable cities

37110

ISO/WD

https://www.iso.org/standard/62069. html

37120

ISO/WD

https://ec.europa.eu/eip/ageing/ standards/city/smart-cities/isowd37120_en

SG5 FG-SSC

ITU-T

https://www.itu.int/en/ITU-T/ focusgroups/ssc/Pages/default.aspx

Smart cities— infrastructures— universal accessibility Accessible mobility in smart cities

178106

PNE

https://ec.europa.eu/eip/ageing/ standards/city/smart-cities/pne178106_en

178306

PNE

https://ec.europa.eu/eip/ageing/ standards/city/smart-cities/pne178306_en

Management system of smart tourist destinations— requirements Smart Sustainable cities —analysis of definitions Technical Report on Standardization Activities and Gaps for SSC and suggestion to SG5, ITU-T Key performance indicators (KPIs) definitions for smart sustainable cities Smart cities—open data

178501

PNE

https://ec.europa.eu/eip/ageing/ standards/city/smart-cities/pne178501_en

0100-Rev 2

SSC

https://www.iso.org/iso/ smart_cities_report-jtc1.pdf

0110

SSC

https://www.iso.org/iso/ smart_cities_report-jtc1.pdf

162

SSC

https://www.iso.org/iso/ smart_cities_report-jtc1.pdf

178301:2015: 2015

UNE

https://www.en-standard.eu/une178301-2015-smart-cities-opendata/

Appendix D: List of miscellaneous smart cities and critical infrastructure resources John R. Vacca

Resource

URL

OCIA—The Future of Smart Cities— Cyber-Physical Infrastructure Risk

https://www.us-cert.gov/sites/default/files/documents/ OCIA%20-%20The%20Future%20of%20Smart% 20Cities%20-%20Cyber-Physical%20Infrastructure% 20Risk.pdf

Smart cities readiness guide

http://www.estudislocals.cat/wp-content/uploads/2016/11/ SmartCitiesReadinessGuide.pdf

CSTEP REport Smart Cities Framework

https://india.smartcitiescouncil.com/system/tdf/india/ public_resources/CSTEP%20REport%20Smart% 20Cities%20Framework%20-%20Compendium%20of% 20Resources.pdf?file 5 1&type

Digital Government Smart Cities and Communities Protecting Critical Infrastructure and Roadways: How Smart Cities Create New Risks

https://www.govloop.com/resources/

Smart city technology: India joins global alliance

https://m.economictimes.com/news/economy/ infrastructure/india-joins-global-alliance-on-responsibleuse-of-smart-city-technologies/articleshow/71535525. cms

5 Reasons Why Securing Critical Infrastructure is Essential in Smart Cities Smart Cities—Arm

https://www.lanner-america.com/blog/5-reasons-securingcritical-infrastructure-essential-smart-cities/

Smart Cities and Communities Federal Strategic Plan—NITRD Bridging the smart cities security divide

https://www.nitrd.gov/drafts/scc_strategicplan_draft.pdf

Smart City Indicators India— AIRSOFTNET

http://dqox.airsoftnet.nl/smart-city-indicators-india.html

https://blog.trendmicro.com/protecting-criticalinfrastructure-and-roadways-how-smart-cities-createnew-risks/

https://www.arm.com/solutions/smart-cities

https://www.csoonline.com/article/3252844/bridging-thesmart-cities-security-divide.html

Appendix E: Smart cities and critical infrastructure frequently asked questions John R. Vacca

Question

Answer: URL

What are the techniques for managing municipal solid wastes for smart cities?

https://www.waste360.com/generators/how-smartcities-are-managing-solid-waste

What does it mean that a city is smart?

https://internetofthingsagenda.techtarget.com/ definition/smart-city

What does a smart city mean to you?

https://statescoop.com/what-does-smart-city-meanin-2018/

What is the definition of smart data?

https://whatis.techtarget.com/definition/smart-data

Does the development of smart cities improve people’s lives?

https://www.nlc.org/article/how-smart-cities-willchange-our-lives

What are Data Governance Frameworks for smart cities?

https://smartimpact-project.eu/app/uploads/2018/ 02/SmartImpact_Data-Gov-andIntergration_A4_AW.pdf

What technologies dominate in the field of smart ecology sustainable development cities?

https://link.springer.com/article/10.1186/s40309019-0157-0

What are the trends in smart cities?

https://www2.deloitte.com/us/en/insights/focus/ smart-city.html

What is an active mode of transportation (walking/ cycling) in smart cities?

https://www.railstotrails.org/media/847675/ activetransport_2019-report_finalreduced.pdf

What are the current trends in smart-city contracts?

https://cordis.europa.eu/docs/projects/cnect/6/ 270896/080/deliverables/001D2221NewtrendsforSmartCities.pdf

What is a heterogeneous smart-city dataset?

https://www.mdpi.com/1424-8220/18/9/2994/htm

What is the future of green buildings or smart buildings, or a combination of both practices?

https://idac.co/question/99/What-is-the-futuregreen-buildings-or-smart-buildings-or-acombination-of-both-practices

Is there any existing method, technique, or sensors to control the flow of water in a smart pipeline?

http://www.libelium.com/ smart_water_wsn_pipe_leakages/

(Continued)

696

Appendix E: Smart cities and critical infrastructure frequently asked questions

(Continued) Question

Answer: URL

What are the hot research areas in computer science for smart cities?

https://www.techrepublic.com/article/15-hot-techjobs-for-smart-cities-in-2018-and-beyond/

Which is the appropriate use of technology for urban interiors, is it intelligent or smart? Why?

https://www.askidac.com/question/434/Which-isthe-appropriate-use-of-technology-for-urbaninteriors-is-it-intelligent-or-smart-Why

What could be the best road to start research in smart charging of electric vehicles?

https://www.sciencedirect.com/science/article/pii/ S0968090X17301365

Are there any presentations of smart-city projects?

http://smartcities.gov.in/content/presentation.php

What are the protocols and criteria for smart-city multimodal traffic management?

https://www.diva-portal.org/smash/get/ diva2:975199/FULLTEXT01.pdf

Will the development of autonomous cars be correlated with the development of electric cars?

https://www.quora.com/Will-the-development-ofautonomous-cars-be-correlated-with-thedevelopment-of-electric-cars

How can Artificial Intelligence help make smart cities more competitive?

https://becominghuman.ai/artificial-intelligencefor-smart-cities-64e6774808f8

What are the known future visions of smart-city technology development until 2070? What are the current examples of smart cities?

https://pittsburghpa.gov/domi/transport-vision-plan

Is it possible to build a fully autonomous energetical and ecological smart city?

https://www.plugandplaytechcenter.com/resources/ 9-smart-cities-startups-are-reshaping-cities-weknow-them/

What do we need to know to plan and design better smart cities?

https://medium.com/@anthonymobile/smart-citieswhat-do-we-need-to-know-to-plan-and-designthem-better-b6d05e736ea1

Is 5 G and Ethernet sufficient enough to connect, communicate and help to enable cyber security for 700 million vehicles in a smart-city infrastructure? Clustering with intensive technology integration, how have smart cities impacted competition?

https://arxiv.org/pdf/1909.08096

What are smart city and IOT simulation tools?

https://datasmart.ash.harvard.edu/news/article/ simcities-designing-smart-cities-through-datadriven-simulation-893

Is China the technological leader in the construction of environment-friendly metropolises developed in the smart-city model? What technologies are used in the development of computerized smart-city systems?

https://www.tandfonline.com/doi/full/10.1080/ 13549839.2019.1628730

https://bipartisanpolicy.org/blog/five-innovativeexamples-of-smart-cities-in-the-u-s/

https://www.tandfonline.com/doi/full/10.1080/ 23311975.2018.1532777

https://mobility.here.com/smart-city-technologiesrole-and-applications-big-data-and-iot

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Appendix E: Smart cities and critical infrastructure frequently asked questions

697

(Continued) Question

Answer: URL

Is an artificial intelligence based mathematical model possible to forecast smart cities growing requirements for increasing populations? How do you apply the principles of smart cities to the operation of the smart campus?

https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC6957485/

What will a smart home look like in the future?

https://planetechusa.com/the-future-of-smarthomes/

Should smart cities be steered by IT technology alone or led by land use planning principles?

https://www.planning.org/planning/2019/mar/ smartcities/

How can we connect between banal existent buildings (lacking originality, freshness, or novelty trite) in smart cities? Why do we need to have smart cities and not the smart and social people?

https://www.smartcitiesworld.net/opinions/ opinions/why-smart-cities-need-smart-buildings

What actually is a smart city?

https://meetingoftheminds.org/exactly-smart-city16098

What are the appropriate mobility models for smart-city applications in IoT?

https://mobility.here.com/smart-city-mobility-7major-cities-getting-it-right

Is smart city a utopia or has it become a reality under a methodological process?

https://lists.w3.org/Archives/Public/semantic-web/ 2018Jul/0090.html

How can artificial intelligence impact smart cities?

https://becominghuman.ai/artificial-intelligencefor-smart-cities-64e6774808f8

What are some of the most recent advances and future research directions in smart-city transportation, by utilizing IoT infrastructures and cloud computing? Where are the smart-city monetization research boundaries?

https://www.mdpi.com/2079-9292/7/11/309/htm

How are ideas implemented with regards to research, case studies, and crowdsourcing for smart cities?

https://scielo.conicyt.cl/scielo.php? script 5 sci_arttext&pid 5 S071818762012000300006

https://www2.deloitte.com/us/en/pages/consulting/ solutions/next-generation-smart-campus.html

https://www.forbes.com/sites/ellistalton/2019/07/ 09/smart-cities-are-built-by-smart-people-notsmart-things/

https://thinkbigpartners.com/smart-city-datamonetization/

Appendix F: List of smart cities and critical infrastructure case studies John R. Vacca

Case studies

URL

Smart Cities: Case Studies—ResearchGate

https://www.researchgate.net/publication/310485601_ Smart_Cities_Case_Studies

International Case Studies of Smart Cities— Publications

https://publications.iadb.org/publications/english/ document/ International-Case-Studies-of-Smart-Cities-Rio-deJaneiro-Brazil.pdf

Examples and case studies— Smart Cities Council

https://smartcitiescouncil.com/smart-citiesinformation-center/examples-and-case-studies

Smart Cities and Infrastructure— UNCTAD Case Studies

https://unctad.org/meetings/en/Presentation/ ecn162016p01_Wu_en.pdf

Smart City trends-and-case-studies—Deloitte

https://www2.deloitte.com/content/dam/Deloitte/us/ Documents/process-and-operations/us-consdeloitte-smart-city-trends-and-case-studies.pdf

Case study examples of smart city initiatives in environmental sustainability Case Studies Smart Cities What’s In It For Citizens— Intel Newsroom: Case Studies

https://www.mdpi.com/2624-6511/2/2/19/htm

Smart Cities World: Case Studies

https://smartcitiesworld.net/AcuCustom/Sitename/ DAM/012/ Understanding_the_Challenges_and_Opportunities_ of_Smart_Citi.pdf

Trends in Smart City Development— National League of Cities: Case Studies

https://www.nlc.org/sites/default/files/2017-01/Trends %20in%20 Smart%20City%20Development.pdf

Bridging the smart cities security divide: Case Studies

https://www.csoonline.com/article/3252844/bridgingthe-smart-cities-security-divide.html

https://newsroom.intel.com/wp-content/uploads/sites/ 11/2018/03/smart-cities-whats-in-it-for-citizens.pdf

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700

Appendix F: List of smart cities and critical infrastructure case studies

(Continued) Case studies

URL

OCIA—The Future of Smart Cities—CyberPhysical Infrastructure Risk: Case Studies

https://www.us-cert.gov/sites/default/files/documents/ OCIA%20-%20The%20Future%20of%20Smart% 20Cities%20-%20Cyber-Physical%20Infrastructure %20Risk.pdf

Smart cities: Digital solutions for a more livable future—Case Studies

https://www.mckinsey.com/B/media/mckinsey/ industries/capital%20projects%20and% 20infrastructure/our%20insights/smart% 20cities%20digital%20solutions%20for%20a% 20more%

The Smart City as Global Discourse: Case Studies

https://www.tandfonline.com/doi/full/10.1080/ 10630732.2018.1558387

Smart cities and internet of things: Journal of Information Technology Case and Application Research A Risk Management Approach to Smart City: Case Studies

https://www.tandfonline.com/doi/full/10.1080/ 15228053.2019.1587572

Smart cities with big data: reference models, challenges, and case studies

https://www.sciencedirect.com/science/article/abs/pii/ S0264275117308545

5G security and privacy for smart cities: case studies

https://securelist.com/5g-security-for-smart-cities/ 95057/

A Guide to a Critical Infrastructure Security and Resilience—CISA: case studies

https://www.cisa.gov/sites/default/files/publications/ Guide-Critical-Infrastructure-Security-Resilience110819-508v2.pdf

Lack of Critical Infrastructure Cybersecurity Investments in Smart Cities: case studies

https://www.businesswire.com/news/home/ 20190820005103/en/Lack-Critical-InfrastructureCybersecurity-Investments-Smart-Cities

Global Innovators: International Case Studies on Smart Cities

https://assets.publishing.service.gov.uk/government/ uploads/system/uploads/attachment_data/file/ 249397/bis-13-1216-global-innovatorsinternational-smart-cities.pdf

Connected LED street lighting: Enabling smart cities: case studies

https://www.theclimategroup.org/sites/default/files/ downloads/tcg_smart_cities_introduction.pdf

Smart Cities Seoul: a case study

https://www.itu.int/dms_pub/itu-t/oth/23/01/ T23010000190001PDFE.pdf

Smart cities: five smart steps to cybersecurity: case studies

https://www.pwc.com/us/en/services/consulting/ cybersecurity/library/broader-perspectives/smartcities.html

Building Smarter Cities and Communities: case studies

https://www.comptia.org/content/research/buildingsmarter-cities-and-communities

https://pages.nist.gov/GCTC/uploads/blueprints/ 2019_GCTC-SC3_Cybersecurity_and_Privacy_ Advisory_Committee_Guidebook_July_2019.pdf

(Continued)

Appendix F: List of smart cities and critical infrastructure case studies

701

(Continued) Case studies

URL

ECSO Smart Cities Sector Report— European Cyber Security: case studies

http://www.ecs-org.eu/documents/uploads/smartcities-sector-report-032018.pdf

Data Sharing in Infrastructure— National Infrastructure: case studies

https://www.nic.org.uk/wp-content/uploads/Datasharing-in-infrastructure.pdf

Smart cities survey: Technologies, application domains and case studies

https://journals.sagepub.com/doi/10.1177/ 1550147719853984

Smart City Ahmedabad Development: Case Studies Case Studies in IoT for Smart Cities— Smart Cities India expo

https://www.nec.com/en/case/scadl/index.html

Reconceptualising Smart Cities—NITI: case studies

https://niti.gov.in/writereaddata/files/document_ publication/CSTEP%20Report%20Smart%20Cities %20Framework.pdf

Barriers to the Development of Smart Cities in Indian Context: case studies

https://link.springer.com/article/10.1007/s10796-0189873-4

The Smart Cities Mission in Delhi: case studies

https://www.orfonline.org/research/the-smart-citiesmission-in-delhi-2015-2019-an-evaluation-60071/

Smart Cities in India—India Smart Grid Forum: case studies

http://indiasmartgrid.org/event2017/09-03-2017/1.%20 Plenary%202-%20Smart%20Cities/6.%20Vishal% 20Sharma.pdf

Smart Cities Mission in India: case studies

https://www.emerald.com/insight/content/doi/10.1108/ SASBE-07-2018-0039/full/html

Quantitative analysis of the development of smart cities in India: case studies

https://www.emerald.com/insight/content/doi/10.1108/ SASBE-06-2019-0076/full/html

Head Smart Cities in India: case studies

http://search.proquest.com/openview/ b630eb47c05257bddc7c1121b65ebe2a/1?pqorigsite 5 gscholar&cbl 5 2029987

Smart and Sustainable Cities of the Future Key Initiatives: case studies

https://www2.deloitte.com/content/dam/Deloitte/in/ Documents/public-sector/in-gps-CIISmartCity_SustainableSmartCities.pdf

Smart City Emergence: case studies

https://www.sciencedirect.com/book/9780128161692/ smart-city-emergence

Smart Cities and the Idea of Smartness: case studies

http://iopscience.iop.org/article/10.1088/1757-899X/ 245/8/082008/pdf

Trends in Smart City Development— National League of Cities: case studies

https://www.nlc.org/sites/default/files/2017-01/Trends %20in%20Smart%20City%20Development.pdf

Smart Cities What’s In It For Citizens: case studies

https://newsroom.intel.com/wp-content/uploads/sites/ 11/2018/03/smart-cities-whats-in-it-for-citizens.pdf

http://www.smartcitiesindia.com/images/photogallery-2017/Room-B-Buildings-India/ IoT_enabled_ infrastructure_for_cities/Justin_Bean.pdf

(Continued)

702

Appendix F: List of smart cities and critical infrastructure case studies

(Continued) Case studies

URL

Insights into the incipient smart cities phenomena in India: case studies

https://smartech.gatech.edu/bitstream/handle/1853/ 58547/ zahra_jeena_insights_into_the_incipient_smart_ cities_phenomena_in_india.pdf

Analysing and Rating Smart City Development in India: case studies

https://www.krishisanskriti.org/vol_image/ 03Jul201503070817.pdf

India’s “smart” cities mission: case studies

https://www.tandfonline.com/doi/full/10.1080/ 07352166.2018.1468221?src 5 recsys

Smart Cities Seoul: A Case Study

http://icities4greengrowth.in/casestudy/smart-citiesseoul-case-study

Why the Smart Cities Mission will miss its deadline—India Today: case studies

https://www.indiatoday.in/india-today-insight/story/ why-the-smart-cities-mission-will-miss-itsdeadline-1574728-2019-07-29

Appendix G: Answers to review questions/exercises, hands-on projects, case projects, and optimal team case project by chapter

G.1

Chapter 1: Introduction to the critical success factors of e-government adoption of the utilization of emerging smart cities technologies

G.1.1 Review questions/exercises G.1.1.1 True/false 1. 2. 3. 4. 5.

True False False True False

G.1.1.2 Multiple choice 1. 2. 3. 4. 5.

D E A C B

G.1.1.3 Exercise G.1.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why it is critically important to advance a smart cities’ financial and policy planner’s understanding of the factors leading to success and failure; and to elaborate on the underlying enabling and inhibiting conditions. With respect to research and practice, it is extremely significant to avoid the pitfalls of imposing universal approaches to

704

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

smart cities research and policy practices. Rather, a smart cities financial and policy planner should be able to draw a distinction between specific (context-contingent) and generic (general) factors. With this fundamental understanding, a smart cities financial and policy planner should be able to define the kind of factors that have strategic importance; and which are irrelevant in terms of e-government policy formulations. Finally, a smart cities financial and policy planner should be able to provide a model for successful e-government implementation techniques.

G.1.1.4 Hands-on project G.1.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the implementation of e-government initiatives has become one of the main goals of many countries around the words. However, e-government implementation is not straightforward. Projects encounter different problems, be it in developed or developing countries. Many studies have focused on failed e-government implementation, while some focus on the critical success factors (CSFs) that lead to success. In other words, CSFs must be identified that could spur the growth and success of e-government. Finally, these CSFs have practical implementation and must be incorporated in e-government implementation plans.

G.1.1.5 Case projects G.1.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the high failure of e-government is a motivation to do the research and develop case studies about the CSFs of e-government implementation. Studying CSFs is an important issue that helps to implement e-government successfully and to avoid failure. There have been various CSFs of e-government implementation obtained from CSFs studies by other researchers, but give no overall big picture. The student should be able to synthesize some case studies to get a generic model of the CFFs for e-government implementation. Finally, a result should be obtained from the study in the form of synthesized success factors (SSFs), in which all government organizations and parties must adhere to, with regards to a successful e-government implementation.

G.1.1.6 Optional team case project G.1.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why political instability is often observed in the political will of e-government, and the political participation in the policy-making sense. The political conditions demand an awareness of the political value of e-government; a commitment

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

705

to e-government and good governance; and strong leadership skills. E-government implementation is often associated with organizational change in public organizations. It also has an impact on the availability of public e-services; not only for its citizens, but also for employees who will be the link between the employer and the end users (the citizens). Finally, internal financial problems, such as a lack of adequate funding arrangements have consequences for implementation, often leading to unfinished projects and higher maintenance costs.

G.2

Chapter 2: Smart-city infrastructure components

G.2.1 Review questions/exercises G.2.1.1 True/false 1. 2. 3. 4. 5.

True False True False True

G.2.1.2 Multiple choice 1. 2. 3. 4. 5.

B, D E B D A

G.2.1.3 Exercise G.2.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following partial list: G

G

G

G

G

G

G

G

G

G

Adequate water supply Assured electricity supply Sanitation, including solid waste management Efficient urban mobility and public transport Affordable housing, especially for the poor Robust IT connectivity and digitalization Good governance, especially e-governance and citizen participation Sustainable environment Safety and security of citizens, particularly women, children, and the elderly Health and education

706

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.2.1.4 Hands-on project G.2.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the geographic information system operational platform should be the base for managing the infrastructure development components with the systems interoperability for the available smart-city infrastructure-related systems. The concentration should be on the available utility networks in order to develop a comprehensive, common, standardized geospatial data models. The construction operations for the utility networks such as electricity, water, gas, district cooling, irrigation, sewerage, and communication networks are needed to be fully monitored on a daily basis; in order, to utilize the involved huge resources and manpower. These resources are allocated only to convey the operational status for the construction and execution sections that used to do the required maintenance. Finally, the need for a system that serving the decision makers for following up these activities with a proper geographical representation will definitely reduce the operational cost for the long term.

G.2.1.5 Case projects G.2.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following: Focus on why pairing devices and data with a smart city’s physical infrastructure and services can cut costs and improve sustainability. Together, these smart-city technologies are optimizing infrastructure, mobility, public services, and utilities. In addition to people, dwellings, commerce, and traditional urban infrastructure, there are essential elements that should be used and are necessary for successful smart cities. For instance, subscription-based models offer a way to monetize hardware and software that is used to build smart infrastructures and spread out expenses moving away from a huge one time capital expenses spend. Finally, there are essential technologies that should be used to make smart cities: smart energy, transportation, data, infrastructure, mobility, and devices.

G.2.1.6 Optional team case project G.2.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why urban smog is becoming worse, worldwide: breathing air polluted beyond safe limits. One answer would be to plant more trees, right? Unfortunately, smart cities’ limited free space means this is rarely a viable option. Finally, come up with a workaround that addresses the space issue by bringing together plant life and IoT technology to improve air quality without requiring vast amounts of land.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.3

707

Chapter 3: Smart buildings and urban spaces

G.3.1 Review questions/exercises G.3.1.1 True/false 1. 2. 3. 4. 5.

True False False True False

G.3.1.2 Multiple choice 1. 2. 3. 4. 5.

E A, B, C, D, E E B A, B, D

G.3.1.3 Exercise G.3.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why smart buildings and urban spaces, may contain thousands of sensors measuring various building operating parameters, including temperature, humidity, occupancy, energy usage, keycard readers, parking space occupancy, fire, smoke, flood, security, elevators, and air quality. These sensors collectively capture massive amounts of data that must be transmitted, stored, analyzed, and acted upon, often in real-time, to provide a truly smart building and urban space experience. These actions require thousands of actuators capable of exercising fine-granularity control over lighting, environment, security, safety, and building systems. Some of this processing and actuating is extremely time-sensitive, but some applications are so bandwidth-intensive that they would swamp the building’s fiber access bandwidth. Finally, this exercise is designed to give smart building and urban spaces technology suppliers the flexibility to collaborate with their customers to create more targeted, outcome-based solutions.

G.3.1.4 Hands-on project G.3.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why smart urban pioneers should try to inspire urban visionaries to come up with innovative ideas for urban space in order to make cities more livable.

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Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Urbanites who enjoy their own city’s everyday transformation and variety, find that ever increasing urbanization, also makes living in cities a stifling affair. In other words, smart city and urban visionaries should try to improve and rethink the urban environment and habitat with pioneering social, digital, technological, and creative concepts.

G.3.1.5 Case projects G.3.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. This case project should provide a snapshot of smart cities and urban spaces from different parts of the world, by exploring the differences in the approach of extensive use of information and communication technology (ICT). The case project should also explore the dimensions of smart cities and urban spaces in both developing and developed nations. It should also highlight the potential benefits from how developing and developed nations view the aspirations of their citizens (connected city, sustainable city, low carbon city, etc.) to target the prevalent issue and build solutions around it. Another focus of smart cities and urban spaces is to attract investment from all over the world and create global cities, by investing in services—such as high-speed Internet connectivity, intelligent transportation systems, and a high suitable economic climate. Finally, the case project should also show how cities have been transformed into social laboratories for innovating new ways of enhancing the quality of life for their citizens and piloting new initiatives.

G.3.1.6 Optional team case project G.3.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Today, various alternative approaches to smart cities and urban spaces can be observed. Focus on why these approaches have attracted various and significant cases, which either evolved into other forms or they later declined. These approaches are used to identify evolution roadmaps for smart cities and urban spaces, that can show how they have emerged and to which particular directions they are being evolved. The evolution roadmaps are depicted via a technology roadmapping tool. Finally, these roadmaps can become a useful tool for municipal decision makers, who have to choose between evolution forms and smart city and urban spaces projects that secure their viability.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.4

709

Chapter 4: Urban mobility systems components

G.4.1 Review questions/exercises G.4.1.1 True/false 1. 2. 3. 4. 5.

True True False False True

G.4.1.2 Multiple choice 1. 2. 3. 4. 5.

C A C E B

G.4.1.3 Exercise G.4.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Show how to keep private transport affordable or make it more efficient. Show how to make public transport available and convenient, but affordable. Show how issues such as electronic services and shared transport are more important than traditional spheres of authorities’ attention, such as road infrastructure.

G.4.1.4 Hands-on project G.4.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Show how current linear practices in urban mobility, such as a high dependence on individual car ownership and fossil fuels, have created high levels of congestion leading to wasted time and lost productivity, as well as pollution, noise, heat-island effects, and the depletion of finite resources. Discuss how dependence on individual cars in smart cities can also be a strain on household budgets that can lead to high amounts of urban land devoted to parking. With urbanization and the demand for urban freight rapidly increasing, the need for more effective urban mobility solutions is pressing. Finally, given the preceding, show how circular economy principles help design out waste and pollution; keep materials in use and at value; and regenerate natural systems that provide the much-needed solution.

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Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.4.1.5 Case projects G.4.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Do research on why congestion, energy consumption, pollution, and the need to increase transport system sustainability are top-priority problems in urban areas. Show how to reduce the negative effects of vehicles on the environment by increasing accessibility, optimizing economic resources in transport management, and improving citizens’ quality of life. In addition, show the type of incentives that can be given to attract passengers to transit; and disincentives for the use of private cars. In addition, analyze the most relevant aspects, such as restriction of vehicle access to a smart city center, road pricing, goods delivery reorganization, and the development of collective taxis; because, of their innovative features and their potential to achieve improvements. Furthermore, please discuss a suitable methodology, for controlling and validating all the implementation steps. Finally, please pay particular attention to the simulation of scenarios that can be used to assess the feasibility of pricing-related measures and how they can affect the built in environment. In other words, please outline possible users’ reactions to the restriction of policy changes.

G.4.1.6 Optional team case project G.4.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Show how to set a smart city on a sustainable course regarding its land use and transport systems through a clear roadmap: an urban mobility plan. In addition, lay out a vision for a smart city that prioritizes transport system improvements, clarifies the respective responsibilities of different stakeholders in implementing these initiatives, and identifies a robust financing plan.

G.5

Chapter 5: Coupling of the mobility and energy infrastructures as urban mobility needs evolve

G.5.1 Review questions/exercises G.5.1.1 True/false 1. 2. 3. 4. 5.

False True False True False

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G.5.1.2 Multiple choice 1. 2. 3. 4. 5.

A B A C E

G.5.1.3 Exercise G.5.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Take on a new perspective: think of capacity limitations in your city that you experience and try to take a different angle.

G.5.1.4 Hands-on project G.5.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Look at the category that the incentives are falling into. Look at the other measures that would be promising in your city. Look at why other measures are promising in your city.

G.5.1.5 Case projects G.5.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Do research on the Alliance website: https://ec.europa.eu/growth/industry/policy/ european-battery-alliance_de.

G.5.1.6 Optional team case project G.5.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Look at the factors or conditions that impacted their project outcome. Look at how this could be implemented in your home city.

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Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Chapter 6: Urban mobility system components

G.6.1 Review questions/exercises G.6.1.1 True/false 1. 2. 3. 4. 5.

True True True False False

G.6.1.2 Multiple choice 1. 2. 3. 4. 5.

B E B C A

G.6.1.3 Exercise G.6.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why current linear practices in urban mobility, such as a high dependence on individual car ownership and fossil fuels, have created high levels of congestion leading to wasted time and lost productivity, as well as pollution, noise, heat-island effects, and the depletion of finite resources. Dependence on individual cars in smart cities can also be a strain on household budgets, and can lead to high amounts of urban land devoted to parking. With urbanization and the demand for urban freight rapidly increasing, the need for more effective smart urban mobility solutions is pressing. Finally, circular economy principles to design out waste and pollution, keep materials in use and at value, and regenerated natural systems, provide the much-needed solution.

G.6.1.4 Hands-on project G.6.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Cities, which are hubs connecting various markets, will continue to grow, especially if they are governed to address the various diseconomies that come along with the growth. Focus on why these diseconomies are usually related to increasing costs of land, labor, housing, accessibility, or pollution. Nevertheless, there is a need for further complementary policies at the smart-city level to help create even more favorable conditions for enterprises to do business and for citizens to enjoy a good quality of life.

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The complementary policies are related to public infrastructure and services provided at the smart-city level, in particular: transport, housing, water and sanitation, waste management as well as access to work, information, education (access to opportunities). For example, urban transport policies should be oriented at enhanced mobility for ensuring better accessibility to the various markets. Finally, they should help by reducing the transport externalities such as traffic congestion, road crashes, and environmental pollution.

G.6.1.5 Case projects G.6.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why many cities across the globe continue to face challenges in reducing externalities. Due to traffic congestions, the markets accessibility within urban areas deteriorates rather than improves. Road crashes and pollution cause not only large costs, but also reduce the quality of life of citizens and hence impact negatively their well-being. While challenges are faced, a knowledge base should be developed to help authorities in implementing policies to foster more sustainable systems for urban transport and mobility. It should address the role of public transport and nonmotorized transport, for urban mobility and transfers. It should also specify how the quality of public transport and its infrastructure and networks, as well as how the infrastructure for non-motorized transport can impact the preferences for citizen’s mobility. Finally, it should further show the conditions necessary for preventing a false distribution of demand for mobility and urban transfers between the various transport modes.

G.6.1.6 Optional team case project G.6.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the implementation of the available knowledge base, supplies material for analysis to understand the degree of success and its underpinning conditions. It then helps to work out practical solutions for implementation scaled to the circumstances and size of a different smart city. To this end, you should try to promote both the available knowledge base and the lessons learned from its application. For the latter, you should offer the results from the analysis of urban transport systems across the globe, and draw attention to various features of the systems that may require changes for making the systems more sustainable. You should also look into traffic congestions, road safety and environmental pollution, including climate change, as well as the popularity of the nonmotorized transport for urban mobility. You should further consider the affordability of urban transport. Finally, this analysis should be developed for the benefit of authorities at different levels, with the aim of providing them with a knowledge and experience-sharing tool, on a sustainable urban transport system and its application at hand.

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G.7

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Chapter 7: Urbanization and smart cities

G.7.1 Review questions/exercises G.7.1.1 True/false 1. 2. 3. 4. 5.

True True False False False

G.7.1.2 Multiple choice 1. 2. 3. 4. 5.

D B D D C

G.7.1.3 Exercise G.7.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. As you do your research, make sure that you successfully cover all of the key issues, such as the following partial list of issues: G

G

G

G

G

G

G

Sustainable urban development Sustainable building and equipment Infrastructures and mobility Sustainability and circular economy Smart networks infrastructures Provision of urban services Citizens, government and data valorization

G.7.1.4 Hands-on project G.7.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Please expand on three layers that work together to make a city smart:

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1. Technology base: Includes a critical mass of smart phones and other sensors connected by high-speed communication networks, as well as open data portals. 2. Specific applications: Translating raw data into alerts, insight, and action requires the right tools (multiple domains: security, mobility, health, energy, water, waste, economic development and housing, and engagement and community); and this is where technology providers and application developers come in. 3. Public usage: Many applications succeed only if they are widely adopted by the public; and manage to change behaviors by giving users more transparent information they can use to make better choices.

G.7.1.5 Case projects G.7.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Develop a global comprehensive smart cities project approach initiative, aimed at improving key dimensions of cities in the following ways: 1. Urbanization of the environment (buildings, transportation, water, waste, energy services, information, and communications technology) 2. Governance (intersectorial cooperation; cooperation between national, regional, and local authorities; other stakeholders; and establishment of multistakeholder platforms) support to networking with other smart cities 3. Social capital (education, social, and gender equality) 4. Economic conditions (poverty reduction and employment generation) 5. Citizens’ experience 6. Urban tourism

G.7.1.6 Optional team case project G.7.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Here is a partial six-step iterative model approach for implementing urbanization and smart-city solutions that you must follow, for creating an efficient and scalable IoT architecture for a smart city: 1. 2. 3. 4. 5. 6.

Basic IoT-based smart-city platform Monitoring and basic analytics Deep analytics Smart control Instant interacting with citizens via user applications Integrating several solutions

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G.8

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Chapter 8: Priority activities for smart cities and the infrastructure

G.8.1 Review questions/exercises G.8.1.1 True/false 1. 2. 3. 4. 5.

False False True True False

G.8.1.2 Multiple choice 1. 2. 3. 4. 5.

D B D A C

G.8.1.3 Exercise G.8.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why many cities and communities are motivated by a vision of ubiquitous, smart infrastructure systems, and services, and view advances in networking and information technology as a way to increase efficiency, reduce costs, and improve quality of life for their residents. They seek to become “smart cities” and “smart communities” by embedding new digital technologies into their infrastructure, systems, and services to enhance existing, and develop new, city/community resources. Smart-city/community solutions are intended to enable new capabilities and opportunities—all in the face of limited budgets. Finally, the possible applications are numerous: citizen services, smart grids, intelligent transportation systems, and remote healthcare, to name a few.

G.8.1.4 Hands-on project G.8.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. The challenges range from technical to ethical, legal, and social, including cyber security; data sharing and analysis; privacy; public health and well-being; workforce and education needs; and cultural and socioeconomic considerations. Focus on why addressing these challenges requires new forms of cross-sector and cross-government collaboration, experimentation, knowledge sharing, and alignment.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

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A strategic plan should be developed that offers a high-level framework to guide and coordinate smart-city-/community-related initiatives, with an emphasis on local government and stakeholder engagement. Finally, coordinating efforts should help accelerate the development of smart-city/community solutions that maximize the value of investments and optimize benefits to residents.

G.8.1.5 Case projects G.8.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. The partial list of central goals that motivate a smart city’s/community’s strategic plan are to: G

G

G

G

G

Understand local needs and local goals Accelerate smart-city/community innovation and infrastructure improvement Facilitate cross-sector collaboration and bridge existing silos Boost exports and promote U.S. global leadership Focus on people-centered solutions that support job growth and economic competitiveness

G.8.1.6 Optional team case project G.8.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. A key objective of a smart-city/community strategic plan is to identify priorities for Federally funded research and development (R&D), as well as capacity-building, to help transform smart cities and communities and improve the standard of living. To do so, the following partial list of strategic priorities should be able to: G

G

G

G

Accelerate fundamental R&D for smart cities/communities Facilitate secure and resilient infrastructure, systems, and services for smart cities/communities Foster smart cities/communities through data and knowledge sharing, best practices, and collaboration Enable evaluation of progress and long-term growth of smart cities/communities

G.9

Chapter 9: Open data for smart cities

G.9.1 Review questions/exercises G.9.1.1 True/false 1. 2. 3. 4. 5.

False False False True True

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G.9.1.2 Multiple choice 1. 2. 3. 4. 5.

C A C A, B, C B

G.9.1.3 Exercise G.9.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why the urban environments have proved to be one of the main open data generators worldwide. Analyze this phenomenon, as well as presenting the latest findings and facts about smart cities themselves, the initiatives around them, the technology enabling this phenomenon, and the new kinds of businesses and start-ups, which are emerging worldwide.

G.9.1.4 Hands-on project G.9.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Start this project by presenting the current state of the art of Big Data and Open Data worldwide; and continue by proposing a line of development for these two topics that could positively impact the everyday life of citizens. Place particular emphasis on the results that emerged from the challenges posed by four enablers of Big Data and Open Data projects and initiatives: cultural enablers, organizational enablers, governance enablers, and technological enablers.

G.9.1.5 Case projects G.9.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. In a society in which values transparency or sustainable development, focus on why Open Data applications are very important tools in the construction of smart cities. Develop several applications that can search, collect, and analyze geo-located data by using public and private sources related to different institutions and/or companies that participate in the management of a city.

G.9.1.6 Optional team case project G.9.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following.

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Review some of the most pertinent issues within the literature and conduct interviews with organizations involved in the implementation of smart-city technologies. In other words, the aim of this case project is to identify ethical issues in the literature and if they correspond to those faced by organizations in practice.

G.10

Chapter 10: The role of citizens in smart cities and urban infrastructures

G.10.1 Review questions/exercises G.10.1.1 True/false 1. 2. 3. 4. 5.

True True True True True

G.10.1.2 Multiple choice 1. 2. 3. 4. 5.

E C E A D

G.10.1.3 Exercise G.10.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why the smart city is an umbrella for cities that use information technology to improve services and provide better quality of life for its citizens. Show how citizen participation is often highlighted as an important part of the smart-city concept. Finally, participation can be political—influencing political decision making, but also nonpolitical where citizens participate to help the city solve its problems.

G.10.1.4 Hands-on project G.10.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. You should be able to present an overview of technologies used for participation, including their strengths and weaknesses; discuss how different types of projects should be handled differently in the decision-making process; and present recommendations for how practitioners can set up citizen participation projects in smart-city initiatives.

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You also need to look at three different categories of participation: citizen competence and experience; data collection through citizens’ use of technology; and participation as a democratic value. Furthermore, you should be able to discuss how these categories can be understood in terms of: Who sets the agenda and who makes the final decisions in order to frame the project internally in the municipality; and externally, so that citizens participating know what the outcome of the project will be. Finally, you should make suggestions for technologies that could be used to collect citizen input in each of the three categories of participation.

G.10.1.5 Case projects G.10.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Show how to overcome the limitations of most of the existing approaches to measure smart cities that are limited to only certain aspects of cities’ “smartness.” In addition, show how the innovative elements of a framework, is its capacity to address the smart city’s capacity to benefit from the active participation of citizens in assessing the policy decisions and their sustainability over time. In addition, show how to test the applicability of a framework by using it to analyze case studies, concerning citizens’ participation in smart-city initiatives. Finally, examine how the results of a holistic framework, effectively covers all of the relevant aspects of citizens’ participation in smart cities initiatives. In other words, show how a holistic approach can give some new insights on the assessment of the smart cities capacity of delivering a public value by involving citizens in the value generation process.

G.10.1.6 Optional team case project G.10.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Show how a smart city should work towards improving the quality of its residents, and not just the ease of government operations. Thus, a smart city should also support the idea of sustainable development. Many aspects should be included in the case to make the city work as a smart city. Smart-city visions that are holistic, pluralistic, and citizen-centric—focusing on improving services and solving urban issues, will be most effective and cost-efficient in the long run. Finally, show how to prevent future problems by improving both the physical services and infrastructure, and the city’s sense of community.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.11

721

Chapter 11: Smart city and metropolitan governance

G.11.1 Review questions/exercises G.11.1.1 True/false 1. 2. 3. 4. 5.

False False False False False

G.11.1.2 Multiple choice 1. 2. 3. 4. 5.

A D A B E

G.11.1.3 Exercise G.11.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why continued urbanization around the world (and natural population growth), will be creating larger smart cities and local economic areas in the near future, particularly in developing countries. With improved transportation and communication technology steadily advancing, people are able to commute over longer distances from villages or towns to larger urban areas, and flows of people, goods, information, and capital are increasing. Finally, the economic links between the core and the periphery may become so close that one part cannot succeed without the other; and thus, they are perceived and behave as a single entity. Interdependencies characterize the formation and emergence of a metropolitan region.

G.11.1.4 Hands-on project G.11.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why smart government can be considered as a basis for developing smart governance, through the application of emergent information and communication technologies (ICT) for governing. Smart governance’s intelligent use of ICT to improve decision-making through better collaboration among different stakeholders (including government and citizens), can be strongly related to government approaches. In this case, ICT-based tools, such as social media and openness, can be factors that increase

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citizen engagement and support of the development of new governance models for smart government. Smart governance may also have an important role in smart-city initiatives, which require complex interactions between governments, citizens, and other stakeholders. Finally, smart-city governance contributes to developing a framework for building new; smart governance models addressing the challenges of the digital society; collaborative governance; information sharing; citizen engagement; transparency; and openness.

G.11.1.5 Case projects G.11.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Develop field applications for metropolitan governance; and provide a set of policy recommendations. Suggest options on how these recommendations can be turned into practical applications by governments in metropolitan regions; and how development organizations can most effectively support national or metropolitan level partners on the subjects of sustainability; equity; efficiency; transparency and accountability; and civic engagement and citizenship.

G.11.1.6 Optional team case project G.11.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the reality of investing in and implementing smart-city technologies still offers significant challenges to local governments. In order to understand the common challenges and solutions that cities face, do an analyses of how global cities are paving the way in smart-city investment. Core areas of interest during this research should include metropolitan governance and leadership models; the role of open data; smart-city projects underway; investment and business models; barriers to implementation; and future investment priorities. Finally, collect data using a mixed approach of desk research and semistructured interviews with core city stakeholders.

G.12

Chapter 12: Distributed energy in smart cities and the infrastructure

G.12.1 Review questions/exercises G.12.1.1 True/false 1. 2. 3. 4. 5.

True True False True True

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G.12.1.2 Multiple choice 1. 2. 3. 4. 5.

E C E E D

G.12.1.3 Exercise G.12.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Review energy-related work on planning and operation models within the smart city by classifying their scope into five main intervention areas: generation, storage, infrastructure, facilities, and transport. Also, develop more-complex urban energy models that integrate more than one intervention area, outlining their advantages and limitations, existing trends and challenges, and some relevant applications.

G.12.1.4 Hands-on project G.12.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Present a novel global control strategy for a distributed microstorage energy system, where renewable energies will play a specific key role, when it comes to handling energy storage systems (ESS) at houses within a smart residential area.

G.12.1.5 Case projects G.12.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the optimal planning and operation model should consider the uncertainty of the type of vehicle; availability and distance traveled; and how it manages the available resources to obtain the maximum benefit from the grid. Your results should show how the EVs assist to achieve greater benefits of the distributed resources.

G.12.1.6 Optional team case project G.12.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Your results should show not only the optimal sizing, but also how the optimal operation scheduling of the generation and storage systems are found. You should also develop an economic feasibility analysis, comparing the different technologies and defining the best option for a given scenario.

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G.13

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Chapter 13: Energy efficient automated warehouse design

G.13.1 Review questions/exercises G.13.1.1 True/false 1. 2. 3. 4. 5.

False False True False False

G.13.1.2 Multiple choice 1. 2. 3. 4. 5.

A D A A E

G.13.1.3 Exercise G.13.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why it is essential to this automated warehouse, to have the capacity to accommodate vertical storage, space for vehicle material movement, and anticipated high floor loads. You should include a wide range of storage alternatives, picking alternatives, material handling equipment and software that exist to meet the physical and operational requirements of an automated warehouse—where the proper integration of these features is essential. Make sure that your automated warehouse is flexible enough to adapt to future operations and storage needs.

G.13.1.4 Hands-on project G.13.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Your energy efficient automated warehouse software should be able to maximize the efficiency of your workflows to reduce cost and increase output without adding a headcount.

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G.13.1.5 Case projects G.13.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. In your automated energy efficient warehousing operation design, make sure that storage and retrieval systems lead to revising the storage assignment policies, so that the least amount of energy can be consumed by cranes for unit load movements. In addition, make sure that dedicated energy-based policies and related zone shapes are analyzed, with particular attention to the role of unit load weight and the design option of rack stratification from floor to ceiling. Furthermore, compare energy performance of dedicated, class-based, and random storage policies for different demand curves and rack shape. Finally, in order to enhance flexibility while maximizing energy efficiency, make sure that new dynamic energy-based policies are also introduced and evaluated.

G.13.1.6 Optional team case project G.13.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Show how photovoltaic installation can lead to both yearly total cost and energy savings. Use simulations to highlight how design and performance of the refrigerated energy efficient automated warehouse strictly depends on supply chain decision variables. In addition, discuss how photovoltaic integration can offer supply chain managers more opportunities to act on the storage temperature and the incoming product temperatures, that are strictly related to upstream and downstream stages of the whole cold chain. Attention should also be paid to system throughput, which presents an intermediate range for which the design optimization of volume and surfaces reduce the convenience of photovoltaic integration. Finally, use simulations on facility locations to reveal how different climate conditions affect the economic and environmental performance of the refrigerated energy efficient automated warehouses, as well as the specific carbon intensity and energy price

G.14

Chapter 14: Smart utilities

G.14.1 Review questions/exercises G.14.1.1 True/false 1. 2. 3. 4. 5.

True True True False False

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Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.14.1.2 Multiple choice 1. 2. 3. 4. 5.

E C D E D

G.14.1.3 Exercise G.14.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. The potential partial list of solutions for implementing new types of utilities technologies are as follows: G

G

G

G

G

G

G

A summary table of the total cost to build and maintain utilities in the study area over a 40-year construction period A synopsis of the evaluation team’s methodology and assumptions An overview of the technical characteristics, costs, and benefits of smart utilities technologies An analysis comparing old engineering methodologies to the smart utilities vision. New modeling outputs Find ways to enable the installation of new smart utilities technologies by identifying policy needs, new business practices, or engineering solutions Identify which newly contemplated engineering implementation solutions would be the most proficient in putting ideas into practice

G.14.1.4 Hands-on project G.14.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following: Connect various power plants; transformers; transmission and distribution lines; and meters to form a smart-grid line. Then, combine smart-grid lines to form a complex grid (which is very similar to what we have today), including coal-fired plants, natural gas, renewable hydroelectric energy, nuclear, wind, and solar power.

G.14.1.5 Case projects G.14.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following: Focus on why achieving the solutions for smart city-wide strategies that are related to smart utilities and infrastructure, requires a new model for utility planning and design that integrates infrastructure planning across smart-city departments; and facilitates the deployment of smart utilities technologies, such as district energy microgrids and green infrastructure. The strategies also result in the following partial list of engineering and policy recommendations for water, energy, telecommunication, and transit infrastructure, and aims to:

Appendix G: Answers to review questions/exercises, hands-on projects, case projects G

G

G

G

G

G

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Promote utilities that are easier to build, maintain and upgrade Reduce energy/water/telecommunication costs for residents and businesses Harden infrastructure against flooding and heat waves Attract businesses through world-class utility services Integrate cutting edge technologies for innovation Policy and standards to implement smart utilities

G.14.1.6 Optional team case project G.14.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. In order to develop a new model for smart utility design, planning, and construction, you must first implement the following partial list: 1. Design a new policy that will be launched as a 2- to 3-year pilot that should include informational education sessions with developers, engineers, architects, and city staff. 2. Create smart utility standards that set forth guidelines for planning and integrating smart utilities technologies, with existing utility infrastructure in existing or new streets, which, would include cross-section, lateral, and intersection diagrams of an ideal layout for underground services and right-of-ways. The smart utility standards would also serve as guidelines for developers, architects, engineers, and smart utility providers for planning, designing, and locating utilities.

G.15

Chapter 15: Smart cities and infrastructure standardization requirements

G.15.1 Review questions/exercises G.15.1.1 True/false 1. 2. 3. 4. 5.

False True True False True

G.15.1.2 Multiple choice 1. 2. 3. 4. 5.

D E D E C

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Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.15.1.3 Exercise G.15.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following Data aggregation services in a city may consist of the following partial list: G

G

G

G

G

G

G

G

G

G

G

Blood availability Ambulance or health mobile asset availability Entertainment spaces, tourist location, and tickets availability Workspace, house rent space, and tourist rent space availability Foodservices and cloud kitchen Availability of harvested energy and water Modes of traffic and sharing facility Education institute, courses, trainings, and teaching resource availability Local handicrafts, herbs availability Specialist services Parking, gas stations and EV charging points availability

G.15.1.4 Hands-on project G.15.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. A sample list of data sources with their data types and associated security guidelines is enclosed. Students are encouraged to expand on the detailed information on this list. S. no.

Data source

Data type

Data security

Data weening policy

1

Air quality

Data set

low

6 months to 1 year. Analyzed data only may be stored 6 months to 1 year. Analyzed data only may be stored 15 days. Only summary of tickets sold may be kept

2

Energy usage

Data set

Medium

3

Tickets data for entertainment places, tourist places Health data Rain fall data Food item usage/rate

Data set

low

Data set

High Low

4. 5. 6.

5 7 years

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G.15.1.5 Case projects G.15.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Support points: To be able to support tourism for a city, technology needs to be used to provide safety to tourists. The following partial list of use cases may be defined for a tourist where he may need help: 1. 2. 3. 4. 5. 6.

Travel to/from a location Stay at a location Visit to tourist location Visit to sanctuary location Medical Emergency Assets/luggage safety

The tourist looking for support may be asked to wear watch/jewelry item, which is able to track his/her location. Focus on why it is important to ensure that privacy of the tourist is not compromised; and that this watch/jewelry may have a feature to put the track mode on. Additionally, it may also have an emergency button, which can call out to location police. Emergency button may also be used to reach out to hospital. Tourists with some medical condition may be encouraged to wear sensor machines, which are able to transmit their medical parameters. The exceptions in medical parameters may be tracked. The software of phone can also be used for safety of tourist, with emergency setting and location tracking. This may also be used in case of medical emergency. Tourist may also want to use sensor-based trackers on their expensive assets/luggage items to minimize thefts.

G.15.1.6 Optional team case project G.15.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Smart-city technology services group can provide the following partial list of services and convert their group to a profit center: 1. Data aggregation application like parking, hotel or tickets availability, cloud kitchen, coworking space, etc. 2. Travel guidance 3. Special safety services for tourists 4. Energy usage guidance 5. Resource availability like blood bank, medicine, specialist, educational event, and charging station 6. Safety of school children 7. Special services for elders 8. Students are encouraged to detail above points (and more) for their project

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G.16

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Chapter 16: Securing smart-grid infrastructure against emerging threats

G.16.1 Review questions/exercises G.16.1.1 True/false 1. 2. 3. 4. 5.

True True False True False

G.16.1.2 Multiple choice 1. 2. 3. 4. 5.

E A E A B, C, D

G.16.1.3 Exercise G.16.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Look at the complexity of the smart-grid network and the vulnerabilities specific to this huge heterogeneous network. Next, look at the challenges that exist in securing the smart-grid network and how the current security solutions applied for IT networks are not sufficient to secure smart-grid networks. Finally, look at the current and needed security solutions for the smart gird.

G.16.1.4 Hands-on Project G.16.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. The main partial list of goals for smart-grid security are: 1. 2. 3. 4.

Measure the current security posture of the power grid Develop and integrate protective measures Implement attack detection and response strategies Sustain security improvements

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G.16.1.5 Case projects G.16.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Create security profiles for smart-grid components by providing guidance and security best practices from the following partial list of profiles: 1. 2. 3. 4. 5.

Strategy Profile and Guiding Principles Security Profile Blueprint AMI Security Profile Distribution Automation Security Profile Home Area Network (HAN) Security Profile

G.16.1.6 Optional team case project G.16.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on reviewing and discussing security requirements, network vulnerabilities, attack countermeasures, secure communication protocols, and architectures in the smart grid. In addition, provide a deep understanding of security vulnerabilities and solutions in the smart grid and shed light on future research directions for smart-grid security.

G.17

Chapter 17: Components of the smart-grid system

G.17.1 Review questions/exercises G.17.1.1 True/false 1. 2. 3. 4. 5.

True False True False True

G.17.1.2 Multiple choice 1. 2. 3. 4. 5.

A B A, C B A

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G.17.1.3 Exercise G.17.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. The communication components of a smart grid can include wireline and wireless methods, such as power line communication, IEEE 802.15.4 protocol-based technologies, and/or agent-based control mechanisms.

G.17.1.4 Hands-on project G.17.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Design a smart home test bed that is based on the pedagogical model of project-based learning (PBL). The proposed test bed would allow students to gain key knowledge in smart-grid topics, such as flattening demand peaks, real-time price response, wireless sensor networks, machine learning, pattern recognition, embedded system programming, user interface design, circuit design, and databases. The project should be well aligned with smart-grid initiatives; and should provide a platform for students to develop their creativity in engineering design. Finally, it should also offer real-life/hands-on examples to be used for raising general public awareness of energy conservation.

G.17.1.5 Case projects G.17.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. The student should provide an overview of the overall method used, and introduce the theoretical fundamentals behind the approach for the theory, distribution, and use of a smart-grid architectural model. Its usage is demonstrated in several European and national research and development projects. Finally, the student should provide an outlook about future trends, potential adaptations, and extensions, for a smart-grid architectural model.

G.17.1.6 Optional team case project G.17.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why an optional extended-detailed smart-grid distribution system model component includes an individual substation; transformer; feeder-level detail providing additional detail on distribution automation; Volt/VAR control; conservation voltage reduction; customer reliability valuations; and cost-minimizing distribution system upgrade strategies. In addition, the license fee for this optional component depends on each utility’s smart-grid distribution architecture.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.18

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Chapter 18: Introduction to energy management in smart grids

G.18.1 Review questions/exercises G.18.1.1 True/false 1. 2. 3. 4. 5.

False True False True True

G.18.1.2 Multiple choice 1. 2. 3. 4. 5.

E C A, D C B

G.18.1.3 Exercise G.18.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following: Focus on the potential benefits and technical problems of the evolution of smart grids, as well as on the evolution of active grids, microgrids, and virtual utilities, through the presentation of hypothetical scenarios.

G.18.1.4 Hands-on project G.18.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Smart-grid technologies are composed of: integrated communications; sensing and measurement technologies; advanced components; advanced control methods and improved interfaces; and decision support. Focus on why the smart grid must also be able to repair/fix itself; have consumer participation; resist attacks from hackers; have a high quality of power; accommodate generational options; enable the electric market; optimize assets; and enable a high penetration of intermittent generational sources. Finally, look at the smart-grid future; cost and benefit analysis; and citizens quality of life, prosperity, and health. In other words, can the smart grid provide citizens and businesses with a relatively clean, reliable, and affordable energy services?

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G.18.1.5 Case projects G.18.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why in order to ensure effective energy efficiency, you must use energy wisely. Therefore, it is necessary to manage smart grids in an effective and efficient manner. Thus, worldwide, smart grids are the most prominent of energy management systems. The most effective management of energy flow is by monitoring and controlling the energy consumption and production plants by the smart-grid system. For a power system to be operated in an efficient way, consumers, production centers, and electrical devices in smart grids, can communicate with each other in this way. Thus, available energy production becomes possible with consumption of values that can be adapted successfully. In an established smart-grid system, all energy sources (renewable and power plants) can be optimized for the reduction of the consumer’s energy needs to a lower degree.

G.18.1.6 Optional team case project G.18.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Analyze the role of storage systems in the development of smart grids. In addition, provide an analysis and a list of energy storage systems that are applied in smart grids. Finally, examine the various energy storage systems—ranging from electrical, electrochemical, thermal to mechanical systems.

G.19

Chapter 19: DER, energy management, and transactive energy networks for smart cities

G.19.1 Review questions/exercises G.19.1.1 True/false 1. 2. 3. 4. 5.

True False True True False

G.19.1.2 Multiple choice 1. 2. 3. 4. 5.

A, C D B, E E C

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G.19.1.3 Exercise G.19.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on the nature, scope, and pace of the changes that are creating new demands, challenges, and opportunities with respect to the electricity system that warrant an examination of transactive energy systems. You should look at transactive energy systems as a future pathway for utility and power system reform. The objective here should be to foster an efficient and reliable power system that would support sustainable economic development and social welfare.

G.19.1.4 Hands-on project G.19.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. In responding to a rapidly changing energy landscape, global utility regulators and stakeholders should evaluate the cost-effectiveness of developing a transactive energy system framework.

G.19.1.5 Case projects G.19.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Look at profit allocation: Which is due to a coalition between smart home micrgrids for ensuring the optimal use of installed resources in the whole multiple smart home microgrid system. Also, consider the demand fluctuations: show how energy production based on renewable resources in the multiple smart home microgrid system can be accomplished by the demand-side management strategies that try to establish mechanisms to allow for a flatter demand curve.

G.19.1.6 Optional team case project G.19.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. The numerical results of the simulation study should show the capability of a proposed algorithm to encourage market participation and improve profit for all participants. In essence, the impact of the load consumption shifting in a multiple smart home microgrid schedule, should also be considered, while conducting both individual and coalition operations.

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G.20

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Chapter 20: Managing the generation and demand inside the smart-grid structure

G.20.1 Review questions/exercises G.20.1.1 True/false 1. 2. 3. 4. 5.

False True True False True

G.20.1.2 Multiple choice 1. 2. 3. 4. 5.

D E A A D

G.20.1.3 Exercise G.20.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on the potential to further integrate variable renewable resources at a lower cost, so that the potential for the smart grid to enable change may be most visibly exemplified. Next, discuss why the renewable generation in one state or region that supports the energy needs in another state or region, could see a wider deployment of a fully functional smart grid. Finally, take a look at the more effective deployment at lower cost from an integrated smart-grid approach to all of the drivers and technologies, from microgrids; energy efficiency; smart appliances; zero-net energy homes to electric vehicles (EVs); and energy storage.

G.20.1.4 Hands-on project G.20.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the smart grid uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. Explore three major systems: smart infrastructure system, smart management system, and smart protection system. Look at possible future directions in each major system. For the smart infrastructure system: explore the smart energy subsystem, smart information subsystem, and smart communication subsystem. In addition, for the smart management system, explore the various management objectives, such as improving energy efficiency,

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

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profiling demand, maximizing utility, reducing cost, and controlling emission. Next, explore the various management methods to achieve preceding objectives. Finally, for the smart protection system, explore the various failure protection mechanisms, which improve the reliability of the smart grid, as well as the security and privacy issues in the smart grid.

G.20.1.5 Case projects G.20.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on identifying and discussing the barriers to overcome smart-grid deployment concerns, including consumer’s acceptance.

G.20.1.6 Optional team case project G.20.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. The solutions that address the challenges in four key smart-grid areas are: 1. 2. 3. 4.

Customer technology Operational/electrical technology Smart metering Information/data technology

Also, focus on the complexity surrounding smart-grid initiatives, implementations, and the unknown. Finally, provide additional possible flexible solutions for the smart grid, such as innovative technology and applications that increase efficiency; improve stakeholder satisfaction; and future-proof your organization with information that turns into power.

G.21

Chapter 21: Energy management of multienergy and hybrid energy networks in smart grids

G.21.1 Review questions/exercises G.21.1.1 True/false 1. 2. 3. 4. 5.

True True False True False

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G.21.1.2 Multiple choice 1. 2. 3. 4. 5.

E A B B E

G.21.1.3 Exercise G.21.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on including the concepts such as energy hubs, microgrids, virtual power plants, as well as various approaches and criteria for energy, environmental, and techno-economic assessments.

G.21.1.4 Hands-on project G.21.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on highlighting the opportunities that exist from unlocking the efficiency and flexibility potential that lies in other sectors that electricity interacts with. In addition, exemplify the technical, commercial, and regulatory challenges, benefits, and opportunities for the different levels of the energy chain, for the smart multienergy grid.

G.21.1.5 Case projects G.21.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on utilizing the multiobjective particle swarm optimization to minimize the operation cost of the microgrid and maximize the generated power by each source. In addition, minimize the operation cost of the microgrid with respect to the renewable penetration; the fluctuation in the generated power; uncertainty in power demand; and the continuous change of the utility market price. Finally, make sure that the optimization strategy makes the exact choice of sources in the right planning; chooses the power that must be created by each source; and the power that is required by the utility network.

G.21.1.6 Optional team case project G.21.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following.

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Focus on outlining the systemic approach that is required to address both the technical and nontechnical issues that are associated with the implementation of smart grids for renewables. In addition, provide a detailed review of smart-grid technologies for renewables, including their costs, technical status, applicability, and market maturity for various uses.

G.22

Chapter 22: Hybrid renewable energy systems, load, and generation forecasting, new grids structure and smart technologies

G.22.1 Review questions/exercises G.22.1.1 True/false 1. 2. 3. 4. 5.

True False True False True

G.22.1.2 Multiple choice 1. 2. 3. 4. 5.

A B C C A, C, E

G.22.1.3 Exercise G.22.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on improving the accuracy and the confidence level of forecasts, an, how critical it is to the goal of reducing the conventional reserve capacity that will result in substantial savings in capital and operating costs. Please see the following partial recommendations on how to solve this problem: G

G

G

Improve the accuracy of weather and wind forecasts in spatial and temporal resolution, and, on time scales from hours to days Improve the confidence level of the forecasts to allow system operators to reduce reserve requirements and contingency measures to lower and more economical levels Forecast providers, wind plant operators, and regulatory agencies should: Agree on and develop uniform standards for preparing and delivering wind and power generation forecasts G

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Wind plant operators and regulatory agencies should: Develop and codify operating procedures to respond to power generation forecasts Develop, standardize and codify the criteria for contingencies, the response to up- and down-ramps in generation, and the response to large weather disturbances Develop response other than maintaining conventional reserve, including electricity storage and transmission to distant load centers G

G

G

G.22.1.4 Hands-on project G.22.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on how smart grids use technologies to instantly relay information to keep systems operating at optimal efficiency; match supply with demand; and support well-informed decisions. These technologies can be implemented at the level of generation technologies to consumer appliances. For example, a smart transformer on the smart grid can allocate power to industries at more reliable prices, just as a smart appliance in a private home can switch on and off in response to varying electricity prices. The same smart transformer can also automatically notify smartgrid operators and repair personnel if its internal temperatures gets too high. Finally, a smart meter can measure and track the output of a rooftop photovoltaic (PV) system and send that data back to the utility, to make use of surplus or address gaps due to solar variability as required.

G.22.1.5 Case projects G.22.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on the wind speed and solar irradiance variables that are characterized with experimental data from a meteorological station; and the generators are sized according to the power demand. A management system based on multiagents should be designed in order to measure and control the loads inside a building. Finally, the knowledge base of the multi agent system should be aided with functions and a power generation forecast using neural networks.

G.22.1.6 Optional team case project G.22.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on the paradigm shifts that bring up numerous questions that will need to be answered. New financing approaches that answer these questions will need to be developed, in order to support the adoption of new technologies.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.23

741

Chapter 23: Smart lighting for smart cities

G.23.1 Review questions/exercises G.23.1.1 True/false 1. 2. 3. 4. 5.

True True True True True

G.23.1.2 Multiple choice 1. 2. 3. 4. 5.

B C D D B

G.23.1.3 Exercise G.23.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on the guidelines defined by the IP for Smart Objects Alliance (IPSO Alliance), in order to implement an interoperable semantic level for street lighting. Also, describe the integration of the communications and logic, over the existing street lighting infrastructure.

G.23.1.4 Hands-on project G.23.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on the different usage scenarios for internet-of-things enabled indoor and outdoor smart lighting systems. Also, provide an analysis of the power consumption. Finally, provide future research directions in smart lighting systems in the smart city.

G.23.1.5 Case projects G.23.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on how smart streetlights are playing a key role in the development of today’s smart cities. Next, look at how digital networks, embedded sensors, and smart streetlights can collect and transmit information that helps authorities to monitor and respond to different circumstances—from traffic and air quality to crowds and noise. Then,

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look at how smart streetlights also allow local governments to detect traffic congestion and track available parking spaces, among other key functionalities. Finally, look at how those digital networks can also remotely control smart LED lights (making them turn on and off, flash, dim, and more), offering smart cities the possibility to maximize low-energy smart lighting benefits while also improving pedestrian and bicyclist safety.

G.23.1.6 Optional team case project G.23.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on how smart cities can deploy a network of smart controllers, to automatically make second-by-second traffic lights adjustments, by reacting to changing traffic conditions in real time.

G.24

Chapter 24: Smart cities critical infrastructure recommendations and solutions

G.24.1 Review questions/exercises G.24.1.1 True/false 1. 2. 3. 4. 5.

True True False False True

G.24.1.2 Multiple choice 1. 2. 3. 4. 5.

E C A E A

G.24.1.3 Exercise G.24.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on providing a response strategy to first responders based on smart cities information flows. Next, where these information flows have been compromised, propose a robust infrastructure state preservation system to provide an interface to a failing critical infrastructure.

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G.24.1.4 Hands-on project G.24.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on smart-city networks, with special emphasis on energy, communication, data analytics, and transportation. Next, introduce each of these networks; identify the state of the art in them; and explore open challenges for future research. Then, look at the interdependencies between these networks, through realistic examples and scenarios, by identifying the critical need to design, develop, and implement solutions that value such dependencies. Finally, conduct cross-functional research across a smart city’s different interdependent networks.

G.24.1.5 Case projects G.24.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on ways to ease the implementation of smart cities. Show how to use the internet of things to create efficient, sustainable smart cities.

G.24.1.6 Optional team case project G.24.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on how artificial intelligence can be used to develop the many applications that will be needed for smart cities to solve the following real-world problems: G

G

G

Traffic monitoring and roadway analytics that determine roadway utilization; help optimize traffic patterns; and even detect traffic incidents in real time Parking systems that can monitor lot usage, calculate fees, and even help drivers locate empty spaces in real time Emergency response and management tools that leverage existing video systems to help first responders

G.25

Chapter 25: The city as a commons: the concept of common goods

G.25.1 Review questions/exercises G.25.1.1 True/false 1. 2. 3. 4. 5.

False False True True False

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G.25.1.2 Multiple choice 1. 2. 3. 4. 5.

A D B A B

G.25.1.3 Exercise G.25.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on how to manage or govern shared or common resources. Next, look at the collaborative and polycentric governance strategies that are already being employed to manage some natural and urban common resources, which can be scaled up to the smart-city level to guide decisions about how smart-city space and common goods are used; who has access to them; and how they are shared among a diverse population. Finally, explore what it might look like to manage the smart city as a commons, by employing urban collaborative governance—the sharing smart city and the collaborative smart city.

G.25.1.4 Hands-on project G.25.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on the process of reconstitution of urban commons resources. Next, describe a way to reclaim urban space, asserting rights to the smart city, in relation to the utility of the commons framework of how best to manage or govern shared or urban common resources. Finally, address the limitations and critiques, as well as outline further areas of research with regards to urban common resources.

G.25.1.5 Case projects G.25.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on design principles that can help smart cities to transition to a more fair, inclusive, sustainable, and resilient futures. Next, look at the existing patterns of urbanization and the contested nature of urban resources, such as public spaces; open or vacant land; abandoned and underutilized structures; and the aging infrastructure. Finally, show examples of how these resources can be governed as a commons in smart cities around the world.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

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G.25.1.6 Optional team case project G.25.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why smart-city design principles cannot be simply adapted to the city context without significant modification. Next, look at why smart-city design principles can lead to the production of very different urban commons governance devices, which need to be adapted to the local context and the needs of local communities. Then, group the forms of urban commons governance mechanisms and tools into four main categories: institutional, legal, financial and digital. Finally, give a brief description and examples of the four main categories; and explain how they manifest different design principles.

G.26

Chapter 26: Resilient future energy systems: smart grids, vehicle-to-grid, and microgrids

G.26.1 Review questions/exercises G.26.1.1 True/false 1. 2. 3. 4. 5.

True True True False True

G.26.1.2 Multiple choice 1. 2. 3. 4. 5.

E D C B C

G.26.1.3 Exercise G.26.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on why electric distribution companies incorporate public purpose smart microgrids, with accompanying distributed generation and energy storage systems, into their existing smart grid upgrade planning processes. Next, look at how local governments and emergency planners coordinate with public purpose smart microgrid operators to determine how such systems will be utilized during emergencies. Then, look at how state governments develop incentives that support the deployment

746

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

of public purpose smart microgrids, advanced controls, and energy storage systems. Next, look at how state governments’ smart microgrid deployment efforts must utilize existing energy efficiency incentives, as a means to reduce the distributed generation required to meet a local load. Then, look at why the continued deployment of distributed generation will have significant impacts on the smart grid. Finally, look at how state governments analyze and reform the current energy paradigm to allow for the successful integration of smart microgrids and distributed generation, while maximizing social benefits.

G.26.1.4 Hands-on project G.26.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on identifying the smart-grid areas where research is most prevalent. In addition, get a clear picture of potential synergies between labs for smart-grid knowledge sharing and enhancing their research efforts.

G.26.1.5 Case projects G.26.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on how energy storage, distributed generation, and smart microgrids technologies will evolve, given the rapid deployment of smart grids across the world. Next, look at how the industrial sector will most likely deploy the preceding technologies. Finally, examine the major benefits that can be obtained from the deployment of energy storage, distributed generation, and smart microgrids.

G.26.1.6 Optional team case project G.26.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on the evolution of advanced smart microgrids. Next, look at why advanced smart microgrids have been identified as being a necessary part of the modern electrical smart grid. Then, look at how the grid-interconnectivity advantages of advanced smart microgrids, will improve system energy efficiency, reliability, and provide enabling technologies for grid-independence to end-user sites. Next, look at how the value of smart microgrids to protect the nation’s electrical grid from power outages, is becoming increasingly important in the face of the increased frequency and intensity of events caused by severe weather. Finally, examine how new advanced smart microgrids, will enable the user, the flexibility to securely manage the reliability and resiliency of the system and connected loads.

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

G.27

747

Chapter 27: Connected autonomous vehicles in smart cities

G.27.1 Review questions/exercises G.27.1.1 True/false 1. 2. 3. 4. 5.

False True True False True

G.27.1.2 Multiple choice 1. 2. 3. 4. 5.

A A D C D

G.27.1.3 Exercise G.27.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on the smart mobility initiatives and the challenges for smart cities with connected and autonomous vehicles (CAVs). In addition, look at why CAVs are essential for smart maintainable development, as part of the intelligent transportation system (ITS).

G.27.1.4 Hands-on project G.27.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on location-based data that enables smart cities to determine which services could be useful for citizens at a certain time. For example, look at how to improve the citizens’ ability to navigate the most efficient routes and modes of travel. Finally, look at the various aspects of technologies that enable smart mobility in cities, including autonomous vehicles.

G.27.1.5 Case projects G.27.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following.

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Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Focus on the six levels of autonomous driving to explain why vehicles that include interactive advanced driver-assistance systems (ADASs); and cooperative intelligent transport systems (C-ITS) can be regarded as connected: G

G

G

G

G

G

Level 0: No automation. The majority of the cars on the road today belong to this category. Level 1: Driver Assistance. In a vehicle with Level 1 autonomy, the human driver is in control of either steering or acceleration/deceleration by using information about the driving environment. Level 2: Partial Automation. Driving mode controls both the steering and acceleration/ deceleration. Level 3: Conditional Automation. The vehicle’s automated driving system monitors the driving environment controlling the acceleration, braking, and steering. Level 4: High Automation. The system controls all aspects of the driving tasks. Level 5: Full Automation. The automated driving system is in operation full time.

G.27.1.6 Optional team case project G.27.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus in part, on the rapid smart urban development and sustainable transportation solutions. Next, look at autonomous vehicles (AVs) as a potential transportation solution for smart and sustainable development. Then, identify privacy and cybersecurity risks of AVs as crucial to the development of smart and sustainable cities, and examine the steps taken by governments around the globe to address these risks. Next, look at why AVs are essential for smart and sustainable development. Then, identify the aspects of privacy and cybersecurity in Avs that are important for smart and sustainable development. Finally, look at the efforts taken by federal governments around the globe, to address AV-related privacy and cybersecurity risks in-depth.

G.28

Chapter 28: Future developments in vehicle-to-grid (V2G) technologies

G.28.1 Review questions/exercises G.28.1.1 True/false 1. 2. 3. 4. 5.

True True False True False

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

749

G.28.1.2 Multiple choice 1. 2. 3. 4. 5.

B B E D E

G.28.1.3 Exercise G.28.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on an application for V2G residential chargers. Next, do an analysis on market drivers, products, and technology. Finally, provide the research analysis that is needed for the necessary resources within R&D for the next 30 years.

G.28.1.4 Hands-on project G.28.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on V2G’s potentiality as a revenue opportunity for plug-in electric vehicles owners. Next, look at V2G’s ability to provide ancillary services, such as load leveling, regulation and reserve. Then, look at V2G requirements such as mobility needs, charging stations availability, and appropriate plug-in electric vehicles aggregative architectures. Finally, look at V2G’s future developments.

G.28.1.5 Case projects G.28.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on why the lack of progress on vehicle-to-grid has led some to question the viability of the concept. Next, look at the major concerns with vehicle-to-grid that allows a utility to draw on energy storage from stationary vehicles, which in fact would increase the stress on batteries (being one of the most expensive parts of a vehicle). Finally, look at why it is still unclear who would cover the cost of battery replacements, and how vehicle owners should be compensated for taking part in vehicle-to-grid programs.

G.28.1.6 Optional team case project G.28.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following.

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Appendix G: Answers to review questions/exercises, hands-on projects, case projects

Focus in part, on the rapid smart urban development and sustainable transportation solutions. Next, look at autonomous vehicles (AVs) as a potential transportation solution for smart and sustainable development. Then, identify privacy and cybersecurity risks of AVs as crucial to the development of smart and sustainable cities, and examine the steps taken by governments around the globe to address these risks. Next, look at why AVs are essential for smart and sustainable development. Then, identify the aspects of privacy and cybersecurity in AVs that are important for smart and sustainable development. Finally, look at the efforts taken by federal governments around the globe, to address AV-related privacy and cybersecurity risks in-depth.

G.29

Chapter 29: Designing inclusive smart cities of the future: the Indian context

G.29.1 Review questions/exercises G.29.1.1 True/false 1. 2. 3. 4. 5.

True False True False True

G.29.1.2 Multiple choice 1. 2. 3. 4. 5.

C C A A A

G.29.1.3 Exercise G.29.1.3.1 Solution

The following is a partial exercise solution. The students should be able to expand on the following. Focus on an inclusive smart urban development integrated approach, which encourages an institutional delivery mechanism that brings together all institutions and stakeholders (government, the private sector, and civil society) who have the capacity to deliver systems for inclusive urban service delivery. Next, look at how this approach proposes that the capacity of the urban poor communities, slum networks, and nongovernment organizations, should be effectively used in conjunction with city governments and the private sector. Then, look at how this approach presents methods to gather the required information on a particular context and location; and how to decide priorities; and to plan, design, and implement inclusive smart urban projects. Next, look at how to create a record of the project design process that may be of use for

Appendix G: Answers to review questions/exercises, hands-on projects, case projects

751

others as well, to scale up activities; to consolidate information that may be dispersed across different institutions; and to support staff and other development partners to focus on the importance of inclusive smart urban development. Finally, look at the practical guidelines and criteria for inclusive smart urban development projects, and how they are designed to stimulate innovation in the solutions and approaches that define inclusive smart urban development projects.

G.29.1.4 Hands-on project G.29.1.4.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on showing possible solutions for a sustainable, inclusive, standard, and identifiable smart urban equipment that will differentiate it; enhance the public space; and the setting up of quality standards in smart cities.

G.29.1.5 Case projects G.29.1.5.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on the complex relationship between societal and spatial dynamics, asserting that segregation is produced through misinformed smart urban design. In addition, look at the importance of inclusive smart urban design and accessibility in a smart city, within the context of current global challenges.

G.29.1.6 Optional team case project G.29.1.6.1 Solution

The following is a partial project solution. The students should be able to expand on the following. Focus on the relationship between technological innovation and inclusive smart urban design in today’s smart cities. Next, look at smart-city design and implementation shortcomings, coupled with the digital divide between different population segments that might unintentionally leave some communities behind. Finally, look at some approaches that municipal governments can apply, to make digital solutions more accessible and useful for their residents.

Appendix H: Glossary

Accessibility The ability to reach desired goods, services, activities, and destinations (collectively called opportunities). Acute shocks Sudden, sharp events that threaten a smart city. Autonomous Vehicles Autonomous vehicles can assume decision-making and operational tasks, enabling drivers to become passengers, entirely disengaged from the demands of driving. Ballast An electronic device for HPS light that increases the voltage of the supply power up to thousands of volts in order to produce the lighting. Bicycle detection and actuation Sensors at regular traffic signals to alert the controller of bicycle crossing demand on a particular approach. Carbon credits A permit that allows a country or organization to produce a certain amount of carbon emissions and can be traded if the full allowance is not used. Controls Electronic technology that interfaces power to a light or light output electronics to a sensor or timer or remote human interface. Critical Infrastructure Systems and assets, whether physical or virtual, so vital to the United States that the incapacity or destruction of such systems and assets would have a debilitating impact on security, national economic security, national public health or safety, or any combination of those matters. Dimming Reducing light output. Disaster resilience A combination of a society’s preparedness for a hazard; their ability to mitigate, plan, and respond immediately and effectively to it; and their ability to recover and regenerate from the event. Driver An electronic device that converts line electricity into the form that is needed to drive HPS or LED lighting. Eco-smart city A human settlement modeled on the self-sustaining resilient structure and function of natural ecosystems. First and last mile Gaps in public transit that require individuals to use other forms of transportation such as driving their car or riding their bike. Green building An environmentally sustainable building, designed, constructed, and operated to minimize the total environmental impacts. High albedo pavement A special type of concrete pavement that reflects more light than dark-colored materials due to its lighter color. HPS (High Pressure Sodium) Lighting Lighting that uses an arc between electrodes in a sodium vapor environment to produce light from plasma. Intelligent Transportation System A system in which real-time data is gathered and used to inform automated decisions regarding the function of traffic-related infrastructure and hardware. Internet of Things (IoT) The interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data.

754

Appendix H: Glossary

LED (Light Emitting Diode) A semiconductor device (electronics) that produces light directly from electricity. Low carbon smart city A smart city that reduces its carbon footprint by focusing on renewable energy and mitigation measures. Luminaire A device consisting of a light source, optics (reflectors, lenses), driver electronics (ballast, driver), and a housing to protect the components that is used to produce light from electricity. Mobility The movement of people or goods. Modular bike share Is usually solar-powered, quick and cheap to install; has the ability to alter and move the stations; and typically does not require trenching, excavation, or other preparatory work. Normalcy bias The difficulty to comprehend the fact that a disaster is occurring. Open bottom catch basin A box that is put into the ground near areas of standing water to help facilitate proper water drainage and avoid property damage. Permeable pavement Can be asphalt, concrete, or pavers, that lets storm water filter through and drain into the ground, instead of collecting on hard surfaces or draining into the sewer system. Photocontrol An electronic circuit that senses the sun and turns off a luminaire. Positive Train Control A system of remote sensors and automated control devices primarily designed to stop or slow a train automatically to prevent dangerous situations. Resilient smart city A smart city that has developed capacities to help absorb future shocks and stresses to its social, economic, and technical systems and infrastructures, so as to still be able to maintain essentially the same functions, structures, systems, and identity. Sensor An electronic device that senses a parameter such as presence of a vehicle; presence of a pedestrian(s); sunset or sunrise; Wi-Fi; and Bluetooth, etc. Smart City An efficient city, a livable city; as well as, an economically, socially, and environmentally sustainable city. Smart connections A vital component of a smart city, incorporating transportation, online access, technology, and community. Smart Lighting Any lighting that turns on, dims, or turns off in response to a control. Smart Urban Mobility Finding new ways to improve the flow of traffic in cities and encourage more efficient use of transport infrastructure. Sustainable Urban Mobility Satisfies current mobility needs of smart cities without compromising the ability of future generations to meet their own needs. Traffic Vehicle movement. Transition smart city Refers to grassroot community projects that aim to increase selfsufficiency to reduce the potential effects of peak oil, climate destruction, and economic instability. Transportation Moving stuff and people. Urban resilience The ability to adapt to changing conditions and withstand and rapidly recover from disruption due to emergencies. Vehicle-to-Infrastructure Systems allow physical infrastructure to inform vehicles of their presence; and, provide additional data, and also allow vehicles to send information to the infrastructure. Vehicle-to-Vehicle Vehicles that talk to one another to provide data about speed, location, and other information. Vertical garden/farm An alternative form of farming stretching from the ground up, with the ability to be built in areas with limited soil space to grow crops.

Appendix H: Glossary

755

Urban Mobility Concept (UMC) An innovative mobility concept; characteristics of UMC include its suitability for short distance travel, for easy transport by train and the possibility to use it on public roads. Waste-to-energy Incineration of municipal solid waste that then uses the energy (in the form of heat) to produce electricity and/or steam for heating. Zero carbon smart city A smart city that runs entirely on renewable energy; it has no carbon footprint and will in this respect not cause harm to the planet.

Index

Note: Page numbers followed by “f,” “t,” and “b” refer to figures, tables, and boxes, respectively. A Absorption chiller, 461 465, 463f AC network, 476 477 Acceleration/deceleration values effects average net energy consumption vs. average cycle time, 288f on performance metrics, 287 288 Acceptance of M-government, 5 Access Map, 638 Accessibility, 89 91, 649 Accessibility, Adaptability and Affordability (3As), 649 Accessible India Campaign (AIC), 643, 651 Active citizens, 557 city of Verona and subsidiarity pacts with, 557 558 Active command mediation defense (A CMD) system, 369 377, 370f, 378f all-in-one substation gateway, 376 377 architecture and deployment options, 375 376, 376f artificial command-delaying, 371 375 bump-in-the-wire approach, 377 Active disturbance rejection control (ADRC control), 622 ADRC-controlled charging model, 622f Actuators, 636 Adaptability, 649 Adaptive control, 622 Adaptive lighting, 488, 491, 496 497 ADMM, 589 Adoption conceptual model of smart government, 9 of M-government in developing countries, 5 ADR. See Automated demand response (ADR)

ADRC control. See Active disturbance rejection control (ADRC control) ADS. See Automatic distribution system (ADS) Advanced control methods, 304 Advanced HVAC systems, 517 518 Advanced metering infrastructure (AMI), 308, 309f, 523 Advanced metering system infrastructure (AMSI), 251 252 Affordability, 90, 649 650 Agglomerations, 237 Aggregator applications, 348 model, 623 AI. See Artificial intelligence (AI) AIC. See Accessible India Campaign (AIC) Air infiltration, 262 Aisle-captive system, 270 272 Alexandria, USA, 638 Alexandria Commission on Aging, 638 All-in-one substation gateway, 376 377 Amazon, 269 AMI. See Advanced metering infrastructure (AMI) AMR. See Automatic meter reading (AMR) AMSI. See Advanced metering system infrastructure (AMSI) Analytical-based model, 272 ANN model. See Artificial neural network model (ANN model) Apartments/accesorias, 61 Application and data support layer, 334 AR/VR. See Augmented reality and virtual reality (AR/VR) ARENA 16.0 commercial software, 277

758

ARERA. See Italian Energy Authority (ARERA) Argumentation ethics, 406 Arrival rate effect change in average net energy consumption, 287f on performance metrics, 286 287 Artificial command-delaying, 371 375, 375f Artificial intelligence (AI), 122 123, 306, 347, 411 412, 475, 631 632 for smarter decisions in smarter cities, 353 Artificial neural network model (ANN model), 479 Asia-Pacific Economic Cooperation (APEC), 67 68 Asset management and data aggregation services, 346 Asset management systems, 401 Assistive technology (AT), 636 Augmented intelligence and analytics, 353 Augmented reality and virtual reality (AR/ VR), 335 Aurora generator test, 361 Autism specific principles, 638 AutoDR, 67 Automated demand response (ADR), 416 417 Automated garage entry, 338 Automated sensor-based street lighting system, 236 Automated storage and retrieval technologies, 269 Automated warehousing operation, 290 Automatic distribution system (ADS), 251 smarter home, 251 Automatic meter reading (AMR), 312 Automobile era, 92 Autonomous driving, 99 Autonomous intelligent control systems, 477 478 Autonomous vehicles in logistics, 123 AutoVots, 122 123 Average cycle, 279 286 time per transaction, 270, 277 Average daily power consumption, 456 457 Average energy consumption per transaction, 270, 279 286 Ayala Land, Inc., 77 78

Index

B B2G integration. See Buildings-to-grid integration (B2G integration) BACS. See Building automation control systems (BACS) Bandwidth, 420 421 Barangay, 74 Barcelona Lesseps Square example, 223 224 BAS. See Building automation systems (BAS) Base load, 417 418 Battery electric vehicles (BEVs), 131, 134 Battery management system (BMS), 425 426 Battery storage, 252 BEMS. See Building energy management system (BEMS) BERDE. See Building for Ecologically Responsive Design Excellence (BERDE) Best practices, 614 BEVs. See Battery electric vehicles (BEVs) BFP. See Bureau of Fire Protection (BFP) Bidirectional charger, 620 621 BIDs. See Business improvement districts (BIDs) Big data, 187 190 analytics, 422 distributed centralized AI and ML and blockchain, 422 Biomass, 391 boilers, 516 BITW approach. See Bump-in-the-wire approach (BITW approach) Blablacar, 116 117 BlackEnergy, 360 361 BLE. See Bluetooth low energy (BLE) “Blindsquare”, 239 Blockchain, 340, 422 Bluetooth, 392, 419 Bluetooth low energy (BLE), 419 BMS. See Battery management system (BMS); Building management system (BMS); Bus management system (BMS) Bologna regulation on public collaboration for urban commons, 548 553 Bottom-up approach, 547 551, 558

Index

Broadband, 351 Building, 37 Building Automation and Control System, 401 Building automation control systems (BACS), 66 Building automation systems (BAS), 57t, 58 Building energy management system (BEMS), 412 Building for Ecologically Responsive Design Excellence (BERDE), 68, 69t Building information modelling (BIM) and services, 39 Building management, 338 automated garage entry, 338 renewable energy and smarter energy utilization, 338 usage-based cleaning, 338 water conservation/harvesting, 338 Building management system (BMS), 55, 412, 415, 416f, 425 426, 519 520 Buildings-to-grid integration (B2G integration), 67 Bump-in-the-wire approach (BITW approach), 364, 377 Bureau of Fire Protection (BFP), 74 Burning building, 531 Bus management system (BMS), 528 Business continuity concerns of data hub, 354 Business improvement districts (BIDs), 548 549 Business models for utility industry, 321 323 C Cable TV (CATV), 60 Cameras, 533 Canadian Standards Association (CSA), 607 609 Cantiere Barca in Turin, 551 552 CAO. See City Assessor’s Office (CAO) Capability model of disability (CMD), 635 foundation, 635 636 Capex, 649 650 “Car as home” concept, 122 Car registration, 120 Car sharing, 116

759

CAR unit. See High-efficiency cogeneration unit (CAR unit) Car-pooling services, 116 117 Car2Go, 117 118 Carbon dioxide emission (ECO2), 262 Carbon dioxide sensor (CO2 sensor), 58 Carbon-free mobility plan, 258 259 Cars, improving connectivity via, 113 114 CATV. See Cable TV (CATV) CAV. See Connected and autonomous vehicles (CAV) CAV and transportation electrification and (CAVTE), 607 609 CC. See Creative Commons (CC) CCT. See Correlated color temperature (CCT) CCTV. See Closed-circuit television (CCTV) Cellular network, 359 360 5G/4G/3G, 420 421 Central unit, 317 Centralized system, 300 Cerebral palsy, 640 641 Certainty equivalent models, 572 CHAdeMO method, 138 Charge point operators (CPOs), 114 Charge points, 109 Charger control method, 622 623 Charging hubs, 114 115 Charging infrastructure, 120 Charging/discharging strategy, 623 626 game theory TOU, 625 626, 626f grid view, 623 time-of-use electricity price, 625 traditional TOU, 625 user view, 624 625 CHP system. See Combined heat and power system (CHP system) CIDs. See Community improvement districts (CIDs) CIIP. See Critical infrastructure information protection (CIIP) Citizen(s), 213 214 citizen-management intertwined, 294 in city, 221 223 communication center, 509 corruption and urbanism, 228 governance, 218

760

Citizen(s) (Continued) hybridizations and changes in citizen governance, 219 221 open government, 217 218 participation, 219, 254 superation, 230 232 passive to active citizens, 215 217 planning cases, 227 228 practical cases, 223 228 sensors, 45 smart city, 213 superation of citizen participation, 230 232 technological governance, 219 transparency and citizen role in urbanism and infrastructures, 228 230 urban infrastructures, 214 215 Citizenry engagement, 30 “City as Commons, The”, 548 549, 551 553 City Assessor’s Office (CAO), 74 City Mapper, 118 City of Milan, 559 560 City of Turin, 559 560 urban innovative action in, 555 557 City of Verona with active citizens, 557 558 City Planning and Development Office (CPDO), 74 City services’ architecture and assets management, 346 350 asset management and data aggregation services, 346 CCTV across cities, 347 cloud kitchens, 348 connectivity of assets across city and managing solar lights/energy storage, 348 disaster/emergency management and emergency response teams, 347 manpower skill database, 347 smart entertainment, 348 smart governance, 349 350 solid waste management and zero waste policy and green houses, 348 streetlights, 347 tourist spots and hotel management, 347 City/cities, 235, 400 assets, 348

Index

benefit from cooperation on smart city subject in metropolitan area, 236 237 data, 331 financial capacity among cities common challenge, 237 intermunicipal coordination increases overall productivity, 237 management, 294, 411 City4Age, 638 Civic crowdfunding commons and, 558 559 institutions role in promoting, 561 Civil society organizations (CSOs), 546 Clean technologies application, 254 CLLD. See Community Led Local Development (CLLD) Closed-circuit television (CCTV), 57 cameras, 335 336 across cities, 347 Cloud computing, 293, 631 632, 636 Cloud environment, 490 Cloud kitchens, 348 Cloud systems, 411, 421 CMD. See Capability model of disability (CMD) Cocity index, 554 555 Cognitive ICT-based solutions, 651 652 Coherence axioms, 585 Coherent risk measure, 584 Collaboration, 548 549 across jurisdictions level of trust, 241 parochialism phenomenon, 241 prerequisites for effective teamwork, 241 242 proposal, 557 “Collective intelligence” concept, 217 Collective transportation, 93 Color, 492 493 Combined heat and power system (CHP system), 321, 448, 461 465, 463f Comma-separated value files (CSV files), 193 Command authentication using power flow dynamics simulation, 368 369 systems, 365, 375 376 Commercial buildings, 55, 60, 64 65

Index

Commercial off-the-shelf (COTS), 495 Commons, 543 545 Bologna regulation on public collaboration for urban commons, 548 553 to city as commons, 553 554 city of Verona and subsidiarity pacts with active citizens, 557 558 and civic crowdfunding, 558 559 institutions role in promoting, 561 cocity index, 554 555 coproduction and European Social Fund, 547 548 and European Union, 546 547 good exploitation, 543 guidelines, 543 544 Italian practices in matching public funds with private ones, 559 560 Italy and, 551 552 and OECD, 546 urban innovative action in city of Turin, 555 557 Commons Agenda, 543 544 Commons Intergroup, 543 544 Communaute´ urbaine, 238 239 Communications, 235, 386, 411, 508 511 channels for, 509 510 flexibility of communication systems, 509 510 environment for critical infrastructures, 511f layer, 334 medium, 317 recommendations and solutions, 510 511 overview, 508 509 safety and security of communication systems, 510 Community engagement, 29, 332 333 Community improvement districts (CIDs), 548 549 Community Led Local Development (CLLD), 547 548 Comprehensive arrangements, 240 241 Condensing boilers, 321, 322f Conditional risk mapping, 586 587 Conditional value-at-risk or expected shortfall, 585 Connected and autonomous vehicles (CAV), 599

761

CAVTE, 607 609 components of smart city, 600 601 functional architecture, 601 605 control, 604 605, 605f localization, 602, 603f path planning, 603 604, 604f perception, 602, 604f functional diagram, 603f health benefits in smart city, 608f integrated test platform, 608f integration with smart grid, 606f one-UN approach to smart city, 601f and smart energy, 605 606 and smart health, 607 and smart home, 606 607 and smart mobility, 605 USDOT vision elements for smart-city development, 602f Connectivity, 386 of assets across city and managing solar lights/energy storage, 348 and data hub, 351 Consortium, 238 239 Constitutive equations, 450 nonlinearity in, 450 451 Consumers, 411 electricity services, 303 engagement, 310 load management policy, 441 Contemporary intelligent methods, 479 Conto Termico, 466 Contracting models, 259 Control(s), 489 of CAV, 604 605, 605f center function, 236 control-oriented stochastic modeling, 572 574 methodologies, 490 492 schemes, 424 425 Controllable components, 450 451 Conventional energy sources, 433 Conventional planning approaches, challenges with, 144 Convolution operation, 582 Coproduction, 547 548 Coresponsibility, 547 Correlated color temperature (CCT), 487 488 Corruption, 228

762

Cost function, 453 in XEMS13, 453 COTS. See Commercial off-the-shelf (COTS) CPDO. See City Planning and Development Office (CPDO) CPOs. See Charge point operators (CPOs) CrashOverride malware, 361, 364 365 Creative Commons (CC), 191 Crime prediction, 533 Critical city infrastructures, 503 508, 505f identification, 504 507 interdependencies, 506f multisector interdependencies, 507f overview, 504 protection, 507 508 Critical infrastructure information protection (CIIP), 511 Critical infrastructures. See Critical city infrastructures Critical service providers and contractors, 297 298 Critical situations, 503 504 Critical thinking, 165 166 Critical utility infrastructures, 508 509 Cross-organizational smart cities project, 255 Cross-sectorial smart cities project, 255 CSA. See Canadian Standards Association (CSA) CSOs. See Civil society organizations (CSOs) CSV files. See Comma-separated value files (CSV files) CTG input, 371 372 Culture, 31 32 cultural facilities, 41 Curse of dimensionality, 584 Customers, 412 requirements and expectations, 320 Cyber risk, 614 Cyber threats targeting smart grid, 360 361 aurora generator test, 361 Ukraine power plant attacks, 360 361 Cyber-physical integration, 413 Cyber-security and federation, 421 solutions, 361 Cycle power plants, 298

Index

D DA. See Distribution automation (DA) DAC. See Differently abled communities (DAC) Data, 503 acquisition command authentication, 365 368 analytics, 510 block, 647 capture block, 646 diode devices, 362 363 hierarchy, 422 infrastructure, 351 marketplaces, 204 206 monetization, 332 333 privacy requirement, 340 sharing and compilation, 503 silos, 202 storage block, 646 647 weening policy, 354 Data Catalog Vocabulary (DCAT), 192 193 Data Catalog Vocabulary-Application profile (DCAT-AP), 192 193 Data hub, 333, 351 security, privacy, and business continuity concerns of, 354 Data-based decision block, 647 648 Data-based supervisory and control system, 312 313 DC. See Direct current (DC) DCAT. See Data Catalog Vocabulary (DCAT) DCAT-AP. See Data Catalog VocabularyApplication profile (DCAT-AP) Decentralization decentralized power generation, 400 of energy systems, 99 Decision Support and Integrity Protections, 401 Decision-making, 240 241 Delay control commands, 374 375 Delay law-enforcement teams, 259 Delhi Transport Corporation (DTC), 642 Demand demand-side management, 440 441 management, 253 pattern, 417 Demand response (DR), 55, 299, 411, 440 policy, 441

Index

program, 67 support, 400 systems, 249, 399 400 Demand side management (DSM) techniques, 442f Demarcation, 235 Deontological ethics, 406 Department of Public Work and Highways (DPWH), 68 Departure, 38 DER. See Distributed energy resources (DER) Deterministic models, 572 573 Device maintenance, 320 DH network. See District heating network (DH network) DHC network. See District heating and cooling network (DHC network) Diagonal Avenue referendum in Barcelona, 224 227 Differently abled communities (DAC), 631 632, 634 635, 637 Digital education, 28 Digital revolution, 236 Digital systems and components, 418 423 IoT communication technologies for TEN, 419 421 for energy, 418 419 for home and building automation, 418 and sensors, 418 Digital technology, 391 Digital transformation, 411 Digital twins (DT), 589 590 approach, 589 590, 590f Digitalization, 202 Digitization, 412 413 and smart systems, 411 Dimmable driver, 489 Dimming, 489 Direct current (DC), 57 DC DC converter, 622 network, 476 477 Directives, 614 615 Disaster early warning systems, 533 534 management, 333 planning and management system, 348 Disaster recovery (DR), 421

763

Disaster/emergency management, 347 Disease management, 339 Dispatchable components, 450 451 Dispatchable module, 450 451 Distance services, 30 Distributed centralized AI and ML, 422 Distributed energy in smart cities and infrastructure energy efficient designs of sustainable buildings, 260 265 energy storage, 249 energy strategy, 255 257 factors affecting energy in smart city, 257 259 instrumental procedures in smart cities, 252 255 selection of smart cities standards, 255 smart and sustainable balance, 250 smart cities, 250 252 smart microgrids, 249 250 smart-city hacking, 259 260 Distributed energy resources (DER), 67, 300, 387, 411, 414 417 Distributed generation, 391 Distributed power generation, 251 Distributed service operators (DSO), 421 Distribution, 385, 433 434 Distribution automation (DA), 300 and protection, 401 Distribution management system (DMS), 401 Distribution network (DN), 299 Distribution System Operators’ Association (DSOs), 387 District heating and cooling network (DHC network), 448, 454t, 455, 455f, 457 458, 519 demand and losses, 457f electric load profiles for pumping systems, 459 District heating network (DH network), 454 455 DMS. See Distribution management system (DMS) DN. See Distribution network (DN) Dominant energy storage technology, 399 DPWH. See Department of Public Work and Highways (DPWH)

764

DR. See Demand response (DR); Disaster recovery (DR) Drivers, 487 489 DSG. See Dubai Smart Government (DSG) DSO. See Distributed service operators (DSO) DSOs. See Distribution System Operators’ Association (DSOs) DT. See Digital twins (DT) DTC. See Delhi Transport Corporation (DTC) DTE Energy, 515 516 Dubai Smart Government (DSG), 6 8 Dynamic optimization, 583 584 E E-administration, 4 E-bus, 335 336 E-buses/E-rickshaws/cycle, 334 E-business and finance, 31 E-charging stations management, 337 E-communication, 46 E-connection, 40 E-democracy, 4 E-governance, 4, 30, 643 644 E-government, 3 4, 29 30 adoption factors, 7t critical success factors for, 5t services, 4 E-mobility. See Electric mobility (Emobility) E-rickshaws, 335 336 “E.ON SolarCloud Drive”, 115 Eastbrook’s home building process, 301 Eco-conscious homeowners, 249 Economic growth, 293 integration, 236 237 regulation, 303 sustainability, 301 Economic model predictive control (EMPC), 575 Eden Strategy Institute, 173 Edge computing, 493 Education, 28, 342 and incentives for clean vehicle drivers, 119 120 “Efficient DHC”, 468 469 Egyptian civilization, 185

Index

EISA. See Energy Independence and Security Act (EISA) Elderly population, 631 632, 634 635 Electric cars, 130 Electric LCVs, 131 132 Electric mobility (E-mobility), 37 38, 107, 130 132, 599. See also Smart mobility; Urban mobility applications, 107 electric vehicles supporting energy ecosystem, 115 116 electrified car-sharing models, 117 118 examples of shared mobility, 116 117 green charging, 115 necessity of charging hubs, 114 115 optimal charging solutions for, 114 rise of mobility service platforms, 118 Electric power systems (EPSs), 385, 475, 477 Electric streetcar or tram era, 91 92 Electric vehicle supply equipment (EVSE), 109, 129 130 Electric vehicles (EVs), 55, 99, 108 109, 129 130, 249, 252, 337, 385 387, 388f, 411 412, 518, 526 527, 576, 613, 616 617 BEV, 134 charging modes, 135 138 commercial use, 111 connector type, 136 138 electromobility cities, 111 EREV, 134 FCEV, 134 growth in share, 577f HEVs, 133 injection parameters, 581 mitigating air and noise pollution, 111 PHEV, 133 134 smart charging, 387 supply equipment, 135 supporting energy ecosystem, 115 116 sustainability, 111 112 types, 132 134 Electric Vehicles Initiative (EVI), 131 Electrical/electricity, 293 295, 300 312, 359, 512 520, 527, 613 advanced control methods, 304 advantages of SG, 306 307 consumption, 297, 415

Index

distribution network, 513 DN, 306 energy, 294 frequency, 366 generation, 385 by power plants, 302 generation, transmission, and distribution, 302f grid, 249 infrastructure, 302 303 integrated communication, 310 network, 385 ongoing failures of existing networks, 304 overview, 300 302 producers and distributors, 310 production, 300 301, 465 regulations and standards, 303 review of state-of-the-art studies, 310 312 SG, 306 in SGs, 299 smart distribution, 307 308 smart energy hub, 305 306 smart metering, 308 310 smart stations, 307 systems, 310 Electrification, 252 of motorized public transportation, 526 527 Electrified car-sharing models, 117 118 Electro-mechanical elements, 390 391 Electronic industry, 301 Embedded computing, 636 Emergency, 41 management, 349 response optimization, 530 531 teams, 347 services, 529 534 crime prediction, 533 disaster early-warning systems, 533 534 fire detection and prevention, 529 530 first-aid alerts, 530 IoT-based emergency care delivery process, 531f recommendations and solutions, 531 534 smart surveillance, 533

765

Emergency response teams, 347 Emission reduction, 251 EMPC. See Economic model predictive control (EMPC) EMS. See Energy management systems (EMS); Environmental management system (EMS) Enablers, 169 173 smart government, 169 170 smart incorporated city planning, 170 173 standardization, 170 End-to-end modern water management systems, 312 End-use equipment energy efficiency, 260 End-users, 252 253 Energy, 35, 250 251, 297, 433, 512 520 affecting factors in smart city, 257 259 carbon-free mobility plan, 258 259 global governance of energy, 258 plan new neighborhoods, 259 public exemplary plan, 258 base line of energy assessment, 402 consumption, 260 261, 287 per transaction, 279 declaration of existing buildings, 263 264 of new buildings, 264 265 demand, 572 dependency, 295 efficiency, 259, 400 policy, 441 practices, 252 standards, 260 infrastructure, 108 IoT for, 418 419 management layer, 571 572 market, 433 434 microgrids, 514, 515f and mobility sectors to urbanization and clean trends, 110 114 natural gas, 515 516 network, 447 changing face of, 571 574 control-oriented stochastic modeling, 572 574 overview, 512 performance of system components, 262 prices, 460

766

Energy (Continued) recommendations and solutions, 517 520 advanced HVAC systems, 517 518 district heating and cooling, 519 sector coupling, 519 520 refurbishment plan of buildings, 259 renewable energy resources, 516 smart-grid infrastructure, 512 513, 512f system usage in world, 513 514 storage, 249, 399, 518 with grid integration, 252 systems, 312 strategies, 255 257, 404 of companies, 405 European policies, proposals, and initiatives, 256b systems, 307 use, 386 vector balance equations, 451 452 Energy efficient automated warehouse design FEM statistics report, 270f literature review, 272 273 results and discussion, 279 288 graphical results and comments, 279 288 results for designs, 280t, 282t, 283t simulation modeling of system, 277 279 system description and model assumptions in system, 273 276 tier-captive SBS/RS, 271f Energy efficient designs of sustainable buildings, 260 265 agenda for action for international collaboration issues, 264b energy declaration of existing buildings, 263 264 of new buildings, 264 265 energy-efficient buildings, 263 holistic (overall) approach, 261 262 literature review and background, 260 261 Energy Hub, 447 Energy Independence and Security Act (EISA), 308 Energy Internet, 479 Energy management, 401 402, 435 436 base line, 402

Index

challenges, 403 406 agenda for action for energy management savings and rationalization, 403b energy strategies, 404 energy strategies of companies, 405 ethical and normative basis of energy strategies, 405 406 political energy strategies, 405 in operational functions, 402 403 organizational integration, 402 standards, 406 407 techniques in smart grid, 436 439 GSM communication, 437 remote energy management system using smart meter, 439 SCADA, 437 438 ZigBee network interfaced with field programmable gate array, 436 Energy management systems (EMS), 57t, 58, 299, 389 390, 401, 406, 414, 447, 477 478 case study, 454 469 adding local boiler, 461, 463f addition of CHP, absorption chiller, and storage, 461 465, 463f addition of heat pump, 464f, 466 addition of solar heating, 464f, 466 energy prices, 460 hourly load profiles, 458 459 installed power capacities, 462t optimal scheduling, 457 458 proposed configurations, 460 461 results, 466 469 XEMS13 optimization procedure, 449 454 Energy performance of buildings directive agency (EPBDA), 403 Energy Star, 66 Energy-efficient buildings, 263 energy network, 306 practices, 252 smart street lighting, 294 Energy-plus-houses, 403 Enforcement, 350 Entrepreneurship, 32 Environmental datum, 450 451 Environmental management system (EMS), 406

Index

767

Environmental sustainability, 253 254 EPBDA. See Energy performance of buildings directive agency (EPBDA) EPSs. See Electric power systems (EPSs) ERDF. See European regional development fund (ERDF) EREV. See Extended range electric vehicle (EREV) ESF. See European social fund (ESF) Ethical and normative basis of energy strategies, 405 406 EU. See European Union (EU) European Crowdfunding Center, 559 560 European economy, 255 257 European Materials Handling Federation, 269 European policies, proposals, and initiatives, 256b European regional development fund (ERDF), 555 557 European social fund (ESF), 546 548 European Union (EU), 638 Commons and, 546 547 path, 194 195 EVI. See Electric Vehicles Initiative (EVI) EVs. See Electric vehicles (EVs) EVSE. See Electric vehicle supply equipment (EVSE) Execution, 350 Executive saloons, 122 Existing cyber-security solutions limitations, 364 365 Extended range electric vehicle (EREV), 132, 134 eXtensible Mark-up Language (XML), 192

Fine-grained sensor networks, 338 Fire detection and prevention, 529 530 First order Taylor’s series approximation, 456 457 First-aid alerts, 530 First-in-first-out scheduling rule, 274 5G cellular technology. See Fifth-generation cellular technology (5G cellular technology) Five-star Linked Open Data, 194 Flexibility of communication systems, 509 510 Flexible future smart-grid systems, 575 Flexible information communication infrastructures, 509 510 Flexible load shape, 443 Flexible transportation system (FTS), 527 528 Flexible workplaces, 34 Flixbus, 118 FlixTrain, 118 FPGA. See Field programmable gate array (FPGA) Free-balancing approach, 273 Freeway era, 92 Freight transportation, 93 94 Frictionless payments, 172 FTS. See Flexible transportation system (FTS) Fuel cell electric vehicle (FCEV), 132, 134 Fully automated DR, 67 Fuzzy control, 622 Fuzzy marketing principle, 213 Fuzzy-controlled active state-of-charge controller, 622 623

F Facebook, 479, 552 FCEV. See Fuel cell electric vehicle (FCEV) Federation, 421 Fiber-optical networks, 311 312 Field programmable gate array (FPGA), 436, 437f Fifth-generation cellular technology (5G cellular technology), 421 Finance energy sector expansion, 260 261 Financial capacity among cities common challenge, 237 Financial purchase incentives, 120

G G2V technology. See Grid-to-vehicle technology (G2V technology) G3ict. See Global Initiative for Inclusive ICTs (G3ict) Game theory TOU, 625 626, 626f Gas, 512 520 waste, 36 Gestore dei Mercati Energetici S.p.A., 460 Gate stations, 319 Gateway, 369 370, 490 Gearing-up for smart health in cities, 343 346

768

Gearing-up for smart health in cities (Continued) expected benefits of applications in smart city, 346 technology environment for smart healthcare, 344 346 Generation, 433 434 Generic Object Oriented Substation Events (GOOSE), 359 Generic power conversion module, 450, 450f Geographical information systems (GIS), 312 313, 317 geoJSON, 193 Geospatial data, 193 Geothermal heat pumps, 414 GHG emissions. See Greenhouse gas emissions (GHG emissions) GIS. See Geographical information systems (GIS) Global connectivity, 509 510 Global EV Pilot City Programme, 131 Global governance of energy, 257 258 Global Initiative for Inclusive ICTs (G3ict), 639 640 Global positioning system (GPS), 392 Global system for mobile communication (GSM communication), 436 437, 438f Gnu Public License (GPL), 191 GoI. See Government of India (GoI) “Golden Minutes” effect, 103 Google, 479 GOOSE. See Generic Object Oriented Substation Events (GOOSE) Governance, 218 Government of India (GoI), 150, 632 initiatives taken by, 648 649 Government-based agency, 260 GPL. See Gnu Public License (GPL) GPS. See Global positioning system (GPS) Graphical results and comments, 279 288 effect of arrival rate on performance metrics, 286 287 effects of acceleration/deceleration values, 287 288 effect of number of shuttles on average energy consumption, 286 Grassroots initiatives, 549 553, 560 Greek civilization, 185 186

Index

Green Building Act, 80 Green building standards in Philippines, 68 71 Green charging, 115 Green houses, 348 Greenhouse gas emissions (GHG emissions), 79, 255 257, 261 Grid, 512 energy storage with grid integration, 252 interactive BMS/BEMS, 416 417 Grid-to-vehicle technology (G2V technology), 615 616 Gridlock, 259 Gridwise architecture council, 413 414 GSM communication. See Global system for mobile communication (GSM communication) GSO 37-bus model, 372 373, 373t GSO 37-bus power grid model, 369 H H2H communication. See Human-to-human communication (H2H communication) HA. See High availability (HA) HAN. See Home area network (HAN) HAP. See Home Automation. PH (HAP) Health care, 33 Health meters, 392 Hearing, 651 652 Heat pump, 464f, 466, 516 Heat sources, 517 518 Heating, ventilation, and air conditioning systems (HVAC systems), 57, 517 520 “Helium”, 319 HELP. See High-effect low-probability (HELP) Helsinki Region Infoshare (HRI), 239 HEM. See Home energy management (HEM) HEMS. See Home energy management systems (HEMS) HEV. See Hybrid-electric vehicle (HEV) High availability (HA), 421 High-effect low-probability (HELP), 585 High-efficiency cogeneration unit (CAR unit), 465, 467 468 High-income professionals, 76

Index

High-pressure sodium lighting (HPS lighting), 488 High-quality energy supply, 297 High-quality mobility, 94 HMI. See Human machine interface (HMI) Holistic (overall) approach, 261 262, 262f Home and building automation, 418 Home area network (HAN), 422 423 Home Automation. PH (HAP), 59 60 “Home automation” systems, 341 Home energy management (HEM), 414 with market transactions, 423f Home energy management systems (HEMS), 57t, 58 Home savings, 386 Horizontal subsidiarity, 548 549, 552 553 Hourly load profiles, 458 459 Household electricity, 263 264 Houses and lots, 60 Housing/shelter, 40 HPS lighting. See High-pressure sodium lighting (HPS lighting) HRES. See Hybrid renewable energy systems (HRES) HRI. See Helsinki Region Infoshare (HRI) HTML, 193 Human capital, 28 Human-to-human communication (H2H communication), 46 Human machine interface (HMI), 359 HVAC systems. See Heating, ventilation, and air conditioning systems (HVAC systems) Hybrid energy networks, 447 Hybrid power, 414 Hybrid renewable energy systems (HRES), 476 477 Hybrid-electric vehicle (HEV), 132 133 Hybridizations and changes in citizen governance, 219 221 Hydrogen, 525 526 Hygiene/cleanliness drive, 335 336 I I/O. See Input/output (I/O) IAM. See Identity and access management (IAM) ICE. See Internal combustion engine (ICE) ICS Cyber Kill Chain, 360 361

769

ICT. See Information and communication technologies (ICT) Identity and access management (IAM), 421 IDFM. See Ile-de-France Mobilite´s (IDFM) IDR. See Integrated DR (IDR) IDS. See Intrusion detection systems (IDS) IEC. See International Electrotechnical Commission (IEC) IEC 62351 standard, 362, 362t IEDs. See Intelligent electronic devices (IEDs) IEEE standard P2030.5, 422 423 IEEE Transactions on Industrial Electronics, 447 IEEE802.15.4 personal area network standard, 419 Ile-de-France Mobilite´s (IDFM), 117 118 “Inclusive Innovation for Smarter Cities” project, 639 640 Inclusive smart cities, 631 632, 636 637. See also Indian context in inclusive smart cities; Smart cities learning from existing global implementations, 637 640 Alexandria, USA, 638 European Union, 638 G3ict, 639 640 Korsør, Denmark, 639 Melbourne, Australia, 639 Seattle, USA, 638 Sonoma, USA, 638 objective, 650 proposed conceptual model, 644 648 data analytics block, 647 data capture block, 646 data storage block, 646 647 data-based decision block, 647 648 implementation, 646 recommendations, 648 653 review of literature, 632 633 India, 632 Indian context in inclusive smart cities, 632, 640 644 accessibility, 649 adaptability, 649 affordability, 649 650 collaboration of Smart-City Mission and Startup India, 651 existing smart India initiatives, 641 644

770

Indian context in inclusive smart cities (Continued) initiatives taken by Government of India, 648 649 public infrastructure, 652 653 smart vans, 651 study of 3As, 649 use of real-time apps, 650 visual, hearing, and cognitive ICT-based solutions, 651 652 Indian path, 195 Indicator-based evolutionary algorithm, 625 626 Indira Gandhi National Old Age Pension Scheme, 632 Individual transportation, 93 Industrial buildings, 55, 60, 65 Industrial Control Systems (ICS), 506 Industrial firewall products, 362 363 Industroyer. See CrashOverride malware Industry 4.0, 46 47 Influential factors of smart buildings, 78 80 Information and communication technologies (ICT), 3, 55, 254, 293 294, 506 507, 522 523, 526, 631 632 ICT-led initiatives as enablers of smart cities, 145 147 public transportation integration via ICT applications, 526 527 Information technology (IT), 305, 613 Infrared light, 492 Infrastructure, 160 management, 317 Inhibitors, 241 Innovation Ecosystems, 173 Innovative economy, 32 Input/output (I/O), 274 Inside-out approach, 153 154 Institutional energy monitoring services, 304 Instrumental procedures in smart cities, 252 255 application of clean technologies, 254 citizen participation, 254 demand management, 253 energy efficiency practices, 252 environmental sustainability, 253 254 identifying smart cities, 254 255 improved access to information, 253

Index

smart governance, 254 smart grid, 252 253 use of ICT, 254 Instrumented city, 633 Integrated building management, 519 520 systems, 415 Integrated communication, 310 EU members’ targets for smart meter, 311f systems, 304, 392 Integrated DR (IDR), 305, 305f Integrated mobility era, 92 93 Integrated Programme for Older Persons, 640 Integrated sensors, 487 Integrated Water Resources Management (IWRM), 523 524, 524f Integration generation and storage, 310 with GPS systems, 528 Intelligent algorithms, 623 Intelligent city, 633 Intelligent decisions, 434 intelligent decision-making process, 335 336 Intelligent electronic devices (IEDs), 359 Intelligent energy, 305 systems, 315 Intelligent public transport, 37 38 Intelligent transport management system, 337 Intelligent transport systems (ITS), 100, 528 Intelligent water distribution systems, 313 Intelligent water systems, 315 Inter-governmental fiscal transfer system, 237 Inter-Municipal Forum or Council, 238 240 process as important as outcome, 239 240 agree on resourcing, 239 ensure strong support by local governments, 239 start simple and design for success, 239 Interconnected city, 633 Interconnected neighborhoods, 250 Interdependencies, 506f multisector, 507f Interface and controller, 490 Intergovernmental systems, 239

Index

Intermunicipal collaboration approaches, 238 239 Intermunicipal cooperation arrangement application, 242 243 agenda for action for application of systematic approach, 242b increases overall productivity, 237 Internal combustion engine (ICE), 130 Internal rate of return (IRR), 467 International collaboration issues, agenda for action for, 264b International communications, 508 International Electrotechnical Commission (IEC), 359 International Energy Agency (IEA), 447 International organization for standardization (ISO), 406 International Telecommunication Union (ITU), 159 International Transport Forum (ITF), 113 Internet communication networks, 251 252 Internet network, 359 360 Internet of Things (IoT), 99, 159, 170, 249, 293, 399 400, 411 412, 418, 506, 511, 614, 631 632 communication technologies for TEN, 419 421 big data, analytics, 422 Bluetooth, 419 cellular networks 5G/4G/3G, 420 421 cloud systems, 421 cyber security and federation, 421 interoperability and standards, 422 423 LoRa and LoRaWAN, 420 Zigbee, 419 420 for energy, 418 419 evolution, 298 299 framework, 332, 332f for home and building automation, 418 IoT-based emergency care delivery process, 531f IoT-led initiatives as enablers of smart cities, 145 147 Internet technologies, 39 Internet-based systems, 304 Internet-connected computer, 386 Internet-controlled thermostat, 251 Interoperability, 201, 202t standard best practices, 422b

771

and standards, 422 423 Interoperability Solutions for European Public Administrations (ISA), 206 Intra-logistic machinery, 269 Intrusion detection systems (IDS), 363 Intuitive routing software, 304 Inventory management, 316 Investor forums, 342 IoT. See Internet of Things (IoT) IoT for All, 533 534 IPv6 routing protocol for low-power and Lossy networks, 311 312 IRR. See Internal rate of return (IRR) ISA. See Interoperability Solutions for European Public Administrations (ISA) “Islanded” mode, 571 572 ISO. See International organization for standardization (ISO) IT. See Information technology (IT) Italian Energy Authority (ARERA), 460, 467 468 Italian practices in matching public funds, 559 560 Italy and commons, 551 552 ITF. See International Transport Forum (ITF) ITS. See Intelligent transport systems (ITS) ITU. See International Telecommunication Union (ITU) IWRM. See Integrated Water Resources Management (IWRM) J J plug, 138 JavaScript Object Notation (JSON), 192 Joint Venture Silicon Valley, 549 551 K Kalman filtering-artificial neural network model (KF-ANN model), 479 Key performance indicators (KPIs), 607 609 Kirchhoff current law, 452 Kiva robots, 269 KML, 193 Korsør, Denmark, 639 KPIs. See Key performance indicators (KPIs)

772

L Lancaster estate, 60 Land-use planning, 97 98 Law-enforcement response manipulation, 259 LCVs. See Light commercial vehicles (LCVs) Leadership in Energy and Environmental Design (LEED), 66 Leakage detection and control, 521 522 LED. See Light-emitting diode (LED) LEED. See Leadership in Energy and Environmental Design (LEED) Legal frameworks, 239 Legally open data, 191 Legitimacy, 174 Leverage effect, 259 Lifts, 279 Light, 351 Light commercial vehicles (LCVs), 131 Light-emitting diode (LED), 68, 487 488, 488f lightings, 57, 78 luminaires, 492 Lightings, 58 poles, 493 Link-layer multicast communication, 359 Linked data, 187 190 Linked open data (LOD), 187 190 Linked Open Government Data (LOGD), 190, 206 Liquid waste, 36 Live broadcast cameras, 295 LMP. See Locational margin pricing (LMP) LMS. See Local management station (LMS) Load and generation forecasting, 478 479 shifting, 442 LOAD. See 6LoWPAN Ad Hoc On-Demand Distance Vector Routing (LOAD) Local boiler, 461, 463f Local government jurisdictions, 235 with regards to smart cities, 236b Local management station (LMS), 299 Local mindsets, 164 Localization of CAV, 602, 603f Locational margin pricing (LMP), 427 Locomotion, 38

Index

LOD. See Linked open data (LOD) LOGD. See Linked Open Government Data (LOGD) Logistics, 38 39 Long Range (LoRa), 420 LoRaWAN, 351, 420 Low power wide area network (LPWAN), 331 6LoWPAN Ad Hoc On-Demand Distance Vector Routing (LOAD), 311 312 LPWAN. See Low power wide area network (LPWAN) Luminaires, 485 487 and components, 486f luminaire-dimming controller, 491f in variety of shapes and sizes, 486f Lyapunov stability theory control, 622 M M-banking, 5 M-government. See Mobile government (Mgovernment) M-payment, 5 M2H communication. See Machine-tohuman communication (M2H communication) M2M communication. See Machine-tomachine communication (M2M communication) Machine learning (ML), 475 Machine vision, 493 Machine-learning technologies, 363 Machine-to-human communication (M2H communication), 46 Machine-to-machine communication (M2M communication), 46 Magnetic ballasts, 489 Man-in-the-middle (MITM), 364 365 Manpower skill database, 347 Manual DR, 67 Manufacturing Message Specification (MMS), 359 Market evolution, 310 forces, 412 414 and operators, 413, 426 427 Markov risk measure, 587 Mathematical modeling approach, 272 MatLab solver, 453 454

Index

Mechanical ventilation and air-condition systems (MVAC), 68 Medical institutes and hospitals, 342 Melbourne, Australia, 639 Mental Retardation, 640 641 Messaging service, 235 Metro-wide data, 236 Metropolitan, 235 area, 237 238 cities benefit from cooperation on smart city subject, 236 237 authority/ies, 240 governance arrangement, 237 241 comprehensive arrangements, 240 241 inter-municipal forum or council, 238 240 Metropolitan-level local government, 240 241 Micro networks, 517 Microgrids, 294, 401, 514, 515f resilient operational control of, 584 589 MILP. See Mixed-integer-linearprogramming (MILP) Ministry of Electronics and Information Technology (MietY), 641 Ministry of Social Justice and Empowerment (MSJE), 643 Mission-critical-communications, 508 511 MITM. See Man-in-the-middle (MITM) Mixed-integer-linear-programming (MILP), 448, 453 454 ML. See Machine learning (ML) MMS. See Manufacturing Message Specification (MMS) Mobile application, 337 computing, 631 632 devices, 386 systems, 293 technologies, 3 4 2G/3G/4G/5G, 351 Mobile government (M-government), 3 4, 6 8 adoption factors, 7t adoption in developing countries, 5 Mobility, 89 91 as a service caters to customer demands, 112 113 Mobility service providers (MSPs), 114

773

Mobility systems. See also Electric mobility (E-mobility); Smart mobility; Urban mobility action recommendations for regulators, 118 121 education and incentives for clean vehicle drivers, 119 120 innovation and new business models, 120 121 right to electric vehicle chargers, 119 sustainable supply chains for clean transport, 121 artificial intelligence, 122 123 autonomous vehicles in logistics, 123 components, 108 109 electric vehicles, 108 109 energy infrastructure, 108 leisure time in traveling, 121 122 mobility infrastructure, 108 urban vs. rural, 108 Model predictive control methodologies (MPC methodologies), 574 risk-averse, 584 588 Model predictive operation control, 574 575 Modernization of communities, 510 Moov’in, 117 Moovel, 118 MOSEK, 589 MPC methodologies. See Model predictive control methodologies (MPC methodologies) MSJE. See Ministry of Social Justice and Empowerment (MSJE) MSPs. See Mobility service providers (MSPs) Multimedia gateway, 296 Multiobjective evolution algorithm, 625 626 Multiobjective particle swarm optimization, 625 626 Multiple Disabilities Act, 640 641 Multiple lighting node controllers, 490 Multiple tri-generation stations working with gas, 320 321 Multipurpose optimization, 579 Multisector interdependencies, 507f Multistage risk-averse MPC, 588 Mushlom sports, 639

774

MVAC. See Mechanical ventilation and aircondition systems (MVAC) N National communications, 508 National Data Sharing and Accessibility Policy (NDSAP), 195 National energy plans, 297 298 National Institute of Standards and Technology (NIST), 308 National paths to open data, 194 196 EU path, 194 195 Indian path, 195 US path, 195 National policy approach, 516 National Policy on Universal Electronic Accessibility (2013), 651 652 National Trust for Welfare of Persons with Autism, 640 641 Natural gas, 293 295, 318 321, 515 516 customer requirements and expectations, 320 device maintenance, 320 distribution company, 305 grid, 319 infrastructure, 318 319 management of natural gas system, 319 320 overview, 318 review of state-of-the-art studies, 320 321 Navigation, 528 NB-IoT-based intelligent smoke detection systems, 529 530, 529f NDSAP. See National Data Sharing and Accessibility Policy (NDSAP) Near-field communication (NFC), 526 Negawatt sources, 414 NEMA 3 pin connector, 486 487 NEMA 5 connector, 487 NEMA 7 connectors, 485, 487, 487f Nested multistage risk measure, 587 risk-averse problems, 588 589 Net energy consumption per transaction, 279 Net present value (NPV), 467 Net zero premise, 424 Network Operation Control Centre (NOCs), 353

Index

Networks, 490, 512 infrastructure, 162 protocol, 359 Neural network control, 622 New grids structures, 475 478 NFC. See Near-field communication (NFC) NIST. See National Institute of Standards and Technology (NIST) NITI Aayog, 150 NOCs. See Network Operation Control Centre (NOCs) Non-discrimination, 637 Non-dispatchable module, 450 451 Non-organized public, 549 551 (Non)government-communication, 509 Nonfree balancing approach, 273 Nongovernmental organizations, 349 Nonlinearity in constitutive equation, 450 451 NPV. See Net present value (NPV) Numerical optimization methods for multistage optimization, 588 589 Nylon, 318 319 O Objective functions, 579 constraints on, 580 generalized, 581 OBO. See Office of Building Official (OBO) Occupancy sensors, 492 494 ODbL. See Open Database License (ODbL) ODC. See Open Data Commons (ODC) OECD. See Organisation for Economic Cooperation and Development (OECD) Office of Building Official (OBO), 74 OFW. See Overseas Filipino Workers (OFW) Oil, 512 520 On-demand roadway lighting, 494 495, 495f One-size-fits-all approach, 151 Open & Agile Smart Cities, 202 Open architecture, smart-city, 349 Open AutoDR (OpenADR), 67 Open Data Commons (ODC), 191 Open Data Directive, 194 195 Open data for smart cities, 190 194 big data, linked data, and linked open data, 187 190

Index

challenges, 190 data marketplaces, 204 206 eliminating silos by sharing, 202 204 formats, 192 193 free vs. not free, 190 191 licenses, 191 192 national paths to, 194 196 rise of urban data, 186 187 value chain, 196 201, 199f consumption/commercialization, 198, 199t governance, 200 201, 201t interoperability, 201, 202t processing, 198 199, 200t security and trust, 201, 203t Open Database License (ODbL), 191 Open government, 217 218 Open Government Data Act, 195 Open/closed-loop pumped-storage hydropower, 518f OpenADR. See Open AutoDR (OpenADR) Operation technology (OT), 613 Operational and information technologies (OT 1 IT), 411 Operators, 413, 426 427 Opex, 649 650 Opportunities, 90 Optimal charging solutions for E-mobility, 114 Optimal scheduling, 457 458 Optimal sequence of control actions, 574 Optimization and operations efficiency, 310 Organisation for Economic Co-operation and Development (OECD), 113 commons and, 546 Organizational integration, 402 Organizations, 613 614 OT. See Operation technology (OT) OT 1 IT. See Operational and information technologies (OT 1 IT) Outside-in approach, 153 Overseas Filipino Workers (OFW), 76 P Pacific Northwest National Laboratory (PNNL), 413 414, 427 Pacts of collaborations, 555 557 Pag-IBIG Fund, 73 Panic buttons, 532 533

775

Pareto archived evolutionary strategy, 625 626 Parking and public transportation system integration, 527 Parking benefits and preferred lanes, 120 Parochialism phenomenon, 241 Participatory governance, 187 Passenger information system, 337 Passive house, 402 403 Passive to active citizens, 215 217 Path planning of CAV, 603 604, 604f Pay back time (PBT), 467 PCs. See Personal computers (PCs) Peak clipping, 441 Peak load, 417, 417f People-centricity, 169 Perception of CAV, 602, 604f Peripheral network, 43 Personal computers (PCs), 4 PEVs. See Plug-in electric vehicles (PEVs) Phasor measurement unit (PMUs), 392 PHEV. See Plug-in hybrid electric vehicle (PHEV) Philippine Green Building Council (PHILGBC), 68, 74 Photocontrol sensor, 491 Photovoltaic (PVs), 436 Photovoltaic panel (PV panel), 450 451 Piecewise linear approximation of nonlinear characteristic, 450, 450f Pipeline, 319 PJSC Rosseti, 477 478 Plain text, 193 Plan new neighborhoods, 259 PLCs. See Programmable logic controllers (PLCs) PLM. See Product lifecycle management (PLM) Plug-in electric vehicles (PEVs), 620 Plug-in hybrid electric vehicle (PHEV), 132 134 PMUs. See Phasor measurement unit (PMUs) PNNL. See Pacific Northwest National Laboratory (PNNL) Policy makers, 520 Policy making process, 349 Political energy strategies, 405 Political fragmentation, 236 237

776

Pollution, 36 Polycentric governance, 549 551 Polycentrism, 548 549 Polygeneration, 447 448 Potential energy strategies best practices, 404b Power, 174 flow dynamics simulation, 368 369, 368f grid domain, 371 systems, 359 networks, 571 572 power-line communications, 311 312 source, 415 system dynamics simulation, 367f, 368 Power purchase agreements (PPA), 426 PowerWorld simulator, 366, 369 PPA. See Power purchase agreements (PPA) PPPs. See Public private partnerships (PPPs) Practical integration, 369 377 “Precious balance” of lighting, 485 Predictive models, 573f Predigital era, 411 Prepaid cards, 172 173 Primary energy sources, 298 Procurement, 38 39 Product lifecycle management (PLM), 589 Programmable logic controllers (PLCs), 359 Proportional integral derivative (PID) control, 622 Prosumers, 250 behavior, 578 Protection in critical infrastructures, 507 508 Protocol, 554 555 gateway, 376 Proximal gradient method, 589 Proximal-type numerical algorithms, 589 Proxy, 369 370 PSH. See Pump storage (PSH) Public bicycle sharing, 336 337 exemplary plan, 258 fleets, 120 health, 250 251 infrastructure, 652 653 participation in life, 29 public-key cryptography, 364 public-private-people-partnerships, 243

Index

safety organizations, 508 509 service management, 235 transit, 93, 99 Public private partnerships (PPPs), 331 Public transport(ation), 240, 293 294, 525 528 development, 96 electrification of motorized public transportation, 526 527 integration via ICT applications, 526 527 overview, 525 526 parking and public transportation system integration, 527 recommendations and solutions, 527 528 Pulse width modulation rectifier (PWM rectifier), 621 Pump storage (PSH), 518 PV panel. See Photovoltaic panel (PV panel) PWM rectifier. See Pulse width modulation rectifier (PWM rectifier) Q Quality of life (QoL), 632 Quality of service (QoS), 159 160 Queuing network approach, 272 R Radar, 492 Radio frequency identification (RFID), 509 510 Rainwater harvesting, 341 Rapid digitalization, 614 615 Rapid urbanization, 633 Rate discovery, 427 RD. See Register of Deeds (RD) RDF. See Resource Description Framework (RDF) RE. See Renewable energy (RE) Real time control systems, 433 Real-estate development, 77 Real-time information, 305 306 observation, 251 Regional/provincial government, 241 Register of Deeds (RD), 74 Regulations and standards, 303 Relationship mapping, 76 77 Reliability, 310, 400, 505 Relocation, 37

Index

Remote energy management system, 439 using smart meter, 439, 439f Remote terminal unit (RTU), 317, 362, 438 Renewable electricity, 258 Renewable energy (RE), 338, 347, 412 Renewable energy sources (RES), 299 300, 307, 312, 447, 516 Renewable generation, 251 RES. See Renewable energy sources (RES) Research, 342, 447 Residential buildings, 55, 60 62 Residential condominiums, 60 61 Resilience, 400, 424 Resiliency, 310 Resilient future energy systems changing face of energy networks, 571 574 flexible future smart-grid systems, 575 model predictive operation control, 574 575 resilient operational control of microgrids, 584 589 smart grids and digital twins, 589 590 Resilient operational control of microgrids, 584 589 numerical optimization methods for multistage optimization, 588 589 risk-averse multistage optimization and risk-averse MPC, 584 588 Reskilling institutes, 342 Resource availability, 298 Resource Description Framework (RDF), 189, 192 193 Retrieval process, 274, 276f Return on investment (ROI), 56, 424 RFID. See Radio frequency identification (RFID) Ride-hailing, 99, 117 Ride-pooling, 117 Right to electric vehicle chargers, 119 Right to equality, 653 654 Right to life, 653 654 Risk, 506 Risk-averse concept, 574 575, 586f formulations, 588 MPC, 584 588 multistage optimization, 584 588 Road and city cleanliness, 339

777

“Robo-taxis”, 122 ROI. See Return on investment (ROI) Rooftop solar/wind turbines, 415 RTU. See Remote terminal unit (RTU) S S-metric-selection evolutionary multiobjective optimization algorithm, 625 626 Safe drinking water, 520 Safe Drinking Water Act, 315 316 Safety, 41, 90 of communication systems, 510 Sampled Value (SV), 359 Sanitation, 36 Satellite, 351 SBA model framework. See Smart building architecture model framework (SBA model framework) SBS/RS. See Shuttle-based storage and retrieval system (SBS/RS) SC&C. See Smart Cities and Communities (SC&C) SCADA. See Supervisory control and data acquisition (SCADA) Scanned images, 193 Schedule-based system, 491 Schuko plug, 138 SCM. See Smart City Mission (SCM) “ScottMadden Management Consultants” company, 293 294 SDDP algorithm. See Stochastic dual dynamic programming algorithm (SDDP algorithm) SDGs. See Sustainable development goals (SDGs) Seattle, USA, 638 Second-order problem (SOCP), 589 Sector coupling, 519 520 Security, 41, 58 59, 310, 354 cameras system, 295 of communication systems, 510 gaps, 506 solutions for protecting smart grid, 361 365 limitations of existing cyber-security solutions, 364 365 system, 251 SeenAb, 650

778

Self-driving vehicles, 99 Self-healing grids, 401 Semiautomated DR, 67 Senate Bill 1799, 79 Senate Bill 2574, 79 Sensing and measurements, 393 Sensors, 338, 418, 491, 533, 636. See also Smart sensor integrated, 487 layer, 334 occupancy, 493 494 occupation, 492 utilizing, 496 497 Series resonance converter (SRC), 622 Service Level Agreements (SLAs), 159 160 Sewage and waste treatment operators, 258 Sewerage services, 240 SG. See Smart grid (SG) SGAM framework. See Smart grid architecture model framework (SGAM framework) Shared means of transport, 113 Shared mobility, 116 117 Sharing economy, 113 Shuttle-based storage and retrieval system (SBS/RS), 269 Shuttles, 279, 285f net energy consumption versus number of shuttle per aisle graph, 286f effect of number of shuttles on average energy consumption per transaction, 286 Simulation modeling of system, 277 279 design scenarios for experiments, 277 279 description of utilized parameters, 278t design scenarios for experiments, 278t Sinusoidal pulse width modulation (SPWM), 621 Skilling, 342 SLAs. See Service Level Agreements (SLAs) Small-level energy production techniques, 391 Small-scale distributed energy systems, 309 Smart advertisements, 342 Smart and intelligent appliances, 251 Smart and sustainable balance, 250 Smart appliances, 386

Index

connectivity and home savings, 386 energy use, 386 Smart building architecture model framework (SBA model framework), 56, 56f Smart buildings, 55 market potentials, 72 80 building association, 74 contractors, 75 designers, 75 end-users, 76 financial institution, 75 government, 73 74 influential factors, 78 80 real-estate agent, 75 real-estate developers/owners, 74 75 relationship mapping, 76 77 stakeholders for smart building in Philippines, 73 suppliers, 75 permits and standards, 66 72 building permits and standards in Philippines, 67 68 Green building standards in Philippines, 68 71 Stratford Building, 72 stakeholders, 55 systems, 57 60 enterprise and integration system software, 57 58 hardware, 57 technologies applied in Philippines, 58 60 types in urban space, 60 65 types of building construction in Philippines, 61 65 Smart charging of EVs, 387 Smart cities, 6 8, 18 20, 129, 159 160, 235, 250 252, 503, 615 616, 632 634. See also Inclusive smart cities ADS, 251 AMSI, 251 252 application architecture, 335 342 background information, 161 162 blocks to market, 163 166 challenges and opportunities, 151 154 inside-out approach, 153 154 need for integrated approach, 152

Index

outside-in approach, 153 citizens in, 213 communications, 508 511 components of, 600 601 critical city infrastructures, 503 508, 505f data democracy architecture, 350 354 distributed power generation, 251 emergency services, 529 534 enablers, 169 173 energy, 512 520 storage with grid integration, 252 EV, 252 expanding market, 166 167 factors affecting energy in, 257 259 features, 652f goals, 149 151 greening market, 167 168 HVAC and audio visual, 251 infrastructure components, 17, 19 infrastructure platforms and domains, 21 47 and infrastructure standardization requirements city services’ architecture and assets management, 346 350 data monetization, 332 333 gearing-up for smart health in cities, 343 346 security, privacy, and business continuity concerns of data hub, 354 smart energy and light, 343 initiatives, 143 instrumental procedures in, 252 255 IoT-and ICT-led initiatives as enablers of, 145 147 efficiency and flexibility by adopting technology, 146 147 key foundations, 20 21, 20t market generation, 162 163 metadata model, 352 353, 352f and metropolitan governance agenda for action for coordinating collaboration effort, 236b application of intermunicipal cooperation arrangement, 242 243 cities benefit from cooperation on smart city subject, 236 237 collaboration across jurisdictions, 241 242

779

metropolitan governance arrangement, 237 241 need for, 143 144 one-UN approach to, 601f pillars, 21f platforms, domains, main components, and secondary components, 23t public transportation, 525 528 solutions, 298 standards selection, 255 process-level standards, 255 technical-level standards, 255 technologies, 240, 294 architecture, 333 334, 334f smart-city standardization outcome, 335f technology architecture, 333 334 TEN for, 412 414, 413f training and involving stakeholders, 173 176 urban planning, and policy, 147 151 USDOT vision elements for smart-city development, 602f water, 520 525 Smart Cities and Communities (SC&C), 170 Smart citizens, 214, 220 Smart City Mission (SCM), 163, 632, 634, 641 642 in Varanasi, 643 Smart communication, 46 Smart contracts, 340 Smart culture, 31 32 Smart data, 43 44 analysis, 44 information linkage, 44 resource, 44 Smart decision support systems and investments, 294 Smart digital infrastructure, 23t, 41 Smart distribution, 307 308 Smart elements grid, 401 Smart energy CAV and, 605 606 hub, 305 306 and light, 343 management system, 436, 439 443 demand response, 440 demand-side management, 440 441 flexible load shape, 443

780

Smart energy (Continued) load shifting, 442 peak clipping, 441 strategic conservation, 442 strategic load growth, 442 supplier-side management, 439 440 valley filling, 441 442 Smart entertainment, 348 Smart governance, 220, 254, 349 350 analysis, 349 enforcement, 350 execution, 350 planning, 349 policy making, 349 Smart government, 3, 169 170 conceptual model of smart government adoption, 9 in developing counties, 6 9 Smart grid (SG), 250 253, 294, 306, 340 341, 343, 475 478, 513, 520, 589 590, 615 616 advantages of, 306 307 agenda for action for implementation of characteristics of, 253b applications, 334 energy management techniques in, 436 439 evolution from traditional grid to, 615f infrastructure, 512 513, 512f integration, 426 systems, 298 299, 360, 372 373 technology, 400 Smart grid architecture model framework (SGAM framework), 56 Smart health(care) CAV and, 607 gearing-up in cities, 343 346 proposed standard systems and processes for, 344b technology environment for, 344 346 Smart home, 34, 341 CAV and, 606 607 Smart incorporated city planning, 170 173 Smart infrastructure, 298 299, 476t Smart inverter, 425 Smart lighting for smart cities, 485 challenges, 494 495 color, 492 493 controls, 489

Index

methodologies, 490 492 drivers and dimming, 489 interface and controller, 490 LEDs, 487 488, 488f luminaires, 485 487 and components, 486f in variety of shapes and sizes, 486f networks, 490 on-demand roadway lighting, 494 495, 495f ubiquitous network and infrastructure, 492 494 Smart management system, 476t Smart marketing, 32 Smart metering, 308 310 single-and three-phase meters and communications module, 308f water efficiency via, 522 523 Smart meters, 57, 315, 343, 387 390, 523 advanced air pollution monitoring systems, 294 remote energy management system using, 439 working principle of, 390 Smart microgrids, 249 250, 424 Smart mobility, 615 616. See also Electric mobility (E-mobility) areas, 606f CAV and, 605 Smart networks, 41 43 international connectivity, 42 smart-city dashboard, 43 socially reliable networks, 42 surveillance network, 43 Smart parking systems, 527 Smart physical infrastructure, 23t, 34 47 smart environment, 34 37 smart living, 40 41 smart mobility, 37 39 smart utility, 39 40 Smart poles, 493 Smart sensor, 45 47, 529 530. See also Sensors citizen sensors, 45 E-communication, 46 Industry 4.0, 46 47 smart communication, 46 urban sensors, 45 46 Smart solutions, 295 300

Index

consumer requirements and expectations, 296 297 energy need, 297 national energy plans, 297 298 overview, 295 296 resource availability, 298 smart infrastructure, 298 299 VU, 299 Smart stations, 307 Smart substation, 390 Smart surveillance, 33, 533 Smart Sustainable Cities (SSC), 170 Smart systems, 413 Smart TE microgrids, 424 426 Smart technologies, 475 478 Smart thermostats, 414 Smart tourism, 335 Smart traffic-management system, 38 Smart transportation system, 526 Smart urban forests, 342 planning, 633 Smart utilities business models for utility industry, 321 323 electricity, 300 312 natural gas, 318 321 smart solutions, 295 300 systems, 294 295 and underlined technologies, 294f water, 312 318 Smart vans, 651 Smart waiting areas, 342 Smart water, 341 grid, 315 management solutions, 313 systems, 294, 317 network, 313 quality monitoring system, 524 525 Smart working spaces, 341 342 Smart-city age, urban mobility in, 98 104 benefits of smart urban mobility, 98 99 infrastructure components, 100 101 communications technology, 100 101 information technology, 101 operational technology, 100 physical infrastructure, 100

781

integration of smart mobility solutions within and across sectors, 102 103 switching from traditional to smart mobility, 101 102 urban planners, 103 104 Smart-city application architecture, 335 342 building management, 338 care for physically disabled, 340 disease management, 339 E-buses, 336 E-rickshaw, 336 fire safety, 340 hygiene/cleanliness drive, 335 336 intelligent transport management system, 337 management of E-charging stations, 337 of traffic lights, 337 338 medical institutes and hospitals, 342 passenger information system through mobile application, 337 public bicycle sharing, 336 337 research, education, skilling, and reskilling institutes, 342 road and city cleanliness, 339 smart contracts, 340 smart grid, 340 341 smart homes, 341 smart tourism, 335 smart urban forests, 342 smart waiting areas and smart advertisements, 342 smart water, 341 smart working spaces, 341 342 special care for elders, 339 340 speed management, based on time of day, 337 start-up ecosystem and investor forums, 342 traffic and travel management, 336 usage of data for safety, 340 Smart-city data democracy architecture, 350 354 AI for smarter decisions in smarter cities, 353 components of smart-city data, 350 351 connectivity and data hub, 351 data infrastructure, 351

782

Smart-city data democracy architecture (Continued) operational requirements, skills, and expertise, 353 354 smart city metadata model, 352 353, 352f Smart-city hacking, 259 260 manipulation of law-enforcement response, 259 solution for smart cities, 260 Smart-City Mission and Startup India collaboration, 651 Smart-grid infrastructure security against emerging threats emerging cyber threats targeting smart grid, 360 361 SCADA command authentication as additional line of defense, 365 377 security solutions for protecting smart grid, 361 365 Smart-grid system components of smart grid, 385 393 distributed generation, 391 EVs, 386 387 integrated communication system, 392 PMUs, 392 sensing and measurements, 393 smart appliances, 386 smart meters, 387 390 smart substation, 390 usage in world, 513 514 Smart-society infrastructures, 22 34, 23t, 28f smart economy, 31 32 smart governance, 29 30 smart lifestyle, 32 34 smart people, 22 29 Smarter energy utilization, 338 Smarter home, 251 Smarter London Together, 163 Smarthoods, 250 Smartness of new energy systems, 447 Smartphone application, 235 Smartphones, 532 533 SoC. See State of charge (SoC) Social and economic development, 433 inclusion, 34

Index

innovation, 546 547 media networks, 250 251 services, 33 Streets, 552 value, 544 545 SOCP. See Second-order problem (SOCP) Solar, 391, 399 energy, 301 sources, 399 heating, 464f, 466 lights/energy storage, 348 power systems, 343 properties of windows, 262 thermal water heaters, 516 Solid waste, 36 management and zero waste policy and green houses, 348 Solid-state technologies, 487 488 Solving constraint integer programs (SCIP), 453 454 Sonoma, USA, 638 Space vector pulse width modulation (SVPWM), 621 Special care for elders, 339 340, 339b Speed management, based on time of day, 337 Spreadsheets, 193 SPWM. See Sinusoidal pulse width modulation (SPWM) SRC. See Series resonance converter (SRC) SSC. See Smart Sustainable Cities (SSC) Stadalone object, 447 Stakeholders, 258, 412 414 consultation, 355 for smart building in Philippines, 73 training and involving, 173 176 Standardization, 170 Starbucks card, 172 173 Start-up ecosystem and investor forums, 342 Startup India, 651 State of charge (SoC), 624 625 State-of-the-art cyber-security, 360 Steady-state power flow simulation, 366, 367f, 369 Stochastic dual dynamic programming algorithm (SDDP algorithm), 583 Stochastic models offer probabilistic information, 573 stochastic modeling approaches, 574

Index

Storage in EMS, 461 465, 463f process, 274, 275f Strategic conservation, 442 Strategic load growth, 442 Strategic Plan on Aging, 638 Strategic-level standards, 255 Stratford Building, 72, 72t Streetlights, 347 Strength Pareto evolutionary algorithm, 625 626 Stuxnet case, 360 Stuxnet malware, 360 Subdivisions, 60 Subscriber management, 316 317 Subsidiarity pact, 557 with active citizens, 557 558 Super SCS, 589 Superation of citizen participation, 230 232 Supervisory control, 365 368 Supervisory control and data acquisition (SCADA), 58, 364 365, 392, 419, 436 438, 438f, 506 command authentication as additional line of defense, 365 377 A CMD system and practical integration, 369 377 command authentication using power flow dynamics simulation, 368 369 supervisory control and data acquisition command authentication, 365 368 communication channel, 359 360 master system, 360 361 SCADA-database based control surveillance system, 317 system, 522 523 Supplier-side management, 439 440 Supply chain, 614 Surveillance network, 43 Sustainability, 293, 400 urban mobility in context of, 95 98 Sustainable and well-functioning smart city, 331 Sustainable buildings, energy efficient designs of, 260 265 Sustainable development goals (SDGs), 143, 220 221, 631 632 SV. See Sampled Value (SV)

783

SVPWM. See Space vector pulse width modulation (SVPWM) Swiss Federal Council, 405 Synchrophasors, 392 Syndicats inter-communaux, 238 239 System description and model assumptions in system, 273 276 operations and assumptions in system, 274 276 Systematic approach, agenda for action for application of, 242b Systems hackers, 259 T Tariffs mechanisms, 252 TaxiBots, 122 123 TBM. See Technical building management (TBM) TE EMS microgrid architecture, 425, 425f TE service platform, 421 Tech bridges, 331 Technical building management (TBM), 66 Technical-level standards, 255 Technically open data, 191 Technological governance, 219 Technology environment for smart healthcare, 344 346 Technology-based “inclusive development”, 632 Telecommunications, 510 manufacturing, 8 9 TEN. See Transactive energy network (TEN) Tesla’s design principles, 301 Text documents, 193 Thermal transmission properties, 262 Thomas Jefferson University, 493 494 Threats, 506 Tier-to-tier SBS/RS design, 270, 273, 274f, 277 Time, 90 Time-based algorithm, 272 Time-of-use (TOU), 623 electricity price, 625 game theory, 625 626, 626f Italian tariff, 460 traditional, 625 TLS. See Transport layers security (TLS) Total primary energy (EP), 262 TOU. See Time-of-use (TOU)

784

Tourism, 31 Tourist spots and hotel management, 347 Townhouse, 61 Trackside suburbs, 91 Traditional TOU, 625 Traditional transport business models, 112 Traffic, 38 congestion, 525 lights management, 337 338 management automation, 528 sensors. See Occupancy sensors and travel management, 336 zones, 120 Training and readiness for disaster, 349 Transactive energy challenges, 428 429 strategy, 427 429 subsystems for, 415 418 building management systems, 415 grid interactive BMS/BEMS, 416 417 levels of operation, 417 418 Transactive energy network (TEN), 411 414 IoT communication technologies for, 419 421 for smart cities, 412 414 customers and stakeholders, 412 digitization and smart systems, 413 markets and operators, 413 transactive energy networks, 413 414 Transforming energy systems, 300 Transit systems, 93 94, 118 collective transportation, 93 freight transportation, 93 94 individual transportation, 93 Transmission, 385, 433 434 grid, 401 Transparency, 187 and citizen role in urbanism and infrastructures, 228 230 Transport, 235 services, 643 644 Transport layers security (TLS), 361 362 Transportation, 89 91, 250 251, 295, 301 302 collective, 93 freight, 93 94 individual, 93 quality in, 528

Index

systems, 252 Travel cards, 337 Triple helix model, 549 551 Tubular skylights, 414 Two-way communication, 385, 390 network, 305 U U4SSC. See United for Smart Sustainable Cities (U4SSC) Ubiquitous network and infrastructure, 492 494 UIA. See Urban innovative action (UIA) Ukraine power plant attacks, 360 361 UMC. See Urban mobility concept (UMC) Unified Theory of Acceptance and Use of Technology (UTAUT), 9 United Arab Emirates (UAE), 6 9 United for Smart Sustainable Cities (U4SSC), 143 United Nations (UN), 220 221 United Nations World Urbanization Prospects Report, 631 632 University of Ontario Institute of Technology (UOIT), 599 Unplanned city’s evolutions, 258 Urban, 235 assets, 548 549 community, 238 239 data, 186 187 facilities, 39 40 sensors, 45 46 Urban electric grids optimization dynamic optimization, 583 584 with EV charging load and V2G generation, 576 584 high-level model description, 579 580 lower level of optimization, 578 579 minimization of losses in electric grid, 580 of voltage deviations, 580 probabilistic statement of problem, 581 583 reducing environmental impact, 580 581 statement of optimization problem, 576 578 Urban infrastructures citizens in, 214 215 and networks, 293 294

Index

Urban innovative action (UIA), 555 557 in city of Turin, 555 557 Urban mobility, 89, 643 644. See also Electric mobility (E-mobility); Smart mobility challenges, 94 97 in context of sustainability, 95 98 evolution, 91 93 examples of urban mobility components, 114 118 mobility, transportation, and accessibility, 89 91 in smart-city age, 98 104 trends shaping, 109 110 types of transit systems, 93 94 Urban mobility concept (UMC), 90 Urbanism, 228 in smart-cities world, 221 223 Urbanization, 505 506 future of, 143 144 Urgency, 174 US path, 195 Usage-based cleaning, 338 User groups, 162, 175t User-side device, 320 UTAUT. See Unified Theory of Acceptance and Use of Technology (UTAUT) Utilitarianism, 406 Utility meter, 421 Utilizing sensors, 496 497 V V2G technology. See Vehicle-to-grid technology (V2G technology) Valley filling, 441 442 Variable air volume, 517 518 Variable frequency pulse width modulation (VFPWM), 622 Vehicle tracking system, 295 Vehicle-to-grid technology (V2G technology), 115 116, 387, 615 618 advantages, 618 architecture, 617 618, 617f bidirectional topology, 621f centralized and decentralized control solutions, 619t charging/discharging strategy, 623 626 state-of-the-art, 618 623

785

Venezuela, 613 Verona regulation, 557 558 VFPWM. See Variable frequency pulse width modulation (VFPWM) Villages, 60 Virginia Tech Transportation Institute (VTTI), 493 495 Virtual controlled critical services, 299 “Virtual Power Plants”, 299 300 Virtual private network (VPN), 359 360 Virtual utility (VU), 299 benefits of VU model, 299 300 Visual solutions, 651 652 Voltage source rectifier (VSR), 621 VPN. See Virtual private network (VPN) VSR. See Voltage source rectifier (VSR) VTTI. See Virginia Tech Transportation Institute (VTTI) VU. See Virtual utility (VU) Vyttila Mobility Hub, 110 W Walking-horse car era, 91 WAN. See Wide-area network (WAN) Waste, 36 Waste management, 294 Wastewater treatment, 341 Water, 35 36, 250 251, 258, 293 295, 312 318, 520 525. See also Smart water conservation/harvesting, 338 distribution system, 313 314, 314f district, 74 GIS and infrastructure management, 317 infrastructure, 313 315 inventory management, 316 management of water utility system, 315 316 network, 314 315 overview, 312 313, 520 521 recommendations and solutions, 523 525 review of state-of-the-art studies, 317 318 SCADA-database based control surveillance system, 317 smart meter, 315 smart water grid, 315 smart water network, 313f subscriber management, 316 317

786

Water (Continued) subscriber system, 316 317 supply, 240 monitoring and control systems, 522 utility system management, 315 316 water systems infrastructures, 521 523, 522f leakage detection and control, 521 522 water efficiency via smart metering, 522 523 water quality monitoring, 523 Way forward today, The, 351 Western Electricity Coordinating Council (WECC), 366 “Whim” App, 118 Wi-Fi, 351, 392 Wide-area network (WAN), 359 Wind, 391, 399 power, 302 303 turbines, 414 Wireless cellular, 311 312 mesh networks, 311 312 network, 387 389 Wireless sensor networks (WSNs), 57 58, 354

Index

World energy consumption, 434t Worst-case robust approach, 572 573 X XEMS13, 454 components, 449 451 cost function, 453 energy vector balance equations, 451 452 optimization, 449 454 tool, 457 458, 466 467 XML. See eXtensible Mark-up Language (XML) Y Yandex, 479 Yinchuan, 227 228 Z Zero waste policy, 348 ZigBee, 392, 419 420, 492 493 network interfaced with field programmable gate array, 436 Zigbee Home Automation (Zigbee HA), 420 Zigbee Smart Energy (Zigbee SE), 419 420