Wireless Communication. Advancements and Challenges 9780367751593, 9781032020655, 9781003181699

Table of contents :
Cover
Half Title
Series Information
Title Page
Copyright Page
Table of Contents
Preface
Readers
Chapter Organization
About the Authors
1 Internet of Things (IoT)
1.1 Introduction
1.1.1 Internet of Things Vision
1.1.2 Evolution and Rapid Adoption of IoT
1.1.3 The Need for M2M Connectivity
1.1.4 The Chicken and Egg Analogy
1.2 The Continuing Evolution of IoT
1.3 The Key Drivers of Rapid Adoption of IoT
1.4 How Does IoT Work
1.5 Importance of IoT
1.6 Benefits of IoT to Businesses
1.6.1 Consumer and Enterprise IoT Applications
1.6.2 Engineering, Industry, and Infrastructure
1.6.3 Home Applications
1.6.4 Wearables
1.6.5 Healthcare and Medicine
1.6.6 Smart Cities
1.6.7 Smart Grid and Smart Meters
1.6.8 Agri-Tech
1.6.9 Tyre Air Pressure Detection
1.6.10 Personal IoT Applications
1.6.10.1 Gesture Control Armband
1.6.10.2 Smart Glass
1.6.10.3 Smart Eye
1.6.10.4 Pulse Oximeter
1.7 Potential of IoT
a) There Will Be More Than 21 Billion IoT Devices By 2025
b) More Cities Will Become “Smart”
c) Artificial Intelligence Continues to Be a Big Thing
d) 5G Networks Continues to Fuel IoT Growth
e) Cars Are Getting Even Smarter
f) 5G Networks Will Also Open the Floodgates On Concerns Related to Security and Privacy
g) Cybercriminals Will Use IoT Devices to Facilitate DDoS Attacks
h) Routers Will Be More Secure and Smarter
i) IoT-Based DDoS Attacks Will Be More Dangerous
j) Security and Privacy Concerns Drive for Legislation and Regulations
1.8 Architecture of IoT
1.8.1 Smart Device/Sensor Layer
1.8.2 IoT – Technology and Protocols
1.8.3 RFID and NFC
1.8.4 Low-Energy Bluetooth (BLE)
1.8.5 Low-Energy Wireless
1.8.6 Radio Protocols
1.8.7 LTE-Advanced
1.8.8 NB-IoT
1.8.9 LoRa
1.8.10 SigFox
1.8.11 TV White Space
1.8.12 WiFi-Direct
1.8.13 Gateways and Networks
1.8.14 Management Service Layer
1.8.15 Application Layer
1.8.16 IoT Software
1.8.17 Data Collection
1.8.18 Device Integration
1.8.19 Real-Time Analytics
1.8.20 Applications and Process Extension
1.9 IoT Standards and Frameworks
1.10 Enabling Technologies for IoT
1.11 Future Technological Developments for IoT
1.12 Future Application Areas
1.13 Pros and Cons of IoT
1.14 IoT Security and Privacy Issues
1.15 Tips to Help Secure User’s Smart Home and IoT Devices
1.16 Future Challenges for IoT
1.16.1 Privacy and Security
1.16.2 Cost Versus Usability
1.16.3 Interoperability
1.16.4 Data Management
1.16.5 Impact of COVID-19 Pandemic On IoT
1.17 Conclusion
References
2 Application of IoT for Pandemic Detection
2.1 Introduction
2.2 Emergency Care System
2.3 Previous Works
2.4 Application of IoT and Smart Technology for Pandemic Detection
2.5 Conclusion
References
3 TV White Space (TVWS) Technology
3.1 Introduction
3.2 Underutilised Spectrum
3.3 Evolution of TVWS
3.4 Standardisation of TVWS
3.5 Regulations On TVWS
3.5.1 Regulation in the USA
3.5.2 Regulation in Singapore
3.5.3 Regulation in the UK
3.5.4 Regulation in Canada
3.5.5 Regulation in Colombia
3.5.5.1 DTT and TVWS Systems Co-Existence In Colombia
3.5.6 Regulation in South Africa
3.5.7 Regulation in Ghana
3.5.8 Regulation in New Zealand
3.5.9 Regulation in South Korea
3.5.10 Draft Regulation in Uganda
3.5.11 Draft Regulation in Nigeria
3.5.12 Draft Regulation in Kenya
3.5.13 Draft Regulation in the Philippines
3.5.14 Draft Regulation in Brazil
3.5.15 Draft Regulation in Brunei
3.5.16 TV Spectrum Allocation in India
3.5.17 Draft Regulation in Pakistan
3.5.18 Draft Regulation in Australia
3.6 The Limitations of TVWS Regulation
3.7 Commercial Pilots and Trials of TVWS
3.7.1 Botswana Pilot Project (March 2015)
3.7.2 Ghana Commercial Pilot (May 2014)
3.7.3 Namibia Trial (August 2014)
3.7.4 The Philippines (July 2013)
3.7.5 India Pilot Trials (Nov 2015)
3.7.6 South Africa Commercial Pilot (July 2013)
3.7.7 Tanzania Commercial Pilot (May 2013)
3.7.8 Kenya “Mawingu” Commercial Pilot (February 2013)
3.7.9 Singapore Commercial Pilot (April 2012)
3.7.10 Cambridge White Spaces Trial (June 2011)
3.7.11 Claudville, Virginia (September 2009)
3.8 Applications and Use Cases of TVWS
3.8.1 Cost Comparison and Performance Comparison of TVWS Compared to Alternate Solutions for Various Applications
3.9 SWOT Analysis
3.10 Conclusion
References
4 Health Monitoring and Pandemic Detection Using IoT and Wireless Communication Technologies
4.1 Introduction
4.2 Previous Works
4.3 Proposed Model
4.4 Conclusions
References
5 V2V: The Future of VANET’s Communications
5.1 Vehicular Ad-Hoc Network (VANET)
5.2 Communication Domains of VANET
5.3 VANET’s Characteristics
5.4 VANET’s Challenges
5.5 VANET Applications
5.5.1 Safety Applications
5.5.2 Commercial and Comfort Applications
5.5.3 Entertainment Related Applications
5.5.4 Urban Sensing and Health Monitoring Applications
5.6 Vehicle-To-Vehicle Communication (V2V)
5.7 Working of V2V Communication
5.7.1 Vehicle-To-X Communication (V2X)
5.8 Benefits of V2V Communications
5.9 V2V Tracking and Reporting
5.10 V2V Security in Communication
5.11 Future of V2V Communication
5.12 Conclusion
References
6 IoT Based Flood Control and Disaster Management System for Dam and Barrage
6.1 Introduction
6.2 Investigations On Dam and Barrage Monitoring
6.3 Circuit Configuration for Monitoring and Control of Dam/Barrage
6.4 Conclusions
References
7 An Overview of Smart Antenna Technology for Wireless Communication
7.1 Introduction
7.2 Smart Antenna
7.3 Advantages and Disadvantages of Smart Antennas
7.3.1 Advantages of Smart Antenna
7.3.2 Disadvantages of Smart Antenna
7.4 Types of Smart Antenna System
7.4.1 Switched Beam System
7.4.2 Digitally Adaptive Beamforming (DAB) System
7.5 Difference Between Switched Beam System and Digitally Adaptive Beamforming System
7.6 Applications of Smart Antenna System
7.7 Conclusions
References
8 UAV: Communication and Object Detection System
8.1 Introduction
8.2 Application Scenarios of UAVs
8.2.1 Research Trends and Technologies
8.2.2 Construction and Infrastructure Investigation
8.2.3 Media and Entertainments
8.2.4 Product Delivery
8.2.5 Onboard Health Planning
8.2.6 Smart City Management
8.2.7 Reconnaissance and Patrolling
8.3 Major Issues and Challenges of UAVs
8.3.1 Mobility Models
8.3.2 High Reliability
8.3.3 Routing
8.3.4 Path Scheduling
8.3.5 Quality of Service (QoS)
8.3.6 Security Issues
8.3.7 Energy Constraint
8.4 UAV Communications
8.4.1 Object Detection System
8.4.2 Limitations of Automating the Utilization of Aerial Imagery
8.5 Conclusion
References
9 Smart Pole System: A Connectivity to City Services
9.1 Introduction
9.2 Limitations of Conventional Pole System
9.3 Benefits of Smart Pole System
9.3.1 Improving City Operations
9.3.2 Decreasing Emergency Response Time
9.3.3 Environmental Aspects
9.3.4 Data Monetization Probabilities
9.3.5 International Market
9.4 Smart Pole System Design
9.4.1 5G Enabled Smart Pole With LED Street Lighting
9.4.2 PIR Sensor
9.4.3 Wi-Fi Hotspot Services
9.4.4 CCTV Surveillance Camera
9.4.5 Traffic Control Management
9.4.6 Air Pollution Sensors
9.4.7 Electronic Vehicle Charger
9.4.8 Fast EV Charging
9.4.9 Smart Billboard
9.4.10 Mobile Applications
9.4.11 Integration With Command and Control Centre
9.4.12 Integrated Antenna On Smart Pole
9.5 Conclusion
References
Index

Citation preview

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Wireless Communication This reference text will benefit readers in enhancing their understanding of the recent technologies, protocols, and challenges in various stages of development of wireless communication and networking. The text discusses the cellular concepts of 4G, 5G, and 6G along with their challenges. It covers topics related to vehicular technology, wherein vehicles communicate with the traffic and the environment around them using short-​range wireless signals. The text comprehensively covers important topics including use of the Internet of Things (IoT) in wireless communication, architecture, and protocols. It further covers the role of smart antennas in emerging wireless technologies. The book • Discusses advanced techniques used in the field of wireless communication. • Covers technologies including network slicing, 5G wireless communication, and TV white space technology. • Discusses practical applications including drone delivery systems, public safety, IoT, virtual reality, and smart cities. • Covers radio theory and applications for wireless communication with ranges of centimeters to hundreds of meters. • Discusses important topics including metamaterials, inductance coupling for loop antennas, bluetooth low energy, wireless security, and wireless sensor networks. Discussing latest technologies including 5G, 6G, IoT, vehicular technology and TV white space technology, this text will be useful for senior undergraduate, graduate students, and professionals in the fields of electrical engineering, and electronics and communication engineering.

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Wireless Communications and Networking Technologies: Classifications, Advancement and Applications Series Editor: D.K. Lobiyal, R.S. Rao and Vishal Jain

The series addresses different algorithms, architecture, standards and protocols, tools and methodologies which could be beneficial in implementing next generation mobile network for the communication. Aimed at senior undergraduate students, graduate students, academic researchers and professionals, the proposed series will focus on the fundamentals and advances of wireless communication and networking, and their such as mobile ad-​hoc network (MANET), wireless sensor network (WSN), wireless mess network (WMN), vehicular ad-​hoc networks (VANET), vehicular cloud network (VCN), vehicular sensor network (VSN) reliable cooperative network (RCN), mobile opportunistic network (MON), delay tolerant networks (DTN), flying ad-​hoc network (FANET) and wireless body sensor network (WBSN). Cloud Computing Enabled Big-​Data Analytics in Wireless Ad-​hoc Networks Sanjoy Das, Ram Shringar Rao, Indrani Das, Vishal Jain and Nanhay Singh Smart Cities Concepts, Practices, and Applications Krishna Kumar, Gaurav Saini, Duc Manh Nguyen, Narendra Kumar and Rachna Shah Wireless Communication Advancements and Challenges Prashant Ranjan, Ram Shringar Rao, Krishna Kumar and Pankaj Sharma For more information about this series, please visit: www.routle​dge.com/​Wirel​ess%20 Com​muni​cati​ons%20and%20Net​work​ing%20T​echn​olog​ies/​book-​ser​ies/​WCANT

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Wireless Communication Advancements and Challenges

Prashant Ranjan, Ram Shringar Rao, Krishna Kumar and Pankaj Sharma

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First edition published 2023 by CRC Press 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-​2742 and by CRC Press 4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN CRC Press is an imprint of Taylor & Francis Group, LLC © 2023 Prashant Ranjan, Ram Shringar Rao, Krishna Kumar and Pankaj Sharma Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www.copyri​ght.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-​750-​ 8400. For works that are not available on CCC please contact [email protected] Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. ISBN: 9780367751593 (hbk) ISBN: 9781032020655 (pbk) ISBN: 9781003181699 (ebk) DOI: 10.1201/​9781003181699 Typeset in Times by Newgen Publishing UK

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Contents Preface........................................................................................................................xi Readers.....................................................................................................................xiii Chapter Organization................................................................................................ xv About the Authors...................................................................................................xvii Chapter 1 Internet of Things (IoT)......................................................................... 1 1.1

1.2 1.3 1.4 1.5 1.6

1.7 1.8

Introduction................................................................................. 1 1.1.1 Internet of Things Vision............................................... 1 1.1.2 Evolution and Rapid Adoption of IoT........................... 2 1.1.3 The Need for M2M Connectivity.................................. 2 1.1.4 The Chicken and Egg Analogy...................................... 3 The Continuing Evolution of IoT...............................................3 The Key Drivers of Rapid Adoption of IoT................................ 4 How Does IoT Work................................................................... 5 Importance of IoT....................................................................... 6 Benefits of IoT to Businesses...................................................... 6 1.6.1 Consumer and Enterprise IoT Applications.................. 7 1.6.2 Engineering, Industry, and Infrastructure...................... 7 1.6.3 Home Applications........................................................ 8 1.6.4 Wearables...................................................................... 8 1.6.5 Healthcare and Medicine............................................... 9 1.6.6 Smart Cities................................................................... 9 1.6.7 Smart Grid and Smart Meters...................................... 10 1.6.8 Agri-​tech...................................................................... 11 1.6.9 Tyre Air Pressure Detection........................................ 13 1.6.10 Personal IoT Applications........................................... 13 1.6.10.1 Gesture Control Armband......................... 13 1.6.10.2 Smart Glass............................................... 13 1.6.10.3 Smart Eye.................................................. 13 1.6.10.4 Pulse Oximeter.......................................... 13 Potential of IoT......................................................................... 14 Architecture of IoT................................................................... 18 1.8.1 Smart Device/​Sensor Layer......................................... 18 1.8.2 IoT –​Technology and Protocols.................................19 1.8.3 RFID and NFC............................................................ 19 1.8.4 Low-​Energy Bluetooth (BLE)..................................... 19 1.8.5 Low-​Energy Wireless.................................................. 19 1.8.6 Radio Protocols........................................................... 19 1.8.7 LTE-​Advanced............................................................19 1.8.8 NB-​IoT........................................................................ 20 1.8.9 LoRa............................................................................ 20 v

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1.9 1.10 1.11 1.12 1.13 1.14 1.15 1.16

1.17

1.8.10 SigFox.........................................................................20 1.8.11 TV White Space.......................................................... 20 1.8.12 WiFi-​Direct.................................................................. 20 1.8.13 Gateways and Networks.............................................. 21 1.8.14 Management Service Layer......................................... 21 1.8.15 Application Layer........................................................ 22 1.8.16 IoT Software................................................................ 22 1.8.17 Data Collection............................................................ 23 1.8.18 Device Integration....................................................... 23 1.8.19 Real-​Time Analytics.................................................... 23 1.8.20 Applications and Process Extension...........................24 IoT Standards and Frameworks................................................ 24 Enabling Technologies for IoT................................................. 25 Future Technological Developments for IoT............................ 27 Future Application Areas.......................................................... 29 Pros and Cons of IoT................................................................ 32 IoT Security and Privacy Issues................................................ 33 Tips to Help Secure User’s Smart Home and IoT Devices....... 33 Future Challenges for IoT......................................................... 34 1.16.1 Privacy and Security.................................................... 34 1.16.2 Cost versus Usability................................................... 35 1.16.3 Interoperability............................................................ 35 1.16.4 Data Management.......................................................36 1.16.5 Impact of COVID-19 Pandemic on IoT...................... 36 Conclusion................................................................................ 40

Chapter 2 Application of IoT for Pandemic Detection........................................ 43 2.1 2.2 2.3 2.4 2.5

Introduction............................................................................... 43 Emergency Care System........................................................... 43 Previous Works......................................................................... 45 Application of IoT and Smart Technology for Pandemic Detection................................................................................... 48 Conclusion................................................................................ 50

Chapter 3 TV White Space (TVWS) Technology................................................ 53 3.1 3.2 3.3 3.4 3.5

Introduction............................................................................... 53 Underutilised Spectrum............................................................ 54 Evolution of TVWS.................................................................. 58 Standardisation of TVWS......................................................... 62 Regulations on TVWS.............................................................. 66 3.5.1 Regulation in the USA................................................ 66 3.5.2 Regulation in Singapore.............................................. 67 3.5.3 Regulation in the UK................................................... 71 3.5.4 Regulation in Canada.................................................. 72 3.5.5 Regulation in Colombia............................................... 72

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3.5.6 Regulation in South Africa.......................................... 75 3.5.7 Regulation in Ghana.................................................... 76 3.5.8 Regulation in New Zealand......................................... 78 3.5.9 Regulation in South Korea.......................................... 78 3.5.10 Draft Regulation in Uganda........................................ 80 3.5.11 Draft Regulation in Nigeria......................................... 80 3.5.12 Draft Regulation in Kenya........................................... 81 3.5.13 Draft Regulation in the Philippines............................. 81 3.5.14 Draft Regulation in Brazil........................................... 82 3.5.15 Draft Regulation in Brunei.......................................... 84 3.5.16 TV Spectrum Allocation in India................................ 84 3.5.17 Draft Regulation in Pakistan....................................... 87 3.5.18 Draft Regulation in Australia...................................... 88 3.6 The Limitations of TVWS Regulation...................................... 89 3.7 Commercial Pilots and Trials of TVWS................................... 92 3.7.1 Botswana Pilot Project (March 2015)......................... 92 3.7.2 Ghana Commercial Pilot (May 2014)......................... 92 3.7.3 Namibia Trial (August 2014)...................................... 92 3.7.4 The Philippines (July 2013)........................................ 92 3.7.5 India Pilot Trials (Nov 2015)....................................... 93 3.7.6 South Africa Commercial Pilot (July 2013)................ 93 3.7.7 Tanzania Commercial Pilot (May 2013)..................... 93 3.7.8 Kenya “Mawingu” Commercial Pilot (February 2013)........................................................... 93 3.7.9 Singapore Commercial Pilot (April 2012).................. 93 3.7.10 Cambridge White Spaces Trial (June 2011)................ 94 3.7.11 Claudville, Virginia (September 2009)........................ 94 3.8 Applications and Use Cases of TVWS..................................... 95 3.8.1 Cost Comparison and Performance Comparison of TVWS Compared to Alternate Solutions for Various Applications.............................. 98 3.9 SWOT Analysis......................................................................... 99 3.10 Conclusion................................................................................ 99 Chapter 4 Health Monitoring and Pandemic Detection Using IoT and Wireless Communication Technologies............................................ 105 4.1 4.2 4.3 4.4

Introduction............................................................................. 105 Previous Works....................................................................... 107 Proposed Model...................................................................... 110 Conclusions............................................................................. 113

Chapter 5 V2V: The Future of VANET’s Communications............................... 115 5.1 5.2 5.3

Vehicular Ad-​hoc Network (VANET)..................................... 115 Communication Domains of VANET..................................... 116 VANET’s Characteristics........................................................ 117

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5.4 5.5

VANET’s Challenges.............................................................. 118 VANET Applications.............................................................. 119 5.5.1 Safety Applications................................................... 119 5.5.2 Commercial and Comfort Applications..................... 119 5.5.3 Entertainment Related Applications.......................... 119 5.5.4 Urban Sensing and Health Monitoring Applications.............................................................. 120 5.6 Vehicle-​to-​Vehicle Communication (V2V)............................. 120 5.7 Working of V2V Communication........................................... 121 5.7.1 Vehicle-​to-​X Communication (V2X)........................ 122 5.8 Benefits of V2V Communications.......................................... 123 5.9 V2V Tracking and Reporting.................................................. 124 5.10 V2V Security in Communication............................................ 124 5.11 Future of V2V Communication.............................................. 125 5.12 Conclusion.............................................................................. 126 Chapter 6 IoT Based Flood Control and Disaster Management System for Dam and Barrage......................................................................... 129 6.1 6.2 6.3 6.4

Introduction............................................................................. 129 Investigations on Dam and Barrage Monitoring..................... 133 Circuit Configuration for Monitoring and Control of Dam/​Barrage........................................................................... 136 Conclusions............................................................................. 136

Chapter 7 An Overview of Smart Antenna Technology for Wireless Communication................................................................................. 139 7.1 7.2 7.3 7.4 7.5 7.6 7.7

Introduction............................................................................. 139 Smart Antenna......................................................................... 139 Advantages and Disadvantages of Smart Antennas................ 141 7.3.1 Advantages of Smart Antenna................................... 141 7.3.2 Disadvantages of Smart Antenna.............................. 142 Types of Smart Antenna System............................................. 142 7.4.1 Switched Beam System............................................. 143 7.4.2 Digitally Adaptive Beamforming (DAB) System..... 145 Difference Between Switched Beam System and Digitally Adaptive Beamforming System............................... 147 Applications of Smart Antenna System.................................. 148 Conclusions............................................................................. 148

Chapter 8 UAV: Communication and Object Detection System........................ 151 8.1 8.2

Introduction............................................................................. 151 Application Scenarios of UAVs.............................................. 152 8.2.1 Research Trends and Technologies........................... 153 8.2.2 Construction and Infrastructure Investigation........... 154 8.2.3 Media and Entertainments......................................... 154

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8.2.4 Product Delivery........................................................ 154 8.2.5 Onboard Health Planning.......................................... 154 8.2.6 Smart City Management............................................ 154 8.2.7 Reconnaissance and Patrolling.................................. 154 8.3 Major Issues and Challenges of UAVs.................................... 155 8.3.1 Mobility Models........................................................ 155 8.3.2 High Reliability......................................................... 156 8.3.3 Routing...................................................................... 156 8.3.4 Path Scheduling......................................................... 156 8.3.5 Quality of Service (QoS)........................................... 156 8.3.6 Security Issues........................................................... 156 8.3.7 Energy Constraint...................................................... 157 8.4. UAV Communications............................................................ 157 8.4.1 Object Detection System........................................... 157 8.4.2 Limitations of Automating the Utilization of Aerial Imagery........................................................... 159 8.5 Conclusion.............................................................................. 159 Chapter 9 Smart Pole System: A Connectivity to City Services........................ 163 9.1 9.2 9.3

9.4

9.5

Introduction............................................................................. 163 Limitations of Conventional Pole System..............................165 Benefits of Smart Pole System................................................ 165 9.3.1 Improving City Operations........................................ 165 9.3.2 Decreasing Emergency Response Time.................... 166 9.3.3 Environmental Aspects.............................................. 166 9.3.4 Data Monetization Probabilities................................ 166 9.3.5 International Market.................................................. 166 Smart Pole System Design...................................................... 166 9.4.1 5G Enabled Smart Pole with LED Street Lighting..................................................................... 166 9.4.2 PIR Sensor................................................................. 167 9.4.3 Wi-​Fi Hotspot Services............................................. 167 9.4.4 CCTV Surveillance Camera...................................... 168 9.4.5 Traffic Control Management..................................... 168 9.4.6 Air Pollution Sensors................................................ 168 9.4.7 Electronic Vehicle Charger........................................ 169 9.4.8 Fast EV Charging...................................................... 169 9.4.9 Smart Billboard......................................................... 170 9.4.10 Mobile Applications.................................................. 171 9.4.11 Integration with Command and Control Centre........ 171 9.4.12 Integrated Antenna on Smart Pole............................. 172 Conclusion.............................................................................. 172

Index....................................................................................................................... 177

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Preface Today and in the future, wireless technology plays a significant role in human life. New forms of emerging wireless technologies include self-​driving vehicles, 5G and beyond cellular technology, backscatter-​networking technology, network slicing, IoT, etc. Keeping this in mind, the present book aims to explore the various technologies emerging in wireless communication. The concept of technological advancements and issues related to them will be discussed in detail. 5th generation cellular network (5G) is a new global wireless technology after 1G, 2G, 3G, and 4G networks. 5G provides a new kind of network which is designed to connect virtually everyone and everything, including devices, objects, and machines. Billions of smart objects being connected through the cellular network is the vision of the Internet of Things. It needs to address the problem of uninterrupted power consumption. Backscatter networking technology is a solution to the limited battery life problem and enables future battery-​free communications for combatting the energy issues for devices in emerging wireless networks. Uses of the Internet of Things for industrial plants’ real-​time monitoring and operation may help optimize the system’s performance. Both self-​driving and conventional cars will need to communicate with each other and also with road infrastructure. This will be facilitated by Vehicle-​to-​everything (V2X) wireless technology. V2X technology is to pass the information from a vehicle to any object that may affect the vehicle and vice versa. The main motivations for V2X are traffic efficiency, energy savings, and road safety. Smart antenna have an important influence on the optimization of service quality, the cost minimization during establishment of new wireless networks, efficient use of the spectrum, and recognition of transparent operation through multi technology wireless networks.

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Readers This book is helpful for researchers, academicians, and developers working in the area of wireless communication, intelligent transport systems, IoT applications, and smart antennas. The main features of the book are: • It has covered all the latest developments and future aspects of wireless technologies. • This book is very useful for the new researchers and developers working to learn the best-​performing methods quickly. • The book is concisely written, lucid, comprehensive, application-​based, graphical, schematics and covers all aspects of wireless communication.

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Chapter Organization In Chapter 1, the evolution of the Internet of Things (IoT) and the architecture have been discussed. The available technological challenges for IoT have also been discussed in detail. In Chapter 2, the application of IoT for pandemic detection and emergency care systems has been discussed. One IoT-​based architecture has also been suggested for pandemic detection. A detailed discussion on TV white space (TVWS) technology has been discussed with their standardization and limitations in Chapter 3. This chapter has also discussed the existing regulation on TVWS, commercial pilots & trials, and SWOT analysis. The discussion on health monitoring and pandemic detection using IoT and wireless communication Technologies has been presented in Chapter 4. In Chapter 5, the future of VANET’s communications, vehicular Ad-​hoc network (VANET), Communication Domains of VANET, VANET’s Characteristics, Vehicle-​ to-​Vehicle Communication (V2V), and V2V Security in Communication has been discussed in detail. IoT-​based flood control and disaster management system for dam and barrage and circuit configuration have been discussed in Chapter 6. In Chapter 7, an overview of smart antenna technology and adaptive beamforming system has been discussed. The UAV communication, object detection system, and their issues have been discussed in Chapter 8. In Chapter 9, smart pole system and their limitations of design have been discussed.

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About the Authors Dr. Prashant Ranjan is presently working as an Associate Professor in the Department of Electronics and Communication Engineering, University of Engineering and Management Jaipur, Rajasthan, India. He received his M.Tech and Ph.D. degree from Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh, India. He has more than five years of teaching experience. He has published numerous research papers in international journals and conferences, including IEEE, Elsevier, Taylor & Francis. His present area of research includes the design and development of UWB filtering antennas, vehicle-​to-​vehicle wireless technology, Non-​Invasive RF Sensors, Agricultural & Medical Applications.

Dr. Ram Shringar Rao received his Ph.D. (Computer Science and Technology) from School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India. He has obtained his M. Tech (IT) and B. E. (CSE) 2005 and 2000 respectively. He has worked as an Associate Professor in the Department of Computer Science, Indira Gandhi National Tribal University (A Central University, MP) from April 2016 to March 2018. He is currently working in the Department of Computer Science and Engineering of Netaji Subhas University of Technology, East Campus, Delhi, India. He has more than 18 years of teaching, administrative and research experience. Currently, he is associated with a wide range of journals and conferences as chief editor, editor, chairs and members. Dr. Rao has published more than 100 research papers including edited books with good impact factors in reputed International Journals and Conferences including IEEE, Elsevier, Springer, Wiley & Sons, Taylor & Francis, IERI Letters, American Institute of Physics, etc. He has supervised 25 M. Tech and four PhD students for their dissertation and thesis work. His current research interests include Mobile Ad hoc Networks, Vehicular Ad hoc Networks, Flying Ad-​hoc Networks and Cloud Computing.

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About the Authors

Er. Krishna Kumar is presently working as a Research and Development Engineer at UJVN Ltd. Before joining UJVNL he has worked as Assistant Professor at BTKIT, Dwarahat. He received his B.E. (Electronics and Communication Engineering) from Govind Ballabh Plant Engineering College, Pauri Garhwal, M.Tech (Digital Systems) from Motilal Nehru NIT Allahabad. He is presently pursuing his Ph.D. from the Indian Institute of Technology, Roorkee. He has more than 11 years of experience and has published numerous research papers in international journals like IEEE, Elsevier, Taylor & Francis, Springer, and Wiley. His research areas include Renewable Energy and Artificial Intelligence. Mr. Pankaj Sharma is M.Sc. (Physics), M.Tech. (Microwave Electronics) from University of Delhi & MBA from Lancaster University (UK). He was a senior researcher at A*STAR (Singapore’s premium research organization) and developed many wireless communication technologies & products with Indian and Singapore technology companies. He led many deployment projects in many countries. He filed many patents and published various research papers in reputed journals and conferences. He is currently CTO & Co-​Founder of Whizpace Pvt. Ltd., a spin-​off from A*STAR and running the company and secured many projects in Singapore & overseas, connecting the unconnected. Harnessing the power of TV White Space technology.

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Internet of Things (IoT)

1.1  INTRODUCTION The concept of IoT was invented in 1999 by the Radio Frequency Identification (RFID) research group member and has recently become more applicable to society, essentially due to the rise of mobile phones, embedded systems and ubiquitous networking, data processing and cloud computing [1]. In the near future, there will be billions of devices sensing, interacting, and exchanging information, connected over private or public Internet Protocol (IP) networks. The interconnected devices collect data on a regular basis, which is then processed and action initiated accordingly. This provides a large quantity of information for strategy, management, and decision-​ making. This is the world of IoT [3]. IoT can be broadly categorized into three categories as below: 1. Things/things to things/machine, interacting through the internet. 2. People to people. 3. People to machine/things.

1.1.1 Internet of Things Vision IoT is a concept that recognizes the ubiquitous presence in wired and wirelessly connected devices and has special addressing schemes capable of communicating with each other to build new applications and services. However, there are enormous R&D challenges to create a smart world. We are creating a world where tangible objects and virtual services are converging to create smart ecosystems to make energy consumption, transport management, cities operation, and many other areas more intelligent [4]. Another definition of IoT refers to the general idea of things, mostly everyday objects that are readable, recognised, located, addressed through information sensing device, and controlled by smartphones or internet, irrespective of the communication means. These means could be RFID, WiFi, and wide area networks (WAN). These artefacts include electronic devices, items of deep-​tech growth, such as auto industry and heavy machinery, and non-​electronics items, such as food, water, clothes, furniture, plants, livestock, etc. IoT is a modern Internet movement DOI: 10.1201/9781003181699-1

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in which devices are recognised and receive information by making context-​based decisions [4]. Besides, they can express their criteria and view knowledge that has been aggregated from other items. This transformation of communication is concurrent with the transition from the Internet to IPv6 with unlimited addressing capacity and cloud computing evolution [4]. The IoT aims to make it possible for devices to be linked to something and anyone, anywhere, preferably using any service, path, or network.

1.1.2 Evolution and Rapid Adoption of IoT The concept of IoT is not new and is now one of the fastest business success generators. It is important to hear more about how IoT has grown over the last two decades and became part of mainstream business now.

1.1.3 The Need for M2M Connectivity The idea of connecting the physical systems or machines has been a matter of interest to technological innovators, and numerous developments have been made since then. RFID has been used for a very long time by suppliers of consumer products and retailers on costly goods and palettes for quick inventory control. The word “IoT” was not envisaged at the time. The essential context of making multiple machines interact with each other over a distance to increase performance has always been the ideal means of operation. Nevertheless, the concept of integration RFID with networking technologies by MIT professor Kevin Asht was a breakthrough when he incepted the Internet of Things (IoT) term (Figure 1.1). As soon as IoT started to incorporate the connecting and remotely tracking methods of different organizations into a shared system, it was not possible to look back.

FIGURE 1.1  From RFID to IoT (Source: Mojix).

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FIGURE 1.2  Inception of IoT is similar to the chicken-​egg problem (Source: Pinterest).

1.1.4 The Chicken and Egg Analogy It makes sense to compare the IoT evolution and RFID to the chicken or egg causality problem (Figure 1.2). While Ashton coined the term IoT to describe connecting physical objects via RFID, the concept of linking physical structures existed well before that.

1.2  THE CONTINUING EVOLUTION OF IOT Below is the evolution of IoT development timelines: Year 1999: Kevin Ashton, co-​founder of the MIT Auto-​ID Centre, invented the word “Internet of Things”. Its concept of IoT was based on integrating RFID with networking technology by connecting devices to the internet using the RFID symbol. Ashton had the vision to create a system “where computers would be capable of gathering information without human help and deliver it into useful information, which would be possible with technologies like sensors and RFID that enable computers to observe, identify and understand the world.” Year 1999: Device to Device (D2D) connectivity definition was conceived by Bill Joy for his “Six Webs” system of the World Economic Forum. Year 2000: World’s the first internet-​connected refrigerator, LG Wireless Digital DIOS, was invented with an IP networking LAN port. Year 2001: A modern object recognition system, the Electronic Product Code (EPC) instead of the standard Universal Product Code (bar code) for specific identification and monitoring of objects over the entire product life cycle using the network was proposed by David Brock (co-​director of the Auto-​ID Center in MIT). Year 2003: “Project JXTA-​C: Enabling a Web of Things” was presented by Bernard Traversat and his team at the 36th Annual Hawaii International Conference. The JXTA project aimed to define a common series of protocols for the ad-​hoc, ubiquitous, peer-​to-​peer computing as the basis for the upcoming Web of Things.

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McCormick Place Conference Center established unique network to link millions of tags that existed at that time in the world. It was introduced to the delegates from all over the field of retail, technology and academics engaged in unveiling the electronic product code (EPC) network. They aimed to replace global barcodes with a standardized framework with unique identification for every device in the world. People started calling this network ‘the Internet of Things.’ Year 2005: A single-​board microcontroller used in immersive projects was built by Faculty of Interaction Design Institute Ivrea, Italy. Later in the same year, the ITU released a paper entitled “The Internet of Things”. Year 2008: A variety of industry players have come together to support connected devices. This was a massive step in IoT being introduced in a real manufacturing plant for the large-​scale enterprise. Beyond 2016: IoT has spread its wings across many industries, such as connected homes, connected vehicles, IoT enabled factories, connected offices, and IoT based solar trackers. Thus, a newer term “Industrial IoT (IIoT)” was launched, which includes devices used in industries. It was postulated that there would be around 50 billion connected devices by 2020. With the new technological inventions, IoT’s scope and definition have changed from what Ashton had envisioned. However, the basic principle of connected devices interacting with each other in a network to analyse the collected information using internet remains unchanged. The IoT system based on RFID model has not gained adequate publicity over the years due to restricted networking opportunities and high costs for hardware and infrastructure. Besides, the RFID-​based system was not ideal for large-​scale industrial automation. Nevertheless, the IP-​based wireless network and many other technological developments helped IoT continue developing for many applications.

1.3  THE KEY DRIVERS OF RAPID ADOPTION OF IOT [5] Below are the key drivers for the rapid adoption of IoT across various industries: a) Networking capabilities evolution: Currently, various wireless technologies such as WiFi, Bluetooth, ZigBee, Z-​Wave, DECT and Thread enable connectivity between users. In addition to these technologies, the peer-​to-​peer networking technologies AllSeen, DLNA, and UPnP are also available. b) Cloud computing development: The rapid development in cloud computing is also a significant factor in making IoT available. The cloud provides low-​ cost storage and retrieval of data and info. Availability of accessible cloud infrastructure has enabled streamlined unloading of IoT network storage and processing activities on cloud servers. This made many companies implement IoT more effortlessly. IoT and cloud are now inseparably connected and applied to streamline complicated market issues. c) Cost reduction: The availability of various sensors and connected devices at low cost has benefited mid-​size and small-​scale businesses.

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FIGURE 1.3  The IoT adoption and evolution of big data connection.

d) Advances in data processing and analysis: Data handling and data analysis capability have increased tremendously over the last decade. Data processing and interpretation are the USP of IoT based devices. Advances in data analysis have also opened new instances in IoT applications. Many embedded devices communicate and share a massive amount of data in several data formats. The magic of translating data to make sense and making money from it is achievable by introducing significant data processing software. Various data analytics methods, such as Time Series, Spatial, and Streaming Analytics, are used to analyse data that differ in both structure and formats. These make use of structured and unstructured data, such as location and time-​based data. Advances in data analytics have enabled companies to embrace IoT broadly and have opened new possibilities for market growth and expansion, as depicted in Figure 1.3. In addition, the rapid implementation of IoT was made possible by: 1. Improvement in the field of data traffic, processing and storage, and data amounts, 2. Innovation of newer norms for networking from nodes to edges and software from different provider.

1.4  HOW DOES IOT WORK The IoT ecosystem consists of nodes with sensors, internet-​enabled smart edge devices integrated with embedded systems, such as sensors, processors, and communication module, to transmit, receive and process the parameters these devices acquire from the nodes. IoT devices share the sensor data they collect and send to a gateway or an edge device through wireless communication protocols. Data may be sent to the cloud to be analysed (on cloud services) or might be analysed locally

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Wireless Link Nodes with SSen ensorss ensor Sensors

On-Premises Gateway

On Cloud Cloud Services

IoT Network #1

UI/UX

Wireless Link

Nodes with Sensors Gateway

IIoTT Network N t k #2

FIGURE 1.4  Typical IoT network.

(on-​premises). These devices sometimes communicate with other peer devices and process the information they get from each other in a mesh topology. The devices get connected to the cloud through edge without any human intervention, though humans can setup and access the data. So, there is a need for two-​way communication from IoT sensors to analysing device and vice-​versa. Connectivity, networking, and communication protocols used by edge devices rely on the deployed IoT use cases. IoT may also allow machine learning (ML) and artificial intelligence (AI) to help make data collection processes more dynamic and simpler. Figure 1.4 provides an overview of how the standard IoT system operates from data collection to execution.

1.5  IMPORTANCE OF IOT IoT helps people’s life and work smarter and more productively. Not only can these smart devices simplify households, but IoT is also vital for companies. IoT provides organisations with real-​time info on how the operational process is carried out and delivers insight into device efficiency distribution activities and supply chain. IoT also allows businesses to simplify processes and reduce manpower costs. It further increases service quality, decreases waste, lowers the expense of making and distributing products, and provides accountability in consumer purchases. In plantation, IoT helps increase yield and efficiency. IoT is one of the most important innovations to pick up.

1.6  BENEFITS OF IOT TO BUSINESSES IoT provides a range of incentives to businesses. Some of the advantages are industry-​ specific, and some are common to many sectors. The expected benefits of IoT enabled companies are to [6]:

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save time and money, monitor their overall business processes, make better business decisions, enhance employees’ productivity, improve the customer experience, integrate and adapt business models, and generate more revenue.

The IoT can help to monitor operations surrounding infrastructures, such as changes in the structure of buildings, bridges, and other infrastructure using adequate sensors. IoT offers advantages such as reduction of cost, time savings, quality of people’s life, improvements in the organization’s process, and a paperless workflow. IoT related to home automation helps to track and manage electrical and mechanical equipment in a house. Smart cities will help people minimize pollution and energy use and improve their quality of life on a larger scale. IoT covers all industries, including healthcare, finance, retail, and manufacturing enterprises.

1.6.1 Consumer and Enterprise IoT Applications The applications of IoT are spread across all markets and industries. It covers users from technology freaky individuals, who care and want to have an energy-​efficient home to those who want to streamline their operations and improve efficiency in large organizations. IoT usage is becoming useful and critical in many industries. IoT is especially important in factories, transportation, logistics, and public utility organizations. However, IoT has also applications for organizations dealing with infrastructure, agriculture, and home automation, leading some organizations towards digital transformation.

1.6.2 Engineering, Industry, and Infrastructure Consumer IoT, commercial IoT, manufacturing, and industrial IoT are just a few examples of real-​world internet of things applications (IIoT). IoT applications can be found in a variety of industries, including telecommunications, automotive, and energy. Marketing, production, safety, and service delivery are just a few of the areas where IoT may help. IoT allows for the monitoring of numerous operations as well as true transparency, resulting in more visibility and improved prospects. IoT’s deep level of control allows for faster and more action on those opportunities, which include non-​conforming items, clear client needs, equipment faults, distribution network difficulties, and more. One of the examples in a manufacturing facility is in the shields used for manufacturing equipment. When the function of the shields and regulations changes for the specifications of composition, the new appropriate requirements are programmed automatically in the robots deployed in the factory, and engineers are alerted about these changes. Another example is seamless communication where a robot is engaged in carrying out a real-​time job in a factory environment. As per Industry

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FIGURE 1.5  Seamless OT connectivity to robot (Source: Whizpace).

4.0 guidelines, the IT (information technology) and OT (operational technology) networks must be isolated to avoid any delay and congestions. Figure 1.5 illustrates one of the deployments with OT connectivity to a moving robot.

1.6.3 Home Applications In our daily lives, the Internet of Things increases our overall enjoyment, productivity, and health and safety. IoT can assist us in customizing our working space in order to maximize our productivity. Smart homes have smart appliances, smart thermostats, lighting, connected heating, and electrical gadgets that can be managed remotely via computers and smartphones in the consumer market. Sensors that identify how many people are in a room are used in smart buildings to decrease energy expenses. If sensors identify a full or empty conference room, the temperature might adjust automatically, turning the air conditioner on or off, and even bringing the heat down if everyone left the office. The Internet of Things (IoT) combines lighting control with mesh networking to create large-​scale, dependable wireless lighting systems for households. The inbuilt sensors can also detect the presence of individuals and turn off the lights when they are not there. This lighting system is intended for use in both home and business settings to reduce energy consumption. IoT appliances that aim to provide intelligence for the user through sensors and devices found in the local area in a home to connect to an aggregator and then to cloud via a WiFi router, as illustrated in Figure 1.6.

1.6.4 Wearables Wearable devices with sensors collect and analyse users’ data, send messages to other technologies about the person to make users’ lives safer and more comfortable.

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FIGURE 1.6  Smart home connectivity with IoT sensors.

Wearables are also useful for public safety as they provide optimized routes and vital escape signs in emergencies. These wearables are also very useful for tracking the people during the pandemic of COVID-19. Figure 1.7 depicts the contact tracing during COVID-19 and a wearable. These wearables are also used for significant events such as Tomorrowland in Belgium and football stadiums.

1.6.5 Healthcare and Medicine IoT offers access to our imagined future of medicine, offering a fully integrated network of advanced medical instruments. Today, IoT will significantly change medical science, treatment, equipment, and emergency care. The incorporation of all the above components into the hospital allows greater precision, quick responses to incidents, more attention to detail and continuous change, while at the same time reducing the usual overhead of medical research and organizations. IoT helps a critically injured patient to be taken to the emergency department by ambulance. The machine identifies the patient and registers the patient. Paramedical equipment collects vital information delivered to the hospital. The framework analyses data in real-​time and previous documents to provide a leading approach. The status of the patient is changed every second in the system during travel to the emergency. The system advises hospital workers to approve system actions for the delivery of medications and preparing medical supplies. Figure 1.8 demonstrates the implementation of IoT in the healthcare sector.

1.6.6 Smart Cities IoT sensors such as smart streetlights and smart meters are deployed, helping conserve electricity, alleviate traffic, monitor and address environmental concerns, and improve sanitation in a smart city. IoT deployments for government and safety allow

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FIGURE 1.7  Contact tracing using wearables (Source: Sostark).

FIGURE 1.8  IoT in healthcare (Source: Zetakey).

improved law enforcement, city planning, traffic management, water supply control and economic management, as illustrated in Figure 1.9. The technology also helps fill in the current gaps, correct many current flaws, and expand these efforts’ reach. IoT can help city planners have a clearer view of the design’s impact so that government agencies have a better idea of the local economy.

1.6.7 Smart Grid and Smart Meters A grid becomes smart only when there is two-​way connectivity to monitor and analyse the stream of energy from solar panels, wind turbines, and powerhouse to the edge. Usually, there is dust deposition on solar panels, which deteriorates the efficiency

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FIGURE 1.9  Concept of Smart Cities (Source: Starhub).

Power Grid

Head End MDMS System • Manage Asset • Data Analysis • Tariffs Calculation • Time of Use • Billing

Central Control Centre

WhizNano Aggregator connecting to broadband

WhizNano Gateway + WhizMesh as backhaul

Industrial

WhizMesh for long distance backhaul

FIGURE 1.10  Smart grid connectivity (Source: Whizpace).

of panels. There might be partial faults in the panel with p-​n junctions, reducing the efficiency. Once the efficiency is low, the panels must be cleaned to reduce the energy wastage. Similarly, there is two-​way communication with users’ electricity meters to analyse the usage patterns and Power Supply Controllers (PSC). The generated energy is used to power up telecommunications devices, computers, consumer products, and solar power installations. So, monitoring and optimizing performance and efficiency in solar plants are critical use cases in the smart grid. Figure 1.10 illustrates the IoT deployments in smart grid and smart meters.

1.6.8 Agri-​tech IoT-​based smart farming systems can help monitor a few parameters such as light, temperature, humidity and soil moisture of crop fields using connected sensors. IoT devices’ ecosystem enables farmers to know precise and real-​time information about soil nutrition, their crops’ yields, the infestation of pests, rainfall and more for them to take any preventive or corrective actions. Smart farming also gives farmers the ideas

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FIGURE 1.11  A typical deployment of connectivity from plantation to the base station (Source: Whizpace).

FIGURE 1.12  Sensor layer, last mile and back haul connectivity in large plantation, greenhouse and connectivity with Base station (Source: Whizpace).

on modified farming techniques according to prevailing conditions to make the best harvest. Though this technology is a game-​changer, the farmers need to be educated on its implementation. Sugarcane yield has increased up to 300% in Maharashtra (India) after using IoT sensors in the field [7]. IoT is also instrumental in automating irrigation systems and by making farmers’ job more manageable. The IoT sensors can collect data on rainfall, temperature, humidity, fertilizers, soil content, and other factors automating farming techniques. Farmers can save a lot on the cost of fertilizers and water by feeding at an adequate level and have improved yield. Wireless connectivity for backbone layer, last-​mile layer and sensor layer is required for end-​end connectivity from the sensor to cloud. Figure 1.11 illustrates a typical deployment of IoT sensors connectivity from plantation to the base station through an aggregator or gateway. Figure 1.12 illustrates the plantation’s actual deployments, where various IoT sensors are planted with node devices. These devices send the data to an aggregator that is either stationary and deployed on a truck. As soon as a truck reaches any plantation division, it aggregates all the data wirelessly from the nodes and then sends the data to cloud from the truck.

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1.6.9 Tyre Air Pressure Detection This is one of the unique IoT applications, wherein the pressure sensors can detect the air pressure in the tyres of the vehicle and send the information of under-​inflated tyres to the dashboard. These sensors are embedded in the tyres and sense the pressure. Once the driver observes a drop in tyre pressure, he can take corrective actions for the safe driving conditions, where most people can be warned of under or over-​ inflated tyres.

1.6.10 Personal IoT Applications IoT devices are largely used for personal applications, including the following: 1.6.10.1  Gesture Control Armband Another wearable gadget used for gesture control is an armband that detects muscle activity and allows users to control any device connected to the IoT network simply by making gestures or motions. Electrodes in these armbands monitor muscle activation as well as relaxation and contraction when the hands are in motion. These actions are directed to the backend program, which decodes and converts the data into commands and performs the action. 1.6.10.2  Smart Glass The Internet of Things (IoT) technology does not always have to be oriented to anything enormous or global; even something as simple as personal care can have a huge impact on our daily lives. This application demonstrates that the Internet of Things can be useful in personal situations as well. These glasses might serve as a reminder to individuals who do not drink enough water on a daily basis. The glass keeps track of how much water you use and gives you alerts when you don’t have enough. It can also sense the current temperature and keep the water at the optimum temperature. A smartphone can be used to sync this smart glass. 1.6.10.3  Smart Eye The smart eye application is remarkably similar to Google’s ambitious Glass project. This use case is outfitted with sensors and connectivity options ranging from WiFi to Bluetooth, allowing for a variety of options and accessible features to be shown in front of the user without being distracting. Opening maps, reading emails or messages, surfing the internet, capturing moments, and more are all possible. 1.6.10.4  Pulse Oximeter Pulse oximeters are useful gadgets that guides use to assess oxygen levels anytime one rises to a significant height while walking in high altitude mountains. The results indicate whether the hiker is physically capable of ascending or should remain at a lower elevation. With a pulse oximeter attached, the device may notify a doctor through cloud about oxygen administration without having to visit a clinic. This could be useful as a preventative step for a variety of chronic illnesses.

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FIGURE 1.13  Overall ranking: Most IoT projects in Smart City (Source: IoT Analytics).

Figure 1.13 illustrates the use of IoT in every sector in 2018 as per IoT Analytics data, and this shows that smart city projects capture a giant pie [8].

1.7  POTENTIAL OF IOT There is enormous current and future potential for IoT devices. Users mostly use mobile phones to connect with IoT devices, such as smart speakers and thermostats. Associated devices provide ease, help users plan for savings, make a grocery list, turn on or off the households even away from home. The way IoT is proliferating, people’s dependency on the internet is rising. It is no longer about connecting smartphones and computers, but various devices that we use in our everyday lives also need the internet to support people. Ten predictions for the future of IoT: a)  There will be more than 21 billion IoT devices by 2025 According to IoT Analytics, there were 4.7 billion IoT devices in 2016. About 17 billion devices were connected to the internet worldwide in 2018. Out of which the number of IoT devices were 7 billion (excluding the devices such as smartphones and laptops). There was a rise to almost 11.6 billion IoT devices in 2021 and there will be 21 billion devices by 2025. As per Statista Research Department’s forecast, 75.44 billion devices will be connected to IoT worldwide by 2025. IDC (International Data Corporation) predicted that IoT devices would produce 79.4 Zettabytes of data in 2025 [8]. IoT will also grow at a CAGR of 28.7% from 2020 to 2025. The IoT market globally is expected to reach $1.6 billion by 2025. IoT is the big step forward in

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FIGURE 1.14  Growth of IoT devices worldwide (Source: IoT Analytics).

making the world a connected place. In its Ericsson Mobility Report November 2018, Ericsson estimated that the total number of IoT devices would grow to more than 22 billion by 2024, with a CAGR of 17% [9]. Most of the businesses and industries are banking on the exponential growth of IoT, as it not only enables business ideas but also reduces business operational cost. Utilities, logistics, manufacturing, and transport industries alone were expected to spend a sum of around US$40 billion on IoT infrastructure by 2020. Other industries, such as healthcare, insurance, energy and retail storage, process, B2C, and other industries, are also spending a huge amount on IoT infrastructure [10]. Figure 1.14 illustrates IoT devices’ growth worldwide, the technology used to connect them to the gateway. b)  More cities will become “smart” IoTs are used for connecting sensors in smart cities. Cities and companies are increasingly adopting smart technologies to save time and money. This means that the cities will be able to remotely manage, automate, and collect data through visitor kiosks, video camera surveillance systems, bike rental stations, and taxis. Figure 1.15 shows the surveillance cameras with wireless connectivity to Network Center, checking the vehicles crossing the Singapore checkpoint. c)  Artificial intelligence continues to be a big thing IoT transfers an enormous amount of collective data over a network, and many organizations have no idea how to handle this vast data. All household equipment such as Smart home hubs, lighting systems, thermostats, washing machines, refrigerators, and coffee makers gather data on preferences and usage patterns. The voice-​controlled

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FIGURE 1.15  Surveillance cameras checking vehicles (Source: Whizpace).

devices are set up, and the data is recorded on the cloud. All the usage patterns are also stored locally or on the cloud to promote ML further. Machine learning is a form of AI that lets computers learn without a human being needing to program it. Machines are configured in a way that relies on the data they have received, and this data can help the computer learn the expectations and change it accordingly. The organizations will implement this data as it applies to clients and their personal information. Computers are designed to focus on the data they have obtained from the devices and learn from the data they have received to consider the consumers’ needs and learn accordingly. To address this volume of consumer data, IoT lets the data flow between the system and AI that can handle this data without any human error. AI is a crucial catalyst for the success of the IoT revolution. d)  5G networks continues to fuel IoT growth Currently up to 5500 to 6000 NB-​IoT devices can be accommodated by the 4G/​LTE network in a single cell. Most cellular providers are introducing 5G networks. 5G is offering more incredible speed and the potential to connect more mobile devices simultaneously. This faster network will allow more data to be accumulated by smart devices and then it is processed, analysed, and handled in a higher order. This fuels innovation and boosts customer demand for new products. Up to one million users can be managed in a single 5G mobile network. Over ten years, from 2020 to 2030, IoT devices are projected to expand to more than 100 billion, and migration from a 4G to 5G network will continue to close the gap [11]. e)  Cars are getting even smarter The 5G network will shift the automobile industry to a higher gear. Due to extremely low latency on the connected vehicles, the recent development of driverless cars will benefit from data moving seamlessly. New cars will increasingly analyse the data and connect with other IoT devices, including the devices on board.

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f)  5G networks will also open the floodgates on concerns related to security and privacy 5G enabled IoT devices will directly connect to the Telco’s 5G network, instead of connecting via a WiFi router. This direct connection will make those devices more vulnerable to security attack. All IoT devices at home will connect directly, bypassing the home router. So, all the data will be stored on the cloud, which will give hackers new targets to breach. g)  Cybercriminals will use IoT devices to facilitate DDoS attacks The first IoT malware to infect connected devices such as surveillance cameras, DVRs, and more was experienced in 2016. Another malware, Mirai, used default passwords and usernames to enter the computers. Later, the malware converted the affected devices into a botnet to enable Distributed Denial of Service (DDoS) attacks. This attack was targeted at swamp websites with massive internet traffic. This attack flooded one of the most comprehensive website hosting providers, blocking many big, well-​known websites and services for a few hours. h)  Routers will be more secure and smarter Most IoT gadgets, such as smart TVs, surveillance cameras, door locks and others, bring convenience and luxury to life. These devices reside at home and usually do not have security features installed, and they can be vulnerable to attacks and hence are unsafe. Some manufacturers bring their devices to the market soon, so that protection can be an afterthought. Home routers have a pivotal role to play in this case. The router is the gateway of the internet to the house. Since most of the devices are not secured, the router will secure the home entry point. Typical commercial routers provide protections, such as firewalls, password protection, and the ability to customize them to allow restricted devices on the home network. Router manufacturers will continue to search for new ways to improve security in routers. i)  IoT-​based DDoS attacks will be more dangerous Compromised IoT devices were used by Botnet-​powered distributed denial of service (DDoS) attacks to swamp websites. In future, there could be a chance of attempts to harm IoT devices. A potential example might be shutting down the power grid or thermostats in an enemy state during a harsh winter. j)  Security and privacy concerns drive for legislation and regulations The growth in IoT devices is one of the reasons for raising security and privacy issues. The European Union adopted the General Data Protection Regulation (GDPR) in mid-​2018. GDPR has led projects around privacy and protection in many countries around the world. California has recently enacted a more stringent privacy rule. Such initiatives could allow consumers more power over their data.

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1.8  ARCHITECTURE OF IOT The IoT architecture consists of various levels of technologies supporting IoT. It illustrates how different technologies connect and how they express the modularity, scalability, and configuration of IoT implementations in various scenarios. Figure 1.16 illustrates the different layers of the architecture of IoT. The functionality of all technology layers is discussed below:

1.8.1 Smart Device/​Sensor Layer The lowest IoT layer comprises sensors and smart devices. The sensors are connected to the physical and digital environment and transfer real-​time information to be processed. There are various types and they are used for a plethora of applications. These sensors can read parameters such as temperature, humidity, speed, air quality, flow, movement, pressure, current, etc. Some sensors may also come with memory, enabling some measurements to be recorded or signal strength indication to be received (RSSI). Sensors measure the physical properties of the environment and the devices they are connected with and convert them into a digital signal. Sensors are grouped according to their purposes such as body sensors, vehicle telematics sensors, environmental sensors, home appliance sensors etc. Sensors using low data rate and low power usually form the network, termed as wireless sensor networks (WSNs). These WSNs are wide-​spreading as they support

Application Layer

SMART LIVING

SMART CITIES

SMART ENERGY

SMART TRANSPORT

Fleet Mgmt

Asset Mgmt

Supply Chain

People Tracking

-Device Modelling -Device & cfgn Mgmt -Performance Mgmt -Security Mgmt

SMART HOME

Environmental

Statistical Analytics

Data Mining

In -Motion Analytics

Test Mining

In -Memory Analytics

Predictive Analytics

BPM

-Workflow -Process Modelling -Process Simulation -Process Execution

Security

-Data Governance -Data Anonymity -Data Repository -Data Quality Mqmt

-Billing -Reporting

SMART BUILDING

Surveillance

Data

BSS

BRM

-Access Controls -Encryption -Identity Access Mgmt

-Rule Definition -Rule Modelling -Rule Simulation -Rule Execution

Transport Capability

Networking Capability

Network/ Communication Layer

SMART INDUSTRY

Analytics Platform

OSS Management Service

SMART HEALTH

Embedded & Signal Processor

Gateway

OS

NB -IoT

5G

TVWS

Microcontroller

Ethernet

GSM/GPRS

WiFi

Gateway Network

SIM Module

LTE Bluetooth

Sensor Networks

Smart Device/ Sensor Layer

S e n s o r s

ZIGBEE

WiFi LTE Analog GPS

5G

LoRa Digital

Solid State

ETHERNET

Bluetooth

SigFox

TVWS

UWB

Electro -Mech

RFID Infra -Red

Wired

GSM/GPR S

Gyroscope

Devices

FIGURE 1.16  IOT Architecture (Source: http://​ijesc.org/​ & IDA).

Photo -Electric Electro -Chemical

W S N

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many sensor nodes while spanning broad areas and maintaining sufficient battery life. Many sensors need node access to the gateways. This gateway has a Local Area Network (LAN) such as an Ethernet and WiFi link or a Personal Area Network (PAN) such as Bluetooth, ZigBee, TVWS and Ultra-​Wideband (UWB).

1.8.2 IoT –​Technology and Protocols IoT uses standard protocols and networking techniques to establish a network. However, the leading technologies and protocols used by IoT are NFC (Near Field Communication), RFID (RF Identification), low-​energy wireless, low-​energy radio protocols, low-​energy Bluetooth, LTE, NB-​IoT, LoRa, SigFox, TVWS, and WiFi-​ Direct. All these solutions support an IoT system’s special networking features instead of a standard uniform network of typical systems [12].

1.8.3 RFID and NFC • RFID and NFC offer simple, low-​energy, and access tokens and payment options. • RFID uses a two-​way transceiver to recognize and monitor the tags. • NFC uses communication protocols to connect electronic devices such as handheld devices or standard devices.

1.8.4 Low-​Energy Bluetooth (BLE) • BLE enables low-​power, long-​term use of IoT features, using standard technology that is supported across networks.

1.8.5 Low-​Energy Wireless • This technology is also used for IoT network to make it less power-​hungry when sensors and communication nodes go to sleep or deep sleep mode and wake up only during data transmission. • This system is used for low power consumption and extends the device life.

1.8.6 Radio Protocols • Z-​Wave, ZigBee, and Thread are some of the radio protocols which are used to form low data-​rate private area network. • Unlike many similar technologies, these technologies are lower power consumption and provide better throughput.

1.8.7 LTE-​Advanced • LTE-​A (or LTE Advanced) delivers the upgraded LTE technology by increasing the coverage and throughput while reducing the latency. • LTE-​A makes IoT an effective system by expanding the range. The longer-​ range introduces significant applications such as vehicle, UAV, and drones.

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1.8.8 NB-​IoT • NB-​IoT mainly covers indoor with high connection density, longer battery life, and low cost. • It uses the fraction of the LTE band, but bandwidth is limited to 200 kHz. • It uses SC-​FDMA for uplink and OFDM modulation for downlink [13].

1.8.9 LoRa • LoRa (Long Range) is an LPWAN protocol developed by Semtech and its alliances. • This technology is based on chirp spread spectrum (CSS) modulation technology. • LoRa uses license-​free ISM bands such as 433 MHz in many countries, 868 MHz in Europe, Middle East and Africa, 920 MHz in North America and Australia, 865 MHz in India and 925 MHz in some part of Asia. • It covers long-​range (more than 10 km) with low power consumption. • LoRa covers the physical layer, while LoRaWAN (Long Range Wide Area Network) occupies the upper layer. The data rate can be achieved from 300 bps to 27 kbps, depending on the spread factor [14].

1.8.10 SigFox • SigFox continuously transmits a small amount of data, such as smartwatches and electricity meters. • It uses DBPSK and Gaussian frequency-​shift keying (GFSK), enabling communication in the ISM radio band using 868 MHz in Europe and 902 MHz in the US. • Uses a wide-​ reaching signal that passes from solid objects called “Ultra Narrowband,” which needs little LPWAN energy. • The network operated by the mobile operator to carry the traffic generated based on a single-​hop star topology [15].

1.8.11 TV White Space • TV White Space (TVWS) technology uses the frequency spectrum in the range of VHF & UHF bands under-​utilized by broadcasters. • The coverage is extended due to usage of the sub-​GHz band. The capacity is high as the available spectrum is more than 200 MHz. • Narrowband TVWS devices are used for data communication. • This is a license exempted band, so with very low deployment and recurring cost.

1.8.12 WiFi-​Direct • WiFi-​ Direct allows peer-​ to-​ peer connections with lower latency, and it eliminates the requirement of an access point.

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Internet of Things (IoT)

• It does not have a single point of failure, and it does not compromise on speed and throughput of the network. Some sensors connect to backend servers/​applications without a need for an aggregator. This connectivity can be supported via WAN, such as GSM, GPRS, ZigBee, LTE, LoRa, SigFox, NB-​IoT and TVWS. As plotted in Figure 1.17, all the above technologies have pros and cons. Discussing the characteristics of technologies, WiFi and ZigBee have a high capacity, but the coverage is very limited. LoRa, SigFox and NB-​IoT have more extended coverage, but the capacity is meagre. LTE, 3G and NB-​ IoT have adequate coverage, but the capacity is limited, and since these services are Telco’s dependent, so there is a monthly subscription. TVWS happens to have the advantage in terms of capacity and coverage with no subscription, making the recurring charges minimal.

Capacity

High

Low

Low

Coverage

High

FIGURE 1.17  Wireless technologies used for IoT (Source: Whizpace).

1.8.13 Gateways and Networks The large amount of data generated by these sensors requires secure and high-​ performance wireless or wired connectivity for the transport of info. Networks are also connected to different protocols used to support M2M networks. To facilitate broader deployment of IoT systems and applications such as context-​aware applications, high-​speed transactional services, etc., multiple networks with various technologies and connection protocols are expected to work with each other in mixed and heterogeneous configurations. These networks can be public, private or hybrid models and are designed to support connectivity requirements. Various gateways with microcontrollers or microprocessors and gateway networks (WiFi, GPRS, GSM, etc.) are illustrated in Figure 1.16.

1.8.14 Management Service Layer The management service delivers the data that can be accessed by analytics, access controls, process modelling and system management. One of the critical aspects of this layer is to communicate and interact with objects and devices to provide information such as incidents or weather, traffic data and current location. Some of these aspects include the filtering, routing, and normalization of periodic data. Any of the material includes responding to urgent emergencies, such as attending to the health

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conditions of the patient. The rule engines help to formulate the real-​time decision logics. The rule engines present a very responsive IoT system by prompt interactive and automated processes. Data analytics tools extract relevant information from the enormous amount of raw data and are processed without a time lag. In-​memory analytics reduces the time required for data query, making decision making faster, and allows this enormous amount of data to be cached in RAM without storing it in physical disks. Streaming analytics helps in the analysis of data, which is data-​in-​ motion and is required to be carried out in real-​time so that the decisions can be made without any latency. Data management controls the flow of information. It helps in accessing, integrating, and controlling information. Higher layer systems should be protected from the need to process unnecessary data and reduce the possibility of privacy. Data filtering methods, such as data synchronization, data integration and data anonymization, are used to mask knowledge specifics by presenting just the information required for the specific applications. Data abstraction helps extract and offer a common enterprise interpretation of data to improve agility and reuse across domains. Security is another tool in the management layer to be enforced in all dimensions, from the device layer to the application layer. Device security prevents the system from breaching and compromising unauthorized employees in order to reduce the risk factor.

1.8.15 Application Layer The application layer is the interface between the user and the device [16]. This layer covers smart environments such as in Agriculture, City, Building, Transportation, Lifestyle, Retail, Grid, Factory, Warehouse, Emergency, Healthcare, User Interaction, Supply Chain, Culture and Tourism, Environment and Energy. Figure 1.18 shows a typical end to end IoT network using narrowband TVWS solution with four key stages: i) Nodes send the sensor parameters in the form of MAC ID and data format to the gateway. The gateway forwards the received data pair from the nodes to any of the cloud services (Azure in this example) ii) IoT Central receives the data pair from the gateway. In some cases, this data pair is sent to a server or a PC for on-​premises solution for the more secure network. iii) User views data through IoT Central in-​built user interface (for Azure) or on-​ premises user interface.

1.8.16 IoT Software IoT software is critical for networking and connectivity to partner systems, platforms, middleware, and embedded systems. These applications are used for device integration, data collection, real-​time analytics, application, and process extension within the IoT framework. They exploit integration with critical business systems in the execution of related tasks with the below processes:

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23

FIGURE 1.18  Schematics of a typical IoT network (Source: Whizpace).

1.8.17 Data Collection Data collection manages sensing, measurements, light data filtering, light data security, and its aggregation. It utilizes various protocols to connect sensors in real-​ time M2M networks. Also, data is collected from multiple devices and distributed in the following settings. It also works in reverse order by distributing data to the devices. The system finally transmits all collected data to a central server.

1.8.18 Device Integration Software supporting integration binds all system devices to create the IoT network, ensuring the necessary cooperation and enabling stable networking. These applications compile the software technology of the IoT network to complete. This integration manages the various protocols, applications, and limitations of each device to allow communication in the range.

1.8.19 Real-​Time Analytics This application takes data or input from various devices, converts it into viable actions, and makes sensible human analysis patterns. They analyse information based on various settings and designs to perform automation-​related tasks or provide industry data. This analysis can be performed on the cloud or on-​premises. The most common and popular real-​time analytics are Microsoft’s Azure, Google Cloud Protocol (GCP) and Amazon Web Services (AWS).

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1.8.20 Applications and Process Extension These applications extend the reach of software to allow a broader and more effective system. They integrate predefined devices with specific purposes and allow certain mobile devices access. They also support improved productivity and more accurate data collection.

1.9  IOT STANDARDS AND FRAMEWORKS Below are some of the emerging IoT standards [17]: • IPv6 over 6LoWPAN is an IETF defined standard. This standard enables low-​ power radios to connect to the cloud, including BLE, 804.15.4, and Z-​Wave for home automation. • ZigBee is based on IEEE 802.15.4 standards and is the low-​data rate, low-​power wireless technology primarily used in the industrial environment. The ZigBee Alliance has developed Dotdot, a universal language for IoT. This allows smart objects to function safely on every network. • LiteOS is a Unix-​like WSN operating system. LiteOS is supported on wearables, phones, smart homes, smart manufacturing applications, and the Internet of Vehicles (IoV). LiteOS has also been used as a platform for the advancement of smart devices. • OneM2M is M2M service layer embedded in software and hardware to connect the devices. OneM2M was developed as a reusable standard to facilitate IoT applications across different verticals to communicate with devices. • Advanced Message Queuing Protocol (AMQP) is an opensource standard for asynchronous messaging, facilitating encrypted and interoperable communications between organizations and applications. The protocol is used for server-​client communications and IoT system control. • Constrained Application Protocol (CoAP) is a network protocol which used constraint-​bandwidth and constraint-​network and applications with minimal access in M2M communication. CoAP is also a transmission protocol for documents that operates via the User Datagram Protocol (UDP) [16]. • Data Distribution Service (DDS) is a versatile peer-​to-​peer networking protocol that runs from small devices to high-​performance network connections. It increases reliability, eliminates complexity, and streamlines deployment. DDS has been developed by the Object Management Group (OMG) and is an IoT standard for real-​time, scalable, and high-​performance M2M communication. • HTTP is based on the request-​response paradigm and thus does not satisfy the needs of IoT applications. MQTT (Message Queuing Telemetry Transport) is a lightweight application-​layer messaging protocol based on a Publishing/​ Subscribing (Pub/​Sub) model. In the pub/​sub model, multiple sensor clients will connect to a central server termed as a broker and subscribe to topics of interest to them. Clients, with the specific topic of their interest, can also publish messages via the broker. The broker is an app for linking and sharing data with sensor devices. MQTT utilizes a TCP link on the transport layer to connect the sensors to the broker, making the communication robust.

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25

• MQTT messages are only released on topics that represent the destination address. The client can subscribe as well as publish multiple themes. Any client who has subscribed to the topic gets all the messages released on the topic. As a common procedure, subjects can adopt a hierarchy using a slash (/​) as a separator. This facilitates conceptual grouping/​arrangement for a network of sensors. For example, the theme “room/​sensor/​indoor” simply conveys the hierarchy of human information through a thermal sensor in the room. The IoT sensor network in a modern room can have multiple sensors, each with multiple sensed data. Themes then obey this hierarchical array. Topics thus adopt this hierarchical structure for quick interpretation and logical arrangement of sensor variables [18]. • LoRaWAN is designed to serve big networks, such as smart cities and plantations, with numerous devices. • The IoT structures shall contain the following: • Amazon launched an IoT cloud hosting platform called Amazon Web Services (AWS). This architecture is designed so those smart devices are conveniently connected and safely interacted with the AWS cloud. • Arm Mbed IoT is another IoT application development focused on ARM processors. This platform’s objective is to offer a connected, scalable and secured environment for the integration of Mbed tools and resources with IoT devices. • Google’s cloud platform is designed for the fast deployment of IoT applications with the following two key pillars: • Brillo is an Android-​based operating system for low-​power embedded devices, and • Weave serves as a communication language between IoT devices and the cloud. • Ericsson released an open-​source IoT framework, Calvin, designed to create and manage numerous applications that allow devices to talk to each other. Other features of Calvin are the development framework for web designers with a runtime environment for operating applications. • Microsoft’s Azure IoT Suite offers a portal consisting of a series of services that enable users to communicate with and receive data from IoT devices on the network. This platform performs various operations on the data collected, such as multidimensional analysis, aggregation and transformation, and visualization of appropriate parameters for business purposes.

1.10  ENABLING TECHNOLOGIES FOR IOT Through the IoT, connectivity is spread across the internet to all the objects that surround us. The IoT is much more than a machine-​to-​machine (M2M) connectivity and consists of sensor networks, WSN, 2G/​3G/​4G, GPRS, GSM, RFID, WiFi, GPS and microcontrollers. All these supporting technologies make IoT implementations feasible. Of the 22 billion IoT cellular connections predicted for 2024, more than 4 billion are anticipated. According to ABI Research, embedded SIM (eSIM) will be one of the biggest cellular IoT enablers, with 420 million new connections annually by 2022. “This is the moment industry providers (such as the eSIM provider, mobile

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network operator and device manufacturer) have been waiting for. With both Apple and Google deploying smart devices, adoption of eSIM technology is only going to speed up,” said Tania Ferreira, KNect365’s e-​SIM Connect senior official. Other participants, such as Microsoft, Samsung, and Huawei, are a few to offer eSIM connectivity [10]. IoT enabling can be grouped into three categories [19]: a) “Things” acquiring contextual information enabling technologies b) “Things” processing contextual information enabling technologies, and c) Technologies are improving privacy and security. The categories first and second are used as functional building blocks required to build “intelligence” into “things”, which differentiate the IoT from the typical internet. The third category is a mandatory requirement, without which the penetration of the IoT would be severely compromised. The IoT consists of a combination of different hardware & software technologies. The IoT network provides solutions based on integrating operational technology (OT) and information technology (IT), which includes software and hardware for storing, retrieving, and processing data. IoT also consists of communications technology with electronic systems used for communication between groups and individuals. The IoT network consists of a diverse combination of connectivity technologies which need to be tailored to satisfy different applications, such as speed, energy consumption, reliability, and protection. A variety of manageable networking solutions that meet the IoT applications implemented on the market will be scaled to the extent of diversity. These applications have also been seen to be serviceable and enabled by robust infrastructure partnerships. Many of the hardware examples of standards in these categories include wired and wireless systems such as Ethernet, WiFi, Bluetooth, GPRS, ZigBee, GSM, NBIOT, LTE-​m, TVWS, LoRa, SigFox, and 5G. The key enabling technologies for the IoT is illustrated in Figure 1.19.

System Integration Cost Effective

Interoperability Identification Nanoelectronics Hardware

Software

Sensor Network

Embedded System

Security & Privacy Data & Signal Processing Data Management Network Management

Discovery Service

Communication Cloud Computing Network Tech

Power & Energy Storage

Semiconductor Electronics

FIGURE 1.19  IoT enabling technologies.

Future Internet

Protocol/Standards

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1.11  FUTURE TECHNOLOGICAL DEVELOPMENTS FOR IOT The enhancement of the above discussed enabling technologies allows upcoming technological advancement environment where everything will be connected all the time everywhere. The technologies have been categorized into three groups, as per IoT layers. I. The first group, impacting the devices and microcontroller chips: a. Low power sensors for energy sustainability and power b. The intelligence of sensors deployed in the field c. Wireless sensors network (WSN) for sensor connectivity d. Miniaturisation of chips II. The second group, comprising the network sharing, address capacity, and latency concerns: a. Network sharing includes software-​defined radios (SDR) and cognitive networks b. Network technologies are addressing capacity and latency concerns such as TVWS, LTE or 5G. III. The third group, impacting the management services: a. Real-​ time decision-​ making technologies such as context-​ aware computing, predictive or preventive analytics, complex event processing, and behavioural analytics b. Speed of data processing technologies such as in-​memory and streaming analytics. Table 1.1 shows future development & future research needs for enabling technologies of IoT.

TABLE 1.1 Future Developments and Research Needed Technologies Hardware Devices

Future Development

• Nanotechnology • Miniaturisation of chipsets • Ultra-​low power circuits Sensor • Smart Bio-​Chemical sensors • More tiny sensors • Low power sensors • Wireless sensor network for sensor connectivity Communication • On-​chip antennas for different Technology technologies & frequency bands • Broad-​spectrum and spectrum aware Protocols

Research Needed Low-​cost modular devices Ultra-​low power EPROM Autonomous circuits Self-​powering sensors Intelligence of sensors

Protocols for mteroperability Multi-​protocol chips Gateway convergence On-​chip networks (continued)

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TABLE 1.1  (Continued) Future Developments and Research Needed Technologies

Network Technology

Calibration

Software & Algorithms

Data & Signal Processing Technology

Discovery and Search Engine Technology Security & Privacy Technologies

Future Development

Research Needed

• Unified protocol over a broad spectrum • Multi-​functional, reconfigurable chips • Self-​aware and self-​organising networks • Self-​learning, self-​repairing networks • IPv6-​enabled sealability • Ubiquitous IPv6-​based IoT deployment • The sensors get out of calibration with time • The sensor data varies and gives wrong parameters • Goal-​oriented software • Distributed intelligence. problem-​solving • User-​oriented software

Longer range (sub-​GHz band) 5G developments

• Context-​aware data processing and data responses • Cognitive processing and optimisation • IoT complex data analysis • IoT intelligent data visualisation • Energy, frequency spectrum aware data processing • Automatic route tagging and identification management centres • On-​demand service discovery and integration • User-​centric context-​aware privacy and privacy policies • Privacy-​aware data processing • Privacy and security profiles selection based on security and privacy need

Grid/​Cloud network Software-​defined networks Service-​based network Need-​based network

Find a way to auto-​calibrate the sensors to have correct parameters Context-​aware software Evolving software Self-​reusable software Autonomous things: Self-​configurable Self-​healing Self-​management Common sensor ontology Distributed, energy-​efficient Data processing Autonomous computing

Scalable Discovery services for Connecting things with services

Low cost, secure and high-​ performance identification/​ Authentication devices Decentralised approaches to privacy by information localisation

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1.12  FUTURE APPLICATION AREAS The IoT has diverse and numerous potential applications, pervading essentially all areas of everyday life for: 1. The individuals, 2. The enterprises, 3. The community of citizens. The IoT application encompasses “smart” ecosystems such as Lifestyle, Transportation, Buildings, Communities, Cities, Supply Chains, Retails, Warehousesies Agriculture, Emergency, Healthcare, Culture and Tourism, User interactions, Climate and Electricity. Following are a few of the IoT applications for the future [20]. a) IoSL (Internet of smart living): • Smart Home Appliances: The LCD on the refrigerators can display the food availability inside, food about to expire, ingredients to be bought and all the available information on a smartphone. Washing machines can be monitored for the laundry status remotely, and kitchen appliances with an interface to a mobile phone allowing remote control of the oven’s self-​ cleaning feature, • Remote Control Appliances: The appliances can be switched on/​ off remotely to save energy and avert accidents, • Weather: The outdoor weather environments such as temperature, pressure, humidity, wind speed, and rain levels can be displayed over long distances, • Intrusion Detection Systems: The doors and windows openings are detected, and the system can detect intruders’ infringement, • Safety Monitoring: Home alarm systems and cameras make users feel safe, monitoring toddlers, kids, or parents at home, • Water and Energy Use: Real-​time monitoring of water and energy consumption to obtain advice on saving cost and natural resources. b) IoSC (Internet of smart cities): • Structural Health: Material conditions and vibrations in bridges, buildings, and historical monuments can be monitored and preventive actions can be taken, • Lift monitoring: Monitoring the status of lifts and take preventive actions to avoid accidents, • Lightning: Intelligent and weather adaptive lighting in streetlights, • Smart lamps: Make lamps as smart lamps, which are used not only as streetlights, but also as WiFi hot-​spots, announcement poles and digital hoardings, • Safety: Digital video monitoring, public announcement systems, fire control management,

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FIGURE 1.20  Use cases in Smart City (Source: IoT Analytics).

• Transportation: Deployment of warning messages and diversions according to climate conditions and unexpected events such as traffic jams and accidents on smart Roads and Intelligent Highways, • Smart Parking: Real-​time checking of availability of parking lots in the vicinity so that riders can identify and reach the closest available lots, • Waste Management: Detection of rubbish levels in the smart bins to optimize the routes of trash collection. RF tags or sensors are mounted on the garbage cans and recycle bins, allowing the sanitation staff to see when the bins are full and need to be cleared. Figure 1.20 illustrates various IoT applications in smart cities application with most of the projects used in traffic management. c) IoSE (Internet of smart environment): • Weather monitoring: Monitors the weather conditions such as temperature, humidity, pressure, wind speed, rain, and even early detection of earthquakes, • Air Pollution Monitoring: Control of polluting gases and sewage from industrial units, pollution emission from vehicles and toxic gases emitted in the farms, • Water Quality: Study and purification of water in rivers, lakes, reservoirs, underground water or sea if it is suitable for drinking, • River Floods: Monitor the water level variation in drains, dams, rivers, and reservoirs during rainy days to monitor and control flood, • Forest Fire Detection: Monitors the combustion of gases and pre-​emptive fire conditions to identify possible fire alert zones and avert the possibility of fire,

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FIGURE 1.21  Use of IoT in Industry 5.0 (Source: International Business Center for Suitable Development).

• Protecting wildlife: Wildlife animals are tagged with tracking devices through GPS/​GSM to locate and track and communicate their coordinates in real-​time. d) ISI (Internet of smart industry): • Explosive and Hazardous Gases in industries: Detection of level and leakage of gas, monitoring of oxygen levels and toxic gas inside chemical plants to ensure human and goods safety, surroundings of chemical factories and inside mines, monitoring of water, oil and gas levels in storage tanks and the possibility of corrosion, • Maintenance and repair: The sensors are installed on the machines. These sensors detect the faults and help to predict, and schedule service maintenance and equipment malfunctions before actual failure. These sensors also help the equipment to monitor, send reports and prevent faults, • Industry 5.0: The fifth industrial revolution (Industry 5.0) focuses on cooperation between machine and man, as human intelligence works in coordination with cognitive computing (Figure 1.21). Human intelligence shall be used to teach collaborative robots to upskill workers to provide value-​added production tasks. This will lead to mass customization and personalization for customers [21]. e) IoT (Internet of smart health): • Patients Surveillance: Monitors the conditions of patients in older people’s home and hospitals, • Medical Fridges: Monitors and controls the conditions inside fridges storing medicines, vaccines, and organic elements -​very low-​temperature refrigerators are needed for storing the COVID-19 vaccines. • Fall Detection: Detects and assists elderly or disabled people who are living independently, • Dental: Toothbrushes with Bluetooth connects with a smartphone to analyse the brush usage and gives information about the brushing habits on the mobile phone for personal information or for sharing the statistics to the dentist,

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• Physical Activity Monitoring: The sensors are mounted all along with the mattress. These sensors sense body smaller motions such as heart rate and breathing and larger motions caused by turning during sleep. These sensors provide data for sound or deep sleep through an app on the smartphone. f) USA (Internet of smart agriculture): • Green Houses: Control micro-​climate conditions and quality of fruits and vegetables to maximize the production, send the fertilizer’s ingredients in water in aquaculture to head office, • Compost: Controls the temperature and humidity levels in alfalfa, straw, hay, etc. to prevent mould and other microbial impurities in the compost, • Animal Farming/​Tracking: Identification and location of animals grazing in the open meadows or location of animals in big stables. The installed sensors are also used for the study of air quality and ventilation in farms and detection of toxic gases, • Offspring Care: Control of the conducive conditions of offspring in animal farms to ensure their health and survival, • Field Monitoring: Reduction of the crop wastage and spoilage with proper monitoring, management of the agriculture fields, and accurate ongoing data obtaining. This also helps in better control of electricity, water, and fertilizers.

1.13  PROS AND CONS OF IOT Some of the pros of IoT are listed below: • • • •

improved connectivity between electronic devices. access the information from any device, anywhere, and at any time. transfer of data over a connected network which saves money and time; and automated tasks help to improve the quality of service of an enterprise with reduced need for human intervention.

Some of the cons of IoT are listed below: • With the exponential increase in connected devices, more information is shared between devices, and hence the potential of hacking the confidential information also increases. • Enterprises will eventually have to deal with massive numbers of IoT devices of the order of multi-​millions. To collect and manage the massive amount of data from all those devices will be a challenge. • A small bug in the system will corrupt all connected devices. • Since there is no single international standard of compatibility for IoT, it is challenging to manage the network for devices from different sources to communicate.

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Internet of Things (IoT)

33

1.14  IOT SECURITY AND PRIVACY ISSUES The IoT connects billions of devices and involves the massive data points to the internet. All this data needs to be secured. Due to significant exposure, IoT security privacy is a major concern. In 2016, one of the most infectious IoT attacks, Mirai, a botnet that intruded the domain name server provider Dyn. This attack turned down many websites for a long duration in one of the most significant DDoS attacks ever experienced. Hackers got access to the network by exploiting weakly secured IoT devices. The threat posed by IoT botnets, such as Mirai to unsecured IoT devices remains very high. Mirai, BASHLITE, Amnesia, Persirai, Hajime, and similar botnets attacked IP camera and DVR systems via SSH or telnet and used a short list of commonly used login credentials, such as root, admin and support and commonly used passwords such as admin, 1234 or abcd. There were login attempts from different IP addresses over 45 hours. Someone or something would log into it every two minutes using the hacked credentials. After performing a Shodan search, it is revealed that the attacks were mainly coming from Synology, TP-​Link, D-​Link, and AvTech. The distribution of attacks matched the earlier attacks with Mirai, but the researchers noted that different variants hit the device. BrickerBot malware attempted to break the vulnerable devices because most stuck devices cannot be malfunctioned by overwriting the disk. However, it becomes unresponsive until a reboot. Sometimes, these devices are very buggy, and the user keeps on rebooting the device, and the system works after the reboot, and that is how the maintenance is performed by rebooting [23]. If a hacker exploits one device in a connected system, there is a susceptibility to manipulate all the devices, and hence data delivery is unfeasible. Manufacturers ought to update their devices regularly to safeguard vulnerability to cybercriminals. Hackers also access users’ personal information, including names, phone numbers, addresses, ages, social media accounts, and even company details and confidential information through connected devices [17, 23].

1.15  TIPS TO HELP SECURE USER’S SMART HOME AND IOT DEVICES [24] a) Give the router a name: Avoid sticking with the manufacturer default name as it might identify the make or model. Giving it an unusual name not associated with an individual name is beneficial. The router should not be a personal identifier. b) Use strong encryption for WiFi: It is good to login with a robust encryption technique, such as WPA2, WPA3, or SAE while setting up a WiFi router. This will help keep communications and network security. c) Set up a guest network: Keep the WiFi account private. Set up a guest network for visitors to log into a separate network that does not tie into IoT devices. Keep IT and IoT login separate. d) Change default usernames and passwords: Cyber-​ criminals are aware of the default logins and passwords of many IoT products. These default

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e)

f) g) h)

i) j) k) l)

passwords make it easy for them to access the IoT devices and, potentially, the information on them. It is always advisable to use their own password, which is easy to remember yet difficult to hack. Password Strength of WiFi: The user is advised to use stronger and unique passwords and avoid common words or easy to guess passwords, such as “password”, “abcdef” or “123456” for WiFi networks. Instead, the user should use unique and complex passwords made up of capital and small letters, numbers, and symbols. One might consider using a password manager to tighten their security plan. Settings of the devices: The default settings of IoT devices usually are weaker privacy and security. It is advisable to change those default settings as these are beneficial for the manufacturers, not the users. Disable undesirable features: The IoT devices have a number of default features and services such as remote access activated. If the user does not need them, it is advisable to disable them. Keep the software up to date: Keep updating the latest software updates as they might have patches for the bugs or security flaws. Security of mobile is also vital as mobile devices access some networks. Keep updating IoT devices also for the latest software from their respective websites. Assessment of the IoT devices: User should check for the newer models of the camera with the latest security features. Do the two-​ factor authentication: Opting for two-​ factor authentication (2FA) is a smart idea. Get the one-​time password (OTP) on the mobile phone for the secured network. Avoid public WiFi networks: Using public WiFi is not a good idea. In case there is no other option but to use public WiFi, use VPN. One can manage IoT devices through a mobile device, rather than using public WiFi. Watch for the outages: Make sure that the outage in hardware does not result in an insecure state. More IoT devices shall be placed in home and offices. These devices make life more convenient but remember to secure the smart home, offices, and IoT devices.

1.16  FUTURE CHALLENGES FOR IOT Some implications and key challenges to be addressed for mass deployment of IoT in future.

1.16.1 Privacy and Security As the IoT becomes a vital component of the internet in the future and IoT’s wide operations need to address privacy and security features adequately. If not adequately addressed, every new gadget brought into the home or office presents a potential threat to the network. For instance, according to recent research, on average, the IoT device is attacked every 120 seconds [25, 26]. New identified challenges for reliability, privacy, and safety are:

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Internet of Things (IoT)

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TABLE 1.2 The Security Requirement at Different IoT Layers IoT Layer

Security Requirements

Application

• Application-​specific data minimisation • Privacy protection and policy management • Authentication • Authorisation, Assurance • Application specific encryption, cryptography. Service Support • Protected data management and handling • Search, Aggregation, Correlation, Computation) • Cryptographic data storage • Secured computation, In-​network data processing, data aggregation • Cloud computing Network Layer • Secured sensors/​cloud interaction • Cross-​domain data security handling • Security of communication and connectivity Smart object/​sensor • Access control to nodes • Lightweight encryption • Data format and structures • Trust anchors and attestation Source: http://​ijesc.org/​

• To provide quality and security of the data in information sharing models to facilitate reuse across various applications • To provide protection mechanisms for vulnerable devices • Providing secured transfer of data between IoT devices and users Table 1.2 depicts various privacy and security requirements at different IoT layers.

1.16.2 Cost versus Usability IoT connects physical objects to the internet using technology. The cost of components needed to support capabilities such as tracking, sensing, and control mechanisms needs to be cheaper in the coming years and with increasing volumes for IoT adoption to grow.

1.16.3 Interoperability Traditional internet interoperability is the most essential key value. The fundamental criterion for internet connectivity is that all connected devices and systems must communicate in the same protocol and encoding language. Currently, different sectors employ various standards to support their IoT applications. The adoption of common interfaces between these disparate organizations becomes crucial when dealing with a

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variety of data sources and heterogeneous devices. These interfaces are critical, especially for applications that span organizational and system boundaries. As a result, IoT systems must be able to handle a high level of interoperability.

1.16.4 Data Management Data management is another crucial aspect of the IoT. Considering a world of interconnected devices and continually exchanging various types of information, the volume of the generated data and the processes involved in handling those data become very critical. So, research is needed to produce energy-​efficient communication ICs.

1.16.5 Impact of COVID-19 Pandemic on IoT COVID-19 pandemic continues to threaten the world and has an unprecedented impact on the economy and our society. As many states, countries, and regions installed and lifted lockdowns and reopen businesses, the way forward requires using technologies in different ways. There is a high likelihood of acceptance of various technologies in the coming years because workforce is becoming more digitally oriented as they accept technology while working from home. Industrial analytics and IoT devices have abundant potential for helping companies explore this new normal [27]. The following are some of the compelling examples: i. Organizations to use cameras in new ways • More installed cameras helped to reduce thefts on premises • Some transport companies started using AI to detect riders and passengers without a facemask • IoT sensors are installed to control the entry and exit of people in the shopping malls, office area or a stadium ii. Help enterprises use analytics to explore actions • Analytics makes the system run with reduced workforce and technicians keeping tabs on essential characteristics such as vibration and flow rate while maintaining social distancing • Studying the data from a specialized industrial platform makes it easier for organizations to determine when to send on-​site crews to resolve immediate issues • For the meatpacking industry, data assists companies with screening visitors and workers, with the sanitation needs and abiding by other essential practices to operate safely iii. Give Companies More Ways to Meet Needs • Supermarkets are coming with innovative ways such as a “virtual queue” system to manage social distancing while in the queue. People register for places in a virtual queue and can wait in their cars until their turn. • IoT thermal imaging cameras can take the temperatures of groups from a distance to speed up temperature checks in practical ways without compromising safety

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• Industrial analytics platforms give enterprises real-​time insights about the products or services their customers demand most and anticipate and prevent shortages or other order fulfilment delays iv. Businesses to explore connected tools • The wearables send an alert to management and in contact staff, if two or more staff violate social distancing and come closer to each other • The wearables help in contact tracing, along with other efforts to keep people healthy. Some gadgets indicate users to wash their hands when entering or leaving key areas, such as the restroom or cafeteria • The data can be used for preparing timesheet of workers and their productivity v. Smart Analytics Can Keep People Safer • All the above points show that there is much potential for the technology to guide decisions and maintain safety. Companies should investigate the appropriate ways to implement technology for the benefit of everyone involved vi. Elderly care, tracking & remote monitoring • The thermal sensors can be mounted on the door, and it can detect how many older people are at home at any time or for how long they were out of the home • This solution can also send the alarm to the local municipality if any person under quarantine or stay home notice tries to go out or someone comes to meet the person vii. Processes are more automated. • Businesses have been automating their processes more. The automation was considered a jobs snatcher as technologies such as autonomous vehicles and robots were threatening to replace humans. But now this is becoming a new norm to use automation with a reduced workforce viii. Access to remote asset becomes essential [27] • Video Conference tools such as Zoom are becoming very popular because they connect people remotely. Zoom’s daily participation has increased from 10 million to 300 million in 3 months at the start of the pandemic [28]. Similarly, Librestream tool, connecting people with their assets and machines, has recently reported a surge in their remote expert software usage. • Many establishments were affected by production, shipping, distribution channels, and demand variation due to the pandemic. So, digital twins create digital representations of the end-​to-​end logistic chain. ix. New uses for drones • Drones were a great help during the pandemic. • Drone’s 300 flights delivered medicines related to the COVID-19 virus in Xinchang County • For monitoring of lockdowns and surveillance in public places • For broadcasting and spreading relevant messages and information • For spraying, a agricultural drone from XAG and Huawei converted their 2,600 drones and smart robots to disinfectant sprayers x. Health applications surge Research suggests that pandemic related digital health solutions are surging.

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• Digital diagnostics. IoT devices are used to perform digital diagnostics. There was a spike in usage of a digital thermometer, Kinsa, as the pandemic spread in the US • Telehealth consultations. Telehealth has surged during the lock downs. The digital visits in Stanford Children’s Health Hospital have increased from 30 to 620 per day approximately • Robot assistance. Robots were used to clean and disinfect hospitals to avoid human interaction and to perform medicine delivery in China xi. Trace and track solutions • With huge disruption on supply chains and change in demand patterns, the supply chain visibility became more critical. IoT technology providers make use of this data and update the customers accordingly • Vesseltracker.com and Geotag publish the updates on the global cruise ship and freight and road transports respectively • Singapore International Airlines (SIA) geared up to transport and deliver COVID-19 vaccines [29] xii. Smart City data platforms • During the crisis, a predominant data platform was set up, and this became one of the most vital tools in many Smart City initiatives • Smart City Data Hub allowed epidemiologic investigators to obtain and confirm data about coronavirus cases in South Korea • Some cities, such as Boston, built new platforms to monitor the cases of pandemic spread xiii. Easy-​to-​install IoT retrofit solutions have increased [27] • Easy to use retrofit IoT solutions are beneficial to organizations and end-​ users who are not connected digitally • Bosch’s smart meter retrofit is one of the good examples that enable utility agencies to read meter reading xiv. Delay in Technology roadmaps • Many technology standards rely on face-​to-​face discussions and consensus among a group of experts. The pandemic made it more difficult for these experts to work together due to border restrictions. This issue has resulted in delays in finalizing new technology standards • 3GPP revealed that the Release 16 of 5G, significant for IIoT, is postponed by a few months. This enhances reliability, network latency, and introduces support for time-​sensitive networking (TSN). Subsequently, Release 17 will also be further rescheduled • The decisions of other organizations (e.g., IEEE) will have similar issues, and further setbacks will happen xv. Free supply of products/​services from vendors • Many IoT vendors offered free services, upgrades, or software during the pandemic. • Here is a long list of IoT products vendors who provided free products/​services during the pandemic such as ABB, Autodesk, AVEVA, GE, Hexagon, and MachineMatrics Oden Technologies, Prosoft, PTC/​Rockwell Automation, and Siemens.

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xvi. Shortage of skills became less of an issue • IoT Analytics shows the survey data that the missing talent and skills are the number one problem faced by IoT users and vendors during project implementation. The challenge has intensified during recent years as unemployment was low. The tech talent will be soon available to be hired as many people lost their jobs due to the pandemic. With demand for new jobs declining (Figure 1.22) and more talent available, “missing talent” may soon not be the top challenge anymore after the pandemic is over. xvii. The complete picture of COVID-19 IoT impact • The complete picture of all effects of COVID-19 on the IoT is illustrated in Figure 1.23. This illustrates the short-​term and long-​term effects (positive and negative) in various IoT fields.

FIGURE 1.22  Top 5 Industry 40 implementation challenges before the pandemic.

FIGURE 1.23  COVID-19 IoT impact: The complete picture (Source: IoT Analytics).

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1.17  CONCLUSION Internet of Things is a new paradigm shift in the field of the internet. It is a major research field for researchers in embedded systems, information technology, and computer science. This is owing to its diverse applications and diverse mix of various embedded and communication technologies in its architecture. Like the famous quote “Rome was not built in a day”, the evolution of IoT also has evolved gradually over a period with a lot of research being carried out. The modern IoT is a convergence of numerous technologies such as sensor interfaces and integration, wireless communication, data management, cloud computing, and data analytics. The digital world does not come without loopholes and security risks. The IoT is no exception to the risk of being hacked into the devices to steal valuable customer information and data. Researchers need to address the current IoT issues such as security and privacy of the devices and networks, cost of devices, interoperability, and power requirements [5]. COVID-19 has significantly changed the working habits of employees and employers, and IoT helps in the new normal. So, there are various positive and negative impacts of IoT on the way we live and work. Finding a skilled workforce has been the biggest challenge for Industrial IoT before the pandemic. However, the job losses will lead to gaining skills in IoT, which might not be the biggest challenge for IoT in the future.

REFERENCES [1] https://​en.wikipe​dia.org/​wiki/​Int​erne​t_​of​_​thi​ngs [2] https://​int​erne​toft​hing​sage​nda.tec​htar​get.com/​def​i nit​ion/​Inter​net-​of-​Thi​ngs-​IOT [3] www.imda.gov.sg/​-​/​media/​imda/​files/​indus​try-​deve​lopm​ent/​inf​rast​ruct​ure/​tec​hnol​ogy/​ inter​neto​fthi​ngs.pdf%3Fla%3Den [4] “Internet of Things-​ IoT: Definition, Characteristics, Architecture, Enabling Technologies, Application & Future Challenges”, IJESC, Preprint · May 2016. www. resea​rchg​ate.net/​publ​icat​ion/​330425​585. [5] www.embi​tel.com/​blog/​embed​ded-​blog/​unr​avel​ing-​the-​story-​of-​evolut​ion-​of-​IOT-​and-​ its-​rapid-​adopt​ion [6] https://​int​erne​toft​hing​sage​nda.tec​htar​get.com/​def​i nit​ion/​Inter​net-​of-​Thi​ngs-​IoT [7] Avg. yields per hectare in India: https://​data.gov.in/​resour​ces/​yield-​hect​are-​major-​crops/​ downl​oad [8] The Top ten IoT Segments in 2018 –​based on 1,600 real IoT projects. IoT Analytics. https://​iot-​analyt​ics.com/​top-​10-​iot-​segme​nts-​2018-​real-​iot-​proje​cts/​ [9] The Future of IoT: 4 Predictions about the Internet of Things. Thrive Global, COMMUNITY, October 7, 2019, Mehavarunan. https://​thriv​eglo​bal.com/​stor​ies/​the-​fut​ ure-​of-​IoT-​4-​pred​icti​ons-​about-​the-​inter​net-​of-​thi​ngs/​#: [10] A New Generation of Connected Devices, Thrive Global, Community, April 15, 2019, Debora John. https://​thriv​eglo​bal.com/​stor​ies/​a-​new-​gen​erat​ion-​of-​connec​ted-​ devi​ces/​ [11] The Future of IoT: 4 Predictions about the Internet of Things. Thrive Global, COMMUNITY, October 7, 2019, Mehavarunan. https://​thriv​eglo​bal.com/​stor​ies/​the-​fut​ ure-​of-​IOT-​4-​pred​icti​ons-​about-​the-​inter​net-​of-​thi​ngs/​#: [12] www.tut​oria​lspo​int.com/​int​erne​t_​of​_​thi​ngs/​inte​rnet​_​of_​thin​gs_​t​utor​ial.pdf

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https://​en.wikipe​dia.org/​wiki/​Nar​rowb​and_​IoT https://​en.wikipe​dia.org/​wiki/​LoRa https://​en.wikipe​dia.org/​wiki/​Sig​fox IoT technologies and protocols. https://​azure.micros​oft.com/​en-​us/​overv​iew/​inter​net-​ of-​thi​ngs-​iot/​iot-​tec​hnol​ogy-​protoc​ols/​ [17] https://​int​erne​toft​hing​sage​nda.tec​htar​get.com/​def​i nit​ion/​Inter​net-​of-​Thi​ngs-​IoT [18] Introduction to MQTT protocol for IoT applications. Concurrency, Digital Transformation Realized. June 26, 2019. Siddharth Bhola www.conc​urre​ncy.com/​blog/​ june-​2019/​intro​duct​ion-​to-​mqtt-​proto​col-​for-​iot-​appli​cati​ons [19] Dr. Ovidiu Vermesan SINTEF, Norway, Dr. Peter FriessEU, Belgium, “Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems”, River Publishers’ series in communications, 2013. [20] Dr. Ovidiu Vermesan SINTEF, Norway, Dr. Peter FriessEU, Belgium, “Internet of Things–​From Research and Innovation to Market Deployment”, River Publishers’ series in communications, 2014. [21] Industry 5.0: what is it, and what will it do for manufacturing? (raconteur.net). www. racont​eur.net/​manufa​ctur​ing/​manufa​ctur​ing-​gets-​perso​nal-​indus​try-​5-​0/​ [22] Debunking The Myths That Surround The Internet Of Things. Thrive Global, Community, April 24, 2019, Melissa Cook. https://​thriv​eglo​bal.com/​stor​ies/​debunk​ing-​ the-​myths-​that-​surro​und-​the-​inter​net-​of-​thi​ngs/​ [23] IoT Device Hit by Credential Attack Every Two Minutes: Experiment. Ionut Arghire on August 29, 2017. www.secur​ityw​eek.com/​iot-​dev​ice-​hit-​cre​dent​ial-​att​ack-​every-​two-​ minu​tes-​exp​erim​ent [24] 12 tips to help secure your smart home and IoT devices. Steve Symanovich for NortonLifeLock. August 28, 2019. https://​us.nor​ton.com/​inter​nets​ecur​ity-​iot-​smart-​ home-​secur​ity-​core.html [25] We Need to Talk Privacy Protection: What Can You Do to Secure Your Devices and Networks. Thrive Global Community //​February 28, 2019. Natasha Lane. [26] IoT Device Hit by Credential Attack Every Two Minutes: Experiment. Ionut Arghire on August 29, 2017. www.secur​ityw​eek.com/​iot-​dev​ice-​hit-​cre​dent​ial-​att​ack-​every-​two-​ minu​tes-​exp​erim​ent [27] The impact of COVID-19 on the Internet of Things | (iot-​analytics.com). https://​iot-​ analyt​ics.com/​the-​imp​act-​of-​covid-​19-​on-​the-​inter​net-​of-​thi​ngs/​ [28] https://​vent​ureb​eat.com/​2020/​04/​02/​zooms-​daily-​act​ive-​users-​jum​ped-​from-​10-​mill​ ion-​to-​over-​200-​mill​ion-​in-​3-​mon​ths/​ [29] SIA gears up to transport and deliver COVID-19 vaccines. Straits Times. 06 December 2020. www.strai​tsti​mes.com/​singap​ore/​transp​ort/​singap​ore-​airli​nes-​to-​pri​orit​ise-​ capac​ity-​for-​trans​port​ing-​covid-​19-​vacci​nes

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Application of IoT for Pandemic Detection

2.1  INTRODUCTION Various countries around the world are in a vulnerable situation after the global spread of the COVID-​19 virus. Now almost every nation in the world is affected by COVID-​19. There have been unprecedented increases globally in the amount of test reported coronavirus infections. Further to these issues, after the outbreak of COVID-​ 19, several misleading claims, rumors, and unfounded suspicions of coronavirus have also been circulated regularly. They utilize many reputable outlets to study in-​depth many of the critical facets of the COVID-​19 pandemic. The common symptoms of COVID-​19 are listed in Table 2.1. The business sectors most affected by COVID-​19 are automobile, transportation, agriculture, construction, transport, food industry, safety, telecommunications, etc. Now, there has been immense pressure on the healthcare system. To minimize the spread of COVID-​19, everyone has to follow some rules, such as avoiding touching your face, washing hands regularly, using masks, and maintaining social distancing. Furthermore, the latest technologies can be used to minimize the spreading of the pandemic. IoMT is an amalgamation of smart medical devices that offer extensive healthcare services. Telemedicine is a method for using IoMT technology to allow remote monitoring of the patients. This practice will enable physicians to assess, diagnose, and treat patients without needing any patient’s physical presence. Many IoMT software and telemedicine networks experienced a massive surge in traffic. The use of telemedicine reduces the transmission of infection and traffic reduction. Several telemedicine devices such as telemedicine carts, teleconsultation apps, and portable tablets have proved their worth in combating the COVID-​19 pandemic over the past few months. However, telemedicine’s true potential can only be realized with 5G cellular networks. During a pandemic, drones can provide many services. They can ensure minimal human contact and can also be used to enter inaccessible places.

2.2  EMERGENCY CARE SYSTEM The World Health Organization has developed an emergency care system framework to understand the action process during an emergency. There are two striking DOI: 10.1201/9781003181699-2

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TABLE 2.1 Common Symptoms of COVID-​19 Most Common Symptoms

Less Common Symptoms

Fever Dry Cough Fatigue Sputum Production

Shorten of Breath Myalgia Headache Sore Throat

TABLE 2.2 Pathogen Adaptation and Pandemic Risk [1] Stage

Transmission to Humans

Pathogen Examples

Stage 1: animal None reservoir transmission only

H3N8 equine influenza virus

Stage 2: primary infection

Only from animals

Anthrax

Stage 3: limited outbreaks

Few human-​to-​human transmission chains

Marburg virus

Stage 4: sustained outbreaks

Many human-​to-​human transmission chains

Pandemic A (H1N1) 2009 influenza virus

Stage 5: predominant human transmission

Human-​to-​Human

Smallpox virus

Simplified Transmission Diagram

characteristics of the more disaggregated collection of risk factors. First, several risk factors may overlap and combine to affect the occurrence of various diseases or accidents, all of which can lead to the development of ischemic heart disease, such as smoking, food risks, and physical inactivity. Second, a small fraction of cases of multiple diseases or accidents may be caused by particular risk factors; for instance, outdoor air pollution may contribute, among other conditions, to chronic obstructive pulmonary disease and asthma. One consequence of these encounters is that active regulation of a few major risk factors such as smoke from cigarettes and air pollution will dramatically improve the population’s health. Pathogen adaption and pandemic risk charts are shown in Table 2.2 to identify the risk of virus transmission.

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2.3  PREVIOUS WORKS An extensive literature review has been done on pandemic detection using IoT, AI, machine learning, etc. Many researchers have carried out a critical analysis of the research on disease detection systems using IoT [2]. IoT can be used in healthcare for maintaining quality control with real-​time information with a statistical-​based approach, IoT becomes helpful in predicting this disease’s coming situation [3]. An IoT PCR system in real-​time showed the sensitivity and reproducibility of the unit [4]. In the early detection of the novel coronavirus (COVID-​19) work of two firms, BlueDot and Metabiota, the role of Artificial Intelligence (AI) demonstrate how AI-​driven algorithms can make future predictions and readings more accurate by increasing data sharing [5]. Ebola virus spreads by transmission from human to human. It is important to continuously detect and remotely track infected patients. IoT-​based healthcare systems and cloud computing technology is an efficient and proactive approach that offers continuous remote patient monitoring. To detect and track Ebola-​infected patients, a novel architecture based on an RFID system, wearable sensor technology, and cloud computing is helpful, as shown in Figure 2.1 [6]. An IoT-​based surveillance system for disease control can also be used [7]. The COVID-​19 pandemic is unprecedented and has devastated millions of lives across the globe. The pandemic has opened up many scientific problems and opportunities that our society must face to prepare itself for the future, architecture and AI-​assisted applications can be used to efficiently and timely implement community-​based social distance steps and maximize resource use in critical circumstances [8]. Large user-​ specific social interaction has been generated by the advent and proliferation of online social networks (OSNs) that generate comprehensive data that can be used as a potential tool to identify a pandemic for a real-​time surveillance system [9]. A model tractable quantitative study of the ideal disease dynamic management strategy using both lockdown and detection intervention levers can also be helpful [10].

FIGURE 2.1  An architecture based on RFID system.

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The surveillance of influenza-​like diseases can be used to determine the magnitude of outbreaks, location, and timing. Advances in computational and information technology produces higher volumes of electronic data to be automatically collected and analyzed in a more timely fashion than previously possible [11]. The comprehensive indicators for preparedness at the national level are important to assess global vulnerability to disease and pandemic [12]. The moving average cumulative sums and influenza-​like disease (ILI) threshold methods are more sensitive and quicker [13]. The Google Scholar, Pubmed, and Scopus databases using the keyword COVID-​ 19 and Artificial Intelligence (AI) can be used to analyze and identify the applications for pandemic detection [14]. Identifying and isolating infected persons in the crowd is very difficult. IoT can be used to identify infected persons and help to maintain social distancing. Data can be stored in the Cloud, which can be used for remote monitoring and data analysis [15]. IoT can control, track, manage, distribute, and gather user information to provide healthcare assistance. This technology will help people to handle COVID-​19 and possible pandemics better. Three stages need to be addressed during this pandemic, including “Early Detection,” “Quarantine Period” and “After Recovery.” Technology performance differs across connected devices, but it also has its privacy concerns due to unstructured data collected from various devices [16]. AI and Big Data principles can help in the quick and efficient detection of COVID-​ 19. AI technologies can be used in the identification and diagnosis, tracking and prediction of outbreaks, infodemiology, and infoveillance, biomedicine, and pharmacotherapy; large-​scale COVID-​19 disease technologies can also assist in the prediction of outbreaks, surveillance of virus transmission, diagnosis and treatment, and discovery of vaccines and drugs [17]. The Chinese cities and government have taken a techno-​driven approach, and a human-​driven approach has been adopted by Western governments to control the transmission of COVID-19. The findings demonstrate that the techno-​driven approach might be more effective in identifying, isolating, and quarantining individuals [18] and using the Robust Weibull distribution model [19]. The mIoT revamps healthcare systems, as people have started using IoT to handle their health needs, like for appointments, blood pressure monitoring, calories burnt, and much more. The remote health management system is one of the best aspects of IoTs in the healthcare sector, where patients can be tracked and consulted from anywhere. Real-​ time location services are yet another major IoT offer approach. Doctors can conveniently monitor the positions of devices by using the app, which significantly eliminates the unnecessary time spent [20]. Artificial Intelligence (AI) and Big Data will assist with the huge, immense volume of public health surveillance data produced, real-​time monitoring of outbreaks of disease, current trend/​analysis, regular briefing and updating from government organizations and agencies, and awareness of the use of health facilities [21]. The molding of artificial intelligence (AI) along with geographic information system (GIS) dimensions produces GeoAI. GeoAI’s infrastructure and healthcare position is growing, as the location is an integral part of both population and individual health [22]. COVID-​19 has spread to 210 countries around the world. The health system has been profoundly influenced by contemporary society’s economic, educational, and social aspects. Different collaborative approaches between stakeholders have been observed to develop novel ways of screening and detecting COVID-​19 cases at a proportionate rate among humans as the transmission rate continues to increase. Furthermore,

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computational models associated with the 4th Industrial Revolution Technology are helpful in achieving the desired feat [23]. The Big Data techniques for human development in various contexts, including humanitarian crises (including disaster response and migrant crisis), agriculture, poverty alleviation, food security, health care, and education, will play a vital role in the future [24]. Recent developments have shown that collaboration between medical researchers and engineers is crucial to developing expeditious and less expensive approaches to pandemic management [25]. AI’s capacity to aid in diagnosing and monitoring coronavirus development or resolution reliably for detecting, characterizing, and monitoring COVID-​19 development. Automated CT image analysis software based on AI can achieve high accuracy in detecting positive coronavirus patients as well as quantifying the burden of the disease. In a slice-​based “heat screen” or a 3D volume monitor for coronavirus patients, the computer generates quantitative opacity measurements and a visualization of the larger opacities [26]. AI response helps bacteria to organize gene expression on a population-​wide scale and thus execute complex behaviors in unison, similar to multicellular organisms [27]. Outbreaks of swine flu (H1N1) and avian flu (H5N1) jeopardize global health in developing countries in the South-​East Asia region, and there was an urgent need for swift and effective screening methods [28]. Swine-​born influenza was detected in April 2009 in the US and Mexico. Rapid diagnosis of influenza is critical for the initiation of antiviral therapy and quarantine steps, as antiviral therapy should be initiated preferably within 24 hours after the first clinical symptoms of the patient appear [29]. Today, COVID-​19, without an effective vaccine or treatment, is a global, highly transmissible pandemic. With varying degrees of effectiveness, governments around the world have synchronized programs based on containment and mitigation. Countries with low per capita mortality rates of COVID-​19 prefer to share early detection, inspection, touch monitoring, and strict quarantine strategies. The complexity of planning and data analysis needed to adopt these strategies effectively was focused on the introduction and application in the most prosperous nations of digital technology into policy and healthcare [30]. A single bad flu pandemic could cost $3 trillion. To end extreme poverty or to improve shared prosperity in developed countries is hard to imagine more danger. Indeed, OECD sees a significant pandemic, among others, as a top global catastrophe risk, one that is higher than the risk of terrorism. It will bring widespread suffering, economic downturn, and global social disruption, with the poor and fragile states hitting hardest. Setting a pandemic risk mitigation objective should be the first step towards risk control, complemented by guidelines for international organizations working towards the aim. Risk management could strengthen and bridge the public veterinary and human health structures in developed countries to remove the weakest links in global pathogens protection. Pandemic risk prevention is a public benefit that the governments can only offer by their concerted acts. The provision of this service will benefit from the systematic implementation of ‘supply science,’ primarily through the use of One Health approaches for early successful control of contagion [31]. Wireless networks of the fifth generation (5G) will be launched globally as of 2020, and more features such as universal convergence, ultra-​reliability, and low latency are being standardized. However, 5G will not fulfill all feasible standards in

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FIGURE 2.2  Sensors and their applications [32].

2030. Wireless communication networks of the sixth generation (6G) are expected to have global scope, improved spectral/​energy/​cost performance, improved intelligence and protection levels, etc. 6G networks should rely on emerging technology that can satisfy these requirements, i.e., waveform architecture, multi-​access, channel coding schemes, multi-​antenna systems [32] as shown in Figure 2.2. Geospatial technology with best practices from China in the battle against COVID-​ 19 in Ghana is modeled on incessant mobility trends [33]. Industrial processes, communication, networking technologies, and Unmanned Aerial Vehicle technology advancement have led to an increase in their use in political, industrial, and social applications [34]. Owing to the COVID-​19 pandemic, the year 2020 is facing a global health and economic crisis. Countries worldwide are using digital technologies to address this global crisis, which depends heavily on the availability of wireless communication systems in one way or another [35]. 6G and beyond will fulfill the requirements of a fully connected world and provide everybody with all-​around wireless connectivity. In order to satisfy an ever-​growing number of smart devices and services, transformative technologies are expected to drive acceleration. Major technological breakthroughs to achieve convergence objectives within 6G [36]. 6G is a ground-​breaking technology for networking that, from 2030, will dominate the entire healthcare sector. It will govern not only the health sector but also numerous industries. The most significant barriers to healthcare are still time and space, and 6G will overcome those barriers. 6G can also be seen to be a game-​changing technology for healthcare [37].

2.4  APPLICATION OF IOT AND SMART TECHNOLOGY FOR PANDEMIC DETECTION IoT can be used effectively in telemedicine applications to monitor patient conditions (as shown in Figure 2.3). It is very much required in such a COVID period. Online

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FIGURE 2.3  Telemedicine architecture.

FIGURE 2.4  Emergency care system.

medical consultation can help to minimize the spread of the pandemic, it also helps to minimize traffic jams, save fuel, and minimize air pollution. It can be more helpful for children and old people to monitor their health condition regularly. WHO has been implemented in one framework (shown in Figure 2.4) for effective emergency care. The development of digital infrastructures like 5G and 6G technology for mobile communication, application of IoT sensors, and smart devices will enable us to monitor real-​time data from a remote location. Data analytics can be used to

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FIGURE 2.5  Role of technology for pandemic detection.

understand the data better to extract the information and accurate prediction of future trends. The application of telemedicine and drone technology can help make social distancing to avoid spreading the pandemic. Technologies that can be used in pandemic detection are shown in Figure 2.5.

2.5  CONCLUSION The outbreak of the coronavirus pandemic has intensified once again. Many Asian and European countries have been dealing with the fourth wave of coronavirus in recent weeks. The corona's omicron subvariant BA.2 is thought to be the cause of the abrupt spike in new cases. Researchers have identified a new XE variation of the corona in this hour of distress. The use of the latest technologies such as IoT, Telemedicine, AI, 5G, and 6G technologies can help minimize the pandemic’s spread. Also, IoMT can be used to monitor and control the pandemic remotely.

REFERENCES [1]‌

Jamison DT. Disease Control Priorities, 3rd edition: improving health and reducing poverty. vol. 391. 2018. https://​doi.org/​10.1016/​S0140-​6736(15)60097-​6. [2]‌ Sittisaman NP and A. Malicious Apps 2019:437–​ 46. https://​doi.org/​10.1007/​ 978-​981-​13-​6861-​5. [3]‌ Singh RP, Javaid M, Haleem A, Suman R. Internet of things (IoT) applications to fight against COVID-​19 pandemic. Diabetes Metab Syndr Clin Res Rev 2020;14:521–​4. https://​doi.org/​10.1016/​j.dsx.2020.04.041.

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[4]‌ Zhu H, Podesva P, Liu X, Zhang H, Teply T, Xu Y et al. IoT PCR for pandemic disease detection and its spread monitoring. Sensors Actuators, B Chem 2020;303. https://​doi. org/​10.1016/​j.snb.2019.127​098. [5]‌ Allam Z, Dey G, Jones DS. Artificial Intelligence (AI) Provided Early Detection of the Coronavirus (COVID-​19) in China and Will Influence Future Urban Health Policy Internationally. Ai 2020;1:156–​65. https://​doi.org/​10.3390/​ai1020​009. [6]‌ Sareen S, Sood SK, Gupta SK. IoT-​based cloud framework to control Ebola virus outbreak. J Ambient Intell Humaniz Comput 2018; 9:459–​76. https://​doi.org/​10.1007/​s12​ 652-​016-​0427-​7. [7]‌ Mathew A, Amreen FS, Verma A. Smart Disease Surveillance Based on Internet of Things (IoT). Int J Adv Res Comput Commun Eng 2015; 4:180–​3. https://​doi.org/​ 10.17148/​IJAR​CCE.2015.4541. [8]‌ Gupta M, Abdelsalam M, Mittal S. Enabling and Enforcing Social Distancing Measures using Smart City and ITS Infrastructures: A COVID-​19 Use Case 2020:1–​5. [9]‌ Al-​garadi MA, Khan MS, Varathan KD, Mujtaba G, Al-​Kabsi AM. Using online social networks to track a pandemic: A systematic review. J Biomed Inform 2016; 62:1–​11. https://​doi.org/​10.1016/​j.jbi.2016.05.005. [10] Charpentier A, Elie R, Laurière M, Tran VC. COVID-​19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability 2020:1–​45. [11] Olson DR, Konty KJ, Paladini M, Viboud C, Simonsen L. Reassessing Google Flu Trends Data for Detection of Seasonal and Pandemic Influenza: A Comparative Epidemiological Study at Three Geographic Scales. PLoS Comput Biol 2013; 9. https://​ doi.org/​10.1371/​jour​nal.pcbi.1003​256. [12] Oppenheim B, Gallivan M, Madhav NK, Brown N, Serhiyenko V, Wolfe ND, et al. Assessing global preparedness for the next pandemic: Development and application of an Epidemic Preparedness Index. BMJ Glob Heal 2019; 4:1–​9. https://​doi.org/​10.1136/​ bmjgh-​2018-​001​157. [13] Singh BK, Savill NJ, Ferguson NM, Robertson C, Woolhouse ME. Rapid detection of pandemic influenza in the presence of seasonal influenza. BMC Public Health 2010; 10. https://​doi.org/​10.1186/​1471-​2458-​10-​726. [14] Vaishya R, Javaid M, Khan IH, Haleem A. Artificial Intelligence (AI) applications for COVID-​19 pandemic. Diabetes Metab Syndr Clin Res Rev 2020; 14:337–​9. https://​doi. org/​10.1016/​j.dsx.2020.04.012. [15] Kumar K, Kumar N, Shah R. Role of IoT to avoid spreading of COVID-​19. Int J Intell Networks 2020; 1:32–​5. https://​doi.org/​10.1016/​j.ijin.2020.05.002. [16] Nasajpour M, Pouriyeh S, Parizi RM, Dorodchi M, Valero M, Arabnia HR. Internet of Things for Current COVID-​19 and Future Pandemics: An Exploratory Study 2020. [17] Pham Q-​V, Nguyen DC, Huynh-​The T, Hwang W-​J, Pathirana PN. Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-​19) Pandemic: A Survey on the State-​of-​the-​ Arts. IEEE Access 2020; 8:130820–​39. https://​doi.org/​10.1109/​acc​ess.2020.3009​328. [18] Kummitha RKR. Smart technologies for fighting pandemics: The techno-​and human-​ driven approaches in controlling the virus transmission. Gov Inf Q 2020;37:101481. https://​doi.org/​10.1016/​j.giq.2020.101​481. [19] Omputing C. Predicting the Growth and Trend of COVID-19 Pandemic Using Machine Learning and Cloud 2020. [20] Dimitrov DV. Medical internet of things and big data in healthcare. Health Inform Res 2016; 22:156–​63. https://​doi.org/​10.4258/​hir.2016.22.3.156. [21] Bragazzi, N.L.; Mansour, M.; Bonsignore, A.; Ciliberti, R. The Role of Hospital and Community Pharmacists in the Management of COVID-​19: Towards an Expanded

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Wireless Communication: Advancements and Challenges Definition of the Roles, Responsibilities, and Duties of the Pharmacist. Pharmacy 2020, 8, 140. https://​doi.org/​10.3390/​phar​macy​8030​140 Kamel Boulos MN, Peng G, Vopham T. An overview of GeoAI applications in health and healthcare. Int J Health Geogr 2019;18:1–​9. https://​doi.org/​10.1186/​s12​ 942-​019-​0171-​2. Agbehadji IE, Awuzie BO, Ngowi A. Review of Big Data, Artificial Intelligence and Nature-​Inspired Computing Models for Performance Improvement towards Detection of COVID-​19 Pandemic Case and Contact Tracing Review of Big Data, Artificial Intelligence and Nature-​Inspired Computing Models. WwwResearchgateNet 2020:1–​ 17. https://​doi.org/​10.13140/​RG.2.2.28677.70883. Ali A, Qadir J, Rasool R ur, Sathiaseelan A, Zwitter A, Crowcroft J. Big data for development: applications and techniques. Big Data Anal 2016; 1. https://​doi.org/​10.1186/​ s41​044-​016-​0002-​4. Tsikala Vafea M, Atalla E, Georgakas J, Shehadeh F, Mylona EK, Kalligeros M et al. Emerging Technologies for Use in the Study, Diagnosis, and Treatment of Patients with COVID-​19. Cell Mol Bioeng 2020. https://​doi.org/​10.1007/​s12​195-​020-​00629-​w. Gozes O, Frid M, Greenspan H, Patrick D. Rapid AI Development Cycle for the Coronavirus (COVID-​19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis Article Type: Authors: Summary Statement: Key Results: List of abbreviations. ArXiv:200305037 2020. Hammer BK, Bassler BL. Regulatory small RNAs circumvent the conventional quorum sensing pathway in pandemic Vibrio cholerae. Proc Natl Acad Sci USA 2007; 104:11145–​9. https://​doi.org/​10.1073/​pnas.070​3860​104. Sun G, Matsui T, Kim S, Takei O. KAZEKAMO: An infection screening system remote monitoring of multiple vital-​signs for prevention of pandemic diseases. 2014 IEEE 3rd Glob Conf Consum Electron GCCE 2014 2014:225–​6. https://​doi.org/​10.1109/​ GCCE.2014.7031​086. Patel P, Graser E, Robst S, Hillert R, Meye A, Hillebrand T, et al. RapidSTRIPE H1N1 test for detection of the pandemic swine origin influenza A (H1N1) virus. J Clin Microbiol 2011; 49:1591–​3. https://​doi.org/​10.1128/​JCM.02563-​10. Whitelaw S, Mamas MA, Topol E, Van Spall HGC. Applications of digital technology in COVID-​19 pandemic planning and response. Lancet Digit Heal 2020; 2:e435–​40. https://​doi.org/​10.1016/​S2589-​7500(20)30142-​4. Olga J Pandemic Risk. Financ Dev 2014; 51:16–​7. Xiaohu Y, Cheng-​xiang W, Jie H, Xiqi G, Michael W, Yongming H, et al. Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts. Sci CHINA Inf Sci 2020; 020300:1–​ 76. https://​doi.org/​10.1007/​s11​ 432-​020-​2955-​6. Sarfo AK, Karuppannan S Application of Geospatial Technologies in the COVID-​19 Fight of Ghana. Trans Indian Natl Acad Eng 2020; 5:193–​204. https://​doi.org/​10.1007/​ s41​403-​020-​ Euchi J. Do drones have a realistic place in a pandemic fight for delivering medical supplies in healthcare systems problems? Chinese J Aeronaut 2020. https://​doi.org/​ 10.1016/​j.cja.2020.06.006. Saeed N, Bader A, Al-​Naffouri TY, Alouini M-​S When Wireless Communication Faces COVID-​19: Combating the Pandemic and Saving the Economy 2020:1–​11. Akyildiz IF, Kak A, Nie S 6G and Beyond: The Future of Wireless Communications Systems. IEEE Access 2020; 8:133995–​4030. https://​doi.org/​10.1109/​acc​ess.2020.3010​896. Nayak S, Patgiri R 6G Communication Technology: A Vision on Intelligent Healthcare 2020; 00:1–​9.

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3

TV White Space (TVWS) Technology

3.1  INTRODUCTION There has been much research in the past few years to tap the unutilized TV bands for communication. As the allocated spectrum for TV band is quite huge, ranging from 400 to 900MHz [1–​2]. Some channels utilize this band, and the rest is left unused or called the “White Spaces”. White Spaces emerge as a research output of Cognitive Radio (CR). In 2002, DARPA initiated a project for using this research area for communication. The demand for wireless communications has been growing exponentially over the past few decades, with the advancement of technologies such as GSM, 2G, 3G, 4G, 5G and upcoming 6G for cellular communications and other applications such as satellite, aeronautics, civil aviation, transport (including long-​distance railways and metro railways), maritime, military, security and surveillance, remote sensing, emergency services and radio astronomy. To date, activity on the internet has primarily consisted of communication between people. So far, only 50% of the world’s population has wired, wireless or cellular internet connectivity. The remaining 50% or 3 billion people (O3B) have no connectivity at all. The United Nations Broadband Commission has set the goal to bring broadband connectivity to 3.8 billion people worldwide, who are not connected to the internet and unable to use social and economic resources in the modern world. To achieve the target of “Connecting the Other Half”, the United Nations’ Broadband Commission for Sustainable Development (UNBSD) has set ambitious 2025 goals. At the Commission’s meeting and the 2018 Annual Meeting of the World Economic Forum in Davos, these targets were launched [3]. One of the biggest reasons for no connectivity is poor or no infrastructure in developing countries’ remote & rural areas. Laying the fibre to these outlying flanged areas is too expensive and challenging task. So, wireless is the only solution to provide connectivity to these areas. Due to the advent of the Internet of Things (IoT), wireless connectivity is required for a wide variety of sensors and control mechanisms supporting various applications. These applications include smart cities, smart grid, smart meters, smart factories, and precision agriculture. As per the Statista report, the number of intelligent connected devices is likely to exceed 38.6 billion by 2025 and 50 billion by 2030 [4]. All the DOI: 10.1201/9781003181699-3

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Wireless Communication: Advancements and Challenges

above services need wireless communication to connect, and the spectrum is blood to these communication needs.

3.2  UNDERUTILISED SPECTRUM If one looks at the spectrum allocation chart of any country, it is a 100% allocated spectrum. Figure 3.1 and Figure 3.2 illustrate the Spectrum allocation chart by FCC in the USA and IMDA in Singapore. A study was carried out in Singapore and found that the spectrum usage at any vicinity and time is only 6.5% of the actual allocation. This measurement is plotted in Figure 3.3. Various agencies have carried out similar measurements at many places, and the results are almost similar (within the range

FIGURE 3.1  Spectrum allocation chart by FCC (Source: FCC website).

FIGURE 3.2  Spectrum allocation chart by IMDA (Source: IMDA website).

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TV White Space (TVWS) Technology

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FIGURE 3.3  Actual usage of the spectrum at any time.

FIGURE 3.4  Type of spectrums.

of 5 to 15%). The reason for low usage of spectrum allocation is that a spectrum is issued permanently to an agency or user. This phenomenon of spectrum allocation and actual usage is very alarming and inefficient. There is an urge to make the changes in the way the spectrum is allocated, and it is used. The above discussion shows that even though the spectrum is 100% allocated worldwide, the spectrum usage is significantly lower. With an increase in the spectrum demand, the spectrum’s allocation and usage should be dynamic and opportunistic. The licensed bands have to be used for essential services such as cellular communication. The users own the spectrum, and there is no interference in this band. Industrial, Scientific & Medical (ISM) bands should be used for non-​essential services such as WiFi, Bluetooth and other IoT services such as LoRa and Sigfox. These are unlicensed bands where the spectrum is free to use for all users, but there are chances of interference from other users. There is a requirement of license-​exempt spectrum growing in the past decade. The user does not own this spectrum, and the user has to use the spectrum on a need basis dynamically and opportunistically. These bands are known as White Spaces, as depicted in Figure 3.4. TV White Spaces (TVWS) is the under-​utilized spectrum in the band allocated to TV broadcasters. Since digital transmission has better spectrum efficiency than analogue, the trend of converting from analogue to digital TV has freed up more space in TV bands for TVWS worldwide (Figure 3.5). Sharing of

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FIGURE 3.5  White Spaces in the TV band.

FIGURE 3.6  Spectrum overlay.

the spectrum by TVWS is an essential topic as it is the first step towards the effective usage of spectrum in a dynamic and opportunistic manner. Figure 3.6 illustrates the spectrum overlay for any instance with allowed transmitting power level. TVWS is expected to be the first CR system. It has unrivalled propagation characteristics in the very-​high frequency (VHF) and ultra-​high frequency (UHF) range. This long-​range of TVWS makes it an appealing choice for rural connectivity. Simultaneously, better penetration gives it an advantage over other technologies for machine-​to-​machine implementations in cluttered and dense regions. It also offers a strong choice as a networking backbone for smart cities due to urbanisation. The favourable propagation characteristics of TVWS helps to make white space devices (WSDs) more potent than their WiFi predecessors. White space technology would greatly increase the usefulness and help reduce the cost of using a license-​exempted spectrum for broadband connectivity. The deployment of last-​mile connectivity in hard-​to-​serve areas is also going to make it more accessible. These advantages have significant economic and growth benefits [6].

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TABLE 3.1 Affordability versus Reach Challenge Across the Billion Demography Billions of People on Earth

Average Annual Income

Affordable Monthly Spent on Communication

First billion Second billion Third billion Fourth billion Fifth billion Sixth billion Seventh billion

$29206 $12722 $5540 $2987 $1771 $1065 $540

$205 $53 $23 $12 $7 $4.4 $2.25

Source: Richard Thanki, University of Southampton, from UN, ITU Data, WSA & IEEE.

FIGURE 3.7  Demographic coverage disparity in developing countries (Source: Whizpace).

Currently, urban areas have excellent connectivity, and suburbs have moderate connectivity and almost no connectivity in most developing countries. The key reason for this disparity is user affordability versus the Telco cost for providing the infrastructure. The cost of installing infrastructure is cheaper in cities as one base station can cover a significant population. Whereas in the rural area one base station covers a larger area but a smaller population, making the cost of deployment per user more expensive. On the other hand, the user affordability (paying capacity) in cities is much higher than the villages, as depicted in Figure 3.7. Table 3.1 shows the average annual income and monthly affordability on communication for every billion. This disparity makes Telcos less interested in providing connectivity in the rural areas, as this does not make an economic sense to the operators unless there is a government subsidy. Since TVWS can propagate through a non-​line of sight (NLOS) environment, there is no need to erect a tower for the installation. The TVWS equipment is usually cheaper than the 3G/​4G base stations. This characteristic reduces the cost of deployment heavily, and hence Telcos can provide the connectivity at a lower cost even in the rural demographics.

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3.3  EVOLUTION OF TVWS The first device for TVWS application was commercialised in 2011 by the Federal Communication Commission (FCC) [7]. The product was officially deployed in 2012 in North Carolina as the first TVWS network device. West Virginia University became the first campus in July 2013 to deploy a fully functional wireless broadband within the university and adjacent areas using TVWS [8]. FCC laid out the guidelines that the unutilized spectrum in the TV bands can only be used by TVWS equipment explicitly designed to operate in the unlicensed band [9]. To determine the potential and practical use of TVWS technology, the University of Cambridge put up a trial named Cambridge White Space Trial. It mainly focused on promoting research in TVWS without disturbing the licensed bands in the TV spectrum [10]. While performing free channel analysis on TVWS, even though Singapore receives TV signals from its neighbouring countries, such as Malaysia & Indonesia, multiple unused channels can be found at a lower frequency in 470-​530 MHz and some channels in the 530-​698 MHz band. The European Commission of communities also approved the use of TVWS in 2014 for research purposes and is working to commercialize the technology for broadband deployment using TVWS [11]. Later, Microsoft came up with the idea to implement TVWS in rural areas and provide resources to companies working in TVWS. Microsoft’s FarmBeats is a project that integrates IoT sensors, data analysis, and machine learning using TVWS [12]. Even though TVWS gives excellent RF propagation, the technology faces many technological challenges emerging from such co-​ existence restrictions. These restrictions enable users to avoid causing interference to primary users or each other. COGEU (COGnitive radio systems for efficient sharing of TVWS in the EUropean context) has devised the detailed framework to resolve the implementation issues faced by TVWS technology, as outlined in Figure 3.8. COGEU [13] was a joint project designed to exploit the ASO through the development of cognitive radio systems that utilise the excellent propagation characteristics of TVWS through the implementation and promotion of real-​time secondary spectrum trading [14]. This model includes issues such as technical feasibility, regularity feasibility and market potential in that country. These issues lead to the generation of standards, patents, and technological know-​how; spectrum policies and business models developed by system integrators and ISPs. The availability of TVWS varies worldwide, depending on regulatory authorities’ policies, which is the critical drawback of the COGEU model. A framework is therefore required to explain the opportunities, strengths, and shortcomings of TVWS. The commonly used SLEPT (Social, Legal, Economical, Political and Technological) tool is used to analyse the existing challenges, and possible research concerns related to database assisted TVWS solutions. Spurred by global pilot projects and deployments conducted for TVWS, the COGEU framework’s shortcomings create a gap and need comprehensive research using this approach. The contributions of the research can be summarised as follows [14]: a) Practical challenges faced by geolocation database (GLDB). b) Challenges of TVWS networks using the SLEPT framework. c) Emerging trends in TVWS technology, based on current developments.

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FIGURE 3.8  COGEU TVWS Framework [15].

TABLE 3.2 Widely Used Propagation Models [17] Model Line of Sight (LOS) ITU-​R P.525 Irregular Terrain Model (ITM) Okumura-​Hata

Description

Simple model for viewing obstructions Free Space Path Loss model 'Longley Rice' Model. US Government general-​purpose model used by FCC Hata model for cellular communications in urban areas ECC33 (ITU-​R P.529) ECC33 model for cellular and microwave communications Stanford University SUE model is used for WiMax Interim (Sill) communications COST231-​Hata European COST231 is the frequency extension to Hata model for urban Ericsson 9999 Ericsson 9999 model for cellular communications up to 1900MHz Egli VHF/​UHF' General-​purpose VHF/​UHF model. More conservative than FSPL

Frequency Range All frequency range 20 to 100,000 MHz 20 to 20,000 MHz 150 to 500 MHz 700 to 3500 MHz 1900 to 11000MHz 150 to 2000 MHz 150 to 1900 MHz 30 to 1000MHz

Three tuples are required for the geolocation database to approximate the availability of TVWS within a geographical area. These tuples are the availability of time, location, and frequency. There is a variety of propagation models for different purposes, and their brief comparison is tabulated (Table 3.2), and two popular TVWS propagation models are: (i) Okumura-​Hata Model. The Hata models were designed to support the frequency range (150-​1500MHz) for Urban cellular planning and are focused on

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FIGURE 3.9  The simulation of TVWS coverage in (a) urban & (b) rural area with hilly terrain.

the tower height more than 30m. This model assumes that the transmitter is at more height than the average height of the rooftops [17]. (ii) Longley-​Rice model and the irregular terrain model (ITM). This model is widely used as it is ideal for any RF devices from handheld walkie-​talkies in VHF band to microwave links in SHF band. Electromagnetic parameters, terrain, atmospheric diffraction, and ground cluttering are used to calculate the radio signal’s attenuation at any point on the Earth [18]. The coverage area in a rural area is always longer than in an urban area, and Figure 3.9 illustrates the area covered in urban and rural, keeping all other parameters the same. The distance covered in rural areas and partially hilly terrain is up to ten times more in urban areas. SLEPT framework (Table 3.3) is used to discuss different parameters, such as WSDs’ transmitting power, geolocation contours, the number of channels, channel bandwidths, and whether the conservative or non-​conservative approach is used. Under the widely used database supported TVWS deployments, devices consist of Master (or Access Point) and Slave (Station, or Client) WSDs. The master device communicates with the database (GLDB) operator the GPS coordinates and HAAT and obtains operational parameters such as frequency of operation and Tx power. Whereas a Slave WSD can only access the parameters through a Master WSD. Figure 3.10 illustrates a typical example of the functions and components of a GLDB assisted TVWS network. This network can be described in the steps below [16]: Step I: A GLDB-​assisted master WSD queries the spectrum regulator to collect official GLDB operators’ list. GLDB operators have completed the certification process. The spectrum regulator checks the GLDB operators to ensure that their databases can function within the specified operating terms and conditions before permission is granted. Step II: The spectrum regulator sends a reply with the list of approved GLDB operators to the master WSD. The reply to query lists the certified GLDB operators. Step III: The master WSD sends the query to the GLDB operators for the availability of TVWS channels in the vicinity by providing its operational parameters

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TABLE 3.3 Summary of SLEPT Indicators for Database Assisted TVWS technology Components

Indicators

Performance Matrices

Social

TWTS projects centric needs. Non-​ commercial approach.

Legal

SDR enablement. Legal certifications. TVWS parameters to be permitted. Real-​time strategy-​proof auction mechanism for secondary spectrum market. Highly competitive secondary spectrum price. Spectrum regulation and policies. Enabling acts for dynamic spectrum access. Incumbent co-​existence. Self-​ coexistence. Heterogeneous co-​existence.

Successful implementation of projects. Technical issues such as self-​coexistence and heterogeneous co-​existence are not emphasised. Market-​driven. Regulation driven.

Economic

Political

Technology

Strategy-​proof real-​time spectrum trading. Complexity analysis.

Spectrum measurement campaigns, pilot projects. The existence of TVWS databases. Transmission power control mechanism. Dynamic spectrum sharing.

such as the antenna configuration and the maximum transmission power, the height above average terrain (HAAT), and the frequency range. Step IV: The GLDB performs the necessary calculations on the queries based on the set of operational parameters corresponding to that WSD and then responds to it. The regulator then provides the GLDB operators with a database for the occupied spectrum by DTT (Digital Terrestrial Television), licensed programme-​making and special events (PMSE), and wireless microphones. The GLDB then informs the WSD of available channels with the highest allowed transmission power in terms of EIRP (Effective Isotropic Radiated Power). Step V: The slave WSD sends the query to the master WSD about the usage of channel and EIRP. The slave device needs to provide its unique device identifier, usually its MAC address. The slave device requests the operational parameters specific to it, or this can use its generic parameters. Step VI: Once the request from the slave device is received, the master device sends the general operational parameters to the slave device. The slave device must listen to the master device’s instructions before transmission. The slave device will decide whether to request specific operational parameters or use the generic parameters. Once the slave device requests any of the operational parameters to the master device, it relays to the GLDB. GLDB would estimate the optimal operational parameters for the slave device (Figure 3.10).

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FIGURE 3.10  Database-​assisted TVWS network architecture [16].

The next topics will be on the standardization, regulation scenarios in different countries, trials, deployments, and applications of TVWS. The standardization is different from the regulation. The standards help to set the operational limits to avoid interference to the primary services such as TV transmission and microphones [18]. International bodies guide standards. Whereas the regulations help provide maximum and interoperable protocols and devices for particular implementations using the spectrum such as RANs, LANs, and Database Access specific countries control regulations.

3.4  STANDARDISATION OF TVWS The unrivalled propagation characteristics of TVWS results in more extended coverage and superior penetration through obstacles. The extended coverage makes TVWS an alluring technology for rural connectivity. Simultaneously, this improved penetration and susceptibility to work in a multi-​path environment gives TVWS an edge over other options for narrowband (IoT applications) communication in a dense and cluttered environment [19]. Since WSDs utilize TVWS, these devices should not cause interference to the Primary Users (PUs) such as TV broadcasting station and microphones. Geolocation database (GLDB), spectrum sensing or beacons are the techniques for PUs protection from WSDs. All the above techniques have their pros and cons, though there is more harmony on using GLDB to determine under-​utilised TVWS channels [19]. In addition to avoiding the interference using the above techniques, there must be a process to avoid any possibility of interference caused due to spilling the spectrum of

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FIGURE 3.11  Comparison of Spectrum masks (scaled) for WiFi, LTE with TVWS (Source: Microsoft Research).

WSD. This spilling of spectrum is termed as out-​of-​band (OOB) emission and might cause interference to the incumbent devices, including PUs. Meeting this OOB set by regulators is one of the most challenging criteria for TVWS. One of the reasons for stricter OOB set by FCC was due to technology uncertainty initially. Besides, existing PUs protested on the potential interference to their current system. There were not enough datasets to back these assertions, so FCC adopted a very cautious approach to emission mask specifications [19]. With more studies conducted and Ofcom’s results in the UK and IMDA in Singapore, emission masks’ requirements were relaxed in the UK and Singapore [20, 21]. Moving forward, other regulators also are following existing regulators [22]. Figure 3.11 depicts the stringent spectrum mask of TVWS and its comparison with WiFi and LTE. The spectrum mask limit for TVWS is 35dB stricter than WiFi or 5000 times in absolute terms and 20dB stricter than LTE or 100 times in absolute terms. A series of standards have been created to support White Space development. 802.11af is the standard issued by IEEE to govern and develop protocols in TVWS, which is referred to as Super-​WiFi [23, 24]. The physical layer development for 802.11af carries forward from 802.11ac in the lower frequency bands of VHF and UHF in the range of 54 MHz to 790 MHz using Orthogonal Frequency Division Multiplexing [25, 26]. In addition to 802.11af, the IEEE has standardised another TVWS standard, 802.22 [27]. While 802.11af is a wireless LAN standard designed for long-​range connectivity, 802.22 is a wireless regional area network (WRAN) standard, for ranges as long as 100 km [28]. The co-​existence of 802.11af and 802.22 standards can be applied either in centralized or distributed manners and various co-​existence techniques [29, 30]. There are other standards such as ECMA 392, 802.16h and DySPAN. Table 3.4 is the comparison of all TVWS standards.

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Features/​ Standards ECMA 392 Key Feature

Freq Range Support for multiple frequency channels Mobility support Max. Throughput (Mbps) Range (km) Channelisation (MHz) Modulation Network Topology Handover Support

IEEE 802.11af

Specifies MAC First cognitive radio for WLAN operation in sub-​layer and unconnected geographic TVWS band a PHY layer. locations on non-​ Also specifies a interfering channels MUX sublayer for higher-​layer protocols Personal/​ portable Rural connectivity Rural connectivity & devices surveillance

IEEE 802.15.4m

IEEE 802.19.1

Enabled for inexpensive, low-​rate WPAN systems with a low power consumption over the short distance

Allows discovery services to discover the neighbouring devices in the same band

54-​862 MHz No

54-​862 MHz No

54-​862 MHz Yes

M2M Local & Metropolitan communications, smart grid Area Network communications, and sensor networks 54-​960MHz & 2.4GHz Sub-​GHz Yes No

Yes 31.56

No 22.69

No 10-​100

No 1.5625

Yes >10

10-​30 6,7,8

10-​30 6,7,8

10

OFDM No No

OFDM Yes No

OFDM No Yes

FSK; NB-​OFDM Yes Yes

Wireless Communication: Advancements and Challenges

Main applications

IEEE 802.22 (Wi-​FAR)

newgenrtpdf

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TABLE 3.4 Comparison of TVWS Standards [31]

65

Yes Yes CSMA/​CS, TDMA

Yes Yes 2012 Yes

No Yes OFDMA with coding support from BPSK, QPSK, 16-​QAM & 64-​ QAM with configurable code rate Yes Yes 2011 Yes

Spectrum Sensing Geolocation database Approval year Quite period for sensing Inter-​System Coexistence

No

No

No

No Yes 2012 No

Yes Yes Slotted CSMA-​CA for periodic beacons; else unslotted CSMA-​CA

No Yes 2014

Yes Yes 2016 Yes Yes

newgenrtpdf

Yes Yes CSMA/​CS, TDMA

TV White Space (TVWS) Technology

Mesh Topology Self-​Coexistence Multiple Access Techniques

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Many countries are now considering the next step in the evolution of spectrum policies through this spectrum’s license-​exempt use.

3.5  REGULATIONS ON TVWS The use of under-​utilized spectrum in TV band has been gaining traction worldwide over the last decade. In the RRC GE Geneva 2006 conference, the main discussion point was the coordination on the transition from analogue to digital television and implementing a strategy to fulfil more than 70,000 broadcasting criteria in all European, African, and Asian countries. Initially, most of the initial requirements were quite inconsistent. It took six years for experts from 100 countries to decide on national proposals to submit and discuss. Finally, a joint reference plan was accepted to design the national TV plans for digital broadcasting in the frequency bands of 174-​230 MHz and 470-​862 MHz [32]. Regulation is usually a top-​down approach, being led by regulators in developed countries such as FCC in the USA, OFCOM in the UK, IMDA in Singapore and IC in Canada. Many regulators in different parts of the world have either released or are working on the framework to release the spectrum to be used by secondary users. The analogue to the digital switchover of TV transmission is still growing at a slow pace, slowing down the regulation process with many regulators. TVWS applications depend primarily on GLDB. There are still other requirements such as OOB emission, self-​positioning, and update times while TVWS networks are implemented in each country as this criterion varies for different territories. Thus, suitable regulation is necessary for TVWS deployment.

3.5.1 Regulation in the USA FCC of USA was the front runner to propose using the unlicensed band to operate in the TV spectrum at locations where these bands are not used [33]. In 2008, the Commission authorized WSD operations in VHF and UHF broadcast bands for both fixed and personal/​portable WSDs. FCC took a few more steps to promote additional opportunities to use spectrum in these bands for unlicensed WSDs in 2010, 2012, and 2015 [34]. WSDs need to obtain channels available in that vicinity and allowed Tx power to prevent interference to broadcasted TV reception and protected users at that location. This information is administered from database entities approved by the FCC. Fixed WSDs must incorporate a geolocation capability to access a database. Portable WSDs either acquire channels available via another device (Mode I), or themselves include geolocation and database access capabilities (Mode II) [33]. FCC came out with the White Spaces Order in 2015 with additional actions to promote WSDs transmission in the reassigned TV bands after the auction of broadcast TV spectrum. The Commission also authorized WSD operations in the unused 600 MHz duplex gap, and unused channel 37 [33]. To promote greater flexibility for WSDs in rural areas, FCC relaxed the EIRP from 4 watts to 10 watts in less congested areas. There was no change in the height of fixed devices antennas that was not more than 30 meters above ground and 250 meters height above average terrain (HAAT) in this order. Later, in March 2019, FCC

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adopted the White Spaces Report and Order and Order on Reconsideration, providing more flexibility and allowing fixed WSDs to operate up to 100 meters above ground in less congested areas, retaining the 250 meters HAAT limit [35]. On May 3, 2019, Microsoft requested the petition providing additional flexibility for WSDs operations: • Permit fixed devices in less congested areas to operate at higher radiated power, up to 16 Watts EIRP, to support the expansion of broadband in rural America, • Permit fixed devices to operate with higher HAAT, up to 500 meters, to improve rural coverage, • Examine the possibility of authorizing higher-​ power operations on first-​ adjacent channels to TV operations, with appropriate safeguards to prevent harmful interference, • Permit higher power mobile operations within geo-​fenced areas, and • Adjust the rules to support narrowband IoT white space devices [36]. Based on the discussion, the Commission accepted the following conditional requests [37]: • WSDs are allowed to transmit up to 16 Watt EIRP for channels 2-​35 for less congested areas. • WSDs can operate with higher HAAT of 500 meters for channels 2-​35. • It protects TV broadcasters. Commission proposed to stick to White Spaces Order in 2015 and earlier for determining the minimum co-​channel TV station contours separation distances (Table 3.5). It includes HAAT values up to 500 meters and up to a 16-​Watt EIRP level. Similarly, the proposed Table 3.6 illustrates the separation distances from adjacent channel TV station contours, as modified to include a 16-​Watt power level and HAAT values up to 500 meters. To limit the potential of harmful interference caused by the portable devices, the Commission proposed that the WSD check location every 60 seconds. If the portable device moves within 1.6 km to the device’s geofenced area, it does not have to check the channel availability at multiple locations. The proposed limitation was restricted for the movement less than 60 miles per hour. The Commission proposed to permit narrowband WSDs to limit the conducted PSD (Power Spectral Density) to 12.6 dBm/​100 kHz. This PSD is equivalent to the allowed level for fixed devices operating at the limit of 1-​Watt conducted power in a 6 MHz channel bandwidth. Narrowband devices must comply with the same maximum antenna gain regulations as fixed devices and hence the EIRP. FCC also proposed to require narrowband WSD to comply with OOB requirement of -​42.8 dBm out of 6 MHz adjacent channels.

3.5.2 Regulation in Singapore With one year of industry feedback gathering on TVWS, Singapore regulator IMDA (then IDA) finalised the framework for TVWS to accelerate commercial deployments

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TABLE 3.5 The Proposed Table for Co-​Channel TV Station Contours Separation Distances Fixed White Space Devices Antenna Required separation in kilometers from co-​channel digital or analog height TV (full service or low power) protected contour based on fixed white above space device EIRP average terrain of 20 24 32 unlicensed dBm dBm 28 dBm dBm devices 16 dBm (100 (250 (625 (1600 36 dBm 40 dBm 42 dBm (meters) (40 mV) mW) mW) mW) mW) (4 W) (10 W) (16 W) Less than 3 3–​10 10–​30 30–​50 50–​75 75–​100 100–​150 150–​200 200–​250 250–​300 300–​350 350–​400 400–​450 450–​500

1.3 2.4 4.2 5.4 6.6 7.7 9.4 10.9 12.1 13.9 15.3 16.6 17.6 18.3

1.7 3.1 5.1 6.5 7.9 9.2 11.1 12.7 14.3 16.4 17.9 19.3 20.4 21.4

2.1 3.8 6.0 7.7 9.4 10.9 13.2 15.8 18.2 20.0 21.7 23.2 24.4 25.5

2.7 4.8 7.1 9.2 11.1 12.8 16.5 19.5 22.0 23.9 25.7 27.3 28.7 30.1

3.3 6.1 8.9 11.5 13.9 17.2 21.4 24.7 27..3 29.4 31.4 33.3 35.1 36.7

4.0 7.3 11.1 14.3 18.0 21.1 25.3 28.5 31.2 35.4 37.6 39.7 41.9 43.7

4.5 8.5 13.9 19.1 23.8 27.2 32.3 36.4 39.5 42.1 44.5 46.9 49.4 51.4

5.0 9.4 15.3 20.9 26.2 30.1 35.5 39.5 42.5 45.9 48.4 51.0 53.8 55.9

and ease the demand for more spectrum. “Singapore has released its regulatory framework for TVWS to facilitate the deployment of the technology and ease demand for more bandwidth amid growing demand. Telecommunication regulators across the globe have been searching for new, efficient ways to allocate and utilise spectrum. This is essential with increasing demand for online and mobile communications”, said Dr. Yaacob Ibrahim, then Minister for Communications and Information. To encourage the adoption and deployment of TVWS, IMDA has been reviewing and gathering industry feedback since 2009 to develop the framework. Singapore White Spaces Pilot Group (SWSPG) was set up to drive commercial trials and deployments. Three projects were initiated in 2012 that involved Singapore Island Country Club (SICC), National University of Singapore (NUS), and near-​shore WiFi access to ships. The TVWS bands in 630-​742 MHz was allocated to be used for wide-​area outdoor wireless coverage, the potential for high-​speed connectivity, and superior building penetration. The white space spectrum can be in the frequency range of 470 MHz to 786 MHz. The new regulations based on the gathered feedback from industry were in effect from November 2012. The framework specified the WSD requirements, available channels for TVWS, and how this equipment should align with geolocation databases (GLDB).

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TABLE 3.6 The Proposed Table for Adjacent Channel TV Station Contours Separation Distances Fixed White Space Devices Antenna height above average terrain of unlicensed devices (meters) Less than 3 3–​10 10–​30 30–​50 50–​75 75–​100 100–​150 150–​200 200–​250 250–​300 300–​350 350–​400 400–​450 450–​500

Required separation in kilometers froth adjacent channel digital or analog TV (full service or low power) protected contour based on white space device EIRP

20 dBm (100 mW) 0.1 0.1 0.2 0.3 0.3 0.4 0.5 0.5 0.6 0.7 0.7 0.8 0.8 0.8

24 dBm 28 dBm 32 dBm (250 (625 (1600 36 dBm 40 dBm mW) mW) mW) (4 W) (10 W) 0.1 0.2 0.3 0.3 0.4 0.5 0.6 0.7 0.8 0.8 0.9 1.0 1.0 1.1

0.1 0.2 0.3 0.4 0.5 0.6 0.8 0.9 1.0 1.0 1.1 1.2 1.3 1.4

0.1 0.2 0.4 0.5 0.7 0.8 0.9 1.1 1.2 1.3 1.4 1.5 1.6 1.7

0.2 0.3 0.5 0.7 0.8 1.0 1.2 1.4 1.5 1.6 1.8 1.9 2.1 2.1

0.2 0.4 0.6 0.8 0.9 1.1 1.3 1.5 1.7 2.1 2.2 2.4 2.6 2.7

42 dBm (16 W) 0.3 0.5 0.7 1.0 1.0 1.3 1.5 1.7 1.9 2.3 2.4 2.7 2.9 2.9

Later, SWSPG carried out a commercial deployment at Gardens by the Bay (GBB), where TVWS was used as the backhaul to provide WiFi to visitors without trenching at the newly built centre of attraction. Sentosa Island in Singapore also deployed TVWS as backhaul for WiFi coverage and deployed security surveillance cameras. TVWS was used to enable video monitoring for security on the rooftop and car park compliance and view real-​time video from lift systems in HDB (Housing and Development Board) apartments. Real-​time video archives allow for video processing which allows various agencies to share the resources [38]. In October 2016, IMDA allocated VHF III spectrum of 174-​230 MHz (Channels 5-​12) after the analogue switch over (ASO) with 7 MHz bandwidth, UHF V 470 –​ 534 MHz (Channel 21-​28) and 614-​806 MHz (Channel 39-​62) with 8 MHz bandwidth. The allowed EIRP for Fixed WSD is 4 Watt (36 dBm) for Mode I WSD and Mode II WSD is 100 mWatt (20 dBm). Once 698–​806 MHz has been harmonized and allocated for the IMT (International Mobile Telecommunications) services, ten channels between 49-​62 shall be removed from the usage of TVWS. The GLDB shall block channels 25-​26 until further field tests have been conducted on adjacent channel interference. Channel 47 for microphone and channels 25 and 47 shall be

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TABLE 3.7 Available TV Channels and Frequencies for TVWS in Singapore TV Band VHF III

Frequencies /​Channel(s)

Total Bandwidth /​No. of Channels Channel Bandwidth Before ASO After ASO

174–​181 MHz (Channel 5) 7 MHz 181–​188 MHz (Channel 6) 195–​202 MHz (Channel 8) 209–​223 MHz (Channel 10 and 11) 223–​230 MHz (Channel 12) UHF V 470–​534 MHz (Channel 21 to 28) 8 MHz 614–​622 MHz (Channel 39) 622–​630 MHz (Channel 40) 630–​694 MHz (Channel 41 to 48) 694–​710 MHz (Channel 49 to 50) 718–​742 MHz (Channel 52 to 54) 750–​774 MHz (Channel 56 to 58) 790–​806 MHz (Channel 61 and 62)

21 MHz (3 channels)

42 MHz (6 channels)

168 MHz (21 channels)

144 MHz (18 channels)

blocked from TVWS operations by the GLDB [39]. Table 3.7 shows the available TVWS channels in Singapore [39]. The PSD from the WSD shall be within the specified limits, measured in any of the 100 kHz band within TV channel specified by GLDB or required by a master WSD: (i) The EIRP limit for fixed WSD is 17.5 dBm (PSD in 100 kHz) in 7 MHz band, or 17 dBm (PSD in 100 kHz) in 8 MHz band. (ii) The EIRP for mode I or mode II WSD shall not exceed 1.55 dBm (PSD in 100 kHz) in 7 MHz bands; or 0.97 dBm (PSD in 100 kHz) in 8 MHz band. Below are the requirements for Transmitter Unwanted Emission: (i) Out-​of-​band Emissions: OOB emissions limit is –​56.8 dBm for the adjacent channel with a resolution bandwidth (RBW) setting of 100 kHz. The OOB should be measured at adjacent and next to adjacent channels. (ii) Spurious Emissions: The limit for in-​band spurii emissions from WSD is –​54 dBm in the freq range of 470–​862 MHz or maximum detection of 200 μV/​m at the distance of 3 m. Spurious emissions are measured in the range of 30 MHz to 4 GHz for out of band emission [39]. Approved Database Providers by IMDA: IMDA authorized three companies for TVWS Geolocation Database licenses to provide commercial services in Singapore:

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FIGURE 3.12  Snapshot of Network Genetics GLDB (Source: Network Genetics website).

1.  Network Genetics Pte Ltd 2.  Starhub Ltd 3.  DNNA Solution Pte Ltd. Figure 3.12 illustrates the snapshot of geolocation database for TVWS.

3.5.3 Regulation in the UK The UK regulator, Ofcom launched a Digital Dividend Review in 2005 to assess the usage of TV spectrum freed up after DSO and to share it for new services and released a consultation paper on the usage of this unused spectrum in 2006. Ofcom stated that it would allow interleaved spectrum by WSDs. In the first statement published on technical parameters, WSDs will determine the availability of spectrum by sensing technique, and/​or WSDB (White Space Data Base). WSDB shall be considered as the more acceptable method [40]. Beacons technique was considered as the least appropriate and hence was not considered. Since WSDB was critical, Ofcom released more details on the WSDB parameters [41]. Ofcom classified WSDs into master and slave devices. Master WSDs gets the list of available channels in the vicinity from WSDB while slave WSDs receive required parameters from the master WSDs. The slave WSDs do not have to connect directly

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to WSDB. The master WSDs estimate their location with 95% accuracy and the boundary of slave WSDs. If the slave and master are different models, the master must report the slave model number to WSDB. The master WSDs need to access the list of available channels from Ofcom through WSDB at least once in 24 hours and frequency of query to one of the WSDBs is once in every 2 hours. Once the master WSD moves out of its authorized area, it needs to reaccess WSDB immediately. If the slave WSD does not receive a response from the master WSDs within 5 seconds, the slave WSD must stop operation. Also, the slave WSD has to stop transmission whenever the master WSDs request it [42].

3.5.4 Regulation in Canada The regulatory agency of Canada, Industry Canada (IC), published a consultation paper in 2011 on the technical framework and policy to use underutilized bands for various applications. These consultation papers were released to obtain industry feedback on launching WSDs and to use freed-​up channels. The feedback also includes the possible amendments required for rural connectivity with licensed low power wireless microphones in the same band. After receiving feedback from relevant stakeholders, IC finalized and released the framework in 2012 and proposed the operation of TVWS in Canada to be allowed [43]. Like other regulators, IC developed preliminary regulations of WSDB-​assisted WSDs. Spectrum sensing might be considered in future when sensing technique is more matured. The WSDs in Canada, especially near the USA border, will be harmonized and classified with the WSDs in the USA. However, IC will determine the technical rules for WSDs in Canada with its own established processes and based on the consultations [42].

3.5.5 Regulation in Colombia ITU recognized that there are connectivity issues in Colombia. The first issue is that providing broadband connection in rural areas is not profitable for private operators. The per capita income in those areas is meagre, and they live very far from each other. So, setting up a tower by operator does not have the return of investment. Some village schools are connected through the satellite, but this connectivity is prohibitively expensive, and most residents cannot afford it. The terrain in Colombia is very rough, most of the free spectrum bands are very congested, and licensing cost for spectrum is very high. So, TVWS is the most suited solution to solve these issues. National radio spectrum regulator (ANE), Education Ministry, ICT Ministry, Microsoft, some radio manufacturers, and a prominent internet service provider were instrumental in adopting TVWS in Colombia. In August 2017, ANE completed the publication of TVWS regulations [44]. With recent regulation, many deployments came into force, such as [44] (i) A rural municipality, Mesetas, was previously affected by the Colombian armed conflict. A small TVWS deployment was carried out in two primary schools and five coffee plantations to provide internet connectivity. This

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deployment enhanced the quality of education and promoted agriculture economic growth. (ii) The local government of Antioquia, Gobernación de Antioquia, two remotely located schools were connected with TVWS in a hilly rainforest area. The successful trial test convinced the Gobernación to use TVWS to connect around 4000 rural schools in Antioquia to improve education quality. (iii) Gobernación de Caldas (the local government of Caldas) later signed an agreement to provide connectivity to 15 public schools located in remote mountainous zones for testing purposes through TVWS. This deployment would benefit more than 1,000 primary students. ANE came up with a resolution in August 2017, recommendations following technical conditions must be fulfilled by all WSDs that operate in the Colombian territory [45:] (i) Operating Frequency WSDs may only use the 470-​698 MHz band segments that are available following that established by the ANE. (ii) Operation Mode WSDs should operate only in locations fixed in the point to point or point to multipoint modalities. The use of portable or mobile WSDs is forbidden. (iii) Maximum Power Spectral Density The power that a WSD delivers to the antenna is limited 12.6 dBm in a 100 kHz band. (iv) Maximum Antenna Gain The antenna’s gain connected to a WSD must not exceed 14 dBd. (v) Limit of Unwanted Emissions The unwanted emissions should be limited to a power of −​42.8 dBm in any 100 kHz band. (vi) Automatic Power Control WSDs shall employ automatic power control techniques to transmit their signals with the minimum power required to establish communication. (vii) Maximum Antenna Height Antenna height above the ground level of WSDs cannot exceed 50 meters. (viii) Maximum Height Above Terrain Average WSDs may operate at any geographical locations, where the average height above the ground is not more than 800 meters. (ix) Periodic Request for the List of Available Channels Master devices should periodically obtain a list of available channels to make use of the spectrum. (x) Operating Restrictions a) Operation of WSDs is prohibited in some geographical regions of the country defined by the ANE, to avoid interference to PUs. The determination of said areas will be subject to changes without prior notice from the ANE.

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b) The use of specific channels at the national level cannot avoid interference to telecommunications services operating in adjacent bands. The determination of these channels by the ANE will be subject to changes without prior notice. (xi) Availability of Spectrum There is no guarantee that once a WSD is installed, the device will always have a channel available for use. Additionally, the availability of channels is subject to change without prior notice. (xii) Interference Solution In case there is a doubt that a WSD generates interference to a primary or secondary service, the ANE may perform the relevant technical verification. In case it is determined that the said device is the cause of the interference, the ANE will order the cessation of its transmission until the user of such device presents the measures that will be used to mitigate the interference, and ANE approves these. If the originator of the interference does not present the measures used to stop the interference or does not meet those that have been proposed, the user of the device will be subject to sanctions provided for in Law 1341 of 2009. GENERAL CONDITIONS, the following conditions must also be met when the BDEB (Geolocation Database) goes into operation [45:] (i) Use of the Spectrum WSD can only connect to the BDEB designated by the ANE to make requests for available channels. The ANE will publish the internet address of the BDEB on its website in the year 2018. (ii) Geolocation Capacity Only use of white spaces that have capacity of automatic geolocation with a margin of error less than ±50 meters. (iii) Use of Multiple Channels A white space device may use more than one unused that the BDEB communicates. (iv) Start of the Communication of Slave Devices A slave device must use the same transmission channel of the device associated master to perform the initial request of available channels to the BDEB. After obtaining its list of available channels, the slave device must immediately use a channel belonging to that list in order to continue its operation. 3.5.5.1  DTT and TVWS Systems Co-​Existence In Colombia In 2018, Tatiana Giraldo and German D. Castellanos devised a methodological and technical study to avoid TVWS services’ interference to DTT. They proposed a method for establishing security parameters like the Guard Band (GB) and Protection Distance (PD) between primary and secondary services that helped the deployment of automatic schemes for co-​existence between the services and yet interference avoidance [46].

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TABLE 3.8 Client WSD Features

Client WSD Type

Internal Geolocation Capability

Direct Access to an S-​GLSD to Request & Receive Operational Parameters from S-​GLSD

Fixed WSD Fixed WSD Nomadic WSD Nomadic WSD Any

With Without With Without Without

No No No No Through Master WSD

3.5.6 Regulation in South Africa ICASA in South Africa came up with the regulation on the use of TVWS in March 2018. The key features of this regulation are [47]: 1. WSD can operate in 470 MHz to 694 MHz band, excluding 606 MHz to 614 MHz channel for Radio Astronomy. 2. Setup the conditions for the function of Geolocation Spectrum Databases (GLSDs) in the frequency band 470 MHz to 694 MHz, excluding 606 MHz to 614 MHz channel for Radio Astronomy. 3. The WSD wireless apparatus must be a Fixed WSD (intended to operate at a fixed location only) or Nomadic device (intended to operate within an allowed coverage area). 4. Categories of White Space Devices: a. A Master WSD can either be a Fixed WSD or a Nomadic WSD. Both will have internal geolocation capabilities and an internet connection to query operational parameters from a secondary GLSD (S-​GLSD). b. A Client WSD must-​have features as per Table 3.8. Figure 3.13 illustrates the TVWS regulatory framework for GLSD connectivity. ICASA also recommended using Protocol to Access White-​ Space (PAWS) approach to use the database. PAWS allows secondary users to access the available spectrum by unlocking the existing spectrum to maximize its utilization and provide innovation opportunities, resulting in greater overall spectrum utilization [48]. Below is the interpretation of requirements for PAWS messages: +​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​+​ | Message Type | +​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​+​ |Parameter: Type | Requirement | +​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​-​+​

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FIGURE 3.13  TVWS Regulatory Framework -​ICASA Ruleset for using GLSD (Source: CSIR, South Africa).

• • • •

Message Type: PAWS message of a specific type Parameter: The name of a parameter that is part of a specific message Type: A valid type as per JSON [RFC 7159] Requirement: Keyword indicating a Requirement Level as per [RFC 2119], e.g., REQUIRED, OPTIONAL [49]

The purposes of PAWS messages are depicted in Table 3.9. All WSDs must transmit Electromagnetic compatibility (EMC) and radio emissions complying with ETSI EN 301 598 standards, or successor directives with below permitted transmission level (Table 3.10). A WSD operating in the adjacent to broadcasting TV channels must have the OOB limits based on the adjacent channel leakage ratios (ACLRs) limits for the WSD emission classes as recommended in Table 3.11 complying with ETSI EN 301 598 standard, or successor directives. Figure 3.14 illustrates the wholistic view of the TVWS regulatory framework for South Africa, as per the ICASA ruleset.

3.5.7 Regulation in Ghana Regulations in Ghana are similar to South Africa. The UHF Band IV (in the range of 470 MHz to 528 MHz) and Band V (in the range of 528 MHz to 694 MHz) allocated to broadcast television services are also allowed for WSDs to use, subject

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TABLE 3.9 The Purpose of PAWS Messages Message INIT REGISTRATION AVAIL_​SPECTRUM AVAIL_​SPECTRUM_​BATCH SPECTRUM_​USE

Purpose as per RFC 7545 WSD initiate exchange of capabilities with GLSD Master WSD is required to send its registration information to the GLSD before requesting operational parameters Master WSD obtains the available spectrum (operational parameters) from GLSD, on its behalf and associated Clients Master WSD sends a notification to GLSD to indicate anticipated use of spectrum, by itself or associated Clients.

Source: ICASA, South Africa.

TABLE 3.10 Location-​Specific WSD EIRP and EIRP Spectral Density Limits [49] Location

Type of WSD

Rural Urban Rural Urban

Fixed Fixed Nomadic Nomadic

EIRP per 8MHz Channel (dBm)

EIRP per 100 kHz Channel (dBm)

41.2 36 22 22

22.2 17 1 1

TABLE 3.11 ACLR Limits Per Classes of WSD’s on the nth Adjacent TV Channel [49] WSD Out-of-Band Power Falls within the nth Adjacent TV Channel (per 8 MHz Channels) n=​+​/​-​1 n=​+​/​-​2 n≥+​3 or n≤-​3

ACLR (dB) Class 1

Class 2

Class 3

Class 4

Class 5

74 79 84

74 74 74

64 74 84

54 64 74

43 53 64

to the protection from the interference protection as outlined in the technical rules and regulations. WSDs shall use underutilized channels following the interference avoidance mechanisms. If the TVWS database indicates that the broadcast television stations use the channel, WSDs shall not operate on that region’s co-​ channel

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FIGURE 3.14  The holistic view of TVWS Regulatory Framework -​ICASA Ruleset (Source: ICASA, South Africa).

basis. Client WSDs shall follow the master channel and only operate on the channels determined by Master WSD. The radiated power limits, conducted power limits, and out of band emissions specifications are also similar to ICASA regulations.

3.5.8 Regulation in New Zealand The Radio Spectrum Management (RSM) of New Zealand created a provisional licensing scheme allowing trials of WSDs operating in the UHF band of TV spectrum. RSM released a consultation paper for TVWS in 2014 [50]. A suitable and long-​term regime shall be established after international regulations and frameworks are established. WSDs should transmit with the transmission guidelines as per either FCC Part 15, Subpart H standard [51] or the standard “ETSI EN 301 598 V1.1.1” published by ETSI [52]. The consultation paper suggested that WSDs can transmit with a limit of 10 dBW EIRP [53]. RSM recommended the WSDs signals arriving at a DTT receiver lower than -​ 106dBm for the 48dBμV/​m coverage contour. This level is calculated with the thermal noise floor for a 7.77MHz bandwidth and 6dB noise figure for DTT receivers. It also recommended conducting calculations that WSDs signal at DTT receiver should be 6dB below the noise floor anywhere within a DTT transmitter’s coverage. Besides considering ACLR from WSD and adjacent channel selectivity of DTT, the limits for unwanted emission are depicted in Table 3.13 [19].

3.5.9 Regulation in South Korea The South Korean government made unlicensed band-​ based TVWS regulatory requirements to build a TVWS database that protects incumbent services such as terrestrial DTV, licensed wireless microphone, and CATV services in 470-​698 MHz band. A notice of TVWS Rule was given in November 2016. In Korea, the TVWS

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TABLE 3.13 Specified OOB for TVWS Limits within DTV Bands (dBm/​100 kHz, EIRP) Fixed (conducted +​6dBi attenna gain) −​36.8

Personal/​portable adjacent to occupied TV channels

Other personal/​portable

−​​56.8dB

−​52.8dB

Services can be summarized by such service models like WiFi, IoT Sensor, and disaster monitoring wireless CCTV applications. It also mentions that spectrum sharing could address the scarcity of frequency resources, and increase public convenience in the coming well-​connected society. South Korea will develop and provide public services for a remote area with local government involvement, such as Internet service and wireless CCTV nationwide [54]. The main content of the TVWS policy formulation was to revise the frequency allocation and radio technical standard for introducing TVWS services and set up legal criteria: (i) Protect the current operation (ii) For efficient management and usage of the spectrum between emerging services (iii) Revision of frequency allocation table by adding a new application, for allowing WSD to use DTV spectrum band (470-​ 698 MHz) based on unlicensed usage (iv) Revision of radio technology standard to make technical requirements of TVWS wireless equipment through analysis of interference and actual measurement WS database was established to provide available channels. This database allocates appropriate Korea’s spectrum environment with: (i) Database establishment (ii) Management and operation: Public organization is under consideration TVWS technology may play a crucial role in achieving some critical strategic initiatives regarding the Asia-​Pacific Information Superhighway Master Plan for the 2019–​2022 initiative: (i) Enhancing communication and information technology infrastructure resilience; and (ii) Providing inclusive access to broadband internet. (iii) TVWS could be useful to provide underserved communications in villages and remote island with low-​cost internet access infrastructure, as illustrated in Figure 3.15 [55, 56].

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FIGURE 3.15  TVWS system architecture for broadband connectivity in South Korea (Source: www.tvws.kr/​).

Bridging the digital divide: This document examines current policy and technology approaches to bridge the digital divide in rural areas in OECD countries [57]. • Korea ranked the second-​largest internet access rate in and remote areas among all OECD countries. • Some countries are planning to use TVWS technology for the broadband program by themselves.

3.5.10 Draft Regulation in Uganda Uganda Communication Commission (UCC) came with the regulation in November 2019 that WSDs can operate in the TV broadcasting band of 470–​694 MHz in Uganda. The channel bandwidth of 8 MHz is allowed, although higher bandwidth may be achieved by channel aggregation. Database administrators and all TVWS service providers shall pay nominal fees as shall be prescribed by UCC. All WSDs devices shall operate in the freq band of 470-​694 MHz and comply with the parameters stated in Table 3.14 to ensure co-​existence with other communications services [58]. Rest all requirements are similar to ICASA requirements.

3.5.11 Draft Regulation in Nigeria In 2019, the Nigerian Communication Commission (NCC) came up with draft guidelines, in consultation with the Nigerian Broadcasting Commission (NBC) on TVWS in Nigeria. The regulations are similar to ICASA, South Africa.

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TABLE 3.14 TVWS Operational Parameters in Uganda Transmission Power (EIRP) over a Channel

Fixed WSD

Portable WSD

4 W (36 dBm)

100 mW (20 dBm)

Transmitter Unwanted Emission (EIRP)

OOB Emissions from the WSD shall be limited;

Spurious Emissions from a WSD operating in 470-​694 MHz shall be limited; –​54 dBm/100 kHz 50 m

Maximum Antennae Height Above Ground Level

−56.8 dBm/​100 kHz 50 m

3.5.12 Draft Regulation in Kenya Communication Authority of Kenya (CAK) came up with the following recommendations: • The WSDs should be type approved by CAK before installation and use. • The user takes steps to eliminate the interfering protecting radio services. Upon notification by the Commission, the user should immediately cease the transmission if it causes interference until the interference is eliminated. • The WSDs are installed and operated complying technical rules and international standards that ensure interference avoidance to any licensed devices. • The user presents the report on the project review to the Commission after the trial period’s expiry. The trial’s satisfactory performance and studies’ results will help to conclude if the trial shall be transformed to an operating license. • Figure 3.16 illustrates the setup to query the geolocation to access white spaces. • Figure 3.17 depicts an example of available TVWS in Kitui (Kenya) • CAK prefers to make simple sharing, and the overall approach for sharing is summarised in Figure 3.16. Figure 3.17 illustrates a typical diagram of TVWS Network and Figure 3.18 depicts the framework for the use of TVWS in Kenya.

3.5.13 Draft Regulation in the Philippines The Philippines regulator, ICTO promoted the deployment of wireless infrastructure to provide WiFi access in public areas. ICTO decided to utilize TVWS for wireless connectivity, in unserved and underserved areas. In utilizing TVWS, WSDs must not interfere with TV broadcasters. The White Space Database (WSDB) is needed to analyse TV channels’ availability and avoid the interference at each location. NICT developed WSDB, which satisfies the requirements from other countries around the world for technical evaluations. This WSDB keeps all the TV broadcasters information

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FIGURE 3.16  A typical diagram of TVWS Network (Source: CAK).

FIGURE 3.17  Example of available TV White Spaces in Kitui in Kenya (Source: CAK).

in the Philippines and estimates their broadcasting areas. The WSD sends the query to the WSDB with its location, the WSDB replies with the availability of channels to the WSD, and it starts transmission in TVWS [60]. Figure 3.19 illustrates the WSDB snapshot of the Philippines.

3.5.14 Draft Regulation in Brazil Brazilian regulator ANATEL allocates to the Serviço Telefônico Fixo Comutado (STFC), to the Serviço de Comunicação Multimídia (SCM) and Serviço Limitado Privado (SLP), on a secondary basis, without exclusivity, the following radio frequency bands [61] I -​54 MHz to 72 MHz band; II -​174 MHz to 216 MHz band; III -​470 MHz to 608 MHz band; IV -​614 MHz to 698 MHz band.

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TV White Space (TVWS) Technology

FIGURE 3.18  Framework for the use of TVWS [59].

FIGURE 3.19  NICT’s WSDB snapshot of the Philippines (Source: NICT website).

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Annex to the Resolution Draft (i) WSDs should be stopped at the locations, regardless of the existence of users, if new grants are issued for the provision of Serviços de Radiodifusão de Sons and Imagens e de Retransmissão de Televisão in the same blocks and the database of geolocation indicates incompatibility between transmissions. Dynamic Spectrum Alliance (DSA) believes that this is not possible to stop the transmission immediately. ANATEL’s proposal refers to using a database automatically. These databases can be updated quickly and the blocks granted may be indicated as unavailable a few days before the start of transmissions when broadcasting equipment is already installed. To guarantee the protection of the other systems that operate in this range, the WSDs should use the GLDB, responsible for identifying radio frequency blocks available in a particular location [61]. (ii) The maximum peak power of the WSDs, measured at the transmitter output, may not exceed 1-​Watt for 6 MHz channel. (iii) There are requirements regarding out-​of-​band and spurious emissions limits. There have to be some additional conditions for operating WSDs for narrowband applications, whose transmission signals occupy much less bandwidth than the used channels. There are conditions for protecting the broadcasting service, defined by the Superintendence Act responsible for administering the radio frequency spectrum. DSA published a model of “Proposed technical rules and regulations for the use of TV White Spaces” [62]. This model can be a reference to the technical operating requirements of WSDs.

3.5.15 Draft Regulation in Brunei Brunei is following the regulations from IMDA, Singapore. Table 3.15 illustrates the regulations snapshots in different countries.

3.5.16 TV Spectrum Allocation in India Prasaar Bharti holds all of the terrestrial TV broadcasting licenses for government’s national broadcaster, Doordarshan. IIT Bombay organized Cognitive Radio Systems (CRS) and TVWS seminar in 2013 to discuss how much TV white spaces are available in different parts of India and ongoing study for affordable and rural broadband coverage in India. The study results showed that a minimum of 12 out of 15 channels is always available at any place in 470-​590 MHz spectrum. The participants believed that mesh topology in the TV band would provide rural connectivity in India [63]. The Government of India (GoI) proposed creating Digital Highways through National Optical Fiber Network (NOFN) to provide connectivity up to the Gram Panchayats. ERNET India (an autonomous body under the Telecom Ministry) introduced the trials on TVWS for connectivity in remote areas at a lower cost. The research results show that unused channels can be for internet connectivity without interfering with TV transmissions [64]. Additionally, TVWS can be used for connecting in rough

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Channel Bandwidth

EIRP (dBm)

Info from DB to WSD

USA

54-​88, 174-​216, 470-​602 54–​72, 76–​88, 174–​216, 470–​608, 614–​694 181–​188, 209–​223, 502–​518, 614–​622, 630–​694 470–​550, 614–​790 470-​606, 614-​694

6 MHz

16 Watt

Available TV channels

20 min

6 MHz

4 Watt

Available TV channels

Once a day Once a day ±50m

1

7 MHz (VHF) 4 Watt 8 MHz (UHF)

Available TV channels

6 hours

6 hours

50m

2

8 MHz

4 Watt

Available TV channels

2 hours

2 hours

100m

0

8 MHz

12 Watt

GLSD to WSD with PAWS

60 seconds 24 hours

100m

1

470-​694

6 MHz

10 Watt

24 calendar 24 calendar ±50m hours hours

0

54–​72, 174–​216, 470–​ 608, 614–​694 470-​694

6 MHz

1 Watt

Request by a master device to BDEB for a list of available channels Available TV channels

1 Watt

Not specified Not defined

1

6 MHz

470-​606, 614-​694 470-​694

8 MHz 8 MHz

12 Watt 10 Watt

Not specified Not defined 60 seconds 60 seconds

100m 100m

1 0

Canada

Singapore

UK South Africa Colombia

Brazil

Available TV channels with RRA (DB Est) GLSD to WSD with PAWS Available TV channels

Not specified Not defined 24 hours 24 hours

50m

Reserve Channels for WSDs 1

0

(continued)

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South Korea Nigeria Ghana

1 hour

Location Accuracy

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Parameter/​ Country Freq. Range (MHz)

Default WSD Time Access Validity Frequency of Data

TV White Space (TVWS) Technology

TABLE 3.15 WSDB Requirements in Various Regulations

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Channel Bandwidth

EIRP (dBm)

Kenya

470–694

8 MHz

4 Watt

Uganda

470–694

8 MHz

4 Watt

New Zealand

510–​606

8 MHz

10 Watt

Info from DB to WSD Request to BSD for a list of available channels Request to UCC defined GLDB for a list of available channels Interim licencing regime is replaced by a database

Location Accuracy

24 hours

24 hours

± 50m

0

24 hours

24 hours

± 50m

0

Not defined

Not defined

Not defined

2

Reserve Channels for WSDs

Wireless Communication: Advancements and Challenges

Parameter/​ Country Freq. Range (MHz)

Default WSD Time Access Validity Frequency of Data

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TABLE 3.15  (Continued) WSDB Requirements in Various Regulations

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terrains, remote areas, and locations where fibre deployment is not feasible. It was also recommended to use this technology as backhaul to WiFi operations in Panchayats and villages. ERNET India applied for the experimental licenses for using underutilized bands to Department of Telecommunication (DOT)/​Wireless Planning & Coordination (WPC). ERNET India was launching ICT Centres for e-​Learning in schools in tribal and rural areas of Srikakulam, Andhra Pradesh. ERNET convinced WPC to use TVWS by setting up POC test-​beds for these schools. The successful PoC was carried out from July 2015 to June 2016 by connecting five schools with the 10 Mbps throughput. This PoC was identified as a viable connectivity solution beyond NOFN termination at Gram Panchayats. MeitY (Ministry of Electronics and Information Technology) formed a Working Group Committee to frame a policy to use TVWS after gaining various experimenters’ experience. ERNET obtained experimental license 60 MHz (500-​568 MHz, excluding 510-​518 MHz) from DoT. ERNET carried out a Skype video conferencing call over TVWS flawlessly in the presence of Mr Satya Nadella, the CEO of Microsoft. In March 2016, DoT allotted eight licences in the range of 470-​582 MHz to ERNET. Then Telecom Minister Mr Ravi Shankar Prasad gave a written reply in the Rajya Sabha (Upper House of Parliament) that “Government has issued eight licences for carrying out experiments at several places, using TV whitespace technology, in the frequency band 470-​582 MHz” [65]. However, DoT decided not to assign this band for the commercial deployment in June 2016. DoT also decided that white space band would not be de-​licensed and the government would work out a pricing model in the future. DoT also rejected Microsoft’s application for the grant of license for the pilot project in Harisal, leading Microsoft to pull out of this project in July 2017. The critical factor behind the DoT’s decision was that this frequency band should not be limited to TVWS only but can be used for other technologies. Furthermore, COAI suggested DoT against licensing of this band, commenting that band licensing would cause distortions in the market and cause substantial losses to the national exchequer. Moving forward, it was recommended that the government should organize a stakeholder consultation to discuss its current position on licenses for the commercial deployment of TVWS. The regulator will boost rural access to the internet in India by doing so. While the absence of regulation on TVWS is a challenge, DoT can draw upon the countries’ best practices, including USA, UK, Singapore and South Africa where TVWS is currently being deployed.

3.5.17 Draft Regulation in Pakistan The telecom sector in Pakistan started de-​regulation in the year 2003. Government of Pakistan (GOP) issued Telecom Policy 2015 to use joint spectrum, effectively, and efficiently. The purpose of the Telecom Policy 2015 concerning spectrum was “Allocation and assignment of spectrum to maximise social and economic benefits derived from the use of this scarce resource” [66]. As per Telecom Policy 2015, the Spectrum Sharing Framework is to carry out sharing of the spectrum to eligible users. This framework is developed for sharing

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conditions, sharing types, best use of spectrum, and interference avoidance caused by spectrum sharing with the following considerations: (i) The spectrum can be shared among licensees for similar or different service(s) for a specific period or the license’s remaining term. (ii) The spectrum can be shared only to the licensees who declare the application for the shared spectrum. (iii) The spectrum assigned to licensees shall be shared only when the Federal Government’s Ministry of IT (MoIT) authorizes the sharing explicitly for people’s benefit. (iv) There can be three types of Spectrum Sharing: a. Equal Rights, where all the licensees will have the same rights of spectrum usage b. Primary Users (PU) shall have higher rights on the usage of spectrum. PU will be protected against potential interference c. The secondary user (SU) will be authorized to share the spectrum avoiding potential interference or deteriorates the QoS to the PUs (v) If all sharing licenses follow the necessary framework terms and conditions, a license holder can share the assigned spectrum with other license-​holders. The agreement shall be in place with: a. Interested licensee’s CEO or his/​her authorized person will apply to PTA, seeking permission for the spectrum sharing. b. The spectrum can fully or partially be shared among licensees. (vi) Sharing Terms and Prices can be negotiated between the concerned users, as long as they comply with regulations. (vii) The admin fees for license sharing will be Rs. 100,000 [66].

3.5.18 Draft Regulation in Australia The ACMA has been following the development of TVWS technology and regulatory arrangements for some time. ACMA surveyed the approaches used in eight regulatory bodies worldwide to identify the best spectrum management practice. ACMA selected examples from the regulators already implementing market-​based, well-​established techniques for sharing the spectrum, facilitated by technical coordination techniques. They implemented sharing mechanisms, licensed shared access (LSA) for TVWS. Specialized coordination mechanisms used in sharing consist of dynamic spectrum access (DSA), using GLDB to keep track of users, avoid spectrum usage in specific locations and frequencies to protect existing users from interference. The tiered spectrum access approach was recommended, in which premium users can offer priority rights for spectrum usage. While ACMA had conducted tests and trials of TVWS technology in Australia, there has not been any interest expressed in commercial deployments yet. As a result, ACMA has not formally considered or consulted about developing regulatory arrangements to support TVWS devices in Australia. However, a trial or demonstration of TVWS in the 520-​694 MHz frequency range used for digital terrestrial television in Australia is possible under existing regulatory arrangements. While the ACMA is required to prioritize planned broadcasting

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services in that band, it is possible to make a spectrum not required for planned broadcasting services available for other purposes such as the fixed and mobile services. Some of the considerations ACMA might consider are: (i) User requirements such as wireless connectivity around the home, create personal and local area network and support IoT applications. (ii) Competitive environment: The network typically provides wireless connectivity in a local area and should not compete with Telcos instead of complementing their coverage. (iii) Regulatory development environment: The GLDB approach shall minimize the efforts needed to manage the sharing of spectrum. GLDB helps to make the sharing ecosystem more flexible and ‘lightly licensed’. (iv) Band characteristics: TVWS trials have mostly used UHF spectrum below 694 MHz, allocated to the primary users (e.g. the USA, the UK and Singapore) and is not allocated for primary mobile use [67]. ACMA suggested the suitability of TVWS on spectrum sharing in Table 3.16. Figure 3.20 depicts the status of regulation and trials in different countries worldwide. The green colour indicates the regulation ready countries such as USA, Canada, Colombia, UK, Ghana, Singapore and South Korea. The orange colour illustrates the countries with draft regulations. The countries in yellow show the completed trials and pilots, whereas countries in blue show interest. Figure 3.21 illustrates the TVWS technology has captured a significant market since its inception. It has got interests from the countries covering 3.17 billion population with 41% of the world population.

3.6  THE LIMITATIONS OF TVWS REGULATION Generally, more frequent WSDB or GLDB access makes the spectrum utilization more efficient. However, more frequent access makes the system more complex and hence there is a trade-​off between efficiency and complexity. In future, the frequency of accessing the spectrum opportunistically and dynamically might increase. So far, it has been realized that there have been many limitations despite regulations happening in many countries. The first limitation is that the adoption of FCC’s TVWS regulations is too stringent and undesirable. TVWS is one of the most suitable technologies for providing broadband access to billions of people in developing countries. So, this technology should be a welcome opportunity in these countries. Thus, there have to be alternative design options to promote network adaptability and flexibility, such as: (i) Boosting the TVWS GLDB with spectrum sensing techniques to create a more accurate map for channels available in the vicinity, (ii) Relaxing the spectrum mask criterion in the sparsely used spectrum, and

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Priority Issue

TV White Space

CBRS/​Tiered Sharing

5G

Might suit where density of deployment is low (e.g. rural)

Might suit, subject to QoS and licence tenure

Incentive Auctions Might suit for re-​allocation of sub-​694MHz (if allocated to mobile)

Spectrum Parks Might be suitable for test and development /​trials

Might be suitable in some bands (2.7–​3.1GHz?)

Good

Might suit for some solutions (e.g. small cells in smart cities)

Not likely to be relevant

DSA

Good

Good

Not likely to be relevant

Might enable interference coordination by licensees

Some LSA implementations might feature DSA

Suitable for some bands (VHF?)

Might be suitable in some bands

Suitable to repurpose use from one service to another

Might be suitable for test and development/​trials

Might be suitable in some bands (2.7–​3.1GHz?)

Key

Low suitability

Source: Analysys Mason, 2017.

High suitability

Not suitable

Wireless Communication: Advancements and Challenges

IoT

To facilitate new uses in bands under review (VHF, 2.7–​ 3.1, 3.5–​3.7GHz)

Might encourage test and development/​ trials

LSA

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TABLE 3.16 Suitability of Various Approaches to Achieve Selected Priorities in Australia

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FIGURE 3.20  Status of TVWS regulations & trials worldwide.

FIGURE 3.21  Growth of TVWS adopting countries.

(iii) Allowing flexibility in the choice of spectrum masks and other operation parameters, so that a diverse and vibrant TVWS ecosystem can be promoted while protecting the primary licensed user.

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Wireless Communication: Advancements and Challenges

In summary, perhaps due to being pioneers in crafting TVWS regulations, the regulators have been rigid and conservative. As a result, the desired balance between providing adequate interference protection to the primary user and effective advancement of secondary users is not achieved. This imbalance resulted in an unmatured TVWS ecosystem to take off, let alone thrive, like WiFi [68].

3.7  COMMERCIAL PILOTS AND TRIALS OF TVWS For more than five years, many organizations have been working with government organizations for viability and potential of TVWS, mainly led by Microsoft in opening up the gates. This technology’s viability is established in over tens of commercial deployments and trials worldwide, stretching from villages of Africa to the dense urban centres of the USA, UK and Asia [69].

3.7.1 Botswana Pilot Project (March 2015) In collaboration with Microsoft Corporation, the Botswana-​ UPenn Partnership (BUP), Botswana Innovation Hub has launched a TVWS pilot project. The project, Project Kgolagano (to be connected or networked), will provide telemedicine services and internet connectivity to local clinics and hospitals, which will enable access to specialized medicine in Gaborone and nearby locations.

3.7.2 Ghana Commercial Pilot (May 2014) SpectraLink Wireless project provided low-​ cost wireless connectivity to faculty and students at university in Koforidua, Ghana, and a joint research initiative with Facebook. The pilot was part of Microsoft’s 4Afrika Initiative to improve Africa’s competitiveness globally.

3.7.3 Namibia Trial (August 2014) MyDigitalBridge Foundation has successfully trialled the Namibian TVWS pilot project. The intention was to provide a blueprint of broadband internet connectivity for the whole country. This ‘Citizen Connect’, the pilot project consists of a network deployed to cover the area of 62 km × 152 km (9,424 km²). This was the biggest TVWS project of its kind in terms of area coverage.

3.7.4 The Philippines (July 2013) DOST-​ICT Office and the private sector were looking to provide the connectivity in rural areas with TVWS technology to connect rural areas in Bohol and Leyte. The initial plan was to use TVWS as backhaul connectivity for public service, eGovernment services, eHealth, education, environmental sensor networks for NOAH project, and internet access in public areas, such as town plazas and barangay halls.

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3.7.5 India Pilot Trials (Nov 2015) Microsoft proposed to use TVWS to provide internet access to 500,000 Indian villages at low-​cost in 2015 and was allowed to carry out pilots in Harisal (Maharashtra), Srikakulam (Telangana) and Varanasi (UP). DoT allocated eight licences in the 470-​ 582 MHz band in March 2016 to ERNET India, BHEL, IIT Bombay, IIT Hyderabad, IIIT Bangalore, IIT Delhi, Tata Advanced Systems, and Amrawati to carry out the experiments in TVWS technology [70].

3.7.6 South Africa Commercial Pilot (July 2013) Microsoft Corporation launched a pilot project in the rural area of Limpopo in July 2013. This project aims to use TVWS to deliver high-​speed and affordable broadband to underserved communities in South Africa by 2020. The pilot was a joint effort between the Council for Scientific and Industrial Research (CSIR), the University of Limpopo, Microsoft, and Multisource. Its trial used TVWS to provide wireless connectivity to five secondary schools in Limpopo province’s underserved parts at low cost.

3.7.7 Tanzania Commercial Pilot (May 2013) In May 2013, Microsoft Corporation announced another pilot in Dar es Salaam at the World Economic Forum on Africa. Microsoft partnered with the Tanzania Commission for Science and Technology (COSTECH) and ISP UhuruOne to offer affordable connectivity to university faculty and students using TVWS as backhaul. Students and faculty were able to access the Windows 8 device and service packages through the pilot. The initial deployment was targeted for the university and some other universities through this pilot.

3.7.8 Kenya “Mawingu” Commercial Pilot (February 2013) Microsoft Corporation, in collaboration with Indigo Telecom Ltd and Ministry of Information and Communications in Kenya, launched a pilot project to deliver connectivity to unserved locations near Kalema and Nanyuki in Kenya in February 2013 at low-​cost. The network utilizes TVWS and solar-​powered base stations to connect to various applications such as education, healthcare, commerce, and government services delivery. This pilot helped improve Africa’s competitiveness globally and was part of Microsoft’s 4Afrika Initiative to connect the masses and empower African entrepreneurs, students, developers and others to become digitally active citizens.

3.7.9 Singapore Commercial Pilot (April 2012) With the Infocomm Development Authority (IDA) support, Singapore White Spaces Pilot Group (SWSPG) was established in April 2012. This group’s objective was to deploy TVWS technology pilots in Singapore, accelerating TVWS technology adoption globally. This group was expanded to 18 members in 2013. Initially, the

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group focused on three projects. It was extended to five later, demonstrating the variety of commercial services that could be deployed in a terrain where traditional wireless deployment would be challenging to connect: • National University of Singapore (NUS): The third commercial deployment was a collaboration between Institute for Infocomm Research (I2R) and Power Automation (PA) to allow the NUS students in U-​town to measure the usage of air conditioners in the rooms and charge students staying in hostel according to their usage. • Gardens by the Bay: TVWS was used as the backhaul to provide WiFi connectivity to the visitors in a cost-​efficient and reliable manner in this newly built iconic attraction. Three different sites at this garden (Canopy, Meadow, and Supertree Grove) offer free WiFi connectivity to all visitors. • Sentosa: Merlion complex, Belawang Beach, and Siloso Beach, in Sentosa implemented a trial to deploy security surveillance cameras while exhibiting the co-​existence of multiple TVWS vendors in a single location. • Singapore Island Country Club: The country club used this technology to connect with deployed smart sensors, which help owners track golf buggies and monitor the golf course’s moisture. • Changi district near the airport: Initially, vessels near the port rely on satellite communication to access the internet, voice, and emails. This mode of communication is expensive and subject to latency depending on weather conditions. TVWS provides a cheaper and more reliable alternative. • Housing & Development Board (HDB): This pilot project was deployed for surveillance in car park enforcement, rooftop security, and receiving real-​time video from the lifts in HDB buildings, enhancing safety and security for the residents. • Eurokars Group: Singapore’s premium car dealer used TVWS to extend its network to several far-​flung buildings cost-​effectively. This was also with unique concierge services such as customer scheduled service management and test-​ drive vehicle tracking.

3.7.10 Cambridge White Spaces Trial (June 2011) Cambridge TVWS trial was designed to evaluate the technical capabilities of this technology and potential end-​user applications. The consortium explored and measured applications, such as urban pop-​up coverage, rural wireless broadband, and the emerging m2m communication. It was established that TVWS could be developed successfully to satisfy the rapidly growing demand for wireless connectivity.

3.7.11 Claudville, Virginia (September 2009) Microsoft Corporation was involved in the first US deployment of TVWS in Claudville, Virginia. The TVWS trial offers a model by which the government might

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better utilize scarce spectrum resources and an alternate broadband network to deliver pervasive mobile broadband.

3.8  APPLICATIONS AND USE CASES OF TVWS The excellent propagation and coverage characteristics of the TVWS band are the most attractive parts to the major stakeholders. Not only 3.8 billion people need connectivity, but connectivity is needed for broadband connectivity of devices such as cameras, backhaul for WiFi routers, moving devices etc. TVWS is also needed for the narrowband connectivity of many devices such as agriculture sensors, precision sensors, smart building sensors, smart meters, smart grid, smart city sensors, lift sensors or solar panels. The broad applications for TVWS can be classified into broadband connectivity and narrowband (IoT) connectivity: A. Broadband connectivity (i) Bridging Digital divide Nowadays, people cannot live without internet access. To provide WiFi in buildings is not difficult. However, setting up WiFi in outdoor areas is challenging due to the high cost of cabling and the requirement of many regulatory approvals. Aside from costing only a fraction (