Unmanned Aerial Vehicles for Internet of Things (IoT) Concepts, Techniques, and Applications

This comprehensive book deeply discusses the theoretical and technical issues of unmanned aerial vehicles for deployment by industries and civil authorities in Internet of Things (IoT) systems.

Unmanned aerial vehicles (UAVs) has become one of the rapidly growing areas of technology, with widespread applications covering various domains. UAVs play a very important role in delivering Internet of Things (IoT) services in small and low-power devices such as sensors, cameras, GPS receivers, etc. These devices are energy-constrained and are unable to communicate over long distances. The UAVs work dynamically for IoT applications in which they collect data and transmit it to other devices that are out of communication range. Furthermore, the benefits of the UAV include deployment at remote locations, the ability to carry flexible payloads, reprogrammability during tasks, and the ability to sense for anything from anywhere. Using IoT technologies, a UAV may be observed as a terminal device connected with the ubiquitous network, where many other UAVs are communicating, navigating, controlling, and surveilling in real time and beyond line-of-sight.

The aim of the 15 chapters in this book help to realize the full potential of UAVs for the IoT by addressing its numerous concepts, issues and challenges, and develops conceptual and technological solutions for handling them. Applications include such fields as disaster management, structural inspection, goods delivery, transportation, localization, mapping, pollution and radiation monitoring, search and rescue, farming, etc. In addition, the book covers:

• Efficient energy management systems in UAV-based IoT networks
• IoE enabled UAVs
• Mind-controlled UAV using Brain-Computer Interface (BCI)
• The importance of AI in realizing autonomous and intelligent flying IoT
• Blockchain-based solutions for various security issues in UAV-enabled IoT
• The challenges and threats of UAVs such as hijacking, privacy, cyber-security, and physical safety.

Audience: Researchers in computer science, Internet of Things (IoT), electronics engineering, as well as industries that use and deploy drones and other unmanned aerial vehicles.

Vandana Mohindru PhD is an Assistant Professor in the Department of Computer Science and Engineering, Chandigarh Group of Colleges, Mohali, Punjab, India. Her research interest are in the areas of Internet of Things, Wireless Sensor Networks, Security, Blockchain and Cryptography, Unmanned Aerial Vehicles. She has published more than 20 technical research papers in leading journals and conferences.

Yashwant Singh PhD is an Associate Professor & Head in the Department of Computer Science & Information Technology at the Central University of Jammu. His research interests lie in the area of Internet of Things, Wireless Sensor Networks, Unmanned Aerial Vehicles, Cyber Security. He has published more than 70 research articles in the International Journals and Conferences.

Ravindara Bhatt PhD is an Assistant Professor at Jaypee University of Information Technology, Solan, H.P., India. He has over 20 years of experience in Academics and Industry in India. He has published more than 30 research papers in leading journals and conferences. His areas of research include Sensor networks: Deployment modeling, communication, and energy-efficient algorithms, Security and Unmanned Aerial Vehicles.

Anuj Kumar Gupta PhD is Professor & Head in CSE at Chandigarh Group of Colleges, Mohali, Punjab, India. He has published 100+ research papers in reputed journals.

Preface xvii

1 Unmanned Aerial Vehicle (UAV): A Comprehensive Survey 1
Rohit Chaurasia and Vandana Mohindru

1.1 Introduction 2

1.2 Related Work 2

1.3 UAV Technology 3

1.3.1 UAV Platforms 3

1.3.1.1 Fixed-Wing Drones 3

1.3.1.2 Multi-Rotor Drones 4

1.3.1.3 Single-Rotor Drones 5

1.3.1.4 Fixed-Wing Hybrid VTOL 6

1.3.2 Categories of the Military Drones 6

1.3.3 How Drones Work 8

1.3.3.1 Firmware—Platform Construction and Design 9

1.3.4 Comparison of Various Technologies 10

1.3.4.1 Drone Types & Sizes 10

1.3.4.2 Radar Positioning and Return to Home 10

1.3.4.3 GNSS on Ground Control Station 11

1.3.4.4 Collision Avoidance Technology and Obstacle Detection 11

1.3.4.5 Gyroscopic Stabilization, Flight Controllers and IMU 12

1.3.4.6 UAV Drone Propulsion System 12

1.3.4.7 Flight Parameters Through Telemetry 13

1.3.4.8 Drone Security & Hacking 13

1.3.4.9 3D Maps and Models With Drone Sensors 13

1.3.5 UAV Communication Network 15

1.3.5.1 Classification on the Basis of Spectrum Perspective 15

1.3.5.2 Various Types of Radio communication Links 16

1.3.5.3 VLOS (Visual Line-of-Sight) and BLOS (Beyond Line-of-Sight) Communication in Unmanned Aircraft System 18

1.3.5.4 Frequency Bands for the Operation of UAS 19

1.3.5.5 Cellular Technology for UAS Operation 19

1.4 Application of UAV 21

1.4.1 In Military 21

1.4.2 In Geomorphological Mapping and Other Similar Sectors 22

1.4.3 In Agriculture 22

1.5 UAV Challenges 23

1.6 Conclusion and Future Scope 24

References 24

2 Unmanned Aerial Vehicles: State-of-the-Art, Challenges and Future Scope 29
Jolly Parikh and Anuradha Basu

2.1 Introduction 30

2.2 Technical Challenges 30

2.2.1 Variations in Channel Characteristics 32

2.2.2 UAV-Assisted Cellular Network Planning and Provisioning 33

2.2.3 Millimeter Wave Cellular Connected UAVs 34

2.2.4 Deployment of UAV 35

2.2.5 Trajectory Optimization 36

2.2.6 On-Board Energy 37

2.3 Conclusion 37

References 37

3 Battery and Energy Management in UAV-Based Networks 43
Santosh Kumar, Amol Vasudeva and Manu Sood

3.1 Introduction 43

3.2 The Need for Energy Management in UAV-Based Communication Networks 45

3.2.1 Unpredictable Trajectories of UAVs in Cellular UAV Networks 46

3.2.2 Non-Homogeneous Power Consumption 47

3.2.3 High Bandwidth Requirement/Low Spectrum Availability/Spectrum Scarcity 47

3.2.4 Short-Range Line-of-Sight Communication 48

3.2.5 Time Constraint (Time-Limited Spectrum Access) 48

3.2.6 Energy Constraint 49

3.2.7 The Joint Design for the Sensor Nodes’ Wake-Up Schedule and the UAV’s Trajectory (Data Collection) 49

3.3 Efficient Battery and Energy Management Proposed Techniques in Literature 50

3.3.1 Cognitive Radio (CR)-Based UAV Communication to Solve Spectrum Congestion 51

3.3.2 Compressed Sensing 52

3.3.3 Power Allocation and Position Optimization 53

3.3.4 Non-Orthogonal Multiple Access (NOMA) 53

3.3.5 Wireless Charging/Power Transfer (WPT) 54

3.3.6 UAV Trajectory Design Using a Reinforcement Learning Framework in a Decentralized Manner 55

3.3.7 Efficient Deployment and Movement of UAVs 55

3.3.8 3D Position Optimization Mixed With Resource Allocation to Overcome Spectrum Scarcity and Limited Energy Constraint 56

3.3.9 UAV-Enabled WSN: Energy-Efficient Data Collection 57

3.3.10 Trust Management 57

3.3.11 Self-Organization-Based Clustering 58

3.3.12 Bandwidth/Spectrum-Sharing Between UAVs 59

3.3.13 Using Millimeter Wave With SWIPT 59

3.3.14 Energy Harvesting 60

3.4 Conclusion 61

References 67

4 Energy Efficient Communication Methods for Unmanned Ariel Vehicles (UAVs): Last Five Years’ Study 73
Nagesh Kumar

4.1 Introduction 73

4.1.1 Introduction to UAV 74

4.1.2 Communication in UAV 75

4.2 Literature Survey Process 77

4.2.1 Research Questions 77

4.2.2 Information Source 77

4.3 Routing in UAV 78

4.3.1 Communication Methods in UAV 78

4.3.1.1 Single-Hop Communication 79

4.3.1.2 Multi-Hop Communication 80

4.4 Challenges and Issues 82

4.4.1 Energy Consumption 82

4.4.2 Mobility of Devices 82

4.4.3 Density of UAVs 82

4.4.4 Changes in Topology 85

4.4.5 Propagation Models 85

4.4.6 Security in Routing 85

4.5 Conclusion 85

References 86

5 A Review on Challenges and Threats to Unmanned Aerial Vehicles (UAVs) 89
Shaik Johny Basha and Jagan Mohan Reddy Danda

5.1 Introduction 89

5.2 Applications of UAVs and Their Market Opportunity 90

5.2.1 Applications 90

5.2.2 Market Opportunity 92

5.3 Attacks and Solutions to Unmanned Aerial Vehicles (UAVs) 92

5.3.1 Confidentiality Attacks 93

5.3.2 Integrity Attacks 95

5.3.3 Availability Attacks 96

5.3.4 Authenticity Attacks 97

5.4 Research Challenges 99

5.4.1 Security Concerns 99

5.4.2 Safety Concerns 99

5.4.3 Privacy Concerns 100

5.4.4 Scalability Issues 100

5.4.5 Limited Resources 100

5.5 Conclusion 101

References 101

6 Internet of Things and UAV: An Interoperability Perspective 105
Bharti Rana and Yashwant Singh

6.1 Introduction 106

6.2 Background 108

6.2.1 Issues, Controversies, and Problems 109

6.3 Internet of Things (IoT) and UAV 110

6.4 Applications of UAV-Enabled IoT 113

6.5 Research Issues in UAV-Enabled IoT 114

6.6 High-Level UAV-Based IoT Architecture 117

6.6.1 UAV Overview 117

6.6.2 Enabling IoT Scalability 119

6.6.3 Enabling IoT Intelligence 120

6.6.4 Enabling Diverse IoT Applications 121

6.7 Interoperability Issues in UAV-Based IoT 121

6.8 Conclusion 123

References 124

7 Practices of Unmanned Aerial Vehicle (UAV) for Security Intelligence 129
Swarnjeet Kaur, Kulwant Singh and Amanpreet Singh

7.1 Introduction 130

7.2 Military 132

7.3 Attack 133

7.4 Journalism 134

7.5 Search and Rescue 136

7.6 Disaster Relief 138

7.7 Conclusion 139

References 139

8 Blockchain-Based Solutions for Various Security Issues in UAV-Enabled IoT 143
Madhuri S. Wakode and Rajesh B. Ingle

8.1 Introduction 144

8.1.1 Organization of the Work 145

8.2 Introduction to UAV and IoT 145

8.2.1 UAV 145

8.2.2 IoT 146

8.2.3 UAV-Enabled IoT 147

8.2.4 Blockchain 150

8.3 Security and Privacy Issues in UAV-Enabled IoT 151

8.4 Blockchain-Based Solutions to Various Security Issues 153

8.5 Research Directions 154

8.6 Conclusion 154

8.7 Future Work 155

References 155

9 Efficient Energy Management Systems in UAV-Based IoT Networks 159
V. Mounika Reddy, Neelima K. and G. Naresh

9.1 Introduction 160

9.2 Energy Harvesting Methods 161

9.2.1 Basic Energy Harvesting Mechanisms 162

9.2.2 Markov Decision Process-Based Energy Harvesting Mechanisms 163

9.2.3 mm Wave Energy Harvesting Mechanism 164

9.2.4 Full Duplex Wireless Energy Harvesting Mechanism 165

9.3 Energy Recharge Methods 165

9.4 Efficient Energy Utilization Methods 166

9.4.1 GLRM Method 166

9.4.2 DRL Mechanism 167

9.4.3 Onboard Double Q-Learning Mechanism 168

9.4.4 Collision-Free Scheduling Mechanism 168

9.5 Conclusion 170

References 170

10 A Survey on IoE-Enabled Unmanned Aerial Vehicles 173
K. Siddharthraju, R. Dhivyadevi, M. Supriya, B. Jaishankar and Shanmugaraja T.

10.1 Introduction 174

10.2 Overview of Internet of Everything 176

10.2.1 Emergence of IoE 176

10.2.2 Expectation of IoE 177

10.2.2.1 Scalability 177

10.2.2.2 Intelligence 178

10.2.2.3 Diversity 178

10.2.3 Possible Technologies 179

10.2.3.1 Enabling Scalability 179

10.2.3.2 Enabling Intelligence 180

10.2.3.3 Enabling Diversity 180

10.2.4 Challenges of IoE 181

10.2.4.1 Coverage Constraint 181

10.2.4.2 Battery Constraint 181

10.2.4.3 Computing Constraint 181

10.2.4.4 Security Constraint 182

10.3 Overview of Unmanned Aerial Vehicle (UAV) 182

10.3.1 Unmanned Aircraft System (UAS) 183

10.3.2 UAV Communication Networks 183

10.3.2.1 Ad Hoc Multi-UAV Networks 183

10.3.2.2 UAV-Aided Communication Networks 184

10.4 UAV and IoE Integration 184

10.4.1 Possibilities to Carry UAVs 184

10.4.1.1 Widespread Connectivity 185

10.4.1.2 Environmentally Aware 185

10.4.1.3 Peer-Maintenance of Communications 185

10.4.1.4 Detector Control and Reusing 185

10.4.2 UAV-Enabled IoE 186

10.4.3 Vehicle Detection Enabled IoE Optimization 186

10.4.3.1 Weak-Connected Locations 186

10.4.3.2 Regions with Low Network Support 186

10.5 Open Research Issues 187

10.6 Discussion 187

10.6.1 Resource Allocation 187

10.6.2 Universal Standard Design 188

10.6.3 Security Mechanism 188

10.7 Conclusion 189

References 189

11 Role of AI and Big Data Analytics in UAV-Enabled IoT Applications for Smart Cities 193
Madhuri S. Wakode

11.1 Introduction 194

11.1.1 Related Work 195

11.1.2 Contributions 195

11.1.3 Organization of the Work 195

11.2 Overview of UAV-Enabled IoT Systems 196

11.2.1 UAV-Enabled IoT Systems for Smart Cities 197

11.3 Overview of Big Data Analytics 197

11.4 Big Data Analytics Requirements in UAV-Enabled IoT Systems 198

11.4.1 Big Data Analytics in UAV-Enabled IoT Applications 199

11.4.2 Big Data Analytics for Governance of UAV-Enabled IoT Systems 201

11.5 Challenges 202

11.6 Conclusion 202

11.7 Future Work 203

References 203

12 Design and Development of Modular and Multifunctional UAV with Amphibious Landing, Processing and Surround Sense Module 207
Lakshit Kohli, Manglesh Saurabh, Ishaan Bhatia, Nidhi Sindhwani and Manjula Vijh

12.1 Introduction 208

12.2 Existing System 208

12.3 Proposed System 210

12.4 IoT Sensors and Architecture 212

12.4.1 Sensors and Theory 212

12.4.2 Architectures Available 213

12.4.2.1 3-Layer IoT Architecture 213

12.4.2.2 5-Layer IoT Architecture 214

12.4.2.3 Architecture & Supporting Modules 215

12.4.2.4 Integration Approach 215

12.4.2.5 System of Modules 216

12.5 Advantages of the Proposed System 217

12.6 Design 218

12.6.1 System Design 219

12.6.2 Auto-Leveling 219

12.6.3 Amphibious Landing Module 221

12.6.4 Processing Module 223

12.6.5 Surround Sense Module 223

12.7 Results 224

12.8 Conclusion 227

12.9 Future Scope 228

References 228

13 Mind Controlled Unmanned Aerial Vehicle (UAV) Using Brain–Computer Interface (BCI) 231
Prasath M.S., Naveen R. and Sivaraj G.

13.1 Introduction 232

13.1.1 Classification of UAVs 232

13.1.2 Drone Controlling 232

13.2 Mind-Controlled UAV With BCI Technology 233

13.3 Layout and Architecture of BCI Technology 234

13.4 Hardware Components 235

13.4.1 Neurosky Mindwave Headset 235

13.4.2 Microcontroller Board—Arduino 236

13.4.3 A Computer 237

13.4.4 Drone for Quadcopter 238

13.5 Software Components 239

13.5.1 Processing P3 Software 239

13.5.2 Arduino IDE Software 240

13.5.3 ThinkGear Connector 240

13.6 Hardware and Software Integration 241

13.7 Conclusion 243

References 244

14 Precision Agriculture With Technologies for Smart Farming Towards Agriculture 5.0 247
Dhirendra Siddharth, Dilip Kumar Saini and Ajay Kumar

14.1 Introduction 247

14.2 Drone Technology as an Instrument for Increasing Farm Productivity 248

14.3 Mapping and Tracking of Rice Farm Areas With Information and Communication Technology (ICT) and Remote Sensing Technology 249

14.3.1 Methodology and Development of ICT 250

14.4 Strong Intelligence From UAV to the Agricultural Sector 252

14.4.1 Latest Agricultural Drone History 252

14.4.2 The Challenges 254

14.4.3 SAP’s Next Wave of Drone Technologies 254

14.4.4 SAP Connected Agriculture 256

14.4.5 Cases of Real-World Use 257

14.4.5.1 Crop Surveying 257

14.4.5.2 Capture the Plantation 258

14.4.5.3 Image Processing 258

14.4.5.4 Working to Create GeoTiles and an Image Pyramid 259

14.5 Drones-Based Sensor Platforms 260

14.5.1 Context and Challenges 260

14.5.2 Stakeholder and End Consumer Benefits 261

14.5.3 The Technology 262

14.5.3.1 Provisions of the Unmanned Aerial Vehicles 262

14.6 Jobs of Space Technology in Crop Insurance 263

14.7 The Institutionalization of Drone Imaging Technologies in Agriculture for Disaster Managing Risk 267

14.7.1 A Modern Working 267

14.7.2 Discovering Drone Mapping Technology 268

14.7.3 From Lowland to Uplands, Drone Mapping Technology 269

14.7.4 Institutionalization of Drone Monitoring Systems and Farming Capability 269

14.8 Usage of Internet of Things in Agriculture and Use of Unmanned Aerial Vehicles 270

14.8.1 System and Application Based on UAV-WSN 270

14.8.2 Using a Complex Comprehensive System 271

14.8.3 Benefits Assessment of Conventional System and the UAV-Based System 271

14.8.3.1 Merit 272

14.8.3.2 Saving Expenses 272

14.8.3.3 Traditional Agriculture 273

14.8.3.4 UAV-WSN System-Based Agriculture 273

14.9 Conclusion 273

References 273

15 IoT-Based UAV Platform Revolutionized in Smart Healthcare 277
Umesh Kumar Gera, Dilip Kumar Saini, Preeti Singh and Dhirendra Siddharth

15.1 Introduction 278

15.2 IoT-Based UAV Platform for Emergency Services 279

15.3 Healthcare Internet of Things: Technologies, Advantages 281

15.3.1 Advantage 281

15.3.1.1 Concurrent Surveillance and Tracking 281

15.3.1.2 From End-To-End Networking and Availability 282

15.3.1.3 Information and Review Assortment 282

15.3.1.4 Warnings and Recording 282

15.3.1.5 Wellbeing Remote Assistance 283

15.3.1.6 Research 283

15.3.2 Complications 283

15.3.2.1 Privacy and Data Security 283

15.3.2.2 Integration: Various Protocols and Services 284

15.3.2.3 Overload and Accuracy of Data 284

15.3.2.4 Expenditure 284

15.4 Healthcare’s IoT Applications: Surgical and Medical Applications of Drones 285

15.4.1 Hearables 285

15.4.2 Ingestible Sensors 285

15.4.3 Moodables 285

15.4.4 Technology of Computer Vision 286

15.4.5 Charting for Healthcare 286

15.5 Drones That Will Revolutionize Healthcare 286

15.5.1 Integrated Enhancement in Efficiency 286

15.5.2 Offering Personalized Healthcare 287

15.5.3 The Big Data Manipulation 287

15.5.4 Safety and Privacy Optimization 287

15.5.5 Enabling M2M Communication 288

15.6 Healthcare Revolutionizing Drones 288

15.6.1 Google Drones 288

15.6.2 Healthcare Integrated Rescue Operations (HiRO) 289

15.6.3 EHang 289

15.6.4 TU Delft 289

15.6.5 Project Wing 289

15.6.6 Flirtey 289

15.6.7 Seattle’s VillageReach 290

15.6.8 ZipLine 290

15.7 Conclusion 290

References 290

Index 295

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