Preface xvii 1 Unmanned Aerial Vehicle (UAV): A Comprehensive Survey 1Rohit 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 29Jolly 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 43Santosh 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 73Nagesh 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) 89Shaik 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 105Bharti 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 129Swarnjeet 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 143Madhuri 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 159V. 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 173K. 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 193Madhuri 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 207Lakshit 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) 231Prasath 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 247Dhirendra 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 277Umesh 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

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 networksIoE enabled UAVsMind-controlled UAV using Brain-Computer Interface (BCI)The importance of AI in realizing autonomous and intelligent flying IoTBlockchain-based solutions for various security issues in UAV-enabled IoTThe 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.