Unmanned Aerial Vehicles for Internet of Things (IoT)
Concepts, Techniques, and Applications
1. Auflage August 2021
320 Seiten, Hardcover
Wiley & Sons Ltd
ISBN:
978-1-119-76882-1
John Wiley & Sons
Weitere Versionen
UNMANNED AERIAL VEHICLES FOR INTERNET OF THINGS
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.
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
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
Vandana Mohindru PhD is an assistant professor in the Department of Computer Science and Engineering, Chandigarh Group of Colleges, Mohali, Punjab, India. Her research interests 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, cybersecurity. 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.
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, cybersecurity. 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.
