Drone Technology Future Trends and Practical Applications

This book provides a holistic and valuable insight into the revolutionary world of unmanned aerial vehicles (UAV).

The book elucidates the revolutionary and riveting research in the ultramodern domain of drone technologies, drone-enabled IoT applications, and artificial intelligence-based smart surveillance. The book explains the most recent developments in the field, challenges, and future scope of drone technologies. Beyond that, it discusses the importance of a wide range of design applications, drone/UAV development, and drone-enabled smart healthcare systems for smart cities. It describes pioneering work on mitigating cyber security threats by employing intelligent machine learning models in the designing of IoT-aided drones. The book also has a fascinating chapter on application intrusion detection by drones using recurrent neural networks. Other chapters address interdisciplinary fields like artificial intelligence, deep learning, the role of drones in healthcare in smart cities, and the importance of drone technology in agriculture.

Audience

The book will be read and consulted by a range of industry engineers involved with introducing drone technology to their daily operations.

Sachi Nandan Mohanty received his PhD from the Indian Institute of Technology Kharagpur, India. He is an associate professor, VIT-AP University, Andhra Pradesh. He has edited 24 books in association with several publishers including many with the Wiley-Scrivener imprint. His research areas include data mining, big data analysis, cognitive science, fuzzy decision-making, brain-computer interface, cognition, and computational intelligence.

J.V.R. Ravindra is a professor of electronics and computer engineering and is the Principal of Vardhaman College of Engineering, Hyderabad. He holds a PhD in VLSI design from the Indian Institute of Technology, Hyderabad. He is working on quantum computing, wireless sensor networks, machine learning for VLSI, low power DSP architectures. Dr. Ravindra has 120 publications in reputed journals and conferences.

G. Surya Narayana, PhD, is an associate professor in the Department of CSE, Vardhaman College of Engineering, Hyderabad, India. He has more than 15 years of teaching and 11 years of research experience. He has 37 research publications in reputed journals, three books, and filed six Indian and international patents and two copyrights. His research interests are in artificial intelligence, machine learning, and big data analytics.

Chinmaya Ranjan Pattnaik, PhD, is a professor in the Department of Computer Science and Engineering at Ajay Binay Institute of Technology CDA, Cuttack, India. He has published 18 research papers in journals and conferences as well as filed six national and international patents. His fields of interest are machine learning and digital image processing.

Y. Mohamed Sirajudeen, PhD, is an assistant professor in the School of Computer Science and Engineering, VIT University, Andra Pradesh, India. His research areas are cloud computing, big data, blockchain, and the Internet of Things. He has published more than 25 research papers in international journals.

Preface xvii

1 Drone Technologies: State-of-the-Art, Challenges, and Future Scope 1
Arun Agarwal, Chandan Mohanta and Saurabh Narendra Mehta

1.1 Introduction 2

1.2 Forces Acting on a Drone 3

1.3 Principal Axes 3

1.4 Broad Classification of Drones 3

1.4.1 Fixed-Wing Drones 3

1.4.1.1 Advantages 4

1.4.1.2 Disadvantages 5

1.4.2 Lighter-Than-Air Systems 5

1.4.2.1 Advantages 5

1.4.2.2 Disadvantages 6

1.4.3 Multi-Rotor Configuration 6

1.4.3.1 Advantages 6

1.4.3.2 Disadvantages 7

1.5 Military Necessity of Drones 7

1.5.1 Features of Sixth-Generation Fighter Planes 7

1.5.1.1 Introduction 7

1.5.1.2 Cyber Warfare and Cyber Security 9

1.5.1.3 Artificial Intelligence 9

1.5.1.4 Drones and Drone Swarms 10

1.5.1.5 Directed Energy Weapons 10

1.5.2 Pseudo Satellite of HAL 11

1.5.3 Surface to Air Missile vs. Modern Fighter Aircraft 13

1.5.4 Drones as Weapons of Mass Destruction 14

1.6 Conclusion and Future Scope 16

References 17

2 Introduction to Drone Flights—An Eye Witness for Flying Devices to the New Destinations 21
S. Venkata Achuta Rao, P. Srilatha, G.V.R.K. Acharyulu and G. Suryanarayana

2.1 Introduction 22

2.1.1 Brief History 23

2.1.2 The Indomitable Significance of Drone Technology 23

2.1.3 Trends 24

2.2 How Drones Work and Their Anatomy 25

2.2.1 Anatomy of a Drone 25

2.2.1.1 Propellers 25

2.2.1.2 Brushless Motors 26

2.2.1.3 Landing Gear 26

2.2.1.4 Electronic Speed Controllers [ESC] 26

2.2.1.5 Flight Controller 26

2.2.1.6 Receiver 27

2.2.1.7 Transmitter 27

2.2.1.8 GPS Module 27

2.2.1.9 Battery 27

2.2.1.10 Camera 28

2.2.2 Types of Drones 28

2.2.2.1 Sub-System of UAVs 29

2.2.2.2 Other Specific Types of Drones 29

2.2.3 Components of Drones 32

2.2.3.1 Hardware 32

2.2.3.2 Software 33

2.2.3.3 Other Specific Components 33

2.3 Salient Features and Important Codes with Public Awareness with Respect to Safety and Necessary Precautionary Points 36

2.3.1 Safety and Legal Note 36

2.3.2 Public Perception 36

2.3.3 Crew 36

2.3.4 Know Before You Fly 36

2.3.5 Simulation Training 37

2.3.6 Mapping Configuration 37

2.3.7 Mapping BFS Camera and Mapping Camera Mount 37

2.3.8 Equipment to Remove 38

2.3.9 Flight Planning 38

2.3.10 Post Processing Data 39

2.4 Top 10 Stunning Applications of Drone Technology 39

2.4.1 Aerial Photography 40

2.4.2 Shipping and Delivery 40

2.4.3 Geographic Mapping 40

2.4.4 Disaster Management 40

2.4.5 Precision Agriculture 40

2.4.6 Search and Rescue 41

2.4.7 Weather Forecast 41

2.4.8 Wildlife Monitoring 41

2.4.9 Law Enforcement 41

2.4.10 Entertainment 42

2.5 Drones in Enterprises: What Value Do They Add? Work Place Safety and Industry Benchmarks 42

2.5.1 Total Workplace Safety with Drones 43

2.5.2 Future of Drones with Idea Forge’s Industry Benchmarks 43

2.6 Advantages and Disadvantages of Drones 44

2.6.1 Significant Advantages 45

2.6.2 Disadvantages of Drones 45

2.6.3 Significant Disadvantages 46

2.6.4 Best Uses for Drones and Its Applications 46

2.7 Drone Technology as Career and Offered Jobs in the Current Industry 47

2.8 Societal Impact—Commercial Drones 47

2.9 Drones Research Challenges and Solutions 48

2.10 Conclusion 49

References 50

3 Drone/UAV Design Development is Important in a Wide Range of Applications: A Critical Review 53
M. V. Kamal, P. Dileep, G. Sharada, V. Suneetha and M. Gayatri

3.1 Introduction 54

3.2 Classification of Various Categories of Air Drones 55

3.2.1 VTOL and HTOL UAVs 57

3.2.2 Tilt-Body, Tilt-Rotor, and Tilt-Wingducted Fan UAVs 57

3.2.3 Heli-Wing and Helicopter UAVs 58

3.3 Drones Acting on Various Industries 58

3.3.1 Military Drones 58

3.3.2 Medical Drones 58

3.3.3 Agricultural Drones 62

3.4 Conclusions and Future Scope 62

References 63

4 A Comprehensive Study on Design and Control of Unmanned Aerial Vehicles 69
P. Venkateshwar Reddy, P. Srinivasa Rao, M. Hrishikesh and C. Satya Kumar

4.1 Introduction 70

4.2 Classification of Drones 72

4.3 Flight Performance Analysis 75

4.4 Dynamics and Design Objectives of Drones 79

4.4.1 Drone Dynamics 79

4.4.2 Design Objectives and Scaling Laws 80

4.4.3 Energy Utilization 81

4.4.4 Agility and Speed 81

4.4.5 Survivability and Robustness 83

4.4.6 Low-Level Control and Stabilization 83

4.5 Design Methods and Challenges 86

4.5.1 Proposed Solutions for Design Challenges 87

4.6 Guidance, Navigation, and Control of Drones 88

4.7 Conclusion 92

References 93

5 Some Studies of the Latest Artificial Intelligence Applications of Drones are Explored in Detail with Application Phenomena 99
G. Vaitheeswaran, B. Sundaravadivazhagan and Karthikeyan

5.1 Introduction 100

5.2 Evolution of the Drone 101

5.2.1 Military Drones 102

5.2.2 Commercial Drones 103

5.3 Drone Features 104

5.4 AI Meets Drones 105

5.5 Use Cases 109

5.5.1 Army 109

5.5.2 Weather Forecast 111

5.5.3 Industry 112

5.5.4 Agriculture 113

5.5.5 Logistics 113

5.6 Conclusion 115

References 115

6 Drone Technologies: Aviation Strategies, Challenges, and Applications 117
Devshri Satyarthi, K.V. Arya and Manish Dixit

6.1 Introduction 118

6.1.1 Categorization of Unmanned Aerial Vehicle (UAV) 119

6.1.1.1 Classification Based on Size 119

6.1.1.2 Classification Based on Range, Endurance, and Altitude 121

6.1.1.3 Classification Based on Weight 121

6.1.1.4 Classification Based on Engine Type 122

6.1.1.5 Classification Based on Configuration 122

6.1.1.6 Classification Based on Mechanical Design and Analysis 123

6.1.2 Specification of Drones 123

6.2 Drone Technology 124

6.2.1 Drone Monitoring Equipment 125

6.2.2 Drone Countermeasure Equipment 127

6.2.3 Collision Avoidance and Obstacle Detection Technology 129

6.2.4 Flight Controllers, Gyroscope Stabilization, and IMU 129

6.2.5 Drone Propulsion Technology 130

6.2.6 Real-Time Telemetry Flight Parameters 130

6.2.7 No Fly Zone Drone Technology 130

6.2.8 LED Flight Indicators 130

6.2.9 Drones with High Performance Camera 131

6.2.10 Remote Control System and Receiver of UAV 131

6.2.11 Range Extender UAV Technology 131

6.2.12 Video Editing Software 131

6.2.13 Operating Systems in Drone 131

6.2.14 Drone Security and Hacking 131

6.2.15 Modern Top Technology (Drones with Camera) 132

6.2.16 Intelligent Flight Systems 133

6.2.17 Drones For Tracking 133

6.3 India 2021: The Drone Policy and Rules 133

6.3.1 India Policy Guideline for Drones 133

6.3.2 Drone Rules 2021 136

6.4 Unmanned Aerial Vehicle (UAV) or Drone Application 137

6.4.1 Precision Agriculture 137

6.4.1.1 Related Work 138

6.4.1.2 Uses of UAV in Precision Agriculture 139

6.4.1.3 Challenges 140

6.4.1.4 Research Trends 140

6.4.1.5 Future Insights 141

6.4.2 Surveillance Applications of UAVs 141

6.4.2.1 Literature Review 141

6.4.2.2 State-of-the-Art Research 142

6.4.2.3 Product Introduction 142

6.4.2.4 Research Trends and Future Insights 142

6.4.3 Search and Rescue (SAR) 142

6.4.3.1 How SAR Operations Utilize UAVs 143

6.4.3.2 Challenges 143

6.4.3.3 Research Trends 143

6.4.3.4 Future Insights 143

6.4.4 Construction and Infrastructure Inspection 144

6.4.4.1 Literature Review 144

6.4.4.2 Deployment of Drone for Construction and Infrastructure Inspection Applications 144

6.4.4.3 Challenges 144

6.4.4.4 Research Trends 144

6.4.4.5 Future Insights 145

6.4.5 Delivery of Goods 145

6.4.5.1 UAVs-Based Goods Delivery System 145

6.4.5.2 Challenges 145

6.4.5.3 Research Trends 146

6.4.5.4 Future Insights 146

6.5 Conclusion 147

References 147

7 AI Applications of Drones 153
LNC Prakash K., Santosh Kumar Ravva, M.V. Rathnamma and G. Suryanarayana

7.1 Introduction 154

7.2 Review of Literature 159

7.3 AI in Drone Navigation 165

7.4 Companies that Use the AI Drone to Solve Big Problems 166

7.5 Drone Applications Using AI 169

7.6 Issues in the Integration of AI with Drones 176

7.7 Conclusion 177

References 179

8 Applications of Drones—A Review 183
Swathi Gowroju and Santhosh Ramchander N.

8.1 Introduction 184

8.2 Drone Hardware 188

8.3 Components of UAV 189

8.4 Literature Survey 190

8.4.1 Applications of Drones in Aerial Systems 190

8.4.2 Applications of Drones in Oil and Gas Industries 194

8.4.3 Applications of Drones in Military 195

8.4.4 Applications of Drones in Mines 195

8.4.4.1 Underground Mine Geotechnical Characterization 196

8.4.4.2 Underground Mine Rock Size Distribution Analysis 196

8.4.4.3 Underground Coal Mine Gas Detection 196

8.5 Analysis and Discussion 196

Conclusion 203

References 204

9 Drone Enables IoT Applications for Smart Cities 207
R. Santosh Kumar, LNC Prakash K. and G. Suryanarayana

9.1 Introduction to Smart Cities 208

9.2 Components and Characteristics of Smart Cities 209

9.2.1 Smart Healthcare 210

9.2.2 Smart Transportation 210

9.2.3 Smart Pollution Monitoring System 211

9.2.4 Smart Infrastructure and Building 212

9.2.5 Smart Building 212

9.3 The Role of IoT in Smart Cities 213

9.3.1 Road Traffic 213

9.3.2 Smart Parking 214

9.3.3 Public Transport 214

9.3.4 Utilities 215

9.3.4.1 Billing and Smart Meters 215

9.3.4.2 Disclosing Consumption Habits 215

9.3.4.3 Remote Surveillance 215

9.3.5 Waste Management 215

9.3.6 Environment 216

9.3.7 Public Safety 216

9.3.8 Security and Privacy for Smart Cities 216

9.4 General Approach to Implement IoT Solutions in Smart City Design 217

9.5 Challenges in IoT Solutions to Use in Smart City Design 219

9.6 Introduction to Unmanned Aerial Vehicles 221

9.7 Opportunities and Challenges of UAV’s in Smart Cities 222

9.8 Drone-Enabled IoT 224

9.8.1 Drone-Enabled IoT for Disaster Management 224

9.8.2 Drone-Enabled IoT for Public Safety 225

9.8.3 Drone-Enabled IoT for Data Collection 226

9.8.4 Drones and IoT for Improving Life Quality 227

9.8.5 Drone-Enabled IoT for Energy Efficiency 227

9.8.6 Privacy and Security Issues in Drone-Enabled IoT 228

9.9 Conclusion and Future Scope 229

References 229

10 AI-Based Smart Surveillance for Drowning and Theft Detection in Beaches Using Drones 243
V. Sakthivel, Suriya E., Jae Woo Lee and P. Prakash

10.1 Introduction 244

10.2 Literature Survey 244

10.3 Proposed Model 245

10.3.1 Drown Detection by Deep Learning Methods 245

10.3.2 People Alert System Using BLE Beacons 250

10.3.3 Abnormal Event Monitoring for Theft Detection 251

10.4 Deep Learning Model Safeties 252

10.5 Performance Evaluation 254

10.6 Conclusion 254

10.7 Conclusion and Future Work 255

Acknowledgements 256

References 256

11 Algorithms to Mitigate Cyber Security Threats by Employing Intelligent Machine Learning Models in the Design of IoT-Aided Drones 257
Devee Siva Prasad, Pyla Jyothi, G. Suryanarayana and Sachi Nandan Mohanty

11.1 Introduction 258

11.2 Research Methodology 260

11.3 Motivation 260

11.4 Machine Learning for Drone Security 262

11.5 Use of AI in Cyber Security 266

11.6 Use of AI in System to Achieve Robustness, Resilience and Response 267

11.7 NIC Algorithms in Cyber Security 271

11.8 Example Systems for AI and ML Applications for Cyber Security Diagnose 272

11.9 Introduction of New Threats 274

11.10 Areas were Malicious Use of Deepfakes is Trending 276

11.11 Model-Aided Deep Reinforcement Learning for Sample- Efficient UAV Trajectory Design in IoT Networks 276

11.12 Model-Aided Deep Q-Learning 278

11.13 Algorithm Model-Aided Deep Q-Learning Trajectory Design 280

11.13.1 Numerical Results 281

11.14 Machine Learning for Drone Security 282

11.15 Surveillance 283

11.16 Technologies Driving Drones’ Success 284

11.17 Related Work 286

11.18 Drones for Public Safety 289

11.19 Securing Drones 292

11.19.1 Machine and Deep Learning Models 293

11.20 Future Work 294

11.21 Contributions 295

Conclusion 295

References 296

12 IoT-Enabled Unmanned Aerial Vehicle: An Emerging Trend in Precision Farming 301
Gayatri Phade, A. T. Kishore, S. Omkar and M. Suresh Kumar

12.1 Introduction to IoT Enabled UAV 302

12.2 Drones in Precision Farming 306

12.2.1 Types of Agriculture Drones for Precision Agriculture 308

12.2.2 Drone Architecture for Precision Farming 310

12.2.3 IoT-Enabled Drone in Precision Farming 311

12.2.4 Safety and Security in IoT-Enabled Drones in Precision Farming 316

12.2.5 IoT Architecture in Drone 316

12.3 Challenges and Future Scope in IoT-Enabled Drone 319

12.4 Results and Discussion 320

Acknowledgement 322

References 322

13 Unmanned Aerial Vehicle for Land Mine Detection and Illegal Migration Surveillance Support in Military Applications 325
C. Anil Kumar Reddy and B.Venkatesh

13.1 Introduction to Military Drones 326

13.1.1 Unmanned Aerial Vehicle (UAV) 326

13.1.2 UAV Types 329

13.1.2.1 Multi-Rotor Drones 330

13.1.3 Problem Statement 330

13.1.4 Objective 330

13.1.5 Previous Work 331

13.2 Literature Review 331

13.2.1 Need of Drones for Indian Borders 334

13.2.2 UAV Technical Specifications 336

13.3 Methodology of UAV’s in Military Applications 336

13.3.1 Proposed System 336

13.3.2 Methodology 337

13.3.2.1 UAV Work Principle 337

13.3.2.2 UAV Controls and Installation 338

13.3.2.3 Drone Material and Frame 342

13.3.2.4 Program Used/Software Used (e.g., Aurdino) and Data Collection 342

13.3.2.5 Illegal Migration Surveillance with Camera 343

13.3.2.6 Data Collection from Mine Detector and Camera 344

13.3.2.7 Testing Conditions Applied for this Drone 344

13.4 Software Implementation 344

13.4.1 Arduino IDE 345

13.4.2 UAV Program/Coding 345

Appendix A 345

13.5 Conclusion 348

References 348

14 Importance of Drone Technology in Agriculture 351
Karuppiah Natarajan, Karthikeyan R. and Rajalingam S.

14.1 Introduction 352

14.2 Components of a Drone 352

14.3 Study of Natural Resources 355

14.3.1 Study of Natural and Manmade Pastures 357

14.3.2 Monitor Water Resources, Floods, and Droughts 357

14.3.3 Study of Weather Patterns 357

14.3.4 Monitoring of Soil Erosion 358

14.3.5 Cloud Seeding 359

14.4 Soil Fertility Management 359

14.4.1 Management of Soils and Their Fertility 360

14.4.2 Variable-Rate Technology for Soil Fertility Management 361

14.5 Irrigation and Water Management 362

14.5.1 Crop Water Stress Index 363

14.5.2 Drones to Monitor Water Resources 363

14.5.3 Drones to Design an Irrigation System 364

14.6 Crop Disease Identification 365

14.6.1 Monitoring and Identification Using Different Drone Platforms and Peripherals 365

14.6.2 Disease Symptoms 366

14.6.2.1 Sheath Blight 366

14.6.2.2 Narrow Brown Leaf Spot 367

14.7 Pest Control Management 368

14.7.1 Drones Offer a Sustainable Pest Control Solution 368

14.8 Agricultural Drones to Improve Crop Yield Management Efficiency 369

14.9 Issues and Challenges 370

14.9.1 Power Source and Flight Time 370

14.9.2 High Capital Cost 371

14.9.3 The Capacity of the Tank to Carry Fertilizer and Water for Spraying 372

14.9.4 Lack of Technical Skills to Operate, Repair, and Service 372

14.9.5 Job Loss of Existing Farm Workers 372

14.10 Conclusion 372

References 373

15 Network Intrusion Detection of Drones Using Recurrent Neural Networks 375
Yadala Sucharitha, Pundru Chandra Shaker Reddy and G. Suryanarayana

15.1 Introduction 376

15.2 Related Works 378

15.3 Drone Intrusion Detection Methodology 380

15.3.1 Drone RNN 381

15.3.2 Data Collector 382

15.3.3 Centralized-RNN 383

15.3.4 Decision-Maker 383

15.4 Results and Discussion 384

15.4.1 Model Assessment 384

15.4.2 Performance Analysis 384

15.4.3 LSTM_RNN Performance over UNSW-NB 15

Dataset 385

15.5 Conclusion 388

References 388

16 Drone-Enabled Smart Healthcare System for Smart Cities 393
Subasish Mohapatra, Amlan Sahoo, Subhadarshini Mohanty and Sachi Nandan Mohanty

16.1 Introduction 394

16.2 Related Works 397

16.3 Applications of Drones 399

16.4 Suggested Framework 411

16.5 Challenges 415

16.6 Conclusion 418

Future Scopes 419

References 420

17 Drone Delivery 425
V. Sakthivel, Sourav Patel, Jae Woo Lee and P. Prakash

17.1 Introduction 426

17.2 History of Drones 427

17.3 Drone Delivery in Healthcare 432

17.4 Drone Delivery of Food 432

17.5 Drone Delivery in Postal Service 433

17.6 Delivery of Goods 433

Acknowledgements 439

References 439

Index 441

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.