Drone Technology

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 xvii1 Drone Technologies: State-of-the-Art, Challenges, and Future Scope 1Arun Agarwal, Chandan Mohanta and Saurabh Narendra Mehta1.1 Introduction 21.2 Forces Acting on a Drone 31.3 Principal Axes 31.4 Broad Classification of Drones 31.4.1 Fixed-Wing Drones 31.4.1.1 Advantages 41.4.1.2 Disadvantages 51.4.2 Lighter-Than-Air Systems 51.4.2.1 Advantages 51.4.2.2 Disadvantages 61.4.3 Multi-Rotor Configuration 61.4.3.1 Advantages 61.4.3.2 Disadvantages 71.5 Military Necessity of Drones 71.5.1 Features of Sixth-Generation Fighter Planes 71.5.1.1 Introduction 71.5.1.2 Cyber Warfare and Cyber Security 91.5.1.3 Artificial Intelligence 91.5.1.4 Drones and Drone Swarms 101.5.1.5 Directed Energy Weapons 101.5.2 Pseudo Satellite of HAL 111.5.3 Surface to Air Missile vs. Modern Fighter Aircraft 131.5.4 Drones as Weapons of Mass Destruction 141.6 Conclusion and Future Scope 16References 172 Introduction to Drone Flights—An Eye Witness for Flying Devices to the New Destinations 21S. Venkata Achuta Rao, P. Srilatha, G.V.R.K. Acharyulu and G. Suryanarayana2.1 Introduction 222.1.1 Brief History 232.1.2 The Indomitable Significance of Drone Technology 232.1.3 Trends 242.2 How Drones Work and Their Anatomy 252.2.1 Anatomy of a Drone 252.2.1.1 Propellers 252.2.1.2 Brushless Motors 262.2.1.3 Landing Gear 262.2.1.4 Electronic Speed Controllers [ESC] 262.2.1.5 Flight Controller 262.2.1.6 Receiver 272.2.1.7 Transmitter 272.2.1.8 GPS Module 272.2.1.9 Battery 272.2.1.10 Camera 282.2.2 Types of Drones 282.2.2.1 Sub-System of UAVs 292.2.2.2 Other Specific Types of Drones 292.2.3 Components of Drones 322.2.3.1 Hardware 322.2.3.2 Software 332.2.3.3 Other Specific Components 332.3 Salient Features and Important Codes with Public Awareness with Respect to Safety and Necessary Precautionary Points 362.3.1 Safety and Legal Note 362.3.2 Public Perception 362.3.3 Crew 362.3.4 Know Before You Fly 362.3.5 Simulation Training 372.3.6 Mapping Configuration 372.3.7 Mapping BFS Camera and Mapping Camera Mount 372.3.8 Equipment to Remove 382.3.9 Flight Planning 382.3.10 Post Processing Data 392.4 Top 10 Stunning Applications of Drone Technology 392.4.1 Aerial Photography 402.4.2 Shipping and Delivery 402.4.3 Geographic Mapping 402.4.4 Disaster Management 402.4.5 Precision Agriculture 402.4.6 Search and Rescue 412.4.7 Weather Forecast 412.4.8 Wildlife Monitoring 412.4.9 Law Enforcement 412.4.10 Entertainment 422.5 Drones in Enterprises: What Value Do They Add? Work Place Safety and Industry Benchmarks 422.5.1 Total Workplace Safety with Drones 432.5.2 Future of Drones with Idea Forge’s Industry Benchmarks 432.6 Advantages and Disadvantages of Drones 442.6.1 Significant Advantages 452.6.2 Disadvantages of Drones 452.6.3 Significant Disadvantages 462.6.4 Best Uses for Drones and Its Applications 462.7 Drone Technology as Career and Offered Jobs in the Current Industry 472.8 Societal Impact—Commercial Drones 472.9 Drones Research Challenges and Solutions 482.10 Conclusion 49References 503 Drone/UAV Design Development is Important in a Wide Range of Applications: A Critical Review 53M. V. Kamal, P. Dileep, G. Sharada, V. Suneetha and M. Gayatri3.1 Introduction 543.2 Classification of Various Categories of Air Drones 553.2.1 VTOL and HTOL UAVs 573.2.2 Tilt-Body, Tilt-Rotor, and Tilt-Wingducted Fan UAVs 573.2.3 Heli-Wing and Helicopter UAVs 583.3 Drones Acting on Various Industries 583.3.1 Military Drones 583.3.2 Medical Drones 583.3.3 Agricultural Drones 623.4 Conclusions and Future Scope 62References 634 A Comprehensive Study on Design and Control of Unmanned Aerial Vehicles 69P. Venkateshwar Reddy, P. Srinivasa Rao, M. Hrishikesh and C. Satya Kumar4.1 Introduction 704.2 Classification of Drones 724.3 Flight Performance Analysis 754.4 Dynamics and Design Objectives of Drones 794.4.1 Drone Dynamics 794.4.2 Design Objectives and Scaling Laws 804.4.3 Energy Utilization 814.4.4 Agility and Speed 814.4.5 Survivability and Robustness 834.4.6 Low-Level Control and Stabilization 834.5 Design Methods and Challenges 864.5.1 Proposed Solutions for Design Challenges 874.6 Guidance, Navigation, and Control of Drones 884.7 Conclusion 92References 935 Some Studies of the Latest Artificial Intelligence Applications of Drones are Explored in Detail with Application Phenomena 99G. Vaitheeswaran, B. Sundaravadivazhagan and Karthikeyan5.1 Introduction 1005.2 Evolution of the Drone 1015.2.1 Military Drones 1025.2.2 Commercial Drones 1035.3 Drone Features 1045.4 AI Meets Drones 1055.5 Use Cases 1095.5.1 Army 1095.5.2 Weather Forecast 1115.5.3 Industry 1125.5.4 Agriculture 1135.5.5 Logistics 1135.6 Conclusion 115References 1156 Drone Technologies: Aviation Strategies, Challenges, and Applications 117Devshri Satyarthi, K.V. Arya and Manish Dixit6.1 Introduction 1186.1.1 Categorization of Unmanned Aerial Vehicle (UAV) 1196.1.1.1 Classification Based on Size 1196.1.1.2 Classification Based on Range, Endurance, and Altitude 1216.1.1.3 Classification Based on Weight 1216.1.1.4 Classification Based on Engine Type 1226.1.1.5 Classification Based on Configuration 1226.1.1.6 Classification Based on Mechanical Design and Analysis 1236.1.2 Specification of Drones 1236.2 Drone Technology 1246.2.1 Drone Monitoring Equipment 1256.2.2 Drone Countermeasure Equipment 1276.2.3 Collision Avoidance and Obstacle Detection Technology 1296.2.4 Flight Controllers, Gyroscope Stabilization, and IMU 1296.2.5 Drone Propulsion Technology 1306.2.6 Real-Time Telemetry Flight Parameters 1306.2.7 No Fly Zone Drone Technology 1306.2.8 LED Flight Indicators 1306.2.9 Drones with High Performance Camera 1316.2.10 Remote Control System and Receiver of UAV 1316.2.11 Range Extender UAV Technology 1316.2.12 Video Editing Software 1316.2.13 Operating Systems in Drone 1316.2.14 Drone Security and Hacking 1316.2.15 Modern Top Technology (Drones with Camera) 1326.2.16 Intelligent Flight Systems 1336.2.17 Drones For Tracking 1336.3 India 2021: The Drone Policy and Rules 1336.3.1 India Policy Guideline for Drones 1336.3.2 Drone Rules 2021 1366.4 Unmanned Aerial Vehicle (UAV) or Drone Application 1376.4.1 Precision Agriculture 1376.4.1.1 Related Work 1386.4.1.2 Uses of UAV in Precision Agriculture 1396.4.1.3 Challenges 1406.4.1.4 Research Trends 1406.4.1.5 Future Insights 1416.4.2 Surveillance Applications of UAVs 1416.4.2.1 Literature Review 1416.4.2.2 State-of-the-Art Research 1426.4.2.3 Product Introduction 1426.4.2.4 Research Trends and Future Insights 1426.4.3 Search and Rescue (SAR) 1426.4.3.1 How SAR Operations Utilize UAVs 1436.4.3.2 Challenges 1436.4.3.3 Research Trends 1436.4.3.4 Future Insights 1436.4.4 Construction and Infrastructure Inspection 1446.4.4.1 Literature Review 1446.4.4.2 Deployment of Drone for Construction and Infrastructure Inspection Applications 1446.4.4.3 Challenges 1446.4.4.4 Research Trends 1446.4.4.5 Future Insights 1456.4.5 Delivery of Goods 1456.4.5.1 UAVs-Based Goods Delivery System 1456.4.5.2 Challenges 1456.4.5.3 Research Trends 1466.4.5.4 Future Insights 1466.5 Conclusion 147References 1477 AI Applications of Drones 153LNC Prakash K., Santosh Kumar Ravva, M.V. Rathnamma and G. Suryanarayana7.1 Introduction 1547.2 Review of Literature 1597.3 AI in Drone Navigation 1657.4 Companies that Use the AI Drone to Solve Big Problems 1667.5 Drone Applications Using AI 1697.6 Issues in the Integration of AI with Drones 1767.7 Conclusion 177References 1798 Applications of Drones—A Review 183Swathi Gowroju and Santhosh Ramchander N.8.1 Introduction 1848.2 Drone Hardware 1888.3 Components of UAV 1898.4 Literature Survey 1908.4.1 Applications of Drones in Aerial Systems 1908.4.2 Applications of Drones in Oil and Gas Industries 1948.4.3 Applications of Drones in Military 1958.4.4 Applications of Drones in Mines 1958.4.4.1 Underground Mine Geotechnical Characterization 1968.4.4.2 Underground Mine Rock Size Distribution Analysis 1968.4.4.3 Underground Coal Mine Gas Detection 1968.5 Analysis and Discussion 196Conclusion 203References 2049 Drone Enables IoT Applications for Smart Cities 207R. Santosh Kumar, LNC Prakash K. and G. Suryanarayana9.1 Introduction to Smart Cities 2089.2 Components and Characteristics of Smart Cities 2099.2.1 Smart Healthcare 2109.2.2 Smart Transportation 2109.2.3 Smart Pollution Monitoring System 2119.2.4 Smart Infrastructure and Building 2129.2.5 Smart Building 2129.3 The Role of IoT in Smart Cities 2139.3.1 Road Traffic 2139.3.2 Smart Parking 2149.3.3 Public Transport 2149.3.4 Utilities 2159.3.4.1 Billing and Smart Meters 2159.3.4.2 Disclosing Consumption Habits 2159.3.4.3 Remote Surveillance 2159.3.5 Waste Management 2159.3.6 Environment 2169.3.7 Public Safety 2169.3.8 Security and Privacy for Smart Cities 2169.4 General Approach to Implement IoT Solutions in Smart City Design 2179.5 Challenges in IoT Solutions to Use in Smart City Design 2199.6 Introduction to Unmanned Aerial Vehicles 2219.7 Opportunities and Challenges of UAV’s in Smart Cities 2229.8 Drone-Enabled IoT 2249.8.1 Drone-Enabled IoT for Disaster Management 2249.8.2 Drone-Enabled IoT for Public Safety 2259.8.3 Drone-Enabled IoT for Data Collection 2269.8.4 Drones and IoT for Improving Life Quality 2279.8.5 Drone-Enabled IoT for Energy Efficiency 2279.8.6 Privacy and Security Issues in Drone-Enabled IoT 2289.9 Conclusion and Future Scope 229References 22910 AI-Based Smart Surveillance for Drowning and Theft Detection in Beaches Using Drones 243V. Sakthivel, Suriya E., Jae Woo Lee and P. Prakash10.1 Introduction 24410.2 Literature Survey 24410.3 Proposed Model 24510.3.1 Drown Detection by Deep Learning Methods 24510.3.2 People Alert System Using BLE Beacons 25010.3.3 Abnormal Event Monitoring for Theft Detection 25110.4 Deep Learning Model Safeties 25210.5 Performance Evaluation 25410.6 Conclusion 25410.7 Conclusion and Future Work 255Acknowledgements 256References 25611 Algorithms to Mitigate Cyber Security Threats by Employing Intelligent Machine Learning Models in the Design of IoT-Aided Drones 257Devee Siva Prasad, Pyla Jyothi, G. Suryanarayana and Sachi Nandan Mohanty11.1 Introduction 25811.2 Research Methodology 26011.3 Motivation 26011.4 Machine Learning for Drone Security 26211.5 Use of AI in Cyber Security 26611.6 Use of AI in System to Achieve Robustness, Resilience and Response 26711.7 NIC Algorithms in Cyber Security 27111.8 Example Systems for AI and ML Applications for Cyber Security Diagnose 27211.9 Introduction of New Threats 27411.10 Areas were Malicious Use of Deepfakes is Trending 27611.11 Model-Aided Deep Reinforcement Learning for Sample- Efficient UAV Trajectory Design in IoT Networks 27611.12 Model-Aided Deep Q-Learning 27811.13 Algorithm Model-Aided Deep Q-Learning Trajectory Design 28011.13.1 Numerical Results 28111.14 Machine Learning for Drone Security 28211.15 Surveillance 28311.16 Technologies Driving Drones’ Success 28411.17 Related Work 28611.18 Drones for Public Safety 28911.19 Securing Drones 29211.19.1 Machine and Deep Learning Models 29311.20 Future Work 29411.21 Contributions 295Conclusion 295References 29612 IoT-Enabled Unmanned Aerial Vehicle: An Emerging Trend in Precision Farming 301Gayatri Phade, A. T. Kishore, S. Omkar and M. Suresh Kumar12.1 Introduction to IoT Enabled UAV 30212.2 Drones in Precision Farming 30612.2.1 Types of Agriculture Drones for Precision Agriculture 30812.2.2 Drone Architecture for Precision Farming 31012.2.3 IoT-Enabled Drone in Precision Farming 31112.2.4 Safety and Security in IoT-Enabled Drones in Precision Farming 31612.2.5 IoT Architecture in Drone 31612.3 Challenges and Future Scope in IoT-Enabled Drone 31912.4 Results and Discussion 320Acknowledgement 322References 32213 Unmanned Aerial Vehicle for Land Mine Detection and Illegal Migration Surveillance Support in Military Applications 325C. Anil Kumar Reddy and B.Venkatesh13.1 Introduction to Military Drones 32613.1.1 Unmanned Aerial Vehicle (UAV) 32613.1.2 UAV Types 32913.1.2.1 Multi-Rotor Drones 33013.1.3 Problem Statement 33013.1.4 Objective 33013.1.5 Previous Work 33113.2 Literature Review 33113.2.1 Need of Drones for Indian Borders 33413.2.2 UAV Technical Specifications 33613.3 Methodology of UAV’s in Military Applications 33613.3.1 Proposed System 33613.3.2 Methodology 33713.3.2.1 UAV Work Principle 33713.3.2.2 UAV Controls and Installation 33813.3.2.3 Drone Material and Frame 34213.3.2.4 Program Used/Software Used (e.g., Aurdino) and Data Collection 34213.3.2.5 Illegal Migration Surveillance with Camera 34313.3.2.6 Data Collection from Mine Detector and Camera 34413.3.2.7 Testing Conditions Applied for this Drone 34413.4 Software Implementation 34413.4.1 Arduino IDE 34513.4.2 UAV Program/Coding 345Appendix A 34513.5 Conclusion 348References 34814 Importance of Drone Technology in Agriculture 351Karuppiah Natarajan, Karthikeyan R. and Rajalingam S.14.1 Introduction 35214.2 Components of a Drone 35214.3 Study of Natural Resources 35514.3.1 Study of Natural and Manmade Pastures 35714.3.2 Monitor Water Resources, Floods, and Droughts 35714.3.3 Study of Weather Patterns 35714.3.4 Monitoring of Soil Erosion 35814.3.5 Cloud Seeding 35914.4 Soil Fertility Management 35914.4.1 Management of Soils and Their Fertility 36014.4.2 Variable-Rate Technology for Soil Fertility Management 36114.5 Irrigation and Water Management 36214.5.1 Crop Water Stress Index 36314.5.2 Drones to Monitor Water Resources 36314.5.3 Drones to Design an Irrigation System 36414.6 Crop Disease Identification 36514.6.1 Monitoring and Identification Using Different Drone Platforms and Peripherals 36514.6.2 Disease Symptoms 36614.6.2.1 Sheath Blight 36614.6.2.2 Narrow Brown Leaf Spot 36714.7 Pest Control Management 36814.7.1 Drones Offer a Sustainable Pest Control Solution 36814.8 Agricultural Drones to Improve Crop Yield Management Efficiency 36914.9 Issues and Challenges 37014.9.1 Power Source and Flight Time 37014.9.2 High Capital Cost 37114.9.3 The Capacity of the Tank to Carry Fertilizer and Water for Spraying 37214.9.4 Lack of Technical Skills to Operate, Repair, and Service 37214.9.5 Job Loss of Existing Farm Workers 37214.10 Conclusion 372References 37315 Network Intrusion Detection of Drones Using Recurrent Neural Networks 375Yadala Sucharitha, Pundru Chandra Shaker Reddy and G. Suryanarayana15.1 Introduction 37615.2 Related Works 37815.3 Drone Intrusion Detection Methodology 38015.3.1 Drone RNN 38115.3.2 Data Collector 38215.3.3 Centralized-RNN 38315.3.4 Decision-Maker 38315.4 Results and Discussion 38415.4.1 Model Assessment 38415.4.2 Performance Analysis 38415.4.3 LSTM_RNN Performance over UNSW-NB 15Dataset 38515.5 Conclusion 388References 38816 Drone-Enabled Smart Healthcare System for Smart Cities 393Subasish Mohapatra, Amlan Sahoo, Subhadarshini Mohanty and Sachi Nandan Mohanty16.1 Introduction 39416.2 Related Works 39716.3 Applications of Drones 39916.4 Suggested Framework 41116.5 Challenges 41516.6 Conclusion 418Future Scopes 419References 42017 Drone Delivery 425V. Sakthivel, Sourav Patel, Jae Woo Lee and P. Prakash17.1 Introduction 42617.2 History of Drones 42717.3 Drone Delivery in Healthcare 43217.4 Drone Delivery of Food 43217.5 Drone Delivery in Postal Service 43317.6 Delivery of Goods 433Acknowledgements 439References 439Index 441