Computer Vision in Smart Agriculture and Crop Management

Rajesh Kumar Dhanaraj, PhD, is a professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, India. He has contributed to over 25 books on various technologies, 21 patents, and 53 articles and papers in various refereed journals and international conferences. He is a Senior Member of the Institute of Electrical and Electronics Engineers, member of the Computer Science Teacher Association and International Association of Engineers, and an Expert Advisory Panel Member of Texas Instruments Inc., USA. His research interests include Machine Learning, Cyber-Physical Systems, and Wireless Sensor Networks.Balamurugan Balusamy, PhD, is an associate dean student at Shiv Nadar University, Delhi, India with over 12 years of experience. He has published over 200 papers, edited and authored over 80 books, and collaborated with professors across the world from top ranked universities. Additionally, he has several top-notch conferences on his resume, serves on the advisory committee for several startups and forums, and does consultancy work for the industry on industrial IoT and has given over 195 talks at various events and symposiums.Prithi Samuel, PhD, is an assistant professor in the Department of Computational Intelligence at the SRM Institute of Science and Technology, Kattankulathur Campus, Chennai, India with over 15 years of teaching experience in reputed engineering colleges. She is a pioneer researcher in the areas of automation theory, machine learning, deep learning, computational intelligence techniques, and the Internet of Things. She has published papers in leading international journals and conferences and published books and book chapters for several renowned publishing houses. She is an active member of the Institute of Electrical and Electronics Engineering and Association for Computing Machinery and holds an International Society for Technology in Education and International Association of Engineers lifetime membership.Malathy Sathyamoorthy is an assistant professor in the department of Computer Science and Engineering, Kongu Engineering College, Erode, Tamil Nadu, India. She is a life member of the Indian Society for Technical Education and International Association of Engineers. She has also published over 20 research papers in various journals, 15 papers in international conferences, two patents, and four book chapters. Her areas of interest include wireless sensor networks, networking, security, and machine learning.Ali Kashif Bashir, PhD, is a reader of Networks and Security at the Manchester Metropolitan University, United Kingdom. He is also affiliated with the University of Electronic Science and Technology of China, National University of Science and Technology, Islamabad, Pakistan, and University of Guelph, Canada. He is managing several research and industrial projects and reviews funding proposals for the Engineering and Physical Sciences Research Council, UK, Commonwealth, UK, National Science and Engineering Research Council, Canada, Mitacs, Canada, the Irish Research Council, and Qatar National Research Fund. He has delivered more than 30 talks across the globe, organized over 40 guest editorials, and chaired more than 35 conferences and workshops.

• Preface xxi1 Computer Vision-Based Innovations for Smart Agriculture and Crop Surveillance: Evolution, Trends, and Future Challenges 1M. Nalini and B. Yoga Bhuvaneswari1.1 Introduction 21.2 Artificial Intelligence in Agriculture 31.3 Evolution of Smart Agriculture 51.4 AI Technology Trends in Computer Vision 101.5 Benefits of Artificial Intelligence in Agriculture 101.6 Precision Farming 141.7 Future Challenges 151.8 Conclusion 21References 222 Cyber Biosecurity Solutions for Protecting Smart Agriculture and Precision Farming 25Balakesava Reddy Parvathala and Srinivas Kolli2.1 Introduction 262.2 Cyber-Attacks on SF and PA 282.3 Network and Related Equipment Attacks 302.4 Security Threats to SF and PA Using the Cyber-Kill-Chain (CKC) Taxonomy 322.5 The Taxonomy 342.5.1 Threats Pertaining to the Phase of Reconnaissance 342.6 Data Collection 362.7 Vulnerability of the Food and Agricultural System and the Bio Economy 382.8 The APTs in SF and PA 472.9 Challenges in the Implementation of Technologies in the Agricultural Sector 502.10 Open Challenges and Research Areas 512.11 Conclusions 52References 533 Precision Smart Farming and Cultivation with Virtual Reality/ Augmented Reality Technology - Applications and Use Cases 57Himani Sharma, Atin Kumar and Rohit Kumar3.1 Introduction 583.2 Advantages of Precision Smart Farming 603.3 Disadvantages of Precision-Smart Farming 633.4 How Could India Benefit from Precision Farming? 643.5 Challenges in Adopting Precision Farming in India 643.6 Cultivation with Virtual Reality/Augmented Reality Technology 653.7 Benefits of Cultivation with Virtual/Augmented Reality Technology 653.8 Conclusion 693.9 Summary 69References 694 Stereo Vision Subsystem and Scene Segmentation Self-Steering Tractors in Smart Agriculture 71Dileep Pulugu, Revathy Pulugu, K. Muthumanickam, S. Gopinath and A. Manikandan4.1 Introduction 724.2 Global Positioning System 734.3 Self-Steering Tractors with Vision Have Evolved 744.4 Safety Issues 764.5 The System Architecture of Self-Guiding Tractors 784.6 Basic Modeling 784.7 Building with a Vision 794.8 Path Tracking Control System 804.9 Development of a Tractor-Based Agricultural Row Detection System Using Stereovision 804.10 Creation of a Crop Row Detecting Method Using Stereo Vision 834.11 Stereo Vision for Absolute Localization 874.12 Multi-Vision Methods 894.13 Conclusions 89References 905 Vision-Based Image Classification and Image Segmentation Algorithms for Plant Disease Diagnostics 93N. Ashokkumar, A. Manikandan, S. Hariprasath and P. Vijayalakshmi5.1 Introduction 945.2 Signs and Symptoms of Plant Disease 955.3 Techniques and Algorithms for Detecting Plant Disease 1015.4 Dataset for Diagnosis Plant Disease 1035.5 Segmentation 1065.6 Classification 1095.7 Conclusion 117References 1186 Smart Dust Technology for Monitoring and Control Systems in Smart Agriculture and Crop Surveillance Systems 123M. Yogeshwari and A. Prasanth6.1 Introduction 1246.2 Smart Dust Technology in Smart Agriculture 1266.3 Precision Agriculture and Its Functional Elements 1306.4 Yield Monitoring and Forecast 1316.5 Advanced Agricultural Practices 1346.6 Conclusion 135References 1367 An Advanced Application of UAV – Drone Technologies in Precision Agriculture for Seed Dropping, Fertilizers and Pesticides Spraying and Field Monitoring 139Daniel Lawrence I., A. Rehash Rushmi Pavitra, Ragupathy Karu and M.P. Saravanan7.1 Introduction 1407.2 Irrigation Management 1417.3 Seed Dropping 1437.4 Pesticide and Fertilizer Spraying System 1457.5 Improving Soil Productivity 1457.6 Supporting Crop Growth 1477.7 Crop Management Strategies 1477.8 Increasing Crop Yield 1497.9 Preventing Crop Disease 1507.10 Predicting Crop Yield 1517.11 Conclusion 151References 1528 Cognitive Intelligence and Distributed Computing Systems Applications in Smart Farming 159Sangeetha Radhakrishnan and A. Prasanth8.1 Introduction 1598.2 Cognitive Intelligence 1658.3 Distributed Computing 1718.4 Cognitive Intelligence and Distributed Computing in Smart Farming 1798.5 Conclusion and Summary 182References 1849 Blockchain-Based Smart Agriculture with the Internet of Things: A Revolutionary Approach in Agriculture and Food Supply Chain 187Vasanth R. and Pandian A.9.1 Introduction 1889.2 Literature Review 1929.3 Methodology 1989.4 Blockchain Technology in Agriculture 2059.5 Internet of Things in Agriculture 2099.6 Integration of Blockchain and IoT in Agriculture 2119.7 Case Studies 2139.8 Challenges and Future Directions 2159.9 Conclusion 216References 21610 Computer Vision Systems in Livestock Farming, Poultry Farming, and Fish Farming: Applications, Use Cases, and Research Directions 221Balasubramaniam S., Vijesh Joe C., A. Prasanth and K. Satheesh Kumar10.1 Introduction 22210.2 Smart Agriculture 22510.3 Computer Vision 23210.4 Primary Computer Vision Techniques 23410.5 Computer Vision-Based Systems in Livestock Farming, Poultry Farming, and Fish Farming 24110.6 Computer Vision Systems for Intelligent Farming: Current Research Challenges 24810.7 Conclusion and Future Scope 252References 25511 Forestry Management with AI and Drone Technology – Digital Forestry 259M. Shanthalakshmi, M. Jeevasree, R. Kavitha, V. Madhumathi, S. Mythreye and A. Naafiah Yusra11.1 Introduction 26011.2 Drone Technology 26111.3 Drones Employed for Disaster Management 26311.4 Drones Equipped with Remote Sensing, GIS and LiDar for Geographical Dispersal Maintenance and Surveillance 27111.5 Drones for Livestock Management 27711.6 Conclusion 278Bibliography 27912 Drone Application and Use Cases in Smart Agriculture and Crop Surveillance: Future Research Directions 283Nilotpal Das, Atin Kumar and Rohit Kumar12.1 Introduction 28412.2 Definition of Drones 28512.3 Classification of Drones 28612.4 Application of Drones in Agriculture 29012.5 Agriculture Using Drone Technology 29212.6 Drone Use Rules and Regulations in India 29612.7 Policy Need 29712.8 Another Benefits of Drones in Agriculture 29812.9 Drawbacks of Drones in Agriculture 29912.10 Drone Agriculture Cost 29912.11 Future Research Direction 29912.12 Summary 300References 30113 A Comprehensive Study on Machine Vision Techniques for an Automatic Weeding Strategy in Plantations 303Manikandan J., Rhikshitha K., Sathya Sudarsen G. S. and Saran J. U.13.1 Introduction 30413.2 Related Study 30613.3 Methodology 30713.4 Experimentation and Analysis 31413.5 Conclusion and Future Enhancements 318References 31814 An Effective Study on the Machine Vision-Based Automatic Control and Monitoring in Furrow Irrigation and Precision Irrigation 323Manikandan J., Saran J. U., Samitha S. and Rhikshitha K.14.1 Introduction 32414.2 Methodology 32614.3 Maintenance and Upgrades 33314.4 Experimentation and Analysis 33414.5 Conclusion and Future Enhancement 337References 33915 Applications in Agriculture for Assessing and Monitoring Soil Using Smart Sensing and Edge Computing 343G. Padmapriya, V. Vennila, Prithi Samuel, Rajesh Kumar Dhanaraj, Balamurugan Balusamy and Malathy Sathyamoorthy15.1 Introduction 34415.2 Smart Agriculture Using Smart Sensing and Edge Computing 35115.3 IoT-Based Smart Agriculture 35415.4 KNN-Based Smart IoT System 35715.5 Results and Discussion 36115.6 Performance Evaluation 36115.7 Conclusion 363References 364Index 367