Sustainable Agriculture Production Using Blockchain Technology

Rekh Ram Janghel, PhD is an Assistant Professor in the Department of Information Technology at the National Institute of Technology. He has published more than 30 research papers in national and international journals and conferences and two book chapters. His areas of research include deep learning, machine learning, biomedical healthcare systems, expert systems, neural networks, hybrid computing, and soft computing. Rajesh Doriya, PhD is an Assistant Professor in the Department of Information Technology at the National Institute of Technology with more than ten years of experience. He has authored over 50 research papers published in international journals and conferences. His research interests include distributed computing, cloud computing, artificial intelligence, robotics, soft computing techniques, and network security. Jaykumar Lachure is pursuing a PhD in the Department of Information Technology at the National Institute of Technology. He has published more than 15 research papers in national and international journals and conferences and two book chapters in reputed publications. His interests include cyber physical systems, security, precision agriculture, quantum computing, blockchain, pattern recognition, image processing, and video processing. Yogesh Kumar Rathore is an Assistant Professor in the Department of Computer Science Engineering at the Shri Shankaracharya Institute of Professional Management and Technology with more than 16 years of experience. Raipur. He has published more than 40 research papers in various conferences and journals, many book chapters, and two patents. His interests include pattern recognition, image processing, video processing, deep learning, machine learning, and artificial intelligence.

• List of Figures xvList of Tables xixPreface xxi1 A Critical Review of Ethical Challenges in the Use of Deep Learning, Blockchain, and Big Data in Agriculture 1Kirti Nahak, Anurag Shrivastava, Sheela Hundekari, Qasem AlAttaby, Lavish Kansal and Saloni Bansal1.1 Introduction 21.2 Related Works 41.3 Background and Theoretical Framework 51.4 Ethical Challenges Identified 71.5 Results 81.6 Discussion 91.7 Conclusion 11References 122 Agriculture Supply Chain Management System Using Blockchain 15Harshvardhan Chunawala, Mohammed Ihsan, R.V.S. Praveen, Nandini Shirish Boob, H. Pal Thethi and Arti Badhoutiya2.1 Introduction 162.2 Related Works 182.3 Methods and Materials 212.4 Results 222.5 Discussion 242.6 Conclusion 24References 253 Crop Product Health Management System Using DL, Precision Irrigation System Using Internet of Things and DL/ML 27Anurag Shrivastava, Sheela Hundekari, R.V.S. Praveen, Haideer Alabdeli, Vikrant Vasant Labde and Saloni Bansal3.1 Introduction 283.2 Related Works 303.2.1 Deep Learning for Monitoring Crop Health 303.2.2 IoT-Based Precision Irrigation Systems 303.2.3 Artificial Intelligence-Based Forecast of Crop Yield 313.3 Methodology 313.4 Result 333.5 Discussion 353.6 Conclusion 36Bibliography 364 Soil Nutrient Analysis and Optimization Using DL/ML Techniques 39S. Selvaraju, S. Thangamayan, Sornalakshmi R.R. and Krishnamoorthy S.4.1 Introduction 404.2 Related Works 424.2.1 Deep Learning for Soil Texture Classification and Nutrient Analysis 424.2.2 Machine Learning-Based Soil Nutrient Prediction and Optimization 434.2.3 IoT-Enabled Real-Time Soil Monitoring 434.2.4 Blockchain and AI Integration for Soil Data Management 444.3 Methods and Materials 444.4 Result 454.5 Discussion 474.6 Conclusion 47References 485 Weather Forecasting and Crop Yield Prediction Using AI/ML Models 51S. Thangamayan, Murugan Ramu and S. Selvaraju5.1 Introduction 525.2 Related Works 545.2.1 AI-Based Weather Forecasting Approaches 545.2.2 Crop Yield Prediction Using AI and ml 555.3 Methods and Materials 565.4 Results 575.5 Discussion 595.6 Conclusion 61References 626 Fertilizer Quality Ensure Certification Using Blockchain 65Harshvardhan Chunawala, Raed Alfilh, Nandini Shirish Boob, Manish Gupta, Vamsi Krishna Chidipothu and Rishabh Chaturvedi6.1 Introduction 666.2 Related Works 676.3 Methods and Materials 706.4 Results 706.5 Discussion 736.6 Conclusion 74References 747 Leaf Health Classification Using Deep Learning and Machine Learning Approaches 77Kireet Muppavaram, P. Jyothi, Diana George, Ajith Sundaram, Sivaram Murugan and V. Porkodi7.1 Introduction 787.2 Related Works 807.3 Methods and Materials 817.3.1 Data Collection 817.3.2 Preprocessing 817.3.3 Feature Extraction and Model Development 827.3.4 Model Training and Evaluation 827.3.5 Hybrid Model Integration and Comparative Analysis 827.3.6 Deployment Considerations and Optimization 827.4 Result 837.5 Discussion 857.6 Conclusion 86References 868 Pest Detection in Plants Using Advanced Deep Learning Techniques 89Kayal Padmanandam, Shravan M. B., Y. Divya, Ajith Sundaram, S. Athinarayanan and Kavitha Ramachandran8.1 Introduction 908.2 Related Works 918.3 Methods and Materials 938.4 Result 958.5 Discussion 968.6 Conclusion 97References 989 A Technological Turn in Agriculture: Digital Pathways and Innovations 101Padmapriya S.S., C. Jayamala and B. Lavaraju9.1 Introduction 1029.2 Literature Survey 1039.3 Methodology 1069.3.1 Define Scope of Research 1069.3.2 Collection of Literature 1069.3.3 Bibliometric & Content Review 1069.3.4 Case Study Selection 1069.3.5 Stakeholder Survey 1079.3.6 Data Analysis 1079.3.7 Develop Framework/Model 1079.3.8 Validation & Feedback 1079.3.9 Final Reporting 1079.4 Results 1089.5 Discussion 1109.6 Conclusion 111References 11110 Smart Crop Health Monitoring and Precision Irrigation with IoT-Driven Systems 115Prem Kumar Sholapurapu, Raami Riadhusin, R.V.S. Praveen, Nandini Shirish Boob, Navdeep Singh and Jitendra Gudainiyan10.1 Introduction 11610.2 Related Works 11810.3 Methods and Materials 12010.3.1 System Architecture Design 12110.3.2 Sensor Selection 12110.3.3 Communication Setup 12110.3.4 Predictive Analytics 12110.3.5 Field Trials and Evaluation 12110.4 Result 12210.5 Discussion 12410.6 Conclusion 124References 12511 Integrating IoT, Sensors, and Machine Learning for Enhancing Crop Yield and Irrigation Efficiency Systems 127Kunal Dhaku Jadhav11.1 Introduction 12811.2 Related Works 12911.2.1 Agricultural Machine Learning 13011.2.2 Disease Detection and Crop Monitoring Enabled by IoT 13011.2.3 Intelligent Water Efficiency Irrigation Systems 13111.2.4 Blockchain for Farm Data Security 13111.2.5 Energy-Efficient Solutions in IoT-Driven Farming 13211.2.6 Developing Patterns and Future Directions 13211.3 Methods and Materials 13211.4 Result 13411.5 Discussion 13611.6 Conclusion 137References 13812 Introduction to Digital Transformation in Agriculture: Trends and Opportunities 141Dilip R., Kusumadevi G. H., Ravi Kumar H. C., Mahadev S., Sowbhagya M. P. and Raveendra Kumar T. H.12.1 Introduction 14212.2 Literature Survey 14312.3 Methodology 14612.3.1 Data Collection 14612.3.2 Data Storage 14612.3.3 Data Processing 14612.3.4 Decision Support 14612.3.5 Implementation 14712.3.6 Monitoring and Feedback 14712.3.7 Continuous Improvement 14712.4 Results 14812.5 Discussion 15012.6 Conclusion 150Bibliography 15113 Smart Farming Technologies: IoT, Sensors, and Data Analytics 155Dilip R., Nishchitha M. H., Mallika Talikoti, Kalpavi C.Y., Harshini Veronica Deepak Balaraj and Tejashwini N.13.1 Introduction 15613.2 Literature Survey 15713.3 Methodology 15913.3.1 IoT Sensors 15913.3.2 Data Collection 15913.3.3 Data Analytics and Machine Learning 16013.3.4 Decision-Making 16013.3.5 Agricultural Processes 16113.4 Results 16113.5 Discussion 16313.6 Conclusion 163References 16414 Artificial Intelligence and Machine Learning Applications in Precision Agriculture 167Charanjeet Singh, R.V.S. Praveen, Hari Krishna Vemuri, Satya Subramanya Sai Ram Gopal Peri, Anurag Shrivastava and Saif O. Husain14.1 Introduction 16814.2 Literature Survey 16914.3 Methodology 17114.3.1 Smart Farming 17114.3.2 Sensor Data Collection 17114.3.3 Data Preprocessing 17114.3.4 Machine Learning and AI Models 17214.3.5 Prediction and Decision Making 17214.3.6 Resource Optimization 17314.4 Results 17314.5 Discussion 17514.6 Conclusion 176References 17615 Big Data and Cloud Computing for Agricultural Decision Support 179Shikhar Sharma15.1 Introduction 18015.2 Literature Survey 18115.3 Methodology 18315.3.1 IoT Sensors 18315.3.2 Data Collection & Transmission 18315.3.3 Cloud Computing Infrastructure 18315.3.4 Data Processing & Analysis 18415.3.5 Big Data Analytics & Artificial Intelligence 18415.3.6 Decision Support in Agriculture 18415.4 Results 18615.5 Discussion 18715.6 Conclusion 188References 18816 Cybersecurity Threats in Digital Agriculture: An Emerging Concern 191Pranjal Sharma16.1 Introduction 19216.2 Literature Survey 19216.3 Methodology 19416.3.1 Data Collection & Preprocessing 19416.3.2 Cyber Threat Analysis 19416.3.3 AI-Based Threat Detection 19516.3.4 Development & Testing of Cybersecurity Strategy 19516.4 Results 19616.5 Discussion 19816.6 Conclusion 199References 19917 Risk Assessment and Cybersecurity Strategies for Agricultural Systems 203Keerthna. G., C. Jayamala and B. Lavaraju17.1 Introduction 20417.2 Literature Survey 20517.3 Methodology 20717.3.1 Data Review 20717.3.2 Identification of Cybersecurity Threats 20817.3.3 Cybersecurity Model Development 20817.3.4 Implementation and Evaluation 20817.4 Results 20917.5 Discussion 21117.6 Conclusion 212References 21218 Blockchain Technology for Traceability and Security in Agri-Food Supply Chains 215Shalini. R., U. Marimuthu and Anju Mohan18.1 Introduction 21618.2 Literature Review 21718.3 Methodology 21918.3.1 Data Collection 21918.3.2 Data Processing 21918.3.3 Blockchain Integration 21918.3.4 Traceability Management 21918.3.5 Agri-Food Supply Chain Traceability 22018.4 Results 22118.5 Discussion 22318.6 Conclusion 224References 22419 Policy and Regulatory Frameworks for Secure Digital Agriculture 227Shalini. R., Anju Mohan and U. Marimuthu19.1 Introduction 22719.2 Literature Survey 22919.3 Methodology 23119.3.1 Literature Search 23119.3.2 Choice of Relevant Studies 23219.3.3 Review and Synthesis 23219.3.4 Measurement of Challenges 23219.3.5 Recommendations for Digital Agriculture 23319.4 Results 23419.5 Discussion 23519.6 Conclusion 236References 23620 Case Studies of Smart Farming Implementations and Security Solutions 239Mihir Harishbhai Rajyaguru, Anurag Shrivastava, R.V.S. Praveen, Hari Krishna Vemuri, Sriharsha Sista and Ramy Riad Al-Fatlawy20.1 Introduction 24020.2 Literature Survey 24120.3 Methodology 24420.3.1 Assessment of Cybersecurity Risks 24420.3.2 Threats and Risk Analysis 24420.3.3 Framework Design & Development 24420.3.4 AI-Based Threat Detection 24420.3.5 Digital Twin Integration 24520.3.6 Implementation in Smart Farming 24620.3.7 Performance Evaluation 24620.4 Results 24720.5 Discussion 24820.6 Conclusion 249References 25021 Sustainable Agriculture and Environmental Impacts of Digital Technologies 253Keerthna. G., B. Lavaraju and C. Jayamala21.1 Introduction 25421.2 Literature Survey 25521.3 Methodology 25721.3.1 Digital Technologies 25721.3.2 Data Collection 25721.3.3 Data Analysis 25821.3.4 Identifying Key Areas 25821.3.5 Instituting Smart Practices 25821.3.6 Sustainable Agriculture 25821.4 Results 26021.5 Discussion 26121.6 Conclusion 261References 26222 Future Directions and Challenges in Smart Agriculture and Cybersecurity 265Anurag Shrivastava, R.V.S. Praveen, Hari Krishna Vemuri, Satya Subramanya Sai Ram Gopal Peri, Sriharsha Sista and Montater Muhsn Hasan22.1 Introduction 26622.2 Literature Review 26722.3 Methodology 27022.3.1 Carry Out Literature Survey 27022.3.2 Evaluate Security Challenges in Smart Agriculture 27022.3.3 Analyze Threat Mitigation Strategies 27022.3.4 Identify Gaps and Future Directions 27122.4 Results 27222.5 Discussion 27322.6 Conclusion 274References 275About the Editors 277Index 279