{"product_id":"optimizing-ai-applications-for-sustainable-agriculture-hardback-9781394287239","title":"Optimizing AI Applications for Sustainable Agriculture (Hardback) 9781394287239","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eOptimizing AI Applications for Sustainable Agriculture\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eRoheet Bhatnagar (Edited by), Bhatnagar (Author), Chandan Kumar Panda (Edited by), Mahmoud Yasin Shams (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394287239, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 3 November 2025\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e576 pages\u003cbr\u003e28 x 19 x 2.6 cm, 1.021 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eEmbrace the future of sustainable food production with this comprehensive guide that explores how artificial intelligence and emerging technologies are revolutionizing agriculture. \u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eIn an era marked by climate change, resource depletion, and population growth, innovation is not a luxury—it is a necessity. Integrating AI into agricultural practices offers a promising solution. From precision farming and crop monitoring to predictive analytics and decision support systems, AI has the potential to revolutionize how we grow, manage, and distribute food. This book is a comprehensive guide that delves into the transformative potential of artificial intelligence and emerging technologies in the field of agriculture. An in-depth exploration of various AI technologies, such as machine learning, deep learning, natural language processing, and computer vision, will demonstrate the wide applications these tools have for agricultural practices. It covers emerging technologies like the Internet of Things, drones, precision farming, and agro-technology. The primary focus is on how these technologies can enhance sustainability in agriculture by improving crop yields, reducing water consumption, minimizing chemical use, and promoting eco-friendly farming practices. This essential guide will give readers a deep understanding of how cutting-edge technology can be harnessed to create a more sustainable future for agriculture. \u003c\/p\u003e\n\u003cp\u003eReaders will find the volume: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eDives into the latest research and innovations in AI and emerging technologies that are transforming agricultural practices;\u003c\/li\u003e \u003cli\u003eProvides real-world examples and case studies that show how these technologies can be implemented in farming;\u003c\/li\u003e \u003cli\u003eExplores how these modern technologies align with global sustainability goals and how they can be integrated into national strategies;\u003c\/li\u003e \u003cli\u003eIntroduces the role of AI and emerging technologies in promoting sustainable agricultural practices that protect the environment.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eResearchers, computer and agricultural scientists, farmers, and policymakers looking to leverage the potential of artificial intelligence and machine learning for the benefit of farmers.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I: Artificial Intelligence-Assisted Sustainable Agriculture 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 AI and Emerging Technologies for Precision Agriculture: A Survey 3\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBrajesh Kumar Khare\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 4\u003c\/p\u003e \u003cp\u003e1.2 Precision Agriculture 5\u003c\/p\u003e \u003cp\u003e1.3 Artificial Intelligence 9\u003c\/p\u003e \u003cp\u003e1.3.1 Role of AI in Agriculture 11\u003c\/p\u003e \u003cp\u003e1.4 Internet of Things (IoT) 11\u003c\/p\u003e \u003cp\u003e1.4.1 Basics of IoT in Agriculture 13\u003c\/p\u003e \u003cp\u003e1.4.2 Role of IoT 15\u003c\/p\u003e \u003cp\u003e1.5 Blockchain Technology 15\u003c\/p\u003e \u003cp\u003e1.6 Technologies Used in Smart Farming 17\u003c\/p\u003e \u003cp\u003e1.6.1 Global Positioning System (GPS) 17\u003c\/p\u003e \u003cp\u003e1.6.2 Sensor Technologies 17\u003c\/p\u003e \u003cp\u003e1.6.3 Variable Rate Technology and Grid Soil Sampling 18\u003c\/p\u003e \u003cp\u003e1.6.4 Geographic Information System (GIS) 19\u003c\/p\u003e \u003cp\u003e1.6.5 Crop Management 19\u003c\/p\u003e \u003cp\u003e1.6.6 Soil and Plant Sensors 20\u003c\/p\u003e \u003cp\u003e1.6.7 Yield Monitor 20\u003c\/p\u003e \u003cp\u003e1.7 Challenges 24\u003c\/p\u003e \u003cp\u003e1.8 Future Research 26\u003c\/p\u003e \u003cp\u003e1.9 Conclusion 29\u003c\/p\u003e \u003cp\u003eReferences 29\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 AI-Enabled Framework for Sustainable Agriculture Practices 33\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eYukti Batra, Suman Bhatia and Ankit Verma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 34\u003c\/p\u003e \u003cp\u003e2.2 Sustainable Agriculture Imperatives 35\u003c\/p\u003e \u003cp\u003e2.2.1 Environmental Degradation 36\u003c\/p\u003e \u003cp\u003e2.2.2 Biodiversity Loss 36\u003c\/p\u003e \u003cp\u003e2.2.3 Climate Change Impacts 36\u003c\/p\u003e \u003cp\u003e2.2.4 Resource Scarcity 37\u003c\/p\u003e \u003cp\u003e2.2.5 Food Security and Economic Stability 37\u003c\/p\u003e \u003cp\u003e2.2.6 Public Health Concerns 37\u003c\/p\u003e \u003cp\u003e2.2.7 Social Equity and Rural Livelihoods 37\u003c\/p\u003e \u003cp\u003e2.2.8 Global Food Shortage Concerns 38\u003c\/p\u003e \u003cp\u003e2.2.9 Empowerment and Awareness 38\u003c\/p\u003e \u003cp\u003e2.3 Social Relevance of Sustainable Practices in Agriculture 38\u003c\/p\u003e \u003cp\u003e2.3.1 Livelihood Security 39\u003c\/p\u003e \u003cp\u003e2.3.2 Community Health and Well-Being 39\u003c\/p\u003e \u003cp\u003e2.3.3 Social Equity and Inclusion 39\u003c\/p\u003e \u003cp\u003e2.3.4 Rural Empowerment and Resilience 40\u003c\/p\u003e \u003cp\u003e2.4 Sustainable Agriculture Indicators 40\u003c\/p\u003e \u003cp\u003e2.4.1 Food Grain Productivity 40\u003c\/p\u003e \u003cp\u003e2.4.2 Population Density 41\u003c\/p\u003e \u003cp\u003e2.4.3 Cropping Intensity 42\u003c\/p\u003e \u003cp\u003e2.5 Sustainable Agriculture Practices Followed Till Date 42\u003c\/p\u003e \u003cp\u003e2.5.1 Agroforestry 42\u003c\/p\u003e \u003cp\u003e2.5.2 Integrated Pest Management (IPM) 44\u003c\/p\u003e \u003cp\u003e2.5.3 Crop Rotation 44\u003c\/p\u003e \u003cp\u003e2.5.4 Cover Cropping 44\u003c\/p\u003e \u003cp\u003e2.5.5 Organic Farming 44\u003c\/p\u003e \u003cp\u003e2.5.6 No-Till Farming 44\u003c\/p\u003e \u003cp\u003e2.6 AI-Enabled Conceptual Framework 44\u003c\/p\u003e \u003cp\u003e2.6.1 Perception from Environment Using IoT Sensors 45\u003c\/p\u003e \u003cp\u003e2.6.1.1 Remote Sensing 45\u003c\/p\u003e \u003cp\u003e2.6.1.2 IoT Sensors 46\u003c\/p\u003e \u003cp\u003e2.6.2 Data Storage 46\u003c\/p\u003e \u003cp\u003e2.6.3 Data Processing 47\u003c\/p\u003e \u003cp\u003e2.6.4 Training and Testing by ML Models 47\u003c\/p\u003e \u003cp\u003e2.7 Applications of Artificial Intelligence in Agriculture 48\u003c\/p\u003e \u003cp\u003e2.8 Challenges and Barriers to Sustainable Agriculture 51\u003c\/p\u003e \u003cp\u003e2.8.1 Theoretical Obstacles 51\u003c\/p\u003e \u003cp\u003e2.8.2 Methodological Obstacles 52\u003c\/p\u003e \u003cp\u003e2.8.3 Personal Obstacles 53\u003c\/p\u003e \u003cp\u003e2.8.4 Practical Obstacles 54\u003c\/p\u003e \u003cp\u003e2.9 Future Directions 55\u003c\/p\u003e \u003cp\u003e2.10 Conclusion 57\u003c\/p\u003e \u003cp\u003eReferences 58\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 The Impact of Artificial Intelligence on Agriculture: Revolutionizing Efficiency and Sustainability 61\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSanthiya S., P. Jayadharshini, N. Abinaya, Sharmila C., Srigha S. and Sruthi K.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eApplications 62\u003c\/p\u003e \u003cp\u003e3.1 Introduction 62\u003c\/p\u003e \u003cp\u003e3.2 Precision Farming 64\u003c\/p\u003e \u003cp\u003e3.2.1 Data Collection and Analytics 64\u003c\/p\u003e \u003cp\u003e3.2.2 Disease Detection 65\u003c\/p\u003e \u003cp\u003e3.2.3 Yield Production and Optimization 65\u003c\/p\u003e \u003cp\u003e3.2.4 Precision Irrigation 66\u003c\/p\u003e \u003cp\u003e3.3 Crop Monitoring 67\u003c\/p\u003e \u003cp\u003e3.3.1 Remote Sensing and Satellite Imagery 67\u003c\/p\u003e \u003cp\u003e3.3.2 Drones 67\u003c\/p\u003e \u003cp\u003e3.3.3 Computer Vision and Image Analysis 68\u003c\/p\u003e \u003cp\u003e3.3.4 Sensor Network and IoT 68\u003c\/p\u003e \u003cp\u003e3.3.5 Weed Detection Management 68\u003c\/p\u003e \u003cp\u003e3.4 AI in Aquaculture 69\u003c\/p\u003e \u003cp\u003e3.4.1 Monitoring Water Quality 69\u003c\/p\u003e \u003cp\u003e3.4.2 Feed Management 70\u003c\/p\u003e \u003cp\u003e3.4.3 Breeding Technique 70\u003c\/p\u003e \u003cp\u003e3.4.4 Autonomous Systems and Market Optimization 70\u003c\/p\u003e \u003cp\u003e3.5 Predictive Analysis 71\u003c\/p\u003e \u003cp\u003e3.5.1 Irrigation Optimization 71\u003c\/p\u003e \u003cp\u003e3.5.2 Supply Chain Management 72\u003c\/p\u003e \u003cp\u003e3.5.3 Weather and Climate Modeling 72\u003c\/p\u003e \u003cp\u003e3.5.4 Equipment Maintenance 73\u003c\/p\u003e \u003cp\u003e3.6 Robotics and Automation in AI Agriculture 73\u003c\/p\u003e \u003cp\u003e3.6.1 Robotic Planting System 73\u003c\/p\u003e \u003cp\u003e3.6.2 Automated Irrigation Systems 74\u003c\/p\u003e \u003cp\u003e3.6.3 AI-Driven Crop Monitoring 75\u003c\/p\u003e \u003cp\u003e3.6.4 Harvesting Robots 75\u003c\/p\u003e \u003cp\u003e3.7 Livestock Monitoring 75\u003c\/p\u003e \u003cp\u003e3.7.1 Video and Image Analysis 76\u003c\/p\u003e \u003cp\u003e3.7.2 Health Monitoring 76\u003c\/p\u003e \u003cp\u003e3.7.3 Behavior Analysis 77\u003c\/p\u003e \u003cp\u003e3.7.4 Predictive Analysis 77\u003c\/p\u003e \u003cp\u003e3.7.5 Environment Analysis 77\u003c\/p\u003e \u003cp\u003e3.7.6 Disease Analysis and Prediction 78\u003c\/p\u003e \u003cp\u003e3.8 AI for Climate Smart Agriculture 78\u003c\/p\u003e \u003cp\u003e3.8.1 Climate Prediction and Weather Forecasting 79\u003c\/p\u003e \u003cp\u003e3.8.2 Enhancing Resilience to Climate Variability 79\u003c\/p\u003e \u003cp\u003e3.8.3 Water Management 80\u003c\/p\u003e \u003cp\u003e3.8.4 Reducing Greenhouse Gas Emissions 80\u003c\/p\u003e \u003cp\u003e3.8.5 Increasing Productivity and Sustainability 80\u003c\/p\u003e \u003cp\u003e3.9 AI in Agroecology 81\u003c\/p\u003e \u003cp\u003e3.9.1 Decision Support Systems 81\u003c\/p\u003e \u003cp\u003e3.9.2 Biodiversity Conservation 82\u003c\/p\u003e \u003cp\u003e3.9.3 Soil Health Management 82\u003c\/p\u003e \u003cp\u003e3.10 Soil Analysis 83\u003c\/p\u003e \u003cp\u003e3.10.1 Soil Classification 83\u003c\/p\u003e \u003cp\u003e3.10.2 Soil Nutrient Management 83\u003c\/p\u003e \u003cp\u003e3.10.3 Disease and Pest Detection 84\u003c\/p\u003e \u003cp\u003e3.10.4 Soil Moisture Monitoring 84\u003c\/p\u003e \u003cp\u003e3.10.5 Precision Agriculture 84\u003c\/p\u003e \u003cp\u003e3.10.6 Soil Erosion Prediction 85\u003c\/p\u003e \u003cp\u003e3.10.7 Soil Remediation 85\u003c\/p\u003e \u003cp\u003e3.11 Conclusion 86\u003c\/p\u003e \u003cp\u003eBibliography 87\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Integrating Artificial Intelligence into Sustainable Agriculture: Advancements, Challenges, and Applications 89\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDjamel Saba and Abdelkader Hadidi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 90\u003c\/p\u003e \u003cp\u003e4.2 Literature Review 92\u003c\/p\u003e \u003cp\u003e4.3 Key Critical Challenges of Conventional Agriculture 97\u003c\/p\u003e \u003cp\u003e4.3.1 Overview of Conventional Agriculture 97\u003c\/p\u003e \u003cp\u003e4.3.2 The Distinction Between Agriculture in the Past and Now 99\u003c\/p\u003e \u003cp\u003e4.4 AI Technologies and Sustainable Agriculture 103\u003c\/p\u003e \u003cp\u003e4.5 Artificial Intelligence’s Practical Use in Farming 104\u003c\/p\u003e \u003cp\u003e4.6 Challenges and Ethical Considerations 107\u003c\/p\u003e \u003cp\u003e4.6.1 Challenges 107\u003c\/p\u003e \u003cp\u003e4.6.1.1 Data Privacy and Security 107\u003c\/p\u003e \u003cp\u003e4.6.1.2 Accessibility and Inclusivity 107\u003c\/p\u003e \u003cp\u003e4.6.1.3 Algorithm Bias 107\u003c\/p\u003e \u003cp\u003e4.6.1.4 Interoperability and Standardization 107\u003c\/p\u003e \u003cp\u003e4.6.1.5 Job Displacement 108\u003c\/p\u003e \u003cp\u003e4.6.2 Ethical Considerations 108\u003c\/p\u003e \u003cp\u003e4.6.2.1 Transparency and Accountability 108\u003c\/p\u003e \u003cp\u003e4.6.2.2 Environmental Impact 108\u003c\/p\u003e \u003cp\u003e4.6.2.3 Informed Consent 108\u003c\/p\u003e \u003cp\u003e4.6.2.4 Fair Distribution of Benefits 109\u003c\/p\u003e \u003cp\u003e4.6.2.5 Long-Term Sustainability 109\u003c\/p\u003e \u003cp\u003e4.7 Conclusions and Further Work 109\u003c\/p\u003e \u003cp\u003eReferences 110\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Artificial Intelligence for Sustainable and Smart Agriculture 117\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDjamel Saba and Abdelkader Hadidi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 118\u003c\/p\u003e \u003cp\u003e5.2 Literature Review 120\u003c\/p\u003e \u003cp\u003e5.3 AI Techniques for Revolutionizing Traditional Farming 125\u003c\/p\u003e \u003cp\u003e5.4 Role of the IoT in Smart Farms 128\u003c\/p\u003e \u003cp\u003e5.4.1 Smart Farming Technologies 130\u003c\/p\u003e \u003cp\u003e5.4.1.1 Precision Agriculture 130\u003c\/p\u003e \u003cp\u003e5.4.1.2 Livestock Monitoring 130\u003c\/p\u003e \u003cp\u003e5.4.1.3 Crop Monitoring 130\u003c\/p\u003e \u003cp\u003e5.4.2 Climate Management and Weather Forecasting 130\u003c\/p\u003e \u003cp\u003e5.4.3 Supply Chain Optimization 131\u003c\/p\u003e \u003cp\u003e5.4.4 Analytics and Assistance for Decision-Making 131\u003c\/p\u003e \u003cp\u003e5.4.5 The Advantages and Difficulties of IoT in Agriculture 131\u003c\/p\u003e \u003cp\u003e5.4.5.1 Advantages 131\u003c\/p\u003e \u003cp\u003e5.4.5.2 Difficulties 131\u003c\/p\u003e \u003cp\u003e5.5 Environmental Concerns Related to Agriculture 132\u003c\/p\u003e \u003cp\u003e5.5.1 Environmental Concerns Related to Sustainable Agriculture 132\u003c\/p\u003e \u003cp\u003e5.5.2 Environmental Concerns Related to Smart Agriculture 132\u003c\/p\u003e \u003cp\u003e5.6 Challenges and Considerations 135\u003c\/p\u003e \u003cp\u003e5.7 Conclusions and Further Work 137\u003c\/p\u003e \u003cp\u003eReferences 142\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Data-Driven Approaches for Sustainable Agriculture and Food Security 145\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eS.C. Vetrivel, V. Sabareeshwari, K.C. Sowmiya and V.P. Arun\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 146\u003c\/p\u003e \u003cp\u003e6.1.1 The Role of Data in Agriculture 146\u003c\/p\u003e \u003cp\u003e6.1.2 Importance of Sustainability and Food Security 147\u003c\/p\u003e \u003cp\u003e6.1.3 Overview of Data-Driven Technologies 148\u003c\/p\u003e \u003cp\u003e6.2 Big Data in Agriculture 150\u003c\/p\u003e \u003cp\u003e6.2.1 Definition and Characteristics of Big Data 150\u003c\/p\u003e \u003cp\u003e6.2.2 Applications of Big Data in Agriculture 151\u003c\/p\u003e \u003cp\u003e6.2.3 Challenges and Opportunities 152\u003c\/p\u003e \u003cp\u003e6.2.3.1 Challenges 152\u003c\/p\u003e \u003cp\u003e6.2.3.2 Opportunities 153\u003c\/p\u003e \u003cp\u003e6.3 Internet of Things (IoT) in Agriculture 154\u003c\/p\u003e \u003cp\u003e6.3.1 Understanding IoT and Its Components 154\u003c\/p\u003e \u003cp\u003e6.3.2 IoT Applications in Farming 155\u003c\/p\u003e \u003cp\u003e6.3.3 Benefits and Challenges of IoT Implementation 156\u003c\/p\u003e \u003cp\u003e6.4 Artificial Intelligence and Machine Learning in Agriculture 157\u003c\/p\u003e \u003cp\u003e6.4.1 Fundamentals of AI and Machine Learning 157\u003c\/p\u003e \u003cp\u003e6.4.2 AI and ML Applications in Crop Monitoring and Management 158\u003c\/p\u003e \u003cp\u003e6.4.3 Predictive Analytics for Yield Optimization 159\u003c\/p\u003e \u003cp\u003e6.5 Remote Sensing and GIS in Agriculture 159\u003c\/p\u003e \u003cp\u003e6.5.1 Remote Sensing Technologies Overview 159\u003c\/p\u003e \u003cp\u003e6.5.2 GIS Mapping for Precision Agriculture 160\u003c\/p\u003e \u003cp\u003e6.5.3 Monitoring Environmental Impact and Land Use 161\u003c\/p\u003e \u003cp\u003e6.6 Data-Driven Approaches for Sustainable Crop Management 162\u003c\/p\u003e \u003cp\u003e6.6.1 Precision Agriculture Techniques 162\u003c\/p\u003e \u003cp\u003e6.6.2 Crop Disease Detection and Management 162\u003c\/p\u003e \u003cp\u003e6.6.3 Water Management and Irrigation Systems 163\u003c\/p\u003e \u003cp\u003e6.7 Data-Driven Livestock Management 163\u003c\/p\u003e \u003cp\u003e6.7.1 Monitoring Animal Health and Welfare 163\u003c\/p\u003e \u003cp\u003e6.7.2 Precision Livestock Farming 164\u003c\/p\u003e \u003cp\u003e6.7.3 Sustainable Feed Management 164\u003c\/p\u003e \u003cp\u003e6.8 Supply Chain Management and Food Security 165\u003c\/p\u003e \u003cp\u003e6.8.1 Traceability and Transparency in the Food Supply Chain 165\u003c\/p\u003e \u003cp\u003e6.8.2 Data-Driven Approaches for Food Distribution 165\u003c\/p\u003e \u003cp\u003e6.8.3 Enhancing Food Security through Data Analytics 166\u003c\/p\u003e \u003cp\u003e6.9 Policy Implications and Ethical Considerations 167\u003c\/p\u003e \u003cp\u003e6.9.1 Regulatory Frameworks for Data-Driven Agriculture 167\u003c\/p\u003e \u003cp\u003e6.9.2 Ethical Issues Surrounding Data Collection and Privacy 167\u003c\/p\u003e \u003cp\u003e6.9.3 Balancing Innovation with Social Responsibility 168\u003c\/p\u003e \u003cp\u003e6.10 Future Trends and Conclusion 168\u003c\/p\u003e \u003cp\u003e6.10.1 Emerging Technologies and Trends 168\u003c\/p\u003e \u003cp\u003e6.10.2 Potential Impact on Sustainable Agriculture and Food Security 169\u003c\/p\u003e \u003cp\u003e6.11 Conclusion 170\u003c\/p\u003e \u003cp\u003eReferences 170\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II: Recent Developments in Crop Disease Detection and Prevention 175\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Advances in Plant Disease Detection and Classification Systems 177\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBhakti Sanket Puranik, Karanbir Singh Pelia, Shrivatsasingh Khushal Rathore and Vaibhav Vikas Dighe\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 178\u003c\/p\u003e \u003cp\u003e7.2 Literature Review 179\u003c\/p\u003e \u003cp\u003e7.3 Methodologies and Techniques 185\u003c\/p\u003e \u003cp\u003e7.3.1 CNN Architectures 185\u003c\/p\u003e \u003cp\u003e7.3.2 Activation Functions 186\u003c\/p\u003e \u003cp\u003e7.3.3 Loss Functions 187\u003c\/p\u003e \u003cp\u003e7.3.4 Learning Rate Schedulers 187\u003c\/p\u003e \u003cp\u003e7.3.5 Early Stopping 188\u003c\/p\u003e \u003cp\u003e7.3.6 Checkpoints and Callbacks 188\u003c\/p\u003e \u003cp\u003e7.3.7 Data Preprocessing 189\u003c\/p\u003e \u003cp\u003e7.3.8 Data Augmentation 189\u003c\/p\u003e \u003cp\u003e7.3.9 Transfer Learning 190\u003c\/p\u003e \u003cp\u003e7.3.10 Ensemble Learning 191\u003c\/p\u003e \u003cp\u003e7.4 Challenges and Limitations 191\u003c\/p\u003e \u003cp\u003e7.4.1 Dataset Scarcity 192\u003c\/p\u003e \u003cp\u003e7.4.2 Image Variability 192\u003c\/p\u003e \u003cp\u003e7.4.3 Label Inconsistency 193\u003c\/p\u003e \u003cp\u003e7.4.4 Model Interpretability 193\u003c\/p\u003e \u003cp\u003e7.5 Proposed Model 194\u003c\/p\u003e \u003cp\u003e7.5.1 Model Architecture 195\u003c\/p\u003e \u003cp\u003e7.5.2 Training Mechanism 196\u003c\/p\u003e \u003cp\u003e7.6 Future Scope 198\u003c\/p\u003e \u003cp\u003e7.6.1 Development of Comprehensive Datasets 199\u003c\/p\u003e \u003cp\u003e7.6.2 Exploration of Novel Architectures 199\u003c\/p\u003e \u003cp\u003e7.6.3 Integration of Advanced Technologies 200\u003c\/p\u003e \u003cp\u003e7.6.4 Crowdsourcing New Data 201\u003c\/p\u003e \u003cp\u003e7.6.5 Adaptation and Interaction 201\u003c\/p\u003e \u003cp\u003e7.6.6 Integrated Remediation Strategies 202\u003c\/p\u003e \u003cp\u003e7.7 Conclusion 203\u003c\/p\u003e \u003cp\u003eReferences 204\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Ensemble-Based Crop Disease Biomarker Multi-Domain Feature Analysis (ECDBMFA) 207\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eChilakalapudi Malathi and Sheela J.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 208\u003c\/p\u003e \u003cp\u003e8.2 Literature Survey 208\u003c\/p\u003e \u003cp\u003e8.3 Design of ECDBMFA 210\u003c\/p\u003e \u003cp\u003e8.4 Result Evaluation and Comparative Analysis with Existing Techniques 217\u003c\/p\u003e \u003cp\u003e8.5 Conclusion 226\u003c\/p\u003e \u003cp\u003eReferences 226\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Artificial Intelligence and Machine Learning in Crop Yield Prediction and Pest Control 231\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eArchana Negi, Jitendra Singh, Robin Kumar, Atin Kumar, Nisha and Sharad Sachan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 232\u003c\/p\u003e \u003cp\u003eArtificial Intelligence 234\u003c\/p\u003e \u003cp\u003eMachine Learning 235\u003c\/p\u003e \u003cp\u003eAI-Based ML Algorithm Models 237\u003c\/p\u003e \u003cp\u003eSome Important Evaluation Metrics Used in AI-Based Predictive Models 239\u003c\/p\u003e \u003cp\u003eApplications of Artificial Intelligence and Machine Learning in Crop Yield Prediction Models 241\u003c\/p\u003e \u003cp\u003eAI-Based Crop Yield Prediction Method—Case Study 242\u003c\/p\u003e \u003cp\u003eSteps for Crop Yield Prediction 243\u003c\/p\u003e \u003cp\u003eApplications of Artificial Intelligence and Machine Learning in Pest and Disease Management 244\u003c\/p\u003e \u003cp\u003eAdvantages of Using Artificial Intelligence\/Machine Learning in Agriculture 248\u003c\/p\u003e \u003cp\u003eChallenges of Artificial Intelligence and Machine Learning Application in Agriculture 249\u003c\/p\u003e \u003cp\u003eConclusion and Future Prospects 250\u003c\/p\u003e \u003cp\u003eReferences 250\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Farming in the Digital Age: A Machine Learning Enhanced Crop Yield Prediction and Recommendation System 257\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eArti Sonawane, Akanksha Ranade, Apurva Kolte, Siddharth Daundkar and Shreyas Rajage\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Background 258\u003c\/p\u003e \u003cp\u003e10.2 Introduction 260\u003c\/p\u003e \u003cp\u003e10.3 Importance 261\u003c\/p\u003e \u003cp\u003e10.4 Machine Learning in Agriculture 262\u003c\/p\u003e \u003cp\u003e10.5 Objectives 267\u003c\/p\u003e \u003cp\u003e10.6 Related Work 267\u003c\/p\u003e \u003cp\u003e10.6.1 Research Gaps 276\u003c\/p\u003e \u003cp\u003e10.7 Proposed Methodology 277\u003c\/p\u003e \u003cp\u003e10.7.1 Data Collection 277\u003c\/p\u003e \u003cp\u003e10.7.2 Data Preprocessing 277\u003c\/p\u003e \u003cp\u003e10.7.3 Training and Testing Model 278\u003c\/p\u003e \u003cp\u003e10.7.4 Decision Tree Repressor 278\u003c\/p\u003e \u003cp\u003e10.7.5 Random Forest Regressor 279\u003c\/p\u003e \u003cp\u003e10.8 Implications for Farmers 282\u003c\/p\u003e \u003cp\u003e10.9 Future Directions 284\u003c\/p\u003e \u003cp\u003e10.10 Conclusion 285\u003c\/p\u003e \u003cp\u003eReferences 285\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III: IoT and Modern Agriculture 289\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Digital Agriculture: IoT Applications and Technological Advancement 291\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eK. Aditya Shastry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 292\u003c\/p\u003e \u003cp\u003e11.2 Related Work 296\u003c\/p\u003e \u003cp\u003e11.3 Emerging Technologies and Related Applications in Smart Agriculture 299\u003c\/p\u003e \u003cp\u003e11.3.1 Internet of Things (IoT) in Agriculture 300\u003c\/p\u003e \u003cp\u003e11.3.2 Artificial Intelligence (AI) and Machine Learning (ml) 300\u003c\/p\u003e \u003cp\u003e11.3.3 Remote Sensing (RS) and Satellite Technology 302\u003c\/p\u003e \u003cp\u003e11.3.4 Blockchain Technology 305\u003c\/p\u003e \u003cp\u003e11.3.5 Robotics and Automation 309\u003c\/p\u003e \u003cp\u003e11.3.6 Sustainable Agriculture Practices 310\u003c\/p\u003e \u003cp\u003e11.4 Challenges in Smart Farming 315\u003c\/p\u003e \u003cp\u003e11.5 Future Trends in Smart Farming 317\u003c\/p\u003e \u003cp\u003e11.6 Conclusion 320\u003c\/p\u003e \u003cp\u003eReferences 320\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 IoT in Climate-Smart Farming 323\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMaitreyi Darbha, S. V. Sanjay Kumar, S. R. Mani Sekhar and Sanjay H. A.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 323\u003c\/p\u003e \u003cp\u003e12.2 IoT in Agriculture 325\u003c\/p\u003e \u003cp\u003e12.2.1 What is IoT? 325\u003c\/p\u003e \u003cp\u003e12.2.2 Methods Involved in the Incorporation of IoT in Agriculture 325\u003c\/p\u003e \u003cp\u003e12.2.2.1 Greenhouse Farming 325\u003c\/p\u003e \u003cp\u003e12.2.2.2 Vertical Farming 326\u003c\/p\u003e \u003cp\u003e12.2.2.3 Hydroponics 326\u003c\/p\u003e \u003cp\u003e12.2.2.4 Phenotyping 327\u003c\/p\u003e \u003cp\u003e12.2.3 Resources Required for the Incorporation 328\u003c\/p\u003e \u003cp\u003e12.3 Climate-Smart Farming Practices 329\u003c\/p\u003e \u003cp\u003e12.3.1 What is Climate-Smart Farming? 329\u003c\/p\u003e \u003cp\u003e12.3.2 Integration of IoT 330\u003c\/p\u003e \u003cp\u003e12.3.2.1 Precision Farming 330\u003c\/p\u003e \u003cp\u003e12.3.2.2 Smart Irrigation 331\u003c\/p\u003e \u003cp\u003e12.3.2.3 Crop Monitoring 331\u003c\/p\u003e \u003cp\u003e12.3.2.4 Livestock Management 331\u003c\/p\u003e \u003cp\u003e12.3.3 Environmental Impact and Resilience to Climate Change 332\u003c\/p\u003e \u003cp\u003e12.4 Case Studies 333\u003c\/p\u003e \u003cp\u003e12.4.1 IoT Applications in Precision Agriculture 333\u003c\/p\u003e \u003cp\u003e12.4.1.1 Weather Monitoring 333\u003c\/p\u003e \u003cp\u003e12.4.1.2 Soil Content Monitoring 333\u003c\/p\u003e \u003cp\u003e12.4.1.3 Diseases Monitoring 334\u003c\/p\u003e \u003cp\u003e12.4.2 IoT Applications in Greenhouse 334\u003c\/p\u003e \u003cp\u003e12.5 Evaluation of IoT Technologies 336\u003c\/p\u003e \u003cp\u003e12.5.1 Effectiveness of IoT Technologies 336\u003c\/p\u003e \u003cp\u003e12.5.2 Comparison with Traditional Methods 336\u003c\/p\u003e \u003cp\u003e12.5.3 Advantages and Disadvantages 337\u003c\/p\u003e \u003cp\u003e12.6 Relevance to Current-Day Global Issues 338\u003c\/p\u003e \u003cp\u003e12.6.1 Future Scope 338\u003c\/p\u003e \u003cp\u003e12.7 Conclusion 339\u003c\/p\u003e \u003cp\u003eReferences 340\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV: Technological Trends and Advancements in the Agricultural Sector 345\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Sustainable Agriculture Practices with ICT for Soil Health Management 347\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBhabani Prasad Mondal, Anshuman Kohli, Ingle Sagar Nandulal, Roheet Bhatnagar, Chandan Kumar Panda, Sonal Kumari, Bharat Lal, Sai Parasar Das, Chandrabhan Patel, Vimal Kumar, Achin Kumar, Karad Gaurav Uttamrao, Suman Dutta and Ali R.A. Moursy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 348\u003c\/p\u003e \u003cp\u003e13.2 Advanced ICT Technologies 350\u003c\/p\u003e \u003cp\u003e13.2.1 Gps 350\u003c\/p\u003e \u003cp\u003e13.2.2 Gis 351\u003c\/p\u003e \u003cp\u003e13.2.3 Dss 352\u003c\/p\u003e \u003cp\u003e13.2.4 Remote Sensing 352\u003c\/p\u003e \u003cp\u003e13.2.5 IoT 353\u003c\/p\u003e \u003cp\u003e13.2.6 Sensor Technology 354\u003c\/p\u003e \u003cp\u003e13.2.7 Grid Soil Sampling and Variable Rate Technology (vrt) 356\u003c\/p\u003e \u003cp\u003e13.2.8 Agricultural Robotics 357\u003c\/p\u003e \u003cp\u003e13.3 Application of ICT in Soil Health Management 358\u003c\/p\u003e \u003cp\u003e13.3.1 Artificial Intelligence in Analyzing Soil Health Parameters 358\u003c\/p\u003e \u003cp\u003e13.3.1.1 Data Collection 358\u003c\/p\u003e \u003cp\u003e13.3.1.2 Data Preprocessing 358\u003c\/p\u003e \u003cp\u003e13.3.1.3 Feature Selection 358\u003c\/p\u003e \u003cp\u003e13.3.1.4 Model Training 359\u003c\/p\u003e \u003cp\u003e13.3.1.5 Model Validation 359\u003c\/p\u003e \u003cp\u003e13.3.1.6 Soil Health Parameter Prediction 359\u003c\/p\u003e \u003cp\u003e13.3.2 Fertilizer Recommendation Using ICT 359\u003c\/p\u003e \u003cp\u003e13.3.2.1 Soil App 360\u003c\/p\u003e \u003cp\u003e13.3.2.2 Multimodal DSS in Soil Fertility Management 360\u003c\/p\u003e \u003cp\u003e13.3.3 Smart Soil Health Management Using Sensor-Based Technology 362\u003c\/p\u003e \u003cp\u003e13.3.3.1 Sensor Selection 362\u003c\/p\u003e \u003cp\u003e13.3.3.2 Sensor Placement 362\u003c\/p\u003e \u003cp\u003e13.3.3.3 Data Collection 362\u003c\/p\u003e \u003cp\u003e13.3.3.4 Data Processing 362\u003c\/p\u003e \u003cp\u003e13.3.4 Real-Time Monitoring 363\u003c\/p\u003e \u003cp\u003e13.3.4.1 Sensors’ Efficiency Evaluation 363\u003c\/p\u003e \u003cp\u003e13.3.5 Satellite and Drone-Based Remote Sensing Technology in Soil Health Management 363\u003c\/p\u003e \u003cp\u003e13.3.6 ICT-Based Soil Conservation for Soil Health Management 364\u003c\/p\u003e \u003cp\u003e13.3.7 Autonomous Robots in Efficient Soil Health Management 365\u003c\/p\u003e \u003cp\u003e13.4 Challenges in Implementing ICT-Based Technologies 365\u003c\/p\u003e \u003cp\u003e13.4.1 Lack of Availability of Accurate Data 365\u003c\/p\u003e \u003cp\u003e13.4.2 High Cost of Technology and Higher Investment 366\u003c\/p\u003e \u003cp\u003e13.4.3 Lack of Sound Skill and Knowledge of Farmers 366\u003c\/p\u003e \u003cp\u003e13.4.4 Lack of Communication Structure and Support 367\u003c\/p\u003e \u003cp\u003e13.4.5 Low-Risk–Bearing Capacity of Farmers 367\u003c\/p\u003e \u003cp\u003e13.5 Opportunities or Pathways to Tackle the Issues in ICT-Based Soil Management 367\u003c\/p\u003e \u003cp\u003e13.6 Conclusion 369\u003c\/p\u003e \u003cp\u003eAcknowledgment 370\u003c\/p\u003e \u003cp\u003eReferences 370\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Water Resource Management Model for Smart Agriculture 375\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAysulu Aydarova\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 375\u003c\/p\u003e \u003cp\u003eMain Part 376\u003c\/p\u003e \u003cp\u003eConclusion 397\u003c\/p\u003e \u003cp\u003eReferences 398\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 A Big Data Analytics–Based Architecture for Smart Farming 399\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eTanvi Chawla, Tamanna Gahlawat and TanyaShree Thakur\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 400\u003c\/p\u003e \u003cp\u003e15.2 Related Work 402\u003c\/p\u003e \u003cp\u003e15.3 Research Issues in Big Data for Smart Agriculture 404\u003c\/p\u003e \u003cp\u003e15.4 Applications of Big Data Analytics in Smart Agriculture 405\u003c\/p\u003e \u003cp\u003e15.5 Types of Big Data in Agriculture 407\u003c\/p\u003e \u003cp\u003e15.6 Proposed Work 408\u003c\/p\u003e \u003cp\u003e15.7 Conclusion and Future Work 414\u003c\/p\u003e \u003cp\u003eReferences 414\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Adoption of Blockchain Technology for Transparent and Secure Agricultural Transactions 417\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eS.C. Vetrivel, V. Sabareeshwari, K.C. Sowmiya and V.P. Arun\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction to Blockchain Technology 418\u003c\/p\u003e \u003cp\u003e16.1.1 Definition and Overview 418\u003c\/p\u003e \u003cp\u003e16.1.2 Evolution of Blockchain 418\u003c\/p\u003e \u003cp\u003e16.1.3 Basic Components and Principles 419\u003c\/p\u003e \u003cp\u003e16.1.4 Blockchain’s Significance in Agriculture 419\u003c\/p\u003e \u003cp\u003e16.2 Challenges in Traditional Agricultural Transactions 420\u003c\/p\u003e \u003cp\u003e16.2.1 Lack of Transparency 420\u003c\/p\u003e \u003cp\u003e16.2.2 Security Issues 420\u003c\/p\u003e \u003cp\u003e16.2.3 Trust Deficit 421\u003c\/p\u003e \u003cp\u003e16.2.4 Inefficiencies in Supply Chain 421\u003c\/p\u003e \u003cp\u003e16.3 Understanding Blockchain Solutions 422\u003c\/p\u003e \u003cp\u003e16.3.1 How Blockchain Operates 422\u003c\/p\u003e \u003cp\u003e16.3.2 Types of Blockchain 423\u003c\/p\u003e \u003cp\u003e16.3.3 Smart Contracts and Their Role 424\u003c\/p\u003e \u003cp\u003e16.3.4 Benefits of Blockchain in Agriculture 425\u003c\/p\u003e \u003cp\u003e16.4 Use Cases of Blockchain in Agriculture 427\u003c\/p\u003e \u003cp\u003e16.4.1 Produce Traceability 427\u003c\/p\u003e \u003cp\u003e16.4.1.1 Tracking Farm to Fork 427\u003c\/p\u003e \u003cp\u003e16.4.1.2 Quality Assurance 427\u003c\/p\u003e \u003cp\u003e16.4.2 Supply Chain Management 428\u003c\/p\u003e \u003cp\u003e16.4.2.1 Inventory Tracking 428\u003c\/p\u003e \u003cp\u003e16.4.2.2 Real-Time Monitoring 428\u003c\/p\u003e \u003cp\u003e16.4.3 Payment and Financing Solutions 428\u003c\/p\u003e \u003cp\u003e16.4.3.1 Microfinancing for Farmers 428\u003c\/p\u003e \u003cp\u003e16.4.3.2 Instant and Secure Payments 430\u003c\/p\u003e \u003cp\u003e16.5 Implementing Blockchain in Agriculture 430\u003c\/p\u003e \u003cp\u003e16.5.1 Infrastructure Requirements 430\u003c\/p\u003e \u003cp\u003e16.5.2 Data Management and Integration 432\u003c\/p\u003e \u003cp\u003e16.5.3 Regulatory Considerations 432\u003c\/p\u003e \u003cp\u003e16.5.4 Challenges in Adoption 432\u003c\/p\u003e \u003cp\u003e16.6 Case Studies and Success Stories 434\u003c\/p\u003e \u003cp\u003e16.6.1 IBM Food Trust 434\u003c\/p\u003e \u003cp\u003e16.6.2 Provenance 434\u003c\/p\u003e \u003cp\u003e16.6.3 AgriDigital 434\u003c\/p\u003e \u003cp\u003e16.7 Future Trends and Opportunities 435\u003c\/p\u003e \u003cp\u003e16.7.1 Integration with IoT and AI 435\u003c\/p\u003e \u003cp\u003e16.7.2 Expansion of Blockchain Applications 435\u003c\/p\u003e \u003cp\u003e16.7.3 Potential Impact on Global Food Security 437\u003c\/p\u003e \u003cp\u003e16.8 Conclusion 439\u003c\/p\u003e \u003cp\u003eReferences 439\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 AI-Assisted Environmental Parameter Monitoring of Plants in Greenhouse Farming 445\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eK. Sujatha, N.P.G. Bhavani, R. S. Ponmagal, N. Shanmugasundaram, C. Tamilselvi, A. Ganesan and Suqun Cao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 446\u003c\/p\u003e \u003cp\u003e17.2 Background 447\u003c\/p\u003e \u003cp\u003e17.3 Importance of Smart Agriculture 448\u003c\/p\u003e \u003cp\u003e17.4 Artificial Neural Network (ANN) 449\u003c\/p\u003e \u003cp\u003e17.4.1 Mayfly Optimization 451\u003c\/p\u003e \u003cp\u003e17.5 Problem Statement 453\u003c\/p\u003e \u003cp\u003e17.6 Objectives 454\u003c\/p\u003e \u003cp\u003e17.7 Strategy for Polyhouse Monitoring 454\u003c\/p\u003e \u003cp\u003e17.8 Results and Discussion 460\u003c\/p\u003e \u003cp\u003e17.9 Conclusion 467\u003c\/p\u003e \u003cp\u003eReferences 469\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Metaverse in Agricultural Training and Simulation 471\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSyed Quadir Moinuddin, Himam Saheb Shaik, md Atiqur Rahman and Borigorla Venu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 471\u003c\/p\u003e \u003cp\u003e18.2 AI in Agriculture 473\u003c\/p\u003e \u003cp\u003e18.3 Metaverse 475\u003c\/p\u003e \u003cp\u003e18.3.1 Agriculture with AI-Based Metaverse 476\u003c\/p\u003e \u003cp\u003e18.4 Augmented Reality (AR) 478\u003c\/p\u003e \u003cp\u003e18.5 Virtual Reality (VR) 480\u003c\/p\u003e \u003cp\u003e18.6 Mixed Reality (MR) 482\u003c\/p\u003e \u003cp\u003e18.7 Agriculture Training Simulations 485\u003c\/p\u003e \u003cp\u003e18.8 Metaverse in Agriculture Trainings 487\u003c\/p\u003e \u003cp\u003e18.9 Conclusions 488\u003c\/p\u003e \u003cp\u003eAcknowledgment 489\u003c\/p\u003e \u003cp\u003eReferences 489\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Sustainable Farming in the Digital Era: AI and IoT Technologies Transforming Agriculture 493\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eArti Sonawane, Suvarna Patil and Atul Kathole\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 494\u003c\/p\u003e \u003cp\u003e19.1.1 The Role of Artificial Intelligence in Agriculture 495\u003c\/p\u003e \u003cp\u003e19.1.2 The Role of the Internet of Things in Agriculture 495\u003c\/p\u003e \u003cp\u003e19.1.3 The Intersection of AI and IoT in Agriculture 496\u003c\/p\u003e \u003cp\u003e19.1.4 The Importance of Sustainability in Agriculture 496\u003c\/p\u003e \u003cp\u003e19.1.5 Problem Statement 497\u003c\/p\u003e \u003cp\u003e19.1.6 Motivation 497\u003c\/p\u003e \u003cp\u003e19.1.7 Objective 497\u003c\/p\u003e \u003cp\u003e19.2 Related Work 498\u003c\/p\u003e \u003cp\u003e19.2.1 Comparative Analysis of Existing Challenges 499\u003c\/p\u003e \u003cp\u003e19.2.1.1 Precision Agriculture: Challenges in Future IoT (2023) 501\u003c\/p\u003e \u003cp\u003e19.2.1.2 AI-Driven Precision Agriculture: Challenges and Perspectives (2023) 502\u003c\/p\u003e \u003cp\u003e19.2.1.3 IoT and AI in Agriculture: An Overview (2022) 502\u003c\/p\u003e \u003cp\u003e19.2.1.4 Smart Farming with IoT and AI: Benefits and Challenges (2022) 502\u003c\/p\u003e \u003cp\u003e19.2.1.5 AI and IoT-Based Crop Monitoring: A Review (2023) 502\u003c\/p\u003e \u003cp\u003e19.2.1.6 Integration of AI and IoT in Agriculture: State-of-the-Art and Future Trends (2023) 502\u003c\/p\u003e \u003cp\u003e19.2.1.7 Sustainable Agriculture: The Role of IoT and AI (2022) 503\u003c\/p\u003e \u003cp\u003e19.2.1.8 Advances in IoT and AI for Precision Agriculture (2022) 503\u003c\/p\u003e \u003cp\u003e19.3 Discussion of Proposed Approach 503\u003c\/p\u003e \u003cp\u003e19.3.1 System Architecture 504\u003c\/p\u003e \u003cp\u003e19.3.2 Components and Tools 505\u003c\/p\u003e \u003cp\u003e19.3.3 Result and Discussion 506\u003c\/p\u003e \u003cp\u003e19.4 Application 508\u003c\/p\u003e \u003cp\u003e19.5 Advantages and Disadvantages of System 509\u003c\/p\u003e \u003cp\u003e19.6 Conclusion 510\u003c\/p\u003e \u003cp\u003eFuture Scope 510\u003c\/p\u003e \u003cp\u003eReferences 511\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Precision Agriculture with Unmanned Aerial Vehicles 513\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSuresh S., Sampath Boopathi, Elayaraja R., Velmurugan D. and Selvapriya R.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 514\u003c\/p\u003e \u003cp\u003e20.2 Agri-UAV Construction and Controls 516\u003c\/p\u003e \u003cp\u003e20.3 Applications of UAVs in Agriculture 519\u003c\/p\u003e \u003cp\u003e20.3.1 Crop Spraying 520\u003c\/p\u003e \u003cp\u003e20.3.2 Crop Health Monitoring 524\u003c\/p\u003e \u003cp\u003e20.3.3 Drone Seeding 527\u003c\/p\u003e \u003cp\u003e20.4 Conclusion 529\u003c\/p\u003e \u003cp\u003eReferences 530\u003c\/p\u003e \u003cp\u003eIndex 535\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Agriculture \u0026amp; farming [\u003ca title=\"See our other books on Agriculture \u0026amp; farming\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Agriculture%20\u0026amp;%20farming%20%5BTV%5D%22\"\u003eTV\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433291903256,"sku":"9781394287239","price":163.59,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394287239.jpg?v=1784853172","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/optimizing-ai-applications-for-sustainable-agriculture-hardback-9781394287239","provider":"Freshly Printed Books","version":"1.0","type":"link"}