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Bring the latest technology to bear in the fight for sustainable agriculture with this timely volume Artificial intelligence (AI) has the potential to revolutionize virtually every area of research and scientific practice, including agriculture. With AI solutions emerging to drive higher yields, produce increased resource efficiency, and foster sustainability, there is an urgent need for a volume outlining this progress and charting its future course. Emerging Smart Agricultural Practices Using Artificial Intelligence meets this need with a deep dive into the rapidly developing…mehr
Bring the latest technology to bear in the fight for sustainable agriculture with this timely volume
Artificial intelligence (AI) has the potential to revolutionize virtually every area of research and scientific practice, including agriculture. With AI solutions emerging to drive higher yields, produce increased resource efficiency, and foster sustainability, there is an urgent need for a volume outlining this progress and charting its future course.
Emerging Smart Agricultural Practices Using Artificial Intelligence meets this need with a deep dive into the rapidly developing intersection of agriculture and artificial intelligence. Taking an interdisciplinary approach which applies data science, computer science, and engineering techniques, the book provides cutting-edge insights on the latest advancements in AI-driven agricultural practices. The result is an absolutely critical tool in the ongoing fight to develop sustainable world agriculture.
In addition, this book provides:
Case studies and real-world applications of new techniques throughout
Detailed discussion of agricultural applications for AI-driven technologies such as machine learning, computer vision, and data analytics
A regional approach showcasing international best practices and addressing the varying needs of farmers worldwide
Emerging Smart Agricultural Practices Using Artificial Intelligence is ideal for agricultural professionals and scientists, as well as data scientists, technologists, and agricultural policymakers.
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Autorenporträt
Ashish Kumar, PhD, is an Associate Professor with Bennett University, Greater Noida, U.P. India. He has published widely on subjects including object tracking, image processing, artificial intelligence, and medical imaging analysis, and is a member of the IEEE. Jai Prakash Verma, PhD, is an Associate Professor in the Department of Computer Science and Engineering, Nirma University, Ahmedabad, India. He offers customized training on big data analytics to the Indian Navy, SAC-ISRO scientists in Ahmedabad, and other experts from industry and academia. Rachna Jain, PhD, is an Associate Professor in the Department of Information Technology Bhagwan Parshuram Institute of Technology. She has 18+ years of academic/research experience with more than 100+ publications in various international conferences and international journals (Scopus/ISI/SCI) of high repute.
Inhaltsangabe
About the Editors xvii List of Contributors xix Preface xxiii 1 Agricultural Resilience: Water Quality and Human Well-Being 1 Tanu Taneja, B.S Bhatia, and Shalom Akhai 1.1 Introduction 1 1.2 The Nexus of Water Quality and Agriculture 2 1.3 Impact of Contaminated Water on Crop Health 2 1.4 AI-Driven Water Monitoring Systems 4 1.5 Research Gaps and Research Dimensions 6 1.6 Precision Irrigation Techniques 7 1.7 Waterborne Pathogens in Farming 8 1.8 Livestock Health and Water Safety 8 1.9 Sustainable Water Management Strategies 9 1.10 Human Health Implications 11 1.11 Significance of Research in Agricultural Water Quality 12 1.12 Conclusion 12 2 Precision Farming: A Technological Revolution for Sustainable Agriculture 25 Ashish Kumar, Prasoon Kumar Pandey, and Divya Singh 2.1 Introduction 25 2.2 Principles of Precision Farming 27 2.3 Technologies in Precision Farming 28 2.4 Role of Drones in Precision Farming 35 2.5 Benefits of Precision Farming 37 2.6 Conclusion 40 3 Precision Farming and Smart Crop Management 45 Bhavin Patel, Jitendra Bhatia, and Malaram Kumhar 3.1 Introduction 45 3.2 Related Work 46 3.3 Technologies in Precision Farming 47 3.4 Smart Crop Management Techniques 58 3.5 Mapping to Site-Specific Applications 59 3.6 Challenges and Limitations 62 3.7 Conclusion 66 4 Empowering Smart Agriculture with Artificial Intelligence 71 Shipra Raheja and Himanshi Bansal 4.1 Introduction 71 4.2 Benefits of AI in Agriculture 72 4.3 Applications of Artificial Intelligence in Agriculture 74 4.4 Part of AI Within the Farming Data Administration Cycle 76 4.5 Optimizing AI for Farming and Agrarian Forms 78 4.6 AI's Limitations with Regard to Agriculture 79 4.7 Future of AI in Agriculture 81 4.8 The Future Research of AI in Small-Scale Farming 82 5 Foundations of Agricultural AI 87 Divya Singh, Naman Agrawal, Jaya Saini, and Manoranjan Kumar 5.1 Introduction 87 5.2 Machine Learning 91 5.3 Deep Learning 91 5.4 Applications of AI in Agriculture 92 5.5 Challenges and Opportunities 94 5.6 Ethical and Social Implications 96 5.7 Current Trends and Future Directions 98 5.8 Conclusion 100 6 AI in Agriculture: A Comprehensive Exploration of Technological Transformation 105 Manya Gupta, Gargi Mishra, Supriya Bajpai, Abhinav Bhardwaj, and Milind Gautam 6.1 Introduction 105 6.2 AI Integration in Agricultural Practices 108 6.3 AI-Monitored Agricultural Parameters 110 6.4 Application Areas of AI in Agriculture 112 6.5 Limitations 120 6.6 Conclusion and Future Scope 124 7 Integrating AI and Climate-Smart Agricultural Mechanization: Strategies for Enhancing Productivity and Sustainability in a Changing Climate 133 Anil Kumar 7.1 Introduction 133 7.2 Literature Review 138 7.3 Methodology 140 7.4 Analysis 142 7.5 Future Mechanization Pathways Through Climate-Smart Technologies 153 7.6 Discussion 157 7.7 Conclusion 158 8 Harvesting Tomorrow: Exploring Real-World Applications of AI in Agriculture 163 Priya and Neha Gupta 8.1 Introduction 163 8.2 Precision Agriculture: Transforming Farming Practices 165 8.3 Crop Monitoring and Management Techniques 171 8.4 Revolutionizing Livestock Management Through AI 174 8.5 Innovations in Food Supply Chains with AI 179 8.6 Addressing Ethical and Regulatory Considerations 182 8.7 Conclusion 184 8.8 Future Directions 185 9 Smart Agriculture: Predictive Modeling of Fertilizer Requirements Using Neural Networks 189 Heet Dave and Jai Prakash Verma 9.1 Introduction 189 9.2 Related Work 190 9.3 Proposed Research Work 194 9.4 Methodology and Concepts 195 9.5 Implementation and Execution flow 197 9.6 Results 204 9.7 Discussion 206 9.8 Conclusion 206 10 Reviewing Advances in Image-Based Plant Disease Detection 209 Gautmi Tomar, Yuvraj Ahuja, Yogita Arora, and Neera Agarwal 10.1 Introduction 209 10.2 Literature Review 212 10.3 Imaging Techniques of Plant Disease 214 10.4 Critical Discussion 223 10.5 Conclusion 225 11 Leveraging ResNeXt50 and LSTM for Enhanced Plant Disease Detection: A Hybrid Model Proposal 231 Jaspreet Singh and Shashi Tanwar 11.1 Introduction 231 11.2 Literature Review 234 11.3 Research Methodology 236 11.4 A Proposed Hybrid Model Using ResNext50 & LSTM for Plant Disease Detection 240 11.5 Results and Implementation 241 11.6 Conclusion and Future Work 243 12 FarmTechAI: Artificial-Intelligence-Based Modern Farmer Management System 247 Murat Can Cardak, Muhammed Golec, and Sukhpal Singh Gill 12.1 Introduction 247 12.2 Related Works 248 12.3 FarmTechAI: Proposed System 251 12.4 Performance Evaluation and Testing 271 12.5 Legal, Social, Ethical, and Sustainability Issues 277 12.6 Conclusions and Future Work 278 13 Livestock Monitoring and Welfare 283 V. Kanakaris, E. Vrochidou, and G. A. Papakostas 13.1 Introduction 283 13.2 Benefits of Livestock Monitoring 287 13.3 Innovative Livestock Monitoring Technology Methods 288 13.4 Impact of Livestock Monitoring Methods on Welfare 298 13.5 Discussion 300 13.6 Conclusions 302 14 Smart Crop Management: Harnessing Green IoT Tomorrow 315 Shipra Raheja, Vimal Gaur, and Rachna Jain 14.1 Introduction 315 14.2 Greening Agriculture: Advancing with IoT Technology 316 14.3 Green IoT Key Components 318 14.4 Future of AI in Agriculture 324 14.5 Conclusion and Future Aspects 324 15 Current Progress of Sustainable Smart Agriculture Using Internet of Things 329 Savita Kumari Sheoran, Suraj Ranga, and Ghanapriya Singh 15.1 Introduction 329 15.2 Literature Review 331 15.3 Methodology 339 15.4 Current Status of SDGs (Global and Local) in Ranking 343 15.5 Analysis 344 15.6 Conclusions 346 Funding 346 References 346 Index 353
About the Editors xvii List of Contributors xix Preface xxiii 1 Agricultural Resilience: Water Quality and Human Well-Being 1 Tanu Taneja, B.S Bhatia, and Shalom Akhai 1.1 Introduction 1 1.2 The Nexus of Water Quality and Agriculture 2 1.3 Impact of Contaminated Water on Crop Health 2 1.4 AI-Driven Water Monitoring Systems 4 1.5 Research Gaps and Research Dimensions 6 1.6 Precision Irrigation Techniques 7 1.7 Waterborne Pathogens in Farming 8 1.8 Livestock Health and Water Safety 8 1.9 Sustainable Water Management Strategies 9 1.10 Human Health Implications 11 1.11 Significance of Research in Agricultural Water Quality 12 1.12 Conclusion 12 2 Precision Farming: A Technological Revolution for Sustainable Agriculture 25 Ashish Kumar, Prasoon Kumar Pandey, and Divya Singh 2.1 Introduction 25 2.2 Principles of Precision Farming 27 2.3 Technologies in Precision Farming 28 2.4 Role of Drones in Precision Farming 35 2.5 Benefits of Precision Farming 37 2.6 Conclusion 40 3 Precision Farming and Smart Crop Management 45 Bhavin Patel, Jitendra Bhatia, and Malaram Kumhar 3.1 Introduction 45 3.2 Related Work 46 3.3 Technologies in Precision Farming 47 3.4 Smart Crop Management Techniques 58 3.5 Mapping to Site-Specific Applications 59 3.6 Challenges and Limitations 62 3.7 Conclusion 66 4 Empowering Smart Agriculture with Artificial Intelligence 71 Shipra Raheja and Himanshi Bansal 4.1 Introduction 71 4.2 Benefits of AI in Agriculture 72 4.3 Applications of Artificial Intelligence in Agriculture 74 4.4 Part of AI Within the Farming Data Administration Cycle 76 4.5 Optimizing AI for Farming and Agrarian Forms 78 4.6 AI's Limitations with Regard to Agriculture 79 4.7 Future of AI in Agriculture 81 4.8 The Future Research of AI in Small-Scale Farming 82 5 Foundations of Agricultural AI 87 Divya Singh, Naman Agrawal, Jaya Saini, and Manoranjan Kumar 5.1 Introduction 87 5.2 Machine Learning 91 5.3 Deep Learning 91 5.4 Applications of AI in Agriculture 92 5.5 Challenges and Opportunities 94 5.6 Ethical and Social Implications 96 5.7 Current Trends and Future Directions 98 5.8 Conclusion 100 6 AI in Agriculture: A Comprehensive Exploration of Technological Transformation 105 Manya Gupta, Gargi Mishra, Supriya Bajpai, Abhinav Bhardwaj, and Milind Gautam 6.1 Introduction 105 6.2 AI Integration in Agricultural Practices 108 6.3 AI-Monitored Agricultural Parameters 110 6.4 Application Areas of AI in Agriculture 112 6.5 Limitations 120 6.6 Conclusion and Future Scope 124 7 Integrating AI and Climate-Smart Agricultural Mechanization: Strategies for Enhancing Productivity and Sustainability in a Changing Climate 133 Anil Kumar 7.1 Introduction 133 7.2 Literature Review 138 7.3 Methodology 140 7.4 Analysis 142 7.5 Future Mechanization Pathways Through Climate-Smart Technologies 153 7.6 Discussion 157 7.7 Conclusion 158 8 Harvesting Tomorrow: Exploring Real-World Applications of AI in Agriculture 163 Priya and Neha Gupta 8.1 Introduction 163 8.2 Precision Agriculture: Transforming Farming Practices 165 8.3 Crop Monitoring and Management Techniques 171 8.4 Revolutionizing Livestock Management Through AI 174 8.5 Innovations in Food Supply Chains with AI 179 8.6 Addressing Ethical and Regulatory Considerations 182 8.7 Conclusion 184 8.8 Future Directions 185 9 Smart Agriculture: Predictive Modeling of Fertilizer Requirements Using Neural Networks 189 Heet Dave and Jai Prakash Verma 9.1 Introduction 189 9.2 Related Work 190 9.3 Proposed Research Work 194 9.4 Methodology and Concepts 195 9.5 Implementation and Execution flow 197 9.6 Results 204 9.7 Discussion 206 9.8 Conclusion 206 10 Reviewing Advances in Image-Based Plant Disease Detection 209 Gautmi Tomar, Yuvraj Ahuja, Yogita Arora, and Neera Agarwal 10.1 Introduction 209 10.2 Literature Review 212 10.3 Imaging Techniques of Plant Disease 214 10.4 Critical Discussion 223 10.5 Conclusion 225 11 Leveraging ResNeXt50 and LSTM for Enhanced Plant Disease Detection: A Hybrid Model Proposal 231 Jaspreet Singh and Shashi Tanwar 11.1 Introduction 231 11.2 Literature Review 234 11.3 Research Methodology 236 11.4 A Proposed Hybrid Model Using ResNext50 & LSTM for Plant Disease Detection 240 11.5 Results and Implementation 241 11.6 Conclusion and Future Work 243 12 FarmTechAI: Artificial-Intelligence-Based Modern Farmer Management System 247 Murat Can Cardak, Muhammed Golec, and Sukhpal Singh Gill 12.1 Introduction 247 12.2 Related Works 248 12.3 FarmTechAI: Proposed System 251 12.4 Performance Evaluation and Testing 271 12.5 Legal, Social, Ethical, and Sustainability Issues 277 12.6 Conclusions and Future Work 278 13 Livestock Monitoring and Welfare 283 V. Kanakaris, E. Vrochidou, and G. A. Papakostas 13.1 Introduction 283 13.2 Benefits of Livestock Monitoring 287 13.3 Innovative Livestock Monitoring Technology Methods 288 13.4 Impact of Livestock Monitoring Methods on Welfare 298 13.5 Discussion 300 13.6 Conclusions 302 14 Smart Crop Management: Harnessing Green IoT Tomorrow 315 Shipra Raheja, Vimal Gaur, and Rachna Jain 14.1 Introduction 315 14.2 Greening Agriculture: Advancing with IoT Technology 316 14.3 Green IoT Key Components 318 14.4 Future of AI in Agriculture 324 14.5 Conclusion and Future Aspects 324 15 Current Progress of Sustainable Smart Agriculture Using Internet of Things 329 Savita Kumari Sheoran, Suraj Ranga, and Ghanapriya Singh 15.1 Introduction 329 15.2 Literature Review 331 15.3 Methodology 339 15.4 Current Status of SDGs (Global and Local) in Ranking 343 15.5 Analysis 344 15.6 Conclusions 346 Funding 346 References 346 Index 353
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