Cover image for Emerging smart agricultural practices using artificial intelligence
Title:
Emerging smart agricultural practices using artificial intelligence
ISBN:
9781394274277

9781394274260

9781394274253
Physical Description:
1 online resource
Contents:
About the Editors -- List of Contributors -- Preface -- 1 Agricultural Resilience: Water Quality and Human Well-Being 1 Tanu Taneja, B.S Bhatia, and Shalom Akhai -- 1.1 Introduction -- 1.2 The Nexus of Water Quality and Agriculture -- 1.3 Impact of Contaminated Water on Crop Health -- 1.4 AI-Driven Water Monitoring Systems -- 1.5 Research Gaps and Research Dimensions -- 1.6 Precision Irrigation Techniques -- 1.7 Waterborne Pathogens in Farming -- 1.8 Livestock Health and Water Safety -- 1.9 Sustainable Water Management Strategies -- 1.10 Human Health Implications -- 1.11 Significance of Research in Agricultural Water Quality -- 1.12 Conclusion -- 2 Precision Farming: A Technological Revolution for Sustainable Agriculture 25 Ashish Kumar, Prasoon Kumar Pandey, and Divya Singh -- 2.1 Introduction -- 2.2 Principles of Precision Farming -- 2.3 Technologies in Precision Farming -- 2.4 Role of Drones in Precision Farming -- 2.5 Benefits of Precision Farming -- 2.6 Conclusion -- 3 Precision Farming and Smart Crop Management 45 Bhavin Patel, Jitendra Bhatia, and Malaram Kumhar -- 3.1 Introduction -- 3.2 Related Work -- 3.3 Technologies in Precision Farming -- 3.4 Smart Crop Management Techniques -- 3.5 Mapping to Site-Specific Applications -- 3.6 Challenges and Limitations -- 3.7 Conclusion -- 4 Empowering Smart Agriculture with Artificial Intelligence 71 Shipra Raheja and Himanshi Bansal -- 4.1 Introduction -- 4.2 Benefits of AI in Agriculture -- 4.3 Applications of Artificial Intelligence in Agriculture -- 4.4 Part of AI Within the Farming Data Administration Cycle -- 4.5 Optimizing AI for Farming and Agrarian Forms -- 4.6 AI's Limitations with Regard to Agriculture -- 4.7 Future of AI in Agriculture -- 4.8 The Future Research of AI in Small-Scale Farming -- 5 Foundations of Agricultural AI 87 Divya Singh, Naman Agrawal, Jaya Saini, and Manoranjan Kumar -- 5.1 Introduction -- 5.2 Machine Learning -- 5.3 Deep Learning -- 5.4 Applications of AI in Agriculture -- 5.5 Challenges and Opportunities -- 5.6 Ethical and Social Implications -- 5.7 Current Trends and Future Directions -- 5.8 Conclusion -- 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 -- 6.2 AI Integration in Agricultural Practices -- 6.3 AI-Monitored Agricultural Parameters -- 6.4 Application Areas of AI in Agriculture -- 6.5 Limitations -- 6.6 Conclusion and Future Scope -- 7 Integrating AI and Climate-Smart Agricultural Mechanization: Strategies for Enhancing Productivity and Sustainability in a Changing Climate 133 Anil Kumar -- 7.1 Introduction -- 7.2 Literature Review -- 7.3 Methodology -- 7.4 Analysis -- 7.5 Future Mechanization Pathways Through Climate-Smart Technologies -- 7.6 Discussion -- 7.7 Conclusion -- 8 Harvesting Tomorrow: Exploring Real-World Applications of AI in Agriculture 163 Priya and Neha Gupta -- 8.1 Introduction -- 8.2 Precision Agriculture: Transforming Farming Practices -- 8.3 Crop Monitoring and Management Techniques -- 8.4 Revolutionizing Livestock Management Through AI -- 8.5 Innovations in Food Supply Chains with AI -- 8.6 Addressing Ethical and Regulatory Considerations -- 8.7 Conclusion -- 8.8 Future Directions -- 9 Smart Agriculture: Predictive Modeling of Fertilizer Requirements Using Neural Networks 189 Heet Dave and Jai Prakash Verma -- 9.1 Introduction -- 9.2 Related Work -- 9.3 Proposed Research Work -- 9.4 Methodology and Concepts -- 9.5 Implementation and Execution flow -- 9.6 Results -- 9.7 Discussion -- 9.8 Conclusion -- 10 Reviewing Advances in Image-Based Plant Disease Detection 209 Gautmi Tomar, Yuvraj Ahuja, Yogita Arora, and Neera Agarwal -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 Imaging Techniques of Plant Disease -- 10.4 Critical Discussion -- 10.5 Conclusion -- 11 Leveraging ResNeXt50 and LSTM for Enhanced Plant Disease Detection: A Hybrid Model Proposal 231 Jaspreet Singh and Shashi Tanwar -- 11.1 Introduction -- 11.2 Literature Review -- 11.3 Research Methodology -- 11.4 A Proposed Hybrid Model Using ResNext50 & LSTM for Plant Disease Detection -- 11.5 Results and Implementation -- 11.6 Conclusion and Future Work -- 12 FarmTechAI: Artificial-Intelligence-Based Modern Farmer Management System 247 Murat Can Cardak, Muhammed Golec, and Sukhpal Singh Gill -- 12.1 Introduction -- 12.2 Related Works -- 12.3 FarmTechAI: Proposed System -- 12.4 Performance Evaluation and Testing -- 12.5 Legal, Social, Ethical, and Sustainability Issues -- 12.6 Conclusions and Future Work -- 13 Livestock Monitoring and Welfare 283 V. Kanakaris, E. Vrochidou, and G. A. Papakostas -- 13.1 Introduction -- 13.2 Benefits of Livestock Monitoring -- 13.3 Innovative Livestock Monitoring Technology Methods -- 13.4 Impact of Livestock Monitoring Methods on Welfare -- 13.5 Discussion -- 13.6 Conclusions -- 14 Smart Crop Management: Harnessing Green IoT Tomorrow 315 Shipra Raheja, Vimal Gaur, and Rachna Jain -- 14.1 Introduction -- 14.2 Greening Agriculture: Advancing with IoT Technology -- 14.3 Green IoT Key Components -- 14.4 Future of AI in Agriculture -- 14.5 Conclusion and Future Aspects -- 15 Current Progress of Sustainable Smart Agriculture Using Internet of Things 329 Savita Kumari Sheoran, Suraj Ranga, and Ghanapriya Singh -- 15.1 Introduction -- 15.2 Literature Review -- 15.3 Methodology -- 15.4 Current Status of SDGs (Global and Local) in Ranking -- 15.5 Analysis -- 15.6 Conclusions -- Funding -- References -- Index.
Abstract:
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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John Wiley and Sons
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E-Book 600019-1001 S494.5 .D3 E44 2025
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