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    Emerging Smart Agricultural Practices Using Artificial Intelligence

    AvAshish Kumar,Ashish Kumar

    Inbunden, Engelska, 2025

    1 727 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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 throughoutDetailed 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 worldwideEmerging Smart Agricultural Practices Using Artificial Intelligence is ideal for agricultural professionals and scientists, as well as data scientists, technologists, and agricultural policymakers.

    Produktinformation

    • Utgivningsdatum:2025-06-23
    • Mått:152 x 229 x 22 mm
    • Vikt:680 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:384
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394274246

    Utforska kategorier

    • Lantbruksteknik inom Naturvetenskap och teknik
    • Artificiell intelligens inom Data och IT

    Mer om författaren

    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.

    Innehållsförteckning

    • About the Editors xviiList of Contributors xixPreface xxiii1 Agricultural Resilience: Water Quality and Human Well-Being 1Tanu Taneja, B.S Bhatia, and Shalom Akhai1.1 Introduction 11.2 The Nexus of Water Quality and Agriculture 21.3 Impact of Contaminated Water on Crop Health 21.4 AI-Driven Water Monitoring Systems 41.5 Research Gaps and Research Dimensions 61.6 Precision Irrigation Techniques 71.7 Waterborne Pathogens in Farming 81.8 Livestock Health and Water Safety 81.9 Sustainable Water Management Strategies 91.10 Human Health Implications 111.11 Significance of Research in Agricultural Water Quality 121.12 Conclusion 122 Precision Farming: A Technological Revolution for Sustainable Agriculture 25Ashish Kumar, Prasoon Kumar Pandey, and Divya Singh2.1 Introduction 252.2 Principles of Precision Farming 272.3 Technologies in Precision Farming 282.4 Role of Drones in Precision Farming 352.5 Benefits of Precision Farming 372.6 Conclusion 403 Precision Farming and Smart Crop Management 45Bhavin Patel, Jitendra Bhatia, and Malaram Kumhar3.1 Introduction 453.2 Related Work 463.3 Technologies in Precision Farming 473.4 Smart Crop Management Techniques 583.5 Mapping to Site-Specific Applications 593.6 Challenges and Limitations 623.7 Conclusion 664 Empowering Smart Agriculture with Artificial Intelligence 71Shipra Raheja and Himanshi Bansal4.1 Introduction 714.2 Benefits of AI in Agriculture 724.3 Applications of Artificial Intelligence in Agriculture 744.4 Part of AI Within the Farming Data Administration Cycle 764.5 Optimizing AI for Farming and Agrarian Forms 784.6 AI's Limitations with Regard to Agriculture 794.7 Future of AI in Agriculture 814.8 The Future Research of AI in Small-Scale Farming 825 Foundations of Agricultural AI 87Divya Singh, Naman Agrawal, Jaya Saini, and Manoranjan Kumar5.1 Introduction 875.2 Machine Learning 915.3 Deep Learning 915.4 Applications of AI in Agriculture 925.5 Challenges and Opportunities 945.6 Ethical and Social Implications 965.7 Current Trends and Future Directions 985.8 Conclusion 1006 AI in Agriculture: A Comprehensive Exploration of Technological Transformation 105Manya Gupta, Gargi Mishra, Supriya Bajpai, Abhinav Bhardwaj, and Milind Gautam6.1 Introduction 1056.2 AI Integration in Agricultural Practices 1086.3 AI-Monitored Agricultural Parameters 1106.4 Application Areas of AI in Agriculture 1126.5 Limitations 1206.6 Conclusion and Future Scope 1247 Integrating AI and Climate-Smart Agricultural Mechanization: Strategies for Enhancing Productivity and Sustainability in a Changing Climate 133Anil Kumar7.1 Introduction 1337.2 Literature Review 1387.3 Methodology 1407.4 Analysis 1427.5 Future Mechanization Pathways Through Climate-Smart Technologies 1537.6 Discussion 1577.7 Conclusion 1588 Harvesting Tomorrow: Exploring Real-World Applications of AI in Agriculture 163Priya and Neha Gupta8.1 Introduction 1638.2 Precision Agriculture: Transforming Farming Practices 1658.3 Crop Monitoring and Management Techniques 1718.4 Revolutionizing Livestock Management Through AI 1748.5 Innovations in Food Supply Chains with AI 1798.6 Addressing Ethical and Regulatory Considerations 1828.7 Conclusion 1848.8 Future Directions 1859 Smart Agriculture: Predictive Modeling of Fertilizer Requirements Using Neural Networks 189Heet Dave and Jai Prakash Verma9.1 Introduction 1899.2 Related Work 1909.3 Proposed Research Work 1949.4 Methodology and Concepts 1959.5 Implementation and Execution flow 1979.6 Results 2049.7 Discussion 2069.8 Conclusion 20610 Reviewing Advances in Image-Based Plant Disease Detection 209Gautmi Tomar, Yuvraj Ahuja, Yogita Arora, and Neera Agarwal10.1 Introduction 20910.2 Literature Review 21210.3 Imaging Techniques of Plant Disease 21410.4 Critical Discussion 22310.5 Conclusion 22511 Leveraging ResNeXt50 and LSTM for Enhanced Plant Disease Detection: A Hybrid Model Proposal 231Jaspreet Singh and Shashi Tanwar11.1 Introduction 23111.2 Literature Review 23411.3 Research Methodology 23611.4 A Proposed Hybrid Model Using ResNext50 & LSTM for Plant Disease Detection 24011.5 Results and Implementation 24111.6 Conclusion and Future Work 24312 FarmTechAI: Artificial-Intelligence-Based Modern Farmer Management System 247Murat Can Cardak, Muhammed Golec, and Sukhpal Singh Gill12.1 Introduction 24712.2 Related Works 24812.3 FarmTechAI: Proposed System 25112.4 Performance Evaluation and Testing 27112.5 Legal, Social, Ethical, and Sustainability Issues 27712.6 Conclusions and Future Work 27813 Livestock Monitoring and Welfare 283V. Kanakaris, E. Vrochidou, and G. A. Papakostas13.1 Introduction 28313.2 Benefits of Livestock Monitoring 28713.3 Innovative Livestock Monitoring Technology Methods 28813.4 Impact of Livestock Monitoring Methods on Welfare 29813.5 Discussion 30013.6 Conclusions 30214 Smart Crop Management: Harnessing Green IoT Tomorrow 315Shipra Raheja, Vimal Gaur, and Rachna Jain14.1 Introduction 31514.2 Greening Agriculture: Advancing with IoT Technology 31614.3 Green IoT Key Components 31814.4 Future of AI in Agriculture 32414.5 Conclusion and Future Aspects 32415 Current Progress of Sustainable Smart Agriculture Using Internet of Things 329Savita Kumari Sheoran, Suraj Ranga, and Ghanapriya Singh15.1 Introduction 32915.2 Literature Review 33115.3 Methodology 33915.4 Current Status of SDGs (Global and Local) in Ranking 34315.5 Analysis 34415.6 Conclusions 346Funding 346References 346Index 353
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