This book explains the best practices and their respective outcomes in artificial intelligence (AI) to meet sustainable development goals and demands. It examines the practices, technologies, and innovations at the core of various research issues to meet the sustainable development demands in agriculture to balance social, economic, and environmental sustainability with AI. AI in Agriculture for Sustainable and Economic Management discusses AI-driven nanotechnology approaches for precision agriculture and solutions for the optimization of farming resources and their management. The authors examine the impact of AI in agriculture and how technology-driven sustainable farming with smart waste-water treatment for zero waste for the circular economy can extend crop shelf-life. It discusses how AI expertise can be advantageous to envisage and evaluate the increasing demands of productivity, and to help to maintain ecosystems and strengthen the capacity for crop adaptation in response to drastic changes in climate and weather, natural disasters, and other significant factors. These findings and practices are also useful to emphasize how an agricultural ecosystem can be advanced and industrialized so that it can aid not only large commercial farms but also smaller farmlands. Finally, it also discusses how AI practices will help to find a balance between the volume of food manufactured and the proper maintenance of the ecosystem. This book is intended for researchers and upper graduate students interested in artificial intelligence in agricultural engineering, AI advances in crop science and technology for sustainable development.

AI in Agriculture for Sustainable and Economic Management / Potluri, S.; Satpathy, S.; Basa, S. S.; Zuorro, A.. - (2024), pp. 1-236. [10.1201/9781003451648]

AI in Agriculture for Sustainable and Economic Management

Zuorro A.
2024

Abstract

This book explains the best practices and their respective outcomes in artificial intelligence (AI) to meet sustainable development goals and demands. It examines the practices, technologies, and innovations at the core of various research issues to meet the sustainable development demands in agriculture to balance social, economic, and environmental sustainability with AI. AI in Agriculture for Sustainable and Economic Management discusses AI-driven nanotechnology approaches for precision agriculture and solutions for the optimization of farming resources and their management. The authors examine the impact of AI in agriculture and how technology-driven sustainable farming with smart waste-water treatment for zero waste for the circular economy can extend crop shelf-life. It discusses how AI expertise can be advantageous to envisage and evaluate the increasing demands of productivity, and to help to maintain ecosystems and strengthen the capacity for crop adaptation in response to drastic changes in climate and weather, natural disasters, and other significant factors. These findings and practices are also useful to emphasize how an agricultural ecosystem can be advanced and industrialized so that it can aid not only large commercial farms but also smaller farmlands. Finally, it also discusses how AI practices will help to find a balance between the volume of food manufactured and the proper maintenance of the ecosystem. This book is intended for researchers and upper graduate students interested in artificial intelligence in agricultural engineering, AI advances in crop science and technology for sustainable development.
2024
Artificial Intelligence (AI) in Agriculture; Sustainable Agriculture; Precision Farming; Agri-Tech; Smart Farming; Agricultural Economics; Environmental Sustainability; AI Applications in Farming; Crop Management; Soil Analysis; Climate-Smart Agriculture; Decision Support Systems; Farm Automation; Predictive Analytics in Agriculture; Food Security; Sustainable Economic Development; Agri-Business Management; Digital Transformation in Agriculture; Machine Learning in Agriculture; Data-Driven Farming
03 Monografia::03a Saggio, Trattato Scientifico
AI in Agriculture for Sustainable and Economic Management / Potluri, S.; Satpathy, S.; Basa, S. S.; Zuorro, A.. - (2024), pp. 1-236. [10.1201/9781003451648]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1732490
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