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AI in Agriculture for Sustainable and Economic Management

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AI in Agriculture for Sustainable and Economic Management Synopsis

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.

About This Edition

ISBN: 9781032585697
Publication date: 1st August 2024
Author: Sirisha Potluri, Suneeta Satpathy, Santi Swarup Basa, Antonio Zuorro
Publisher: CRC Press
Format: Hardback
Pagination: 236 pages
Series: Artificial Intelligence for Sustainable Engineering and Management
Genres: Agribusiness and primary industries
Automatic control engineering
Agricultural science
Algorithms and data structures
Artificial intelligence
Information technology: general topics
Environmental science, engineering and technology