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OverviewThis book explores the transformative potential of ML technologies in agriculture. It delves into specific applications, such as crop monitoring, disease detection, and livestock management, demonstrating how AI/ML can optimize resource management and improve overall productivity in farming practices. Sustainable Farming through Machine Learning: Enhancing Productivity and Efficiency provides an in-depth overview of AI and ML concepts relevant to the agricultural industry. It discusses the challenges faced by the agricultural sector and how AI/ML can address them. The authors highlight the use of AI/ML algorithms for plant disease and pest detection and examine the role of AI/ML in supply chain management and demand forecasting in agriculture. It includes an examination of the integration of AI/ML with agricultural robotics for automation and efficiency. They also cover applications in livestock management, including feed formulation and disease detection, they also explore the use of AI/ML for behavior analysis and welfare assessment in livestock. Finally, the authors also explore ethical and social implications of using such technologies. This book can be used as a textbook for students in agricultural engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in machine learning, and deep learning working on sustainable agriculture applications. Full Product DetailsAuthor: Suneeta Satpathy (CE Bhubaneswar) , Bijay Kumar Paikaray , Ming Yang , Arunkumar BalakrishnanPublisher: Taylor & Francis Ltd Imprint: CRC Press ISBN: 9781032777498ISBN 10: 1032777494 Pages: 284 Publication Date: 25 November 2024 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Forthcoming Availability: Not yet available This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of ContentsReviewsAuthor InformationDr. Suneeta Satpathy, PhD, is an Associate Professor in Center for AI & ML, Siksha 'O' Anusandhan (Deemed to be) University, Odisha, India. Her research interests include computer forensics, cyber security, data fusion, data mining, big data analysis, decision mining and machine learning. She has published papers in many international journals and conferences in repute. She has two Indian patents in her credit, and is a member of IEEE, CSI, ISTE, OITS, and IE. Dr. Bijay Kumar Paikaray, PhD, is an Associate Professor at the Center for Data Science, Siksha 'O' Anusandhan (Deemed to be) University, Odisha. His interests include high-performance computing, information security, machine learning and IoT. Dr. Ming Yang has a Ph.D. in Computer Science from Wright State University, Dayton, Ohio, US, 2006. Currently he is a Professor in the College of Computing and Software Engineering Kennesaw State University, GA, USA. His research interests include multimedia communication, digital image/video processing, computer vision, and machine learning. Dr. Arunkumar Balakrishnan PhD, holds the position of Assistant Professor Senior Grade in the Computer Science and Engineering department at VIT-AP University. He obtained his Ph.D. in Information Science and Engineering from Anna University, Chennai. He possesses 12 years of academic expertise and an additional 6 years of concurrent research experience in the domains of Cryptography, Medical Image Security, Blockchain, and NFT. His research interests encompass Cryptography, Network Security, Medical Image Encryption, Blockchain, lightweight cryptography methods, and NFT. Tab Content 6Author Website:Countries AvailableAll regions |