Description
Machine Learning and Deep Learning for Smart Agriculture and Applications delves into the captivating realm of artificial intelligence and its pivotal role in transforming the landscape of modern agriculture. With a focus on precision agriculture, digital farming, and emerging concepts, this book illuminates the significance of sustainable food production and resource management in the face of evolving digital hardware and software technologies.
Geospatial technology, robotics, the Internet of Things (IoT), and data analytics converge with machine learning and big data to unlock new possibilities in agricultural management. This book explores the synergy between these disciplines, offering cutting-edge insights into data-intensive processes within operational agricultural environments. From automated irrigation systems and agricultural drones for field analysis to crop monitoring and precision agriculture, the applications of machine learning are far-reaching. Animal identification and health monitoring also benefit from these advanced techniques. With practical case studies on vegetable and fruit leaf disease detection, drone-based agriculture, and the impact of pesticides on plants, this book provides a comprehensive understanding of the applications of machine learning and deep learning in smart agriculture. It also examines various modeling techniques employed in this field and showcases how artificial intelligence can revolutionize plant disease detection. This book serves as a comprehensive guide for researchers, practitioners, and students seeking to harness the power of AI in transforming the agricultural landscape.
Author's/Editor's Biography
Mohamamd Hashmi (Ed.)
Mohammad Farukh Hashmi
(Senior Member, IEEE) received the B.E. degree in electronics and communication engineering from MIT Mandsaur/RGPV Bhopal University in 2007, the M.E. degree in digital techniques and instrumentation from SGSITS Indore/RGPV Bhopal University, in 2010. Dr. Hashmi Received Ph.D. degree from the Visvesvaraya National Institute of Technology (VNIT), Nagpur in 2015, under the supervision of Dr. Avinash G. Keskar. He is currently an Assistant Professor with the Department of Electronics and Communication Engineering, National Institute of Technology, Warangal. He has published up to 75 articles in International/National Journals/Conferences. He has a teaching and research experience of 12 years. His current research interests include computer vision, machine vision, machine learning, deep learning, embedded systems, Internet of things, digital signal processing, image processing, and digital IC design. He is a senior member of IEEE, Life member of IETE, Life member ISTE, and Life member of IAENG societies.
Avinash Kesakr (Ed.)
Avinash G. Keskar
(Senior Member, IEEE) was born in Nagpur, India, in 1959. He received the B.E. degree (Hons.) from the Visvesvaraya National Institute of Technology (VNIT), Nagpur, in 1979, the M.E. degree (Hons.) from the Indian Institute of Science (IISc), Bangalore, in 1983, and the Ph.D. degree from Nagpur University, in 1997. He has 30 years of teaching experience and seven years of industrial experience. He is currently working as a Professor and the Head of the Department of Electronics and Communication Engineering, VNIT. His current research interests include computer vision, soft computing, embedded systems, and fuzzy logic. He is a Senior Member of FIETE, FIE, and LMISTE.