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.
One of the book's key focuses is the critical role of health monitoring for plants and fruits in achieving sustainable agriculture. Plant diseases pose significant financial challenges in the farming industry worldwide. By leveraging sophisticated image processing and advanced computer vision techniques, automated detection and identification of plant diseases are revolutionized, enabling precise and rapid identification while minimizing human effort and labor costs.
For researchers involved in image processing and computer vision for smart agriculture, this book offers invaluable insights. It covers the most important fields of image processing in the agricultural domain, encompassing computer vision applications, machine learning, and deep learning approaches. From the analysis of agricultural data using machine learning to the implementation of bio-inspired algorithms, the book explores the breadth and depth of agricultural modernization through the lens of AI technologies.
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.