Description
The book is a timely and forward-looking volume that explores the transformative role of Artificial Intelligence, Federated Learning, IoT, blockchain, and edge computing in building sustainable and climate-resilient agricultural systems. The book brings together interdisciplinary research and practical applications that address critical agricultural challenges such as crop disease detection, pest forecasting, livestock monitoring, resource optimization, climate-risk assessment, and smart farming automation.
Through diverse chapters authored by experts from academia and industry, the book highlights how privacy-preserving federated AI enables collaborative learning across farms, institutions, and regions without compromising data ownership. It also examines ethical, legal, and societal dimensions of deploying intelligent agricultural technologies. Combining innovation with sustainability, this book serves as a valuable resource for researchers, policymakers, students, agritech professionals, and practitioners working toward the future of precision agriculture and resilient global food systems.
Through diverse chapters authored by experts from academia and industry, the book highlights how privacy-preserving federated AI enables collaborative learning across farms, institutions, and regions without compromising data ownership. It also examines ethical, legal, and societal dimensions of deploying intelligent agricultural technologies. Combining innovation with sustainability, this book serves as a valuable resource for researchers, policymakers, students, agritech professionals, and practitioners working toward the future of precision agriculture and resilient global food systems.