Agricultural Supply Chain Optimization Using Federated Learning

Master the next evolution of agricultural intelligence with this definitive guide to federated learning, providing decentralized, privacy-preserving strategies needed to optimize global supply chains without compromising data sovereignty.

As global agriculture faces challenges such as climate variability, resource inefficiency, and data privacy concerns, traditional centralized AI systems struggle to operate at scale. Federated learning addresses these limitations by enabling decentralized, privacy-preserving model training across distributed datasets, supporting secure and collaborative optimization. This book explores how federated learning enhances precision farming, logistics optimization, and sustainable resource management through real-time, data-driven decision-making while respecting local variations and regulatory constraints. It bridges the gap between advanced AI technologies and practical agricultural supply chain management, covering foundational concepts, system architectures, and real-world implementations. Through case studies and applied insights, the book demonstrates how federated learning can improve productivity, reduce waste, and strengthen sustainability while maintaining data sovereignty. It offers a balanced perspective on both technical and managerial aspects, making it accessible to a wide audience while retaining depth for academic and industry professionals.

Abhishek Kumar, PhD is an Assistant Director and Professor in the Computer Science and Engineering Department at Chandigarh University with more than 13 years of teaching experience. He has authored seven books, edited 51 books, and published more than 170 peer-reviewed articles. His research spans artificial intelligence, renewable energy, image processing, and data mining.

Pooja Dixit is an Assistant Professor in the Department of Computer Science at Shri Ratanlal Kanwarlal Patni Girls’ College, Kishangarh, India. With more than seven years of teaching and two years of research experience, she has published more than 25 research papers. Her research interests include artificial intelligence, machine learning, and data mining.

J.P. Ananth, PhD is a Professor and Dean in the Internal Quality Assurance Cell at Sri Krishna College of Engineering and Technology with more than 23 years of experience. His research interests include computer vision, pattern recognition, artificial intelligence, and data analytics.

S. Oswalt Manoj, PhD is an Associate Professor in the Department of Computer Science and Engineering at Sri Krishna College of Engineering and Technology with more than 14 years of experience. He has published more than 100 works and focuses on big data analytics, artificial intelligence, computer vision, machine learning, deep learning, and cloud computing.

S. Panneerselvam, PhD is a Professor in the Department of Agricultural Engineering at Hindustan College of Engineering and Technology. He has published 65 research articles, more than 12 books, and 20 book chapters.