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.

C Kishor Kumar Reddy, currently working as Associate Professor, Dept. of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India. He has research and teaching experience of more than 12 years. He has published more than 220+ research papers in National and International Conferences, Book Chapters, and Journals indexed by Scopus and others. He is an author for 2 text books and 25+ coedited books. He is the member of ISTE, CSI, IAENG, UACEE, and IACSIT.

T Monika Singh received her M.Tech degree in Computer Science and Engineering Department from Osmania University. Currently Pursuing Ph.D in IT Department in Annamalai University. From 2017 she is working as faculty in Computer Science and Engineering Department at Stanley College of Engineering and Technology for Women. She possesses extensive experience in both teaching and research. She is certified as a project-based learning mentor by Wipro and holds a TalentNext certification in Java Full Stack. Her research interest area is Machine Learning. She has various paper publications in national and international journals. In addition to her credits, she also has a patent in her credits.

Fatima Zahra Ouariach is a Doctoral Researcher specializing in Educational Technology and Temporary Professor at Abdelmalek Essaadi University. She is currently working on her PhD, focusing on the management of communication tools in e-learning through an LMS platform. Her research aims to design an efficient architecture for communication tools in the specific context of online learning using an LMS platform. In addition to her academic work, She has gained experience as a reviewer for prestigious publishing houses such as Hindawi , Inderscience and IGI Global... Furthermore, she has made valuable contributions as a member of the jury for oral interviews at Abdelmalek Essaadi University, showcasing her dedication and contribution to the advancement of research and higher education.

Dr. Jothi Paranthaman is a Lecturer at Botho University’s Faculty of Engineering and Technology with a strong research focus in data science, blockchain, big data, and IoT security. Her work includes applying bioinspired encryption methods and steganographic techniques to safeguard medical data transmission. She actively publishes with interdisciplinary teams and contributes to the university’s mission on technological innovation.

Meetu Malhotra is a Data Analytics Principal at S&P Global with over 17 years of experience and currently pursuing a PhD in Data Science from Harrisburg University. I’m a senior member of IEEE and an active contributor to the data science community through publishing, peer-reviewing, and technical writing. I have been invited for speaking engagements at highimpact platforms. My recent work includes a published book on GenAI and cyberbullying, and some technical blogs in machine learning and AI field.

Dr. Haïfa Nakouri is a Machine Learning specialist and currently holds the Invited Professor of Computer Science position at the University of Quebec at Chicoutimi (UQAC). She is also an Assistant Professor in Business Computing at the Higher School of Digital Economy, University of Manouba, Tunisia. Dr. Nakouri obtained her Business Computing Bachelor, M.Sc., and PhD degrees from the Higher Institute of Management, University of Tunis, Tunisia (ISG Tunis) in 2007, 2009, and 2016, respectively. She is associated with the LARODEC laboratory at ISG Tunis and focuses on research topics such as Machine learning, Responsible/Secure AI, Computer Vision, and Image Processing. Her developed expertise in analyzing the vulnerabilities and shortcomings of Machine Learning models and designing solutions to enhance their resilience. Dr. Nakouri is a member of the UQAC Cybersecurity Research Chair, where she collaborates with experts in the field to advance knowledge in learning model security. She is actively involved in various international research projects and collaborations and has published over 25 research papers. Additionally, she has contributed to Program Committees, Organizing Committees, and chaired several reputable international conferences and workshops.

Chapter 1. Federated Learning in Agriculture for the Next Generation of Data-Driven and Autonomous Farming Monalisha Pattnaik, Umrah Naushad, Sudev Kumar Padhi and Guddi Mohanty

Chapter 2. Integrating IoT, Edge Computing, and Federated Learning for Scalable Agricultural Intelligence S. Anand and Wan Mazlina Wan Mohamed

Chapter 3. Federated Learning Architectures for Climate-Resilient and Sustainable Agricultural Practices Desham Archana, B. Rama Sree, Bhoomeshwar Bala Raja Shekar Kadurka and Sabih Ahmad

Chapter 4. Advancing Early Crop Disease Detection Using Federated Deep Learning and Remote Sensing Ushaa Eswaran, Vishal Eswaran, Vivek Eswaran and Keerthna Murali

Chapter 5. Livestock Health Monitoring Using Federated Learning and Wearable IoT Sensors
Dr. V. Umadevi

Chapter 6. Federated Learning for Climate Resilience: Overcoming Data Silos and Enhancing Agricultural Sustainability Md. Shoeab Akhter, Sakibul Islam Ratul, Fahmida Tasnim and Prof. Dr. Mohammed Ataur Rahman

Chapter 7. Blockchain-Enabled Federated Learning for Secure and Transparent AgriTech Data Sharing Mohammed Abdul Bari, Md Fasihuddin, Dr. Mohd Ashraf, Dr. Shahanawaj Ahamad and Dr. Akhil Khare

Chapter 8. Federated Learning Case Studies for Plant Disease Forecasting Across Diverse Agro-Ecosystems Singamaneni Krishnapriya, Dr. Amaravarapu Pramodkumar and Rasmitha Kumari Mohanty

Chapter 9. The Future of Autonomous Farming through Intelligent and Distributed Federated AI Systems Lingala Thirupathi, Ananya Seeta, Kashif Mohammed and Ramya G

Chapter 10. Tools, Frameworks, and Real-World Deployment Strategies for Federated Learning in Agriculture Shaheda Begum, Patchipulusu Sneha, Monika Singh T and Dr. S Md Shakir Ali

Chapter 11. Federated Artificial Intelligence for Climate-Resilient Agricultural Marketing Systems Check Mohammed Abdul Bari, Dr. Md Zair Hussain, Dr. G F Ali Ahammed and Dr. Shahanawaj Ahamad

Chapter 12. Proactive Pest and Disease Management: AI-Powered Early Detection, Prediction, and Prevention Systems Satvika Pullisani, Nishitha Pujala and Harish Kannan

Chapter 13. Ethical, Legal, and Societal Challenges in Deploying Federated AI in Agricultural Domains Nishitha Pujala, Satvika Pullisani, Harish Kannan and Samanvitha Karri