Intelligent Agro-Technological Ecosystems: Architectures, Analytics, and Autonomous Innovations for Next-Generation Precision Agriculture presents a comprehensive exploration of the technologies transforming modern agriculture from conventional, experience-based management toward data-driven, connected, intelligent, and increasingly autonomous farming systems. The book brings together precision agriculture, Internet of Things (IoT), remote sensing, computer vision, artificial intelligence, machine learning, big data analytics, communication networks, agricultural robotics, intelligent irrigation, soil health monitoring, crop yield prediction, and automated pest and weed management.

The opening chapters establish the foundations of precision agriculture and intelligent farming architectures, emphasizing spatial variability, real-time sensing, data analytics, autonomous decision-making, and Agriculture 5.0. Subsequent chapters examine IoT-enabled sensor networks, computer vision and image processing, scalable big-data platforms, predictive modelling, and communication protocols that enable connected agricultural systems.The book further addresses practical intelligent-farming applications including autonomous agricultural robotics, intelligent irrigation and water optimization, AI-driven soil health and nutrient management, crop-yield forecasting, and AI-enabled pest detection and automated weed management. The final chapter extends the discussion through international case studies from technologically advanced agricultural economies, highlighting implementation, adoption, infrastructure, regulation, and sustainability considerations.

Dr. C. Kishor Kumar Reddy is a seasoned academician and researcher with over 13 years of experience in computer science and engineering. Currently serving at Stanley College of Engineering and Technology for Women, Hyderabad, he holds a Ph.D. in Computer Science and Engineering and a Postdoctoral Fellowship from Universiti Kebangsaan Malaysia, Malaysia. Dr. C. Kishor Kumar Reddy has made significant contributions in areas such as Artificial Intelligence, Machine Learning, Deep Learning, Federated Learning, Cybersecurity, Healthcare 6.0, and Disaster Management. He has authored and co-authored 230+ research articles in reputed SCI/Scopus-indexed journals, presented in international conferences, and contributed to numerous book chapters with leading publishers like Springer, CRC Press, Wiley-IEEE, IGI Global, and Cambridge Scholars Publishing. He also holds several published patents and serves as an editor for multiple scholarly books on emerging technologies. Dr. C. Kishor Kumar Reddy is an active member of professional bodies such as the Indian Society for Technical Education, Computer Society of India, and the International Association of Engineers, among others.

Anindya Nag obtained an M.Sc. in Computer Science and Engineering from Khulna University, Khulna, Bangladesh, and a B.Tech. in Computer Science and Engineering from Adamas University, Kolkata, India. He is working as a lecturer in the Department of Computer Science and Engineering at the Northern University of Business and Technology, Khulna, Bangladesh. Anindya Nag’s research focuses on health informatics, medical Internet of Things, neuroscience, and machine learning. He serves as a reviewer for numerous prestigious journals and international conferences. He has authored and co-authored about 84 publications, including journal articles, conference papers, and book chapters, and has co-edited ten books. He is currently pursuing his PhD in Computer Science at Ca’ Foscari University of Venice, Italy.

Dr Shikha Khullar Department of Computer Science and Engineering, Poornima University Rajasthan India.Dr. Shikha Khullar is an Associate Professor at Poornima University, Jaipur, with over 15 years of experience in teaching and research in the fields of Artificial Intelligence, computational intelligence, cybersecurity, and intelligent systems. She has made significant contributions to interdisciplinary research, particularly in AI-driven technologies, IoT-enabled systems, and smart digital ecosystems. She has authored and edited several scholarly works, including an edited book with IGI Global, and has ongoing publications with reputed international publishers such as Springer and Elsevier. Her research interests include AI-based fraud detection, intelligent robotics, smart healthcare systems, and data-driven technologies. She is also actively involved in patent research and innovation and is a member of professional organizations like ACM, IAENG, and ERDA, contributing actively to global research collaborations.

Dr Sarika S is Professor and Head of the Department of Artificial Intelligence and Data Science at Adi Shankara Institute of Engineering and Technology, Kalady, India, under APJ Abdul Kalam Technological University, India. Dr Sarika S is a patent holder and has authored three books and eight book chapters. She has also served as a reviewer for leading international journals, contributing to academic quality and research advancement in the field of Artificial Intelligence and Data Science.

Chapter 1. Foundations of Precision Agriculture and Intelligent Farming Systems

Chapter 2. Internet of Things (IoT)-Enabled Sensor Networks for Precision Agriculture

Chapter 3. Computer Vision and Image Processing Techniques for Crop Monitoring and Disease Detection

Chapter 4. Big Data Analytics and Predictive Modelling Frameworks in Agricultural Systems

Chapter 5. Digital Communication Networks and Connectivity Protocols for Smart Agriculture Systems

Chapter 6. A Study on Agricultural Robotics and Autonomous Farming System Architecture

Chapter 7. Intelligent Irrigation Systems and Water Resource Optimization Frameworks

Chapter 8. Artificial Intelligence-Driven Soil Health Monitoring and Nutrient Management Systems

Chapter 9. Artificial Intelligence-Based Crop Yield Prediction and Advanced Forecasting Model Architectures

Chapter 10. Intelligent Pest Detection Systems and Automated Weed Management Using Computer Vision and AI Techniques

Chapter 11. Global Case Studies on Artificial Intelligence-Driven Smart Farming Systems across Developed Agricultural Economies