Smart Agriculture through Mathematical Modelling and Computational Approaches presents a comprehensive exploration of advanced computational techniques and mathematical frameworks that are transforming modern agriculture into an intelligent, data-driven, and sustainable system. The book highlights the integration of artificial intelligence, machine learning, remote sensing, Internet of Things (IoT), blockchain, cloud computing, digital twins, and predictive analytics in addressing contemporary agricultural challenges. It systematically discusses applications such as crop yield forecasting, disease prediction, smart irrigation, soil health monitoring, precision farming, risk assessment, and agricultural decision-support systems.

Emphasis is placed on mathematical modelling, optimization methods, simulation techniques, and computational intelligence for improving productivity, resource efficiency, and climate resilience. The volume also examines emerging areas including Web3 technologies, agricultural blockchain systems, agent-based modelling, and AI-enabled smart farming ecosystems. Designed for researchers, academicians, engineers, policymakers, and postgraduate students, this book serves as a valuable reference for advancing sustainable, technology-enabled, and computationally intelligent agricultural systems.

Dr. C Kishor Kumar Reddy, currently working as 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 250+ 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 30+ edited books. He is a member of ISTE, CSI, IAENG, UACEE, IACSIT. His research areas include: Bioinformatics, NeuroScience, Remote Sensing, Deep Learning, Intelligent Systems.

Mrs. B N S M Chandrika is a dedicated Assistant Professor at Gopalan college of Engineering and Management with over 5 years of academic experience in the Department of Mathematics. She holds a Master’s degree in Mathematics from Osmania University. Her core expertise lies in Applied Mathematics, Mathematical Modeling. She is deeply committed to mentoring students in research and innovation, continually striving to advance knowledge and drive progress in her areas of specialization.

Dr. P. R. Anisha is an Associate Professor in the Department of Computer Science & Engineering at Stanley College of Engineering and Technology for Women, Hyderabad, with over nine years of teaching and research experience. She holds a PhD from K L University and has published more than 50+ research papers in reputed international journals and conferences. Her research interests span Artificial Intelligence, Machine Learning, Image Processing, IoT, and data-driven healthcare. She has served as a Special Session Chair at various national and international conferences and is an active member of professional bodies such as ACM and IAENG. She has also co-authored books on C and C++ programming and is recognized as a motivational speaker, contributing significantly to academic and professional communities.

Dr. Inam Ullah Khan is a distinguished academic and industry professional known for his work in Artificial Intelligence, Artificial General Intelligence, UAVs, routing protocols, intrusion detection systems, machine learning, deep learning, and evolutionary computing. He is the Founder of AI-Explain Your Science (AI-EYS), a Senior Member of IEEE, and an active member of several international professional bodies. He currently serves as an Assistant Professor of Artificial Intelligence at Fazaia Bilquis College of Education for Women, Air University, Islamabad, and also mentors and teaches at various institutions, including Corvit Systems, Impact Xcelerator (IE University, Spain), NAVTTC Pakistan, and Lincoln University College, Malaysia. Dr. Khan has previously worked as a Visiting Researcher at King’s College London and held faculty positions at several universities across Pakistan. He holds a PhD and MS in Electronics Engineering from Isra University, along with a Bachelor’s degree in Computer Science, and has published over 100 research papers, authored multiple books, and edited around 20 volumes. A national-level technology expert featured on Pakistan Television, he currently serves as a Postdoctoral Research Fellow at Multimedia University, Malaysia, Visiting Faculty at NAVTTC, Islamabad, and Adjunct Faculty at PSGR Krishnammal College for Women, Coimbatore, India.

Dr. Jothi Paranthaman is an accomplished academic and researcher currently serving as a faculty member in the Faculty of Engineering and Technology at Botho University. With a strong background in engineering and applied sciences, her areas of expertise include smart technologies, computational modeling, and interdisciplinary applications in engineering education. She has contributed to several research projects, academic publications, and curriculum development initiatives aimed at integrating technology-driven solutions into teaching and real-world problem-solving. Dr. Paranthaman is committed to fostering innovation and excellence in engineering education across emerging domains.

Chapter 1. Digital Transformation of Agriculture: Smart Farming Concepts, Constraints, and Future Directions

Chapter 2. Computational Techniques in Agricultural Systems: An Overview of Tools and Applications

Chapter 3. Model-Based Decision Support Systems for Sustainable Agriculture

Chapter 4. AI-Driven Chilli Leaf Disease Classification Using Emerging AgriTech Technologies for Autonomous Crop Health Management

Chapter 5. Yield Forecasting Models: Statistical and Machine Learning Approaches

Chapter 6. Optimizing Irrigation through Hydrological Modelling and Control Theory

Chapter 7. Soil Health Monitoring and Nutrient Dynamics: A Modelling Perspective

Chapter 8. Future Research Directions: Web3, AI, and Digital Twins in Agriculture

Chapter 9. Computational Models for Predicting Crop Diseases and Pathogen Spread

Chapter 10. Risk Assessment and Uncertainty Modelling in Agricultural Decision Making

Chapter 11. Agent-Based Modelling for Intelligent Farm System Simulation and Behaviour-Driven Sustainability Analysis

Chapter 12. Remote Sensing and Satellite Data in Agricultural Monitoring and Forecasting

Chapter 13. Big Data Analytics and Cloud Computing in Smart Farming Systems

Chapter 14. Modelling Socioeconomic Impacts of Smart Agricultural Technologies

Chapter 15. Integrating Multimodal Computer Vision and Mathematical Optimization for Synergistic Crop Health and Soil Nutrient Analysis

Chapter 16. Polygon Network Architecture: Layer-2 Design, Consensus, and Scalability

Chapter 17. Secure Data Sharing and Interoperability with Government and Enterprise Systems

Chapter 18. Security, Privacy, and Regulatory Challenges in Agricultural Blockchain Systems

Chapter 19. Role of Data Science and Artificial Intelligence in Precision Farming