Artificial Intelligence in Smart Agriculture: Techniques, Applications and Challenges 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.

T. Monika Singh received her M.Tech degree in Computer Science and Engineering from Osmania University and is currently pursuing a Ph.D. in the Department of Information Technology at Annamalai University. Since 2017, she has been serving as a faculty member in the Department of Computer Science & Engineering to Department of Artificial Intelligence & Data Science at Stanley College of Engineering and Technology for Women. She has extensive experience in both teaching and research and is certified as a Project-Based Learning (PBL) mentor by Wipro, in addition to holding a TalentNext certification in Java Full Stack Development. Her primary research interest is in the field of Machine Learning, and she has authored many research publications indexed in Scopus, along with several other papers published in reputed national and international journals and conferences. She also holds a patent to her name and is an active member of the Association for Computing Machinery (ACM), demonstrating a strong commitment to advancing technological education and innovation.
Dr. C. Kishor Kumar Reddy is a seasoned academician and researcher with over 12 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. 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 250+ 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. 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.
Dr. Payal Bansal has received her B.Tech., M.Tech., and Ph.D. degrees in the field of Electronics Engineering. She has vast teaching experience of more than 17 years in reputed organizations. She completed her Bachelor of Engineering from Rajasthan University, Jaipur, and her Master of Technology in Digital Communication from Rajasthan Technical University. She earned her Ph.D. from JNU. She is a Senior Member of IEEE and a lifetime member of ISTE, IEEE, and IAENG. Currently, she is working at Poornima Institute of Engineering & Technology, Jaipur, Rajasthan, as Head of Research & Outreach, Professor, and Head of the IoT branch. In her research, she has made remarkable contributions in the field of Radio Frequency Communication and has developed a filter that can function as a protective shield to prevent high-frequency radio signals. She has published more than 40 research articles in peer-reviewed journals, including IEEE Xplore, Scopus, and SCI-indexed publications. Her contributions include 18 journal papers, 29 conference papers, and 13 book chapters, along with 9 national and 2 international books. She also holds 5 patents and 1 copyright. Her main research areas include RF Communication, Internet of Things, wideband antenna design, and Machine Learning. Dr. Bansal has organized several national and international conferences, symposia, and webinars. She has also published 3 patents in the fields of antenna design and IoT-based applications under the Intellectual Property Rights of the Government of India. She is actively involved in NAAC SSR preparation and university interface promotional activities and is a professional member of several national and international bodies.
Dr. Denis R is an Assistant Professor and Program Coordinator for Artificial Intelligence & Machine Learning and Cybersecurity at Mount Carmel College, Autonomous, Bengaluru, India. He holds a Ph.D. in Computer Science from Periyar University and is currently pursuing Postdoctoral Research at Lincoln University College, Malaysia. With over 16 years of academic and research experience, his core expertise lies in Cybersecurity, Artificial Intelligence, Machine Learning, Cloud Computing, and Data Analytics. Dr. Denis has published extensively in reputed SCIE, Scopus, Web of Science, and IEEE-indexed journals and has authored multiple textbooks and book chapters in computer science and engineering. He also serves as a peer reviewer for leading international journals published by Springer, Taylor & Francis, and Elsevier. His research interests include secure data communication, hybrid cryptography, federated learning, intrusion detection systems, healthcare security, and intelligent systems. Dr. Denis is an active academic contributor, serving on boards of studies, institutional committees, and international conference review panels, and has received several awards for his research and academic excellence.
Srinath Doss is the Professor and Dean in the Faculty of Engineering and Technology, Botho University, responsible for Botswana, Lesotho, Eswatini, Namibia and Ghana Campuses. He has previously worked with various reputed Engineering colleges in India, and with Garyounis University, Libya. He has written good number of books and more than 80 papers in International Journals and attended several prestigious conferences. His research interests include MANET, Information Security, Network Security and Cryptography, Artificial Intelligence, Cloud Computing and Wireless and Sensor Network. He serves as an editorial member and reviewer for reputed international journals, and an advisory member for various prestigious conferences. Prof. Srinath is member of IAENG and Associate Member in UACEE.

Chapter 1.  Artificial Intelligence for Autonomous Agriculture Foundations, Applications and Opportunities

Chapter 2.  From Traditional Farming to Autonomous Agriculture: The Evolution of Intelligent Farming Systems

Chapter 3.  Agriculture 5.0: Autonomous Intelligence and the Future of Global  Food Security

Chapter 4.  Deep Learning for Intelligent Crop Monitoring, Disease Detection and Yield Prediction

Chapter 5.  Digital Twins for Autonomous Farming: Real-Time Crop Simulation and Decision Support

Chapter 6.  AI-Enabled Remote Sensing and GIS for Intelligent Agricultural Monitoring

Chapter 7.  AI-Driven Precision Agriculture: Autonomous Resource Management and Decision Support

Chapter 8.  Artificial Intelligence for Soil Health, Fertility Assessment and Precision Nutrient Management

Chapter 9.  AI-Enabled Livestock Farming: Intelligent Monitoring Behaviour Analysis and Farm Management 

Chapter 10.  Agricultural Robotics and Autonomous Field Systems for Smart and Sustainable Farming

Chapter 11.  IoT and Smart Sensor Technologies for Real-Time Autonomous Agriculture

Chapter 12.  Blockchain and IoT for Decentralized and Secure Autonomous Agriculture

Chapter 13.  Climate-Smart Agriculture: AI-Based Weather Prediction and Climate-Resilient Farming

Chapter 14.  Federated Learning and IoT for Privacy-Preserving Autonomous Farming Applications

Chapter 15.  Big Data Analytics for Intelligent Agriculture and Real-Time Farm Decision-Making

Chapter 16.  AI-Driven Farm Management Information Systems and Autonomous Decision Support

Chapter 17.  AI-Powered Smart Greenhouses and Controlled Environment Agriculture

Chapter 18.  Socio-Economic, Ethical and Human Dimensions of AI-Driven Autonomous Agriculture

Chapter 19.  Policies, Initiatives and Governance Frameworks for Autonomous Agriculture

Chapter 20.  Future Trends and Innovations in Artificial Intelligence and  Autonomous Agriculture

Chapter 21.  Integrated Autonomous Farming Systems: Convergence of AI, IoT, Robotics and Emerging Technologies