Description
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.