Transforming Agriculture with Artificial Intelligence

This book discusses the recent deep learning and the Internet of Things tools to optimize resource allocation, enhance decision-making processes, and ultimately boost crop yields. It covers artificial intelligence applications in pre-harvesting, climate and weather prediction for optimized planting, soil nutrient management through artificial intelligence-driven analytics, and predictive modeling for crop health. This book:Discusses artificial intelligence-driven crop monitoring techniques that optimize water and nutrient usage leading to improved yields and better resource utilization. Illustrates artificial intelligence-based disease and pest detection systems for early interventions and reducing crop loss. Explores artificial intelligence-based weather forecasting models that enhance the decision-making for agricultural activities like planting, irrigation, and harvest scheduling. Focuses on employing smart technologies to optimize planting schedules, automate crop health monitoring and pest detection, and enhance resource efficiency through real-time data analytics. Covers artificial intelligence algorithms for soil analysis before planting, computer vision for real-time crop monitoring during growth, and machine learning for yield prediction and harvest optimization. It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communication engineering, agriculture engineering, crop science, computer science and engineering, and information technology.