Artificial Intelligence in Agricultural Systems

Artificial Intelligence in Agricultural Systems: Fundamentals and Advances focuses on advancements in AI in and draws upon the multi-faceted challenges of modern agriculture. This book curates the latest strands of AI applications that are reshaping agricultural systems, including current trends and emerging technologies. It offers an overview of the evolving agricultural landscape and foregrounds the critical role of AI in driving innovation and enhancing productivity in this essential sector. Organized into four parts, it introduces agricultural systems and AI fundamentals, including machine learning, deep learning, natural language processing, and robotics. It then pivots to data collection and processing techniques, explicating the use of sensors, IoT devices, remote sensing, and UAVs. Core applications in crop and livestock management receive emphasis, covering yield prediction, pest detection, precision irrigation, and sustainable farming practices. The final sections address the limitations of AI in agriculture, future trends, and policy recommendations, providing an overarching understanding of AI's responsible adoption. Artificial Intelligence in Agricultural Systems is an important resource for upper-level undergraduate and graduate students studying the impact of AI technologies on agriculture and food production. Researchers, practitioners, and policymakers studying the intersections of agriculture, environmental science, data science, and engineering will find this book compelling as well.