商品簡介
Intelligent Agriculture Systems presents a complete, end-to-end engineering architecture for AI-driven farming across twenty chapters and seven parts. Beginning with foundational data infrastructure, it progresses through soil and environmental intelligence, water and nutrient optimization, plant health and disease management, edge and federated learning, and the full pipeline from yield prediction to farmer-facing interfaces and system economics, closing with data privacy, ethics, and emerging directions such as foundation models and autonomous robotics. Unlike works that isolate machine learning from agronomic knowledge, this book integrates both in depth, offering worked examples, algorithms, case studies, and review questions throughout. Readers learn to design sensor networks, build crop and yield models, architect IoT and edge systems, implement federated learning across farms, and deploy explainable, farmer-facing decision support tools. Written for engineers, researchers, graduate students, and policymakers, it serves as both a structured textbook and a practical reference.
