AI for Agriculture: Intelligent Systems for Computer Vision, Drones, and Autonomous Farming - Tapa blanda

Sinopsis

AI for Agriculture is a practical and forward-looking guide to how artificial intelligence is transforming modern farming. Written for students, researchers, agricultural professionals, technology enthusiasts, and farm decision-makers, this book explains how AI, machine learning, deep learning, computer vision, drones, robotics, IoT, and emerging generative AI can work together to create smarter, more productive, and more sustainable agricultural systems.

Starting with the foundations of agricultural AI, the book introduces essential concepts without assuming a specialized background in computer science or agronomy. It then explores AI-driven forecasting for crop yields, weather, soil moisture, climate risks, agricultural markets, and commodity prices. Readers will discover how computer vision can detect plant diseases, pests, and weeds, support precision spraying, estimate crop conditions, and monitor livestock.

The book also examines drones and autonomous ground robots, showing how intelligent machines can collect data, monitor fields, automate operations, and support precision agriculture. Dedicated coverage of IoT sensors, smart irrigation, controlled-environment agriculture, generative AI, agentic AI, and large language models highlights the technologies shaping the next generation of farming.

Beyond technology, AI FOR AGRICULTURE addresses productivity, sustainability, food security, ethics, data governance, trust, and responsible adoption. Real-world case studies and practical guidance connect concepts to agricultural applications, while the final chapters explore the future of AI and provide a roadmap for building an AI-ready farm.

Whether you are beginning your journey into agricultural AI or seeking a comprehensive reference for modern smart farming, this book provides a clear bridge between artificial intelligence and real-world agricultural innovation and practice.

• Foundations of Agricultural AI — Understand machine learning, deep learning, explainable AI, edge learning, and the role of AI in the fourth agricultural revolution.
• AI Forecasting and Prediction — Explore crop-yield forecasting, weather and climate prediction, soil-moisture modeling, and agricultural market and price forecasting.
• Computer Vision for Agriculture — Learn how AI-powered vision systems support plant disease detection, pest monitoring, weed detection, precision spraying, and livestock monitoring.
• Drones, Robotics, and Smart Machinery — Discover how UAVs, autonomous ground robots, and intelligent agricultural machinery enable precision monitoring and automated field operations.
• IoT, Sensors, and Smart Irrigation — Examine connected sensors, environmental monitoring, precision irrigation, edge computing, and data-driven farm management.
• Generative and Emerging AI — Explore generative AI, agentic AI, large language models, controlled-environment agriculture, and smart greenhouse technologies.
• The Future of Smart Agriculture — Examine productivity, sustainability, food security, ethics, data governance, global case studies, and a practical roadmap for building an AI-ready farm.

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