Vision-Driven Farming. A Practical Guide to Object Detection, Phenotyping, and Edge AI Deployment for Autonomous Agricultural Systems. (en Inglés)
Reseña del libro "Vision-Driven Farming. A Practical Guide to Object Detection, Phenotyping, and Edge AI Deployment for Autonomous Agricultural Systems. (en Inglés)"
Headline: Bridge the gap between Deep Learning research and the rugged reality of the field.
The future of global food security isn't just in the soil-it's in the silicon. As the agricultural industry undergoes a massive shift toward autonomy, the demand for engineers who can deploy robust, real-time Computer Vision at the edge has never been higher. Yet, most AI textbooks stop at the edge of the lab, failing to account for the dust, sun-glint, and variable biology of the real world.
Vision-Driven Farming is the definitive, code-first guide to building production-ready perception systems for the next generation of agriculture.
Written by MOMENT TECH, this book bypasses the fluff and dives straight into the systemic patterns required to build autonomous systems that actually work. From the mathematics of multispectral sensing to the deployment of optimized models on edge hardware, you will learn how to transform raw pixels into actionable agricultural intelligence.
Inside this book, you will master:
The Full Lifecycle of Agri-Vision: Move from data acquisition and multispectral alignment to advanced object detection and instance segmentation.
Digital Phenotyping: Learn the precise geometric math needed to measure plant morphology, leaf area, and biomass estimation.
The "See and Spray" Pattern: Implement real-time Green-on-Green discrimination logic to reduce chemical waste and target weeds with surgical precision.
Edge AI & Model Optimization: Master Quantization, Pruning, and TensorRT conversion to run complex models at 30+ FPS on low-power hardware like NVIDIA Jetson.
Closing the Loop: Bridge the gap between pixels and actuators using ROS 2, coordinate transformations, and visual servoing.
Scalable MLOps: Build the infrastructure to manage a fleet of autonomous rovers, including drift detection and automated "Data Flywheels" for continuous improvement.
Why this book?
Whether you are a Python developer entering the Agri-Tech space, a robotics engineer looking for better perception patterns, or a student of precision agriculture, this book provides the "Blueprint" you've been looking for. Every chapter includes theoretical foundations followed by practical, production-ready Python implementations.
Stop building prototypes. Start engineering the future of the harvest.
