Precision agriculture is a farming-management approach that uses sensing, geolocation, and data analytics to observe and respond to variability within fields at fine spatial resolution. It applies inputs such as water, fertiliser, and pesticide only where and when needed, improving yield and reducing waste. It integrates IoT sensors, satellite and drone imagery, and increasingly autonomous ground robots.
Content
- The approach fuses soil-moisture and weather sensors, multispectral imagery, and GPS-guided machinery to build per-zone prescriptions. Autonomous and semi-autonomous robots perform targeted weeding, spraying, planting, and harvesting, while machine-learning models predict yields and detect disease early, reducing chemical use and environmental impact.