The MVOS Lab team developed an AI-driven robotic sprayer that uses real-time weed detection and canopy area estimation to apply herbicide only where it's needed and adjusts its amount based on weed canopy area, reducing chemical use, labor, and environmental impact.

This project was inspired by the challenges faced by farmers in South Dakota related to excessive herbicide use, high input costs, and increasing herbicide resistance. Through SDSU Extension and local grower conversations, we identified the need for targeted weed management solutions.

Traditional blanket spraying leads to overuse of herbicides, causing environmental harm, health risks, and high costs.