Implementation of an app-supported human–AI interaction for farmers to collect and valorize field data for the needs of precision agriculture. Collaborative project with the Institut für Zuckerrübenforschung gGmbH.
The project develops a mobile app that supports farmers in collecting field data to improve an AI model for detecting Cercospora leaf spot disease in sugar beet. The AI is based on satellite and weather data but requires further training data to increase its accuracy. Through a citizen-science approach, farmers provide data and in return benefit from more precise disease forecasts. This enables the targeted application of crop protection products, reduces costs and minimises environmental impact. In the future, the AI can be transferred to other plant diseases and crops. The project examines feasibility, develops the app, integrates it into the existing AI model and tests it with farmers. The goal is a working prototype that is continuously optimised and supports sustainable, data-driven agriculture in the long term.
