ROSIE: autonomous mobile sensor system for scanning of fields and crops by npk design

In collaboration with our project partners, we will execute this project from 2024 to 2026, working iteratively from training an AI database to a working autonomous system at the end of the project. By combining an autonomously driving robot with AI and ecosystem-friendly preventive treatments, we are taking an important step towards a more efficient and environmentally friendly future for agriculture. This project is supported by the Horst aan de Maas Tree Cultivation Study Club and is funded through the European Innovation Partnership (EIP). The robot is equipped with cameras and lights to collect images. It uses AI to quickly analyze these images and detect subtle signs of disease before visible symptoms appear. By automating disease recognition and mapping weak spots with AI and GPS, treatments are targeted and it also helps Compas Agro to test biostimulants. This helps develop sustainable alternatives to chemical crop protection, leading to healthier and more resilient plants. Currently, fungal disease detection in rose nurseries is manual, labor-intensive and typically results in widespread fungicide use to prevent disease spread. To address this, we are collaborating with our project partners Mythronics, Compas Agro, and Frank Coenders Nurseries to develop an autonomous robot using AI-powered image recognition. This technology will detect diseases like powdery and downy mildew early and enable precise, targeted treatments. The use of chemical crop protection harms sustainability by disrupting ecosystems and fostering resistance in pathogens. To address this, we joined a multi-year EU-funded research-project. We explore how AI can reduce reliance on chemical crop protection while supporting the development of biological alternatives.