Pollinating insects are essential for ecosystems but have declined significantly in the Northern Hemisphere. Gathering timely, robust data to support their conservation is vital yet challenging, as traditional monitoring methods are often time-consuming, lethal, and require expert knowledge.
New approaches such as bulk image collection offer promising, non-invasive solutions.
DiMON aims to develop a non-lethal, compact device that, when coupled with traditional entomological traps, captures high-resolution, multi-view insect images to improve taxonomic accuracy and streamline data collection. By integrating image-based AI technologies into insect monitoring, DiMON aims to serve a diverse range of users, from scientists to educators.
Insect populations are declining, and understanding these trends is crucial for effective conservation. The objective of DiMON is to provide efficient, non-lethal and regularly updated data on insect populations, targeting a wide range of users, from scientists and farm advisors to citizens, enabling more accurate, scalable monitoring. This inclusive approach will support sustainable biodiversity while reducing reliance on traditional, time-consuming methods.