75% of insect mass has been lost in the last 30 years. The BeeVision project team is therefore developing an AI system to monitor pollinator diversity by automatically recognizing the flight patterns of different insect groups.
The loss of pollinators and other insects has reached alarming proportions over the last 30 years. This has serious implications for biodiversity and food security, as pollinators are essential for over 80% of our food crops. Unfortunately, detailed baseline data on pollinator diversity is lacking as current survey methods are time consuming and require invasive sampling.
Therefore, the interdisciplinary team around "BeeVision" is developing a radically new, non-invasive monitoring method with great potential and benefits for biodiversity research. BeeVision combines technical advances in the evaluation of images taken with dynamic image sensors with artificial intelligence methods and our expertise in the field of pollinators. Initial tests with this sensor for insect monitoring have been successfully carried out and their benefits confirmed.
BeeVision will be used to monitor the flight patterns of all pollinators in a landscape or agricultural field and thus record their occurrence. The aim is to classify their flight activity patterns using machine learning and assign them to the corresponding insects such as honeybees, bumblebees, other wild bees, hoverflies, butterflies or other insects.