Monitoring of insects, e.g. of hoverflies as important pollinators and antagonists of various pests, is used to assess their population sizes and design effective conservation measures. With traditional monitoring methods, insects are trapped and killed in most cases, to be able to identify the respective species based on microscopic features or with molecular techniques. Camera traps for insect monitoring can yield data at a high spatiotemporal resolution with less time and money investment. This method could complement traditional monitoring methods (with high taxonomic resolution) and be used as an additional monitoring tool.

In the project MonViA (Monitoring of Biodiversity in Agricultural Landscapes) a weatherproof DIY camera trap system was developed, which is completely self-sufficient by generating the necessary power with a solar panel and can be deployed in the field for the whole season. Flower-visiting insects are visually attracted by a platform with artificial flowers and are detected with an AI-enabled camera in real time when landing on the platform. The areas with detected insects are cropped from the images and saved, and can be used for further classification (= identification) and analysis. By providing detailed instructions and completely open source software, everybody who is interested can build and deploy the camera trap, e.g. in Citizen Science projects or in the private garden.

Website: https://maxsitt.github.io/insect-detect-docs/
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