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International projects source: SICRIS

Using Image-based AI for Insect Monitoring & Conservation

Research activity

Code Science Field Subfield
1.03.00  Natural sciences and mathematics  Biology   

Code Science Field
B003  Biomedical sciences  Ecology 
Keywords
camera, computer vision, statistics, autonomous, standards
Organisations (1) , Researchers (1)
0481  University of Ljubljana, Biotechnical Faculty
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  22766  PhD Gorazd Urbanič  Biology  Researcher  2023 - 2025  381 
Abstract
The InsectAI COST action will support insect monitoring and conservation at the national and continental scale in order to understand and counteract widespread insect declines. The Action will bring together a critical mass of researchers and stakeholders in image-based insect AI technologies to direct and drive the research agenda, build research capacity across Europe, and support innovation and application. There is mounting evidence that populations of insects around the world are in sharp decline. Understanding trends in species and their drivers are key to knowing the size of the hallenge, its causes, and how to address it. To identify solutions that lead to sustainable biodiversity alongside economic prosperity, insect monitoring should be efficient and provide standardised and frequently updated status indicators to guide conservation actions. The EU Biodiversity Strategy 2030 identifies the critical challenge of delivering standardised information about the state of nature, and image-based insect AI can contribute to this. Specifically, the EU Nature Restoration Law will likely set binding targets for the high resolution data that cameras can provide. Thus, outputs of the Action will contribute directly to EU policies implementation, where biodiversity monitoring is considered a key component.
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