WG2 Image Collection

In WG2 we focus on technology to collect images and their effects on downstream AI-based analysis. We co-design best practices for deployment and processing, build capacity in the community to leverage these new methodologies, and spur the revolution of insect monitoring at scale, both in nature and in the lab.

Specifically, we bring together hardware developers and users, facilitate networking, and spark collaborations during workshops and conferences. We run training schools to build expertise and encourage wider uptake of new monitoring paradigms in the community, alongside traditional programs. We directly engage with the user base, from academics to stakeholders, to address specific monitoring needs and simultaneously innovate the methodology to benefit the whole community. We raise awareness by running citizen-science initiatives, engaging makers and biodiversity enthusiasts to “tinker” bottom-up solutions to monitor insects and biodiversity.  The activities of WG2 tightly integrate with WG1 to design fit-for-purpose hardware, with WG3 to ensure robust, transparent AI-based inference, and with WG4 to integrate approaches and address biases, as well as strongly contributing to the development of guidelines for standardization across WGs.