Ecosystem Monitoring using Deep Learning

This is an umbrella project that develops methods to monitor animals and more broadly biodiversity in natural environments. It focuses predominantly on acoustic methods but data fusion with visual and abiotic sensors is also considered. This is part of of our broader initiative in the Environmental Informatics Hub to develop the technologies that are required to effectively support conservation and biodiversity research.

We work both in terrestrial environments as well as marine environments (terrestrial: mostly conservation for threatened birds and amphibians, marine: monitoring the health of coral reefs).

Current foci include (1) acoustic methods for autonomous coral reef monitoring, (2) acoustic identification of individual animals (rather than just species) as the basis of non-invasive mark-recapture methods, and (3) edge-AI for autonomous realtime monitoring.

Projects in any of these areas can be negotiated. 

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