Autonomous biodiversity monitoring through wireless communication technologies and artificial intelligence

Under the ongoing biodiversity crisis due to global environmental change, cost-effective methods are needed for autonomously inferring which species are present in different spatial locations; such monitoring provides critical data for studying impacts of climate change and land use change on biological community dynamics. This project applies wireless communication technologies to automatize audio-based biomonitoring of birds and bats, and develops novel AI-based methods for classifying species and making ecological inferences on audio- and DNA-based data The ongoing biodiversity crisis, characterized by rapid declines in local and global biodiversity, has profound implications on ecosystem and human health. This proposal develops a transformative paradigm for biodiversity monitoring that will impact scientific understanding and provide invaluable data for policymakers concerned with conservation and the impact of climate change.