Bioacoustic AI for wildlife protection
Lead Research Organisation:
University College London
Department Name: Genetics Evolution and Environment
Abstract
The biodiversity crisis is coming into sharp focus. The BioacAI network will establish a vital modern evidence source for wildlife protection, by bringing the promise of AI-powered acoustic monitoring to fruition.
Biodiversity loss is ranked as one of the top 5 global risks, both in impact and likelihood (World Economic Forum 2020, 2021, 2022). Continental-scale assessments warn of population declines in major taxa such as birds and insects. Yet data for monitoring biodiversity change remain incomplete - spatially, temporally and taxonomically. To stabilise biodiversity trends and assess ecosystem restoration interventions, it is crucial to monitor the world's wildlife better, faster, and to provide rapid intelligence that can enable us to manage these risks.
Sound recording is a cheap, rapid and powerful way to monitor many key animal species, and modern machine learning can radically improve its scale and precision. However, there are two barriers: AI-enhanced tools for bioacoustic monitoring are at a low readiness level, with few end-to-end solutions available; and there is a big skills gap - no current training programme produces experts with skills spanning acoustics, artificial intelligence (AI) and zoology/ecology.
The BioacAI doctoral network is designed to address exactly these issues. Our research programme develops new AI methods directly within the context of acoustic wildlife monitoring, using devices from leading European bioacoustics companies, in active wildlife monitoring deployments.Our training programme provides "full stack" bioacoustic AI skills and targeted research experience, to build the next generation of professionals - the people who innovate with technology to monitor and understand animals at unprecedented global scale and detail.
Biodiversity loss is ranked as one of the top 5 global risks, both in impact and likelihood (World Economic Forum 2020, 2021, 2022). Continental-scale assessments warn of population declines in major taxa such as birds and insects. Yet data for monitoring biodiversity change remain incomplete - spatially, temporally and taxonomically. To stabilise biodiversity trends and assess ecosystem restoration interventions, it is crucial to monitor the world's wildlife better, faster, and to provide rapid intelligence that can enable us to manage these risks.
Sound recording is a cheap, rapid and powerful way to monitor many key animal species, and modern machine learning can radically improve its scale and precision. However, there are two barriers: AI-enhanced tools for bioacoustic monitoring are at a low readiness level, with few end-to-end solutions available; and there is a big skills gap - no current training programme produces experts with skills spanning acoustics, artificial intelligence (AI) and zoology/ecology.
The BioacAI doctoral network is designed to address exactly these issues. Our research programme develops new AI methods directly within the context of acoustic wildlife monitoring, using devices from leading European bioacoustics companies, in active wildlife monitoring deployments.Our training programme provides "full stack" bioacoustic AI skills and targeted research experience, to build the next generation of professionals - the people who innovate with technology to monitor and understand animals at unprecedented global scale and detail.
Organisations
People |
ORCID iD |
| Kate Jones (Principal Investigator) |