Project description
Bioacoustic AI 'machine listening' for wildlife monitoring
Biodiversity loss is ranked as one of the top five global risks, both in impact and likelihood. Anticipated significant declines in bird and insect populations could trigger profound ecological changes. Yet, data for monitoring biodiversity change remain incomplete. Sound recording could help: it is cheap and rapid, and modern machine learning can radically improve its precision. However, there are two barriers: AI-enhanced acoustic tools for wildlife monitoring are mostly at prototype stage; and there is a big skills gap – it is very rare to find an expert in animals, sound, and AI methods. The MSCA-funded BioacAI project will address these challenges by developing new AI methods directly within the context of acoustic wildlife monitoring – using new acoustic devices, algorithms, and insights into ecology and behaviour.
Objective
"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."
Fields of science
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral NetworksCoordinator
2333 CR Leiden
Netherlands
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Participants (8)
5037 AB Tilburg
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116 36 Praha 1
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5617 BC Eindhoven
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
3000 Leuven
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75794 Paris
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370 05 Ceske Budejovice
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33100 Tampere
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80539 Munchen
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Partners (11)
3972 LK Driebrgen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
79102 Freiburg im Breisgau
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00040 Castel Gandolfo
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
148 00 Prague
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SO53 3LG EASTLEIGH
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
75005 Paris
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SE11 5RD London
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
6525 ED Nijmegen
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
44321 Nantes Cedex 3
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78464 Konstanz
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WC1E 6BT London
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