AI-Powered Acoustic Monitoring for Scalable Biodiversity Tracking

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OceanOS will pilot an innovative marine biodiversity monitoring system to support sustainable growth of offshore wind farms. The project addresses the lack of cost-effective, non-invasive, accurate tools that provide the near real-time species data needed to guide responsible site development.By leveraging AI techniques, the breakthrough pairs non-invasive hydrophone sensors with machine learning biodiversity models trained on acoustic signature databases. This transforms ambient soundscapes, unlocking new horizons for conservation science and policy. The automated identification and geospatial tracking of vocalising marine life reveals population densities, residency times, habitat uses and more -- customisable key indicators for quantifying human impacts and restoration gains.Initial trials will deploy the modular analytics and monitoring platform at an exposed open water site off the North Devon coast adjacent to planned large-scale Celtic Array FLOW development zones.Overall this project will deliver comprehensive, credible biodiversity due-diligence capability currently lacking, enabling the renewable energy transformation imperative for net zero. Quantified, dynamic, and scalable marine life assessments de-risk project development, attract investment and build public trust. The innovation will unlock adjacent markets from shipping to aquaculture, cementing UK leadership in sustainable blue economic growth rooted in science and technology innovation.