AI-Powered Acoustic Monitoring for Scalable Biodiversity Tracking

OceanOS将试点一个创新的海洋生物多样性监测系统，以支持海上风电场的可持续发展。该项目解决了缺乏成本效益，非侵入性，准确的工具，提供近实时的物种数据，需要指导负责任的网站开发。通过利用人工智能技术，该突破将非侵入式水听器传感器与声学特征数据库训练的机器学习生物多样性模型配对。这改变了环境声景，为保护科学和政策打开了新的视野。发声海洋生物的自动识别和地理空间跟踪揭示了人口密度、居住时间、栖息地使用情况以及更多可定制的关键指标，用于量化人类影响和恢复收益。初步试验将在北德文郡海岸附近的一个暴露的开放水域部署模块化分析和监测平台，该水域毗邻规划的大型凯尔特阵列流开发区。总体而言，该项目将提供目前缺乏的全面、可信的生物多样性尽职调查能力，使可再生能源转型成为实现净零排放的必要条件。量化的、动态的、可扩展的海洋生物评估可以降低项目开发的风险，吸引投资并建立公众信任。这一创新将打开从航运到水产养殖的邻近市场，巩固英国在以科技创新为基础的可持续蓝色经济增长方面的领导地位。

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.