Underwater Noise Identification

Underwater noise identification from acoustic recordings using spectrograms


To develop, using the iMagine platform, a prototype service for processing acoustic underwater recordings for identification and recognition of marine species and other noise types (e.g., offshore piling).

Development actions during iMagine


Setting up development environment at iMagine platform


Connecting the Mongo database to the iMagine platform for ingesting and extracting data


Developing, training and refining the AI model at the iMagine platform


Enhancing the FAIRness of data output in accordance with community standards and relevant vocabularies


Documenting approach and resulting prototype


Contributing to dissemination and outreach

Expected Results


The underwater sound classification service has large potential to support the scientific community in marine biodiversity and ecosystem research. Underwater sound and noise pollution are increasingly recognized as an essential indicator of healthy seas and oceans. 

Detecting and classifying different species can contribute to species abundance assessment, and detection and characterization of noise pollution can provide insight in effects of human activities on marine life.


With this, the scientific interest in underwater sound detection and classification is rapidly increasing. Potential policy supporting examples are downstream applications in monitoring for MSFD (as part of the 11th GES) and OSPAR Underwater noise indicators.

Involved Partners