Smart Adaptive Solutions to Underwater Noise from Ships

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Executive Summary

An adaptive physics-based machine learning framework for anthropogenic noise and ocean soundscape


In collaboration with the University of British Columbia (UBC), Clear Seas is undertaking a project to develop innovative solutions to ship-source underwater noise to help make the ocean soundscape less stressful to marine mammals. Funded by Transport Canada’s Quiet Vessel Initiative and Mitacs’ Accelerate Program, this research bridges the gap between ship design and marine biology based on the premise that ships could become a more sympathetic part of the marine environment if they leveraged the knowledge of the marine mammals they encounter.

This multi-year project brings together an interdisciplinary research team led by Dr. Rajeev Jaiman and Dr. Jasmin Jelovica from UBC’s Naval Architecture and Marine Engineering program, in collaboration with Dr. Andrew Trites and Dr. David Rosen from the UBC Marine Mammal Research Unit.

Underwater noise from shipping vessels poses a serious threat to both the marine environment and the marine mammals that rely on sound to survive and thrive.  Using an adaptive physics-based machine learning framework, this project will develop and test a noise prediction toolkit on board a Canadian Coast Guard research vessel. The toolkit will allow ships to tune and adjust their noise in real-time and based on knowledge of nearby marine mammals. It will also lead to the creation of a software simulation of smart adaptive noise mitigation in action and demonstrate its application to all types of vessels.

The project team believes the that the work conducted under this research initiative will help shape the ships of the future by rethinking their design.