Researchers develop machine learning model that will support safe and accurate decision making for t

Researchers at Dalhousie and ocean data analytics innovation environment DeepSense have developed a machine learning method for predicting wind speed and wave height measurements. Such measurements support safe and more accurate decision making by the Halifax Port Authority and the Halifax Marine Pilots.

Results published in the Journal for Ocean Technology demonstrate how the team used data from smart buoys to provide predictions for use during periods of scheduled buoy maintenance and/or spontaneous sensor failures. These predictions will be valuable to the Port community in providing continuity of critical information used in the safe navigation of vessels within the Port of Halifax and the safe transfer of Halifax Marine Pilots between pilot boats and commercial vessels.

The DeepSense/SmartAtlantic project is a collaboration between the Centre for Ocean Ventures and Entrepreneurship (COVE), DeepSense, the Halifax Port Authority (HPA)and the Canadian Marine Pilots Association (CMPA).

Based out of the Faculty of Computer Science with funding and support from the Atlantic Canada Opportunities Agency (ACOA), the Province of Nova Scotia, the Ocean Frontier Institute (OFI) and IBM, DeepSense drives growth in the ocean economy through artificial intelligence, machine learning and big data applied research.

Making predictions

Initiated by COVE with partners at the HPA and the CMPA, the project aimed to provide a highly accurate additional level of redundancy for the SmartAtlantic Herr....

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