Artificial Intelligence and Deterioration of Ocean Ecosystem

In the context of ocean sustainability of west coast of Canada, some questions that need to be considered are: what is the significance of environmental indicators related to the impact on marine aquatic species? How can changes in environment be predicted by patterns of bioindicators, for example as a result of hypoxia, affecting farmed and wild salmon? A starting point to answer these questions is the development of a centralized, common, accessible database that documents the shift in marine observation metadata collected in the area. The objective of the study is to explore the spatial-temporal correlation between environment parameters and biological measurement of aquatic species in BC. We will develop a deep learning platform to integrate the information from environment conditions and the biological information of marine aquatic speices as follows: mortality of farmed Atlantic salmon (Salmon salar), abundance of wild Pacific salmon, and abundance of amphibian egg abundance in upstream habitat of wild salmon. The integration modeling of different sources of data, as the major output of the project will provide the analytic tool for ocean ecosystem service in the country.

Faculty Supervisor:

Kai Liu


Beibei Jia


Insight Academy of Canada


Computer science




University of Prince Edward Island



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