Graduate students and young researchers typically spend months watching sometimes murky underwater footage and making notes about the fish, crustaceans or corals they’ve seen.

“It’s a long and tedious process,” said Ms. Eboigbe, who manages data collected by oceanographic buoys and the Holyrood observatory operated by MI’s Centre of Applied Ocean Technology.

“Artificial intelligence can be used for the preliminary processing of these videos, and it would allow for keyword searches of the annotated video.”

Comfort Eboigbe,
Ocean Data Specialist

Originally from Nigeria, Ms. Eboigbe received her master of science in environmental systems engineering and management from Memorial in 2020.

She also holds Bachelor in Chemical Engineering from Covenant University in Ota, NG.

Hours versus minutes

Anything that speeds up the process would be a welcome tool for Robyn Whelan and Hannah Steele. Both are both working on the marine conservation area project.

“One of the goals of the project is to collect baseline information to provide an overview of the biodiversity within these areas,” said Ms. Whelan, a fisheries technologist with MI’s Centre for Fisheries Ecosystems Research.

She says it takes about an hour to analyse and annotate 10 minutes of video.

“It could take many hours to go through all the footage. With this model, it could take minutes to do the same review,” said Ms. Whelan.

Ms. Steele, a part-time research assistant and project blogger working on her bachelor of technology, agrees.

“There is a lot of marine life biodiversity in the oceans off Newfoundland and Labrador. You spend a lot of time flipping through textbooks to identify corals and sponges, so it would reduce the time it takes to review the underwater footage.”

Learn more in the Gazette.