A near real-time orca detector using sound and acoustic context awareness is being developed for the Salish Sea, with potential uses including the identification of these mammals for vessels in the area. Fabio Frazao, [one of the first recipients of the $20,000 Roy Hyndman Ocean Observing Award](https://www.oceannetworks.ca/news-and-stories/stories/meet-the-first-recipients-of-the-roy-hyndman-award/), has completed his one-year project with Ocean Networks Canada (ONC). Using hydrophone data from ONC’s Victoria Experimental Network Under the Sea (VENUS) observatory, Frazao expanded upon his artificial intelligence (AI) algorithm to detect and classify orca sounds in the Salish Sea. Orcas make a wide range of sounds like whistles, echolocation clicks, and low-frequency pops, which can be mistaken for other marine mammals and masked by ambient underwater noises. The AI algorithm learned from thousands of these orca vocalizations and other sounds recorded from ONC’s hydrophone network deployed in the Salish Sea. The detector was then tested on 65 hours of acoustic data to detect and distinguish orca sounds.