AI drones are being used to patrol the skies and keep swimmers safe as great white sharks prowl off California beaches.
SharkEye, an initiative by the University of California Santa Barbara's Benioff Ocean Science Laboratory (BOSL), has been brought in at Padaro Beach in the Golden State, a stretch of sand popular with young people learning to surf. Unfortunately, it's also popular with young great white sharks.
If a shark is detected, SharkEye sends a text alert to around 80 people who have subscribed to their alerts, including local lifeguards, surf shop owners, and parents of kids taking surfing lessons.
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They monitor videos streamed from a camera, requiring a pilot to stay glued to a screen, battling choppy water and sun glare, to distinguish sharks from paddleboarders, seals, and swaying kelp strands. However, one study revealed that human-monitored drones only detect sharks about 60% of the time.
SharkEye, being part research program and part community safety tool, uses the video it collects to study shark behavior. It's also feeding its footage into a computer vision machine learning model a type of artificial intelligence (AI) technology that enables computers to extract information from images and videos to train it to detect great white sharks near Padaro Beach, close to the city of Santa Barbara.
"Automating shark detection ... can (also) be really helpful for a lot of communities outside of ours here in California," Neil Nathan, a project scientist with BOSL, told CNN.
Rising ocean temperatures are pushing sharks into new habitats and juvenile great whites, which can grow to about eight to 10 feet long, like to swim near the shore, making them more visible to beachgoers. Although there hasn't been a fatal attack recorded at Padaro Beach, some community members were concerned when sharks began loitering there.
That's why SharkEye has been regularly running drone flights to monitor the coastline for about five years, once spotting 15 juvenile great white sharks in a single day. Early tests indicate that the AI technology is already performing "incredibly well," detecting most sharks a human can, and sometimes sharks that a human missed, perhaps because it was swimming too deep to spot easily, said Nathan.
This summer, the project began field testing its technology by pitting drone pilots against AI. Its pilot surveys the area and counts the number of sharks she spots. Then SharkEye's model analyzes the video to see how many sharks it can find.
Today, the community alerts are based on human analysis. If all goes swimmingly, those reports may become AI-assisted with manual monitoring and checks by the end of the season, or the start of next summer, said Nathan. In the future, the process may even become totally automated, making it faster and potentially more accurate.
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