Innovating the Future of Surf Patrol
Sharkspotter: the world's first drone-enabled automatic shark detection system
Research Lead
Professor Michael Blumenstein
Associate Professor Nabin Sharma
Collaborators
The Ripper Group
Sharks, rips and other factors present real challenges to keeping swimmers safe in our oceans. A pioneering collaboration between UTS researchers and The Ripper Group is fusing artificial intelligence and drone technologies to herald a new wave in surf lifesaving. SharkSpotter leverages advanced machine learning techniques known as ‘deep learning’ to detect sharks and other potential threats in real time.
The UTS-developed software turns aerial drones into powerful and highly accurate shark detectors, analysing streaming video from the drone to detect valid objects instantly. It then categorises them into one of 16 categories such as shark, whale, dolphin, ray, various watercraft and boat types, surfer and swimmer. When a shark is detected, SharkSpotter provides a visual indication on the computer screen and an audible alert to the operator. The operator verifies the alert, triggering system text messages to surf lifesaving crews on the ground and enabling them to act quickly. It’s not just swimmers who benefit: safer beaches are a boon for coastal tourism and regional economies. The ground-breaking technology also demonstrates more effective ways to detect moving objects in a complex, dynamic marine environment, with significant potential to protect our unique marine life.