SharkSpotter, which uses artificial intelligence to spot sharks and protect people in the water, has been named one of Australia's top innovations at the annual iAwards.
The shark detection system, developed by the UTS School of Software, was named the national AI or Machine Learning Innovation of the Year at the Australian Information industry Association's annual iAwards.
A world-first software system that allows for faster reaction times to potential shark threats, SharkSpotter was developed by UTS with industry partner The Ripper Group.
Little Ripper Lifesavers are unmanned aerial vehicles (UAVS or drones) created to react quickly and efficiently to save lives in the water.
The drones are loaded with the SharkSpotter AI application, which can efficiently distinguish and identify sharks in real time using image processing techniques, state-of-the-art sensors and software.
“This automated system for detection and identification of sharks in particular, and marine life or objects more generally, uses cutting-edge deep learning neural networks and image processing techniques for object recognition and classification,” explains Dr Nabin Sharma, from the Centre of Artificial Intelligence in the UTS School of Software.
Deep learning algorithms and image processing techniques examine live video feeds from the drones, hovering over the ocean, to detect the presence of sharks and their potential threat to water users.
SharkSpotter is a great example of how an AI application can help humans, as it has significantly higher rates of visual accuracy in shark detection than we have
Dr Nabin Sharma
The system has 90 per cent accuracy in detecting sharks, distinguishing between them and 16 other categories of marine life, such as dolphins, rays and whales.
It can identify surfers, swimmers, boats, humans and other objects in the water. This visual information is relayed immediately for interpretation to emergency services, beach lifeguards and water users.
“Information is sent to a control station on the beach where a human responder will have final say on what action to take – this could be continued monitoring of the shark to see if it moves away from swimmers or, if it appears to become a direct threat, sounding alarms and advising evacuation,” Dr Sharma says.
"SharkSpotter is a great example of how an AI application can help humans, as it has significantly higher rates of visual accuracy in shark detection than we have. The drone will certainly help us to improve detection rates and to maintain safer conditions for those in the water.”
SharkSpotter is already deployed at dozens of beaches in Queensland and New South Wales, with much interest elsewhere in having SharkSpotter technology patrol beaches.