Westpac Little Ripper Lifesaver and Shark Spotter AI Algorithm Recognized

The Ripper Group and University of Technology Sydney(UTS), in a highly successful collaborative partnership, have won the National Award for the iAwards Artificial Intelligence or Machine Learning Innovation of the Year in Melbourne, Australia.

This was for the Westpac Little Ripper Lifesaver and SharkSpotter AI algorithm which was developed collaboratively with University of Technology, Sydney.  It follows on from the three category wins at the NSW State Awards recently.

This means that the Ripper Group will now represent Australia in this category at the international awards in Guangzhou, China, October 9 -13 October.

The award comes on the heels of the Westpac Little Ripper Lifesaver drone executing the world’s first surf rescue by a drone on January 18 this year. Two young men had been swept out to sea at Lennox Head, and the Westpac Little Ripper drone was deployed to drop it’s SOS marine pod to the boys. The SOS marine pod inflated on contact with the water, and the two boys hung onto the inflatable device and were pushed safely to shore by the wave action.

"SharkSpotter automated system for detection and identification of sharks in particular, and marine life/objects more generally, uses cutting edge deep learning neural networks and image processing techniques for object recognition  and classification,” said Dr Nabin Sharma, UTS School of Software.

Deep learning algorithms and image processing techniques examine live video feeds from the drones to detect the presence of sharks and their potential threat to water users. The system has 90 percent accuracy in detecting sharks, distinguishing between them and 16 other categories of marine life such as dolphins, rays and whales and can identify surfers, swimmers, boats, human beings and other objects in the water.  This visual information is relayed immediately for interpretation to emergency services, beach lifeguards, and water users for appropriate decision-making.

“SharkSpotter is an example of how an AI application assists humans as it has significantly higher rates of visual accuracy in shark detection at 90 percent.  At this level of accuracy the drone will certainly help us to improve detection rates, and to maintain safer conditions for water users,” Sharma said.

(Images provided with Ripper Group news release and from file)

FMI: therippergroup.com