About the Shark AI Project
Drone-based shark surveillance is emerging as an effective, safe and affordable approach to managing human-shark conflict. However, the method is currently labour intensive and relies heavily on pilot skill to detect and identify marine life. This project seeks to improve the reliability of shark-spotting drones by using by using artificial intelligence to confidently identify shark species in live video.
Shark attacks are of increasing public concern in many areas around the globe, with attacks generating media headlines worldwide. In Australia, the issue is severely impacting coastal tourism (worth over 5-billion AUD) and associated communities. To make beaches safer, Governments resort to controversial management methods, such as nets and baited drumlines, that kill sharks and other highly valued marine life. Non-destructive approaches, such as spotting sharks from helicopters, are also used but they are costly, provide low-frequency coverage, and suffer from many false-positive identifications, resulting in unnecessary beach closures that contribute to a climate of fear.
Machine learning techniques have revolutionised computer vision in the last 5 years. Given enough training data, artificial neural networks (ANNs) can learn the distinguishing features of different objects and accurately recognise them in images. Our tests have shown that ANNs can reliably detect sharks in video footage from shark-spotting drones. In good conditions modern networks can even distinguish between similar looking species - for example harmless guitarfish and dangerous bull sharks. Reliable species-level identification means fewer unnecessary beach closures, fewer marine animals killed and safer beaches in general.
The Project Team
The project is led by Dr Cormac Purcell, Dr Andrew Walsh and Dr Andrew Colefax (Sci-eye) in close collaboration with Dr Paul Butcher at the NSW Department of Primary Industries.
Dr Purcell has 18 years experience analysing data from arrays of radio telescopes. Now he is applying his skills to develop machine-learning and image-processing algorithms to analyse the drone footage for this project.
Dr Walsh is a python developer with an astrophysics
background and experience in machine learning,
management, mentoring and public speaking. He is
currently analysing Earth observation data at Geoscience
Australia and is leading the data-processing effort for
the Shark AI project.
Dr Colefax is a leading expert in using drones to
monitor shark behaviour. He recently completed a PhD focusing
on the behaviour of great white sharks and the use of
drones for shark surveillance, and improving their
Dr Paul Butcher is a senior research scientist with the Fisheries Conservation Technology Unit of the DPI. Since 2016, he is has been running trials of drone technology to better detect and deter sharks off the NSW coast.