The Department of Defence is tipping $1.7 million into two university research projects to develop a machine learning algorithm for wearable devices and use AI to unscramble data.
The department announced the two contracts with the University of South Australia and Deakin University on Monday. The funding comes from the Next Generation Technologies Fund (NGTF).
University of South Australia researchers will develop a statistical machine learning algorithm that uses data from devices like smart watches to detect early signs of infection in a person.
The Department of Defence is hoping it may eventually help with earlier detection of chemical or biological threats to maximise the effectiveness of interventions.
The Deakin University contract will see it’s applied Artificial Intelligence Institute also using machine learning. Researchers will attempt to develop models that can process noisy and dynamic data that is multi-source, multi-modal, irregularly timed and that spans a prolonged period.
The projects are part of the Defence Artificial Intelligence Research Network (DAIRNet) Phase II call out and will receive a combined $1.746 million.
Both projects will run for two years and aim to deliver prototypes that deliver defence capabilities, Chief Defence Scientist Professor Tanya Monro said.
“Robotics, autonomous systems and artificial intelligence are a group of technologies that are a Defence Sovereign Industrial Capability Priority,” she said.
“The DAIRNet Phase II call out sought innovative proposals for prototypes that will help warfighters achieve superior decision making, and ultimately enhance Defence capability.”
The funding is from the Next Generation Technologies Fund, a large funding program used to support cutting edge work by universities and the defence industry.
The $1.2 billion fund has been criticised, however, for long assessment times and failing to translate the work into capabilities and exports.
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