Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelli ....Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelligence to infer and predict dangerous driver and passenger behaviour. This has the potential to significantly benefit society by advancing autonomous driving capabilities and reducing driver-induced accidents and fatalities, ensuring that every driver, passenger and pedestrian arrives home safely at the end of each day.Read moreRead less
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
Automated Integrity Assessment of Self-Piercing Rivet Joints: i4.0 Approach. Lightweighting in the car industry by the use of aluminium reduces emissions substantially. It entails joining the car body sections by self-piercing rivets rather than the traditional spot welds. We aim to fill the technology gap for effective quality control of these joints. The project expects to solve the problem by merging industry 4.0 principles, three-dimensional X-ray technology, machine learning computer vision ....Automated Integrity Assessment of Self-Piercing Rivet Joints: i4.0 Approach. Lightweighting in the car industry by the use of aluminium reduces emissions substantially. It entails joining the car body sections by self-piercing rivets rather than the traditional spot welds. We aim to fill the technology gap for effective quality control of these joints. The project expects to solve the problem by merging industry 4.0 principles, three-dimensional X-ray technology, machine learning computer vision and structural mechanics. The expected outcomes are technologies for automation-friendly assessment of these joints. This should benefit industries from medical to electronics to automatically spot a random and delicate abnormality within a solid of complex geometry, such as that in live tissue or an electronic circuit.Read moreRead less
Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation syste ....Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation systems and novel approaches to continuous collaborative learning from multi-spectral media. In addition to the emerging partnership between participants, the project will advance sovereign capability to develop maritime intelligence gathering technology for the Royal Australian Navy to underpin stability in our region. Read moreRead less
Precision Pollination: Data-driven enhancements to boost crop yield. The project aims to transform industrial crop pollination from an intuitive domain to one where decisions are based on sound data and best-practice principles. It proposes to achieve this modernisation of global pollination practice by developing novel technologies to operate a three-stage loop: honeybee pollination monitoring, simulation-based forecasting, and management. This is intended to ensure that the capability of honey ....Precision Pollination: Data-driven enhancements to boost crop yield. The project aims to transform industrial crop pollination from an intuitive domain to one where decisions are based on sound data and best-practice principles. It proposes to achieve this modernisation of global pollination practice by developing novel technologies to operate a three-stage loop: honeybee pollination monitoring, simulation-based forecasting, and management. This is intended to ensure that the capability of honeybees to provide essential ecosystem services is informed by transferable, standardised data acquisition and management techniques that maintain bee health and maximise pollination. The anticipated outcomes are higher fruit yields and quality, and a beneficial step-change in industry productivity and profitability.Read moreRead less