Beyond Speech: Towards better communication for children with hearing loss. Despite the benefits of early newborn hearing screening and early intervention programs for children with hearing loss, most still experience academic and social challenges at school. This is partly due to ongoing listening effort, leading to communicative breakdown. This project aims to identify the locus of the communicative challenges these children face during daily discourse interactions. The outcomes will identify ....Beyond Speech: Towards better communication for children with hearing loss. Despite the benefits of early newborn hearing screening and early intervention programs for children with hearing loss, most still experience academic and social challenges at school. This is partly due to ongoing listening effort, leading to communicative breakdown. This project aims to identify the locus of the communicative challenges these children face during daily discourse interactions. The outcomes will identify which levels of language are most compromised and will inform future interventions to reduce children’s listening effort. This will be undertaken by bringing together researchers in basic science with hearing service providers, parents and industry, providing an innovative model for solving multidisciplinary challenges.Read moreRead less
A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons fo ....A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons for rejection at construction sites, resulting in significant costs, waste, and delays. Multimodal data sources will be used to provide a reliable workability estimate in real time, enabling construction teams to identify and rectify workability issues in transit while continuously monitoring the adjustments effects.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
Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understand ....Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understanding to effectively plan the motion of vehicles and manipulators through larger and more complex workspaces, enabling semi-supervised and autonomous task execution. Our project will demonstrate these capabilities in real-world deployments relevant to industry and marine science.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
The ABC’s of listening and learning: a study in the Northern Territory. Indigenous Australian children experience middle ear disorders earlier in life and for longer periods than their non-Indigenous counterparts. The resulting listening challenges can have implications for academic achievement and future health and well-being, despite normal hearing thresholds. The current project aims to determine the effects of pervasive otitis media and related hearing loss on Indigenous children’s listening ....The ABC’s of listening and learning: a study in the Northern Territory. Indigenous Australian children experience middle ear disorders earlier in life and for longer periods than their non-Indigenous counterparts. The resulting listening challenges can have implications for academic achievement and future health and well-being, despite normal hearing thresholds. The current project aims to determine the effects of pervasive otitis media and related hearing loss on Indigenous children’s listening and pre-literacy skills in the Northern Territory, and how to better identify those at most risk for poor educational outcomes. The findings will lead to policy recommendations to help improve these children’s learning potential.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
Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop ....Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop efficient privacy preserving algorithms to deal with static and dynamic network data sharing. The success of this project will benefit many industries and government agencies to reduce users’ privacy breaches, avoid illegal consequences of sharing data, and enhance these service providers’ service quality.Read moreRead less
Explainable machine learning for electrification of everything. The energy sector is the largest contributor to greenhouse gas emissions. "Electrification of Everything" combined with electricity generation from renewables is a key solution to decarbonise the energy and transport sectors. This project aims to develop an explainable machine learning based data-driven technology to accurately predict the impact of electrification on consumers energy consumption and cost. The expected outcome of th ....Explainable machine learning for electrification of everything. The energy sector is the largest contributor to greenhouse gas emissions. "Electrification of Everything" combined with electricity generation from renewables is a key solution to decarbonise the energy and transport sectors. This project aims to develop an explainable machine learning based data-driven technology to accurately predict the impact of electrification on consumers energy consumption and cost. The expected outcome of this project includes a data-informed decision support technology to help consumers choose the best electrification technologies and solutions. This should provide significant benefits, such as increasing community engagement with electrification, and thus reducing their carbon footprint.Read moreRead less
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