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
Understanding biological pathways underlying social behaviour in humans. This project aims to show for the first time how oxytocin interacts with neural social and reward pathways to guide social behaviour. Oxytocin is a natural neuropeptide and hormone that has a critical role in the regulation of social behaviour across mammalian species. In animals, direct evidence demonstrates how endogenous and exogenous oxytocin interacts with social and reward neural pathways to alter social behaviour, in ....Understanding biological pathways underlying social behaviour in humans. This project aims to show for the first time how oxytocin interacts with neural social and reward pathways to guide social behaviour. Oxytocin is a natural neuropeptide and hormone that has a critical role in the regulation of social behaviour across mammalian species. In animals, direct evidence demonstrates how endogenous and exogenous oxytocin interacts with social and reward neural pathways to alter social behaviour, including social recognition, relationship formation, and long-term bonds. The project intends to use radio-labelling techniques in combination with positron emission tomography to track oxytocin and show what regions of the brain oxytocin impacts to then influence social cognition and behaviour in humans.Read moreRead less
High Quality-of-Experience Real-time Video for Smart Online Shopping. This project aims to develop high quality-of-experience real-time video systems for smart shopping applications by devising new deep-neural-network-enhanced video delivery schemes. It will generate new knowledge of combined AI and network solutions to achieve high-quality and low-latency real-time video delivery, addressing unsatisfactory user experience intrinsically caused by network delay and bandwidth. Fundamental principl ....High Quality-of-Experience Real-time Video for Smart Online Shopping. This project aims to develop high quality-of-experience real-time video systems for smart shopping applications by devising new deep-neural-network-enhanced video delivery schemes. It will generate new knowledge of combined AI and network solutions to achieve high-quality and low-latency real-time video delivery, addressing unsatisfactory user experience intrinsically caused by network delay and bandwidth. Fundamental principles and an all-in-one platform will be developed to address research problems and the industrial partner’s practical problems. It will significantly benefit all shopping businesses and their customers in Australia, as well as all other video-related services (e.g., online education, video conferencing, etc.).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
Machine learning techniques for fuel loss detection at service stations. This project aims to develop effective techniques to identify the sources of fuel losses, such as leaks and calibration errors in underground storage tanks at service stations. Monitoring fuel losses at service stations is influenced by many external factors which can be difficult to predict. The project expects to use machine learning to develop the techniques and test them with live data at service stations. The expected ....Machine learning techniques for fuel loss detection at service stations. This project aims to develop effective techniques to identify the sources of fuel losses, such as leaks and calibration errors in underground storage tanks at service stations. Monitoring fuel losses at service stations is influenced by many external factors which can be difficult to predict. The project expects to use machine learning to develop the techniques and test them with live data at service stations. The expected outcomes are a set of tailor-made machine learning techniques for effective fuel loss detection and a software suite that can be easily incorporated into the normal operation of service stations. This should reduce the costs to the petroleum industry from wasteful leaks and the environmental damage caused by these leaks. Read moreRead less
Optimising the spring in your step to enhance footwear design. This project aims to examine how the nervous system adjusts the mechanical function of our feet across a spectrum of speeds, from slow running through to maximal effort sprinting. The proposed research will explore how the nervous system controls the function of the foot to meet the ever-varying demands of locomotion in the real-world. Expected outcomes of this project are to determine if running shoes help or hinder the natural spri ....Optimising the spring in your step to enhance footwear design. This project aims to examine how the nervous system adjusts the mechanical function of our feet across a spectrum of speeds, from slow running through to maximal effort sprinting. The proposed research will explore how the nervous system controls the function of the foot to meet the ever-varying demands of locomotion in the real-world. Expected outcomes of this project are to determine if running shoes help or hinder the natural spring-like function of the foot. It will explain a conceptually novel design allowing shoes to support our feet, whilst harnessing the energetic benefits of the foot's spring-like function. This research has the potential to revolutionise athletic footwear design and has direct implications for enhanced performance in running athletes.Read moreRead less
Multi-service assessment of intertidal treatment wetlands. This project aims to investigate the use of constructed intertidal wetlands to reduce nitrogen pollution while providing co-benefits including carbon sequestration and biodiversity. This research will generate a holistic assessment of the services, disservices, and cost-effectiveness of intertidal treatment wetlands compared to traditional wastewater treatment approaches. Expected outcomes include a full-scale multi-disciplinary environm ....Multi-service assessment of intertidal treatment wetlands. This project aims to investigate the use of constructed intertidal wetlands to reduce nitrogen pollution while providing co-benefits including carbon sequestration and biodiversity. This research will generate a holistic assessment of the services, disservices, and cost-effectiveness of intertidal treatment wetlands compared to traditional wastewater treatment approaches. Expected outcomes include a full-scale multi-disciplinary environmental and economic assessment of a constructed treatment wetland in a new urban development, providing industry and government partners the knowledge required to broaden uptake of intertidal wetlands as a cost-effective solution to growing levels of coastal anthropogenic pollution.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
A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst provid ....A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst providing valuable training/education for the community stakeholders involved in the production of the system. The research outcome will be globally significant, enabling end users to meet key water quality objectives over time, and considerably increase productivity in the Australian agriculture/aquaculture industries.Read moreRead less
Understanding snow gum dieback for effective and integrated management. The project leverages recent research and infrastructure investments and our determined and collaborative team as it aims to: 1) assess the future geography of snow gum dieback in the high country and identify priority locations for pro-active management, 2) quantify the impact of snow gums on high country water and carbon budgets and thus the socio- economic and biodiversity values, and 3) determine options for mitigation. ....Understanding snow gum dieback for effective and integrated management. The project leverages recent research and infrastructure investments and our determined and collaborative team as it aims to: 1) assess the future geography of snow gum dieback in the high country and identify priority locations for pro-active management, 2) quantify the impact of snow gums on high country water and carbon budgets and thus the socio- economic and biodiversity values, and 3) determine options for mitigation. Dieback of our iconic snow gum forests is diminishing the ecological, hydrological and cultural values of the Australian Alps and will impact state and national water-supply and power-generation systems. Our research will inform Alps-wide management efforts designed for long-term success.Read moreRead less