Scalable Robust Video Surveillance over Constrained Networks. Real-time monitoring of large numbers of people is becoming increasingly important for applications such as efficient service delivery and security against both common crime and terrorism. The use of human operators for such tasks is infeasible due to the large amount of data collected. Existing autonomous video surveillance systems are prone to high numbers of false alarms and often require expensive hardware. This proposal seeks ....Scalable Robust Video Surveillance over Constrained Networks. Real-time monitoring of large numbers of people is becoming increasingly important for applications such as efficient service delivery and security against both common crime and terrorism. The use of human operators for such tasks is infeasible due to the large amount of data collected. Existing autonomous video surveillance systems are prone to high numbers of false alarms and often require expensive hardware. This proposal seeks to address both difficulties by using rigorous statistical signal processing methods to optimally fuse information from a network of low-cost cameras.Read moreRead less
Data Fusion Techniques for Electro-Mechanical Braking Systems. The main focus of this project is to develop data fusion techniques for clamp force estimation and optimum utilisation of redundant information in a brake-by-wire system. Efficient integration of redundant information in an EMB system is expected to significantly improve the reliability and fault tolerance of such systems. The need for costly and complicated clamp force measurement sensors in electric callipers will also be eliminate ....Data Fusion Techniques for Electro-Mechanical Braking Systems. The main focus of this project is to develop data fusion techniques for clamp force estimation and optimum utilisation of redundant information in a brake-by-wire system. Efficient integration of redundant information in an EMB system is expected to significantly improve the reliability and fault tolerance of such systems. The need for costly and complicated clamp force measurement sensors in electric callipers will also be eliminated by accurate estimation of the clamp force signal, through fusion of more readily available measurements. Development of the proposed data fusion techniques influences the design of future EMBs and enhances the functionality of existing brake-by-wire systems.Read moreRead less
Compositional determination of liquefied petroleum gas: Improving engine cold start performance in multipoint LPG-injected engines. Unlike gasoline, the composition of liquefied petroleum gas (LPG) is subject to change depending on a variety of factors including reservoir location and local market pricing. During normal automotive multipoint injection engine operation, closed loop feedback from engine sensors allows the effects of the compositional variations to be overcome and the engine to ope ....Compositional determination of liquefied petroleum gas: Improving engine cold start performance in multipoint LPG-injected engines. Unlike gasoline, the composition of liquefied petroleum gas (LPG) is subject to change depending on a variety of factors including reservoir location and local market pricing. During normal automotive multipoint injection engine operation, closed loop feedback from engine sensors allows the effects of the compositional variations to be overcome and the engine to operate close to optimal levels. However during cold start, the feedback sensors are not operational, and engine performance may deteriorate due to unknown fuel composition - in the worst case the engine may not start at all. This project aims to develop unique methods of estimating the composition of LPG based on existing sensor information to improve performance during cold start.Read moreRead less
Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techn ....Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techniques using concepts of dynamic sensor scheduling and stochastic control to provide computationally feasible and near optimal solutions to the limited and varying bandwidth problem. This work will greatly enhance the operational performance of distributed sensor networks.Read moreRead less
Developing a Smart Monitoring System for Leakage Currents from Insulators on Wooden Poles. Numerous wooden poles are used for electricity power transmission in urban and rural areas of Australia. Insulators suspended on poles are subject to contamination and moisture that cause partial discharge currents to flow through the wooden poles, resulting in pole fires leading to loss of power to customers and possible bush fires. This project aims at studying the characteristics of leakage currents fr ....Developing a Smart Monitoring System for Leakage Currents from Insulators on Wooden Poles. Numerous wooden poles are used for electricity power transmission in urban and rural areas of Australia. Insulators suspended on poles are subject to contamination and moisture that cause partial discharge currents to flow through the wooden poles, resulting in pole fires leading to loss of power to customers and possible bush fires. This project aims at studying the characteristics of leakage currents from insulators on wooden poles in Australian conditions and developing a smart monitoring system to detect and prevent pole fires caused by leakage currents. The outcomes will reduce the risk of pole fires, hence improving public safety, reliability of power supply and sustainability of the Australian power industry.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Towards Distributed Phased Array Radar for High Resolution Weather Monitoring. Several recent reports on climate change by leading international and national bodies forecast that the rate of weather hazards such as storms and wind-shear, and of weather-associated phenomena such as bush fires will increase over the next 40 years. The current technology for monitoring weather events, and effects like wind-shift, which has a serious impact on dangers associated with bush fires, has significant wea ....Towards Distributed Phased Array Radar for High Resolution Weather Monitoring. Several recent reports on climate change by leading international and national bodies forecast that the rate of weather hazards such as storms and wind-shear, and of weather-associated phenomena such as bush fires will increase over the next 40 years. The current technology for monitoring weather events, and effects like wind-shift, which has a serious impact on dangers associated with bush fires, has significant weaknesses. We will deliver considerable improvements in monitoring capability by developing the technology for using a network of small phased array radars. We aim to place monitoring resources where end-user needs are greatest.Read moreRead less
Development of an Intelligent Perception System for Electric Brakes. Electric braking is a vital component of the drive by-wire systems whose development is currently being supported worldwide by many automobile manufacturers. The aim of this project is to contribute to the development of an efficient fully functional electrically operated braking system. The main focus is on development of the intelligent perceptual sensors required for optimum performance of a by-wire braking system (to be com ....Development of an Intelligent Perception System for Electric Brakes. Electric braking is a vital component of the drive by-wire systems whose development is currently being supported worldwide by many automobile manufacturers. The aim of this project is to contribute to the development of an efficient fully functional electrically operated braking system. The main focus is on development of the intelligent perceptual sensors required for optimum performance of a by-wire braking system (to be commercialised by 2007). This project will also facilitate the development of professional courses for by-wire technology. Such courses will play a crucial role in maintaining the competitiveness of the Australian car component industry as by-wire technology emerges.Read moreRead less
Advanced Signal Processing for Radiation Spectroscopy. Southern Innovation develops and markets world-leading pulse processing technologies for the rapid, accurate detection and measurement of radiation. The underlying real-time signal processing challenge relates to isolating often overlapping pulses, determining when each pulse arrived and the energy of each pulse. Recent advances in the computational power of digital signal processing boards makes it timely to develop innovative pulse process ....Advanced Signal Processing for Radiation Spectroscopy. Southern Innovation develops and markets world-leading pulse processing technologies for the rapid, accurate detection and measurement of radiation. The underlying real-time signal processing challenge relates to isolating often overlapping pulses, determining when each pulse arrived and the energy of each pulse. Recent advances in the computational power of digital signal processing boards makes it timely to develop innovative pulse processing algorithms based on optimal filtering of stochastic processes. It is expected that these algorithms will have widespread impact, both commercially for minerals exploration, materials analysis, medical imaging and security screening, and scientifically for improving the performance of synchrotrons and other equipment.Read moreRead less