A mmWave Sensor Network for Hand Gesture Monitoring. This project aims to realise a world-first mmWave radar-based sensor network for device-free ubiquitous hand gesture monitoring. By harnessing recent radar technology breakthrough in mmWave, hand gesture may be monitored in a non-privacy intrusive manner. Pilot studies show different handrub gestures can be sensed and recognised by analysing the radio signal variations in the receiver. Given the many social, economic and health advantages of ....A mmWave Sensor Network for Hand Gesture Monitoring. This project aims to realise a world-first mmWave radar-based sensor network for device-free ubiquitous hand gesture monitoring. By harnessing recent radar technology breakthrough in mmWave, hand gesture may be monitored in a non-privacy intrusive manner. Pilot studies show different handrub gestures can be sensed and recognised by analysing the radio signal variations in the receiver. Given the many social, economic and health advantages of low-cost and non-privacy intrusive hand gesture sensing --- including enabling interactions and communications with smart environments (e.g., homes and offices) in a natural way --- the proposed research promises multiple benefits while positioning Australia as smart buildings innovator.Read moreRead less
Energy-Efficient Human-Sensing with Photovoltaic Internet-of-Things. This project aims to realise a world-first photovoltaic (PV)-based system for device free ubiquitous human monitoring. By harnessing next generation flexible organic PV cells, Internet-of-Things (IoT) devices may be powered using only indoor lighting. Pilot studies show different activities can, in turn, be sensed and recognised by analysing the variations in the energy harvesting patterns in the PV-powered IoT. Given the many ....Energy-Efficient Human-Sensing with Photovoltaic Internet-of-Things. This project aims to realise a world-first photovoltaic (PV)-based system for device free ubiquitous human monitoring. By harnessing next generation flexible organic PV cells, Internet-of-Things (IoT) devices may be powered using only indoor lighting. Pilot studies show different activities can, in turn, be sensed and recognised by analysing the variations in the energy harvesting patterns in the PV-powered IoT. Given the many social, economic and environmental advantages of cost and energy-efficient sensing – including falls detection for the elderly and power savings in smart building – the proposed research promises multiple benefits while positioning Australia as an IoT innovator.
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Decimetre-level indoor positioning on Wi-Fi. This project aims to exploit both spatial and frequency diversities based on the multiple-input, multiple-out and frequency hopping techniques to achieve the goal of decimetre-level position accuracy by significantly increasing Wi-Fi bandwidth. Wi-Fi positioning is utilised in locations where GPS is blocked, typically this is within a structure. The project will design a set of mechanisms to facilitate Wi-Fi positioning, discover key principles to gui ....Decimetre-level indoor positioning on Wi-Fi. This project aims to exploit both spatial and frequency diversities based on the multiple-input, multiple-out and frequency hopping techniques to achieve the goal of decimetre-level position accuracy by significantly increasing Wi-Fi bandwidth. Wi-Fi positioning is utilised in locations where GPS is blocked, typically this is within a structure. The project will design a set of mechanisms to facilitate Wi-Fi positioning, discover key principles to guide practical design, and develop advanced algorithms to push the performance limit to decimetre-level accuracy. The project will develop key fundamental technologies which are expected to promote innovative, practical, and cost-effective applications to local industry and service sectors and contribute to Australia's long-term economic growth.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101439
Funder
Australian Research Council
Funding Amount
$418,998.00
Summary
Towards a Reliable and Explainable Health Monitoring and Caring System. This project aims to unleash the power of deep learning on health monitoring and caring domain through a safe, reliable and explainable way. Its innovations lie on 1) developing a set of robust and explainable deep learning models that are guaranteed to be safe to complex environmental uncertainty; 2) designing an intelligent health monitoring and caring platform, powered by robust deep learning models, to better support the ....Towards a Reliable and Explainable Health Monitoring and Caring System. This project aims to unleash the power of deep learning on health monitoring and caring domain through a safe, reliable and explainable way. Its innovations lie on 1) developing a set of robust and explainable deep learning models that are guaranteed to be safe to complex environmental uncertainty; 2) designing an intelligent health monitoring and caring platform, powered by robust deep learning models, to better support the home-based health monitoring and caring for the elderly. The result will enable end-users to trust the decisions of deep learning models in safety-critical systems and significantly contribute to Australian aging society and national healthcare economy.Read moreRead less
A personalised social network based location search and recommender system. Inspired by the advance and popularity of social networks, this project will investigate new personalised recommendation techniques in social networks. Mobile services will be developed for users to search and obtain recommendations as they wish based on their social relationships and behaviour in the social group.