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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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