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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Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive mu ....Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive multi-component trust framework reflecting trust perspectives. The developed solutions will allow the establishment of trusted interactions among crowdsourced IoT devices and wider deployment of convenient and just-in-time services, thus enabling the development of novel applications, such as the crowdsourcing of green energy.Read moreRead less
Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, ....Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services.Read moreRead less
SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the infor ....SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the information and contracts needed by IoT applications to discover, integrate, pay, and use sensors provided by another parties. These IoT advancements will provide significant economic, environmental, and social benefits via making low-cost and immediate sensing available across the world.Read moreRead less
Flying networks: airborne sensing for environmental monitoring and disaster response. Airborne sensing technology is ideally suited to Australian geography and can be highly effective for monitoring disasters, surveillance, and precision agriculture. There are ample opportunities for local information technology companies and start-ups to create innovative airborne sensing applications for both the Australian and overseas markets.
Non-intrusive human activity sensing with radio signals. This project aims to develop a theoretical framework for sensing and detecting human activities based on wireless radio signals. The framework advances the state-of-the-art by discovering the fundamental theory, and defining a set of principles to guide practical system design. The framework will be validated and its scientific merit demonstrated through building several applications such as contactless human activity detection and vital s ....Non-intrusive human activity sensing with radio signals. This project aims to develop a theoretical framework for sensing and detecting human activities based on wireless radio signals. The framework advances the state-of-the-art by discovering the fundamental theory, and defining a set of principles to guide practical system design. The framework will be validated and its scientific merit demonstrated through building several applications such as contactless human activity detection and vital signs monitoring. This should benefit existing hospital and clinical patient services and promote home-care and self-care services at nationwide.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100479
Funder
Australian Research Council
Funding Amount
$427,116.00
Summary
A Unified Framework to Rapidly Fabricate Individualised Activity Sensors. This proposal aims to develop a unified computational framework which enables non-expert users to co-design and fabricate specialised physical activity sensors to address individualised sensing problems in applications such as rehabilitation, age-care and sports. Specifically, we will develop an analytical framework to classify complex sensing problems into fabricable primitive classes, namely i) conditional – limits of ac ....A Unified Framework to Rapidly Fabricate Individualised Activity Sensors. This proposal aims to develop a unified computational framework which enables non-expert users to co-design and fabricate specialised physical activity sensors to address individualised sensing problems in applications such as rehabilitation, age-care and sports. Specifically, we will develop an analytical framework to classify complex sensing problems into fabricable primitive classes, namely i) conditional – limits of activity, ii) differential – frequency of activity and iii) integrational – cumulative activity. And a co-design interface to synthesize them into complex activity sensors to fit individualised needs. Finally, we will evaluate the framework by deploying the created sensors in real-world settings and gathering data.Read moreRead less
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