Engaging Augmented Reality on 3D Head Up Displays to Reduce Risky Driving. This project aims to reduce risky driving behaviours through novel augmented reality applications for three-dimensional head-up displays, making safe driving more engaging so that drivers will take less risk. Over 1 million people are killed and 50 million are seriously injured on roads each year worldwide. Risky driving behaviours (speeding and distracted driving) are major causes. This project intends to produce novel i ....Engaging Augmented Reality on 3D Head Up Displays to Reduce Risky Driving. This project aims to reduce risky driving behaviours through novel augmented reality applications for three-dimensional head-up displays, making safe driving more engaging so that drivers will take less risk. Over 1 million people are killed and 50 million are seriously injured on roads each year worldwide. Risky driving behaviours (speeding and distracted driving) are major causes. This project intends to produce novel in-car interaction design implementations, provide important visual design guidelines for future display technologies, and provide novel road safety interventions.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101542
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Risky Gadgets to the Rescue: Designing Personal Ubicomp Devices to Foster Safer Driving Behaviours in Young Males. Young males are over-represented in road crashes. Part of the problem is their proneness to boredom, a hardwired personality factor that can lead to risky driving or distractions. This project aims to design innovative ubiquitous computing technologies that make safe driving more stimulating and pleasurable. This research will inform the future design of personal ubiquitous devices ....Risky Gadgets to the Rescue: Designing Personal Ubicomp Devices to Foster Safer Driving Behaviours in Young Males. Young males are over-represented in road crashes. Part of the problem is their proneness to boredom, a hardwired personality factor that can lead to risky driving or distractions. This project aims to design innovative ubiquitous computing technologies that make safe driving more stimulating and pleasurable. This research will inform the future design of personal ubiquitous devices that pose a threat to road safety, by replacing the stimuli from risky driving with safer stimuli and simulating risk to increase risk perception when it is actually not present. This project aims to reduce risky driving behaviours, and, in the process, advance our knowledge about the role of boredom in the road safety context.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190101151
Funder
Australian Research Council
Funding Amount
$398,000.00
Summary
Designing augmented eating interfaces to promote mindful eating. This project aims to develop and test novel augmented eating interfaces in order to address the contradiction between the concept of mindful eating (no distractions) and the reality of screen cultures (eating with screens). Eating while watching screens can be problematic because it can cause overeating, which can manifest into bigger health concerns such as obesity and heart disease. This project expects to generate new knowledge ....Designing augmented eating interfaces to promote mindful eating. This project aims to develop and test novel augmented eating interfaces in order to address the contradiction between the concept of mindful eating (no distractions) and the reality of screen cultures (eating with screens). Eating while watching screens can be problematic because it can cause overeating, which can manifest into bigger health concerns such as obesity and heart disease. This project expects to generate new knowledge in the field of human-food interaction. It presents two new augmented eating systems and a socio-technological study of these systems in use within Australian households. The expected outcomes include a framework on how to design interactive systems that encourage mindful eating without compromising the pleasures of screen-based media and the eating experience, and a greater theoretical understanding of how to support mindful eating in everyday practice.Read moreRead less
Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a sys ....Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a system that is highly efficient, accurate and corrupted-data-tolerant classification solutions for individual stream data as well as multiple stream data. The expected benefits will be far-ranging and adaptable to many domains, such as smart home, medical and healthcare, transportation and manufacturing. Read moreRead less
Coach My Ride: Mentorable Interfaces to support Older Australians' Mobility. This project aims to co-design new interfaces to support older Australians to collaboratively learn the use of automated vehicles. We will seek to understand the needs, expectations, and challenges of urban and rural residents, and the peer support strategies they deploy to learn technology. Mobility is key to the wellbeing of older people, but automated vehicles that are too complex will fail to deliver their promise o ....Coach My Ride: Mentorable Interfaces to support Older Australians' Mobility. This project aims to co-design new interfaces to support older Australians to collaboratively learn the use of automated vehicles. We will seek to understand the needs, expectations, and challenges of urban and rural residents, and the peer support strategies they deploy to learn technology. Mobility is key to the wellbeing of older people, but automated vehicles that are too complex will fail to deliver their promise of independent ageing. Outcomes will be a new theory of collaborative learning and new mentorable interfaces to allow older adults to mentor each other to access and use new mobility solutions. This will contribute to narrow the digital and mobility gap improving the independence, safety and wellbeing of ageing Australians.Read moreRead less
Participatory Visualisation & Assessment of Risks: A Crowdsourcing Approach. The aim of this study is to develop and evaluate innovative interaction and visualisation approaches that allow the insurance sector to include social media and crowdsourced data in risk identification and assessment. This data, combined with traditional risk assessment information, offers time-critical insights into emerging hazards and threats. The study aims to deliver methods and tools to crowdsource data from contr ....Participatory Visualisation & Assessment of Risks: A Crowdsourcing Approach. The aim of this study is to develop and evaluate innovative interaction and visualisation approaches that allow the insurance sector to include social media and crowdsourced data in risk identification and assessment. This data, combined with traditional risk assessment information, offers time-critical insights into emerging hazards and threats. The study aims to deliver methods and tools to crowdsource data from contributors through sensing and active sharing, as well as novel interaction and visualisation approaches to aid in the analysis of the resulting data. The project intends to benefit both the insurers and the insured by making non-traditional data sources available for risk assessment and prevention.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100679
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and effic ....Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and efficiently support a set of primitive queries including rank-based queries, dominance-based queries and proximity-based queries. The results of this project will be an important complement to the development of data stream systems and will bring considerable social, economic and technological benefits to Australia.Read moreRead less
Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database i ....Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database indexing, event-influenced behaviour modelling and prediction. The success of this project is expected to enhance users’ online experience and improve e-commerce’s market value.Read moreRead less
Taming the uncertainty in trajectory data. This project aims to develop effective and efficient methods to manage large scale uncertain trajectory data. It provides individuals, business, government and social groups the ability to explore significant uncertain trajectories and their patterns, for important usages in location based services, logistic, transportation and tourism.
Deep attribute-aware hashing for cross retrieval. This project aims to enable individuals, industries and governments, to freely access vital and linked information carried in different media types from different sources by developing a deep attribute-aware framework that embeds heterogeneous features into a shared data space to achieve effective and efficient cross system information retrieval. With the proliferation of heterogeneous data sources, there is an urgent need to enable search and re ....Deep attribute-aware hashing for cross retrieval. This project aims to enable individuals, industries and governments, to freely access vital and linked information carried in different media types from different sources by developing a deep attribute-aware framework that embeds heterogeneous features into a shared data space to achieve effective and efficient cross system information retrieval. With the proliferation of heterogeneous data sources, there is an urgent need to enable search and retrieval across different media types and domains. The framework developed by the project uses deep learning methods to develop meaningful image attributes to positively bridge the modality gap and the domain gap when hash functions are affixed to data. This project will significantly advance the research of multimedia retrieval, and benefit a series of related research problems whenever heterogeneous multimedia data are involved in their applications.Read moreRead less