An automated system for the analysis of road safety and conditions. This project aims to develop an automated system for the analysis of road safety and conditions. Digital video road data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project will develop deep learning based neural network techniques which can learn and classify roadside objects so that video data can be automatically analysed all ....An automated system for the analysis of road safety and conditions. This project aims to develop an automated system for the analysis of road safety and conditions. Digital video road data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project will develop deep learning based neural network techniques which can learn and classify roadside objects so that video data can be automatically analysed allowing the estimation of the proximity of objects for road safety and rating. The expected outcome will be new identification techniques and software which can be incorporated with road data collection systems.Read moreRead less
Application of artificial neural network in flood emergency decision support system. This project will develop a method for rapid estimation of flood water levels. This will increase the warning time for flood evacuation in small coastal catchments where traditional estimating techniques are too time-consuming.
Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside obje ....Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside objects so that the data can be automatically analysed allowing the estimation of fire risk factors. The final outcome intends to be techniques for segmentation and classification of roadside objects and estimation of fire risk factors.Read moreRead less
Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin ....Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.Read moreRead less
An integrated and real-time passenger travel and public transport service information system. This project will help the Department of Transport provide improved services to the public through a better understanding of journey planning demands in comparison to public transport services. By integrating research through design methods with technological solutions, the project will deliver better quality of service and higher customer satisfaction.
Discovering Patterns using Near Unsupervised Leaning to Support the Quick Detection of New Animal Disease Outbreaks Caused by Viruses. Without the capability to identify and study the vast majority of extant viruses using traditional laboratory techniques, emerging threats to Australian livestock health cannot be efficiently diagnosed or treated. New approaches based on high-throughput sequencing have recently been developed to study such viruses, but making sense of the sequence data is still a ....Discovering Patterns using Near Unsupervised Leaning to Support the Quick Detection of New Animal Disease Outbreaks Caused by Viruses. Without the capability to identify and study the vast majority of extant viruses using traditional laboratory techniques, emerging threats to Australian livestock health cannot be efficiently diagnosed or treated. New approaches based on high-throughput sequencing have recently been developed to study such viruses, but making sense of the sequence data is still a complex problem. Together with the project's Partner Organisations, including YourGene Biosciences Australia and the CSIRO Australian Animal Health Laboratory, this project aims to develop new computational methods to broaden the scope of detection and analysis of unknown viruses, enhancing the capability for research into the causative viral agents of animal diseases.Read moreRead less
Data mining complex transactional and criminal networks. Money laundering, if undetected, poses a major concern for governments and communities. The software system platform for detecting money laundering networks from this project will be the first that can assist intelligence data analysts to detect unknown money laundering networks faster and more accurately, helping fight crimes more efficiently.
Intelligent real time multi-site controller for conserving energy in remote areas and in the resource industry. This project researches the issues in achieving demand response for electricity usage in remote regions of Australia through the use of smart meters and web of things framework to provide ubiquitous monitoring and control of devices, intelligent control systems to dynamically change energy usage patterns and community-based social network architecture. This will lead to several benefit ....Intelligent real time multi-site controller for conserving energy in remote areas and in the resource industry. This project researches the issues in achieving demand response for electricity usage in remote regions of Australia through the use of smart meters and web of things framework to provide ubiquitous monitoring and control of devices, intelligent control systems to dynamically change energy usage patterns and community-based social network architecture. This will lead to several benefits, such as (a) the strengthening of Australian business competitiveness in these regions by reducing energy costs and increasing energy trading, (b) reduction in ecological impact through smarter utilisation of energy and shifting to renewable sources, (c) encourage local generation and distribution of electricity where communities can trade excess energy.Read moreRead less
Mathematics and computing for integrated stockyard-centric management of mining supply chains. Blended mineral products, such as coal and iron ore, make a strong contribution to Australia's economy. Blending occurs in stockpiles, so to realise product value, stockyard and supply chain operational plans must align with blend targets. This project will provide new mathematical and computational planning tools to maximise this value.
Developing best-practice approaches for restoring forest ecosystems that are resilient to climate change. Existing restoration practices for forests tend to rely on ad hoc rules of thumb that lack a firm scientific basis and risk failure due to climate change. The project will model biodiversity, genetic and growth performance data to develop best-practice restoration guidelines for forest ecosystems to enable them to become resilient to climate change and maximise biodiversity and carbon captur ....Developing best-practice approaches for restoring forest ecosystems that are resilient to climate change. Existing restoration practices for forests tend to rely on ad hoc rules of thumb that lack a firm scientific basis and risk failure due to climate change. The project will model biodiversity, genetic and growth performance data to develop best-practice restoration guidelines for forest ecosystems to enable them to become resilient to climate change and maximise biodiversity and carbon capture outcomes.Read moreRead less