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
A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst provid ....A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst providing valuable training/education for the community stakeholders involved in the production of the system. The research outcome will be globally significant, enabling end users to meet key water quality objectives over time, and considerably increase productivity in the Australian agriculture/aquaculture industries.Read moreRead less
A Space-Based Quantum Communications Platform using Continuous Variables. This work proposes to investigate a new space-borne platform capable of quantum communications with a terrestrial ground station. Different from existing space-borne quantum communication platforms, our new platform will be based on CV (Continuous Variable) technology and will integrate the ability to seamlessly switch to classical Free-Space Optical communications when channel conditions deem quantum communications are .... A Space-Based Quantum Communications Platform using Continuous Variables. This work proposes to investigate a new space-borne platform capable of quantum communications with a terrestrial ground station. Different from existing space-borne quantum communication platforms, our new platform will be based on CV (Continuous Variable) technology and will integrate the ability to seamlessly switch to classical Free-Space Optical communications when channel conditions deem quantum communications are too difficult. Currently no quantum satellite built on CV technology exists. Our research will produce a significant advance in an emerging technology space, and will allow Australia to take scientific leadership in an important aspect of ultra-secure communications from satellites.
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Modelling interactions of spray droplets with plants. This project addresses the National Research Priority of an environmentally sustainable Australia by developing sophisticated mathematical models and interactive software that will identify environmentally friendlier technologies to efficiently deliver agrichemicals while minimising large scale water usage. National benefits will accrue from the provision for postdoctoral, PhD and IT staff training, while direct links with industry will provi ....Modelling interactions of spray droplets with plants. This project addresses the National Research Priority of an environmentally sustainable Australia by developing sophisticated mathematical models and interactive software that will identify environmentally friendlier technologies to efficiently deliver agrichemicals while minimising large scale water usage. National benefits will accrue from the provision for postdoctoral, PhD and IT staff training, while direct links with industry will provide technology transfer to end-users to ensure community uptake. The project will benefit rural and regional communities by providing long-term solutions in the areas of water use and quality, pesticide pollution reduction, and improved environment and human health care.Read moreRead less
Diffusion and transport of saltwater in coastal aquifers. Saltwater intrusion is a severe environmental problem in coastal regions of Australia, resulting in loss of agricultural land at an alarming rate. This project aims to develop a three-dimensional mathematical model for the simulation and prediction of saltwater intrusion into complex coastal aquifers based on recent advances in the theory of anomalous diffusion, stochastic modelling and numerical methods. The parameters of the model such ....Diffusion and transport of saltwater in coastal aquifers. Saltwater intrusion is a severe environmental problem in coastal regions of Australia, resulting in loss of agricultural land at an alarming rate. This project aims to develop a three-dimensional mathematical model for the simulation and prediction of saltwater intrusion into complex coastal aquifers based on recent advances in the theory of anomalous diffusion, stochastic modelling and numerical methods. The parameters of the model such as hydraulic conductivity and porosity will be estimated using multifractal techniques based on field data at the microscale. Once validated from measurements, the model will be used directly for resource management and planning.Read moreRead less
Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will ....Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will be verified using available bridge datasets of QDMR and GCCC. The methodology is applicable to other bridge authorities throughout Australia and internationally to maintain ageing bridge stock. Read moreRead less
Detecting and Understanding Dysfunctional Anomalies in Queensland Healthcare Databases. Healthcare systems are large complex organizations that are required to function effectively and efficiently. As the main healthcare provider of the state, Queensland Health faces significant challenges in managing the complexity of its operations. This project will use visualization and data mining techniques to support Queensland Health in effective utilisation of its information and communications technolo ....Detecting and Understanding Dysfunctional Anomalies in Queensland Healthcare Databases. Healthcare systems are large complex organizations that are required to function effectively and efficiently. As the main healthcare provider of the state, Queensland Health faces significant challenges in managing the complexity of its operations. This project will use visualization and data mining techniques to support Queensland Health in effective utilisation of its information and communications technology. Through the analysis, detection and prediction of anomalies in the system, the project will contribute to improvements in patient outcomes and efficiency of the Queensland healthcare system.Read moreRead less
Artificial intelligent system for integrated wear debris analysis and vibration analysis in machine condition monitoring. Vibration and wear debris analyses are the two main condition monitoring techniques for machinery maintenance and fault diagnosis. However, they can diagnose less than 50% of faults. A series of experimental and theoretical studies on the correlation of the two techniques will be conducted. This project will integrate advanced technologies including 3D microscopy, neural netw ....Artificial intelligent system for integrated wear debris analysis and vibration analysis in machine condition monitoring. Vibration and wear debris analyses are the two main condition monitoring techniques for machinery maintenance and fault diagnosis. However, they can diagnose less than 50% of faults. A series of experimental and theoretical studies on the correlation of the two techniques will be conducted. This project will integrate advanced technologies including 3D microscopy, neural networks and expert systems to develop an artificial intelligent system based on the dependent and independent roles of the two condition monitoring techniques. Successful outcomes will result in an improved maintenance program and reduction in human involvement, and will provide significant economic benefit to engineering industries.Read moreRead less