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 data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medi ....A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medicine, which recognises that there are important differences between individuals with a particular disease, and that when patients are separated into sub-populations with similar disease patterns, treatment can be tailored to these sub-populations.Read moreRead less
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
Model Checking Knowledge and Probability in Pursuit-Evasion Games. The research will produce software enabling modellers to better understand their models in applications including planning under uncertainty, information flow security and systems fault diagnosis. The application studied in this project is military search and rescue mission planning, resulting in greater confidence in mission success. The research is also relevant to emergency response and collision avoidance. The project will ....Model Checking Knowledge and Probability in Pursuit-Evasion Games. The research will produce software enabling modellers to better understand their models in applications including planning under uncertainty, information flow security and systems fault diagnosis. The application studied in this project is military search and rescue mission planning, resulting in greater confidence in mission success. The research is also relevant to emergency response and collision avoidance. The project will support retention of Australian intellectual property with potential for future commercialisation. It will foster linkages between Australian researchers and an international defence alliance partner. Outcomes will be available to Australian Defence through existing Defence research sharing arrangements.Read moreRead less
Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techn ....Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techniques using concepts of dynamic sensor scheduling and stochastic control to provide computationally feasible and near optimal solutions to the limited and varying bandwidth problem. This work will greatly enhance the operational performance of distributed sensor networks.Read moreRead less
Enabling small businesses to more cost-effectively use big data on cloud computing platforms. This project will invent a new generic cost model for managing big data in cloud computing. This model will enable agent-based, innovative data management technologies to reduce the cost of storage, computation and bandwidth consumption in the cloud. Outcomes will enable small businesses to use big data in cloud computing more cost effectively.
Accurate Performance Modelling and Prediction of Cluster Computers. The tools, methodologies and data produced by this project will assist
Australian academic and industrial organisations in choosing the most
cost-effective cluster configurations for their specific high
performance computing requirements. It will also help an Australian
company to compete with increasing strength against the major
multinationals. The project will also draw together and promote future
research links between ....Accurate Performance Modelling and Prediction of Cluster Computers. The tools, methodologies and data produced by this project will assist
Australian academic and industrial organisations in choosing the most
cost-effective cluster configurations for their specific high
performance computing requirements. It will also help an Australian
company to compete with increasing strength against the major
multinationals. The project will also draw together and promote future
research links between two major academic institutions in this field.
Finally, the project will provide high-level training in research,
with industrial grounding, in the high performance computing industry.
Read moreRead less
Sentiment detection from opinion surveys -- the quest for customer and employee satisfaction. The research will yield improved international standing through scientific advances disseminated through high impact refereed publications and open source software. The advances made through the application of sophisticated probabilistic techniques to Language Technology problems will attract post-graduate students, and promote commercial interest. The demonstration prototype will provide proof of conce ....Sentiment detection from opinion surveys -- the quest for customer and employee satisfaction. The research will yield improved international standing through scientific advances disseminated through high impact refereed publications and open source software. The advances made through the application of sophisticated probabilistic techniques to Language Technology problems will attract post-graduate students, and promote commercial interest. The demonstration prototype will provide proof of concept of an application that enables business intelligence to automatically process free-form feedback from customers and employees, with resultant recommendations leading to increased customer and employee satisfaction. The applicability of the outcomes of this research to service industries will further improve Australia's service reputation.Read moreRead less
Web Services Reputation Management. This project directly supports the National Research Priority 4: Safeguarding Australia. More specifically, it aims at creating mechanisms that will make it more difficult to use the Internet as a platform for launching attacks against the business processes of Australian organisations that provide and consume Web services. At the same time this will stimulate the establishment of high quality WS markets. As direct social benefit of this research, Australian o ....Web Services Reputation Management. This project directly supports the National Research Priority 4: Safeguarding Australia. More specifically, it aims at creating mechanisms that will make it more difficult to use the Internet as a platform for launching attacks against the business processes of Australian organisations that provide and consume Web services. At the same time this will stimulate the establishment of high quality WS markets. As direct social benefit of this research, Australian organisations will be able to integrate the best quality Web services as part of their business processes, and thereby avoid being negatively impacted by low quality and deceptive Web services. Read moreRead less
Making the Pilbara blend: agile mine scheduling through contingent planning. Mine scheduling is a challenging problem for Rio Tinto which annually mines more than 200 Million tonnes of iron ore. This project will develop agile scheduling techniques of great economic importance to Australia. Carefully planned scheduling reduces infrastructure and minimises environmental impacts, maximising regeneration after mining.