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
Control and communications for high value distributed electrical storage. The project aims to develop a new framework to support the successful deployment of resilient ‘prosumer-based’ energy systems. The increasing deployment of new energy technologies, such as solar photovoltaics, wind turbines, and battery and other energy storages, challenges the current operating regimes of energy systems. The successful and active participation of prosumers, who are both producers and consumers of energy, ....Control and communications for high value distributed electrical storage. The project aims to develop a new framework to support the successful deployment of resilient ‘prosumer-based’ energy systems. The increasing deployment of new energy technologies, such as solar photovoltaics, wind turbines, and battery and other energy storages, challenges the current operating regimes of energy systems. The successful and active participation of prosumers, who are both producers and consumers of energy, becomes a critical issue in the operation and management of such systems. The proposed framework explores ways to integrate new technology into existing systems, focusing on new methods of energy management with interactions with millions of devices and storage units, and real-time communications to devices.Read moreRead less
Cloud scheduling and management of energy systems with real-time support. This project aims to research cloud scheduling and management of modern energy systems with real-time communication support. The approach consists of optimisation with balanced benefits for customers, aggregators and network service providers for modern energy systems; real-time communication support for unified energy scheduling and management over many microgrids; and cloud energy scheduling and management with deadline ....Cloud scheduling and management of energy systems with real-time support. This project aims to research cloud scheduling and management of modern energy systems with real-time communication support. The approach consists of optimisation with balanced benefits for customers, aggregators and network service providers for modern energy systems; real-time communication support for unified energy scheduling and management over many microgrids; and cloud energy scheduling and management with deadline guarantee. This project is expected to facilitate increasing deployment of disruptive energy technologies on a massive scale, create opportunities for energy industries, and maintain Australia’s leading position in renewable energy.Read moreRead less
A Theory of Innovation Systems. The goal of the project is to develop and validate a new theory for how information systems can be designed to assist organisations in becoming innovative. Technological innovation is designed to increase productivity and economic growth, but knowledge is lacking about how information systems can meaningfully support organisations in becoming innovative. The goal of this project is to develop and test a theory of ‘innovation systems’ that would describe design pri ....A Theory of Innovation Systems. The goal of the project is to develop and validate a new theory for how information systems can be designed to assist organisations in becoming innovative. Technological innovation is designed to increase productivity and economic growth, but knowledge is lacking about how information systems can meaningfully support organisations in becoming innovative. The goal of this project is to develop and test a theory of ‘innovation systems’ that would describe design principles for information systems that provide effective and efficient support to organisational innovation processes. The expected project outcomes would assist the development of new systems to support organisational innovations, the management of innovation initiatives to increase productivity and growth, and the effective assessment of technologies to support innovation.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100160
Funder
Australian Research Council
Funding Amount
$423,000.00
Summary
Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expe ....Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expected outcomes include a set of collective, contextualised, and temporal-aware algorithms for information extraction and integration, built on top of effective indexing and in-parallel processing. This project is anticipated to benefit a considerable number of data-driven intelligence-based applications.Read moreRead less
Embedding Enterprise Systems in IoT Fog Networks through Microservices. The project will enable automated re-engineering of enterprise systems, to allow them to reused in Internet-of-Things (IoT) applications. It will support efficient ways in which the core business logic of these large scale and monolithic systems can be extended into resource control and data sensing functions managed through the IoT. The project will develop a novel, fine-grained software architecture style suitable for loca ....Embedding Enterprise Systems in IoT Fog Networks through Microservices. The project will enable automated re-engineering of enterprise systems, to allow them to reused in Internet-of-Things (IoT) applications. It will support efficient ways in which the core business logic of these large scale and monolithic systems can be extended into resource control and data sensing functions managed through the IoT. The project will develop a novel, fine-grained software architecture style suitable for localised IoT execution, through microservices executing autonomously on nodes of IoT fog networks. It will develop new techniques for automated discovery of microservices from enterprise systems and the verification of future-state system execution based on current-state behavioural and other properties such as security.Read moreRead less
A Novel Framework for Optimised Ensemble Classifier. The project aims to develop a novel framework for creating an optimised ensemble classifier that will improve data analysis and the accuracy of many real-world applications such as document analysis, robotics and medical diagnosis. The project plans to develop and investigate novel methods for generating diverse training environment layers, base classifiers and fusion of classifiers. It also plans to design a multi-objective evolutionary algor ....A Novel Framework for Optimised Ensemble Classifier. The project aims to develop a novel framework for creating an optimised ensemble classifier that will improve data analysis and the accuracy of many real-world applications such as document analysis, robotics and medical diagnosis. The project plans to develop and investigate novel methods for generating diverse training environment layers, base classifiers and fusion of classifiers. It also plans to design a multi-objective evolutionary algorithm-based search obtain the optimal number of layers, clusters and base classifiers. The expected outcomes of the proposed framework are advances in classifier learning. The final outcome may be novel methods which will bring in diversity during the learning of the base classifiers and provide an optimal ensemble classifier for real-world applications.Read moreRead less
Risk-aware business process management. Risk-aware business process management will revolutionise the identification and treatment of risks in business processes by integrating the latest technologies for risk management and process management. It will provide organisations with a range of new tools and techniques for designing, deploying and monitoring risk-aware business processes.
Defending AI based FinTech Systems against Model Extraction Attacks. This project aims to develop new methods for defending artificial intelligence (AI) based FinTech systems from highly potent and insidious model extraction attacks whereby an adversary can steal the AI model from the system to cause intellectual property (IP) violation, business advantage disruption, and financial loss. This can be achieved by examining various attack models, creating active and utility-preserving defences, and ....Defending AI based FinTech Systems against Model Extraction Attacks. This project aims to develop new methods for defending artificial intelligence (AI) based FinTech systems from highly potent and insidious model extraction attacks whereby an adversary can steal the AI model from the system to cause intellectual property (IP) violation, business advantage disruption, and financial loss. This can be achieved by examining various attack models, creating active and utility-preserving defences, and inventing non-removable watermarks on AI models. The outcomes are new tools for securing AI-based FinTech systems before deployment and tools for IP violation forensics post-deployment. Such capabilities are beneficial by improving the security and safety of FinTech systems and other nationally critical AI systems.Read moreRead less
Re-engineering enterprise systems for microservices in the cloud. This project will enable automatic re-engineering of large enterprise applications to run in modern cloud environments as microservices. Microservices are the latest wave of service-based software, capable of exploiting the high performance and third-party integration opportunities made available through the cloud. The project will develop new techniques for analysing enterprise systems code and execution data, and making recommen ....Re-engineering enterprise systems for microservices in the cloud. This project will enable automatic re-engineering of large enterprise applications to run in modern cloud environments as microservices. Microservices are the latest wave of service-based software, capable of exploiting the high performance and third-party integration opportunities made available through the cloud. The project will develop new techniques for analysing enterprise systems code and execution data, and making recommendations for restructuring suitable parts as microservices. These microservices manage individual business objects via sets of lightweight distributed computational operations. The outcomes will support progressive evolution of an enterprise system, into distributed microservices running in public clouds, while still being integrated with "backend" systems.Read moreRead less