Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Learning the Focus of Attention to Detect Distributed Coordinated Attacks. Cyber security analysts need to detect and respond to attacks as soon as possible, to minimise the damage attackers can inflict. However, the growth in highly distributed attacks that span multiple networks has meant that massive volumes of data need to be analysed. While machine learning techniques can help filter the data, we need techniques that can automatically provide a focus of attention for analysts on the most re ....Learning the Focus of Attention to Detect Distributed Coordinated Attacks. Cyber security analysts need to detect and respond to attacks as soon as possible, to minimise the damage attackers can inflict. However, the growth in highly distributed attacks that span multiple networks has meant that massive volumes of data need to be analysed. While machine learning techniques can help filter the data, we need techniques that can automatically provide a focus of attention for analysts on the most relevant observations. Our aim is to devise a novel suite of attention mechanisms that can focus the search of machine learning techniques for cyber security. The results of this project will improve the accuracy and efficiency of detecting distributed attacks across multiple networks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180101292
Funder
Australian Research Council
Funding Amount
$324,446.00
Summary
Sparse link discovery for mobile millimeter-wave communications. This project will advance knowledge of designing wireless networks by providing new design principles and delivering innovative techniques for ultra-high data-rate mm-wave communications.. Drawing upon advances in signal processing and optimisation theory, this project will provide new design principles and deliver innovative techniques that will reduce the cost of operating mm-wave networks. The project will release the tension of ....Sparse link discovery for mobile millimeter-wave communications. This project will advance knowledge of designing wireless networks by providing new design principles and delivering innovative techniques for ultra-high data-rate mm-wave communications.. Drawing upon advances in signal processing and optimisation theory, this project will provide new design principles and deliver innovative techniques that will reduce the cost of operating mm-wave networks. The project will release the tension of spectrum crunch, facilitate the development of the next generation cellular systems and will lead to improved wireless service.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120101266
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Low-complexity factor-graph-based receiver design for bandwidth-efficient communication systems over doubly selective channels. This project aims to solve challenging problems in future wireless communications using graph-based signal processing techniques. It will provide practical solutions for future broadband mobile communications to the bush and high-speed underwater acoustic communications in the oceans that are particularly important to Australia.
Scheduling and quality of service in Long Term Evolution telecommunications. There is an explosion of mobile telecommunications with over 50 billion connections expected by 2020. The next generation of mobile broadband will be based on a new technology known as Long Term Evolution (LTE) and, in this context, the goal of this project is to improve the efficiency of these systems by developing new techniques for scheduling.
Blind separation of mutually correlated sources. This project is aimed at developing novel techniques for blind separation of mutually correlated sources. The expected outcomes will significantly advance the theory of blind source separation and improve the performance of important practical systems, such as densely deployed sensor networks and wireless video surveillance systems.
Safeguarding Future Wireless Communications with Physical Layer Security. Wireless communication is vulnerable to eavesdropping attacks since the transmitted signal enters an open wireless medium allowing anyone to overhear it. This project tackles the challenging problem of secure wireless transmissions through the advancement of a new security technology termed physical layer security. Theoretical frameworks are expected to be developed to understand how this new technology extracts the intri ....Safeguarding Future Wireless Communications with Physical Layer Security. Wireless communication is vulnerable to eavesdropping attacks since the transmitted signal enters an open wireless medium allowing anyone to overhear it. This project tackles the challenging problem of secure wireless transmissions through the advancement of a new security technology termed physical layer security. Theoretical frameworks are expected to be developed to understand how this new technology extracts the intrinsic security from the wireless medium to protect the confidentiality of information transmission. The research outcome is expected to provide for innovative solutions to safeguard Australia's future commercial, government and military wireless networks, and to give pivotal insights into the impact of this new technology on national security.Read moreRead less
Robust Federated Learning for Imperfect Decentralised Data. This project aims to develop a next-generation robust federated learning framework to tackle the challenging scenarios of imperfect decentralised data in real applications, e.g. mobile phones and the Internet of Things (IoT) devices. The outcomes will bring great benefits to a broad range of industry sectors by providing novel large-scale intelligent applications with privacy preservation. The proposed method will advance the developmen ....Robust Federated Learning for Imperfect Decentralised Data. This project aims to develop a next-generation robust federated learning framework to tackle the challenging scenarios of imperfect decentralised data in real applications, e.g. mobile phones and the Internet of Things (IoT) devices. The outcomes will bring great benefits to a broad range of industry sectors by providing novel large-scale intelligent applications with privacy preservation. The proposed method will advance the development of a cutting-edge technique to develop new intelligent applications in a decentralised and privacy-sensitive scenario. This game-changing research will advance current data mining and artificial intelligence research from centralised intelligence to decentralised intelligence with a collaboration network.Read moreRead less
Enabling ultra-reliable and sustainable machine-to-machine communications. This project aims to develop spectrum sharing and power transfer techniques for machine-to-machine communications in future wireless networks. Current wireless networks have high data rate as a priority but cannot deliver ultra-reliable and extended battery life operation for many low data rate machine-type devices. Through proper design of wireless and autonomous machine-to-machine communications, this project expects to ....Enabling ultra-reliable and sustainable machine-to-machine communications. This project aims to develop spectrum sharing and power transfer techniques for machine-to-machine communications in future wireless networks. Current wireless networks have high data rate as a priority but cannot deliver ultra-reliable and extended battery life operation for many low data rate machine-type devices. Through proper design of wireless and autonomous machine-to-machine communications, this project expects to improve quality of life and implement ultra-reliable, intelligent and long lasting machine-type monitoring devices for health, agriculture, mining, wildlife and critical national infrastructure.Read moreRead less