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
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.
Optical wireless communications: solving the spectrum crunch. This project aims to make optical wireless communication to handheld mobile receivers a reality by developing systems which combine holographic filters and microsystems to realise a new form of receiver. This will be based on analysis of all of the complex interactions of transmitter, receiver and channel properties. The new receivers will exploit the narrow field of view of holographic optical filters. This project will generate know ....Optical wireless communications: solving the spectrum crunch. This project aims to make optical wireless communication to handheld mobile receivers a reality by developing systems which combine holographic filters and microsystems to realise a new form of receiver. This will be based on analysis of all of the complex interactions of transmitter, receiver and channel properties. The new receivers will exploit the narrow field of view of holographic optical filters. This project will generate knowledge in the fields of communications theory and on the use of holographic filters and microsystems. This solution to the lack of available radio frequency spectrum which conventional wireless face will provide significant practical and commercial benefits.Read moreRead less
Massive Data Reading with Mobile Data Collectors for the Internet of Things. The Internet of Things (IoT) supports the connectivity of almost everything including powerless simple devices (such as radio frequency identification (RFID) tags), making it an indispensable technology for future industry and business. This project is to develop systematic and cost-effective approaches by leveraging existing cellular networks for the connectivity of simple sensors/devices using mobile data collectors ( ....Massive Data Reading with Mobile Data Collectors for the Internet of Things. The Internet of Things (IoT) supports the connectivity of almost everything including powerless simple devices (such as radio frequency identification (RFID) tags), making it an indispensable technology for future industry and business. This project is to develop systematic and cost-effective approaches by leveraging existing cellular networks for the connectivity of simple sensors/devices using mobile data collectors (such as smart phones) so that their information becomes available to IoT applications via cellular systems. For example, products’ information stored in RFID tags or power-limited sensors' data can be provided to logistic or IoT applications, respectively, without building dedicated systems via existing cellular systems.Read moreRead less
Accurate position estimation using intensity-modulated optical signals. Accurate information about the position of a person or device is essential in many situations. However, despite extensive worldwide research, there is still no positioning system suitable for many important indoor applications. The widespread introduction of energy efficient white light emitting diodes (LEDs) for indoor lighting provides an unprecedented opportunity to solve this problem by using these LEDs to transmit signa ....Accurate position estimation using intensity-modulated optical signals. Accurate information about the position of a person or device is essential in many situations. However, despite extensive worldwide research, there is still no positioning system suitable for many important indoor applications. The widespread introduction of energy efficient white light emitting diodes (LEDs) for indoor lighting provides an unprecedented opportunity to solve this problem by using these LEDs to transmit signals from which a receiver can calculate its position. However the theory underlying the design and analysis of position estimation using modulated optical signals does not exist. This project aims to develop this fundamental theoretical basis and apply it to create the accurate indoor positioning systems of the future.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102012
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Estimation and control algorithms over wireless networks. The use of wireless technologies in areas such as mobile communications has provided great benefits to society. Investigating estimation and control algorithms that are reliable when operating over the wireless environment will enable new technologies such as better management of Australia's water resources, and more fuel-efficient transportation.
Decimetre-level indoor positioning on Wi-Fi. This project aims to exploit both spatial and frequency diversities based on the multiple-input, multiple-out and frequency hopping techniques to achieve the goal of decimetre-level position accuracy by significantly increasing Wi-Fi bandwidth. Wi-Fi positioning is utilised in locations where GPS is blocked, typically this is within a structure. The project will design a set of mechanisms to facilitate Wi-Fi positioning, discover key principles to gui ....Decimetre-level indoor positioning on Wi-Fi. This project aims to exploit both spatial and frequency diversities based on the multiple-input, multiple-out and frequency hopping techniques to achieve the goal of decimetre-level position accuracy by significantly increasing Wi-Fi bandwidth. Wi-Fi positioning is utilised in locations where GPS is blocked, typically this is within a structure. The project will design a set of mechanisms to facilitate Wi-Fi positioning, discover key principles to guide practical design, and develop advanced algorithms to push the performance limit to decimetre-level accuracy. The project will develop key fundamental technologies which are expected to promote innovative, practical, and cost-effective applications to local industry and service sectors and contribute to Australia's long-term economic growth.Read moreRead less