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
Human-Unmanned Aerial Vehicle interactions: Making drones talk and listen. This project aims to develop audio technology to enable unmanned aerial vehicles or drones to hear, use speech and sound to communicate with humans, acoustically sense their surroundings and make them less noisy. This project expects to generate new knowledge in acoustic signal processing and its application in drones using innovative approaches, such as use of miniature microphone and loudspeaker arrays, and active noise ....Human-Unmanned Aerial Vehicle interactions: Making drones talk and listen. This project aims to develop audio technology to enable unmanned aerial vehicles or drones to hear, use speech and sound to communicate with humans, acoustically sense their surroundings and make them less noisy. This project expects to generate new knowledge in acoustic signal processing and its application in drones using innovative approaches, such as use of miniature microphone and loudspeaker arrays, and active noise control. Expected outcomes include development of new theories, Intellectual Property, with potential commercial value, and training of next generation researchers. This should provide significant benefits with applications in life saving, search and rescue operations, transportation of goods, and creation of 3D media.Read moreRead less
Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed ....Collision Avoidance in Shipping Lanes via Intelligent Sensor Data Fusion . This project aims to develop an online maritime traffic monitoring system for reliable collision/contact avoidance that exploits complementary data from high-resolution airborne sensors and surface vessel sensors. Our approach is based on optimal scheduling and fusion of the sensor data and possibly other sources of data to construct a comprehensive dynamic picture of maritime traffic, in real-time. Moreover, the proposed methodology enables quantification of confidence in the predictions. This will provide ship owners, directly to their vessels and/or at the fleet management centres, information such as weather reports, reliable collision/no-collision warnings and avoidance strategies, on-the-fly. Read moreRead less
Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expecte ....Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expected outcomes are algorithms for public and private sector data curators to dial up or down their data access arrangements based on privacy risks and fidelity demands linked with different data types and uses. This project intends to enable Australians to securely benefit from valuable data in decision making.Read moreRead less
A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, th ....A Bayesian Approach to Distributed Estimation for Multi-Object Systems. This project aims to develop new signal processing techniques that facilitate autonomous technologies for environmental perception, with the ability to efficiently process large data volumes from multiple sensing modalities. Rapid advances in sensors and networks have led to a digital data deluge, from which extracting useful information presents new technological challenges and opportunities. To address this development, this project seeks to develop new distributed solutions for statistical estimation, which are specifically designed for dynamic systems with multiple object states, and are inherently scalable and robust. The potential benefits include new technologies for smart cities, autonomous infrastructure, and digital productivity.Read moreRead less
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
Creating a Perceptive Mobile Network Using Joint Communication and Sensing. This project aims to develop foundational technologies for an innovative perceptive mobile (cellular) communication network that is also capable of ubiquitous radio sensing. It is expected to generate groundbreaking theorems and algorithms that will significantly advance the knowledge of joint communication and sensing. The intended outcomes are an innovative large-scale sensing solution capable of real-time 3D-plus radi ....Creating a Perceptive Mobile Network Using Joint Communication and Sensing. This project aims to develop foundational technologies for an innovative perceptive mobile (cellular) communication network that is also capable of ubiquitous radio sensing. It is expected to generate groundbreaking theorems and algorithms that will significantly advance the knowledge of joint communication and sensing. The intended outcomes are an innovative large-scale sensing solution capable of real-time 3D-plus radio imaging of the world, and enhanced communications with improved quality and reliability. The technology will revolutionize traditional communication-only mobile networks. It will enable and boost expansive radio sensing applications in e.g. transportation, energy, agriculture, and security.Read moreRead less
Low-energy electro-photonics: novel materials, devices and systems. This project aims to develop low-power technologies for programming and tuning photonic integrated circuits (PICs). By replacing thermal tuning, the project will reduce power consumption from watts to milliwatts, which also eliminates the thermal crosstalk that limits the complexity of today's PICs. The expected outcome will be the basis for a generic field-programmable photonic chip, which can be used to rapidly prototype desig ....Low-energy electro-photonics: novel materials, devices and systems. This project aims to develop low-power technologies for programming and tuning photonic integrated circuits (PICs). By replacing thermal tuning, the project will reduce power consumption from watts to milliwatts, which also eliminates the thermal crosstalk that limits the complexity of today's PICs. The expected outcome will be the basis for a generic field-programmable photonic chip, which can be used to rapidly prototype designs for production as full custom chips as part of a new Australian industry capability. The expected benefits will be a faster innovation cycle, greater adoption of photonic technologies, and support of research into, for example, neuromorphic optical processing, and advanced communications and sensing systems.Read moreRead less
Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New ....Estimation and Control of Noisy Riemannian Systems. Many application areas such as satellite control, computer vision, coordination of rigid bodies, require the estimation and control of systems subject to geometric constraints. Most current algorithms for doing this are deterministic and can fail catastrophically in the presence of noise. This project aims to provide:
(i) Methods for analysing and then redesigning deterministic algorithms to ensure stability in the presence of noise;
(ii) New design methods that deal with noise in an optimal way;
(iii) Noise resistant methods for distributed consensus seeking systems and cooperative control systems.
The outcomes will advance and benefit spatio-temporal data analysis and coordination in areas such as transport, health and video-security.Read moreRead less
Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliabl ....Vector network system identification. This machine learning project aims to provide more reliable ways to identify the structure and function of dynamic networks from both continuous and discrete network data. The project will use all the data and create principled new metrics. This could enable early diagnosis of network faults across a range of applications for example in power systems or diseased human brains. It could also enable discovery of critical functional subnetworks affecting reliable operation in large complex human systems (such as financial systems) or natural systems (such as gene regulatory networks).Read moreRead less