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
Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emer ....Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.Read moreRead less
Enabling Automatic Graph Learning Pipelines with Limited Human Knowledge. This project aims to develop an automatic graph learning system for complex graph data analysis. Machine learning for graph data commonly requires significant human knowledge from both domain professionals as well as algorithm experts, rendering existing systems ineffective and unexplainable. This project expects to design novel graph learning techniques which automatically infer graph relations, learn graph models, adapts ....Enabling Automatic Graph Learning Pipelines with Limited Human Knowledge. This project aims to develop an automatic graph learning system for complex graph data analysis. Machine learning for graph data commonly requires significant human knowledge from both domain professionals as well as algorithm experts, rendering existing systems ineffective and unexplainable. This project expects to design novel graph learning techniques which automatically infer graph relations, learn graph models, adapts existing knowledge to new domains, and provide explanations to the graph learning system. The research results should provide benefit to governments and businesses in many critical applications, such as bioassay activity prediction, credit assessment, and drug discovery and vaccine development in response to the pandemic.Read moreRead less
Modelling and simulation of self-organised behaviour in biological and bio-inspired systems. Understanding self-organised systems is fundamental in biology and bio-inspired engineering. The project develops sophisticated mathematical modelling techniques and high performance simulation methods for such systems. This will increase our capacity to explain complex biological behaviour and to produce reliable bio-inspired engineering solutions
Discovery Early Career Researcher Award - Grant ID: DE120102210
Funder
Australian Research Council
Funding Amount
$350,333.00
Summary
Feedback control as a tool for enhanced neuroprosthetic stimulation. The aim is to use control theory tools to find optimal stimulation parameters to use in a bionic implant. This project will lead to improvements in understanding of mechanisms underlying electrical stimulation and to improvements in medical bionics technologies.
New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficie ....New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficient algorithms for signal quality analysis and enhanced feature extraction methods in resource constrained wearable devices. This will improve the reliability and performance of wearable devices for adoption in intelligent decision-making systems.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
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
A compact microphone array system for outdoor low frequency noise measurements. To investigate the impact of wind farm noise on surrounding communities, the sound level caused by wind turbines must be accurately measured, which sometimes is hard due to wind induced noise and other interference noise. This project aims to propose a novel compact microphone array solution, where the wind induced noise is attenuated by a specially designed windproof shell first, and then the residual wind induced n ....A compact microphone array system for outdoor low frequency noise measurements. To investigate the impact of wind farm noise on surrounding communities, the sound level caused by wind turbines must be accurately measured, which sometimes is hard due to wind induced noise and other interference noise. This project aims to propose a novel compact microphone array solution, where the wind induced noise is attenuated by a specially designed windproof shell first, and then the residual wind induced noise and other interference noise are further filtered out by a specific adaptive noise cancellation algorithm based on the spherical and differential microphone array structure. With the proposed system, the measurement configuration size is expected to be reduced from the current few metres to less than 10 centimetres, and with better accuracy.Read moreRead less
A new approach to compressed sensing. Compressed sensing is an exciting new paradigm promising vastly improved signal sampling and reconstruction in a wide variety of applications including digital cameras, mobile phones and MRI machines. This project will explore a newly discovered approach to compressed sensing which uses mathematical arrays known as hash families.