Control systems for irrigation networks in storage critical operations. The aim of the project is to further develop automatic control technologies for irrigation channels, with particular focus on supply mode operations for channels with critical limits on storage and inflow. The significance relates to the role of irrigation channels in food and fibre production. New knowledge generated will help Rubicon Water expand its Total Channel Control product, already used extensively in Australia, to ....Control systems for irrigation networks in storage critical operations. The aim of the project is to further develop automatic control technologies for irrigation channels, with particular focus on supply mode operations for channels with critical limits on storage and inflow. The significance relates to the role of irrigation channels in food and fibre production. New knowledge generated will help Rubicon Water expand its Total Channel Control product, already used extensively in Australia, to suit emerging markets with significant export potential. Beyond the commercial impact, expected benefits include improved service, reduced environmental footprint, the safeguarding of assets in extreme events, and the training of engineers in the important areas of modelling and control for infrastructure management.
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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
A Novel Inline High-Efficiency Motor/Pump System. Around 19% of the world’s and 30% of the Australia’s electric energy is consumed by pump technologies. Significant energy savings are possible if the major components of pump systems, including inverter, motor and pump, operate at their maximum possible efficiency under varying loads. A novel pump design in this project accommodates integrated electronics in a submersible housing. A seal-less design helps mitigate several aspects of pump failure ....A Novel Inline High-Efficiency Motor/Pump System. Around 19% of the world’s and 30% of the Australia’s electric energy is consumed by pump technologies. Significant energy savings are possible if the major components of pump systems, including inverter, motor and pump, operate at their maximum possible efficiency under varying loads. A novel pump design in this project accommodates integrated electronics in a submersible housing. A seal-less design helps mitigate several aspects of pump failure and its in-line structure reduces assembly cost. Accurately measured efficiency maps will be utilised to demonstrate the non-linear relationship between motor and pump quantities as well as developing models for indirectly estimating feedback quantities and achieving the highest system efficiency.Read moreRead less
Radio Frequency Camera for Low-Complexity and High-Resolution Radar Imaging. This project aims to develop the theory and enabling techniques to realise a low-complexity and high-resolution radar imaging system with uncoordinated illumination. New scientific breakthroughs include fundamental radar imaging theory, advanced radio frequency frontend design and fast signal processing algorithms. These will lead to a paradigm shift in active and passive imaging technologies. A proof-of-concept prototy ....Radio Frequency Camera for Low-Complexity and High-Resolution Radar Imaging. This project aims to develop the theory and enabling techniques to realise a low-complexity and high-resolution radar imaging system with uncoordinated illumination. New scientific breakthroughs include fundamental radar imaging theory, advanced radio frequency frontend design and fast signal processing algorithms. These will lead to a paradigm shift in active and passive imaging technologies. A proof-of-concept prototype of the proposed imaging system with 77 GHz millimetre wave will be developed to demonstrate its feasibility and performance. The expected outcomes include Australia’s scientific and technological leadership in radar imaging and enhanced capability in emergency response, defence, public safety, and healthcare industries.Read moreRead less
Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic ....Biologically Inspired Binaural Coupling for Selective Machine Hearing. This project aims to investigate biologically-inspired binaural coupling models in the context of the deep learning paradigm by formulating desirable higher level auditory structures as neural network sub-systems. This project expects to generate new knowledge for developing the next generation of robust speech processing systems that are capable of mimicking the selecting listening ability of humans when faced with realistic noisy speech signals and the ‘cocktail party problem’ using innovative binaural feedback systems. This work should provide significant benefits, including improved voice biometrics and selective auditory attention capabilities in machines.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
Ultra-reliable and low-latency mission critical communications. This project aims to develop enabling technologies for ultra-reliable and low-latency communications. While the evolution of wireless communication technologies to date has focused on data rate improvement, very little is known on how to achieve ultra-reliability and almost-zero latency which is urgently required for mission critical applications such as smart manufacturing and intelligent vehicles. The outcomes of the project will ....Ultra-reliable and low-latency mission critical communications. This project aims to develop enabling technologies for ultra-reliable and low-latency communications. While the evolution of wireless communication technologies to date has focused on data rate improvement, very little is known on how to achieve ultra-reliability and almost-zero latency which is urgently required for mission critical applications such as smart manufacturing and intelligent vehicles. The outcomes of the project will be new analytical tools and practical guidelines for designing trusted communication platforms to realise these applications, with benefits ranging from improved safety in intelligent transportation systems to digital transformation of the manufacturing industry.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101181
Funder
Australian Research Council
Funding Amount
$403,775.00
Summary
Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multipl ....Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multiple mobile agents (e.g. vehicle) to enhance their ability to anticipate situations in dynamic environments and to act effectively to enhance safety. This should provide benefits for the development of cooperative autonomous driving to enhance road safety.Read moreRead less
Speech recognition adaptation for low resource populations. Automatic speech recognition is an essential attribute of mobile devices and consumer electronics. Unfortunately, as these systems are trained with adult speech, they perform poorly when used by children and people with speaking difficulties. The lack of available training speech from these groups makes developing models for them difficult. We will investigate efficient model adaptation methods that use minimal training data to adapt ex ....Speech recognition adaptation for low resource populations. Automatic speech recognition is an essential attribute of mobile devices and consumer electronics. Unfortunately, as these systems are trained with adult speech, they perform poorly when used by children and people with speaking difficulties. The lack of available training speech from these groups makes developing models for them difficult. We will investigate efficient model adaptation methods that use minimal training data to adapt existing adult speech recognition models for use with children and people with speaking difficulties. The intended outcomes will improve access to automatic speech recognition systems for Australians whose communication with speech-controlled environmental and educational devices is currently restricted.Read moreRead less