Improving Productivity and Efficiency of Australian Airports – A Real Time Analytics and Statistical Approach. Aviation is a major economic driver both within Australia and overseas, but the aviation industry faces growing challenges from the increase in passengers and changing regulations. To meet these challenges, airports, airlines, government agencies and others need to maximise their efficiency and productivity; however, complex dependencies and differing operational objectives complicate t ....Improving Productivity and Efficiency of Australian Airports – A Real Time Analytics and Statistical Approach. Aviation is a major economic driver both within Australia and overseas, but the aviation industry faces growing challenges from the increase in passengers and changing regulations. To meet these challenges, airports, airlines, government agencies and others need to maximise their efficiency and productivity; however, complex dependencies and differing operational objectives complicate this task. This project aims to develop a real-time, whole-of-system operational performance framework that can help operators in finding and evaluating solutions to maximise throughput, reduce wait times and mitigate flow-on effects. Innovative new video analytic and Bayesian Network based tools are integrated to address the challenges of adaptability and uncertainty.Read moreRead less
Developing an integrated optimisation platform for innovative design of composite fabrication process. This project will develop a new optimisation design tool enabling industry to virtually test innovative design concepts for the next generation of composite manufacturing process. This will reduce composite production cost and energy used, making the Australian composites industry more environmentally friendly and sustainable.
Subject-specific computational models for accurate evaluation of muscle function in human locomotion. The purpose of this project is to advance current understanding of muscle function during human locomotion. The most significant outcome will be the development of novel computational tools that can play a pivotal role in the healthcare industry through the prevention, diagnosis and treatment of movement disorders.
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Developing novel big-data based models for designing greener turbines. Developing novel big-data based models for designing greener turbines. This project aims to improve the fuel efficiency of gas turbines, the backbone of power generation and aircraft propulsion, for efficient and affordable power generation and air travel. Australia is large, remote and has some of the world’s highest carbon dioxide emissions per capita. Improving fuel efficiency will reduce cost and emissions, but current de ....Developing novel big-data based models for designing greener turbines. Developing novel big-data based models for designing greener turbines. This project aims to improve the fuel efficiency of gas turbines, the backbone of power generation and aircraft propulsion, for efficient and affordable power generation and air travel. Australia is large, remote and has some of the world’s highest carbon dioxide emissions per capita. Improving fuel efficiency will reduce cost and emissions, but current design tools lack the accuracy to advance technology. This project will investigate fluid flow in gas turbines and use big-data analytics to develop more accurate design tools. Gas turbines with reduced fuel usage and carbon dioxide emissions are expected to reduce the cost and environmental impact of power generation and air travel in Australia.Read moreRead less
Integrating Mobility on Demand in urban transport infrastructures. Australia’s major cities are substantially challenged for public transport services due to the dispersed and low population densities, and thus, roads are at or beyond their capacity. Smarter demand-responsive public transport services are therefore needed. This project studies the viability of such a service under a variety of scenarios.
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Developing an integrated predictive model for optimal design of ventilation systems in buildings. This project will undertake a comprehensive study to characterize indoor contaminant exposure to develop an integrated predictive model for optimal design of ventilation systems. The outcomes of this research may lead to improved preventative measures, reducing occupational diseases and cutting socio-economic burden to the Australian community.