Intelligent real time multi-site controller for conserving energy in remote areas and in the resource industry. This project researches the issues in achieving demand response for electricity usage in remote regions of Australia through the use of smart meters and web of things framework to provide ubiquitous monitoring and control of devices, intelligent control systems to dynamically change energy usage patterns and community-based social network architecture. This will lead to several benefit ....Intelligent real time multi-site controller for conserving energy in remote areas and in the resource industry. This project researches the issues in achieving demand response for electricity usage in remote regions of Australia through the use of smart meters and web of things framework to provide ubiquitous monitoring and control of devices, intelligent control systems to dynamically change energy usage patterns and community-based social network architecture. This will lead to several benefits, such as (a) the strengthening of Australian business competitiveness in these regions by reducing energy costs and increasing energy trading, (b) reduction in ecological impact through smarter utilisation of energy and shifting to renewable sources, (c) encourage local generation and distribution of electricity where communities can trade excess energy.Read moreRead less
Boosting up Productivity: Optimizing Scaffolding Life Cycle Management with Virtual Design and Construction. Scaffolding management can be critical to construction industries across oil and gas, building, and infrastructure sectors. It can lead to low productivity and safety due to static and poor planning. This project aims to innovatively integrate a decision support system, virtual design and construction, and onsite monitoring into one dynamic planning system to significantly lift productivi ....Boosting up Productivity: Optimizing Scaffolding Life Cycle Management with Virtual Design and Construction. Scaffolding management can be critical to construction industries across oil and gas, building, and infrastructure sectors. It can lead to low productivity and safety due to static and poor planning. This project aims to innovatively integrate a decision support system, virtual design and construction, and onsite monitoring into one dynamic planning system to significantly lift productivity. The emphasis is on producing optimal solutions for planning, design, erection, monitoring, dismantling, and relocation of scaffolding, so that productivity is maximised subject to satisfying required cost and safety constraints. The project aims to therefore secure long-term economic benefits by improving productivity and enhancing project performance.Read moreRead less
Congestion management in key road networks of a major city through real time data collection, intelligent forecasting and real time routing. The project researches the issues for allowing Australian Road Traffic Authorities to automatically capture road traffic data, forecast traffic flows and smartly route traffic flows to avoid congestion on road networks. This will lead to several benefits, such as (a) reducing traffic congestion, shorten travel time and lower pollution, (b) better utilizati ....Congestion management in key road networks of a major city through real time data collection, intelligent forecasting and real time routing. The project researches the issues for allowing Australian Road Traffic Authorities to automatically capture road traffic data, forecast traffic flows and smartly route traffic flows to avoid congestion on road networks. This will lead to several benefits, such as (a) reducing traffic congestion, shorten travel time and lower pollution, (b) better utilization of existing road infrastructure by diffusing traffic to alternate routes, (c) provide economic benefit by allowing one to delay infrastructure expansion, (d) monitoring of aberrant behaviour by road users to ensure a safer road environment, and (e) improved flexibility in deployment of the Wireless Sensor Network to meet the needs of the road authorities and community.Read moreRead less
The Relevance of the Bovine Major Histocompatibility Complex (MHC) to Milk Production. The objective of this project is to provide the dairy industry with an integrated package that includes a ?dairy performance database? linked to DNA-based information to complement existing breeding practices. Our intention is increase the profitability of the dairy industry, hence making a dairy farm a sustainable venture in a deregulated environment. Profitability results from a combination of several fact ....The Relevance of the Bovine Major Histocompatibility Complex (MHC) to Milk Production. The objective of this project is to provide the dairy industry with an integrated package that includes a ?dairy performance database? linked to DNA-based information to complement existing breeding practices. Our intention is increase the profitability of the dairy industry, hence making a dairy farm a sustainable venture in a deregulated environment. Profitability results from a combination of several factors. The drivers of the industry include political, market, environmental, husbandry, nutrition, and genetic factors. These factors are interrelated. In this proposal, we are specifically interested in the relationship between milk yields and the DNA profile of dairy cattle.Read moreRead less
Application of Optimisation Techniques to the Truck/Loader Selection Problem in Mining. Australia has world class deposits of most major mineral commodities and is a major producer and exporter of coal and many metals. The mining industry has an annual turnover of around $40 billion. A significant component (up to 55%) of mining costs is material handling. This project aims to develop computational tools for determining the best selection of trucks and loaders for the mining operation. To da ....Application of Optimisation Techniques to the Truck/Loader Selection Problem in Mining. Australia has world class deposits of most major mineral commodities and is a major producer and exporter of coal and many metals. The mining industry has an annual turnover of around $40 billion. A significant component (up to 55%) of mining costs is material handling. This project aims to develop computational tools for determining the best selection of trucks and loaders for the mining operation. To date this important problem has not been addressed. Our strategy is to develop accurate mathematical models and cutting edge optimisation techniques for their solution. The research outcomes will have significant outcomes for the mining industry.Read moreRead less
Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combination ....Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combinations of different types of units. The complexity of typical flowsheet layouts will require new algorithms to discover improved designs in practical time, so parallel hardware, and new parallel EAs, will be utilised.
Read moreRead less
Transforming liquefied
natural gas (LNG) plant construction productivity through mobile computing technologies. Australia's liquefied natural gas (LNG) construction industry is plagued by major cost blowouts. This project will investigate a new mobile computing approach for streamlining LNG construction projects, thus yielding significant productivity gains.
A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons fo ....A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons for rejection at construction sites, resulting in significant costs, waste, and delays. Multimodal data sources will be used to provide a reliable workability estimate in real time, enabling construction teams to identify and rectify workability issues in transit while continuously monitoring the adjustments effects.Read moreRead less
Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop ....Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop efficient privacy preserving algorithms to deal with static and dynamic network data sharing. The success of this project will benefit many industries and government agencies to reduce users’ privacy breaches, avoid illegal consequences of sharing data, and enhance these service providers’ service quality.Read moreRead less