Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa ....Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.Read moreRead less
Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expect ....Reducing direct greenhouse gas emissions from urban wastewater systems. This project aims to develop a systematic framework for water utilities to monitor and reduce direct greenhouse gas (GHG) emissions from wastewater systems. A standardised monitoring protocol will be developed to conduct an unprecedented nationwide sampling campaign. The obtained data, with microbial characterisation and mechanism analysis, will be used to develop novel models for accurate prediction of GHG emissions. Expected outcomes include protocol to accurately monitor emissions, models to predict emission under various conditions, and mitigation guideline for typical plant configurations. The anticipated benefit is a significant reduction in GHG emissions from urban water industry and support it to meet net-zero-emission goal by 2050.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100422
Funder
Australian Research Council
Funding Amount
$386,637.00
Summary
Feasible quantification of greenhouse gas emitted from wastewater treatment. This project aims to develop an accurate and practical approach to quantify greenhouse gas (GHG) emissions from wastewater treatment. Australian water utilities have pledged to net-zero emissions. However, most utilities do not know its actual emissions due to lack of feasible quantification method. This project will apply an interdisciplinary approach via mechanism investigations, mathematical modelling, and field work ....Feasible quantification of greenhouse gas emitted from wastewater treatment. This project aims to develop an accurate and practical approach to quantify greenhouse gas (GHG) emissions from wastewater treatment. Australian water utilities have pledged to net-zero emissions. However, most utilities do not know its actual emissions due to lack of feasible quantification method. This project will apply an interdisciplinary approach via mechanism investigations, mathematical modelling, and field works to develop and validate a new feasible quantification method. This project will also advance knowledge on GHG emissions to guide quantification design. The outcomes will be translated into industry protocols and disseminated into industry. The outcomes provide timely support to water sector on its pathway to net-zero.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
Industrial Transformation Training Centres - Grant ID: IC180100030
Funder
Australian Research Council
Funding Amount
$3,925,357.00
Summary
ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching ....ARC Training Centre for Transforming Maintenance through Data Science. The ARC Training Centre for Transforming Maintenance through Data Science aims to equip practising engineers and Australian graduates with the next generation of data science methods for the maintenance sector. The Centre plans to introduce timely and cost-efficient maintenance scheduling by developing data-intensive mathematical and computational algorithms for asset management and fault prediction. The Centre’s overarching objectives are to enable development and adoption of new practices to improve productivity and asset reliability for industry and to foster a new maintenance technology service sector for national and international markets.Read moreRead less
Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the c ....Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the characteristics of the particles, their sources and spatial and temporal variation across different urban areas and time scales. Further, the impacts of changing fuels, vehicle technologies, and climate on future trends of the particles will be elucidated.Read moreRead less
Fate of PAPs and short-chain PFAS in biosolids amended soils. Biosolids generated during wastewater treatment contain PFAS which are persistent, bioaccumulative and toxic. Application of biosolids to agricultural land may result in soil, groundwater and surface water PFAS contamination via leaching and run-off and pose unknown potential risk to soil health, crops and beneficial biota. This study aims to generate novel knowledge on the PFAS fate in biosolid amended soils, crops and toxicity to ke ....Fate of PAPs and short-chain PFAS in biosolids amended soils. Biosolids generated during wastewater treatment contain PFAS which are persistent, bioaccumulative and toxic. Application of biosolids to agricultural land may result in soil, groundwater and surface water PFAS contamination via leaching and run-off and pose unknown potential risk to soil health, crops and beneficial biota. This study aims to generate novel knowledge on the PFAS fate in biosolid amended soils, crops and toxicity to key soil and aquatic biota at environmentally relevant concentrations. This study is supported by Australian water and its allied industries, as it is important for them to ensure that biosolids application to agricultural land is an environmentally sustainable solution to the Australian farmers and communities.Read moreRead less
Deciphering interactions of conducting polymers in agricultural soils. The project aims to improve agricultural efficiency, productivity and yield by advancing the understanding of polymer materials interacting with fertiliser. This project will test the key assumptions behind a new sensor for real-time in-ground monitoring of fertiliser. The expected outcome from this is the rapid synthesis of conducting polymers for stable sensing of fertiliser in a range of soil types and conditions. This sho ....Deciphering interactions of conducting polymers in agricultural soils. The project aims to improve agricultural efficiency, productivity and yield by advancing the understanding of polymer materials interacting with fertiliser. This project will test the key assumptions behind a new sensor for real-time in-ground monitoring of fertiliser. The expected outcome from this is the rapid synthesis of conducting polymers for stable sensing of fertiliser in a range of soil types and conditions. This should provide the pathway to a world first real-time in-ground fertiliser sensor, providing benefit for the sensor manufacturers, farmers, consumers and the environment.Read moreRead less
Industry Laureate Fellowships - Grant ID: IL230100175
Funder
Australian Research Council
Funding Amount
$3,763,434.00
Summary
Combatting wildlife crime and preventing environmental harm. Wildlife crime is one of the greatest threats to environmental and human security across the globe. In Australia, the illegal harvesting, killing, and trade of wild animals and plants endangers the country’s unique biodiversity and poses serious biosecurity risks to natural and agricultural systems. This Fellowship will deliver the intelligence tools and technologies, in wildlife forensics and cyber security, that are required for step ....Combatting wildlife crime and preventing environmental harm. Wildlife crime is one of the greatest threats to environmental and human security across the globe. In Australia, the illegal harvesting, killing, and trade of wild animals and plants endangers the country’s unique biodiversity and poses serious biosecurity risks to natural and agricultural systems. This Fellowship will deliver the intelligence tools and technologies, in wildlife forensics and cyber security, that are required for step-change reductions in wildlife crime in Australia, and Asia-Pacific. The project will establish new approaches for raising public awareness of the dangers of wildlife crime and provide much needed stewardship to protect Australia’s environmental assets and natural capital from current and future threats.Read moreRead less
Three-dimensional Bayesian Modelling of Geological and Geophysical data. The project aims to develop technologies enabling rapid informed decision-making related to the management of natural resources, including critical metals, copper and water. This new technology will support a greener future, securing our energy future, our access to clean water and reduce the mining footprint. Expected outcomes include an enhanced capability in interoperable, integrated three-dimensional geological and geop ....Three-dimensional Bayesian Modelling of Geological and Geophysical data. The project aims to develop technologies enabling rapid informed decision-making related to the management of natural resources, including critical metals, copper and water. This new technology will support a greener future, securing our energy future, our access to clean water and reduce the mining footprint. Expected outcomes include an enhanced capability in interoperable, integrated three-dimensional geological and geophysical modelling in order to predictively characterise sub-surface geology. The outcome will be an open-source forecasting dashboard enabling decision making while considering underlying risk related to resource extractions and management with significant benefits to the Australian society (lower emissions, clean water).Read moreRead less