Industrial Transformation Research Hubs - Grant ID: IH170100013
Funder
Australian Research Council
Funding Amount
$2,962,655.00
Summary
ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed device ....ARC Research Hub for Digital Enhanced Living. The ARC Research Hub for Digital Enhanced Living aims to address the growing challenges of aging people living in their own home or residential care. This will be through inventing new personalised medical technologies through an innovative approach, with a multi-disciplinary team leveraging diverse expertise. An enhanced capacity to create and deploy fit-for-purpose personalised health solutions will result in revenues from new and repurposed devices, analytics and integration platforms. New jobs and improved care will see cost reductions, better use of resources and enhanced mental, physical and social well-being.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH210100001
Funder
Australian Research Council
Funding Amount
$2,062,428.00
Summary
ARC Research Hub for Nutrients in a Circular Economy (NiCE). Urban utilities are in need to design resilient wastewater infrastructure to tackle the pressures of urban intensification, waterways pollution and climate change. This Hub aims to transform the wastewater industry with an unprecedented, city-scale circular economy of nutrients based on urine separation and processing at building level, to produce safe and effective liquid fertilisers. By engaging with stakeholders across the value cha ....ARC Research Hub for Nutrients in a Circular Economy (NiCE). Urban utilities are in need to design resilient wastewater infrastructure to tackle the pressures of urban intensification, waterways pollution and climate change. This Hub aims to transform the wastewater industry with an unprecedented, city-scale circular economy of nutrients based on urine separation and processing at building level, to produce safe and effective liquid fertilisers. By engaging with stakeholders across the value chain, this Hub expects to bring two urine processing technologies to commercial readiness, and to produce new regulations and business models for the circular economy. This will add resilience to the wastewater and urban farming industries, and will create market opportunities for new Australian technologies.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH200100009
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Transforming Energy Infrastructure Through Digital Engineering. This Research Hub will harness the strengths of data-based and physics-based sciences to transform the operation of Australia’s offshore energy infrastructure. This essential research will create, use and embed observations of past and ongoing activity to engineer tools and approaches necessary to enhance our understanding of the offshore environment, optimise critical operations for existing facilities (includi ....ARC Research Hub for Transforming Energy Infrastructure Through Digital Engineering. This Research Hub will harness the strengths of data-based and physics-based sciences to transform the operation of Australia’s offshore energy infrastructure. This essential research will create, use and embed observations of past and ongoing activity to engineer tools and approaches necessary to enhance our understanding of the offshore environment, optimise critical operations for existing facilities (including installation and maintenance), and efficiently design future infrastructure. The integrated multidisciplinary approach will not only help Operators achieve high productivity through low downtime and optimised maintenance, but also demonstrate, in research and industry, the transformative potential of digital engineering.Read moreRead less
ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environme ....ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environments. EII will address 3 tightly coupled research themes: Ability to interoperate across existing heterogenous platforms & applications; Efficient processing of very large data sets; Technology adoption & impact. Generic results will be applicable to e-science and large business information systems installations.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Understanding and Managing the Occupational Health Impacts on Investigators of Internet Child Exploitation. Through developing best practice models for managing vicarious trauma in investigators of Internet child exploitation, the project will result in enhanced job satisfaction and less burnout of workers, and reduced health costs for policing organisations. Thus the project addresses a serious occupational health issue and contributes to the goal of promoting and maintaining good health. Furth ....Understanding and Managing the Occupational Health Impacts on Investigators of Internet Child Exploitation. Through developing best practice models for managing vicarious trauma in investigators of Internet child exploitation, the project will result in enhanced job satisfaction and less burnout of workers, and reduced health costs for policing organisations. Thus the project addresses a serious occupational health issue and contributes to the goal of promoting and maintaining good health. Further, by better managing the occupational health of investigators, the project will enhance the capacity of police organisations to deliver on their mission of investigating and preventing Internet child exploitation. This in turn contributes to the reduced consumption of Internet child exploitation and the associated traumatisation of abused victims. Read moreRead less
ARC Research Network for a Secure Australia. The Research Network for a Secure Australia (RNSA) is a multi-disciplinary collaboration established to strengthen Australia's research capacity for protecting critical infrastructure from natural or human-caused disasters including terrorist acts. The RNSA will facilitate a knowledge-sharing network for research organisations, government and the private sector to develop research tools and methods to mitigate emerging safety and security issues relat ....ARC Research Network for a Secure Australia. The Research Network for a Secure Australia (RNSA) is a multi-disciplinary collaboration established to strengthen Australia's research capacity for protecting critical infrastructure from natural or human-caused disasters including terrorist acts. The RNSA will facilitate a knowledge-sharing network for research organisations, government and the private sector to develop research tools and methods to mitigate emerging safety and security issues relating to critical infrastructure. World-leaders with extensive national and international linkages in relevant scientific, engineering and technological research will lead this collaboration. The RNSA will launch various activities to foster research collaboration and nurture young investigators.Read moreRead less
On-chip spectroscopy and hyperspectral imaging for remote environments. On-chip spectroscopy and hyperspectral imaging for remote environments. This project aims to investigate techniques and materials for building optical spectrometers based on micromachines, usable in portable ground-based and drone-mounted applications in remote environments. Optical spectroscopy is now an accepted technique for materials detection and analysis. The advent of low-cost drone aircraft makes the potential applic ....On-chip spectroscopy and hyperspectral imaging for remote environments. On-chip spectroscopy and hyperspectral imaging for remote environments. This project aims to investigate techniques and materials for building optical spectrometers based on micromachines, usable in portable ground-based and drone-mounted applications in remote environments. Optical spectroscopy is now an accepted technique for materials detection and analysis. The advent of low-cost drone aircraft makes the potential applications of spectroscopy in an imaging form immense. The project expects the resulting low-cost and highly portable technology will transform Australian industry, including securing Australia’s food supply by improving farming practices, aiding mineral exploration, and enhancing capabilities for monitoring Australia’s coastline.Read moreRead less
Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to bu ....Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to build practical mathematical models for droplet impaction, spreading and evaporation on leaf surfaces, and experimentally calibrate and validate the models. The software is expected to drive the development of agrichemical products that increase retention, minimise environmental impacts, and reduce costs for end-users.Read moreRead less