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Scheme : Linkage Projects
Field of Research : Stochastic Analysis and Modelling
Australian State/Territory : ACT
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  • Funded Activity

    Linkage Projects - Grant ID: LP160101202

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    Predictive analytics from at home telemonitoring of vital signs. Predictive analytics from at home telemonitoring of vital signs. This project aims to reduce unscheduled admissions to hospital, by developing statistical models of people’s health using longitudinal measurements of vital signs and questionnaires. Hospital costs are becoming unsustainable and will overwhelm state budgets within thirty years. Telehealth monitoring to manage chronic disease is becoming increasingly routine internatio .... Predictive analytics from at home telemonitoring of vital signs. Predictive analytics from at home telemonitoring of vital signs. This project aims to reduce unscheduled admissions to hospital, by developing statistical models of people’s health using longitudinal measurements of vital signs and questionnaires. Hospital costs are becoming unsustainable and will overwhelm state budgets within thirty years. Telehealth monitoring to manage chronic disease is becoming increasingly routine internationally and should reduce unnecessary hospital admissions and health service costs. To scale up telehealth services nationally, automated means of assessing changes in an individual health status are needed. This project’s automated risk assessment models are expected to identify exacerbations and orchestrate an optimal response from health services to reduce unscheduled admissions to hospital.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP210301239

    Funder
    Australian Research Council
    Funding Amount
    $537,675.00
    Summary
    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).
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    Active Funded Activity

    Linkage Projects - Grant ID: LP170100985

    Funder
    Australian Research Council
    Funding Amount
    $711,000.00
    Summary
    Enabling three dimensional stochastic geological modelling. This project aims to develop technologies to mitigate three dimensional (3D) geological risk in resources management. This project expects to create new knowledge and methods in the field of 3D geological modelling through the innovative application of mathematical methods, structural geology concepts and probabilistic programming. The expected outcomes are an enhanced capability to model the subsurface, characterise model uncertainty a .... Enabling three dimensional stochastic geological modelling. This project aims to develop technologies to mitigate three dimensional (3D) geological risk in resources management. This project expects to create new knowledge and methods in the field of 3D geological modelling through the innovative application of mathematical methods, structural geology concepts and probabilistic programming. The expected outcomes are an enhanced capability to model the subsurface, characterise model uncertainty and test multiple geological scenarios. This enhanced capability is important for the future of Australia's subsurface management, including urban geology and our continuously growing sustainable resources industry.
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