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Scheme : Linkage Projects
Research Topic : mab database
Australian State/Territory : SA
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  • Funded Activity

    Linkage Projects - Grant ID: LP100200114

    Funder
    Australian Research Council
    Funding Amount
    $230,000.00
    Summary
    Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the effici .... Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the efficiency and accuracy of product tracking in distribution networks. This project will place Australia at the forefront of RFID research. It will also be an excellent vehicle for educating young researchers and engineers in Australia.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP190100140

    Funder
    Australian Research Council
    Funding Amount
    $330,000.00
    Summary
    Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application .... Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.
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    Funded Activity

    Linkage Projects - Grant ID: LP110100166

    Funder
    Australian Research Council
    Funding Amount
    $163,332.00
    Summary
    Techniques for active conceptual modelling and guided data mining for rapid knowledge discovery. Quick, accurate responses to rapidly evolving phenomena are essential. This project will develop a platform able to accept data from a variety of sources in advance of the full definition of the associated conceptual model. The project will facilitate rapid querying and direct manipulation of the mining process allowing fast, user-oriented results.
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    Showing 1-3 of 3 Funded Activites

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