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Field of Research : Distributed Computing
Field of Research : Mobile Technologies
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP210100337

    Funder
    Australian Research Council
    Funding Amount
    $459,593.00
    Summary
    Robust and Scalable Autonomous Landing for Drones. The aim of this project is to develop a transformative robust and scalable autonomous landing system for drones. This is the critical missing technology needed to unleash exponential growth in a potentially enormous drone delivery industry by enabling a multitude of applications to deliver goods and supplies via drones to a wide range of destinations in Australia and the world in a timely, flexible and accurate manner. Such an autonomous landi .... Robust and Scalable Autonomous Landing for Drones. The aim of this project is to develop a transformative robust and scalable autonomous landing system for drones. This is the critical missing technology needed to unleash exponential growth in a potentially enormous drone delivery industry by enabling a multitude of applications to deliver goods and supplies via drones to a wide range of destinations in Australia and the world in a timely, flexible and accurate manner. Such an autonomous landing solution would revolutionise drone technology, and propel Australia to the forefront of technology innovation. This project would benefit not only large scale delivery by drone in urban and suburban areas of Australia but also long distance delivery via drone to remote areas of Australia.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220102520

    Funder
    Australian Research Council
    Funding Amount
    $405,000.00
    Summary
    Betrayed by Apps: Automated, Scalable Detection of Mobile App Malpractices. This project aims to develop a novel framework to detect content and privacy malpractices perpetrated by thousands of mobile apps. It will use innovative models and algorithms to achieve unprecedented levels of automation and scalability, making it possible for the first time to identify compliance violations across the global app ecosystem. Outcomes will include a knowledge base of prevalent app malpractices, detection .... Betrayed by Apps: Automated, Scalable Detection of Mobile App Malpractices. This project aims to develop a novel framework to detect content and privacy malpractices perpetrated by thousands of mobile apps. It will use innovative models and algorithms to achieve unprecedented levels of automation and scalability, making it possible for the first time to identify compliance violations across the global app ecosystem. Outcomes will include a knowledge base of prevalent app malpractices, detection algorithms, and a software framework for scalable app analysis. New evidence and tools will benefit both Australian and global policymakers and regulators in combating malpractices, users in identifying safe mobile apps for themselves, and local and global app market stakeholders in being more diligent about compliance.
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