Cloudiness over the Southern Ocean: reducing a key knowledge gap and source of climate model uncertainty. Southern Ocean clouds are key ingredients of the global climate system and yet are only poorly understood and poorly represented in climate models. Through the use of advanced observational analysis techniques this research will provide a deep understanding of key Southern Ocean cloud regimes and improve their representation in models.
The Southern Ocean boundary layer: winds, turbulence, sea spray and clouds. Both satellite products and climate models have large biases in the energy and water budgets over the Southern Ocean (SO). This is a direct consequence of a poor understanding of the structure and dynamics of the SO atmospheric boundary layer, which has arisen from an inability to make the necessary observations in this harsh environment. Due to the availability of new Australian research infrastructure, large steps forw ....The Southern Ocean boundary layer: winds, turbulence, sea spray and clouds. Both satellite products and climate models have large biases in the energy and water budgets over the Southern Ocean (SO). This is a direct consequence of a poor understanding of the structure and dynamics of the SO atmospheric boundary layer, which has arisen from an inability to make the necessary observations in this harsh environment. Due to the availability of new Australian research infrastructure, large steps forward are now possible with modest investment. This project will conduct and combine observations from the recently acquired marine vessel, RV Investigator, and the collocated airborne and surface observations to understand the structure and evolution of the unique, pristine SO boundary layer and to evaluate satellites and climate models.Read moreRead less
GBR as a significant source of climatically relevant aerosol particles. Every cloud drop is formed from a microscopic aerosol particle, known as a cloud condensation nuclei (CCN). In unpolluted environments the CCN particles originate from biogenic sources. Determining the magnitude and driving factors of biogenic aerosol production in different ecosystems is crucial to the development and improvement of climate models. This project aims to determine the mechanisms of new particle production fro ....GBR as a significant source of climatically relevant aerosol particles. Every cloud drop is formed from a microscopic aerosol particle, known as a cloud condensation nuclei (CCN). In unpolluted environments the CCN particles originate from biogenic sources. Determining the magnitude and driving factors of biogenic aerosol production in different ecosystems is crucial to the development and improvement of climate models. This project aims to determine the mechanisms of new particle production from one of the biggest ecosystems in Australia, the Great Barrier Reef. It is expected that the project will establish whether marine aerosol along the Queensland coast is coral-derived and show that this aerosol can affect the CCN concentration and therefore cloud formation and the hydrological cycle.Read moreRead less
SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the infor ....SenShaMart: A Trusted Internet of Things Marketplace for Sensor Sharing. This project aims to devise a novel Internet of Things (IoT) sensor sharing marketplace that permits IoT applications to discover, integrate, and pay for any IoT sensor data that is made available by other parties. The project will devise highly-scalable sensor classification, query processing, and transactions solutions and incorporate them in a pair of novel blockchains that work in tandem to securely manage all the information and contracts needed by IoT applications to discover, integrate, pay, and use sensors provided by another parties. These IoT advancements will provide significant economic, environmental, and social benefits via making low-cost and immediate sensing available across the world.Read moreRead less
Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge compu ....Reliable and Seamless Service Provisioning in Mobile Edge Computing . This project aims to develop enabling technologies to provide reliable and seamless services in mobile edge computing environments. This project will develop advanced algorithms with performance guarantees and efficient mechanisms for such service provisioning. The project expects to lay theoretical foundations and generate new knowledge for the provisioning of reliability-aware and mobility-aware services in mobile edge computing. The expected outcome of the project is a set of solutions to the myriad of services relying on mobile edge computing including e-Health, autonomous vehicles, and Internet of Things. This project will develop key fundamental technologies to improve Australia’s standing in the international research community.
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Service Provisioning for the Internet of Things in Mobile Edge Computing. This project aims to develop a suite of novel algorithms and enabling technologies for service provisioning of the Internet of Things (IoT) applications in mobile edge computing (MEC). This project will develop performance-guaranteed algorithms and core technologies for IoT service provisioning through effective cost modelling. The project expects to lay theoretical foundations, discover key principles and generate new kno ....Service Provisioning for the Internet of Things in Mobile Edge Computing. This project aims to develop a suite of novel algorithms and enabling technologies for service provisioning of the Internet of Things (IoT) applications in mobile edge computing (MEC). This project will develop performance-guaranteed algorithms and core technologies for IoT service provisioning through effective cost modelling. The project expects to lay theoretical foundations, discover key principles and generate new knowledge for IoT service provisioning in MEC. The expected outcome of the project is a suite of solutions to the myriad of IoT services in MEC including e-Health and autonomous vehicles. This project should also develop key fundamental technologies to improve Australia's standing in the international research community.Read moreRead less
Flying networks: airborne sensing for environmental monitoring and disaster response. Airborne sensing technology is ideally suited to Australian geography and can be highly effective for monitoring disasters, surveillance, and precision agriculture. There are ample opportunities for local information technology companies and start-ups to create innovative airborne sensing applications for both the Australian and overseas markets.
Affective sensing technology for the detection and monitoring of depression and melancholia. This project will develop reliable and affective sensing technology and evaluate it as an objective measure of depressive disorders; a leading cause of disability worldwide. Outcomes will significantly support and aid clinicians in their diagnosis and treatment, thus providing a major breakthrough with significant research, healthcare and commercial possibilities.
Generative Visual Pre-training on Unlabelled Big Data. This project aims to develop a generative visual pre-training of large-scale deep neural networks on unlabelled big data. Developing pre-trained visual models that are accurate, robust, and efficient for downstream tasks is a keystone of modern computer vision, but it poses challenges and knowledge gaps to existing unsupervised representation learning. Expected outcomes include new theories and algorithms for unsupervised visual pre-training ....Generative Visual Pre-training on Unlabelled Big Data. This project aims to develop a generative visual pre-training of large-scale deep neural networks on unlabelled big data. Developing pre-trained visual models that are accurate, robust, and efficient for downstream tasks is a keystone of modern computer vision, but it poses challenges and knowledge gaps to existing unsupervised representation learning. Expected outcomes include new theories and algorithms for unsupervised visual pre-training, which are anticipated to deepen our understanding of visual representation and make it easier to build and deploy computer vision applications and services. Examples of benefits include modernising machines in manufacturing and farming with visual intelligence. Read moreRead less
Software-defined provisioning of Internet of Things applications in fog computing systems. This project aims to investigate and provide solutions for the realisation of a seemingly integrated Fog Computing (FC) paradigm with cloud environments, networking devices and Internet of Things devices. Fog Computing (FC) is an emerging paradigm with great promises for advancing Information and Communications Technologies. Using interdisciplinary approaches, the project expects to generate new knowledge ....Software-defined provisioning of Internet of Things applications in fog computing systems. This project aims to investigate and provide solutions for the realisation of a seemingly integrated Fog Computing (FC) paradigm with cloud environments, networking devices and Internet of Things devices. Fog Computing (FC) is an emerging paradigm with great promises for advancing Information and Communications Technologies. Using interdisciplinary approaches, the project expects to generate new knowledge for optimising both hardware and software resources of a FC system. Outcomes of this project include practical solutions through building novel mathematical frameworks and optimisation objectives. The project is expected to provide efficient monitoring and control of intelligent spaces, management of urban and rural environments and will have applications in the areas of energy, security, transport and public health.Read moreRead less