Adaptive data stream processing in heterogeneous distributed computing environments using real-time context. This project falls within the ARC research priority goal, Smart Information Use. The innovative contributions of this project through the development of adaptive data stream mining algorithms for heterogeneous devices will have an impact on a range of emerging application areas such as:
1. Meeting time-critical, intelligent information needs of the mobile workforce (e.g. mobile healthca ....Adaptive data stream processing in heterogeneous distributed computing environments using real-time context. This project falls within the ARC research priority goal, Smart Information Use. The innovative contributions of this project through the development of adaptive data stream mining algorithms for heterogeneous devices will have an impact on a range of emerging application areas such as:
1. Meeting time-critical, intelligent information needs of the mobile workforce (e.g. mobile healthcare professionals, stockbrokers). 2. Improving Intelligent Transportation Systems via in-vehicle analysis and crash prevention. 3. Facilitating 'on-board' analysis in sensors that monitor the environment and patients. The project will enhance Australia's leading international role in the area of data stream processing in distributed computing environments.Read moreRead less
Learned Academies Special Projects - Grant ID: LA170100025
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social med ....Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social media archives or financial records in ways that will shed new light on many complex research questions. This project will map existing capability and infrastructure within and across disciplines, identify common and discipline-specific practices, challenges and opportunities, and assess technology, infrastructure, training and collaboration priorities for Australia.
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