Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP140100841
Funding Status
Closed
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Funded Activity Summary
Deep Data Mining for Anomaly Prediction from Sensor Data Streams. Sensor data streams are crucial for anomaly predictions in real-life monitoring. However, balancing efficiency and accuracy in predicting anomalies with sensor streams is a great challenge; it requires new techniques that go beyond detecting anomalies and predicting trends. This project will develop a deep mining method for anomaly prediction from sensor streams; it will comprise mining algorithms at various levels - from compressing massive raw data, to recognition of abnormal waveforms preceding anomalies, and to retrieving and summarising similar past anomalies for creating descriptions of future anomalies. The project will demonstrate our method in health/environment monitoring applications, and its adoption will save resources, money and lives.Funded Activity Details
Start Date: 2014
End Date: 08-2018
Funding Scheme: Discovery Projects
Funding Amount: $329,027.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Pattern Recognition and Data Mining | Artificial Intelligence and Image Processing
ANZSRC Socio-Economic Objective (SEO)
Information Processing Services (incl. Data Entry and Capture) |
