Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP190100587
Funding Status
Active
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Funded Activity Summary
Sensor stream pattern mining for automatic anomaly recognition and intervention. This project will develop a general framework of accurate automatic recognition of meaningful anomalies in multivariate sensor data streams that require action to avoid detrimental events and allow automatic intervention for efficient mitigation. Existing anomaly recognition algorithms miss many patterns and manually relating co-occurring stream patterns to an anomaly is inefficient and error-prone. The project expects to develop methods for intercepting a combination of co-occurring patterns to ascertain what an anomaly is and identify the anomaly and its stages that indicate the necessity of intervention. This project will advance techniques for sensor stream data mining and enable general applications of sensor surveillance and automatic mechanical intervention.Funded Activity Details
Start Date: 2019
End Date: 12-2023
Funding Scheme: Discovery Projects
Funding Amount: $351,725.00
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) | Electronic Information Storage and Retrieval Services |
