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Grant Award View - GA28342-V1
Sensor stream pattern mining for automatic anomaly recognition and...
GA ID:
GA28342-V1
Agency:
Australian Research Council
Approval Date:
27-Nov-2018
Variation Publish Date:
2-Aug-2021
Variation Date:
27-Jul-2021
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2019 to 31-Dec-2021
Value (AUD):
$386,897.50
(GST inclusive where applicable)
Varies:
GA28342
- Sensor stream pattern mining for automatic anomaly recognition and intervention
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 18/19 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Sensor stream pattern mining for automatic anomaly recognition and intervention
Purpose:
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.
GO ID:
GO Title:
Discovery Projects commencing in 2019
Internal Reference ID:
DP19 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
Deakin University
Recipient ABN:
56 721 584 203
Grant Recipient Location
Suburb:
GEELONG
Town/City:
GEELONG
Postcode:
3220
State/Territory:
VIC
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
VIC
Postcode:
3220
Country:
AUSTRALIA