<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/C2BF0A22-EDBA-422D-B98F-F7CB9D8822C4" ns1:id="C2BF0A22-EDBA-422D-B98F-F7CB9D8822C4"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/A3BED823-3256-487A-8D00-940A23BC3ABF" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DA2A8E23-6006-4E83-9DEA-143B392B5073" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/DA2A8E23-6006-4E83-9DEA-143B392B5073" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8BF4C919-F61A-4423-B4E3-57C1F9E280E9" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2014-01-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/322D0C3A-AF33-49A1-A108-FED92B079353" ns1:rel="FUND" ns1:start="2013-02-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">131011</ns2:identifier></ns2:identifiers><ns2:title>Monitoring asset performance with AURAalert</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The benefits of installing on-line asset monitoring systems cannot be fully realised without the development of novel, analytical tools which can extract knowledge across multiple, archived and large time-based data sources. 
During this project, Cybula, an SME focusing on the development of large data analytics, together with Sim-Soft, an SME offering pipeline detection monitoring services to the oil &amp;amp; gas industry, propose to further develop and test AURAalert, novel abnormality detection software. This tool provides alerting of abnormal behaviour of complex systems by comparing against a large, reference data store. The technique can be used across a range of assets but in this proposal, the aim is to provide the enhanced alerting performance being demanded by pipeline operators. Data from a number of Sim-Soft’s existing installations will be used for this study.</ns2:abstractText></ns2:project>