<?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="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/4A52D38F-2CDE-4794-B628-4CE6BBC13422" ns1:id="4A52D38F-2CDE-4794-B628-4CE6BBC13422"><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/73A6FEC1-7E3C-4E50-8997-A11CB8649C85" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/1098BB84-D8AA-43F4-B77D-C842123F849C" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2017-06-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/4BE2C78A-4E32-427F-95BA-3A43BDD152AB" ns1:rel="FUND" ns1:start="2016-03-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">132195</ns2:identifier></ns2:identifiers><ns2:title>ICOMP DM - data mining for interactive components in the built environment</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Condition based maintenance is the future of mechanical equipment management, providing a step change in efficiency and reliability throughout asset life. Systematic approaches to data capture (e.g. temperature, vibration by retrofitted sensor networks) from M&amp;amp;E assets in public/commercial buildings have been proposed. However, whilst data can be captured, providing a means of immediately identifying component failure, we need a better understanding of relationships between changing sensor data patterns and asset performance to quantify rates of degradation and predict timescales for asset failure. The project will look to exploit this opportunity by bringing innovative data analysis techniques derived from other sectors (e.g. nuclear, medicine) to the built environment. Building on the analysis of data being captured from sensors fitted to M&amp;amp;E assets at Skanska-managed facilities it will assess the feasibility of, and develop a plan for creating, a commercial, cost effective data analysis system for the built environment.</ns2:abstractText></ns2:project>