<?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/730E4BFB-2136-4DB9-A2C2-E2C27553F93E" ns1:id="730E4BFB-2136-4DB9-A2C2-E2C27553F93E"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/2FACCDFF-78C1-4F26-9D15-3A4F8DF8D9D8" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/4A786E88-8AC9-4245-AD75-EB52C6AB4414" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/2FACCDFF-78C1-4F26-9D15-3A4F8DF8D9D8" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/15B9E8A6-BB18-48B9-A6A6-C6A17D568414" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FF0624DD-85A5-4439-98FA-AE0FA6BA88F6" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/C9C07DD7-9B1A-41FA-87D3-0B48518876A3" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2009-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/1200FED6-F385-449E-A782-62EFA8BC73CE" ns1:rel="FUND" ns1:start="2007-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">100027</ns2:identifier></ns2:identifiers><ns2:title>Energy Conservation through Resource literacy and Intelligent Systems (ECRIS)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The ECRIS project will deliver the first high-performance behavioural energy-efficiency platform for reducing energy wastage in buildings. This will be commercialised as flexible, user friendly controls and displays backed by novel agent-based inferencing and learning systems to help users make energy-saving decisions. These decisions involve day-to-day energy use and investment in energy efficiency measures. This will lead to an estimated 25% net energy saving, almost twice the performance of competitive product. The principal innovations in this project are the development of agent-based technologies and best practice energy communications design to drive energy efficiency.</ns2:abstractText></ns2:project>