<?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/9D77CD1E-858F-4707-9E4E-CDD2F516B362" ns1:id="9D77CD1E-858F-4707-9E4E-CDD2F516B362"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/F7B6254D-4A67-4D9C-8667-C75B8193D639" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/19116CBD-91FB-4E0E-869C-47A764E8DB05" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/19116CBD-91FB-4E0E-869C-47A764E8DB05" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8E278C23-52CF-4158-9E0E-368CCAD0A858" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-08-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/57173E85-6D77-4029-AF0A-CB21BFE842BC" ns1:rel="FUND" ns1:start="2025-04-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10157253</ns2:identifier></ns2:identifiers><ns2:title>ODIN - Optimisation and Diagnostics for Innovative Networks</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The ODIN Project aims to develop automated methods for interpreting and diagnosing data collected from continuous monitoring of robots operating in high-voltage direct current halls. By leveraging modern advanced analytics, including machine learning and artificial intelligence, the Project will transition from the current labour-intensive process of manual data assessment, which lacks trend analysis for comparing against normal operating conditions. Through the application of artificial intelligence and machine learning, ODIN will uncover novel insights into high-voltage direct current asset behaviour, thereby improving operational efficiency, reliability and resilience to support the transition to a net-zero energy network.</ns2:abstractText></ns2:project>