<?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/4583FC78-9377-427B-84F7-2BE5A2C91B1E" ns1:id="4583FC78-9377-427B-84F7-2BE5A2C91B1E"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/1114D7AF-9F53-4B4E-88F5-D2CC0CA2C024" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/40BC7FF5-35D2-4361-8BFE-BC8A68C064C0" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/A7732051-99B7-4924-8F32-0CD929BFCE01" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/E3EA4A20-0F16-477D-94AA-3C7229C26DD6" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/387EE37F-97CC-4D8D-AD05-8971F42884FD" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/40BC7FF5-35D2-4361-8BFE-BC8A68C064C0" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2018-06-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/09D6547D-8AB1-457F-9499-7A50AEA49306" ns1:rel="FUND" ns1:start="2015-03-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">102083</ns2:identifier></ns2:identifiers><ns2:title>Cow Health Monitor</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>There are considerable animal health challenges in modern dairy farming, all with a profound impact on production output and efficiency. The early detection of metabolic diseases such ketosis, acidosis and lameness and intervention at the pre-clinical stage provides valuable information upon which the farmer can decide on the most appropriate interventions. Thus the project will integrate a number of new dairy livestock sensing systems in real-time, including animal-mounted and product in-line monitoring, to provide a robust decision support system for metabolic disease detection at pre-clinical stages. The solution will be capable of integration within existing technologies on commercial farms to enhance the value of the farmer's investment, and the information presented to the livestock-keepers will be in an easily accessible and digestible fashion delivered over multiple channels viz. smartphones, tablets or PCs.</ns2:abstractText></ns2:project>