<?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/F662E794-7A78-4EDB-A883-29F3EC80B2B3" ns1:id="F662E794-7A78-4EDB-A883-29F3EC80B2B3"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/C7974068-4419-4806-8E05-AB4E7F9C7BFB" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B1D2E606-AA45-414B-A63D-26FA2EE39C46" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B1D2E606-AA45-414B-A63D-26FA2EE39C46" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/47AC5C0C-6553-4E0E-B591-65899B6059E4" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/50EDDEAD-DEDC-44BE-9C6F-FED498224FA2" ns1:rel="FUND" ns1:start="2018-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">104160</ns2:identifier></ns2:identifiers><ns2:title>QV2 - Feasibility of commercialising QT microgravity sensors in non-utility markets</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>&amp;quot;QV2 is a continuation of the InnovateUK funded QVision project (132541) which investigated the feasibility of commercialising microgravity QT devices in the utility market sector when integrated with the OXEMS system. QVision, almost complete, has been successful and includes proposed new layered data and associated ROI models using Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate the surveying process and deliver enhanced value for utilities.

QV2 is a feasibility study to continue investigating the market potential for microgravity QT devices but to broaden the future market focus from utilities to all other markets that have a need to survey underground structures. Moreover, QV2 will develop novel inversion techniques based on numerical modelling combined with machine learning to help with the location of buried features, while also investigating the potential of obtaining condition information. QV2 is a collaboration between OXEMS and the University of Birmingham (UoB) which will provide access to the QT-Hub in Sensors and Metrology led by the UoB. The overall aim is to generate a comprehensive understanding of the potential future market for QT microgravity sensors in the UK and overseas.&amp;quot;</ns2:abstractText></ns2:project>