<?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="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/036AE817-3DCC-4BF8-937C-6E02C800B3EF" ns1:id="036AE817-3DCC-4BF8-937C-6E02C800B3EF"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/916BF2D6-E8EC-4285-AA2C-1BA13698239D" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/68270845-A0E9-479F-BAA6-1D62E26C4B9C" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/68270845-A0E9-479F-BAA6-1D62E26C4B9C" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-05-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/1DAA21BC-4F10-4508-9C9F-3C53CBECAA3F" ns1:rel="FUND" ns1:start="2020-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">971714</ns2:identifier></ns2:identifiers><ns2:title>Station Advanced Visual Sensing Of Risks (Station ADVISOR)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Small Business Research Initiative</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Station Advanced Visual Detection of Risks (Station ADVISOR)

The Station ADVISOR product will provide a scalable and cost-efficient, live station risk monitoring solution for use across the rail network, enabling station asset owners and operators to respond more proactively to risks, incidents and events in real time through visual analytics integrated with station surveillance systems.

Sensing Feeling delivers advanced human behaviour IoT sensing products powered by Computer Vision and Machine Learning. The company's products incorporate patent-pending sensing capability that performs automatic visual observation and analysis of human physical behaviours that can be used to reliably predict and detect high-risk situations relating to individuals or groups of people in real world conditions within safety-critical environments, entirely passively, in real-time, and at scale.</ns2:abstractText></ns2:project>