<?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/87358316-9F23-41A2-876A-C42260650C9C" ns1:id="87358316-9F23-41A2-876A-C42260650C9C"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/A49E2D90-5300-425B-B820-C838A88E9D88" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/2FDB052A-9A6D-41D0-9A36-A84F7804139C" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/2FDB052A-9A6D-41D0-9A36-A84F7804139C" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-10-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/0A792957-F5CF-44A7-A734-0BD0FD8295DF" ns1:rel="FUND" ns1:start="2020-04-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">58392</ns2:identifier></ns2:identifiers><ns2:title>Real time measurement of UK Rail Passengers to enable social distancing during a pandemic</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>The UK is currently experiencing severe disruption due to the Covid-19 lockdown, and ending the lockdown in a controlled way is vital to the UK's economic future. Public transport is critical to getting key workers to their jobs as well as for the wider UK economy to function efficiently.

However, given the requirements under social distancing, the overcrowding of people on public transport could lead to faster transmission of Covid-19 leading to a potential second wave or aiding a future outbreak.

RazorSecure provides cyber security intrusion and anomaly detection using machine learning to give real time visibility of networks onboard UK trains.

We propose to extend the data we currently collect and produce new visualisations to give real time data regarding overcrowding of public transport to allow for more active management of social distancing while transiting the UK transport network. As a direct, actionable item, guards would be given an application that will allow them to inform passengers that a particular carriage is less crowded and operators would have a real-time dashboard to review crowding.</ns2:abstractText></ns2:project>