<?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/4587ACE2-52CE-4B60-8EDC-A997ED0BED04" ns1:id="4587ACE2-52CE-4B60-8EDC-A997ED0BED04"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/CD1D8C7F-69D3-4DBF-81CE-FABBFFF93628" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/56B62DA4-E3A8-4D75-92EE-70FE09026F1D" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/56B62DA4-E3A8-4D75-92EE-70FE09026F1D" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/D8AFD58B-618B-4AE6-B1CC-B93EBF10ABAA" ns1:rel="FUND" ns1:start="2020-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">60564</ns2:identifier></ns2:identifiers><ns2:title>Covid-19 eHealth Data Acquisition Unit (COVeHealth)</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 in &amp;quot;lock down&amp;quot; due to the novel coronavirus pandemic. Before putting the currently locked down country back to work we need to:

1) Reduce the incidence of cases to reduce the burden on the NHS to more normal levels

2) Once that is achieved, we need to prevent the virus from catching fire a second time

To reduce the risk of a second wave, we need to develop tools to enable us to:

a) Preemptively identify early stage Covid-19 sufferers

b) Use these tools to guard the borders of spaces (hospitals, homes, shops, workplaces, shopping malls, schools, universities etc.)

The World Health Organization's message is that we must **&amp;quot;Find, isolate, test and treat every case to break the chains of Covid transmission.&amp;quot;**

Covid-19 screening tests are currently performed at a modest distance by a health worker using a &amp;quot;no touch&amp;quot; infrared thermometer to detect the tell tale fever. The other common symptom indicative of Covid-19 is the persistent dry cough, detected by the characteristic sound.

What is desperately needed, both in the UK and around the World, is a way of performing screening for early stage Covid-19 symptoms remotely.

With DfT seed funding V2G EVSE have developed a low cost &amp;quot;smart&amp;quot; 0G to 5G enabled communications controller with a wide range of input/output, currently configured to monitor and control an electric vehicle charging station and securely communicate with a cloud based management system.

We will repurpose our existing technology by connecting the controller to a microphone and infra-red camera, then use novel machine learning algorithms to detect the characteristic cough and fever of Covid-19 sufferers. This will allow us to create an installed or hand held device that can be used to identify those with potential Covid-19 symptoms.

Since our existing hardware is effectively the internals of a smartphone with no touch screen but more versatile communications, including Bluetooth, we are also ideally placed to participate in the recently announced Apple/Google track/trace initiative.

The COVeHealth project will develop proof of concept prototypes of a &amp;quot;commercial&amp;quot; version suitable for use at the entrance to public spaces and an alternative low-cost &amp;quot;domestic&amp;quot; version for use hand held or in confined spaces.</ns2:abstractText></ns2:project>