<?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/0AC8DC6B-7E59-422F-B389-3E198014175E" ns1:id="0AC8DC6B-7E59-422F-B389-3E198014175E"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/317E01FA-849A-4C60-BFFD-D9B0E24FE3FE" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/F22AF067-996B-4105-9094-12E1AB7C7845" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/F22AF067-996B-4105-9094-12E1AB7C7845" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2022-06-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/157860EA-D26D-447D-81C1-9334062CA539" ns1:rel="FUND" ns1:start="2020-04-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">971724</ns2:identifier></ns2:identifiers><ns2:title>Detection and deterrence of tresspass with advanced AI controller.</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Small Business Research Initiative</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Edge based trespass detection software for the detection of individuals trespassing, fare evasion and causing criminal damage; such as graffiti. Deterrence through responses tailored to the individual and the nature of the trespass. The solution reduces false positives through the use of convolutional neural nets for object classification and scene context to determine behaviour. The solution is low cost, can accept a wide range of sensors and is capable of operating at sites without mains power or WiFi.</ns2:abstractText></ns2:project>