<?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/537A54B0-5F7F-4EBF-8F66-D86448BBF61C" ns1:id="537A54B0-5F7F-4EBF-8F66-D86448BBF61C"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/27094A2C-6F2F-4EC0-9E83-38A1540897C6" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8B482E57-B52C-425F-A04D-68DEB48AE150" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8B482E57-B52C-425F-A04D-68DEB48AE150" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/73A03527-BD50-4AC5-9F6A-A82CE701E5A4" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-05-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/0660C24B-A7F1-42B0-A967-38949C4E19D5" ns1:rel="FUND" ns1:start="2018-08-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">104510</ns2:identifier></ns2:identifiers><ns2:title>Insights from Satellite Video using Artificial Intelligence</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>This project develops AI techniques to automatically extract insights from satellite video, together with complementary satellite and terrestrial data sets, for risk monitoring of complex construction project progress and critical global supply chain assets. By providing ongoing proactive change detection and analysis, these services will provide indicators and warnings to increase monitoring efficiencies and help reduce or prevent the significant costs associated with construction progress delays and asset failure, respectively.
Through this project Earth-i is developing advanced AI-based analytics using automated interpretation of satellite high definition video together with other correlative geospatial Earth Observation data including colour optical, infra-red and radar imagery, from a range of sources including satellite, drone, aerial and ground-based sensors. This data is fused with additional non-Earth Observation data sources, such as weather, news, activity, pollution and IoT sensors, to extract factual understanding and generate predictive and more accurate insights for businesses and government organisations within construction, supply chain management and infrastructure, on a global scale. 
 
Satellite video has the potential to provide unique insights to a wide range of customers as it offers improved and faster object recognition, more accurate 3D modelling, as well as enhanced change detection, object movement identification and analysis. This project will provide reusable techniques for satellite video, as well as multi-sensor and high-resolution earth observation still imagery data sets, that can also be adapted for further commercial applications in future.</ns2:abstractText></ns2:project>