<?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="2026-08-26T13:36:10Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/8E2600C4-88CF-4462-872A-37E79883CFC5" ns1:id="8E2600C4-88CF-4462-872A-37E79883CFC5"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/72B2CE4F-686E-4B0B-8904-3669259635A6" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/58EE5D30-F5D1-4217-9FAB-D3E946D26372" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/58EE5D30-F5D1-4217-9FAB-D3E946D26372" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-04-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/9A5E4E6B-B68A-48A6-8E35-71CC340C48BF" ns1:rel="FUND" ns1:start="2022-11-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10043984</ns2:identifier></ns2:identifiers><ns2:title>TranzGreen- An AI-enabled Data-driven Application for the Delivery and Courier Industry</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>This is the **first-of-its-kind** application to track delivery drivers' carbon footprints and make precise recommendations to reduce them. Furthermore, the application follows up with delivery drivers until a net zero is achieved. Our goal-based incentive motivates them to reduce their carbon footprint in their day-to-day operations.

Because a substantial amount of emissions come from delivery drivers in supplier chains, our application focuses on delivery drivers' emissions that can be reduced from the **total supply chain's emissions**.

&amp;quot;TranzGreen&amp;quot; simply measure each delivery driver's contribution to the specific supply chain's emissions. Then, based on their scenario, our system generates emission-cutting recommendations. The advice differs for each delivery driver because it is generated based on their situation (i.e., personalised recommendation). As a result, this is incredibly efficient, and delivery drivers can lower their emissions by following the application's recommendations.

Our application contributes to the UK government's objective of reaching net zero emissions by 2050\. Also, help taxpayers reduce their carbon footprint and help them make significant changes for themselves and their families.</ns2:abstractText></ns2:project>