<?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/CE49F090-0B0A-42F2-BE01-A6CA75994FA1" ns1:id="CE49F090-0B0A-42F2-BE01-A6CA75994FA1"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/9B1E5005-F9FC-47DF-B773-7E363C136D0D" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/7B69186F-6058-4950-86CE-C2B46E367819" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/7B69186F-6058-4950-86CE-C2B46E367819" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/E2405B36-DC91-41AB-8F68-B7F879C75719" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-04-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/DA321135-370F-448F-91BB-3FD8E7E14F28" ns1:rel="FUND" ns1:start="2022-02-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10020954</ns2:identifier></ns2:identifiers><ns2:title>Plastic packaging, a complete recognition and monitoring system based on AI and fusing RGB-based computer vision with Near Infrared spectral Imaging (NIR SI)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>By 2040, c.3billion tons of waste will be produced globally, with plastic waste doubling to 430million tons. It is predicted that only 13% will be recycled due to inefficient, inaccurate (manual) auditing and processing, driven by a lack of data, thus inhibiting the effective sorting of waste. Sorters using Near InfraRed (NIR) cameras, in place today, provide a partial solution; however they are extremely expensive (&amp;pound;200k-&amp;pound;300k/unit), and technically limited (NIR vision is unable to differentiate all types of waste), meaning plastics packaging recovery/recycling rates are significantly lower than current UK Plastics Pact targets (c.50% in 2019, WRAP-2020 vs. 70%-target).

To address the challenge, Greyparrot (GP) in collaboration with Blue Green Vision (BGV) are developing a hybrid waste recognition and monitoring system to complement and enhance NIR sorting machines, and tackle the lack of accurate data with a holistic approach. The system will combine Greyparrot's AI-based technology using RGB cameras (Red-Green-Blue i.e.human vision) with BGV's high-speed point-to-point NIR system (5-10x cheaper than current hyperspectral NIR cameras) to provide automated, cost-effective, accurate recognition of plastics waste (with transferability to all waste types) at-scale. Critically, the system will enable the identification of all types of material and packaging, e.g including black plastics or Polyethylene terephthalate (PET) bottles with a Low-Density Polyethylene (LDPE) sleeve, not currently recognised/sorted by existing NIR systems. By providing accurate and real-time data required to improve processes in the plant, and integrating the proposed system to enhance sorting machines, the partners anticipate a conservative 5% increase in plastics recovery rates; making a significant contribution towards delivering the 3rd target of the UK Plastics Pact.

The unique waste recognition and monitoring system will enable waste companies to accurately and comprehensively audit waste at-scale, critical to meeting strict Extended Producer Responsibility (EPR) legislation set to take effect in 2023,(with which samples will be required as often as every 8 tonnes against every 125 tonnes currently) providing greater accountability and increased recycling rates. This project will be a catalyst to deliver such a service. In addition, the system will support new approaches to carry out a global optimisation of entire plants instead of local optimisations in singular sorters, leading to better recovery rates in all waste categories and helping to build a stronger UK recycling system.</ns2:abstractText></ns2:project>