<?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/80584572-6835-41BF-A19A-F72D9B210BA3" ns1:id="80584572-6835-41BF-A19A-F72D9B210BA3"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/7554EA10-093F-461C-B622-905FC11F6EC5" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/139BFFC7-EE3F-4010-956C-85147D198324" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/139BFFC7-EE3F-4010-956C-85147D198324" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2020-12-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/A874E417-C666-4C87-AE11-ED579913A55C" ns1:rel="FUND" ns1:start="2020-09-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">77814</ns2:identifier></ns2:identifiers><ns2:title>Project ADER (Automated Detection, Ejection &amp;amp; Recovery)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Small Business Research Initiative</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Project ADER (**A**utomated **D**etection, **E**jection &amp;amp; **R**ecovery) delivers a turnkey waste sorting solution that outperforms the current state-of-the art in recycling technology. ADER utilises cutting-edge computer vision algorithms and a novel air jet ejection system sorting to a higher granularity, speed, and greater affordability than ever possible before. ADER's eyes, combining near-infra-red (NIR) and advanced computer vision algorithms, provide the speed and accuracy of NIR with the granularity and knowledge of the Recycleye AI Vision system. The ejection system, cuts down space, reduces cost, and can sort into more categories than existing NIR machines (10+ vs 2-3). This project is led by Recycleye, a world-leading company in smart AI systems for the waste industry. Recycleye's first product line radically innovated waste detection by leveraging advanced proprietary computer vision algorithms spun-out of PhD research at Imperial College London. At Recycleye we believe waste does not exist -- only material in the wrong place. Project ADER is formed from Recycleye's team of technologists, each with years of industry experience delivering radical new innovations. There are no subcontractors as part of the project as the Recycleye team is perfectly placed to pioneer the next breakthrough for the industry. ADER's development is in two Phases: Phase 1 feasibility studies focus on validating the radical innovation of combining NIR sensors with Recycleye Vision and the novel ADER ejection system. Phase 2 involves data acquisition, further software development, prototype build and industrial testing. This culminates in the production of a commercial system that brings together newly developed IP, harnessing novel technological development to benefit waste facilities in the UK and abroad. _Enhancing the benefits and value of our natural resources_ is the main theme of this project supporting the UK's Clean Growth Strategies, working towards achieving zero avoidable waste by 2050\. Project ADER contributes to this by enabling sorting of entirely new waste materials, increased granularity (sort food-grade vs non-food-grade material) and a radically cheaper system. By optimising the waste industry and improving the recycling rate of materials, ADER is accelerating the UK's transition to a circular economy.</ns2:abstractText></ns2:project>