Zori Tex: reducing the environmental impact of the fashion industry
Authors/Creators
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University of Exeter
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Science and Technology Facilities Council
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The Alan Turing Institute
Description
This case study is published under the InnovateUK BridgeAI - Bespoke AI and Data Science Advice for SMEs offer. The Alan Turing Institute Independent Scientific Advisors (ISAs) offer transformative support to SMEs across BridgeAI sectors, enabling them to harness AI for both practical and strategic benefits. This initiative is supported by Innovate UK BridgeAI.
We thank gratitude to Alexandra Harrod, CEO, and Dominic Waithe, Lead Engineer at Zori Tex, as well as Dr. Andrew Corbett, Independent Scientific Advisor for BridgeAI based at The Alan Turing Institute, and Megan Yates, Impact Evidence and Evaluation Manager at Hartree Centre for their significant contributions to the development of this case study.
Special thanks to Alexandra Araujo Alvarez, Senior Research Community Manager for BridgeAI, Dominica D'Arcangelo, Programme Manager, and Punita Maisuria, Project Coordinator, for their leadership and support. We also acknowledge Stuart Gillespie for his role as the technical writer for this and other case studies in the programme. Additional thanks go to Aida Mehonic, Principal Researcher for Research Applications from The Alan Turing Institute for her reviews and feedback.
This work is led by Dr. Vera Matser, Head of Skills and Principal Investigator for BridgeAI at The Alan Turing Institute.
For any comments, questions, or collaboration opportunities with BridgeAI, please email: bridgeAI@turing.ac.uk.
Abstract
Reducing the environmental impact of the fashion industry The fashion industry is hugely resource intensive. While estimates vary, it is thought the sector contributes at least 4% of global greenhouse gas emissions. To compound matters, efforts to recycle clothing are hampered by the difficulty of accurately identifying fibre composition: more
than 40% of garments are thought to be incorrectly labelled, and traditional manual or laboratory-based methods of classifying and sorting are either too time-consuming or economically unviable. Only around 1% of the millions of tonnes of clothing that make it to the market each year are recycled into new clothing –the rest goes to landfill or incineration.
Zori Tex, a startup founded in 2022 by former fashion and textiles leader Alexandra Harrod, is using cutting-edge machine vision and AI techniques – and deep sector knowledge – to optimise the sorting of used textiles, enabling old, worn-out clothing to be turned into new, usable materials at scale.
Zori Tex’s textile analysis system uses an infrared hyperspectral camera to measure the absorbance and reflection of light within certain wavelengths. The company’s bespoke machine learning algorithm then delves into its extensive training to identify the composition of fibres – at better-than-human performance – readying the materials
for fibre-to-fibre recycling.
Files
Zori Tex Case Study.pdf
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Additional details
Biodiversity
- Catalog number
- ATI Publications 1