AI4Fibres – Artificial Intelligence for Textile and Fibres Recycling

人工智能驱动的布料回收通过再利用和回收纺织品来减少时尚产业对环境的影响，最大限度地减少资源消耗、水污染和温室气体排放。此外，它还有助于减少纺织品浪费，这是全球关注的一个重大问题。人工智能技术可以有效地分类和处理纺织废料，提高回收率，减少垃圾填埋场。此外，它通过重复使用纤维而不是从头开始生产新的纺织品来节省宝贵的资源，如水、能源和原材料，从而最大限度地减少对原始资源的依赖。此外，它通过在纺织品回收中建立新的产业和就业岗位创造了经济机会。它还通过结合人工智能算法、机器学习和机器人技术，推动创新和技术进步。有人声称，在自动化纺织品回收过程中最困难的问题之一是拉链和纽扣的去除。因此，纺织废料必须按照适用的用户要求进行扫描和分类。我们的主要重点领域是设计、开发和制造一种自动化的人工智能纺织品分拣机，它可以处理大量的纺织品流量，并检测纺织品成分（棉花、聚酯等）的百分比，这些百分比比今天的人工分拣更适合不同的回收过程。拟议的项目是开发和创建一个人工智能支持的半自动纺织品回收框架，并提供实验室演示，同时提供一个小型机器原型，可以根据衣物的成分检测和分类，并去除拉链等不需要的特征。作为AI4FIBRES项目的一部分，将计划和实施许多用例和试点，以证明拟议的框架和机器每周处理多达10吨旧衣服的潜力。机器学习和计算机视觉系统用于纺织品分析、分类和分割，使用基于多光谱相机的架构，将集成到我们提出的平台中。总体目的是进一步实现纺织品分析过程的自动化，减少每单位的预期处理时间、总体成本和增加处理项目的数量。因此，对许多家庭、当地社区或市镇以及总体环境的影响是巨大的。AI4FIBRES将为设计和评估先进的新型人工智能和计算机视觉解决方案提供支持，用于纺织品和织物分类，减少错误。此外，将使用高光谱传感器收集数据，旨在改进人工智能解决方案，并提供自动化纺织品加工平台。

AI-powered cloth recycling reduces the environmental impact of the fashion industry by reusing and recycling textiles, minimizing resource depletion, water pollution, and greenhouse gas emissions. Moreover, it helps reduce textile waste, which is a significant global concern. AI technologies can effectively sort and process textile waste, increasing recycling rates and reduce landfills. Also, it conserves valuable resources like water, energy, and raw materials by reusing fibers instead of producing new textiles from scratch minimizing reliance on virgin resources. Additionally, it creates economic opportunities by establishing new industries and job roles in textile recycling. It also drives innovation and technological advancement by combining AI algorithms, machine learning, and robotics.It has been claimed that one of the most difficult issues in the automated textile recycling process is the removal of zips and buttons. As a result, textile waste must be scanned and sorted in accordance with the applicable user requirements. Our main areas of focus is to design, develop and build an automated AI-powered textile sorting machine that makes it possible to handle large textile flows and detect textile composition (cotton, poly, etc.) percentages that are better adapted to different recycling processes than today's manual sorting.The proposed project is to develop and create an AI-enabled semi-automated textiles recycling framework, as well as to provide lab demonstrations accompanied by a small-scale machine prototype that can detect and classify clothing based on their compositions and remove undesired features such as zippers. As part of the AI4FIBRES project, many use cases and pilots will be planned and conducted to demonstrate the proposed framework and machine's potential to handle up to 10 tonnes of used clothing each week. The machine learning and computer vision system for textile analysis, classification, and segmentation using a multispectral camera-based architecture, will be integrated into our proposed platform.The overall purpose is to further automate the process of textile analysis reducing the expected processing time per unit, the overall cost and increase the volume of processing items. As a result the impact to many families, local communities or boroughs and the general environmental impact is high and significant. AI4FIBRES will offer support on designing and evaluating advanced novel AI and computer vision solution for textile and fabric classification reducing the errors. Additionally data will be collected using hyperspectral sensors aiming to improve the AI solutions and offer an automated textile processing platform.