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ImprovinG waste management through an AI-powered detection system of batteries utilising data from X- Ray detectors and pick-and-place robots

ImprovinG waste management through an AI-powered detection system of batteries utilising data from X- Ray detectors and pick-and-place robots
通过人工智能驱动的电池检测系统利用 X 射线探测器和拾放机器人的数据来改善废物管理
批准号:
10042345
负责人:
金额:
$50.06万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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中文摘要
翻译
WEEE(来自电气和电子设备的废物)管理链已经实现了火灾事件的爆炸,这是由于不小心丢弃的电池被扔进回收箱或黑色垃圾袋,它们很容易被分类设备损坏并开始燃烧,危及人类生命,扰乱废物处理服务,造成数百万欧元的损失(每次火灾事故从19万欧元到130万欧元不等)。Grinner项目旨在将一种自主的人工智能机器人分拣系统商业化,该系统能够在当前的废物流中检测并移除含有电池的废物,然后将其放入粉碎和整合废物的机器中。该系统将包括(i)市场上最快的能量分辨x射线探测器,(ii)一个支持机器学习的软件模块,该软件模块将分析x射线数据,并在通过废物流时有效地检测含有电池的废物,以及基于视觉的拾取机器人(s),该机器人将移除标记的报废电子电气设备。项目目标:•建立报废电子电气设备x射线数据集。•开发人工智能软件模块,用于使用x射线数据检测WEEE中的电池。•在WEEE设施环境中开发、集成和安装原型系统,进行现场试验并验证Grinner。•探索Grinner作为一种经济可行的、独立的回收设施产品的潜在开发。
英文摘要
The WEEE (waste from electrical and electronic equipment) management chain has realised an explosion of fire incidences, caused by carelessly discarded batteries into either recycling bins or black rubbish bags, where they are easily damaged by sorting equipment and start to burn, endangering human lives, disrupting waste services and causing millions of Euros of damage (from €190,000 up to €1.3m per fire incident). The Grinner project aims at commercialising an autonomous AI-enabled robotic sorting system capable of detecting and removing waste containing batteries from current waste streams before they enter inhospitable-to-battery machines that crush and consolidate waste. The system will comprise (i) the fastest Energy-resolved X-Ray detectors in the market, (ii) an ML-enabled software module that will analyse X-Ray data and effectively detect waste containing batteries while passing through the waste flow and vision-based pick-and-place robot(s) that will remove the flagged WEEE. Project objectives: • Build an X-Ray data set of WEEE scrap. • Customisation of the X-Ray system • Develop the AI software module for detection of batteries within WEEE using X-Ray data. • Deploy a vision-based robotic solution capable of Picking-and-Placing WEEE • Develop, integrate and install a prototype system in a WEEE facility environment to conduct live trials and validate Grinner. • Explore the potential exploitation of Grinner as an economically viable, stand-alone product for recycling facilities.
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