Measure recyclable resources in the waste industry to meet the foundational industries demands for recycled material using AI for tracking SKU
使用 AI 跟踪 SKU 测量废物行业中的可回收资源,以满足基础行业对回收材料的需求
基本信息
- 批准号:10028681
- 负责人:
- 金额:$ 104.76万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Investment Accelerator
- 财政年份:2022
- 资助国家:英国
- 起止时间:2022 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The foundation industries (plastics and chemical industry, paper, metal etc.) use large volumes of virgin feedstock in the manufacture of packaging. Substitution of part of this feedstock by recycled waste packaging is reducing this demand, save money, the energy used in processing by 75%, and greenhouse gas emissions by up to 2148 kgCO2e/t. Accelerating this shift is pressure towards sustainable packaging that contains sufficient recycled content, and regulation; the UK government is introducing a tax on packaging that doesn't contain 30% or more recycled content. Thus, the demand for recycled material is inexorably increasing. However, the low recycling rate (predicted to be 13% by 2040, while quantity of plastic waste will double) due to inefficient, inaccurate (manual) auditing and processing, driven by a lack of data, thus inhibiting the effective sorting of waste, limits our ability to feed the industry with enough reclaimed material. There is an urgent need to decrease the stress on new resources by leveraging the value of waste. To achieve this, transparency/accountability across the product life cycle need to be established and the only way to do it is to digitise the industry, providing it with the necessary data. Across all sorts of materials - plastics, paper, glass, metals and others - recycling systems spanning producers, recyclers, and foundational industries could be far more efficient when powered by data:more effective sorting, data-driven optimisation decisions, enforcement of regulation, better policy decisions guided by data. This project aims to build on Greyparrot's existing AI vision technology which is a novel, affordable system that uses state-of-the-art approaches in AI-computer vision to accurately identify and classify in real-time product packaging/waste at a brand/SKU level, recognising and tracking these all along the sorting process across different sorting lines, informing on whether each one is correctly being recycled or not. Although securing strong interest (with ongoing trials in MRFs) the technology is limited in terms of number (100s) and type (plastic) of SKUs being currently recognised. This project will significantly scale-up this solution through hardware and software development allowing for the recognition of a representative market share (70% of PET/HDPE main SKUs, main non-plastic packaging ones), helping to hold producers accountable for poor packaging design, enabling intelligent sorting and policy makers/waste managers to take informed decisions to adapt and improve regulations and processes, increasing the percentage of packaging being effectively recycled and going back into the manufacturing process in foundational industry.Thanks to this project and through larger scale hardware deployment and data gathering and processing, Greyparrot will increase the speed of product development, moving toward a shorter timeline for the product to reach the market and start having an impact on the foundational industry and other stakeholders.
基础工业(塑料和化学工业、造纸、金属等)在包装制造中使用大量的原始原料。用回收的废弃包装替代部分原料,减少了这一需求,节省了资金,加工中使用的能源减少了75%,温室气体排放量高达2148 kgCO 2 e/t。加速这一转变的是对含有足够回收成分的可持续包装的压力和监管;英国政府正在对不含30%或更多回收成分的包装征税。因此,对回收材料的需求正在无情地增加。然而,由于缺乏数据导致的低效、不准确(人工)审计和处理,回收率较低(预计到2040年将达到13%,而塑料废物的数量将翻一番),从而抑制了废物的有效分类,限制了我们为行业提供足够再生材料的能力。迫切需要通过利用废物的价值来减少对新资源的压力。 为了实现这一目标,需要在整个产品生命周期内建立透明度/问责制,唯一的方法是将行业数字化,为其提供必要的数据。在各种材料中-塑料,纸张,玻璃,金属等-跨越生产商,回收商和基础行业的回收系统在由数据驱动时可能会更有效:更有效的分类,数据驱动的优化决策,监管的执行,更好的政策决策由数据指导。 该项目旨在建立在Greyparrot现有的人工智能视觉技术基础上,该技术是一种新颖的,负担得起的系统,使用人工智能计算机视觉中最先进的方法,在品牌/包装级别实时准确识别和分类产品包装/废物,识别和跟踪这些所有沿着不同分拣线的分拣过程,告知每个人是否正确回收。虽然获得了强烈的兴趣(正在进行的MRF试验),但该技术在目前认可的SKU数量(100个)和类型(塑料)方面受到限制。 该项目将通过硬件和软件开发显著扩大该解决方案,从而获得具有代表性的市场份额(占PET/HDPE主要SKU的70%,主要非塑料包装),有助于让生产商对不良包装设计负责,使智能分拣和决策者/废物管理者能够做出明智的决定,以适应和改进法规和流程,提高包装被有效回收并重新进入基础行业制造过程的百分比。由于这个项目,通过更大规模的硬件部署和数据收集和处理,Greyprotor将提高产品开发的速度,缩短产品进入市场的时间轴,并开始对基础行业和其他利益相关者产生影响。
项目成果
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
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LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
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2021 - 期刊:
- 影响因子:0
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吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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{{ truncateString('', 18)}}的其他基金
An implantable biosensor microsystem for real-time measurement of circulating biomarkers
用于实时测量循环生物标志物的植入式生物传感器微系统
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2901954 - 财政年份:2028
- 资助金额:
$ 104.76万 - 项目类别:
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Exploiting the polysaccharide breakdown capacity of the human gut microbiome to develop environmentally sustainable dishwashing solutions
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$ 104.76万 - 项目类别:
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- 资助金额:
$ 104.76万 - 项目类别:
Studentship
Likelihood and impact of severe space weather events on the resilience of nuclear power and safeguards monitoring.
严重空间天气事件对核电和保障监督的恢复力的可能性和影响。
- 批准号:
2908918 - 财政年份:2027
- 资助金额:
$ 104.76万 - 项目类别:
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Proton, alpha and gamma irradiation assisted stress corrosion cracking: understanding the fuel-stainless steel interface
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- 批准号:
2908693 - 财政年份:2027
- 资助金额:
$ 104.76万 - 项目类别:
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Field Assisted Sintering of Nuclear Fuel Simulants
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2908917 - 财政年份:2027
- 资助金额:
$ 104.76万 - 项目类别:
Studentship
Assessment of new fatigue capable titanium alloys for aerospace applications
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- 批准号:
2879438 - 财政年份:2027
- 资助金额:
$ 104.76万 - 项目类别:
Studentship
Developing a 3D printed skin model using a Dextran - Collagen hydrogel to analyse the cellular and epigenetic effects of interleukin-17 inhibitors in
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- 资助金额:
$ 104.76万 - 项目类别:
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CDT 第 1 年,预计 2024 年 10 月
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- 资助金额:
$ 104.76万 - 项目类别:
Studentship
Understanding the interplay between the gut microbiome, behavior and urbanisation in wild birds
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- 批准号:
2876993 - 财政年份:2027
- 资助金额:
$ 104.76万 - 项目类别:
Studentship
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