AI Vision Helps Green Recycling Plants
Each year, the world recycles only around 13% of its two billion-plus tons of municipal waste. By 2050, the world’s annual municipal waste will reach 3.88B tons.
But the global recycling industry is far from efficient. Annually, as much as $120B of potentially recoverable plastic—let alone paper or metals—ends up in landfills rather than within new products made with recycled materials.
A UK-based startup,
Greyparrot
, has developed a small, AI-powered device offering “waste intelligence,” and aims to help recycling plants become more efficient and environmentally friendly.
The sleek, two-foot-square device—dubbed the Greyparrot Analyzer—uses embedded cameras to identify and differentiate among materials on conveyor belts running through recycling plants.
The analyzer—using a machine learning, object detection model (ODM)—is attached to, and helps retrofit recycling plants’ infrastructure. Trained on tens of millions of waste images, the ODM takes less than 60 milliseconds to capture and analyze images of quickly-moving waste.
The analyzer’s ODM, which was trained on-premise and in the cloud using
NVIDIA H100 Tensor Core GPUs
,
NVIDIA L4 Tensor Core GPUs
, as well as PyTorch and
NVIDIA CUDA-X
libraries, can identify roughly 90 different types of materials. Each analyzer, which weighs around 40 pounds, is also powered by an
NVIDIA GeForce RTX 4060 GPU
.
In 2024, Greyparrot analyzed more than 40 billion waste objects across its worldwide facilities. Armed with this “waste intelligence,” operations managers use the data for two primary purposes.
First, plant operators get real-time and longitudinal analytical insights into how effectively their facility separates and creates homogenous piles of recyclable materials—like paper, metals, and plastics. Creating purer collections of recyclable materials, which are then sold to product manufacturers, is a key component of the world’s $1.3T recycling industry.
A second use case for the data—or really, the ODM—is to supplement the operating systems of robotic arms that are deployed within facilities to sort different types of waste. The arms communicate with the ODM to help them more accurately sort materials.
“A recycling plant’s job is to turn what we discard, and never think of again, back into virgin material that can be recycled to make more of those same things,” said James Paterson, Greyparrot’s vice president of engineering. “We’re constantly tackling throughput and quality, so recycling facilities can process more waste, and still end up with more purified products.”
Figure 1. Greyparrot’s analyzer system sits above conveyor belts in recycling facilities and provides real-time as well as longitudinal data insights to improve efficiency
Recycling plants deploying the analyzer also use it as something of a trip wire.
It’s not uncommon, for instance, for one component of a sorting facility to jam. When that happens, different materials can get mixed together, or end up inadvertently getting thrown out rather than being readied for recycling.
With the analyzer’s ODM, sorting errors—triggered by unanticipated jams—are quickly identified and relayed to operators, who can quickly intervene. Without the ODM, it might take hours for facilities to identify a mechanical mishap.
“You can imagine in a big facility with a lot of machines, it may take three to four hours for someone to notice a machine is jammed,” said Paterson. “And then someone looks and sees there are all these valuable aluminum cans [incorrectly] getting thrown out, and they say, ‘Oh my god. The system is down. We better check the machines.’ And that’s money that’s literally going down the drain and into landfills.”
The five-year-old London-based startup—which is part of the
NVIDIA Inception Program
— operates in more than 55 recycling facilities across 20 different countries. With about 50 full-time employees, primarily in the UK and US, but also in Spain, Italy, and The Netherlands, Greyparrot is expanding its global presence.
In early 2024, the Dutch recycling firm Bollegraaf Group, the world’s largest recycling plant builder, agreed to integrate Greyparrot’s technology into its new facilities.
As more state-of-the-art facilities integrate AI into their waste analytics and robotic capabilities, Greyparrot anticipates the analyzer will help improve operational performance and improve recycling yields at scale.
Read more about Greyparrot’s
recycling efforts
and its relationship with iconic product designer, Tony Fadell.
There’s
additional
reporting on Greyparrot’s efforts to bring AI to the world’s recycling industry.
AI 视觉技术助力绿色回收工厂智能化
全球每年仅回收约 13% 的 20 多亿吨城市垃圾。到 2050 年，全球每年的城市废弃物量将达到 3.88 亿吨。
但全球回收行业的效率远远不够。每年，价值高达 120 亿美元的可回收塑料 (更不用说纸张或金属了) 最终进入垃圾填埋场，而不是使用回收材料制造的新产品。
英国的初创公司
Greyparrot
开发了一款由 AI 驱动的小型设备，可提供“废弃物智能”功能，旨在帮助回收工厂变得更高效、更环保。
这款名为 Greyparrot Analyzer 的两英尺方形时尚设备使用嵌入式摄像头来识别和区分流经回收工厂的传送带上的材料。
该分析器使用机器学习物体检测模型（ODM）连接到回收工厂，并帮助改造其基础设施。ODM 根据数千万张废弃物图像进行训练，捕获和分析快速废弃物图像只需不到 60 毫秒。
分析器的 ODM 使用
NVIDIA H100 Tensor Core GPU
、
NVIDIA L4 Tensor Core GPU
以及 PyTorch 和
NVIDIA CUDA-X
库在本地和云端进行训练，可以识别大约 90 种不同类型的材料。每台重约 40 磅的分析器也由
NVIDIA GeForce RTX 4060 GPU
提供支持。
2024 年，Greyparrot 分析了其全球设施中超过 40 亿个废弃物。借助这种“废弃物情报”，运营经理可以将数据用于两个主要目的。
首先，工厂操作人员可以获得实时的纵向分析见解，了解其设施分离和生成同质可回收材料（如纸张、金属和塑料）的效率。打造更纯净的可回收材料系列，然后将其出售给产品制造商，这是全球价值 1.3 万亿美元的回收行业的重要组成部分。
数据（实际上是 ODM）的第二个用例是补充部署在设施内的机械臂操作系统，以分类不同类型的废弃物。手臂与 ODM 通信，帮助他们更准确地分类材质。
Greyparrot 工程副总裁 James Paterson 表示：“回收工厂的工作是将我们丢弃且永远不会想到的东西重新转化为可以回收的原生材料，以制造更多类似的东西。”我们在不断提高吞吐量和质量，因此回收设施可以处理更多的废弃物，最终仍能获得更多的净化产品。”
图 1、Greyparrot 的分析系统位于回收设施的传送带上方，可提供实时和纵向数据洞察，从而提高效率
部署分析器的回收工厂也将其用作触发器。
例如，分拣设施的一个组件卡死的情况并不少见。当这种情况发生时，不同的材料可能会混合在一起，或者最终在无意中被丢弃，无法准备回收。
借助分析器的 ODM，可快速识别由意外的卡阻引发的分拣错误并将其转发给操作员，以便操作员快速干预。如果没有 ODM，设施可能需要数小时才能识别机械事故。
Paterson 说：“可以想象，在拥有大量机器的大型设施中，人们可能需要 3 到 4 个小时才能注意到机器卡住了。”“然后有人看了看，发现有很多有价值的铝罐【错误】被丢弃，他们说，‘天哪，我的天哪。系统机了。我们最好检查机器。“这笔钱实际上会流入垃圾填埋场。”
这家成立五年的初创公司位于伦敦，是
NVIDIA Inception Program
的一部分，在 20 个不同国家地区的超过 55 家回收设施中运营。Greyparrot 拥有大约 50 名全职员工，主要分布在英国，也分布在西班牙、意大利和荷兰，正在扩展其全球业务。
2024 年初，全球最大的回收工厂制造商荷兰回收公司 Bollegraaf Group 同意将 Greyparrot 的技术整合到其新设施中。
随着越来越多的先进设施将 AI 集成到其垃圾分析和机器人功能中，Greyparrot 预计该分析器将有助于提高运营性能并大规模提高回收产量。
详细了解 Greyparrot 的
回收工作
及其与标志性产品设计师 Tony Fadell 的关系。
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