AI Helping Recycling Industry Improve Accuracy, Speed Sorting Rate
AI is helping the recycling industry improve the accuracy of identifying specific types of plastics and other materials, including items contaminated with food and other substances, as well as speed up the sorting rate.
Smart robots, sensors and vision systems fortified with machine learning software are creeping into production at recycling facilities in Colorado, Japan and Europe.
Here are two companies talking up the potential to make the act of processing everything from plastic to demolished construction materials far more efficient and scalable, according to an account in GreenBiz: five-year-old startup AMP Robotics, a machine learning and computer vision specialist headquartered in Louisville, Colorado; and a Norwegian company, TOMRA, which got its start managing reverse vending machines that uses sensors to endow its food sorting and recycling systems with more intelligence.
A New Vision for Sorting
As its name suggests, AMP Robotics’ innovations lie in how it’s rethinking recycling robots. Founder and CEO Matanya Horowitz began receiving grants back in 2014 to research and develop vision systems that could improve the accuracy of separating items with machines rather than by humans. The company’s equipment is “trained” by being shown millions of images — everything from logos to box shapes to dyed plastics.
“If you can teach a person to distinguish something, you can teach our vision system to distinguish it,” said Horowitz to GreenBiz.
The idea, he said, is to help facilities become far more specific about separating streams of waste, which could allow operations to capture revenue from entirely new sorts of services.
For example, the technology — using a combination of light and machine learning software — could be used to sort out colored whipped cream tubs or yogurt containers from clear plastics. It can even identify items that carry a specific brand logo. One early adopter, Alpine Recyling in Colorado, recently was able to add coffee cups to the mix of stuff that its facility can handle. These levels of specificity could be valuable for consumer products companies seeking either to put their own product packaging back into circulation or to buy specific types of plastics.
“We can track what is truly being recycled,” Horowitz added, and that could help provide insight into where better collection systems — and messaging — might be needed.
AMP’s latest technology is a dual-robot system called Cortex, which the 35-person company will sell for municipal solid waste, electronic waste and construction and demolition applications. The equipment can sort, pick and place items at a speed of 160 pieces per minute. More important, it will allow facilities to tackle a process that typically has been very difficult to scale — separating post-consumer fiber from cardboard to sheets of paper.
Horowitz is cagey about how much money his company has raised, although its backers include Closed Loop Partners, and he called out the Alphabet company Sidewalk Labs during our conversation. Likewise, he won’t talk about the cost of his firm’s technology, pointing out that customers are seeing a payback of less than two years and that it sorts at the rate of two people.
That latter statistic might give pause to those concerned about the job-elimination potential of robotics technology, but Horowitz says recycling facilities often have high rates of turnover. “Many facilities are run underutilized,” he said.
AMP Robotics is also touting applications in the construction sector. Earlier this year, it disclosed a partnership with Japanese waste management company Ryohshin to sell AI-driven robots for recovering materials out of demolition debris — including wood, metal, electronics and concrete.