Stony Brook University researchers are teaching AI how to sort your recycling

Recycling facilities sort and process recyclable materials such as plastic, glass, and paper, then sell them to manufacturers for new products. When unrecyclable items like grease-soaked pizza boxes are mixed in, the contamination can lead to whole batches being rejected and sent to landfills. Large landfills threaten environmental and human health, and the US generates substantial waste per person. Researchers at Stony Brook University are developing an AI-assisted system to analyze and characterize municipal solid waste with greater speed and scale than traditional methods. The project relies on collaboration with local materials recovery facilities, using low-cost cameras to capture video and audio data for training AI algorithms. National efforts increasingly use AI to streamline recycling and improve waste management systems.

"A pizza box can feel like a recycling pop quiz. It's cardboard, but there's also the greasy bottom and cheese residue. Should the box go into the blue recycling bin or into the trash? The wrong decision may seem like a harmless toss, but it can have serious consequences ones that technologists are hoping artificial intelligence can remedy."

"Recycling facilities, or materials recovery facilities, sort and process recyclable materials such as plastic, glass, and paper, which are then sold to manufacturers to create new products. However, if an unrecyclable item, like the grease-soaked pizza box, gets mixed in with the other valuable materials, the whole batch can be rejected and sent to a landfill."

"Large landfills threaten the environment and human health, and the US is among the world's largest per-person generators of waste. At Stony Brook University, researchers are exploring AI as part of the solution by developing an AI-assisted system to analyze and characterize municipal solid waste with far greater speed and scale than traditional methods."

"Without the collaboration from local facilities, it is impossible to conduct this type of research, because that data is essential for developing artificial intelligence algorithms. During these site visits, Qin and her team used low-cost cameras, such as GoPros, to capture video and audio."

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