Optimization leads to a much more granular sort. Whereas conventional optical sorters accurately identify and sort aluminum from the material stream, “trained deep learning systems take the next step to detect and sort items like used beverage containers (UBC) from other aluminum in the stream,” Rhoad explains. “Deep learning enables recyclers to selectively target a specific value stream and increase purity of that product.”
Rhoad is optimistic about the industry's future with deep learning and sees several areas where AI can play a part in improving the sort. “We’ve already launched applications like wood sorting for TOMRA’s deep learning based GAIN and will soon have an application that focuses on the aforementioned UBC cleaning. We also see value for the industry with PET cleaning and the ability to detect PET food grade containers from the material stream.”
Because of its ability to be trained to see objects on the belt like a human sorter, AI’s deep learning technology, when combined with conventional sorting technologies, can bring final product qualities and yield to the next level. Because deep learning is application specific, however, recyclers need to work with a trusted technology supplier to ensure that they get the most out of it.