The Carton Council, an association dedicated to improving the recovery and recycling of food and beverage cartons, has launched a new initiative to help AI-powered sorting systems more reliably identify cartons moving through MRFs. The North America-based association has created a pilot library of photographs showing cartons as they actually appear in the recycling stream – partially folded, torn, discolored, or otherwise altered through collection, compaction, transportation, and processing.
Computer vision and AI-based material recognition systems can identify objects traveling across MRF conveyor belts based on characteristics learned from large collections of images. The quality and diversity of those training images plays an important role in how reliably the technology recognizes materials under real-world operating conditions. By photographing cartons from MRF recycling streams, the Carton Council aims to give technology providers access to training data that represents real-world conditions.
“As AI solutions become more widely integrated by MRFs to identify and sort recyclable materials, we want to make sure cartons are accurately represented in the data these systems learn from,” said Jason Pelz, VP of Recycling, Carton Council. “The Carton Council has been a longtime supporter of utilizing near-infrared (NIR) optical sorting technology and other advanced sorting tools to recover cartons. Helping emerging AI systems accurately identify and sort cartons is a natural extension of that work.”
“Our goal has always been to work across the recycling system to improve carton recovery,” adds Jordan Fengel, President, Carton Council. “Technology continues to evolve, but our role remains the same: helping MRFs and their equipment partners have the tools and information they need to sort cartons efficiently and effectively to get more of them to end markets for recycling.”
