As explained by ResearchGate in the study “Optimization of recyclable materials collection on conveyor belts”, recycling facilities face challenges in efficiently separating materials as they move rapidly along conveyors. A significant percentage of items pass through without immediate collection, impacting profitability and sustainability. Researchers addressed this issue by introducing robotic arms enhanced with artificial intelligence for smarter sorting.
The system predicts material types — such as paper, plastic, or aluminum — using Hidden Markov Models, then applies reinforcement learning to decide collection priorities based on market value. This approach increases accuracy, reduces waste, and maximizes profitability.
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Article with all rights reserved, courtesy of ResearchGate — https://www.researchgate.net/