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Sustainability
Today’s sustainability challenges are complex and evolving. To address them we urgently need brave thinking that will drive action for a new economy - one where business, people and planet thrive.
AI in the plastic waste management system
AI models can analyze spectral data to classify plastics accurately, distinguishing monolayer from multilayer materials and identifying additives or contaminants. Such information is essential to ensure that the recyclates meet quality standards, such as food-grade recycling requirements, and prevent downcycling (converted waste into products of lower quality or value).
Computer vision-powered robots deployed at recycling facilities can identify, sort, and separate plastics by type, improving recycling efficiency and reducing contamination. Many waste management plants in Europe, for example, are using such robots.
When plastic waste is sorted with the help of AI, correctly identified plastics can undergo tailored processing steps such as washing, shredding, and separation by density and thickness, making them ready for remelting or chemical recycling. Smart recycling technologies chemically break down plastics into molecular feedstocks, producing virgin-quality resin identical to that made from fossil fuels. This molecular recycling addresses plastics that are difficult to recycle mechanically, such as mixed or contaminated waste, enabling a closed-loop system. AI’s role is critical in appropriate recycling of plastic, as it can reduce the plastic waste burden on landfills.
AI-driven material innovation can be a game-changer for recycling plastic. Machine learning models can design biodegradable or recyclable alternatives to traditional plastics by predicting material properties and performance before synthesis. AI can also simulate and predict the best pathways to reuse plastic waste in local or global supply chains, supporting extended producer responsibility (EPR) schemes. Monitoring corporate compliance with plastic regulations through image recognition, blockchain-integrated tracking, and satellite monitoring are some other ways AI can make a big impact. Satellite and drone imagery analysis using AI models can help analyze remote sensing data to identify and track plastic waste in oceans, rivers, and landfills.