IPSE project aims at improving the efficiency of plastic waste sorting through the integration of artificial intelligence and eco-design. The project focuses on enhancing the detection of impurities on sorting conveyor belts in sorting implants, collaborating with Corepla, Seruso, and WiSort, entities involved in plastic waste management.
Currently, plastic sorting involves both automated systems and manual sorting, with automated systems mainly utilizing Near Infrared (NIR) technology to identify polymers and colors. Given the limitations posed by NIR implementation, manual intervention is still needed. However, manual sorting is labor-intensive and prone to errors. The IPSE project seeks to develop an improved detection system for sorting impurities, integrating cameras and machine learning algorithms for enhanced sorting accuracy in the output flow.
The final goal is to improve sorting performance which is crucial for improving recycling rates inserted in the EU Targets for 2030. Furthermore, improving the purity of the output flows avoids the imposition of monetary sanctions. Economic evaluations predict that the system could reduce costs and enhance efficiency in plastic sorting plants by optimizing human labor and minimizing errors. Ultimately, the project aims to support a circular economy by improving recycling efficiency and sustainability practices through innovation in AI-based sorting technologies.