Classification of polymers using artificial intelligence and efficient imaging

The CLAIRE project arises from the need to improve the classification processes of recycled plastics, one of the main limitations to achieving more efficient, sustainable, and higher-quality recycling. The presence of impurities and the difficulty in differentiating certain polymers reduce the value of recycled material and generate significant economic and environmental losses in treatment plants.

To address this issue, the project proposes the development of Artificial Intelligence models capable of analyzing terahertz hyperspectral images to classify polymers and detect impurities under real industrial conditions. The methodology includes the preparation of representative samples, the acquisition of hyperspectral images, advanced data preprocessing to select relevant bands, and the training of AI algorithms aimed at estimating the purity of recycled material.

CLAIRE aims to contribute significantly to improving efficiency in recycling processes, making them more sustainable, efficient, and better adapted to the current needs of the circular economy.

Likewise, the project seeks to increase the quality of recycled material, reduce the presence of impurities, and promote more sustainable and environmentally efficient circular economy models.

CLAIRE is being developed through a collaboration between the Universitat Politècnica de València (UPV) and the Universidad Carlos III de Madrid (UC3M), with the participation of the Computer Vision and Behaviour Analysis Lab (CVBLAB), a multidisciplinary team with extensive experience in competitive projects and a strong background in Artificial Intelligence, optical sensors, and hyperspectral imaging.

The project builds on the consortium’s previous experience in initiatives related to AI applied to material analysis, computer vision, and advanced image acquisition and processing technologies.