A fresh perspective on recycling technology emerges from the latest publication by the PLASTICE project, the result of a collaboration between researchers from CIRCE and URBASER: Pedro Compais, Belén Morales, Alberto Gala, and Marta Guerrero. This study, titled “The Integration of Image Intensity and Texture for the Estimation of Particle Mass in Sorting Processes”, offers a new method that could redefine mass estimation in recycling applications.
Published in Processes (2024), the research explores an innovative image-based approach using 2D cameras and machine learning to estimate the mass of low-density materials, such as post-consumer plastic films. By combining image intensity, texture, and size measurements, this method delivers a cost-effective solution to monitor mass flow—an essential metric in recycling facilities. Impressively, the results boast a minimal error margin of just 9 g for subsamples weighing between 2 and 82 g, challenging the need for costly sensor-based systems.
The study highlights how standard cameras can transform waste management, offering an accessible, low-cost alternative to improve recycling rates and operational efficiency.
You can access the full paper here to learn more about this innovative approach to advancing recycling technologies.
Cover image by Sasha Pestano on Unsplash.
