Towards a Greener Future: Sensor-Based Material Characterization in Waste Sorting for a Sustainable Recycling Model

Waste sorting is a vital part of the circular economy.The issue of waste sorting is very complex in terms of detecting individual types of waste, with the aim of recycling and using them in new products. This paper investigates the efficient sorting of metals, plastics, and glass through the application of three distinct sensors—inductive, photoelectric, and capacitive sensors—with the objective of enhancing the recycling process for these materials. Our aim is evaluation of an experimental platform for automatic material sorting, emphasizing reliability, speed, and precision, in order to streamline the recycling process and diminish reliance on manual labor.As a pivotal component of this platform, we incorporated an FPGA Cyclone IV to facilitate decision-making derived from the sensors regarding the sorting of materials. Examining the outcomes of material classification and sorting under various conditions, it is evident that the sorting accuracy circa 90%. Expectations indicate that the deployment of this system will streamline the efficient sorting of metals, plastics, and glass in the recycling process, playing a substantial role in environmental conservation and promoting sustainability within the recycling industry.