Waste Material Classification: A Short-Wave Infrared Discrete-Light-Source Approach Based on Light-Emitting Diodes

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 3; p. 809
• Main Authors: Manakkakudy, Anju, De Iacovo, Andrea, Maiorana, Emanuele, Mitri, Federica, Colace, Lorenzo
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 26.01.2024
• Subjects: Algorithms; Classification; discrete spectroscopy; Environmental monitoring; Feature selection; Light emitting diodes; material classification; Optical properties; optical sensor; Polyethylene terephthalate; Power electronics; Refuse and refuse disposal; Sensors; Spectrum analysis; SWIR; Waste management; Waste materials; material classification; SWIR; discrete spectroscopy; optical sensor; feature selection
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24030809

Waste material classification is a challenging yet important task in waste management. The realization of low-cost waste classification systems and methods is critical to meet the ever-increasing demand for efficient waste management and recycling. In this paper, we demonstrate a simple, compact and low-cost classification system based on optical reflectance measurements in the short-wave infrared for the segregation of waste materials such as plastics, paper, glass, and aluminium. The system comprises a small set of LEDs and one single broadband photodetector. All devices are controlled through low-cost and low-power electronics, and data are gathered and managed via a computer interface. The proposed system reaches accuracy levels as high as 94.3% when considering seven distinct materials and 97.0% when excluding the most difficult to classify, thus representing a valuable proof-of-concept for future system developments.