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

Authors :
Manakkakudy, Anju
De Iacovo, Andrea
Maiorana, Emanuele
Mitri, Federica
Colace, Lorenzo
Source :
Sensors (14248220). Feb2024, Vol. 24 Issue 3, p809. 13p.
Publication Year :
2024

Abstract

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
3
Database :
Academic Search Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
175390511
Full Text :
https://doi.org/10.3390/s24030809