an official journal of: published by:
Editor in Chief: RAFFAELLO COSSU


  • Giuseppe Bonifazi - Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, Italy - Research Center for Biophotonics, Sapienza University of Rome, Italy
  • Riccardo Gasbarrone - Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, Italy
  • Roberta Palmieri - Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, Italy
  • Silvia Serranti - Department of Chemical Engineering, Materials and Environment, Sapienza University of Rome, Italy - Research Center for Biophotonics, Sapienza University of Rome, Italy

DOI 10.31025/2611-4135/2020.14031

Released under CC BY-NC-ND

Copyright: © 2019 CISA Publisher

Editorial History

  • Received: 21 Nov 2019
  • Revised: 31 Jul 2020
  • Accepted: 31 Jul 2020
  • Available online: 30 Nov 2020


The number of flat monitors from televisions, notebooks and tablets has increased dramatically in recent years, thus resulting in a corresponding rise in Waste from Electrical and Electronic Equipment (WEEE). This fact is linked to the production of new high-performance electronic devices. Taking into account a future volume growth trend of WEEE, the implementation of adequate recycling architectures embedding recognition/classification logics to handle the collected WEEE physical-chemical attributes, is thus necessary. These integrated hardware and software architectures should be efficient, reliable, low cost, and capable of performing detection/control actions to assess: i) WEEE composition and ii) physical-chemical attributes of the resulting recovered flow streams. This information is fundamental in setting up and implementing appropriate recycling actions. In this study, a hierarchical classification modelling approach, based on Near InfraRed (NIR) - Hyperspectral Imaging (HSI), was carried out. More in detail, a 3-step hierarchical modelling procedure was designed, implemented and set up in order to recognize different materials present in a specific WEEE stream: End-of-Life (EoL) shredded monitors and flat screens. By adopting the proposed approach, different categories are correctly recognized. The results obtained showed how the proposed approach not only allows the set up of a “one shot” quality control system, but also contributes towards improving the sorting process.



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