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Applicant:
Indian Institute of Technology (IIT) Patna 
Author:
Gundupalli, S.P., S. Hait and A. Thakur.  
Corresponding Authors:
A. Thakur 
DOI #:
https://doi.org/10.1016/j.psep.2018.06.022 
Title:
Classification of metallic and non-metallic fractions of ewaste using thermal imaging-based technique,  
Journal:
Process Safety and Environmental Protection (Elsevier),  
Year:
2018 
Volume:
118,  
Page:
32–39, 
Keywords:
E-waste, Recyclables, Material classification, Thermal imaging, Automated sorting, Recycling 
Abstract:
Electronic waste (e-waste) is generated at a rapid pace due to technological advancement and thereby reduced obsolescence age of electrical and electronic equipment (EEE). E-waste comprises of many use-ful recyclable materials such as metallic fractions (MFs), like aluminum and copper and non-metallic fractions (NMFs), such as plastic, printed circuit boards (PCB) and glass. Classification of MFs and NMFs from e-waste is of great significance from the viewpoint of recycling of materials and resource recovery.In this paper, we focus on the classification of MFs and NMFs from e-waste using thermal imaging-based technique operated in the long-wave infrared range (LWIR) 8–15 m. We use a feature vector comprising of mean intensity, standard deviation and the image-sharpness extracted from the thermograms of indi-vidual materials present in e-waste. We developed a classification model to classify the feature vectors into broad categories of metal, PCB, plastic, and glass. We conducted several experiments on simulated-waste to validate the developed approach and obtained a classification success rate in the range of84–96%. We believe that the proposed approach is a viable solution for multi-material classification of e-waste into broad categories and can be scaled up to fit for an e-waste recycling plant. 
Entered by:
Venkata Dantham on 2020-08-03 
 
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