Smart technologies for collection and classification of electronic waste

Abstract

Purpose: The main aim of this study is to understand the role of smart technologies and show the rankings of various smart technologies in collection and classification of electronic waste (e-waste). Design/methodology/approach: This study presents a framework integrating the concepts of collection and classification mechanisms and smart technologies. The criteria set includes three main which are economic social and environmental criteria including a total of 15 subcriteria. Smart technologies identified in this study were robotics multiagent systems autonomous tools smart vehicles data-driven technologies Internet of things (IOT) cloud computing and big data analytics. The weights of all criteria were found using fuzzy analytic network process (ANP) and the scores of smart technologies which were useful for collection and classification of e-waste were calculated using fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Findings: The most important criterion was found as collection cost followed by pollution prevention and control storage/holding cost and greenhouse gas emissions in collection and classification of e-waste. Autonomous tools were found as the best smart technology for collection and classification of e-waste followed by robotics and smart vehicles. Originality/value: The originality of the study is to propose a framework which integrates the collection and classification of e-waste and smart technologies. © 2024 Elsevier B.V. All rights reserved.