IoT based sustainable smart waste management system evaluation using MCDM model under interval-valued q-rung orthopair fuzzy environment


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ŞEKER Ş.

Technology in Society, vol.71, 2022 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 71
  • Publication Date: 2022
  • Doi Number: 10.1016/j.techsoc.2022.102100
  • Journal Name: Technology in Society
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, International Bibliography of Social Sciences, Periodicals Index Online, Communication & Mass Media Index, Communication Abstracts, Compendex, EBSCO Education Source, Geobase, INSPEC, Political Science Complete, Sociological abstracts, Worldwide Political Science Abstracts
  • Keywords: Waste management, IoT, Uncertainty, MCDM
  • Yıldız Technical University Affiliated: Yes

Abstract

© 2022 Elsevier LtdWaste management has a crucial role for human health and well-being. The novel waste collection technologies, information and communications technologies (ICTs) and Internet of Things (IoT) play important roles in the field of municipal waste management considering sustainability aspects such as economic, social and environmental. Considering future development and the sustainability of the environment, selecting the most appropriate smart technology to manage waste collection may have long-term impacts. This paper aims to evaluate the smart waste collection systems based on IoT with respect to uncertain parameters by applying modified Entropy measure and Multi-Criteria Decision Making (MCDM) method for the local municipal in Istanbul. To deal with uncertainty and vagueness associated with the decision-making process Interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs) is employed in the process. As a result, the waste collection system developed using RFID, GIS and GPRS is selected as the most appropriate smart waste collection system based on IoT for municipal. To validate results and prove robustness of the proposed method in the decision making, Sensitivity and Comparative analysis are conducted at the end of the study.