IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review
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Journal Title
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Volume Title
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
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Date
2022
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Mcode
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Language
en
Pages
38
73326-73363
73326-73363
Series
IEEE Access, Volume 10
Abstract
With urbanization, rising income and consumption, the production of waste increases. One of the most important directions in the field of sustainable development is the design and implementation of monitoring and management systems for waste collection and removal. Smart waste management (SWM) involves for example collection and analytics of data from sensors on smart garbage bins (SGBs), management of waste trucks and urban infrastructure; planning and optimization of waste truck routes; etc. The purpose of this paper is to provide a comprehensive overview of the existing research in the field of systems, applications, and approaches vis-à-vis the collection and processing of solid waste in SWM systems. To achieve this objective, we performed a systematic literature review. This study consists of 173 primary studies selected for analysis and data extraction from the 3,732 initially retrieved studies from 5 databases. We 1) identified the main approaches and services that are applied in the city and SGB-level SWM systems, 2) listed sensors and actuators and analyzed their application in various types of SWM systems, 3) listed the direct and indirect stakeholders of the SWM systems, 4) identified the types of data shared between the SWM systems and stakeholders, and 5) identified the main promising directions and research gaps in the field of SWM systems. Based on an analysis of the existing approaches, technologies, and services, we developed recommendations for the implementation of city-level and SGB-level SWM systems.Description
Publisher Copyright: © 2013 IEEE.
Keywords
Internet of Things, Smart city, smart garbage bin, smart waste management
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Citation
Sosunova, I & Porras, J 2022, ' IoT-Enabled Smart Waste Management Systems for Smart Cities : A Systematic Review ', IEEE Access, vol. 10, pp. 73326-73363 . https://doi.org/10.1109/ACCESS.2022.3188308
