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Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review
Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor envir...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400061/ https://www.ncbi.nlm.nih.gov/pubmed/32659931 http://dx.doi.org/10.3390/ijerph17144942 |
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author | Saini, Jagriti Dutta, Maitreyee Marques, Gonçalo |
author_facet | Saini, Jagriti Dutta, Maitreyee Marques, Gonçalo |
author_sort | Saini, Jagriti |
collection | PubMed |
description | Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015–2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO(2), and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency. |
format | Online Article Text |
id | pubmed-7400061 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-74000612020-08-23 Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review Saini, Jagriti Dutta, Maitreyee Marques, Gonçalo Int J Environ Res Public Health Review Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015–2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO(2), and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency. MDPI 2020-07-09 2020-07 /pmc/articles/PMC7400061/ /pubmed/32659931 http://dx.doi.org/10.3390/ijerph17144942 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Saini, Jagriti Dutta, Maitreyee Marques, Gonçalo Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review |
title | Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review |
title_full | Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review |
title_fullStr | Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review |
title_full_unstemmed | Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review |
title_short | Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review |
title_sort | indoor air quality monitoring systems based on internet of things: a systematic review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400061/ https://www.ncbi.nlm.nih.gov/pubmed/32659931 http://dx.doi.org/10.3390/ijerph17144942 |
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