Air Quality Measurement Using an IoT Network: a Case Study

Context: The evaluation of air quality in Colombia is localized; it does not go beyond determining whether the level of the polluting gas at a specific point of the monitoring network has exceeded a threshold, according to a norm or standard, in order to trigger an alarm. It is not committed to obje...

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Main Authors: Hernán Paz Penagos, Andrés Alejandro Moreno Sánchez, José Noé Poveda Zafra
Format: Article
Language:Spanish
Published: Universidad Distrital Francisco José de Caldas 2022-01-01
Series:Ingeniería
Subjects:
Online Access:https://revistas.udistrital.edu.co/index.php/reving/article/view/17589
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author Hernán Paz Penagos
Andrés Alejandro Moreno Sánchez
José Noé Poveda Zafra
author_facet Hernán Paz Penagos
Andrés Alejandro Moreno Sánchez
José Noé Poveda Zafra
author_sort Hernán Paz Penagos
collection DOAJ
description Context: The evaluation of air quality in Colombia is localized; it does not go beyond determining whether the level of the polluting gas at a specific point of the monitoring network has exceeded a threshold, according to a norm or standard, in order to trigger an alarm. It is not committed to objectives as important as the real-time identification of the dispersion dynamics of polluting gases in an area, or the prediction of the newly affected population. From this perspective, the presence of polluting gases was evaluated on the university campus of Escuela Colombiana de Ingeniería Julio Garavito, located north of the city of Bogotá, and the affected population was estimated for the month of October, 2019, using the Kriging geostatistical technique. Method: This study is part of the design and construction of an auxiliary mobile station that monitors and reports complementary information (CO and SO2 gases) to that provided by the Guaymaral meteorological station, located in the north of Bogotá. This information is transmitted through an IoT network to a server, where a database is created which stores the information on polluting gases reported by the 14 stations of the Bogotá air quality monitoring network, the information sent by the auxiliary station, and the statistical information of the population present on the university campus. Pollutant gas data and population information recorded from October 1st to 31st, 2019, are the input for data analysis using the Kriging interpolation method and predicting the affected population on said campus. Results: There is a particulate matter concentration of 29 µg/m3 of PM10 in the coliseum and 12,6 µg/m3 of PM2,5 in building G, in addition to 9,8 ppb of O3 in building I, 14,9 ppb of NO2 in that same building, 0,79 ppb of CO in building C, and 0,65 ppb of SO2 also in building C, thus allowing to infer, according to the Bogotá air quality index, a favorable air quality for a population of 2.131 people who visited the campus university during the aforementioned period. Conclusions: The correct integration of the data in the web server and their analysis, carried out in the R language, allowed determining the approximate indicators of the polluting factors around Escuela Colombiana de Ingeniería Julio Garavito. Additionally, to determine the affected population, these indicators were correlated with the information on the registered population that entered the campus during the period under study. Based on the results obtained, it was concluded that the air quality on the campus of Escuela Colombiana de Ingeniería Julio Garavito is favorable, and that 2.131 people benefited daily from these conditions.
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spelling doaj.art-fae310cf79b44a7fb2db1f4fbddcd7b22022-12-21T17:24:58ZspaUniversidad Distrital Francisco José de CaldasIngeniería0121-750X2344-83932022-01-0126340141810.14483/23448393.1758913253Air Quality Measurement Using an IoT Network: a Case StudyHernán Paz Penagos0https://orcid.org/0000-0002-2692-1989Andrés Alejandro Moreno Sánchez1https://orcid.org/0000-0001-9757-2635José Noé Poveda ZafraEscuela Colombiana de Ingeniería Julio GaravitoEscuela Colombiana de Ingeniería Julio GaravitoContext: The evaluation of air quality in Colombia is localized; it does not go beyond determining whether the level of the polluting gas at a specific point of the monitoring network has exceeded a threshold, according to a norm or standard, in order to trigger an alarm. It is not committed to objectives as important as the real-time identification of the dispersion dynamics of polluting gases in an area, or the prediction of the newly affected population. From this perspective, the presence of polluting gases was evaluated on the university campus of Escuela Colombiana de Ingeniería Julio Garavito, located north of the city of Bogotá, and the affected population was estimated for the month of October, 2019, using the Kriging geostatistical technique. Method: This study is part of the design and construction of an auxiliary mobile station that monitors and reports complementary information (CO and SO2 gases) to that provided by the Guaymaral meteorological station, located in the north of Bogotá. This information is transmitted through an IoT network to a server, where a database is created which stores the information on polluting gases reported by the 14 stations of the Bogotá air quality monitoring network, the information sent by the auxiliary station, and the statistical information of the population present on the university campus. Pollutant gas data and population information recorded from October 1st to 31st, 2019, are the input for data analysis using the Kriging interpolation method and predicting the affected population on said campus. Results: There is a particulate matter concentration of 29 µg/m3 of PM10 in the coliseum and 12,6 µg/m3 of PM2,5 in building G, in addition to 9,8 ppb of O3 in building I, 14,9 ppb of NO2 in that same building, 0,79 ppb of CO in building C, and 0,65 ppb of SO2 also in building C, thus allowing to infer, according to the Bogotá air quality index, a favorable air quality for a population of 2.131 people who visited the campus university during the aforementioned period. Conclusions: The correct integration of the data in the web server and their analysis, carried out in the R language, allowed determining the approximate indicators of the polluting factors around Escuela Colombiana de Ingeniería Julio Garavito. Additionally, to determine the affected population, these indicators were correlated with the information on the registered population that entered the campus during the period under study. Based on the results obtained, it was concluded that the air quality on the campus of Escuela Colombiana de Ingeniería Julio Garavito is favorable, and that 2.131 people benefited daily from these conditions.https://revistas.udistrital.edu.co/index.php/reving/article/view/17589polluting factorsmodelingkriging methodair qualityareapopulation
spellingShingle Hernán Paz Penagos
Andrés Alejandro Moreno Sánchez
José Noé Poveda Zafra
Air Quality Measurement Using an IoT Network: a Case Study
Ingeniería
polluting factors
modeling
kriging method
air quality
area
population
title Air Quality Measurement Using an IoT Network: a Case Study
title_full Air Quality Measurement Using an IoT Network: a Case Study
title_fullStr Air Quality Measurement Using an IoT Network: a Case Study
title_full_unstemmed Air Quality Measurement Using an IoT Network: a Case Study
title_short Air Quality Measurement Using an IoT Network: a Case Study
title_sort air quality measurement using an iot network a case study
topic polluting factors
modeling
kriging method
air quality
area
population
url https://revistas.udistrital.edu.co/index.php/reving/article/view/17589
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