TY - GEN
T1 - Influence of Indoor Conditions on Sick Building Syndrome
T2 - International Conference on Information Technology and Systems, ICITS 2024
AU - Posada Barrera, Ariel Isaac
AU - Rodríguez Peralta, Laura Margarita
AU - de Oliveira Nunes, Éldman
AU - Sampaio, Paulo Nazareno Maia
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - This study conducted tests to examine the correlation between temperature, relative humidity, and the number of individuals per cubic meter with indoor pollutants such as CO2, TVOC, PM2.5, and PM10. Observations were made under both ideal temperature and relative humidity conditions, as well as under varying temperature and humidity scenarios. To analyze the data, the Levene test, ANOVA, and correlation analyses were employed, ensuring a comprehensive understanding of the relationships between the variables. Drawing from the Environmental Protection Agency’s guidelines and using advanced statistical methods, the influence of these factors on indoor air quality was determined. The findings underscore the significance of maintaining optimal temperature and humidity levels and the need for consistent monitoring of indoor contaminants. Through this rigorous approach, the research aims to establish standards for preventing respiratory diseases and addressing the challenges of Sick Building Syndrome (SBS).
AB - This study conducted tests to examine the correlation between temperature, relative humidity, and the number of individuals per cubic meter with indoor pollutants such as CO2, TVOC, PM2.5, and PM10. Observations were made under both ideal temperature and relative humidity conditions, as well as under varying temperature and humidity scenarios. To analyze the data, the Levene test, ANOVA, and correlation analyses were employed, ensuring a comprehensive understanding of the relationships between the variables. Drawing from the Environmental Protection Agency’s guidelines and using advanced statistical methods, the influence of these factors on indoor air quality was determined. The findings underscore the significance of maintaining optimal temperature and humidity levels and the need for consistent monitoring of indoor contaminants. Through this rigorous approach, the research aims to establish standards for preventing respiratory diseases and addressing the challenges of Sick Building Syndrome (SBS).
KW - IoT
KW - Machine learning
KW - Monitoring
KW - Respiratory diseases
KW - Sick buildings syndrome
UR - https://www.scopus.com/pages/publications/85187794046
U2 - 10.1007/978-3-031-54235-0_5
DO - 10.1007/978-3-031-54235-0_5
M3 - Articulo (Contribución a conferencia)
AN - SCOPUS:85187794046
SN - 9783031542343
T3 - Lecture Notes in Networks and Systems
SP - 46
EP - 57
BT - Information Technology and Systems - ICITS 2024
A2 - Rocha, Alvaro
A2 - Diez, Jorge Hochstetter
A2 - Ferras, Carlos
A2 - Rebolledo, Mauricio Dieguez
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 24 January 2024 through 26 January 2024
ER -