Indoor air quality (IAQ) measurements in a tertiary building via a smart sensor connected to a Raspberry Pi card: application to a demonstrator building
Résumé
The aim of this study is to improve indoor air quality (IAQ) using an intelligent ventilation for optimal air distribution and energy consumption. For this purpose, we developed a smart multi-sensor. This device measures air pollutants (CO2, CO,VOCs, formaldehyde, PM2.5, and benzene) and comfort parameters (temperature, humidity, noise level and lighting) in a demonstrating building. It should be noted that measurements are achieved instantly and temporally, and that data processing is done via an algorithm. This will effectively ventilate the building as needed. To go further, we conducted three sets of measurements on IAQ and hygrothermal comfort in winter, mid-season and summer in a demonstrator building room. The obtained results showed that the level of air quality is acceptable in terms of VOCs, PM2.5, formaldehyde and benzene. In addition, the CO2 rate turned out to be high during occupancy periods. In terms of hygrothermal comfort, the air was dry and very hot, especially during the winter. This is due to the current ventilation system which does not consider the variable "humidity" to predict the comfort. Over the three measurements, we considered the occupants' perception of IAQ and hygrothermal comfort using a survey that has been proposed to occupants (students).
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