The experimental dataset here represented is composed by 3 CSV files (ranging from 7M records to 11M records), each corresponding to air quality records -- related to the presence of gases (as a unified value concentration); the concentration of carbon dioxide (CO2), together with air temperature and humidity; and the concentration of particulate matter (PM) in the monitored environment (PM0.5, PM1, PM2.5, PM4, PM10) -- sampled (every 2 sec) over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy, in the aim of the European project InSecTT (https://www.insectt.eu/, https://cordis.europa.eu/project/id/876038/). In particular, each CSV file has been generated by a prototypical Internet of Things (IoT) sensing node, designed at the IoTLab (https://iotlab.unipr.it/) of the University of Parma, Italy, exploiting a Raspberry Pi 4 (as processing unit) and three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30). Then, as a time reference, each record contains the Unix-like data collection timestamp and the identity of the IoT node sampling the air parameters (for safety purposes, the association with a generic color name in the CSV file name has been a consequence of an anonymization naming process for the IoT nodes, in order to hide their precise positions inside the airside transit area).

Indoor Air Quality Monitoring @ Brindisi Airport / Davoli, Luca; Belli, Laura; Ferrari, Gianluigi. - (2023).

Indoor Air Quality Monitoring @ Brindisi Airport

Luca Davoli
;
Laura Belli;Gianluigi Ferrari
2023-01-01

Abstract

The experimental dataset here represented is composed by 3 CSV files (ranging from 7M records to 11M records), each corresponding to air quality records -- related to the presence of gases (as a unified value concentration); the concentration of carbon dioxide (CO2), together with air temperature and humidity; and the concentration of particulate matter (PM) in the monitored environment (PM0.5, PM1, PM2.5, PM4, PM10) -- sampled (every 2 sec) over a 1-year period (October 2022-October 2023) in an indoor travelers’ transit area in the Brindisi airport, Italy, in the aim of the European project InSecTT (https://www.insectt.eu/, https://cordis.europa.eu/project/id/876038/). In particular, each CSV file has been generated by a prototypical Internet of Things (IoT) sensing node, designed at the IoTLab (https://iotlab.unipr.it/) of the University of Parma, Italy, exploiting a Raspberry Pi 4 (as processing unit) and three low-cost commercial sensors (namely: Adafruit MiCS5524, Sensirion SCD30, Sensirion SPS30). Then, as a time reference, each record contains the Unix-like data collection timestamp and the identity of the IoT node sampling the air parameters (for safety purposes, the association with a generic color name in the CSV file name has been a consequence of an anonymization naming process for the IoT nodes, in order to hide their precise positions inside the airside transit area).
2023
Indoor Air Quality Monitoring @ Brindisi Airport / Davoli, Luca; Belli, Laura; Ferrari, Gianluigi. - (2023).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2965034
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