Dataset for "Q-SCALE: Quantum Sensor Calibration for Advanced Learning and Efficiency"
- 1. Politecnico di Torino, Department of Control and Computer Engineering, Torino, Italy
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2.
University of Naples Federico II
Description
The dataset contains the data used in the article "Q-SCALE: Quantum Sensor Calibration for Advanced Learning and Efficiency".
A low-cost monitoring system composed of 6 monitoring stations was positioned at the official monitoring station of Torino Rubino in the city of Turin (Italy). The official station is managed by the environmental agency ARPA Piemonte.
Each low-cost station contains four low-cost light-scattering PM sensors (Honeywell HPMA115C0-003), one temperature and relative humidity sensor (DHT22), and one atmospheric pressure sensor (BME/BMP280).
The sampling time of the PM sensors was set to one second, while the other sensors generated measurements every 3-4 seconds.
The official monitoring station uses both a gravimetric and a beta attenuation instrument for measuring PM.
The data contained in this dataset was collected from November 2022 to June 2023. It contains the median of the PM2.5, relative humidity, temperature, and atmospheric pressure measurements of the low-cost sensors, after being aggregated to either one minute or one hour.
The official measurements of the beta attenuation device are also provided.
Measurements of low-cost sensors are expressed in UTC, while official measurements are expressed in UTC+1.
Official PM measurements can be also found at https://aria.ambiente.piemonte.it/qualita-aria/dati.
Notes (English)
Disclaimer: ARPA Piemonte can not be ascribed for any mistake contained in this dataset, as well as for any error in the experimental values.
Files
dataset.zip
Files
(7.2 MB)
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