A Densely-Deployed, High Sampling Rate, Open-Source Air Pollution Monitoring WSN

This work contains data gathered by a series of sensors (PM 10, PM 2.5, temperature, relative humidity, and pressure) in the city of Turin in the north part of Italy (more precisely, at coordinates 45.041903N, 7.625850E). The data has been collected for a period of 5 months, from October 2018 to February 2019. The scope of the study was to address the calibration of low-cost particulate matter sensors and compare the readings against official measures provided by the Italian environmental agency (ARPA Piemonte). The database proposed has been designed as general enough to handle not only PM measures plus temperature and relative humidity but also almost any other quantity, such as altitude, wind speed and direction, radioactivity, electromagnetic pollution, etc. The total size of the database is about 50GB of time-stamped data. The directory also contains several useful scripts that can be used to perform the calibration and the analysis of the acquired data, such as plotting graphs, displaying the correlation with the reference values, printing measurement errors, etc. The scripts implement two commonly used calibration techniques, namely Multivariate Linear Regression and Random Forest, resorting to the SciKitLearn Python library. The README files included in the main subdirectories report hints and comments on the data set format and the logic of the scripts. Please refer to them for further details. Please note that, following article 18.5 of Italian Decree 155/2010 on the dissemination of air quality data, which absorbs EU directive 2008/50/CE, ARPA Piemonte (http://www.arpa.piemonte.it/english-version) can not be ascribed for any mistake in these data, that can not be considered official, unlike the ones provided by ARPA itself.