| Abstract |
Nowadays, different projects worldwide are pushing to move the benefit of information and communications technology (ICT) into public transportation in order to decrease the traffic level and air pollution. Cagliari 2020 is a smart city project focused on the area of the city of Cagliari, in Italy, with the aim to improve the quality of life of the citizens thanks to an enhancement of the public transportation system. Traffic reduction and improvement of the air quality are specific goals of the project. In this framework, to better evaluate the pollution level in the urban area, the buses are used as distributed mobile sensors to increase the temporal and spatial information about air quality. The information provided by the low-cost air quality sensors could be affected by high levels of uncertainty due to the atmospheric variability, as humidity and temperature cause a mismatch between the values obtained during laboratory calibration and real-field operation. To increase the trustworthiness of the received data, the measurements need to be correlated with other information to exclude the "bad data". In order to support the data acquisition process, this paper presents a proof-of-concept of a data concentrator with the aim to collect measurements and improve information correlating the measurements with other types of data, such as position, speed, and proximity to high-accuracy and fixed air pollution stations. |
