Mobile crowdsensing accuracy for noise mapping in smart cities

Abstract

This paper deals with the problem of traffic noise in urban areas in terms of noise mapping. It explains in detail the Mobile Crowdsensing (MCS) method and, furthermore, compares the results obtained with this method with the results gained from the standard method that uses a sound level metre. The research done in this paper shows that the MCS method can make noise mapping easier, cheaper and less time-consuming in terms of creating representative noise maps developed on measurements but also noise maps developed on calculations and simulations. The main idea is to show that accuracy and precision of measurements obtained by using calibrated smartphones are acceptable. The paper suggests that when using the smartphone measurement application, the calibration of the measurement chain can be done in free field with class 1 sound level metre, and noise map can be checked in a much larger number of points (in comparison with the standard measurement method) and therefore, smartphones can be used as instruments for creating or even checking final noise maps in urban environment. Another advantage of this method is that citizens can engage in noise monitoring in urban areas and become aware of the noise pollution in their cities.

Keywords

• Mobile Crowdsensing
• IoT
• noise pollution
• noise map