Exploiting data from the NoiseCapture application for environmental noise measurements with a smartphone

Abstract

NoiseCapture is a smartphone application initially developed as part of a participative approach for environmental noise mapping. After more than 3 years, the database produced from all over the world contributions is considerable (more than 77k contributors, nearly 300k tracks representing about 72 million 1-second measurements, in nearly 200 countries). Beyond the initial objective, other uses of the application have emerged: individually by users for their own needs, by associations of people in charge of the fight against noise pollution, within the framework of educational activities, by researchers for the realization of their own research, by communities to address the subject of noise pollution. As these new applications emerged, the development team of NoiseCapture was led to extend the possibilities of exploitation of these data. Thus, in this paper, we present different possibilities for a user to perform his own data analysis, namely: a local export of data from the smartphone, access to raw data and pre-processed data from the NoiseCapture server, access to formatted GIS layers from OGC standard service. All these methods are enabled thanks to the open source ecosystem, such as Python libraries, R software suite and GIS tools.