Abstract
Noise is a major source of pollution with a strong impact on health. Noise assessment is therefore a very important issue to reduce its impact on humans. To overcome the limitations of the classical method of noise assessment (such as simulation tools or noise observatories), alternative approaches have been developed, among which is collaborative noise measurement via a smartphone. Following this approach, the NoiseCapture application was proposed, in an open science framework, providing free access to a considerable amount of information and offering interesting perspectives of spatial and temporal noise analysis for the scientific community. After more than 3 years of operation, the amount of collected data is considerable. Its exploitation for a sound environment analysis, however, requires one to consider the intrinsic limits of each collected information, defined, for example, by the very nature of the data, the measurement protocol, the technical performance of the smartphone, the absence of calibration, the presence of anomalies in the collected data, etc. The purpose of this article is thus to provide enough information, in terms of quality, consistency, and completeness of the data, so that everyone can exploit the database, in full control.
Highlights
Noise is a very significant source of pollution, in urban areas, with significant effects on health
The main tool for decision-makers is the production of strategic noise maps. These maps are generally produced using specific software, integrating noise emission and acoustic propagation models, coupled with geospatial data and traffic information. These maps are limited by the calculation assumptions and the quality of the input data, they make it possible to assess the broad outlines of a noise distribution in a city and to evaluate the effect of action plans to reduce noise
We present statistics and information related to the geolocalization of the NoiseCapture data
Summary
Noise is a very significant source of pollution, in urban areas, with significant effects on health. In Europe, for example, the directive 2002/49/EC aims to establish an inventory of noise nuisance, to propose actions to reduce nuisance and to communicate to citizens about their exposure to noise [1] In this regulatory context, the main tool for decision-makers is the production of strategic noise maps. These maps are generally produced using specific software, integrating noise emission and acoustic propagation models, coupled with geospatial data and traffic information These maps are limited by the calculation assumptions and the quality of the input data, they make it possible to assess the broad outlines of a noise distribution in a city and to evaluate the effect of action plans to reduce noise. The limitation of the number of sensors, for technical and cost reasons, does not allow carrying out noise mapping with a sufficient spatial step
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