A Smartphone-Based Crowd-Sourced Database for Environmental Noise Assessment

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.

Development of Adjustable Parallel Helmholtz Acoustic Metamaterial for Broad Low-Frequency Sound Absorption Band

“…Noise pollution has been considered as one of the most important pollution sources to human lives, which disturbs our daily life and harms our health; especially noise in the low frequency region, which is difficult to dissipate and attenuate in the spreading process for its high penetrability with large wavelength [ 1 , 2 ]. Most noise is generated by the equipment, such as construction equipment, vehicles, machine tools and household appliances [ 3 , 4 ]. Taking into account that reducing the generated noise through optimizing the mechanical structure or assembly process of equipment is difficult to conduct, the application of sound absorbing materials or structures in the noise propagation path is treated as a feasible and practicable method for noise control [ 5 , 6 ].…”

Best practices and current implementation of emerging smartphone-based (bio)sensors – Part 1: Data handling and ethics

“…Data security means safeguarding digital information from unauthorized access, corruption, loss, or theft. Security is an essential component of the GDPR; the regulation mandates that any researcher or company wishing to process personal data, track people's locations, monitor publicly accessible spaces [183], or use new technologies (such as smartphones) to process data, are required first to submit a Data Protection Impact Assessment (DPIA), or in the context of scientific research a Data Management Plan (DMP) [154]. These assessments should demonstrate how and why data will be processed and transparently outline the potential risks and appropriate security mechanisms to protect against them.…”

Crowdsourced Acoustic Open Data Analysis With Foss4g Tools

“…The beginning of this analysis was the release of a 3 years collection of environnemental acoustic samples. A first article presenting this dataset has been published in 2021 (Picaut et al, 2021). It details the structure of the database and the data, the profile of the contributors and the contributions but does not analyze the content of the data.…”

“…There are 18 predefined labels and the user can select one or more of them for each of the traces made. The labels are detailed in (Picaut et al, 2021). The preliminary work presented here focuses on the analysis of the proportion of certain labels in the global sample at certain temporalities.…”