Evidence map›Paper›PMID 35271093›Full record

ArticleSensors (Basel, Switzerland)2022

Evaluation of Acoustic Noise Level and Impulsiveness Inside Vehicles in Different Traffic Conditions.

Daniel Flor, Danilo Pena, Hyago Lucas Oliveira, Luan Pena, Vicente A de Sousa, Allan Martins

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Daniel FlorDepartment of Communications Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0002-4547-8302
Danilo PenaDepartment of Electrical Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0003-2767-5764
Hyago Lucas OliveiraDepartment of Communications Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0002-2664-1581
Luan PenaDepartment of Electrical Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0002-6296-4310
Vicente A de SousaDepartment of Communications Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0003-2859-6136
Allan MartinsDepartment of Electrical Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil.ORCID 0000-0002-9486-4509

Funding

Coordenação de Aperfeicoamento de Pessoal de Nível Superior 001
6 · The paper itself

Abstract

Recently, the issue of sound quality inside vehicles has attracted interest from both researchers and industry alike due to health concerns and also to increase the appeal of vehicles to consumers. This work extends the analysis of interior acoustic noise inside a vehicle under several conditions by comparing measured power levels and two different models for acoustic noise, namely the Gaussian and the alpha-stable distributions. Noise samples were collected in a scenario with real traffic patterns using a measurement setup composed of a Raspberry Pi Board and a microphone strategically positioned. The analysis of the acquired data shows that the observed noise levels are higher when traffic conditions are good. Additionally, the interior noise presented considerable impulsiveness, which tends to be more severe when traffic is slower. Finally, our results suggest that noise sources related to the vehicle itself and its movement are the most relevant ones in the composition of the interior acoustic noise.

Indexed as

AcousticsNoiseSoundalpha-stable noiseimpulsive noisenoise sourcesregression analysistraffic noisevehicle interior noise

Identifiers

PMID35271093
PMCPMC8914845

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.