Awareness and Learning in Participatory Noise Sensing

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Becker, Martin; Caminiti, Saverio; Fiorella, Donato; Francis, Louise; Gravino, Pietro; et. al.: Awareness and Learning in Participatory Noise Sensing. In: PloS ONE 8 (2013), Nr. 12, e81638. DOI: http://dx.doi.org/10.1371/journal.pone.0081638

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/284

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Sum total of downloads: 225




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Abstract: 
The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2013-12-11
Appears in Collections:Forschungszentren

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 139 61.78%
2 image of flag of United States United States 22 9.78%
3 image of flag of China China 17 7.56%
4 image of flag of Ukraine Ukraine 4 1.78%
5 image of flag of Ireland Ireland 3 1.33%
6 image of flag of France France 3 1.33%
7 image of flag of Brazil Brazil 3 1.33%
8 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 2 0.89%
9 image of flag of United Kingdom United Kingdom 2 0.89%
10 image of flag of Canada Canada 2 0.89%
    other countries 28 12.44%

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