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Noise Mapping

Ed. by Asdrubali, Francesco

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Citizens as smart, active sensors for a quiet and just city. The case of the “open source soundscapes” approach to identify, assess and plan “everyday quiet areas” in cities

Antonella Radicchi / Dietrich Henckel / Martin Memmel
  • German Research Center for Artificial Intelligence, Smart Data & Knowledge Services Department, Kaiserslautern, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2018-04-03 | DOI: https://doi.org/10.1515/noise-2018-0001


Today the so-called “smart city” is connoted by massive implementation of novel, digital technology, which is often considered as the best solution to global issues affecting contemporary cities. Sophisticated and low-cost technological solutions are developed also in the field of noise monitoring and they are expected to play an important role for acousticians, city planners and policy makers. However, the “smart city” paradigm is controversial: it relies on advanced technological solutions, yet it fails to consider the city as a social construct and it often overlooks the role of citizens, in the quest for technological advances and novel methods. This is especially true in the field of smart acoustic solutions addressing the issue of urban quiet areas: main methods and technologies developed so far barely involve citizens and consider their preferences. This contribution tackles this challenge, by illustrating a novel mixed methodology, which combines the soundscape approach, the citizen science paradigm and a novel mobile application - the Hush City app - with the ultimate goal of involving people in identifying, assessing and planning urban quiet areas. Firstly, the theoretical background and the methods applied are described; secondly initial findings are discussed; thirdly potential impact and future work are outlined.

Keywords: Smart city; END 49/2002; quiet areas; soundscape research; noise pollution; citizen science; open source; mobile applications; mapping; planning


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About the article

Received: 2017-11-29

Accepted: 2018-02-02

Published Online: 2018-04-03

Citation Information: Noise Mapping, Volume 5, Issue 1, Pages 1–20, ISSN (Online) 2084-879X, DOI: https://doi.org/10.1515/noise-2018-0001.

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© 2018 Antonella Radicchi, et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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