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

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

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.

Related collections

Most cited references 9

Record: found
Abstract: found
Article: found

Is Open Access

Chatty maps: constructing sound maps of urban areas from social media data

Luca Maria Aiello, Rossano Schifanella, Daniele Quercia … (2016)

Urban sound has a huge influence over how we perceive places. Yet, city planning is concerned mainly with noise, simply because annoying sounds come to the attention of city officials in the form of complaints, whereas general urban sounds do not come to the attention as they cannot be easily captured at city scale. To capture both unpleasant and pleasant sounds, we applied a new methodology that relies on tagging information of georeferenced pictures to the cities of London and Barcelona. To begin with, we compiled the first urban sound dictionary and compared it with the one produced by collating insights from the literature: ours was experimentally more valid (if correlated with official noise pollution levels) and offered a wider geographical coverage. From picture tags, we then studied the relationship between soundscapes and emotions. We learned that streets with music sounds were associated with strong emotions of joy or sadness, whereas those with human sounds were associated with joy or surprise. Finally, we studied the relationship between soundscapes and people's perceptions and, in so doing, we were able to map which areas are chaotic, monotonous, calm and exciting. Those insights promise to inform the creation of restorative experiences in our increasingly urbanized world.

0 comments Cited 37 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Evaluation of smartphone sound measurement applications (apps) using external microphones-A follow-up study.

Chucri Kardous, Peter B. Shaw (2016)

This follow-up study examines the accuracy of selected smartphone sound measurement applications (apps) using external calibrated microphones. The initial study examined 192 apps on the iOS and Android platforms and found four iOS apps with mean differences of ±2 dB of a reference sound level measurement system. This study evaluated the same four apps using external microphones. The results showed measurements within ±1 dB of the reference. This study suggests that using external calibrated microphones greatly improves the overall accuracy and precision of smartphone sound measurements, and removes much of the variability and limitations associated with the built-in smartphone microphones.