Smartphone-Based Participatory Soundscape Mapping for a More Sustainable Acoustic Environment

Abstract

The urban environmental planning, a fundamental dynamic process for cities’ sustainability, could benefit from the soundscape approach, dealing with the perception of the acoustic environment in which sound is considered as a resource rather than a waste (noise). Noise and soundscape maps are useful tools for planning mitigation actions and for communication with citizens. Both mappings can benefit from crowdsourcing and participatory sound monitoring that has been made possible due to the large use of internet connections and mobile devices with dedicated apps. This paper is a “scoping review” to provide an overview of the potential, benefits, and drawbacks of participatory noise monitoring in noise and soundscape mapping applications, while also referring to metrological aspects. Gathering perceptual data on soundscapes by using digital questionnaires will likely be more commonly used than printed questionnaires; thus, the main differences between the experimental protocols concern the measurement of acoustic data. The authors propose to classify experimental protocols for in-field soundscape surveys into three types (GUIDE, MONITOR, and SMART) to be selected according to the survey’s objectives and the territorial extension. The main future developments are expected to be related to progress in smartphone hardware and software, to the growth of social networks data analysis, as well as to the implementation of machine learning techniques.

Listening to Forests: Comparing the Perceived Restorative Characteristics of Natural Soundscapes before and after the COVID-19 Pandemic

“…Disordered elements limit exploration and require attention to resolve confusion and, thus, are incompatible with the function of restoring individuals' mental fatigue. One strategy for managers and policymakers is to be mindful of the designs of natural soundscapes that help create harmony and captivating experiences [66].…”

Geo-Crowdsourced Sound Level Data in Support of the Community Facilities Planning. A Methodological Proposal

“…The scientific community is debating the use of these applications as an alternative to the traditional measurement instrumentation [47] because the results are often affected by errors concerning both the sound levels and their localization. The mobile devices used for sound measurements and the professional instruments, such as sound level meters, are characterized by different microphone hardware, filters, and sound application programming interfaces for processing the measured data [48]. The measurement accuracy, indeed, is strictly connected with its purpose and the different features of mobile devices available in the market [49][50][51].…”

Semantic Crowdsourcing of Soundscapes Heritage: A Mojo Model for Data-Driven Storytelling

“…Social media soundscape information can serve for the prediction of health effects of noise pollution in different areas [38]. In this context, cooperative smart-sensing and crowdsourcing practices have been proposed and launched to raise public awareness toward soundscape conservation, safeguarding, and overall ecological consciousness through multimodal mapping capabilities [39][40][41][42][43][44][45][46].…”

“…Smartphone capabilities can serve for citizen science projects, following a user-centered design and providing motivation factors [45]. The cultural sector is also benefitted from this evolution, adopting these practices to collaboratively collect, share, and annotate heritage sites and artifacts [7,[39][40][41][42]47]. These processes feature many resemblances with aspects of the MoJo paradigm and other Digital Journalism genres (i.e., Data, Multimedia, Immersive Journalism, etc.)…”

“…Summing up, the conducted literature review revealed important aspects of soundscapes, i.e., environmental monitoring, sound and intangible cultural heritage, data-driven documentation, decentralized/smart sensing, etc., with diverse extensions on human health and sustainable growth indicators. Many related publications have attempted to enlighten most of the above viewpoints by utilizing mobile terminals and collaborative mapping [17][18][19][38][39][40][41][42][43][44][45]. However, to the best of our knowledge, such a multi-faceted approach (like the current one) has not been reported, incorporating sophisticated on-site semantic analysis and crowdsourcing dynamics, as they are advanced in today's ubiquitous society (i.e., in the era of big data and the semantic web).…”