Mobile crowd-sensing as a resource for contextualized urban public policies: a study using three use cases on noise and soundscape monitoring

ABSTRACT

Environmental noise is a major pollutant in contemporary cities and calls for the active monitoring of noise levels to spot the locations where it most affects the people’s health and well-being. However, due to the complex relationship between environmental noise and its perception by the citizens, it is not sufficient to quantitatively measure environmental noise. We need to collect and aggregate contextualized – both quantitative and qualitative – data about the urban environmental noise so as to be able to study the objective and subjective relationships between sound and living beings. This complex knowledge is a prerequisite for making efficient territorial public policies for soundscapes that are inclined towards living beings welfare. In this paper, we investigate how Mobile Phone Sensing – aka crowd-sensing – enables the gathering of such knowledge, provided the implementation of sensing protocols that are customized according to the context of use and the intended exploitation of the data. Through three case studies that we carried out in France and Finland, we show that MPS is not solely a tool that contributes to sensitizing citizens and decision-makers about noise pollution; it also contributes to increasing our knowledge about the impact of the environmental noise on people’s health and well-being in relation to its physical and subjective perception.

KEYWORDS:

• Environmental noise
• urban health
• well-being
• crowd-sensing
• mobile phone sensing
• noise maps
• ambiciti
• soundscape

Acknowledgements

The authors would like to thank: Ambiciti for granting us access to the specific data as part of research collaboration; the City of Helsinki, notably Forum Virium; and Professor Kirsi Pynnönen-Oudman who is managing the experiment for the zoo. The authors also acknowledge the support of the CityLab@Inria research program on digital solutions contributing to socially and environmentally sustainable cities.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. https://www.soundplan.eu/english/soundplan-acoustics/, accessed 03/19.

2. https://www.datakustik.com/products/cadnaa/cadnaa/, accessed 03/19.

3. https://github.com/Ifsttar/NoiseModelling/wiki/01-Installation, accessed 03/19.

4. https://docs.google.com/forms/d/1LAQN3qCfe7EOFdzzCRPkKznRxUgJB9SeyhNfMmJDDSs.

5. See also: http://www.gisresources.com/types-of-interpolation-methods 2/, accessed 03/19.

6. https://www.portofhelsinki.fi/en/port-helsinki/environmental-responsibility/management-environmental-impacts, accessed 03/19.

Additional information

Notes on contributors

Bruno Lefevre

Bruno Lefevre is a French researcher in Information and Communication Science, associated to Mimove research team at Inria-Paris, where he studied the social and societal conditions of use of collaborative digital tools. His previous research analyzed the socio-economical dimensions of the development of cultural clusters in contexts of creative local policies. He has worked previously for 20 years as a Journalist, Communication assistant and Digital services management. His current works analyze the relationships between social groups, territorial policies and digital economy and services.

Rachit Agarwal

Rachit Agarwal is currently associated to Mimove research team within Inria, Paris. He obtained his Ph.D. in Computer Science and Telecommunications from the University of Pierre and Marie Curie, Paris in 2013 with the lab situated at Telecom SudParis. His research interests mainly span the areas related to ICT, especially relating to the Internet of Things (IoT), human mobility aspects, semantic technologies, and network science. In the past, he has been associated with several projects and has been the Co-PI of the Inria Sarathi Associate team. He has won the 2015 semantic web challenge.

Valerie Issarny

Valerie Issarny holds a Director of research position at Inria, the French National Institute for computer science and applied mathematics. Her research lies in the study of middleware solutions easing the development of distributed collaborative services, including mobile services deployed over smartphones and interacting with sensors and actuators. Since summer 2013, she is the scientific coordinator of the Inria@SiliconValley program promoting and fostering collaboration between Inria and California universities. She also coordinates the CityLab@Inria research program dedicated to the study of urban software systems promoting citizen engagement. She regularly serves in the program committees of major conferences of the software engineering and middleware domains.

Vivien Mallet

Vivien Mallet is research scientist at INRIA. His research focuses on the exploitation of observational data and numerical simulations for the modeling of complex environmental systems. His work dealt with data assimilation, meta-modeling and uncertainty quantification, with applications in air pollution, urban noise propagation, road traffic, wildland fires, weather forecasting, renewable energies.