NoiseTube: Measuring and mapping noise pollution with mobile phones

In this paper we present a new approach for the assessment of noise pollution involving the general public. The goal of this project is to turn GPS-equipped mobile phones into noise sensors that enable citizens to measure their personal exposure to noise in their everyday environment. Thus each user can contribute by sharing their geolocalised measurements and further personal annotation to produce a collective noise map. Acknowledgements This work was partially supported by the EU under contract IST-34721 (TAGora). The TAGora project is funded by the Future and Emerging Technologies program (IST-FET) of the European Commission. Matthias Stevens is a research assistant of the Fund for Scientific Research, Flanders (Aspirant van het Fonds Wetenschappelijk Onderzoek Vlaanderen). Links ITEE 2009 conference: http://www.itee2009.org Published paper: http://dx.doi.org/10.1007/978-3-540-88351-7_16 Full proceedings: http://dx.doi.org/10.1007/978-3-540-88351-7 NoiseTube project: http://www.noisetube.net NoiseTube: Measuring and mapping noise pollution with mobile phones Nicolas Maisonneuve, Matthias Stevens, Maria E. Niessen & Luc Steels ,  Sony Computer Science Laboratory Paris, France  Dept. of Computer Science, Vrije Universiteit Brussel, Belgium  Dept. of Artificial Intelligence, University of Groningen, The Netherlands Abstract: In this paper we present a new approach for the assessment of noise pollution involving the general public. The goal of this project is to turn GPSequipped mobile phones into noise sensors that enable citizens to measure their personal exposure to noise in their everyday environment. Thus each user can contribute by sharing their geo-localised measurements and further personal annotation to produce a collective noise map. In this paper we present a new approach for the assessment of noise pollution involving the general public. The goal of this project is to turn GPSequipped mobile phones into noise sensors that enable citizens to measure their personal exposure to noise in their everyday environment. Thus each user can contribute by sharing their geo-localised measurements and further personal annotation to produce a collective noise map.