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= "Turn your mobile phone into an environmental sensor and participate in the monitoring of noise pollution".


"NoiseTube is built in the spirit of open participation and the software that has been developed as part of the project has been placed under the GNU LGPL v2.1 open source license. The source code has been published on Google Code. "



"Noise pollution is a serious problem in many cities. NoiseTube is a research project, started in 2008 at the Sony Computer Science Lab in Paris and currently hosted by the BrusSense Team at the Vrije Universiteit Brussel, which proposes a participative approach for monitoring noise pollution by involving the general public. The NoiseTube mobile app extends the current usage of mobile phones by turning them into noise sensors enabling citizens to measure the sound exposure in their everyday environment. Furthermore each user can participate in creating a collective map of noise pollution by sharing geolocalized measurement data with the NoiseTube community.

By installing the free app on your smartphone, you will be able to measure the level of noise in dB(A), and tag the measurements obtained (e.g. subjective level of annoyance, source of sound,...). When uploaded to the website (3G, wifi or manually) you can check your sound trajectory on Google Maps." (


"NoiseTube is an application that transforms your smartphone into an acoustic detector to measure noise pollution in a precise place and at a right time.

Using NoiseTube you will be able to detect the noise of your street, block or city.

Are you tired of not being able to open the windows in the summer because of the constant noise? Do you live near a highway or in a particularly busy road?

From now on you can measure the noise that you perceive, by yourself, in real time, and with a smartphone.

The set of data collected from individuals, allows creating mediated map, where the noise is represented by different colors based on the decibel detected.

Moreover, if the acquisition is carried out in a systematic manner, e.g. more people who repeat the same path several times (at least 50 takeovers), it will be possible to create maps with statistically reliable values." (

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