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 OnderzoekVlaanderen). Links 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.

Noise pollution is a major problem in cities around the world. The current methods to assess it neglect to represent the real exposure experienced by the citizens themselves, and therefore could lead to wrong conclusions and a biased representations. In this paper we present a novel approach to monitor noise pollution involving the general public. Using their mobile phones as noise sensors, we provide a low cost solution for the citizens to measure their personal exposure to noise in their everyday environment and participate in the creation of collective noise maps by sharing their geo-localized and annotated measurements with the community. Our prototype, called NoiseTube, can be found online [1].

Abstract.We have created a set of novel visualisations of group activity: they mirror activity of individuals and their interactions, based upon readily available authentic data. We evaluated these visualisations in the context of a semester long software development project course. We give a theoretical analysis of the design of our visualizations using the framework from the "Big 5" theory of team work as well as a qualitative study of the visualisations and the students' reflective reports. We conclude that these visualisations provide a powerful and valuable mirroring role with potential, when well used, to help groups learn to improve their effectiveness.

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Participatory sensing is a new research area that emerged from the need to complement our previous efforts in wireless sensor networks. It takes advantage of the emergence of rich-sensor mobile phones and their wide adoption, in order to turn people to producers of sensed data and enable new classes of collective applications. Unavoidably, this raises a lot of privacy concerns, as people are becoming sensors and give out a lot of personal information, like their location. If we choose to protect their privacy by anonymizing the data and completely hiding any identifying information, then the visibility of their contributions to others is lost. However, it is important to maintain this property, in order to support accountability on one hand and allow people gain reputation for their efforts on the other hand. In this book chapter we investigate which of the available technical solutions we need, in order to resolve this conflict and what are the research directions that emerge.