The case of environmental noise

Sustainability is the main challenge faced by humanity today on global and local scales. This dissertation investigates how the latest developments within computer science and ICT can be applied to establish participatory, low-cost tools and practices that enable citizens to monitor, raise awareness about, and contribute to the sustainable management of the commons they rely on, and thereby protect or improve their quality of life. The general approach proposed in this work is to use community memories – as central data repositories and points of interaction for community members and other stakeholders – and the novel combination of participatory mobile sensing and social tagging – as a low-cost means to collect quantitative and qualitative data about the state of the commons and the health, well-being, behaviour and opinion of those that depend on it. This work also demonstrates in detail how this approach can be turned into a concrete solution for the problem of environmental noise – commonly referred to as noise pollution. The NoiseTube system presented here enables a participatory, low-cost approach to the assessment and mapping of environmental noise and its impact on citizens ’ quality of life. The system has been operational since May 2009 and has since been iteratively improved and validated through lab and field experiments. Via coordinated campaigns with volunteering citizens it is established that participatory noise mapping is a suitable alternative for, or a valuable complement to, conventional methods applied by authorities. NoiseTube is the completest and most widely used participatory noise mapping solution to date