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Community memories for sustainable societies: The case of environmental noise
Sustainability is the main challenge faced by humanity today on global and local scales. Most environmental problems can be seen as the tragic overexploitation of a commons. In this dissertation we investigate 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. As a general approach we propose the use of 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. Through applied, interdisciplinary research we develop a concrete solution for a specific, socially relevant problem, namely that of environmental noise – commonly referred to as noise pollution. Under the name NoiseTube we present an operational system that enables a participatory, low-cost approach to the assessment of environmental noise and its impact on citizens’ quality of life. This approach can be applied in the scope of citizen- or authority-led initiatives. The NoiseTube system consists of a sensing application – which turns mobile phones into a sound level meters and allows users to comment on their experience via social tagging – and a community memory – which aggregates and processes data collected by participants anywhere. The system supports and has been tested and deployed at different levels of scale – personal, group and mass sensing. Since May 2009 NoiseTube has been used by hundreds, if not thousands, of people all around the world, allowing us to draw lessons regarding the feasibility of different deployment, collaboration and coordination scenarios for ...
Community memories for sustainable societies: The case of environmental noise
Sustainability is the main challenge faced by humanity today on global and local scales. Most environmental problems can be seen as the tragic overexploitation of a commons. In this dissertation we investigate 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. As a general approach we propose the use of 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. Through applied, interdisciplinary research we develop a concrete solution for a specific, socially relevant problem, namely that of environmental noise – commonly referred to as noise pollution. Under the name NoiseTube we present an operational system that enables a participatory, low-cost approach to the assessment of environmental noise and its impact on citizens’ quality of life. This approach can be applied in the scope of citizen- or authority-led initiatives. The NoiseTube system consists of a sensing application – which turns mobile phones into a sound level meters and allows users to comment on their experience via social tagging – and a community memory – which aggregates and processes data collected by participants anywhere. The system supports and has been tested and deployed at different levels of scale – personal, group and mass sensing. Since May 2009 NoiseTube has been used by hundreds, if not thousands, of people all around the world, allowing us to draw lessons regarding the feasibility of different deployment, collaboration and coordination scenarios for ...
Community memories for sustainable societies: The case of environmental noise
Stevens, M (Autor:in) / Steels, L / D'Hondt, E
04.06.2012
Doctoral thesis, Vrije Universiteit Brussel.
Hochschulschrift
Elektronische Ressource
Englisch
DDC:
710
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