Integrating Volunteered Human Sensor Data into Crowd-sourced Platforms: A Use Case on Noise Pollution Monitoring and OpenStreetMap

Abstract

Local and national governments deploy environmental monitoring to improve decision making for sustainable development. Especially the monitoring and management of pollution such as noise is of local, national and European relevance, as expressed by the European Noise Directive (END) (European Parliament, 2002). The European Environment Agency (EEA) asks all its member and collaborating countries for information required by the END. However, it is expensive to deploy and maintain a network of sensors or to periodically measure the city with a moving sensor network. Hence, most of the reported data is based on computed models and only some data is captured by reference sensors deployed in the field. According to the END, the reported data is available as strategic noise maps. So far, these noise maps remain still in silos although they are managed in a Geographic Information Infrastructure (Murphy & King, 2010). Concurrently, crowd-sourced information is collected by citizens for environmental monitoring and specific platforms such as for collecting crowd-sourced noise measures become massively populated (Goodchild, 2007). However, this environmental information is rarely accessible to the public such as in the case of eye on earth1, due to a lack of applicable interfaces. This paper describes an approach to publish the captured crowd-sourced environmental information such as noise data to a more popular and open platform for increasing visibility and improving information access. In particular, this approach integrates the world-wide network of human sensors into an existing VGI platform such as Open Street Map. Using this platform allows users to directly integrate static data (captured roads) and dynamic data (e.g. noise).