Author:
Carrera F.,Guerin S.,Thorp J. B.
Abstract
Abstract. This paper traces the genesis and development of StreetBump, a smartphone application to map the location of potholes in Boston, Massachusetts. StreetBump belongs to a special category of "subliminal" crowdsourcing mobile applications that turn humans into sensors. Once started, it automatically collects road condition information without any human intervention, using the accelerometers and GPS inside smartphones. The StreetBump app evolved from a hardware device designed and built by WPI’s City Lab starting in 2003, which was originally intended to measure and map boat wakes in the city of Venice, Italy (Chiu, 2004). A second version of the custom hardware with onboard GPS and accelerometers was adapted to use in Boston, Massachusetts, to map road damage (potholes) in 2006 (Angelini, 2006). In 2009, Prof. Carrera proposed to the newly created office of New Urban Mechanics in the City of Boston to migrate the concept to Smartphones, based on the Android platform. The first prototype of the mobile app, called StreetBump, was released in 2010 by the authors (Harmon, 2010). In 2011, the app provided the basis for a worldwide Innocentive competition to develop the best postprocessing algorithms to identify the real potholes vs. other phone bumps (Moskowitz, 2011). Starting in 2012, the City of Boston has begun using a subsequent version of the app to operationally manage road repairs based on the data collected by StreetBump. The novelty of this app is not purely technological, but lies also in the top-to-bottom crowdsourcing of all its components. The app was designed to rely on the crowd to confirm the presence of damage though repeat hits (or lack thereof) as more users travel the same roads over time. Moreover, the non-trivial post-processing of the StreetBump data was itself the subject of a crowdsourced competition through an Innocentive challenge for the best algorithm. The release of the StreetBump code as open-source allowed the development of the final version of the app now used on a daily basis by the Department of Public Works in Boston, thus making it perhaps the first example of an app that was crowdsourced “from soup to nuts”.
Cited by
22 articles.
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