Urban context detection and context-aware recommendation via networks of 'humans as sensors'

The wide adoption of smart mobile devices makes the concept of human as a sensor possible, opening the door to new ways of solving recurrent problems that occur in everyday life by taking advantage of the information these devices can produce. In the case of this paper, we present part of the work done in the EU project SUPERHUB and introduce how geolocated positioning coming from such devices can be used to infer the current context of the city, e.g., disruptive events, and how this information can be used to provide services to the end-users.
Peer Reviewed
Postprint (author’s final draft)