Urban Context Detection and Context-Aware Recommendation via Networks of Humans as Sensors
Communications in Computer and Information Science
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
... can be used to provide services to the end-users. Keywords: social networks, smart mobile devices, human as a sensor, recommender systems 1. improve knowledge obtained from other data generation approaches, such as GPS pattern analysis, 2. detect unexpected situations in the city that may affect large groups of people at a certain location, e.g., public demonstrations or celebrations, sudden traffic jams caused by accidents, and 3. enable services to users that exploit such generated knowledge, providing novel kinds of real-time information and recommendation. The paper presents, due to space constraints, just a general overview of the problems we tackle, the preliminar results of the parts already implemented, and the future work. For deeper reports on the technical details, please refer to the related deliverables 1 and to  . This paper is structured as follows: in §2 we introduce SUPERHUB, an urban mobility-related EU project; §3 contains an explanation of the extent of the contextual detection, focusing on social network data; §4 explains how the contextual information generated can be used to provide services for the end-users; and finally §5 presents related work and wraps up the paper with conclusions.