Mobile Sensing of User’s Motion and Position Context for Automatic Check-in Suggestion and Validation

Abstract

Users are increasingly interested in mobile social applications that allow them to share opinions, comments and votes about places (restaurants, shops, etc.). Among these, check-in applications are spreading rapidly. In this paper we illustrate a system able to automatically validate users' check-in in a place exploiting device's sensors and inferred knowledge of context (motion activity, nearby friends). Additionally, the system allows check-in suggestion to users staying in a place for a required amount of time. A description of the service scenario, of the architecture and its technical components is given, focusing on how raw context data from accelerometer onboard the device is used to recognize users' motion situation and how it is combined with GPS position to validate check-ins.