Explore places you travel using Android

Safety is naturally location dependent, it is also inherently volatile. It not only exhibits temporal patterns but also depends on the current context. Furthermore public safety has a personal dimension. Users of different backgrounds are likely to be impacted differently by the same location and time context. In this paper we investigate the combination of location and time indexed crime datasets, with mobile technologies and online Geo Social networks to provide personalized safety recommendations for mobile. Specifically, we first define location centric, weather condition, static crime and safety labels, based on recorded crime events that help in predicting the crime and safety index values of a particular location. Moreover, we use mobile device and geo social network technologies to record the trajectory trace of a user: the set of (location, time) pairs where the user has been present.