Exploiting indoor location and mobile information for context-awareness service

Personal mobile devices such as cellular phones, smart phones and PMPs have advanced incredibly in the past decade. The mobile technologies make research on the life log and user-context awareness feasible. In other words, sensors in mobile devices can collect the variety of user’s information, and various works have been conducted using that information. Most of works used a user’s location information as the most useful clue to recognize the user context. However, the location information in the conventional works usually depends on a GPS receiver that has limited function, because it cannot localize a person in a building and thus lowers the performance of the user-context awareness. This paper develops a system to solve such problems and to infer a user’s hidden information more accurately using Bayesian network and indoor-location information. Also, this paper presents a new technique for localization in a building using a decision tree and signals for the Wireless LAN because the decision tree has many advantages which outweigh other localization techniques.

► To propose a simple, yet powerful, technique for indoor localization specific to context awareness.
► To propose new techniques for localization in a building using decision tree and wireless LAN signal.
► To develop a system to infer user’s context by adopting Bayesian network and the indoor localization technique together.