A Dynamic Bayesian Network Approach to Location Prediction in Ubiquitous Computing Environments

The ability to predict the future contexts of users significantly improves service quality and user satisfaction in ubiquitous computing environments. Location prediction is particularly useful because ubiquitous computing environments can dynamically adapt their behaviors according to a user's future location. In this paper, we present an inductive approach to recognizing a user's location by establishing a dynamic Bayesian network model. The dynamic Bayesian network model has been evaluated with a set of contextual data collected from undergraduate students. The evaluation result suggests that a dynamic Bayesian network model offers significant predictive power.