An adaptive location prediction model based on fuzzy control

We focus on the proactivity feature of mobile applications. We propose a short-memory adaptive location predictor that realizes mobility prediction in the absence of extensive historical mobility information. Our predictor is based on a local linear regression model, while its adaptation capability is achieved through a fuzzy controller. Such fuzzy controller capitalizes on an appropriate size of historical mobility information in order to minimize the location prediction error and provide fast adaptation to any detected movement change. Our prediction experiments, performed with real GPS data, show the predictability and adaptability of the proposed location predictor.