A method for predicting future location of mobile user for location-based services system
Convergence of location-aware devices, wireless communications, and geographic information system (GIS) functionalities has been enabling the deployment of a new generation of selective information disseminating services and location-based services (LBSs). Current LBSs use information about current locations of users to provide services, such as nearest features of interest, they request. Although the common computing strategy in LBSs benefits the users, there are additional benefits when future locations are predicted. One major advantage of location prediction is that it provides LBSs with extended resources, mainly time, to improve system reliability which in turn increases the users' confidence and the demand for LBSs. In this study, we propose a movement Rule-based Location Prediction method (RLP), to guess the user's future location for LBSs. Its performance is assessed with respect to precision and recall. In comparison with the previous technique, the prediction accuracy of ours is higher. With the proposed approach, we give an efficient support to the LBSs provider in monitoring user intelligently and sending information to user in a push-driven fashion. Apart from the support of timely and desired services and enhanced automation, the technique helps overcome some existing issues such as network flooding due to the massive tracking of users, the latencies of the positioning systems in providing and information delivery. Accordingly, the positioning is more reliable, which enables the service provider to effectively and efficiently offer location-based services with high frequency. (c) 2008 Elsevier Ltd. All rights reserved.
location-based services location prediction trajectory movement rules