Abstract
Localization systems will evolve towards autonomous system which will use any useful information provided by mobile devices taking the hardware specification and environmental limitations into account. This paper demonstrates the concept of opportunistic localization using a smart phone with the following sensor technologies: Wi-Fi, GSM, GPS and two embedded accelerometers. A particle filter based estimator with an adaptive motion model is used to seamlessly fuse the different sensory readings. Real experiments in multi-floor, indoor-outdoor environments were conducted to analyze the performance of the proposed system. The achieved results using various sensor combinations are presented. © 2009 Springer Berlin Heidelberg.
Cite
CITATION STYLE
Weyn, M., Klepal, M., & Widyawan. (2009). Adaptive motion model for a smart phone based opportunistic localization system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5801 LNCS, pp. 50–65). https://doi.org/10.1007/978-3-642-04385-7_4
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