Abstract
A navigation service that can provide positioning functionalities is benefitial to both customers and supermarkets. Although there are quite a number of indoor positioning algorithms, the accuracy of the existing approaches is not very satisfying. In this paper, we propose a hybrid approach that combines Weighted Centroid Localizatioin Algorithm, Dynamic Position Tracking Model and Location Approximation Algorithm based on Received Signal Strength. The evaluations show that the proposed approach can achieve better accuracy than the existing approaches, with approximately 20% to 40% improvement. © Springer-Verlag 2013.
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CITATION STYLE
Zhang, W., Wang, Y., Chen, L., Liu, Y., & Rao, Y. (2013). A hybrid indoor positioning approach for supermarkets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7759 LNCS, pp. 306–316). https://doi.org/10.1007/978-3-642-37804-1_31
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