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.
Keywords
- Wireless Sensor Network
- Mobile Node
- Receive Signal Strength
- Receive Signal Strength Indicator
- Reference Node
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Zhang, W., Wang, Y., Chen, L., Liu, Y., Rao, Y. (2013). A Hybrid Indoor Positioning Approach for Supermarkets. In: Ghose, A., et al. Service-Oriented Computing - ICSOC 2012 Workshops. ICSOC 2012. Lecture Notes in Computer Science, vol 7759. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37804-1_31
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DOI: https://doi.org/10.1007/978-3-642-37804-1_31
Publisher Name: Springer, Berlin, Heidelberg
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