Autonomous construction of a WiFi access point map using multidimensional scaling

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Abstract

To construct a WiFi positioning system, dedicated individuals usually gather radio scans with ground truth data. This laborious operation limits the widespread use of WiFi-based locating system. Off-the-shelf smartphones have the capability to scan radio signals from WiFi Access Points (APs). In this paper we propose a scheme to construct a map of WiFi AP positions autonomously without ground truth information. From radio scans, we extract dissimilarities between pairs of WiFi APs, then analyze the dissimilarities to produce a geometric configuration of WiFi APs based on a multidimensional scaling technique. To validate our scheme, we conducted experiments on five floors of an office building that has an area of 50 m by 35 m in each floor. WiFi APs were located within a 10m error range, and floors of APs are recognized without error. © 2011 Springer-Verlag.

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Koo, J., & Cha, H. (2011). Autonomous construction of a WiFi access point map using multidimensional scaling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6696 LNCS, pp. 115–132). https://doi.org/10.1007/978-3-642-21726-5_8

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