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Sensors 2016, 16(12), 2074;

A Self-Adaptive Model-Based Wi-Fi Indoor Localization Method

Faculty of Computer and Information Science, University of Ljubljana, Vecna pot 113, SI-1001 Ljubljana, Slovenia
Author to whom correspondence should be addressed.
Academic Editors: Lyudmila Mihaylova, Byung-Gyu Kim and Debi Prosad Dogra
Received: 30 September 2016 / Revised: 14 November 2016 / Accepted: 23 November 2016 / Published: 6 December 2016
(This article belongs to the Special Issue Scalable Localization in Wireless Sensor Networks)
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This paper presents a novel method for indoor localization, developed with the main aim of making it useful for real-world deployments. Many indoor localization methods exist, yet they have several disadvantages in real-world deployments—some are static, which is not suitable for long-term usage; some require costly human recalibration procedures; and others require special hardware such as Wi-Fi anchors and transponders. Our method is self-calibrating and self-adaptive thus maintenance free and based on Wi-Fi only. We have employed two well-known propagation models—free space path loss and ITU models—which we have extended with additional parameters for better propagation simulation. Our self-calibrating procedure utilizes one propagation model to infer parameters of the space and the other to simulate the propagation of the signal without requiring any additional hardware beside Wi-Fi access points, which is suitable for real-world usage. Our method is also one of the few model-based Wi-Fi only self-adaptive approaches that do not require the mobile terminal to be in the access-point mode. The only input requirements of the method are Wi-Fi access point positions, and positions and properties of the walls. Our method has been evaluated in single- and multi-room environments, with measured mean error of 2–3 and 3–4 m, respectively, which is similar to existing methods. The evaluation has proven that usable localization accuracy can be achieved in real-world environments solely by the proposed Wi-Fi method that relies on simple hardware and software requirements. View Full-Text
Keywords: indoor positioning; Wi-Fi localization; propagation model; self-adaptive; received signal strength (RSS) indoor positioning; Wi-Fi localization; propagation model; self-adaptive; received signal strength (RSS)

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Tuta, J.; Juric, M.B. A Self-Adaptive Model-Based Wi-Fi Indoor Localization Method. Sensors 2016, 16, 2074.

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