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Sensors 2015, 15(12), 30142-30164; doi:10.3390/s151229791

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

Facultad de Ciencias Químicas e Ingeniería, Universidad Autónoma de Baja California, Calzada Universidad 14418, Tijuana 22390, Mexico
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Author to whom correspondence should be addressed.
Academic Editor: Kourosh Khoshelham
Received: 1 October 2015 / Revised: 19 November 2015 / Accepted: 24 November 2015 / Published: 2 December 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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Abstract

The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information. View Full-Text
Keywords: wireless networks; indoor location; location-based services; wireless/mobile applications; Type-2 fuzzy inference system; data mining wireless networks; indoor location; location-based services; wireless/mobile applications; Type-2 fuzzy inference system; data mining
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Castañón–Puga, M.; Salazar, A.S.; Aguilar, L.; Gaxiola-Pacheco, C.; Licea, G. A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals. Sensors 2015, 15, 30142-30164.

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