A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals
AbstractThe 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
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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.
Castañón–Puga M, Salazar AS, 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(12):30142-30164.Chicago/Turabian Style
Castañón–Puga, Manuel; Salazar, Abby S.; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo. 2015. "A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals." Sensors 15, no. 12: 30142-30164.