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

Sensors

Manuel Castañón–Puga¹  Abby Stephanie Salazar²  Leocundo Aguilar²  Carelia Gaxiola-Pacheco²  Guillermo Licea² 

[1] Facultad de Ciencias Químicas e Ingeniería, Universidad Autónoma de Baja California, Calzada Universidad 14418, Tijuana 22390, Mexico

关键词: wireless networks;    indoor location;    location-based services;    wireless/mobile applications;    Type-2 fuzzy inference system;    data mining;   

DOI  :  10.3390/s151229791

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.