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Sensors 2018, 18(1), 205; https://doi.org/10.3390/s18010205

Plils: A Practical Indoor Localization System through Less Expensive Wireless Chips via Subregion Clustering

1
Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Hunan University of Commerce, Changsha 410205, China
2
Mobile E-business Collaborative Innovation Center of Hunan Province, Hunan University of Commerce, Changsha 410205, China
3
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
4
School of Information Engineering, Guilin Unversity of Technology, Guilin 541000, China
*
Author to whom correspondence should be addressed.
Received: 13 September 2017 / Revised: 3 January 2018 / Accepted: 8 January 2018 / Published: 12 January 2018
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Abstract

Reducing costs is a pragmatic method for promoting the widespread usage of indoor localization technology. Conventional indoor localization systems (ILSs) exploit relatively expensive wireless chips to measure received signal strength for positioning. Our work is based on a cheap and widely-used commercial off-the-shelf (COTS) wireless chip, i.e., the Nordic Semiconductor nRF24LE1, which has only several output power levels, and proposes a new power level based-ILS, called Plils. The localization procedure incorporates two phases: an offline training phase and an online localization phase. In the offline training phase, a self-organizing map (SOM) is utilized for dividing a target area into k subregions, wherein their grids in the same subregion have similar fingerprints. In the online localization phase, the support vector machine (SVM) and back propagation (BP) neural network methods are adopted to identify which subregion a tagged object is located in, and calculate its exact location, respectively. The reasonable value for k has been discussed as well. Our experiments show that Plils achieves 75 cm accuracy on average, and is robust to indoor obstacles. View Full-Text
Keywords: wireless indoor localization system; subregion clustering; fingerprint; cheap communication chip wireless indoor localization system; subregion clustering; fingerprint; cheap communication chip
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Li, X.; Yang, Y.; Cai, J.; Deng, Y.; Yang, J.; Zhou, X.; Tan, L. Plils: A Practical Indoor Localization System through Less Expensive Wireless Chips via Subregion Clustering. Sensors 2018, 18, 205.

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