SmartCity 360 2016, SmartCity 360 2015: Smart City 360° pp 125-136 | Cite as

Feature-Based Room-Level Localization of Unmodified Smartphones

  • Jiaxing ShenEmail author
  • Jiannong Cao
  • Xuefeng Liu
  • Jiaqi Wen
  • Yuanyi Chen
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 166)


Locating smartphone users will enable numerous potential applications such as monitoring customers in shopping malls. However, conventional received signal strength (RSS)-based room-level localization methods are not likely to distinguish neighboring zones accurately due to similar RSS fingerprints. We solve this problem by proposing a system called feature-based room-level localization (FRL). FRL is based on an observation that different rooms vary in internal structures and human activities which can be reflected by RSS fluctuation ranges and user dwell time respectively. These two features combing with RSS can be exploited to improve the localization accuracy. To enable localization of unmodified smartphones, FRL utilizes probe requests, which are periodically broadcast by smartphones to discover nearby access points (APs). Experiments indicate that FRL can reliably locate users in neighboring zones and achieve a 10 % accuracy gain, compared with conventional methods like the histogram method.


Room-level localization RSS Fingerprinting 



The research was partially supported by NSFC/RGC Joint Research Scheme under Grant N_PolyU519/12, and NSFC under Grant 61332004.


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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016

Authors and Affiliations

  • Jiaxing Shen
    • 1
    Email author
  • Jiannong Cao
    • 1
  • Xuefeng Liu
    • 1
  • Jiaqi Wen
    • 1
  • Yuanyi Chen
    • 2
  1. 1.The Hong Kong Polytechnic UniversityHong KongChina
  2. 2.Shanghai Jiao Tong UniversityShanghaiChina

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