Feature-Based Room-Level Localization of Unmodified Smartphones

Jiaxing SHEN*, Jiannong CAO, Xuefeng LIU, Jiaqi WEN, Yuanyi CHEN

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

10 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationSmart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers
EditorsVeronika KRUTILOVA, Dagmar CAGÁŇOVÁ, Daniela ŠPIRKOVÁ, Julius GOLEJ, Kim NGUYEN, Radim LENORT, David HOLMAN, David STAŠ, Pavel WICHER, Alberto LEON-GARCIA
PublisherSpringer, Cham
Number of pages12
ISBN (Electronic)9783319336817
ISBN (Print)9783319336800
Publication statusE-pub ahead of print - 29 Jun 2016
Externally publishedYes
EventSmartCity 360: International Summit Smart City 360° - Bratislava, Slovakia
Duration: 13 Oct 201516 Oct 2015

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
ISSN (Print)1867-8211
ISSN (Electronic)1867-822X


ConferenceSmartCity 360: International Summit Smart City 360°

Bibliographical note

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


  • Fingerprinting
  • Room-level localization
  • RSS


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