GraphLoc: a graph-based method for indoor subarea localization with zero-configuration

Yuanyi CHEN*, Minyi GUO, Jiaxing SHEN, Jiannong CAO

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

12 Citations (Scopus)


Indoor subarea localization can facilitate numerous location-based services, such as indoor navigation, indoor POI recommendation and mobile advertising. Most existing subarea localization approaches suffer from two bottlenecks, one is fingerprint-based methods require time-consuming site survey and another is triangulation-based methods are lack of scalability. In this paper, we propose a graph-based method for indoor subarea localization with zero-configuration. Zero-configuration means the proposed method can be directly employed in indoor environment without time-consuming site survey or pre-installing additional infrastructure. To accomplish this, we first utilize two unexploited characteristics of WiFi radio signal strength to generate logical floor graph and then formulate the problem of constructing fingerprint map as a graph isomorphism problem between logical floor graph and physical floor graph. In online localization phase, a Bayesian-based approach is utilized to estimate the unknown subarea. The proposed method has been implemented in a real-world shopping mall, and extensive experimental results show that the proposed method can achieve competitive performance comparing with existing methods.

Original languageEnglish
Pages (from-to)489-505
Number of pages17
JournalPersonal and Ubiquitous Computing
Issue number3
Early online date20 Feb 2017
Publication statusPublished - Jun 2017
Externally publishedYes

Bibliographical note

This work is sponsored by the National Basic Research 973 Program of China (No. 2015CB352403), the National Natural Science Foundation of China (NSFC) (61261160502, 61272099), the Program for National Natural Science Foundation of China/Research Grants Council (NSFC/RGC)(612191030), the Program for Changjiang Scholars and Innovative Research Team in University (IRT1158, PCSIRT), the Scientific Innovation Act of STCSM (13511504200), and EU FP7 CLIMBER Project (PIRSES-GA-2012-318939).


  • Graph-based matching
  • Subarea localization
  • WiFi radio signal strength
  • Zero-configuration


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  • A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration

    CHEN, Y., GUO, M., SHEN, J. & CAO, J., 16 Jan 2017, (E-pub ahead of print) 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld). EL BAZ, D. & BOURGEOIS, J. (eds.). IEEE, p. 236-244 9 p. (Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC).

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

    2 Citations (Scopus)

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