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

Yuanyi CHEN; Minyi GUO; Jiaxing SHEN; Jiannong CAO

doi:10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054

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

Yuanyi CHEN, Minyi GUO, Jiaxing SHEN, Jiannong CAO

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

2 Citations (Scopus)

Abstract

Indoor subarea localization remains an open problem due to existing studies face two main bottlenecks, one is fingerprint-based methods require time-consuming site survey, another is triangulation-based methods is lack of scalability in large-scale environment. In this paper, we aim to present a graph-based method for indoor subarea localization with zero-configuration, which can be directly employed without offline manually constructing fingerprint map or pre-installing additional infrastructure. To accomplish this, we first utilize two unexploited characteristics of WiFi radio signal strength to generate logical floor graph,, then formulate the problem of constructing fingerprint map in terms of a graph isomorphism problem between logical floor graph, physical floor graph. Then, a Bayesian-based approach is utilized to estimate the unknown subarea in online localization. The proposed method has been implemented in a real-world shopping mall, extensive experimental results show that our method can achieve competitive performance comparing with existing methods.

Original language	English
Title of host publication	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)
Editors	Didier EL BAZ, Julien BOURGEOIS
Publisher	IEEE
Pages	236-244
Number of pages	9
ISBN (Electronic)	9781509027712
DOIs	https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054
Publication status	E-pub ahead of print - 16 Jan 2017
Externally published	Yes
Event	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) - Toulouse, France Duration: 18 Jul 2016 → 21 Jul 2016

Publication series

Name	Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

Conference

Conference	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)
Country/Territory	France
City	Toulouse
Period	18/07/16 → 21/07/16

Keywords

Graph mapping
Indoor subarea localization
Radio signal strength
Zero-configuration

Access to Document

10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054

Cite this

CHEN, Y., GUO, M., SHEN, J., & CAO, J. (2017). A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration. In D. EL BAZ, & J. BOURGEOIS (Eds.), 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) (pp. 236-244). (Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC). IEEE. Advance online publication. https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054

CHEN, Yuanyi ; GUO, Minyi ; SHEN, Jiaxing et al. / A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration. 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). editor / Didier EL BAZ ; Julien BOURGEOIS. IEEE, 2017. pp. 236-244 (Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC).

@inproceedings{59f0f98d5a334a3dba7465a15480d2d3,

title = "A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration",

abstract = "Indoor subarea localization remains an open problem due to existing studies face two main bottlenecks, one is fingerprint-based methods require time-consuming site survey, another is triangulation-based methods is lack of scalability in large-scale environment. In this paper, we aim to present a graph-based method for indoor subarea localization with zero-configuration, which can be directly employed without offline manually constructing fingerprint map or pre-installing additional infrastructure. To accomplish this, we first utilize two unexploited characteristics of WiFi radio signal strength to generate logical floor graph,, then formulate the problem of constructing fingerprint map in terms of a graph isomorphism problem between logical floor graph, physical floor graph. Then, a Bayesian-based approach is utilized to estimate the unknown subarea in online localization. The proposed method has been implemented in a real-world shopping mall, extensive experimental results show that our method can achieve competitive performance comparing with existing methods.",

keywords = "Graph mapping, Indoor subarea localization, Radio signal strength, Zero-configuration",

author = "Yuanyi CHEN and Minyi GUO and Jiaxing SHEN and Jiannong CAO",

year = "2017",

month = jan,

day = "16",

doi = "10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054",

language = "English",

series = "Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC",

publisher = "IEEE",

pages = "236--244",

editor = "{EL BAZ}, Didier and Julien BOURGEOIS",

booktitle = "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)",

note = "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) ; Conference date: 18-07-2016 Through 21-07-2016",

}

CHEN, Y, GUO, M, SHEN, J & CAO, J 2017, A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration. in D EL BAZ & J BOURGEOIS (eds), 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). Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC, IEEE, pp. 236-244, 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), Toulouse, France, 18/07/16. https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054

A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration. / CHEN, Yuanyi; GUO, Minyi; SHEN, Jiaxing et al.
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). ed. / Didier EL BAZ; Julien BOURGEOIS. IEEE, 2017. p. 236-244 (Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration

AU - CHEN, Yuanyi

AU - GUO, Minyi

AU - SHEN, Jiaxing

AU - CAO, Jiannong

PY - 2017/1/16

Y1 - 2017/1/16

N2 - Indoor subarea localization remains an open problem due to existing studies face two main bottlenecks, one is fingerprint-based methods require time-consuming site survey, another is triangulation-based methods is lack of scalability in large-scale environment. In this paper, we aim to present a graph-based method for indoor subarea localization with zero-configuration, which can be directly employed without offline manually constructing fingerprint map or pre-installing additional infrastructure. To accomplish this, we first utilize two unexploited characteristics of WiFi radio signal strength to generate logical floor graph,, then formulate the problem of constructing fingerprint map in terms of a graph isomorphism problem between logical floor graph, physical floor graph. Then, a Bayesian-based approach is utilized to estimate the unknown subarea in online localization. The proposed method has been implemented in a real-world shopping mall, extensive experimental results show that our method can achieve competitive performance comparing with existing methods.

AB - Indoor subarea localization remains an open problem due to existing studies face two main bottlenecks, one is fingerprint-based methods require time-consuming site survey, another is triangulation-based methods is lack of scalability in large-scale environment. In this paper, we aim to present a graph-based method for indoor subarea localization with zero-configuration, which can be directly employed without offline manually constructing fingerprint map or pre-installing additional infrastructure. To accomplish this, we first utilize two unexploited characteristics of WiFi radio signal strength to generate logical floor graph,, then formulate the problem of constructing fingerprint map in terms of a graph isomorphism problem between logical floor graph, physical floor graph. Then, a Bayesian-based approach is utilized to estimate the unknown subarea in online localization. The proposed method has been implemented in a real-world shopping mall, extensive experimental results show that our method can achieve competitive performance comparing with existing methods.

KW - Graph mapping

KW - Indoor subarea localization

KW - Radio signal strength

KW - Zero-configuration

UR - http://www.scopus.com/inward/record.url?scp=85013212345&partnerID=8YFLogxK

U2 - 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054

DO - 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054

M3 - Conference paper (refereed)

AN - SCOPUS:85013212345

T3 - Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

SP - 236

EP - 244

BT - 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)

A2 - EL BAZ, Didier

A2 - BOURGEOIS, Julien

PB - IEEE

T2 - 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)

Y2 - 18 July 2016 through 21 July 2016

ER -

CHEN Y, GUO M, SHEN J, CAO J. A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration. In EL BAZ D, BOURGEOIS J, editors, 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). IEEE. 2017. p. 236-244. (Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC). Epub 2017 Jan 16. doi: 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054

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

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

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

Cite this