Feature-Based Room-Level Localization of Unmodified Smartphones

Jiaxing SHEN; Jiannong CAO; Xuefeng LIU; Jiaqi WEN; Yuanyi CHEN

doi:10.1007/978-3-319-33681-7_11

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 Proceedings › Conference paper (refereed) › Research › peer-review

10 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers
Editors	Veronika KRUTILOVA, Dagmar CAGÁŇOVÁ, Daniela ŠPIRKOVÁ, Julius GOLEJ, Kim NGUYEN, Radim LENORT, David HOLMAN, David STAŠ, Pavel WICHER, Alberto LEON-GARCIA
Publisher	Springer, Cham
Pages	125-136
Number of pages	12
ISBN (Electronic)	9783319336817
ISBN (Print)	9783319336800
DOIs	https://doi.org/10.1007/978-3-319-33681-7_11
Publication status	Published - 29 Jun 2016
Externally published	Yes
Event	SmartCity 360: International Summit Smart City 360° - Bratislava, Slovakia Duration: 13 Oct 2015 → 16 Oct 2015

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Volume	166
ISSN (Print)	1867-8211
ISSN (Electronic)	1867-822X

Conference

Conference	SmartCity 360: International Summit Smart City 360°
Country/Territory	Slovakia
City	Bratislava
Period	13/10/15 → 16/10/15

Funding

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

Keywords

Fingerprinting
Room-level localization
RSS

Access to Document

10.1007/978-3-319-33681-7_11

Cite this

SHEN, J., CAO, J., LIU, X., WEN, J., & CHEN, Y. (2016). Feature-Based Room-Level Localization of Unmodified Smartphones. In V. KRUTILOVA, D. CAGÁŇOVÁ, D. ŠPIRKOVÁ, J. GOLEJ, K. NGUYEN, R. LENORT, D. HOLMAN, D. STAŠ, P. WICHER, & A. LEON-GARCIA (Eds.), Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers (pp. 125-136). (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 166). Springer, Cham. https://doi.org/10.1007/978-3-319-33681-7_11

SHEN, Jiaxing ; CAO, Jiannong ; LIU, Xuefeng et al. / Feature-Based Room-Level Localization of Unmodified Smartphones. Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. editor / Veronika KRUTILOVA ; Dagmar CAGÁŇOVÁ ; Daniela ŠPIRKOVÁ ; Julius GOLEJ ; Kim NGUYEN ; Radim LENORT ; David HOLMAN ; David STAŠ ; Pavel WICHER ; Alberto LEON-GARCIA. Springer, Cham, 2016. pp. 125-136 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering).

@inproceedings{275bb68d52ff4f338a741bcda52e8ec6,

title = "Feature-Based Room-Level Localization of Unmodified Smartphones",

abstract = "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.",

keywords = "Fingerprinting, Room-level localization, RSS",

author = "Jiaxing SHEN and Jiannong CAO and Xuefeng LIU and Jiaqi WEN and Yuanyi CHEN",

year = "2016",

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booktitle = "Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers",

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SHEN, J, CAO, J, LIU, X, WEN, J & CHEN, Y 2016, Feature-Based Room-Level Localization of Unmodified Smartphones. in V KRUTILOVA, D CAGÁŇOVÁ, D ŠPIRKOVÁ, J GOLEJ, K NGUYEN, R LENORT, D HOLMAN, D STAŠ, P WICHER & A LEON-GARCIA (eds), Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 166, Springer, Cham, pp. 125-136, SmartCity 360: International Summit Smart City 360°, Bratislava, Slovakia, 13/10/15. https://doi.org/10.1007/978-3-319-33681-7_11

Feature-Based Room-Level Localization of Unmodified Smartphones. / SHEN, Jiaxing; CAO, Jiannong; LIU, Xuefeng et al.
Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. ed. / Veronika KRUTILOVA; Dagmar CAGÁŇOVÁ; Daniela ŠPIRKOVÁ; Julius GOLEJ; Kim NGUYEN; Radim LENORT; David HOLMAN; David STAŠ; Pavel WICHER; Alberto LEON-GARCIA. Springer, Cham, 2016. p. 125-136 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Vol. 166).

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

TY - GEN

T1 - Feature-Based Room-Level Localization of Unmodified Smartphones

AU - SHEN, Jiaxing

AU - CAO, Jiannong

AU - LIU, Xuefeng

AU - WEN, Jiaqi

AU - CHEN, Yuanyi

PY - 2016/6/29

Y1 - 2016/6/29

N2 - 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.

AB - 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.

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DO - 10.1007/978-3-319-33681-7_11

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SN - 9783319336800

T3 - Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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BT - Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers

A2 - KRUTILOVA, Veronika

A2 - CAGÁŇOVÁ, Dagmar

A2 - ŠPIRKOVÁ, Daniela

A2 - GOLEJ, Julius

A2 - NGUYEN, Kim

A2 - LENORT, Radim

A2 - HOLMAN, David

A2 - STAŠ, David

A2 - WICHER, Pavel

A2 - LEON-GARCIA, Alberto

PB - Springer, Cham

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SHEN J, CAO J, LIU X, WEN J, CHEN Y. Feature-Based Room-Level Localization of Unmodified Smartphones. In KRUTILOVA V, CAGÁŇOVÁ D, ŠPIRKOVÁ D, GOLEJ J, NGUYEN K, LENORT R, HOLMAN D, STAŠ D, WICHER P, LEON-GARCIA A, editors, Smart City 360 - 1st EAI International Summit, Smart City 360, Revised Selected Papers. Springer, Cham. 2016. p. 125-136. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering). Epub 2016 Jun 29. doi: 10.1007/978-3-319-33681-7_11

Feature-Based Room-Level Localization of Unmodified Smartphones

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