A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues

Hao Li; Joseph K Y Ng; Shuwei Qiu

doi:10.1007/978-3-319-98530-5_49

A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues

Hao Li^*, Joseph K Y Ng, Shuwei Qiu

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

In this paper, we focus on the Wi-Fi based indoor localization in large exhibition venues. We identify and describe the real-world problems in this scenario and present our system. We adopt a passive way to detect mobile devices with the consideration of users’ preference and iOS devices’ privacy issue, and collect signal strength data in a distributed manner which meets the practical demand in exhibition venues and save the power consumption of mobile devices. Since exhibition venues have many restrictions on traditional localization approaches, we propose our approach and solution to fit these special conditions. We propose the clustering and Gaussian process regression (GPR) method to improve localization accuracy. Series of experiments in Hong Kong Convention and Exhibition Centre (HKCEC) show our system’s feasibility and effectiveness. Our approach has significant improvement in the localization accuracy when compared with traditional trilateration, fingerprinting and the state-of-the-art approaches.

Original language	English
Title of host publication	Advances in Network-Based Information Systems
Subtitle of host publication	The 21st International Conference on Network-Based Information Systems (NBiS-2018)
Editors	Leonard Barolli, Natalia Kryvinska, Tomoya Enokido, Makoto Takizawa
Publisher	Springer Cham
Pages	568-577
Number of pages	10
Edition	1st
ISBN (Electronic)	9783319985305
ISBN (Print)	9783319985299
DOIs	https://doi.org/10.1007/978-3-319-98530-5_49
Publication status	Published - 28 Aug 2018
Event	21st International Conference on Network-Based Information Systems, NBiS 2018 - Bratislava, Slovakia Duration: 5 Sept 2018 → 7 Sept 2018

Publication series

Name	Lecture Notes on Data Engineering and Communications Technologies
Volume	22
ISSN (Print)	2367-4512
ISSN (Electronic)	2367-4520

Conference

Conference	21st International Conference on Network-Based Information Systems, NBiS 2018
Country/Territory	Slovakia
City	Bratislava
Period	5/09/18 → 7/09/18

Scopus Subject Areas

Media Technology
Electrical and Electronic Engineering
Computer Science Applications
Computer Networks and Communications
Information Systems

User-Defined Keywords

Clustering
Distributed data acquisition
Exhibition venues
Gaussian process regression
Wi-Fi localization

Access to Document

10.1007/978-3-319-98530-5_49

Cite this

Li, H., Ng, J. K. Y., & Qiu, S. (2018). A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues. In L. Barolli, N. Kryvinska, T. Enokido, & M. Takizawa (Eds.), Advances in Network-Based Information Systems: The 21st International Conference on Network-Based Information Systems (NBiS-2018) (1st ed., pp. 568-577). (Lecture Notes on Data Engineering and Communications Technologies; Vol. 22). Springer Cham. https://doi.org/10.1007/978-3-319-98530-5_49

Li, Hao ; Ng, Joseph K Y ; Qiu, Shuwei. / A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues. Advances in Network-Based Information Systems: The 21st International Conference on Network-Based Information Systems (NBiS-2018). editor / Leonard Barolli ; Natalia Kryvinska ; Tomoya Enokido ; Makoto Takizawa. 1st. ed. Springer Cham, 2018. pp. 568-577 (Lecture Notes on Data Engineering and Communications Technologies).

@inproceedings{63e7e99e379d433e84d74f4c1a2daa7d,

title = "A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues",

abstract = "In this paper, we focus on the Wi-Fi based indoor localization in large exhibition venues. We identify and describe the real-world problems in this scenario and present our system. We adopt a passive way to detect mobile devices with the consideration of users{\textquoteright} preference and iOS devices{\textquoteright} privacy issue, and collect signal strength data in a distributed manner which meets the practical demand in exhibition venues and save the power consumption of mobile devices. Since exhibition venues have many restrictions on traditional localization approaches, we propose our approach and solution to fit these special conditions. We propose the clustering and Gaussian process regression (GPR) method to improve localization accuracy. Series of experiments in Hong Kong Convention and Exhibition Centre (HKCEC) show our system{\textquoteright}s feasibility and effectiveness. Our approach has significant improvement in the localization accuracy when compared with traditional trilateration, fingerprinting and the state-of-the-art approaches.",

keywords = "Clustering, Distributed data acquisition, Exhibition venues, Gaussian process regression, Wi-Fi localization",

author = "Hao Li and Ng, {Joseph K Y} and Shuwei Qiu",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 21st International Conference on Network-Based Information Systems, NBiS 2018 ; Conference date: 05-09-2018 Through 07-09-2018",

year = "2018",

month = aug,

day = "28",

doi = "10.1007/978-3-319-98530-5_49",

language = "English",

isbn = "9783319985299",

series = "Lecture Notes on Data Engineering and Communications Technologies",

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editor = "Leonard Barolli and Natalia Kryvinska and Tomoya Enokido and Makoto Takizawa",

booktitle = "Advances in Network-Based Information Systems",

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Li, H, Ng, JKY & Qiu, S 2018, A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues. in L Barolli, N Kryvinska, T Enokido & M Takizawa (eds), Advances in Network-Based Information Systems: The 21st International Conference on Network-Based Information Systems (NBiS-2018). 1st edn, Lecture Notes on Data Engineering and Communications Technologies, vol. 22, Springer Cham, pp. 568-577, 21st International Conference on Network-Based Information Systems, NBiS 2018, Bratislava, Slovakia, 5/09/18. https://doi.org/10.1007/978-3-319-98530-5_49

A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues. / Li, Hao; Ng, Joseph K Y; Qiu, Shuwei.
Advances in Network-Based Information Systems: The 21st International Conference on Network-Based Information Systems (NBiS-2018). ed. / Leonard Barolli; Natalia Kryvinska; Tomoya Enokido; Makoto Takizawa. 1st. ed. Springer Cham, 2018. p. 568-577 (Lecture Notes on Data Engineering and Communications Technologies; Vol. 22).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues

AU - Li, Hao

AU - Ng, Joseph K Y

AU - Qiu, Shuwei

PY - 2018/8/28

Y1 - 2018/8/28

N2 - In this paper, we focus on the Wi-Fi based indoor localization in large exhibition venues. We identify and describe the real-world problems in this scenario and present our system. We adopt a passive way to detect mobile devices with the consideration of users’ preference and iOS devices’ privacy issue, and collect signal strength data in a distributed manner which meets the practical demand in exhibition venues and save the power consumption of mobile devices. Since exhibition venues have many restrictions on traditional localization approaches, we propose our approach and solution to fit these special conditions. We propose the clustering and Gaussian process regression (GPR) method to improve localization accuracy. Series of experiments in Hong Kong Convention and Exhibition Centre (HKCEC) show our system’s feasibility and effectiveness. Our approach has significant improvement in the localization accuracy when compared with traditional trilateration, fingerprinting and the state-of-the-art approaches.

AB - In this paper, we focus on the Wi-Fi based indoor localization in large exhibition venues. We identify and describe the real-world problems in this scenario and present our system. We adopt a passive way to detect mobile devices with the consideration of users’ preference and iOS devices’ privacy issue, and collect signal strength data in a distributed manner which meets the practical demand in exhibition venues and save the power consumption of mobile devices. Since exhibition venues have many restrictions on traditional localization approaches, we propose our approach and solution to fit these special conditions. We propose the clustering and Gaussian process regression (GPR) method to improve localization accuracy. Series of experiments in Hong Kong Convention and Exhibition Centre (HKCEC) show our system’s feasibility and effectiveness. Our approach has significant improvement in the localization accuracy when compared with traditional trilateration, fingerprinting and the state-of-the-art approaches.

KW - Clustering

KW - Distributed data acquisition

KW - Exhibition venues

KW - Gaussian process regression

KW - Wi-Fi localization

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T3 - Lecture Notes on Data Engineering and Communications Technologies

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A2 - Kryvinska, Natalia

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PB - Springer Cham

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Y2 - 5 September 2018 through 7 September 2018

ER -

Li H, Ng JKY, Qiu S. A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues. In Barolli L, Kryvinska N, Enokido T, Takizawa M, editors, Advances in Network-Based Information Systems: The 21st International Conference on Network-Based Information Systems (NBiS-2018). 1st ed. Springer Cham. 2018. p. 568-577. (Lecture Notes on Data Engineering and Communications Technologies). doi: 10.1007/978-3-319-98530-5_49

A Practical Indoor Localization System with Distributed Data Acquisition for Large Exhibition Venues

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