Enhanced indoor localization in home environments using appearance frequency information

Jonghoon Shin; Hyunchoong Kim; Dayoung Lee; Yohan Ko; Kyoungwoo Lee; Seong Il Hahm; Taejun Kwon

doi:10.1109/SMC.2017.8123037

Enhanced indoor localization in home environments using appearance frequency information

Jonghoon Shin, Hyunchoong Kim, Dayoung Lee, Yohan Ko, Kyoungwoo Lee, Seong Il Hahm, Taejun Kwon

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Recognizing the location of an individual in a home environment is crucial in order to enable various context-aware home applications such as elderly health monitoring and in home appliance automation. However, due to the limited number of dedicated Wi-Fi access points (APs), it is challenging to guarantee the reliable localization performance in a home environment by using the traditional Wi-Fi fingerprinting (WF) technique. In this paper, we propose a room-level localization system for the typical residential home environments which comprise of a living room, a kitchen, a bathroom, and a bedroom. Specifically, we make use of appearance frequency (AF) information of APs at each location in order to narrow down the number of candidate locations before performing the Wi-Fi Fingerprinting scheme. Our system improves the localization performance by up to 17.5 % (11.29 % on average) over that of the traditional WF-based approach which does not exploit AF information. We achieved the room-level positioning accuracy of 84.76% on the dataset of 6 home environments.

Original language	English
Title of host publication	2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2718-2723
Number of pages	6
ISBN (Electronic)	9781538616451
DOIs	https://doi.org/10.1109/SMC.2017.8123037
Publication status	Published - 2017 Nov 27
Event	2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada Duration: 2017 Oct 5 → 2017 Oct 8

Publication series

Name	2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Volume	2017-January

Other

Other	2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Country/Territory	Canada
City	Banff
Period	17/10/5 → 17/10/8

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Science Applications
Human-Computer Interaction
Control and Optimization

Access to Document

10.1109/SMC.2017.8123037

Cite this

Shin, J., Kim, H., Lee, D., Ko, Y., Lee, K., Hahm, S. I., & Kwon, T. (2017). Enhanced indoor localization in home environments using appearance frequency information. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 (pp. 2718-2723). (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2017.8123037

Shin, Jonghoon ; Kim, Hyunchoong ; Lee, Dayoung et al. / Enhanced indoor localization in home environments using appearance frequency information. 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2718-2723 (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017).

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title = "Enhanced indoor localization in home environments using appearance frequency information",

abstract = "Recognizing the location of an individual in a home environment is crucial in order to enable various context-aware home applications such as elderly health monitoring and in home appliance automation. However, due to the limited number of dedicated Wi-Fi access points (APs), it is challenging to guarantee the reliable localization performance in a home environment by using the traditional Wi-Fi fingerprinting (WF) technique. In this paper, we propose a room-level localization system for the typical residential home environments which comprise of a living room, a kitchen, a bathroom, and a bedroom. Specifically, we make use of appearance frequency (AF) information of APs at each location in order to narrow down the number of candidate locations before performing the Wi-Fi Fingerprinting scheme. Our system improves the localization performance by up to 17.5 % (11.29 % on average) over that of the traditional WF-based approach which does not exploit AF information. We achieved the room-level positioning accuracy of 84.76% on the dataset of 6 home environments.",

author = "Jonghoon Shin and Hyunchoong Kim and Dayoung Lee and Yohan Ko and Kyoungwoo Lee and Hahm, {Seong Il} and Taejun Kwon",

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Shin, J, Kim, H, Lee, D, Ko, Y, Lee, K, Hahm, SI & Kwon, T 2017, Enhanced indoor localization in home environments using appearance frequency information. in 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 2718-2723, 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017, Banff, Canada, 17/10/5. https://doi.org/10.1109/SMC.2017.8123037

Enhanced indoor localization in home environments using appearance frequency information. / Shin, Jonghoon; Kim, Hyunchoong; Lee, Dayoung et al.
2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2718-2723 (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - Recognizing the location of an individual in a home environment is crucial in order to enable various context-aware home applications such as elderly health monitoring and in home appliance automation. However, due to the limited number of dedicated Wi-Fi access points (APs), it is challenging to guarantee the reliable localization performance in a home environment by using the traditional Wi-Fi fingerprinting (WF) technique. In this paper, we propose a room-level localization system for the typical residential home environments which comprise of a living room, a kitchen, a bathroom, and a bedroom. Specifically, we make use of appearance frequency (AF) information of APs at each location in order to narrow down the number of candidate locations before performing the Wi-Fi Fingerprinting scheme. Our system improves the localization performance by up to 17.5 % (11.29 % on average) over that of the traditional WF-based approach which does not exploit AF information. We achieved the room-level positioning accuracy of 84.76% on the dataset of 6 home environments.

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Shin J, Kim H, Lee D, Ko Y, Lee K, Hahm SI et al. Enhanced indoor localization in home environments using appearance frequency information. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2718-2723. (2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017). doi: 10.1109/SMC.2017.8123037

Enhanced indoor localization in home environments using appearance frequency information

Abstract

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Bibliographical note

All Science Journal Classification (ASJC) codes

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