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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2718-2723
Number of pages6
Volume2017-January
ISBN (Electronic)9781538616451
DOIs
Publication statusPublished - 2017 Nov 27
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: 2017 Oct 52017 Oct 8

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
CountryCanada
CityBanff
Period17/10/517/10/8

    Fingerprint

All Science Journal Classification (ASJC) codes

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

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 (Vol. 2017-January, pp. 2718-2723). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2017.8123037