Averaged kernel floor localization algorithm for multi-floor WLAN positioning

Multi-floor positioning is important especially to locate a user correctly in an urban area where multi-level buildings are located. In two-stage (vertical and horizontal) positioning, floor level is first determined prior to horizontal localization. Correct floor determination is crucial to ensure...

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Main Authors: Abd Rahman, Mohd Amiruddin, Abbas, Zulkifly
Format: Conference or Workshop Item
Language:English
Published: 2017
Online Access:http://psasir.upm.edu.my/id/eprint/64389/1/ENG%20%26%20New%20Tech%20Oral%20111117%2032.pdf
http://psasir.upm.edu.my/id/eprint/64389/
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Institution: Universiti Putra Malaysia
Language: English
id my.upm.eprints.64389
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spelling my.upm.eprints.643892018-07-05T09:25:25Z http://psasir.upm.edu.my/id/eprint/64389/ Averaged kernel floor localization algorithm for multi-floor WLAN positioning Abd Rahman, Mohd Amiruddin Abbas, Zulkifly Multi-floor positioning is important especially to locate a user correctly in an urban area where multi-level buildings are located. In two-stage (vertical and horizontal) positioning, floor level is first determined prior to horizontal localization. Correct floor determination is crucial to ensure proper database selection for horizontal localization. This paper proposes a floor localization algorithm, the averaged kernel floor, which applies clustering technique and kernel density function to estimate the floor location of the user. The results show that the floor level could be determined accurately up to 91.7% in the tested environment. Additionally, the proposed algorithm has very low processing time of about 29 times lower compared to previous floor localization algorithms. 2017 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/64389/1/ENG%20%26%20New%20Tech%20Oral%20111117%2032.pdf Abd Rahman, Mohd Amiruddin and Abbas, Zulkifly (2017) Averaged kernel floor localization algorithm for multi-floor WLAN positioning. In: 5th International Symposium on Applied Engineering and Sciences (SAES2017), 14-15 Nov. 2017, Universiti Putra Malaysia. (p. 32).
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Multi-floor positioning is important especially to locate a user correctly in an urban area where multi-level buildings are located. In two-stage (vertical and horizontal) positioning, floor level is first determined prior to horizontal localization. Correct floor determination is crucial to ensure proper database selection for horizontal localization. This paper proposes a floor localization algorithm, the averaged kernel floor, which applies clustering technique and kernel density function to estimate the floor location of the user. The results show that the floor level could be determined accurately up to 91.7% in the tested environment. Additionally, the proposed algorithm has very low processing time of about 29 times lower compared to previous floor localization algorithms.
format Conference or Workshop Item
author Abd Rahman, Mohd Amiruddin
Abbas, Zulkifly
spellingShingle Abd Rahman, Mohd Amiruddin
Abbas, Zulkifly
Averaged kernel floor localization algorithm for multi-floor WLAN positioning
author_facet Abd Rahman, Mohd Amiruddin
Abbas, Zulkifly
author_sort Abd Rahman, Mohd Amiruddin
title Averaged kernel floor localization algorithm for multi-floor WLAN positioning
title_short Averaged kernel floor localization algorithm for multi-floor WLAN positioning
title_full Averaged kernel floor localization algorithm for multi-floor WLAN positioning
title_fullStr Averaged kernel floor localization algorithm for multi-floor WLAN positioning
title_full_unstemmed Averaged kernel floor localization algorithm for multi-floor WLAN positioning
title_sort averaged kernel floor localization algorithm for multi-floor wlan positioning
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/64389/1/ENG%20%26%20New%20Tech%20Oral%20111117%2032.pdf
http://psasir.upm.edu.my/id/eprint/64389/
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