WLAN environment for indoor localization

Forecasting; Indoor positioning systems; Motion compensation; Nearest neighbor search; Pattern recognition; Access point (APs); Correction algorithms; Indoor environment; Indoor localization; K nearest neighbor algorithm; K-nearest neighbors; Prediction accuracy; Wireless local area networks (WLAN)

Saved in:
Bibliographic Details
Main Authors: Burhan M.F.B., Shiham N.S.M., Balasubramaniam N., Din N.M.
Other Authors: 57191487465
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-22422
record_format dspace
spelling my.uniten.dspace-224222023-05-29T14:00:53Z WLAN environment for indoor localization Burhan M.F.B. Shiham N.S.M. Balasubramaniam N. Din N.M. 57191487465 57191480082 26967610800 9335429400 Forecasting; Indoor positioning systems; Motion compensation; Nearest neighbor search; Pattern recognition; Access point (APs); Correction algorithms; Indoor environment; Indoor localization; K nearest neighbor algorithm; K-nearest neighbors; Prediction accuracy; Wireless local area networks (WLAN) This paper investigates the deployment of WLAN for indoor localization. K-Nearest Neighbor algorithm is adapted to predict the location of a user in an indoor environment. The accuracy of K-Nearest Neighbor in predicting user's location in an indoor environment is evaluated. As resistance in indoor environment such as walls and movement of objects adversely affect the performance of the algorithm, emphasis is placed on RSS sample vector fluctuation correction. Two simulations were carried out, one adapting the fluctuation correction algorithm and one without fluctuation correction algorithm. The results of the investigation shows that deployment of fluctuation correction algorithm improves the prediction accuracy. The number of access points (APs) deployed in the investigated area also contribute to the prediction accuracy. � 2014 IEEE. Final 2023-05-29T06:00:53Z 2023-05-29T06:00:53Z 2015 Conference Paper 10.1109/ICE2T.2014.7006225 2-s2.0-84990964646 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84990964646&doi=10.1109%2fICE2T.2014.7006225&partnerID=40&md5=94b686a1cda280cc236c5b17c7de4bad https://irepository.uniten.edu.my/handle/123456789/22422 2014-August 7006225 89 93 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Forecasting; Indoor positioning systems; Motion compensation; Nearest neighbor search; Pattern recognition; Access point (APs); Correction algorithms; Indoor environment; Indoor localization; K nearest neighbor algorithm; K-nearest neighbors; Prediction accuracy; Wireless local area networks (WLAN)
author2 57191487465
author_facet 57191487465
Burhan M.F.B.
Shiham N.S.M.
Balasubramaniam N.
Din N.M.
format Conference Paper
author Burhan M.F.B.
Shiham N.S.M.
Balasubramaniam N.
Din N.M.
spellingShingle Burhan M.F.B.
Shiham N.S.M.
Balasubramaniam N.
Din N.M.
WLAN environment for indoor localization
author_sort Burhan M.F.B.
title WLAN environment for indoor localization
title_short WLAN environment for indoor localization
title_full WLAN environment for indoor localization
title_fullStr WLAN environment for indoor localization
title_full_unstemmed WLAN environment for indoor localization
title_sort wlan environment for indoor localization
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806428028255862784
score 13.223943