A new indoor localization system based on Bayesian graphical model

Indoor localization techniques that use wireless local area network beacon signals have recently gained considerable attention among research communities. System accuracy is one of the most important issues in indoor localization technology. We propose a Bayesian graphical model based on fingerprint...

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Main Authors: Alhammadi, Abdulraqeb, Hashim, Fazirulhisyam, A. Rasid, Mohd Fadlee, Alraih, Saddam
Format: Conference or Workshop Item
Language:English
Published: IEEE 2017
Online Access:http://psasir.upm.edu.my/id/eprint/65367/
http://psasir.upm.edu.my/id/eprint/65367/1/A%20new%20indoor%20localization%20system%20based%20on%20Bayesian%20graphical%20model.pdf
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author Alhammadi, Abdulraqeb
Hashim, Fazirulhisyam
A. Rasid, Mohd Fadlee
Alraih, Saddam
author_facet Alhammadi, Abdulraqeb
Hashim, Fazirulhisyam
A. Rasid, Mohd Fadlee
Alraih, Saddam
author_sort Alhammadi, Abdulraqeb
building UPM Institutional Repository
collection Online Access
description Indoor localization techniques that use wireless local area network beacon signals have recently gained considerable attention among research communities. System accuracy is one of the most important issues in indoor localization technology. We propose a Bayesian graphical model based on fingerprinting location algorithm in this study. The proposed Bayesian model was simulated using OpenBUGS, a graphical user interface. We conducted an experiment to collect a sample of reference points in a testbed with a dimension of 51 × 22 m 2 . Results show that the proposed model has improved the accuracy by 25.65% using 15 reference points compared with Madigan model.
first_indexed 2025-11-15T11:22:59Z
format Conference or Workshop Item
id upm-65367
institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T11:22:59Z
publishDate 2017
publisher IEEE
recordtype eprints
repository_type Digital Repository
spelling upm-653672018-10-08T02:25:09Z http://psasir.upm.edu.my/id/eprint/65367/ A new indoor localization system based on Bayesian graphical model Alhammadi, Abdulraqeb Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee Alraih, Saddam Indoor localization techniques that use wireless local area network beacon signals have recently gained considerable attention among research communities. System accuracy is one of the most important issues in indoor localization technology. We propose a Bayesian graphical model based on fingerprinting location algorithm in this study. The proposed Bayesian model was simulated using OpenBUGS, a graphical user interface. We conducted an experiment to collect a sample of reference points in a testbed with a dimension of 51 × 22 m 2 . Results show that the proposed model has improved the accuracy by 25.65% using 15 reference points compared with Madigan model. IEEE 2017 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/65367/1/A%20new%20indoor%20localization%20system%20based%20on%20Bayesian%20graphical%20model.pdf Alhammadi, Abdulraqeb and Hashim, Fazirulhisyam and A. Rasid, Mohd Fadlee and Alraih, Saddam (2017) A new indoor localization system based on Bayesian graphical model. In: 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2017), 22-24 Mar. 2017, Chennai, India. (pp. 1960-1964). 10.1109/WiSPNET.2017.8300103
spellingShingle Alhammadi, Abdulraqeb
Hashim, Fazirulhisyam
A. Rasid, Mohd Fadlee
Alraih, Saddam
A new indoor localization system based on Bayesian graphical model
title A new indoor localization system based on Bayesian graphical model
title_full A new indoor localization system based on Bayesian graphical model
title_fullStr A new indoor localization system based on Bayesian graphical model
title_full_unstemmed A new indoor localization system based on Bayesian graphical model
title_short A new indoor localization system based on Bayesian graphical model
title_sort new indoor localization system based on bayesian graphical model
url http://psasir.upm.edu.my/id/eprint/65367/
http://psasir.upm.edu.my/id/eprint/65367/
http://psasir.upm.edu.my/id/eprint/65367/1/A%20new%20indoor%20localization%20system%20based%20on%20Bayesian%20graphical%20model.pdf