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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Online Access: | http://psasir.upm.edu.my/id/eprint/65367/1/A%20new%20indoor%20localization%20system%20based%20on%20Bayesian%20graphical%20model.pdf http://psasir.upm.edu.my/id/eprint/65367/ |
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my.upm.eprints.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 |
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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. |
format |
Conference or Workshop Item |
author |
Alhammadi, Abdulraqeb Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee Alraih, Saddam |
spellingShingle |
Alhammadi, Abdulraqeb Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee Alraih, Saddam A new indoor localization system based on Bayesian graphical model |
author_facet |
Alhammadi, Abdulraqeb Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee Alraih, Saddam |
author_sort |
Alhammadi, Abdulraqeb |
title |
A new indoor localization system based on Bayesian graphical model |
title_short |
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_sort |
new indoor localization system based on bayesian graphical model |
publisher |
IEEE |
publishDate |
2017 |
url |
http://psasir.upm.edu.my/id/eprint/65367/1/A%20new%20indoor%20localization%20system%20based%20on%20Bayesian%20graphical%20model.pdf http://psasir.upm.edu.my/id/eprint/65367/ |
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