A new indoor localization system based on Bayesian graphical model

Citation

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).

Abstract

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.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/WiSPNET.2017.8300103
Publisher:	IEEE
Keywords:	Bayesian graphical model; Fingerprinting technique; Received signal strength
Depositing User:	Nabilah Mustapa
Date Deposited:	08 Oct 2018 02:25
Last Modified:	08 Oct 2018 02:25
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/WiSPNET.2017.8300103
URI:	http://psasir.upm.edu.my/id/eprint/65367
Statistic Details:	View Download Statistic

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