Robust 3D indoor positioning system based on radio map using Bayesian network
Indoor positioning remains a serious issue due to the difficulty in attaining sufficient accuracy within an indoor environment using tracking technology of low complexity. Currently, most positioning systems do not embed the off-the-shelf (OTS) system which allows mobile devices to estimate location...
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Online Access: | http://psasir.upm.edu.my/id/eprint/36209/1/Robust%203D%20indoor%20positioning%20system%20based%20on%20radio%20map%20using%20Bayesian%20network.pdf http://psasir.upm.edu.my/id/eprint/36209/ |
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my.upm.eprints.362092020-06-15T07:30:04Z http://psasir.upm.edu.my/id/eprint/36209/ Robust 3D indoor positioning system based on radio map using Bayesian network Alhammadi, Abdulraqeb Shaif Ahmed Alraih, Saddam Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee Indoor positioning remains a serious issue due to the difficulty in attaining sufficient accuracy within an indoor environment using tracking technology of low complexity. Currently, most positioning systems do not embed the off-the-shelf (OTS) system which allows mobile devices to estimate location without using any additional hardware. In this paper, we propose a robust 3D indoor positioning system that is suitable for an indoor IoT application. This system based on Bayesian network that depends on Wi-Fi signals strength. It was experimentally tested in a building with pre-deployed access points (APs). The experimental results indicate that localization accuracy of the proposed system is high with the use of a small-sized radio map. IEEE 2019 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/36209/1/Robust%203D%20indoor%20positioning%20system%20based%20on%20radio%20map%20using%20Bayesian%20network.pdf Alhammadi, Abdulraqeb Shaif Ahmed and Alraih, Saddam and Hashim, Fazirulhisyam and A. Rasid, Mohd Fadlee (2019) Robust 3D indoor positioning system based on radio map using Bayesian network. In: 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), 15-18 Apr. 2019, Limerick, Ireland. (pp. 1-4). 10.1109/WF-IoT.2019.8767318 |
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Indoor positioning remains a serious issue due to the difficulty in attaining sufficient accuracy within an indoor environment using tracking technology of low complexity. Currently, most positioning systems do not embed the off-the-shelf (OTS) system which allows mobile devices to estimate location without using any additional hardware. In this paper, we propose a robust 3D indoor positioning system that is suitable for an indoor IoT application. This system based on Bayesian network that depends on Wi-Fi signals strength. It was experimentally tested in a building with pre-deployed access points (APs). The experimental results indicate that localization accuracy of the proposed system is high with the use of a small-sized radio map. |
format |
Conference or Workshop Item |
author |
Alhammadi, Abdulraqeb Shaif Ahmed Alraih, Saddam Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee |
spellingShingle |
Alhammadi, Abdulraqeb Shaif Ahmed Alraih, Saddam Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee Robust 3D indoor positioning system based on radio map using Bayesian network |
author_facet |
Alhammadi, Abdulraqeb Shaif Ahmed Alraih, Saddam Hashim, Fazirulhisyam A. Rasid, Mohd Fadlee |
author_sort |
Alhammadi, Abdulraqeb Shaif Ahmed |
title |
Robust 3D indoor positioning system based on radio map using Bayesian network |
title_short |
Robust 3D indoor positioning system based on radio map using Bayesian network |
title_full |
Robust 3D indoor positioning system based on radio map using Bayesian network |
title_fullStr |
Robust 3D indoor positioning system based on radio map using Bayesian network |
title_full_unstemmed |
Robust 3D indoor positioning system based on radio map using Bayesian network |
title_sort |
robust 3d indoor positioning system based on radio map using bayesian network |
publisher |
IEEE |
publishDate |
2019 |
url |
http://psasir.upm.edu.my/id/eprint/36209/1/Robust%203D%20indoor%20positioning%20system%20based%20on%20radio%20map%20using%20Bayesian%20network.pdf http://psasir.upm.edu.my/id/eprint/36209/ |
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1671341074007719936 |
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13.211869 |