Indoor positioning model based on people effect and ray tracing propagation

WLAN-fingerprinting has been highlighted as the preferred technology in an Indoor Positioning System (IPS) due to its accurate positioning results and minimal infrastructure cost. However, the accuracy of IPS fingerprinting is highly influenced by the fluctuation in signal strength as a result of en...

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Main Author:	Firdaus, Firdaus
Format:	Thesis
Language:	English
Published:	2020
Subjects:	QA75 Electronic computers Computer science T58.5-58.64 Information technology
Online Access:	http://eprints.utm.my/id/eprint/97934/1/FirdausPRAZAK2020.pdf
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spelling	my-utm-ep.979342022-11-07T10:53:19Z Indoor positioning model based on people effect and ray tracing propagation 2020 Firdaus, Firdaus QA75 Electronic computers. Computer science T58.5-58.64 Information technology WLAN-fingerprinting has been highlighted as the preferred technology in an Indoor Positioning System (IPS) due to its accurate positioning results and minimal infrastructure cost. However, the accuracy of IPS fingerprinting is highly influenced by the fluctuation in signal strength as a result of encountering obstacles. Many researchers have modelled static obstacles such as walls and ceilings, but hardly any have modelled the effect of people presence as an obstacle although the human body significantly impacts signal strength. Hence, the people presence effect must be considered to obtain highly accurate positioning results. Previous research proposed a model that only considered the direct path between the transmitter and the receiver. However, for indoor propagation, multipath effects such as reflection can also have a significant influence, but were not considered in past work. Therefore, this research proposes an accurate indoor positioning model that considers people presence using a ray tracing (AIRY) model in a dynamic environment which relies on existing infrastructure. Three solutions were proposed to construct AIRY: an automatic radio map using ray tracing (ARM-RT), a new human model in ray tracing (HUMORY), and a people effect constant for received signal strength indicator (RSSI) adaptation. At the offline stage, 30 RSSIs were recorded at each point using a smartphone to create a radio map database (523 points). The real-time RSSI was then compared to the radio map database at the online stage using MATLAB software to determine the user position (65 test points). The proposed model was tested at Level 3 of Razak Tower, UTM Kuala Lumpur (80 × 16 m). To test the influence of people presence, the number, position, and distance of the people around the mobile device (MD) were varied. The results showed that the closer the people were to the MD in both the Line of Sight (LOS) and Non-LOS position, the greater the decrease in RSSI, in which the increment number of people will increase the amount of reflection signals to be blocked. The signal strength reduction started from 0.5 dBm with two people and reached 0.9 dBm with seven people. In addition, the ray tracing model produced smaller errors on RSSI prediction than the multi-wall model when considering the effect of people presence. The k-nearest neighbour (KNN) algorithm was used to define the position. The initial accuracy was improved from 2.04 m to 0.57 m after people presence and multipath effects were considered. In conclusion, the proposed model successfully increased indoor positioning accuracy in a dynamic environment by overcoming the people presence effect. 2020 Thesis http://eprints.utm.my/id/eprint/97934/ http://eprints.utm.my/id/eprint/97934/1/FirdausPRAZAK2020.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:144337 phd doctoral Universiti Teknologi Malaysia, Razak Faculty of Technology & Informatics Razak Faculty of Technology & Informatics
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science T58.5-58.64 Information technology
spellingShingle	QA75 Electronic computers Computer science T58.5-58.64 Information technology Firdaus, Firdaus Indoor positioning model based on people effect and ray tracing propagation
description	WLAN-fingerprinting has been highlighted as the preferred technology in an Indoor Positioning System (IPS) due to its accurate positioning results and minimal infrastructure cost. However, the accuracy of IPS fingerprinting is highly influenced by the fluctuation in signal strength as a result of encountering obstacles. Many researchers have modelled static obstacles such as walls and ceilings, but hardly any have modelled the effect of people presence as an obstacle although the human body significantly impacts signal strength. Hence, the people presence effect must be considered to obtain highly accurate positioning results. Previous research proposed a model that only considered the direct path between the transmitter and the receiver. However, for indoor propagation, multipath effects such as reflection can also have a significant influence, but were not considered in past work. Therefore, this research proposes an accurate indoor positioning model that considers people presence using a ray tracing (AIRY) model in a dynamic environment which relies on existing infrastructure. Three solutions were proposed to construct AIRY: an automatic radio map using ray tracing (ARM-RT), a new human model in ray tracing (HUMORY), and a people effect constant for received signal strength indicator (RSSI) adaptation. At the offline stage, 30 RSSIs were recorded at each point using a smartphone to create a radio map database (523 points). The real-time RSSI was then compared to the radio map database at the online stage using MATLAB software to determine the user position (65 test points). The proposed model was tested at Level 3 of Razak Tower, UTM Kuala Lumpur (80 × 16 m). To test the influence of people presence, the number, position, and distance of the people around the mobile device (MD) were varied. The results showed that the closer the people were to the MD in both the Line of Sight (LOS) and Non-LOS position, the greater the decrease in RSSI, in which the increment number of people will increase the amount of reflection signals to be blocked. The signal strength reduction started from 0.5 dBm with two people and reached 0.9 dBm with seven people. In addition, the ray tracing model produced smaller errors on RSSI prediction than the multi-wall model when considering the effect of people presence. The k-nearest neighbour (KNN) algorithm was used to define the position. The initial accuracy was improved from 2.04 m to 0.57 m after people presence and multipath effects were considered. In conclusion, the proposed model successfully increased indoor positioning accuracy in a dynamic environment by overcoming the people presence effect.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Firdaus, Firdaus
author_facet	Firdaus, Firdaus
author_sort	Firdaus, Firdaus
title	Indoor positioning model based on people effect and ray tracing propagation
title_short	Indoor positioning model based on people effect and ray tracing propagation
title_full	Indoor positioning model based on people effect and ray tracing propagation
title_fullStr	Indoor positioning model based on people effect and ray tracing propagation
title_full_unstemmed	Indoor positioning model based on people effect and ray tracing propagation
title_sort	indoor positioning model based on people effect and ray tracing propagation
granting_institution	Universiti Teknologi Malaysia, Razak Faculty of Technology & Informatics
granting_department	Razak Faculty of Technology & Informatics
publishDate	2020
url	http://eprints.utm.my/id/eprint/97934/1/FirdausPRAZAK2020.pdf
_version_	1776100537984352256

Indoor positioning model based on people effect and ray tracing propagation

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