An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices

Current GPS navigation systems have proven to be capable of navigating a user in outdoor locations. However, they are not fit for use within indoor locations, due to the blocking of GPS signals indoors. Therefore, Wi-Fi signals have been used to determine a user’s location indoors. However, these si...

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Main Authors: Choa, Archie Shawn O., Jacinto, Daniel Joseph M., Ngo, Vincent Nygel T., Puada, Nico Angelo A.
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Language:English
Published: Animo Repository 2012
Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/11921
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-125662021-09-13T05:48:34Z An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices Choa, Archie Shawn O. Jacinto, Daniel Joseph M. Ngo, Vincent Nygel T. Puada, Nico Angelo A. Current GPS navigation systems have proven to be capable of navigating a user in outdoor locations. However, they are not fit for use within indoor locations, due to the blocking of GPS signals indoors. Therefore, Wi-Fi signals have been used to determine a user’s location indoors. However, these signals are not always reliable due to their constant fluctuations, significantly affecting the overall positioning accuracy of the signals. This paper presents a mobile application that integrated the inertial sensors embedded within a mobile device to navigate a user indoors using the particle filter algorithm. By combining these two distinct technologies, the localization errors that Wi-Fi technology produces were compensated. The proponents compared three different combinations in order to determine if inertial sensor and particle filter are necessary for increasing the accuracy of localization. These three combinations were Wi-Fi Fingerprinting only, Wi-Fi Fingerprinting + Inertial Sensors, Wi-Fi Fingerprinting + Inertial Sensors and particle Filter. Test showed that Wi-Fi Fingerprinting and Wi-Fi Fingerprinting + Inertial Sensors produced almost same results which are 7.79 meters and 6.96 meters and 6.96 meters respectively. Adding inertial sensors was not sufficient since the initial position determined through Wi-Fi Fingerprinting was not highly reliable. Inertial sensors gave only the velocity which helps in following the path of the user. On the other hand, combining particle filter with the previous combination increased the accuracy of localization to 2.68 meters. A test done with 30 respondents showed that the system was able to navigate the user to his/her chosen destination. 2012-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/11921 Bachelor's Theses English Animo Repository
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
description Current GPS navigation systems have proven to be capable of navigating a user in outdoor locations. However, they are not fit for use within indoor locations, due to the blocking of GPS signals indoors. Therefore, Wi-Fi signals have been used to determine a user’s location indoors. However, these signals are not always reliable due to their constant fluctuations, significantly affecting the overall positioning accuracy of the signals. This paper presents a mobile application that integrated the inertial sensors embedded within a mobile device to navigate a user indoors using the particle filter algorithm. By combining these two distinct technologies, the localization errors that Wi-Fi technology produces were compensated. The proponents compared three different combinations in order to determine if inertial sensor and particle filter are necessary for increasing the accuracy of localization. These three combinations were Wi-Fi Fingerprinting only, Wi-Fi Fingerprinting + Inertial Sensors, Wi-Fi Fingerprinting + Inertial Sensors and particle Filter. Test showed that Wi-Fi Fingerprinting and Wi-Fi Fingerprinting + Inertial Sensors produced almost same results which are 7.79 meters and 6.96 meters and 6.96 meters respectively. Adding inertial sensors was not sufficient since the initial position determined through Wi-Fi Fingerprinting was not highly reliable. Inertial sensors gave only the velocity which helps in following the path of the user. On the other hand, combining particle filter with the previous combination increased the accuracy of localization to 2.68 meters. A test done with 30 respondents showed that the system was able to navigate the user to his/her chosen destination.
format text
author Choa, Archie Shawn O.
Jacinto, Daniel Joseph M.
Ngo, Vincent Nygel T.
Puada, Nico Angelo A.
spellingShingle Choa, Archie Shawn O.
Jacinto, Daniel Joseph M.
Ngo, Vincent Nygel T.
Puada, Nico Angelo A.
An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices
author_facet Choa, Archie Shawn O.
Jacinto, Daniel Joseph M.
Ngo, Vincent Nygel T.
Puada, Nico Angelo A.
author_sort Choa, Archie Shawn O.
title An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices
title_short An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices
title_full An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices
title_fullStr An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices
title_full_unstemmed An indoor navigation application using Wi-Fi fingerprinting and inertial-based sensors for mobile devices
title_sort indoor navigation application using wi-fi fingerprinting and inertial-based sensors for mobile devices
publisher Animo Repository
publishDate 2012
url https://animorepository.dlsu.edu.ph/etd_bachelors/11921
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