INDOOR SMARTPHONE LOCALIZATION USING WLAN

Around 80-90% of smartphone users spend their time indoors carrying out various daily activities such as working, playing, shopping, and communicating so that will become a problem that can disrupt daily activities if someone loses their cell phone. Therefore, we need a system that can track the...

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Main Author: Muzaky Dwi Putra, Faishol
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/71871
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:71871
spelling id-itb.:718712023-02-27T11:56:33ZINDOOR SMARTPHONE LOCALIZATION USING WLAN Muzaky Dwi Putra, Faishol Indonesia Theses indoor localization, WLAN, RSSI, fingerprint, kalman filter, K-NN. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/71871 Around 80-90% of smartphone users spend their time indoors carrying out various daily activities such as working, playing, shopping, and communicating so that will become a problem that can disrupt daily activities if someone loses their cell phone. Therefore, we need a system that can track the location of cell phones in the room. Currently, Global Positioning System (GPS) technology is most often used to determine the location of a smartphone. However, the use of GPS for location tracking systems can only work optimally in outdoor conditions. In indoor conditions, the GPS signal strength is unable to penetrate the walls of buildings, as a result, the GPS signal cannot spread evenly and there is a decrease in signal strength, deflection, and reflection of the GPS signal. The purpose of this study is to build a mobile application that can accurately track the location of a cell phone indoors using a fingerprint method based on a Wireless Local Area Network (WLAN) signal and determine the effect of the Kalman Filter algorithm on RSSI measurements on the accuracy of the cell phone tracking system indoors. The results of the test show that the RSSI value using the Kalman Filter obtains an accuracy rate of 85% for k = 5 while the RSSI value without using the Kalman Filter obtains an accuracy rate of 85% for k = 3, and the application of the Kalman Filter algorithm to the measurement of the RSSI value proven capable of increasing the accuracy of RSSI measurements but unable to improve the accuracy of cell phone tracking indoors. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Around 80-90% of smartphone users spend their time indoors carrying out various daily activities such as working, playing, shopping, and communicating so that will become a problem that can disrupt daily activities if someone loses their cell phone. Therefore, we need a system that can track the location of cell phones in the room. Currently, Global Positioning System (GPS) technology is most often used to determine the location of a smartphone. However, the use of GPS for location tracking systems can only work optimally in outdoor conditions. In indoor conditions, the GPS signal strength is unable to penetrate the walls of buildings, as a result, the GPS signal cannot spread evenly and there is a decrease in signal strength, deflection, and reflection of the GPS signal. The purpose of this study is to build a mobile application that can accurately track the location of a cell phone indoors using a fingerprint method based on a Wireless Local Area Network (WLAN) signal and determine the effect of the Kalman Filter algorithm on RSSI measurements on the accuracy of the cell phone tracking system indoors. The results of the test show that the RSSI value using the Kalman Filter obtains an accuracy rate of 85% for k = 5 while the RSSI value without using the Kalman Filter obtains an accuracy rate of 85% for k = 3, and the application of the Kalman Filter algorithm to the measurement of the RSSI value proven capable of increasing the accuracy of RSSI measurements but unable to improve the accuracy of cell phone tracking indoors.
format Theses
author Muzaky Dwi Putra, Faishol
spellingShingle Muzaky Dwi Putra, Faishol
INDOOR SMARTPHONE LOCALIZATION USING WLAN
author_facet Muzaky Dwi Putra, Faishol
author_sort Muzaky Dwi Putra, Faishol
title INDOOR SMARTPHONE LOCALIZATION USING WLAN
title_short INDOOR SMARTPHONE LOCALIZATION USING WLAN
title_full INDOOR SMARTPHONE LOCALIZATION USING WLAN
title_fullStr INDOOR SMARTPHONE LOCALIZATION USING WLAN
title_full_unstemmed INDOOR SMARTPHONE LOCALIZATION USING WLAN
title_sort indoor smartphone localization using wlan
url https://digilib.itb.ac.id/gdl/view/71871
_version_ 1822279206060425216