WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD

WiFi fingerprinting for indoor positioning is well known as one of the most efficient techniques to estimate indoor target location instead of other existing methods which are triangulation and proximity. This method requires a training phase to collect Receiving Signal Strength (RSS) samples that w...

Full description

Main Author: BIN MAZLAN, MUHAMMAD AL AMIN AMALI
Format: Thesis
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.22073 /
Published: 2017
Subjects:
Instrumentation and Control
Online Access: http://utpedia.utp.edu.my/22073/1/UTP%20MSc%20in%20EE%20Thesis%20JULY%202017%20-%20G03140%20-%20Muhammad%20Al%20Amin%20Amali%20Bin%20Mazlan.pdf
http://utpedia.utp.edu.my/22073/
Tags: Add Tag
No Tags, Be the first to tag this record!
id utp-utpedia.22073
recordtype eprints
spelling utp-utpedia.220732021-10-12T20:36:30Z http://utpedia.utp.edu.my/22073/ WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD BIN MAZLAN, MUHAMMAD AL AMIN AMALI Instrumentation and Control WiFi fingerprinting for indoor positioning is well known as one of the most efficient techniques to estimate indoor target location instead of other existing methods which are triangulation and proximity. This method requires a training phase to collect Receiving Signal Strength (RSS) samples that will be utilized in location estimation phase using matching algorithms. Recently, most commercially indoor positioning solutions used on smartphone utilizes the current building infrastructure to estimate personnel location where wireless router is used as an Access Point (AP) in each base station to extract the RSS values. However, for buildings with inadequate infrastructure setup, implementing multiple base stations using a single AP in each base station would require an exhaustive resources of manpower and time especially for a small scale positioning setup. There are also not enough distinct RSS values at each location covered by a single base station. Thus, WiFi fingerprinting using multiple APs with omnidirectional and directional antennas in a single base station employing a probabilistic approach has been proposed to minimize the infrastructure setup. Based on experimental results, the proposed multiple APs in a single base station was found to reduce the number of base stations required to achieve the same or better accuracy as existing approach using the same number of APs. The feasibility of multiple APs in a single base station was demonstrated using kernel estimation with the results indicating the ability of the proposed work with an accuracy of 1.82 m to outperform the existing work by minimizing 22% of Root Mean Square Error (RMSE). 2017-07 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/22073/1/UTP%20MSc%20in%20EE%20Thesis%20JULY%202017%20-%20G03140%20-%20Muhammad%20Al%20Amin%20Amali%20Bin%20Mazlan.pdf BIN MAZLAN, MUHAMMAD AL AMIN AMALI (2017) WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD. Masters thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic Instrumentation and Control
spellingShingle Instrumentation and Control
BIN MAZLAN, MUHAMMAD AL AMIN AMALI
WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD
description WiFi fingerprinting for indoor positioning is well known as one of the most efficient techniques to estimate indoor target location instead of other existing methods which are triangulation and proximity. This method requires a training phase to collect Receiving Signal Strength (RSS) samples that will be utilized in location estimation phase using matching algorithms. Recently, most commercially indoor positioning solutions used on smartphone utilizes the current building infrastructure to estimate personnel location where wireless router is used as an Access Point (AP) in each base station to extract the RSS values. However, for buildings with inadequate infrastructure setup, implementing multiple base stations using a single AP in each base station would require an exhaustive resources of manpower and time especially for a small scale positioning setup. There are also not enough distinct RSS values at each location covered by a single base station. Thus, WiFi fingerprinting using multiple APs with omnidirectional and directional antennas in a single base station employing a probabilistic approach has been proposed to minimize the infrastructure setup. Based on experimental results, the proposed multiple APs in a single base station was found to reduce the number of base stations required to achieve the same or better accuracy as existing approach using the same number of APs. The feasibility of multiple APs in a single base station was demonstrated using kernel estimation with the results indicating the ability of the proposed work with an accuracy of 1.82 m to outperform the existing work by minimizing 22% of Root Mean Square Error (RMSE).
format Thesis
author BIN MAZLAN, MUHAMMAD AL AMIN AMALI
author_sort BIN MAZLAN, MUHAMMAD AL AMIN AMALI
title WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD
title_short WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD
title_full WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD
title_fullStr WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD
title_full_unstemmed WIFI FINGERPRINTING INDOOR POSITIONING WITH MULTIPLE ACCESS-POINTS IN A SINGLE BASE STATION USING PROBABILISTIC METHOD
title_sort wifi fingerprinting indoor positioning with multiple access-points in a single base station using probabilistic method
publishDate 2017
url http://utpedia.utp.edu.my/22073/1/UTP%20MSc%20in%20EE%20Thesis%20JULY%202017%20-%20G03140%20-%20Muhammad%20Al%20Amin%20Amali%20Bin%20Mazlan.pdf
http://utpedia.utp.edu.my/22073/
_version_ 1741195815994523648
score 11.62408

Similar Items