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Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm

Localization of access points has become an important research problem due to the wide range of applications it addresses such as dismantling critical security threats caused by rogue access points or optimizing wireless coverage of access points within a service area. Existing proposed solutions ha...

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Autores principales: Awad, Fahed, Naserllah, Muhammad, Omar, Ammar, Abu-Hantash, Alaa, Al-Taj, Abrar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854978/
https://www.ncbi.nlm.nih.gov/pubmed/29385042
http://dx.doi.org/10.3390/s18020407
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author Awad, Fahed
Naserllah, Muhammad
Omar, Ammar
Abu-Hantash, Alaa
Al-Taj, Abrar
author_facet Awad, Fahed
Naserllah, Muhammad
Omar, Ammar
Abu-Hantash, Alaa
Al-Taj, Abrar
author_sort Awad, Fahed
collection PubMed
description Localization of access points has become an important research problem due to the wide range of applications it addresses such as dismantling critical security threats caused by rogue access points or optimizing wireless coverage of access points within a service area. Existing proposed solutions have mostly relied on theoretical hypotheses or computer simulation to demonstrate the efficiency of their methods. The techniques that rely on estimating the distance using samples of the received signal strength usually assume prior knowledge of the signal propagation characteristics of the indoor environment in hand and tend to take a relatively large number of uniformly distributed random samples. This paper presents an efficient and practical collaborative approach to detect the location of an access point in an indoor environment without any prior knowledge of the environment. The proposed approach comprises a swarm of wirelessly connected mobile robots that collaboratively and autonomously collect a relatively small number of non-uniformly distributed random samples of the access point’s received signal strength. These samples are used to efficiently and accurately estimate the location of the access point. The experimental testing verified that the proposed approach can identify the location of the access point in an accurate and efficient manner.
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spelling pubmed-58549782018-03-20 Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm Awad, Fahed Naserllah, Muhammad Omar, Ammar Abu-Hantash, Alaa Al-Taj, Abrar Sensors (Basel) Article Localization of access points has become an important research problem due to the wide range of applications it addresses such as dismantling critical security threats caused by rogue access points or optimizing wireless coverage of access points within a service area. Existing proposed solutions have mostly relied on theoretical hypotheses or computer simulation to demonstrate the efficiency of their methods. The techniques that rely on estimating the distance using samples of the received signal strength usually assume prior knowledge of the signal propagation characteristics of the indoor environment in hand and tend to take a relatively large number of uniformly distributed random samples. This paper presents an efficient and practical collaborative approach to detect the location of an access point in an indoor environment without any prior knowledge of the environment. The proposed approach comprises a swarm of wirelessly connected mobile robots that collaboratively and autonomously collect a relatively small number of non-uniformly distributed random samples of the access point’s received signal strength. These samples are used to efficiently and accurately estimate the location of the access point. The experimental testing verified that the proposed approach can identify the location of the access point in an accurate and efficient manner. MDPI 2018-01-31 /pmc/articles/PMC5854978/ /pubmed/29385042 http://dx.doi.org/10.3390/s18020407 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Awad, Fahed
Naserllah, Muhammad
Omar, Ammar
Abu-Hantash, Alaa
Al-Taj, Abrar
Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm
title Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm
title_full Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm
title_fullStr Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm
title_full_unstemmed Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm
title_short Collaborative Indoor Access Point Localization Using Autonomous Mobile Robot Swarm
title_sort collaborative indoor access point localization using autonomous mobile robot swarm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854978/
https://www.ncbi.nlm.nih.gov/pubmed/29385042
http://dx.doi.org/10.3390/s18020407
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