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3D trilateration localization using RSSI in indoor environment

Received Signal Strength Indicator (RSSI) is one of the most popular technique for outdoor and indoor localization. There are many previous researches on RSSI-based indoor localization systems. However, most of them lack a solid classification method that reduce localization errors with better accur...

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Main Authors: Rohmat Rose, Nur Diana, Low, Tan Jung, Ahmad, Muneer
Format: Article
Published: SAI Organization 2020
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.um.edu.my/25247/
https://thesai.org/Downloads/Volume11No2/Paper_50-3D_Trilateration_Localization.pdf
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spelling my.um.eprints.252472020-08-05T02:29:49Z http://eprints.um.edu.my/25247/ 3D trilateration localization using RSSI in indoor environment Rohmat Rose, Nur Diana Low, Tan Jung Ahmad, Muneer QA75 Electronic computers. Computer science Received Signal Strength Indicator (RSSI) is one of the most popular technique for outdoor and indoor localization. There are many previous researches on RSSI-based indoor localization systems. However, most of them lack a solid classification method that reduce localization errors with better accuracy. This paper will focus on indoor localization methods to provide a technological perspective of indoor positioning systems. This paper proposes an indoor localization by using 3D trilateration method to locate target tags from RFID readers that used RSSI measurements for range determination. There will be six test cases for each reader. This system can track any target within the selected area with less localization error. © Science and Information Organization. SAI Organization 2020 Article PeerReviewed Rohmat Rose, Nur Diana and Low, Tan Jung and Ahmad, Muneer (2020) 3D trilateration localization using RSSI in indoor environment. International Journal of Advanced Computer Science and Applications, 11 (2). pp. 385-391. ISSN 2158-107X https://thesai.org/Downloads/Volume11No2/Paper_50-3D_Trilateration_Localization.pdf
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Rohmat Rose, Nur Diana
Low, Tan Jung
Ahmad, Muneer
3D trilateration localization using RSSI in indoor environment
description Received Signal Strength Indicator (RSSI) is one of the most popular technique for outdoor and indoor localization. There are many previous researches on RSSI-based indoor localization systems. However, most of them lack a solid classification method that reduce localization errors with better accuracy. This paper will focus on indoor localization methods to provide a technological perspective of indoor positioning systems. This paper proposes an indoor localization by using 3D trilateration method to locate target tags from RFID readers that used RSSI measurements for range determination. There will be six test cases for each reader. This system can track any target within the selected area with less localization error. © Science and Information Organization.
format Article
author Rohmat Rose, Nur Diana
Low, Tan Jung
Ahmad, Muneer
author_facet Rohmat Rose, Nur Diana
Low, Tan Jung
Ahmad, Muneer
author_sort Rohmat Rose, Nur Diana
title 3D trilateration localization using RSSI in indoor environment
title_short 3D trilateration localization using RSSI in indoor environment
title_full 3D trilateration localization using RSSI in indoor environment
title_fullStr 3D trilateration localization using RSSI in indoor environment
title_full_unstemmed 3D trilateration localization using RSSI in indoor environment
title_sort 3d trilateration localization using rssi in indoor environment
publisher SAI Organization
publishDate 2020
url http://eprints.um.edu.my/25247/
https://thesai.org/Downloads/Volume11No2/Paper_50-3D_Trilateration_Localization.pdf
_version_ 1680857013131673600
score 13.211869

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