LoRa RSSI based outdoor localization in an urban area using random neural networks

Winfred Ingabire*, Hadi Larijani, Ryan M. Gibson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The concept of the Internet of Things (IoT) has led to the interconnection of a significant number of devices and has impacted several applications in smart cities’ development. Localization is widely done using Global Positioning System (GPS). However, with large scale wireless sensor networks, GPS is limited by its high-power consumption and more hardware cost required. An energy-efficient localization system of wireless sensor nodes, especially in outdoor urban environments, is a research challenge with limited investigation. In this paper, an energyefficient end device localization model based on LoRa Received Signal
Strength Indicator (RSSI) is developed using Random Neural Networks (RNN). Various RNN architectures are used to evaluate the proposed model’s performance by applying different learning rates on real RSSI LoRa measurements collected in the urban area of Glasgow City. The proposed model is used to predict the 2D cartesian position coordinates with a minimum mean localization error of 0.39 m.
Original languageEnglish
Title of host publicationIntelligent Computing
Subtitle of host publicationProceedings of the 2021 Computing Conference
EditorsKohei Arai
PublisherSpringer
Pages1032-1043
Number of pages12
Volume2
ISBN (Electronic)9783030801267
ISBN (Print)9783030801250
DOIs
Publication statusPublished - 7 Jul 2021
EventComputing Conference 2021 - Virtual, London, United Kingdom
Duration: 15 Jul 202116 Jul 2021
https://saiconference.com/Computing

Publication series

NameLecture Notes in Networks and Systems
PublisherSpringer
Volume284
ISSN (Print)2376-3370
ISSN (Electronic)2367-3389

Conference

ConferenceComputing Conference 2021
Country/TerritoryUnited Kingdom
CityLondon
Period15/07/2116/07/21
Internet address

Keywords

  • IoT, LoRaWAN, RSSI, localization, RNN

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