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.
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 language | English |
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Title of host publication | Intelligent Computing |
Subtitle of host publication | Proceedings of the 2021 Computing Conference |
Editors | Kohei Arai |
Publisher | Springer |
Pages | 1032-1043 |
Number of pages | 12 |
Volume | 2 |
ISBN (Electronic) | 9783030801267 |
ISBN (Print) | 9783030801250 |
DOIs | |
Publication status | Published - 7 Jul 2021 |
Event | Computing Conference 2021 - Virtual, London, United Kingdom Duration: 15 Jul 2021 → 16 Jul 2021 https://saiconference.com/Computing |
Publication series
Name | Lecture Notes in Networks and Systems |
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Publisher | Springer |
Volume | 284 |
ISSN (Print) | 2376-3370 |
ISSN (Electronic) | 2367-3389 |
Conference
Conference | Computing Conference 2021 |
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Country/Territory | United Kingdom |
City | London |
Period | 15/07/21 → 16/07/21 |
Internet address |
Keywords
- IoT, LoRaWAN, RSSI, localization, RNN
ASJC Scopus subject areas
- Signal Processing
- Control and Systems Engineering
- Computer Networks and Communications