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Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments
In this paper, we propose a methodology to use the received signal strength indicator (RSSI) available by the protocol stack of an installed Wireless Sensor Network (WSN) at an electric-power-system environment (EPS) as a tool for obtaining the characteristic of its communication channel. Thereby, i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308897/ https://www.ncbi.nlm.nih.gov/pubmed/32485923 http://dx.doi.org/10.3390/s20113076 |
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author | Antayhua, Roddy A. R. Pereira, Maicon D. Fernandes, Nestor C. Rangel de Sousa, Fernando |
author_facet | Antayhua, Roddy A. R. Pereira, Maicon D. Fernandes, Nestor C. Rangel de Sousa, Fernando |
author_sort | Antayhua, Roddy A. R. |
collection | PubMed |
description | In this paper, we propose a methodology to use the received signal strength indicator (RSSI) available by the protocol stack of an installed Wireless Sensor Network (WSN) at an electric-power-system environment (EPS) as a tool for obtaining the characteristic of its communication channel. Thereby, it is possible to optimize the settings and configuration of the network after its deployment, which is usually run empirically without any previous knowledge of the channel. A study case of a hydroelectric power plant is presented, where measurements recorded over a two-month period were analyzed and treated to obtain the large-scale characteristics of the radiofrequency channel at 2.4 GHz. In addition, we showed that instantaneous RSSI data can also be used to detect specific issues in the network, such as repetitive patterns in the transmitted power level of the nodes, and information about its environment, such as the presence of external sources of electromagnetic interference. As a result, we demonstrate the practical use of the RSSI long-term data generated by the WSN for its own performance optimization and the detection of particular events in an EPS or any similar industrial environment. |
format | Online Article Text |
id | pubmed-7308897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73088972020-06-25 Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments Antayhua, Roddy A. R. Pereira, Maicon D. Fernandes, Nestor C. Rangel de Sousa, Fernando Sensors (Basel) Article In this paper, we propose a methodology to use the received signal strength indicator (RSSI) available by the protocol stack of an installed Wireless Sensor Network (WSN) at an electric-power-system environment (EPS) as a tool for obtaining the characteristic of its communication channel. Thereby, it is possible to optimize the settings and configuration of the network after its deployment, which is usually run empirically without any previous knowledge of the channel. A study case of a hydroelectric power plant is presented, where measurements recorded over a two-month period were analyzed and treated to obtain the large-scale characteristics of the radiofrequency channel at 2.4 GHz. In addition, we showed that instantaneous RSSI data can also be used to detect specific issues in the network, such as repetitive patterns in the transmitted power level of the nodes, and information about its environment, such as the presence of external sources of electromagnetic interference. As a result, we demonstrate the practical use of the RSSI long-term data generated by the WSN for its own performance optimization and the detection of particular events in an EPS or any similar industrial environment. MDPI 2020-05-29 /pmc/articles/PMC7308897/ /pubmed/32485923 http://dx.doi.org/10.3390/s20113076 Text en © 2020 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 Antayhua, Roddy A. R. Pereira, Maicon D. Fernandes, Nestor C. Rangel de Sousa, Fernando Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments |
title | Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments |
title_full | Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments |
title_fullStr | Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments |
title_full_unstemmed | Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments |
title_short | Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments |
title_sort | exploiting the rssi long-term data of a wsn for the rf channel modeling in eps environments |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308897/ https://www.ncbi.nlm.nih.gov/pubmed/32485923 http://dx.doi.org/10.3390/s20113076 |
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