Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments
1
Radio Frequency Laboratory at the Department of Electrical and Electronics Engineering, Federal University of Santa Catarina, Florianopolis, SC 88040-900, Brazil
2
Department of Electrical Engineering, Federal Institute of Santa Catarina, Itajai, SC 88007-303, Brazil
3
Department of Electrical and Computer Engineering, Federal University of Bahia, Salvador, BA 40210-630, Brazil
4
Traceback Technologies, Florianópolis, SC 88090-145, Brazil
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(11), 3076; https://doi.org/10.3390/s20113076
Received: 25 March 2020
/
Revised: 8 April 2020
/
Accepted: 15 April 2020
/
Published: 29 May 2020
(This article belongs to the Special Issue Sensors and Real Time Systems for IIoT)
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.
View Full-Text
Keywords:
IIoT; WSN; RSSI; power plants; RF channel model; EMI
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Antayhua, R.A.R.; Pereira, M.D.; Fernandes, N.C.; Rangel de Sousa, F. Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments. Sensors 2020, 20, 3076. https://doi.org/10.3390/s20113076
AMA Style
Antayhua RAR, Pereira MD, Fernandes NC, Rangel de Sousa F. Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments. Sensors. 2020; 20(11):3076. https://doi.org/10.3390/s20113076
Chicago/Turabian StyleAntayhua, Roddy A.R., Maicon D. Pereira, Nestor C. Fernandes, and Fernando Rangel de Sousa. 2020. "Exploiting the RSSI Long-Term Data of a WSN for the RF Channel Modeling in EPS Environments" Sensors 20, no. 11: 3076. https://doi.org/10.3390/s20113076
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
