Abstract
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.
Highlights
We are currently living in the era of Industrial Internet of Things (IIoT), in which several disruptive technologies have converged to change the way modern companies manage their manufacturing and industrial processes [1]
As an alternative to the cited studies in which the propagation channel in a power plant was characterized through conventional methods, the authors have proposed in Reference [19] to use the received signal strength indicator (RSSI) data reported by the protocol stack level of the nodes from a deployed Wireless Sensor Network (WSN) for the channel characterization
It is often the case that the nodes of the network are installed and their settings, such as the number of nodes and location, are optimized empirically. This common procedure is preferred since a proper characterization of the propagation channel usually demands a considerable measurement effort, hindered by the complex structure and the strict safety regulations of power plants
Summary
We are currently living in the era of Industrial Internet of Things (IIoT), in which several disruptive technologies have converged to change the way modern companies manage their manufacturing and industrial processes [1]. As an alternative to the cited studies in which the propagation channel in a power plant was characterized through conventional methods, the authors have proposed in Reference [19] to use the RSSI data reported by the protocol stack level of the nodes from a deployed WSN for the channel characterization In this way, the inherent information from the network can be used to understand the instantaneous and average large-scale characteristics of the communication channel and its change over time. This method may be a way of overcoming the lack of measurements campaigns before the WSN installation in EPS environments or other similar industrial environments involving large complex facilities and rigid safety regulations in which traditional point-to-point methods are difficult to perform. The conclusions and future work are left for Section 5
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