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Electrical Internet of Things - EIoT: A Platform for the Data Management in Electrical Systems

Authors :
Rodolfo García-Sierra
Germán D. Zapata-Madrigal
Santiago Gil
Source :
Advances in Intelligent Systems and Computing ISBN: 9783030325220
Publication Year :
2019
Publisher :
Springer International Publishing, 2019.

Abstract

The arrival of the IoT has benefited multiple industrial sectors; one of them is the electrical industry. It makes the IoT an attractive platform for the smart grid, because it improves the monitoring, analysis, availability, autonomy, and control of grid systems, from distribution to transmission. In this work, it is proposed the Electrical Internet of Things – EIoT, a platform for the data management in electrical systems. The EIoT platform relies on the LPWAN technologies to connect electrical things geographically distributed. This approach attempts to cover Fire Protection Systems in Substations, Control and Monitoring for the Demand Management, Electrical Asset Management, and Intelligent Power Management and Monitoring in Refrigerators applications, but other smart grid applications fit as well. The EIoT platform implemented LoRa, a LPWAN technology, and its LoRaWAN protocol to connect electrical elements remotely in a first stage. The prototyping phase of the EIoT platform was developed using Mbed-enabled LoRa nodes coupled to electrical elements with the corresponding instrumentation, a LoRaWAN network, and a custom application server; then, all the components of an IoT network were considered. Some results of the implementation are presented, which demonstrate the suitability of the EIoT platform to address several applications of the electrical industry. The results also expose promising opportunities to deal with data processing and analytics, integrate more IoT protocols, and consolidate a complete IoT ecosystem in the electrical industry and the smart grids in further researches.

Details

ISBN :
978-3-030-32522-0
ISBNs :
9783030325220
Database :
OpenAIRE
Journal :
Advances in Intelligent Systems and Computing ISBN: 9783030325220
Accession number :
edsair.doi...........e81a466daeb0ea48e16e7dffb7f3b3e6
Full Text :
https://doi.org/10.1007/978-3-030-32523-7_4