Integrating Microsoft IoT, machine learning in a large scale power metre reading

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Liviu Pascu
Attila Simo
Alin Mihai Vernica

Abstract

Due to fast technological progress in the power engineering field, the need for new information/communication technologies is more and more underlined. e-Learning has become a viable alternative to traditional teaching/learning techniques, adopted especially because of the advantages offered by the possibility of continuous training. This paper presents a Microsoft Internet of Things Platform for a very large scale smart power metre reading, used for training operative staff of the Distribution Network Operator, but also to help end-users to control their electrical energy consumption. The strength of this platform for the Distribution Network Operator is that the read data can be used for energy forecast, which is very useful for the future energy consumption optimisation. The platform can be reached via the Internet using a user name and password. A comparison between the results provided by classical teaching/learning methods and the ones achieved using this platform is presented.

Keywords: Machine learning, internet of things (IoT), training.

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