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IoT and Cloud-Based Energy Monitoring and Simulation Platform

descriptionPublicationkeyboard_double_arrow_right Conference object , Article 01 Mar 2019Publisher:IEEEJournal:2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE)

Authors: Teodora Usurelu; Marian Ceaparu; George Suciu; Raluca Iosu; Lucian Necula;

doi: 10.1109/atee.2019.8724961

IoT and Cloud-Based Energy Monitoring and Simulation Platform

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Abstract

Nowadays, in order to optimize resource consumption and reduce costs, companies concern themselves with the adoption of innovative energy efficiency solutions. Substantiating the decision to implement energy efficiency measures is challenging, due to a high number of factors that influence the rentability of the project, such as weather conditions, energy pricing, laws and regulations, available resources and energy demand. Thus, each company faces a unique combination of factors that needs to be properly evaluated prior to the adoption of energy efficiency measures. The paper presents an IoT and Cloud-based energy monitoring and simulation platform that aims to help companies monitor energy production and consumption within various cost-centers, forecast the energy production potential and simulate the economic efficiency for multiple investment scenarios.

Related Organizations

Polytechnic University of Bucharest
Romania

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	12
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%