Data science leverage and big data analysis for Internet of Things energy systems

Arman Behnam, Sasan Azad, Mousa Marzband, Mohammadreza Daneshvar, Amjad Anvari-Moghaddam

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


With the development of new artificial intelligence and data science (DS) technologies, their applications for implementing analysis in the Internet of Things (IoT) energy systems are becoming more important for smart grids (SGs). DS approaches integrated with IoT data collection protocols in energy sectors can help in improving efficiency in such areas. It will give insight to administrators to manage the system in a data-driven way. Data gathering by sensors is an important step in IoT-based energy grids when it comes to a large amount of data. In the real-time data collection process, the frequency of data rises to become big data and the analysis needs new methods to manage and evaluate this data. The outcome of these analytics comes up as SG intelligence so the system becomes smart, which is depicted as demographics, figures, and informative dashboards. In this chapter, all these kinds of tools and analytics are discussed with attention to data-driven decision-making in smart energy systems.

Original languageEnglish
Title of host publicationIoT Enabled Multi-Energy Systems
Subtitle of host publicationFrom Isolated Energy Grids to Modern Interconnected Networks
EditorsMohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Kazem Zare, Amjad Anvari-Moghaddam
Place of PublicationLondon
PublisherAcademic Press
ISBN (Electronic)9780323957809
ISBN (Print)9780323954211
Publication statusPublished - 3 Mar 2023

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