| Autor: |
Balmiki Vinod, C Santhosh Kumar, Sharma Praveen, Fezaa Laith H.A., Almusawi Muntather, Lakumanan M. |
| Jazyk: |
English<br />French |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
E3S Web of Conferences, Vol 540, p 08007 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2267-1242 |
| DOI: |
10.1051/e3sconf/202454008007 |
| Popis: |
In today’s rapidly evolving world, the demand for energy is steadily increasing, while the need for sustainability and efficient resource utilization becomes ever more critical. Smart Energy Management Systems (SEMS) are poised to play a pivotal role in addressing these challenges. Leveraging the power of Machine Learning (ML), SEMS offer a promising avenue to optimize energy consumption, enhance grid reliability, and reduce carbon footprints. This review article provides an in-depth exploration of the current state of Smart Energy Management Systems empowered by Machine Learning, highlighting their key components, applications, challenges, and future prospects. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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