Intelligent Communication and Advanced Technologies for Smart Hydrogen Energy Networks: A Brief Review
Rachid FATEH, Brahim MOUDOUD
Abstract. Hydrogen is being recognized as pivotal to clean and sustainable energy systems around the world. Nevertheless, in practice it has been challenging to successfully combine techniques for hydrogen production, storage and utilization due to the complexity of systems involved, which are very dynamic depending on operating conditions. This article reviews the most recent advance in artificial intelligence (AI) and communications technology for managing hydrogen energy. AI techniques (e.g. machine learning, predictive control) will advance the optimisation of systems, fault prediction and energy performance. Meanwhile, communication networks and IoT platforms enable the real-time control, data sharing and orchestration across the entire hydrogen value chain. The combination of intelligent sensors and an smart communication system increases the confidence, scalability, and operational sophistication of a Siemens IoT sensor. The study further highlights current research gaps, including data management, connectivity, and security, as well as future opportunities for research, such as on digital twins, edge computing, and IoT communication technologies. In practice, AI and communication technologies are one important direction towards smart and sustainable hydrogen energy systems.
Keywords
Hydrogen Energy, Artificial Intelligence, Machine Learning, Communication technologies, Internet of Things (IoT), Smart Energy Management, Digital Twin, Edge Computing
Published online 4/25/2026, 7 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Rachid FATEH, Brahim MOUDOUD, Intelligent Communication and Advanced Technologies for Smart Hydrogen Energy Networks: A Brief Review, Materials Research Proceedings, Vol. 64, pp 928-934, 2026
DOI: https://doi.org/10.21741/9781644904091-115
The article was published as article 115 of the book Energy Futures
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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