AI-Driven Digital Twin for Energy Optimization in Green Data Centers

Oktria ; Isni
International Journal Science and Technology (IJST... 📅 2025 Vol 4, No 2 🔗 DOI: 10.56127/ijst.v4i2.2249
Abstract
This study proposes the development of an AI-driven digital twin for data centers aimed at improving energy efficiency, reducing carbon footprint, and enhancing operational performance. The digital twin—a virtual replica of the physical data center—will be equipped with real-time AI algorithms to predict thermal loads, analyze cooling requirements, and automatically adjust operations to minimize energy consumption. This paper explores the integration of AI with digital twin architectures, tests its performance in simulated scenarios, and evaluates potential energy savings as well as contributions to Green IT practices.
Keywords
Artificial Intelligence (AI); Digital Twin; Green Data Center; Energy Optimization; Power Usage Effectiveness (PUE); Carbon Usage Effectiveness (CUE); Sustainable Computing
How to Cite

Oktria & Isni (2025). AI-Driven Digital Twin for Energy Optimization in Green Data Centers. International Journal Science and Technology (IJST), 4(2). https://doi.org/10.56127/ijst.v4i2.2249

Oktria, Isni, "AI-Driven Digital Twin for Energy Optimization in Green Data Centers," International Journal Science and Technology (IJST), vol. 4, no. 2, 2025.

Oktria, Isni. "AI-Driven Digital Twin for Energy Optimization in Green Data Centers." International Journal Science and Technology (IJST), vol. 4, no. 2, 2025.

Oktria, Isni. "AI-Driven Digital Twin for Energy Optimization in Green Data Centers." International Journal Science and Technology (IJST) 4, no. 2 (2025).

Oktria & Isni (2025) 'AI-Driven Digital Twin for Energy Optimization in Green Data Centers', International Journal Science and Technology (IJST), 4(2). doi: 10.56127/ijst.v4i2.2249.

Oktria, Isni. AI-Driven Digital Twin for Energy Optimization in Green Data Centers. International Journal Science and Technology (IJST). 2025;4(2).

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