LEVERAGING AI AND ML TO REVOLUTIONIZE ENERGY EFFICIENCY IN DATA CENTERS
This article explores the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on energy efficiency in data centers. It examines various areas where these technologies drive significant improvements, including predictive analytics, dynamic cooling management, smart workload scheduling, automated peak shaving, real-time optimization, enhanced maintenance strategies, and holistic system integration. Implementing AI/ML solutions optimizes operational costs and contributes to sustainability efforts by reducing the overall carbon footprint of data center facilities. Through continuous analysis, immediate adjustments, and unified optimization across subsystems, AI-driven approaches achieve substantial energy savings while maintaining or improving performance. The article discusses the current state of AI applications in data centers and looks ahead to potential future developments in this rapidly evolving field.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-08-08
- DOI
- https://doi.org/10.5281/zenodo.13269832
- Citations
- 1
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 0.78