Convergence of Computer Vision, AR, and Generative AI: A Novel Framework for Hyperscale Data Center Management

This article presents an innovative framework integrating computer vision, augmented reality (AR), and generative AI technologies to revolutionize hyperscale Data Center management. The proposed system employs machine learning-based computer vision for automated asset identification and tracking, while AR overlays provide real-time maintenance guidance to non-technical personnel. Generative AI enhances the framework by enabling interactive troubleshooting and predictive analysis capabilities. The article demonstrates significant improvements in operational efficiency, reduced response times, and enhanced maintenance accuracy through this integrated approach. The article also explores implementation challenges and provides insights into scalability considerations for large-scale deployment. This article contributes to the growing body of knowledge in intelligent Data Center management systems and presents a novel approach to combining emerging technologies for improved infrastructure maintenance and operational reliability. The framework's ability to empower non-technical staff while maintaining high operational standards suggests promising applications across various scales of Data Center operations.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2025-02-18
DOI
https://doi.org/10.32628/cseit251112303
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Convergence of Computer Vision, AR, and Generative AI: A Novel Framework for Hyperscale Data Center Management

Venkata Sampath Kumar Mutharaju
International Journal of Scientific Research in Computer Science Engineering and Information Technology
IoT and Edge/Fog Computing
article

Convergence of Computer Vision, AR, and Generative AI: A Novel Framework for Hyperscale Data Center Management

Venkata Sampath Kumar Mutharaju
article en

Abstract

This article presents an innovative framework integrating computer vision, augmented reality (AR), and generative AI technologies to revolutionize hyperscale Data Center management. The proposed system employs machine learning-based computer vision for automated asset identification and tracking, while AR overlays provide real-time maintenance guidance to non-technical personnel. Generative AI enhances the framework by enabling interactive troubleshooting and predictive analysis capabilities. The article demonstrates significant improvements in operational efficiency, reduced response times, and enhanced maintenance accuracy through this integrated approach. The article also explores implementation challenges and provides insights into scalability considerations for large-scale deployment. This article contributes to the growing body of knowledge in intelligent Data Center management systems and presents a novel approach to combining emerging technologies for improved infrastructure maintenance and operational reliability. The framework's ability to empower non-technical staff while maintaining high operational standards suggests promising applications across various scales of Data Center operations.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 11(1)
The University of Texas at Austin (US)
Openalex Percentile: Top 97%
IoT and Edge/Fog Computing
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Convergence of Computer Vision, AR, and Generative AI: A Novel Framework for Hyperscale Data Center Management — Venkata Sampath Kumar Mutharaju · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2025) | TGRS Research Map | TGRS