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

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.