AI-Powered Carbon Footprint Tracking for IT Operations
Abstract
IT operations contribute significantly to carbon emissions through energy-intensive processes. This paper presents an AI-driven system for real-time tracking and reduction of carbon footprints in IT environments. By analyzing energy consumption patterns and workload distributions, the system employs machine learning algorithms to recommend energy-efficient practices. A deployment in a cloud data center reduced carbon emissions by 22% while maintaining service levels. The research supports SDG 13: Climate Action and SDG 7: Affordable and Clean Energy, emphasizing sustainable IT operations.
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