Utilizing AI-Driven DevOps for Predictive Maintenance and Anomaly Detection in Smart Grids.

Abstract

The research presents an analysis of the enhancement process of AI-driven DevOps in grid management by modifying
anomaly detection, predictive maintenance and entire system effectiveness. It involves an AI driven continuous
feedback loop between these two areas, to get the best delivery and upgrades of the AI models. This collaboration
helps improve system reliability as well as speed up the deployment of needed updates, requiring the smart grid to run
as close to optimal as possible.