Intelligent Network Management: Integration of AI/ML Technologies in Modern Telecommunications Infrastructure - Nagappan Nagappan Palaniappan, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
This article examines the transformative impact of artificial intelligence and machine learning technologies on modern telecommunications infrastructure, with a particular focus on network traffic optimization. It presents a comprehensive analysis of how AI-driven solutions are revolutionizing predictive maintenance protocols, real-time traffic management, and anomaly detection in telecommunication networks. Through an exploration of reinforcement learning applications in dynamic routing and quality of service optimization, this article demonstrates significant improvements in network reliability and operational efficiency. It is drawn from recent implementations across major telecommunications providers and presents novel frameworks for integrating AI/ML solutions with existing network infrastructure. It indicates that AI-enhanced systems consistently outperform traditional network management approaches in both preemptive maintenance and real-time optimization scenarios. This article contributes to the growing body of literature on intelligent network systems while providing practical insights for telecommunications operators transitioning toward AI-driven infrastructure management.
Keywords: Network Traffic Optimization; Predictive Maintenance; Machine Learning in Telecommunications; Reinforcement Learning; Anomaly Detection Systems