The telecommunication industry is experiencing rapid growth due to 5G, the Internet of Things (IoT), and an increasing number of internet users. This surge in network traffic introduces challenges like congestion, latency, packet loss, and poor Quality of Service (QoS). Traditional, rule-based traffic management systems are insufficient for dynamic conditions. This study presents an AI-Based Smart Network Traffic Management System that utilizes Artificial Intelligence and Machine Learning (ML) to analyze patterns, predict congestion probability, and optimize network resource allocation, significantly improving network efficiency over traditional approaches.
Imran Ahmad Khan (Fri,) studied this question.