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1719364PublishedVol 10 · Issue 1

AI-Based Smart Network Traffic Management System for Telecommunication

Imran Ahmad Khan

Subject area: Science,Engineering and Technology  ·  Area of research: Scope of AIML in Telecommunication

DOI: https://doi.org/10.64388/IREV10I1-1719364

Abstract

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.

How to cite this paper

Imran Ahmad Khan "AI-Based Smart Network Traffic Management System for Telecommunication" Iconic Research And Engineering Journals Volume 10 Issue 1 2026 Page 250-251 https://doi.org/10.64388/IREV10I1-1719364
Imran Ahmad Khan "AI-Based Smart Network Traffic Management System for Telecommunication" Iconic Research And Engineering Journals, vol. 10, no. 1, Jul. 2026, doi: https://doi.org/10.64388/IREV10I1-1719364
Imran Ahmad Khan (2026). AI-Based Smart Network Traffic Management System for Telecommunication. Iconic Research And Engineering Journals, 10(1). doi: https://doi.org/10.64388/IREV10I1-1719364
Imran Ahmad Khan "AI-Based Smart Network Traffic Management System for Telecommunication" Iconic Research And Engineering Journals, vol. 10, no. 1, Jul. 2026. Crossref, https://doi.org/10.64388/IREV10I1-1719364
@article{1719364,
      author = {Imran Ahmad Khan},
      title = {AI-Based Smart Network Traffic Management System for Telecommunication},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {1},
      pages = {250-251},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1719364.pdf},
      abstract = {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.},
      month = {July},
      doi = {https://doi.org/10.64388/IREV10I1-1719364}
  }