ARTIFICIAL INTELLIGENCE-BASED FAULT DETECTION AND MONITORING IN OPTICAL TELECOMMUNICATION NETWORKS
Ismatova Sevara Quvondiq qiziTashkent University of Information Technologies Named After Muhammad Al-KhwarizmiToshpoʻlatova Marjona Azamat qiziTashkent University of Information Technologies Named After Muhammad Al-KhwarizmiYarashov Oybek To'lqin o'g'liTashkent University of Information Technologies Named After Muhammad Al-KhwarizmiOchilov Laziz SiddiqovichTashkent University of Information Technologies Named After Muhammad Al-Khwarizmi
Zenodo (CERN European Organization for Nuclear Research)repository2026
ABI
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This article analyzes modern methods of artificial intelligence-based fault detection and monitoring in optical telecommunication networks. The study investigates the application of machine learning and artificial intelligence technologies for detecting communication failures, signal quality degradation, fiber damage, and traffic load variations in optical networks. Particular attention is given to neural networks, deep learning algorithms, and real-time monitoring systems. The research findings demonstrate that artificial intelligence technologies play a significant role in rapid fault detection, predictive maintenance, and service quality improvement in optical telecommunication infrastructures.
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