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August 11, 20250 citations

AI-Powered Predictive Maintenance and Anomaly Detection in Network Infrastructure

Predictive Network Maintenance and Anomaly Detection with AI

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Authors

OAOluwatosin Oladayo Aramide

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Overview

This article demonstrates how predictive maintenance and anomaly detection using AI enhances infrastructure stability, improving response strategies in complex networks.

Key Points

  • Predictive maintenance significantly reduces operational downtime and enhances network resilience while identifying potential failures.
  • Artificial intelligence algorithms, particularly deep neural networks, analyze network data streams to forecast failures and detect anomalies.
  • The approach integrates edge computing and cloud platforms, demonstrating effective real-time responses across various network systems.
  • Key challenges include data quality and model interpretability, which are addressed through strategic frameworks for AI deployment.
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Cite This Study

Oluwatosin Oladayo Aramide (2025) studied this question.

synapsesocial.com/papers/68a35ef30a429f7973328478https://doi.org/10.21590/ijtmh.11.02.08
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Predictive Network Failure Analysis Using Machine Learning2020
  2. 2Enhancing Network Fault Detection with Precision Predictive AI2024
  3. 3AI-Based Approaches For Network Anomaly Detection2024
  4. 4Disrupting Downtime: Different Deep Learning Journeys into Predictive Maintenance Anomaly Detection2024 · 2 citations
  5. 5Intelligent Networks: Enhancing Infrastructure Performance through AI Optimization2023