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Fault Tolerance in IoT Networks for Industrial Automation Using Artificial Intelligence

IJMRB | Published: October 17, 2026 | Vol. 5 Issue 5 | ISSN: 3108-1428
Mubarak Jibril Yeldu1✉
1 Department of Computer Science, Abdullahi Fodio University of Science and Technology Aliero, Nigeria.
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Abstract

The Industrial Internet of Things (IIoT) has become a fundamental component of modern industrial automation by connecting sensors, actuators, programmable logic controllers, robotic systems, machines, edge devices, and cloud platforms for continuous monitoring and intelligent control. However, the dependence of industrial operations on interconnected IoT networks introduces significant risks associated with communication failures, sensor faults, hardware degradation, software errors, cyber-attacks, congestion, and edge computing failures. A single failure can interrupt production, reduce product quality, increase maintenance costs, or create safety hazards. This paper examines the application of Artificial Intelligence (AI) to improve fault tolerance in IoT networks used for industrial automation. The paper reviews recent developments in AI based fault detection, anomaly detection, predictive maintenance, intelligent routing, and edge based recovery, and adaptive resource management. Recent studies demonstrate that machine learning can identify abnormal device and sensor behavior before failures propagate, while Software Defined Networking can support rapid route restoration and network recovery. AI enabled edge computing further reduces response latency by moving fault analysis closer to industrial devices. The paper proposes a conceptual AI enabled fault tolerant architecture consisting of an IoT sensing layer, resilient communication layer, edge intelligence layer, AI fault analysis layer, decision and recovery layer, and industrial control layer. The proposed approach combines real-time monitoring, machine-learning-based prediction, redundant communication paths, automated recovery, and predictive maintenance. The paper concludes that integrating AI with fault-tolerance mechanisms can improve industrial network availability, reliability, resilience, and operational continuity. Nevertheless, challenges involving data quality, explain ability, computational resources, cyber security, interoperability, and validation in real industrial environments require further investigation.
Keywords: Industrial Internet of Things, Fault Tolerance, Artificial Intelligence, Machine Learning, Industrial Automation.

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🔓 Open Access | Published by IR Publishing Group. This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

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