Edge Intelligence for Real-Time Industrial Automation Systems

  • Authors

    • Mr. Vikram Sethi Senior Consultant, Deloitte, India Author

    DOI:

    https://doi.org/10.67228/30715725/IJIARE-2025PI2F4U

    Published 01-04-2025

  • Edge Intelligence, Industrial Automation, Industrial Internet of Things (IIoT), Edge Computing, Artificial Intelligence, Smart Manufacturing, Real-Time Decision Making, Predictive Maintenance, Industry 4.0, Cyber-Physical Production Systems

    Issue

    Vol. 8 No. 1 (2025)

    Section

    Articles

    How to Cite

    [1]
    V. Sethi, “Edge Intelligence for Real-Time Industrial Automation Systems”, IJIARE, vol. 8, no. 1, pp. 01–15, Jan. 2025, doi: 10.67228/30715725/IJIARE-2025PI2F4U.

  • Abstract

    The Fourth Industrial Revolution is accelerating the adoption of Industry 4.0 through intelligent computing, Industrial Internet of Things (IIoT), edge computing, and AI-driven automation. Traditional cloud-based industrial systems often experience latency, bandwidth limitations, network congestion, and privacy concerns, making them unsuitable for real-time manufacturing applications. This paper proposes an Edge Intelligence framework that integrates distributed edge computing, real-time AI analytics, and autonomous decision-making to process industrial IoT data locally. The architecture consists of four layers: perception, edge intelligence, autonomous decision, and cloud coordination. Industrial sensors, PLCs, and robotic systems collect operational data, while lightweight machine learning, deep learning, and reinforcement learning models perform feature extraction, anomaly detection, predictive analytics, and adaptive control with minimal latency. A mathematical optimization model minimizes processing delay, energy consumption, and resource utilization while maximizing accuracy and efficiency. Experimental evaluation demonstrates improved real-time performance, decision accuracy, fault detection, scalability, and resource utilization, making the framework well suited for next-generation smart manufacturing and sustainable industrial automation.

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