Edge Intelligence Framework for Real-Time Industrial Automation and Process Control Systems

Abstract

The rapid evolution of Industry 4.0 technologies has increased the demand for intelligent industrial automation systems capable of performing real-time data processing, adaptive control, and low-latency decision-making. Conventional cloud-centric industrial architectures often face challenges related to communication delays, bandwidth limitations, data security, and reduced responsiveness in time-critical industrial applications. This research presents an edge intelligence framework for real-time industrial automation and process control systems to enhance operational efficiency, responsiveness, and intelligent decision-making capabilities in modern industrial environments. The proposed framework integrates edge computing, artificial intelligence algorithms, Industrial Internet of Things (IIoT) devices, and real-time communication technologies to enable decentralized data processing and autonomous process optimization at the network edge. Industrial sensors and smart devices continuously collect operational data related to machine performance, production conditions, and process parameters, which are analyzed locally using intelligent edge analytics mechanisms. The framework incorporates machine learning–based predictive models, adaptive control algorithms, and anomaly detection techniques to support real-time process monitoring, fault prediction, and automated control actions with minimal latency. Performance evaluation is conducted using parameters such as response time, processing efficiency, communication overhead reduction, fault detection accuracy, energy utilization, and system reliability. Experimental and simulation-based analysis demonstrate that the proposed edge intelligence framework significantly improves real-time process control capability, reduces network dependency, and enhances operational reliability compared with conventional centralized industrial automation systems. The findings further indicate improved scalability, reduced data transmission latency, and enhanced decision-making efficiency through distributed intelligence mechanisms.