Exploring Intelligent Edge Computing and AI for Industrial Automation

Abstract

The advent of intelligent edge computing integrated with artificial intelligence (AI) is reshaping industrial automation by enabling real-time data analysis at the point of generation. This research explores how AI-enhanced edge computing architectures improve productivity, efficiency, and predictive maintenance in industrial environments. Unlike traditional cloud computing, edge computing reduces latency, enhances security, and facilitates immediate decision-making. The study highlights AI-enabled industrial applications such as smart robotics, supply chain optimization, energy management, and quality assurance. Additionally, the paper discusses technical challenges including device interoperability, computational limitations, and data governance. The findings demonstrate that intelligent edge computing combined with AI creates an ecosystem that supports Industry 4.0 by enabling factories to become self learning, adaptive, and resilient in an era of global competition.

KEYWORDS: Edge Computing; Artificial Intelligence; Industrial Automation; Smart Manufacturing; Industry 4.0