AI-Driven embedded systems for industrial automation

This paper explores the integration of artificial intelligence techniques in embedded systems for industrial automation applications. We examine how AI algorithms can enhance embedded systems' capabilities in monitoring, control, diagnostics, and optimization within industrial environments. Our analysis covers implementation challenges, performance considerations, and emerging trends based on literature published before 2020. Through examination of case studies and experimental data, we demonstrate that AI-driven embedded systems offer significant improvements in efficiency, predictive maintenance, and autonomous decision-making in industrial automation contexts.