SMART ELECTRONICS AND EMBEDDED INTELLIGENCE: HARNESSING AI FOR HIGH-PERFORMANCE CIRCUITRY

Abstract

The convergence of artificial intelligence (AI) and electronics is reshaping the landscape of circuit design and embedded systems. By integrating AI-driven algorithms into electronic design automation (EDA), signal optimization, and embedded decision-making, smart electronics can achieve unprecedented levels of performance, adaptability, and energy efficiency. This paper investigates how embedded intelligence can be leveraged to enhance the design and operation of highperformance circuitry. We review the state-ofthe-art in AI-driven circuit design and embedded optimization, propose a synthetic benchmark to assess different AI methods, and present experimental results comparing reinforcement learning, deep neural networks, and evolutionary algorithms for circuit parameter tuning and embedded system control.