Deep Learning Approaches for Energy Optimization in CPS: A survey

Abstract

Cyber-physical systems (CPS) are an essential component of modern applications, but their energy consumption is a major challenge. This study aims to explore ways to improve the energy efficiency of these systems by applying advanced artificial intelligence techniques. Our methodology includes a comprehensive analysis of existing AI-based methods, with a focus on developing a model that combines deep learning, multi-objective optimization techniques, and adaptive intelligence algorithms. Through this research, we aim to provide a viable theoretical framework for enhancing the sustainability of cyber-physical systems. The results of this study are expected to contribute to the development of greener technologies in areas such as the Internet of Things and smart cities, while maintaining system performance.