Optimizing energy and water consumption in smart buildings is a critical challenge for enhancing sustainability and reducing operational costs. This paper presents a Cyber-Physical System (CPS) framework that integrates Deep Reinforcement Learning (DRL) and Genetic Algorithms (GA) for real-time...

This study explores the integration of Variational Autoencoders (VAEs) and Genetic Programming (GP) to address key challenges in the development of smart cities as cyber-physical systems (CPS). The primary objective is to enhance decision-making processes, optimize resource allocation, and...