AN INTEGRATED ARTIFICIAL INTELLIGENCE AND CYBER-PHYSICAL SYSTEMS FRAMEWORK FOR NEXT-GENERATION MULTIDISCIPLINARY ENGINEERING APPLICATIONS

Abstract

The rapid evolution of engineering systems has necessitated the convergence of multiple disciplines to address increasing system complexity, autonomy requirements, and sustainability challenges. Traditional engineering approaches, which operate within isolated domain boundaries, are insufficient to meet the demands of modern intelligent infrastructures such as smart cities, autonomous manufacturing, intelligent healthcare systems, and sustainable energy networks. This research presents a comprehensive and integrated framework that combines Artificial Intelligence (AI) and Cyber-Physical Systems (CPS) to enable next-generation multidisciplinary engineering applications. The proposed framework facilitates real-time sensing, intelligent decision-making, adaptive control, and system optimization across civil, mechanical, electrical, electronics, computer, and biomedical engineering domains. Advanced machine learning models, cyber-physical integration strategies, and system-level optimization techniques are employed to enhance reliability, scalability, and performance. A detailed methodological approach, mathematical modeling, and experimental evaluation demonstrate the effectiveness of the framework in improving system intelligence, fault tolerance, and operational efficiency. The proposed study establishes a unified foundation for future interdisciplinary engineering research and development.