The rapid advancement of digital technologies has driven the emergence of smart systems as a transformative paradigm in modern engineering. These systems integrate physical components with computational intelligence to enable real-time sensing, decision-making, and autonomous operation. This study examines the integration of mechatronics and computer science as the foundational framework for the development of smart systems. Mechatronics provides the physical infrastructure through sensors, actuators, and control mechanisms, while computer science contributes intelligent capabilities through algorithms, artificial intelligence, and data processing techniques. The convergence of these domains results in the development of cyber–physical systems that underpin Industry 4.0 and emerging technological ecosystems. The paper adopts a conceptual and analytical approach to explore the architecture, enabling technologies, and applications of smart systems across sectors such as manufacturing, healthcare, transportation, and agriculture. It further evaluates the benefits of integration, including enhanced automation, real-time optimization, improved accuracy, and sustainability, while critically examining challenges such as system complexity, interoperability issues, cybersecurity risks, high implementation costs, and skill gaps. The study identifies key research gaps in the lack of unified integration frameworks and limited synchronization between physical and computational layers. In response, it emphasizes the need for holistic system design approaches that enable seamless interaction between mechatronic and computational components. Finally, the paper highlights future trends, including AI-driven autonomous systems, digital twin technologies, Industry 5.0, and sustainable smart systems. It concludes that the integration of mechatronics and computer science is essential for advancing intelligent, adaptive, and scalable systems capable of addressing the complexities of modern engineering and industrial environments.