COURSE CURRICULUM

The Embedded Systems & System Integration module is divided into two parts. The first part focuses on embedded systems, introducing students to the fundamentals of C programming for microcontrollers, interrupts, shared-data problems, and the use of sub-routines, co-routines, semaphores, and real-time operating systems (RTOS). Students will also explore assembly language programming and compare it with C programming in microcontroller applications. This part is designed to help students critically analyze engineering problems related to embedded systems and develop both experimental and theoretical skills in this field. The second part covers system integration, introducing Mechatronic philosophies for system design and integration. Students will learn tools and techniques for system analysis, design, modeling, simulation, evaluation, and validation. The module also incorporates case studies and introduces students to Digital Twin technology leveraging Model-Based System Engineering (MBSE).The Machine Vision, Robotics, and Artificial Intelligence module provides both conceptual and in-depth knowledge of robotics, machine vision, and AI. The module explores key concepts, challenges, and developments within these technologies, enabling students to understand their applications and advancements. It provides practical insights into how these technologies are shaping the engineering landscape.The Engineering Business Environment and Research Methods module focuses on the role of business in a rapidly changing global context. It explores opportunities and challenges arising from environmental policies, legislation, and societal changes. Topics such as supply chain management, green accounting, and carbon trading are covered, and students reflect on how businesses can adapt to new economic models and contribute to sustainable development. The research methods component of the module equips students with the skills to undertake independent research, preparing them to address engineering business challenges.The Digital Signal Processing, Control, and Instrumentation module is divided into two parts. The first part covers digital signal processing (DSP) applications, including signal analysis and computational methods for processing digital signals and images in time and frequency domains. The second part focuses on control and instrumentation systems, providing advanced knowledge of state-space representation and control theory. Students will engage with practical laboratory experiments and use computer-aided design tools like MATLAB. The module emphasizes the development of critical problem-solving skills related to control and instrumentation systems.The Individual Project module merges the Dissertation and Individual Project modules. It encourages students to conduct independent research within a set timeframe, either in a practical or desktop-based context. The project involves self-organization and analysis, culminating in a 10,000 to 15,000-word report. Students can select a topic relevant to their course and must work under the guidance of a supervisor. This module enhances students' research and presentation skills, preparing them for professional or academic careers.