TIE 202 builds upon TIE 201 by diving deeper into optimizing AIoT systems through advanced edge computing and machine learning techniques. This course emphasizes the intersection of analytical engineering methods and cutting-edge IoT technologies. Topics include frequency domain analysis, multi-dimensional system dynamics, and advanced embedded systems design. Students will focus on optimizing real-time data processing systems, integrating machine learning for tasks like image recognition and predictive control, while maintaining power efficiency and ensuring secure data transmission at the edge. Security concepts such as encryption, secure communication protocols, and authentication mechanisms will be explored to protect sensitive data and ensure system reliability. The course also covers complex robotic systems, including advanced motion planning and real-time sensor integration for autonomous navigation. Students will undertake project-based work to optimize existing AIoT systems by applying machine learning, improving control algorithms, implementing security measures, and enhancing system performance through advanced edge computing techniques. This course challenges students to bridge theoretical concepts with practical, high-performance, and secure solutions.