With the rapid development of Industry 4.0 and intelligent manufacturing, traditional embedded courses can no longer meet the industry's demand for "AI + embedded" interdisciplinary talents. This paper focuses on the empowering role of AI tools in course teaching, demonstrating the positive impact of AI technology on improving teaching quality through the construction of a three-dimensional support system comprising intelligent Q&A, learning analytics, and adaptive learning. Existing courses mostly concentrate on general embedded development, whereas this course takes measurement and control systems as its core vehicle, emphasizing the cultivation of students' practical skills in key technologies of the measurement and control field. This course introduces edge computing node deployment and lightweight AI inference frameworks to achieve localized intelligent decision-making and control optimization, reducing reliance on cloud computing. This approach more intuitively and effectively addresses the needs of students in this discipline, providing a replicable practical solution for intelligent teaching reform.
 

Artificial Intelligence, Course Reform, Electronic Information Engineering, Practical Teaching Reform