This paper focuses on the development and application of intelligent teaching resource databases in the field of automotive maintenance remote practical training. It first elaborates on the new requirements for professionals in the automotive maintenance industry and the limitations of traditional practical training models, emphasizing the necessity of developing intelligent teaching resource databases. It then details the development process of such a database, including architectural design, content planning, and technical implementation. Following this, it delves into its application in automotive maintenance remote practical training, such as enhancing training effectiveness, promoting personalized learning, and achieving resource sharing. Finally, it analyzes potential challenges in the application process and proposes corresponding solutions. The aim is to provide more efficient and high-quality teaching support for automotive maintenance remote practical training and promote the development of automotive maintenance professional education.