Research on path selection and optimization of college English teaching based on deep learning and IoT technology

This study explores the current application status and optimisation path of Internet of Things (IoT) technology and intelligent teaching systems in business English teaching in universities, aiming to enhance students’ language application ability and cross-cultural communication ability. The gap between curriculum design and student needs was analysed through a questionnaire survey of business English majors at a certain school. The results showed that the current curriculum lacks the cultivation of business knowledge and practical abilities, making it difficult to meet the demand for versatile talents in modern society. Therefore, this study proposes an IoT-based intelligent teaching model with three modules: preparation, learning, and evaluation. The functional design of the model’s four-layer architecture of sensing, control, data, and network is described in detail. The intelligent classroom system based on this model monitors the environment in real-time through sensors, automatically adjusts classroom conditions, and improves classroom management efficiency. In addition, the intelligent attendance system combining Raspberry Pi and facial recognition technology significantly reduces traditional classroom check-in time. A survey shows that most students hope to continue the online learning component of intelligent teaching after returning to traditional classrooms.