Driven by the concept of wisdom education and the development needs of the times, personalized teaching has become a new requirement for the quality of talent cultivation under the national innovation-driven development strategy, and it is the inevitable trend of the current education and teaching reform. This paper builds a personalized teaching system in the era of smart education, based on the characteristics of local comprehensive universities. Face recognition technology is used to analyze the learning behavior of students in the smart campus, combined with virtualization technology and bilateral resources to integrate the teaching service model to realize the distribution of teaching service demand, and the classroom behavior is analyzed by deep intelligence through natural language processing technology. The proposed personalized teaching system is being implemented at Henan University of Science and Technology for specific practical analysis. The practical results show that the occupancy rate of students’ behavior in class 2 with the personalized teaching system is 0.3525 higher than that in class 1 with the traditional teaching system, and the occupancy rate of teachers’ behavior is 0.5422, with a higher conversion rate of teachers’ and students’ behavior. It shows that the new personalized teaching system is student-oriented and can effectively cultivate the quality of students is of great significance for the educational and teaching reform of the same type of colleges and universities.