Educational information system is a hot topic in education today, and informatization is not only reflected in teaching methods. With the development of computer vision and deep learning technologies and the gradual maturity of related hardware, the application of computer algorithms and intelligent identification in distance education has become a norm. This research studies the entrepreneurial model of distance intelligent classrooms, uses machine learning technology as the basis, and combines intelligent image recognition technology to identify the status and expression of students in distance education classrooms. Moreover, this paper has carried out a more detailed study of face detection and expression recognition technology and tried to apply it to classroom teaching evaluation, which has shown certain feasibility in experiments. At the end of this article, the system was tested and analyzed with the collected data, which verified the feasibility and accuracy of the system.

Online education brings both opportunities and challenges to educational institutions. The current application of traditional intelligent mode is relatively backward, in the reform of English learning, but also pays attention to students' learning participation, which will directly affect their learning effect. Therefore, this article explores and offers appropriate recommendations. For example, the development of cloud collection technology, through the installation of classroom intelligent equipment, through intelligent voice system, identify each student's parameters and classroom environment, record students' learning state, then the machine learning results are applied to intelligent classroom management to improve the classroom time utilization rate and students' learning efficiency. The whole system also includes data acquisition equipment, management node, cloud server and cloud data management equipment platform. After designing the relevant system, this paper conducts a practical research on college students' English learning under the intelligent classroom environment. After practice, questionnaire survey was conducted on the construction and use of wisdom classroom. The data show that the use of wireless sensor network and intelligent voice system, and applied in intelligent classroom, greatly improve the students' learning participation.

Online education brings both opportunities and challenges to educational institutions. The current application of traditional intelligent mode is relatively backward, in the reform of English learning, but also pays attention to students' learning participation, which will directly affect their learning effect. Therefore, this article explores and offers appropriate recommendations. For example, the development of cloud collection technology, through the installation of classroom intelligent equipment, through intelligent voice system, identify each student's parameters and classroom environment, record students' learning state, then the machine learning results are applied to intelligent classroom management to improve the classroom time utilization rate and students' learning e ciency. The whole system also includes data acquisition equipment, management node, cloud server and cloud data management equipment platform. After designing the relevant system, this paper conducts a practical research on college students' English learning under the intelligent classroom environment. After practice, questionnaire survey was conducted on the construction and use of wisdom classroom. The data show that the use of wireless sensor network and intelligent voice system, and applied in intelligent classroom, greatly improve the students' learning participation.