Monitor Learning for Virtual Classroom

Face recognition technology is widely used to identify or verify the subject through images or videos. There are various face recognition techniques that are developed in the past and used in various applications. The phenomenal extension and subsequent increase of use of technology and innovations has led to an increase in their use in higher education over the past few decades. The adaptation to the virtual classroom has increased in most educational institutions, especially after the spread of the Novel Coronavirus though there is failure to engage students in their learning. In this paper, a solution is proposed to monitor student(s) in virtual classrooms. “Monitor Learning for Virtual Classroom” detects the person(s) face from the camera or through the video and identifies them firstly which helps to ensure the presence of the person for attendance. A trained model detects facial expression of a person and also whether the subject is using any objects like mobile or not. This technique differentiates people in various conditions, light conditions as well in different posture. Using the microphone of the devices this system also detects the surrounding noise which helps to prepare a report. This solution deals with the current problem as well as in the future that help to ensure the quality of education for virtual classrooms, distant learning or some other form of remote learning.