Development of an AI based teaching assisting system

Abstract

Nowadays, people are facing the issues of declining birthrates and an aging society. Teaching resources are far from enough and the teachers usually have great amount of works, especially in countryside or small towns. Aim to reduce the work of teachers, we developed a teaching assisting system to automatically track and recognize the motions and behaviors of students based on artificial intelligence (AI) technology. The humans are detected accurately by combing the detection results of OpenPose and human area projection method. Each person is identified by fusing his/her personal information, including the features of color, face and moving history, and tracked by using an extended particle filter method based on Markov Chain Monte Carlo (MCMC). By observing the students' behaviors without getting tired with the sensor system instead of the teachers, the performances and growing processes of all the students can be analyzed, referring the excellent knowledge and experiences of professional teachers. This information can be provided to the teacher which can help the teachers to adjust guidance to the students. Moreover, the information can also be provided to education robot so that the robot can also held a class or have interactions with the students.