Multi-terminal long-distance education and training system based on AI video analysis

Abstract

The invention discloses a multi-terminal long-distance education and training system based on AI video analysis. The multi-terminal long-distance education and training system includes three or more terminals, clients, cloud servers, teacher ends and management ends, the clients are installed on intelligent terminals with camera functions, so that the clients can monitor the state of customers inthe whole process of watching video through an artificial intelligence video analysis method, objective analysis is realized, and thus personalized learning advice is provided for the customers.

Description

technical field [0001] The present invention relates to the fields of artificial intelligence (AI) and distance education, in particular to a multi-terminal distance education training system based on AI video analysis. Background technique [0002] In recent years, artificial intelligence (AI) has made great progress in the field of video analysis, so that the video analysis technology based on artificial intelligence has been able to obtain a considerable part of effective information and information preliminary processing from the video. [0003] With the development and progress of Internet technology and the popularization of smart terminals, earth-shaking changes have taken place in the education industry. Distance education has become an important way for people to obtain knowledge and information, especially real-time or recorded video courses. The limitation of time and space has greatly increased the upper limit of the audience, and each customer can conduct indepe...

AI Technical Summary

Problems solved by technology

[0004] There are already some solutions and systems for distance education that can meet part of the needs of distance education, but there are still many problems in the existing technology. The first problem is that teachers and students (clients) are generally in different time and space, and teachers cannot Real-time monitoring of students' listening status, and it is impossible to evaluate and improve the course quality based on students' feedback, and there are a large number of people attending the class, and the workload of monitoring and evaluating each student's full name is huge, which cannot be solved manually; the second The problem is that most students lack self-discipline ability, and the problems of leaving and distracting cannot be solved, which greatly reduces the efficiency of video learning; the third problem is the lack of effective learning evaluation methods. The existing education system mainly relies on test questions to reflect teaching. Objective results, the course is scored by the customer filling in the subjective score, but the subjective score often has huge errors due to individual differences; the fourth problem is that after many video courses are launched, there is no evaluation feedback and improvement, and a large number of low-quality videos flood the Internet , resulting in information redundancy, customers need to spend a lot of energy to select quality courses

Images