MONITORING OF THE EDUCATIONAL PROCESS USING ARTIFICIAL INTELLIGENCE METHODS

Abstract

Considered the problem of increasing the effectiveness of the educational process due to the introduction of automatic control of attendance in the classroom using face recognition and additional information for the collection and further analysis of the received data. Algorithms and methods used in modern Facial Recognition Attendance System are studied. An intelligent system for monitoring the educational process and its analysis is proposed. Structural and functional schemes of the system, databases, software were developed, testing was carried out. During attendance monitoring, the webcam captures an image of the face of the participant of the educational process from the video stream, then the computer automatically creates a vector of facial features, which is compared with the vectors of facial features, pre-entered images and recorded in the relevant database. Vectors with 68 features are used for face recognition. In the development of the software, the tools of the OpenCV library and the Python programming language were used. With several successful comparisons, the person's data is identified: name and status (student or teacher), the current date and time are recorded in an Excel file. Operational data of the system is displayed on the monitor screen, which allows you to correct recognition errors if necessary. The system allows you to automatically keep a log of class attendance, create reports, analyze data to provide recommendations for improving the schedule and order of lessons. The object-relational database with open source code PostgreSQL is used for data storage. The grouping of the system's software code is carried out using the Django web application. The system user has the opportunity to create a personal account and create reports according to his requirements. The system was tested on the example of a group of 15 students and showed satisfactory results.