Auto attendance recorder and performance analyzer

• Main Authors: Kamble, V. A., Thorat, Aniket, Paramane, Bhagyashree, Jadhav, Purva, Toraskar, Prathamesh
• Format: Conference Proceeding
• Language: English
• Subjects: Artificial intelligence; Computer vision; Face recognition; Image processing; Machine learning; Scientific visualization; Students; Teachers; Time and attendance systems
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0130148

Marking attendance in a class is inconvenient, monotonous, and time-consuming. We propose a system of automatic attendance based on a deep learning architecture to prevent these issues. The automatic attendance system based on image processing consists of face recognition. Face identification is a well-studied subject in computer vision, but it remains unsolved because to substantial pose changes, varying lighting conditions, and occlusions. Also, Instructors spend more time analyzing student performance to guide him. The system will automatically mark student attendance through face recognition and criteria of minimum time of student in the classroom set by the instructor so that attendance time gets vanished. Also, the system comes with a Student Performance analysis module so that Instructor can guide students. The technologies being used are Artificial Intelligence and Data Visualization. The In time and Out time will be recorded and as per the timetable time and minimum time set by the instructor, the attendance will be marked. The attendance-based monthly report will be generated and also auto-reminders to students and parents are also included. The student data such as marks and his achievements will be fed to the system and the system will show student performance.