
AI-Based Attendance Monitoring System
Author(s) -
Kanamata Reddy,
S H Manjula,
M Rashmi,
N Simhachalam Reddy,
Sushma Manjula T-Obtained,
Ms Rashmi K -
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b1057.1292s19
Subject(s) - attendance , class (philosophy) , computer science , biometrics , mathematics education , multimedia , psychology , artificial intelligence , political science , law
Attendance Monitoring System is essential in all organizations for checking the performance of students and it is not easy task to check each and every student is present or not. In all organization attendance are taken manually by calling their register numbers or names and noted in attendance registers issued by the department heads as a proof and in some organizations the students wants to sign in these sheets which are stored for future references. This technique is repetitive, complex work and leads to errors as few students regularly sign for their absent students or telling proxy attendance of the absent students. This method additionally makes it more complex to track all the students attendance and difficult to monitoring the individual student attendance in a big classroom atmosphere. In this article, we use are using the technique of utilization face detection and recognition framework to contunisuly recognize students going to class or not and marking their attendance by comparing their faces with database to match and marking attendance. This facial biometric framework takes a picture of a person using camera and contrast that image and compare the image with the image with is stored at the time of enrolment and if it matches marks the attendance and monitor the student performance contunisuly. We may use the concept of artificial intelligence concept to monitor student attendance like capturing the motion pictures of the student when present in class to analyze the student data how much time the student presents in class.