Archive | 2019
Biometric Attendance Management System using Raspberry Pi
Abstract
In every organization or company, attendance is an aspect that is of major importance and is recorded on a daily basis. Currently, in many institutions, attendance is recorded by using a sheet of paper on which students sign in front of their name. The major drawback of this system is that a student may forge his/her friends’ signature even though they are absent. Keeping a track of the number and names of students present in the class is a time-consuming job and costs a lot of working hours of the faculty. This time can be saved if the current method of recording attendance is replaced by some method that consumes less time. After recording the attendance, the next tedious task is of generating reports based on the recorded data. This task can easily be automated. In this paper, we describe ways to curb the existing problem through our biometric attendance management system with customized report generation. Raspberry Pi is used to transmit data and our hardware modules are connected to it. The system provides two ways-Fingerprint Module and Facial Recognition Module in order to record attendance uniquely by checking pre-registered data. In case the main method (fingerprint module) fails to work, students can use the facial recognition module. We have used LBPH face recognizer and Haar Cascade method to implement face detection and recognition. The system, after recording attendance, sends data to Real-time database using Firebase and this data can be retrieved on the Web Application. The system is also able to generate customized report of attendance. Our system stands out from other existing biometric attendance management systems as, our system provides a fullyfunctional backup method to record attendance in case our primary method fails or takes inappropriately long time. Once after all the students have recorded attendance, the data gets sent to the Firebase. KeywordsBiometric, Facial Recognition, Fingerprint Module, Raspberry Pi, LBPH Face Recognizer, Haar Cascade, Firebase, Customized report