A Smart Face Biometric Verification Oriented Attendance Handling System Using Artificial Intelligence

The use of facial recognition for biometric authentication in applications like access control and attendance tracking has made it a popular area of study in recent years. Even though monitoring a simple attendance record might be tedious and time-consuming, attendance management solutions are crucial to the success of any business. Biometrics, radio frequency identification, eye tracking, and voice recognition are just few of the numerous automated methods used to identify people. When it comes to verifying a person’s identification, facial recognition is among the most used methods. The system underlying this will be advanced facial recognition technology. One of a person’s distinguishing characteristics is their facial features. Since there is a little chance of face deviating or being replicated, it may be used to track individuals. In this system, we provide a unique AI-based technique called Artificial Intelligence based Face Biometric Verification (AIFBV), which is responsible for building the face databases that will be used in the subsequent data analysis performed by the suggested recognizer algorithm. Then, during the session when attendance is being taken, photographs of attendees' faces will be matched to those in the database. When a person is recognized, their attendance will be recorded and exported to an Excel spreadsheet mechanically. The daily attendance tally is recorded in an Excel spreadsheet and sent to the appropriate teachers at the close of class. Face detection and recognition using the identified face are the key implementation phases utilized in this sort of system, and dlib is used for both. After these steps are completed, a comparison of the identified faces to a database of student photos should reveal any hidden connections. This strategy will prove to be an effective method for monitoring student attendance.