Performance Analysis of Automatic Integrated Long-Range RFID and Webcam System

In the academic environment, checking attendance can help lecturers better evaluate students' performance in university. Traditional attendance checking has some disadvantages, which are wasting time and effort. The automatic attendance monitoring system, on the other hand, not only can help us solve these drawbacks but also bring a high-accuracy result compared to manually checking. The method uses ultra-high-frequency (UHF) RFID technology with four circularly polarized antennas, combined with the high-definition camera system used for face recognition that allows the system to recognize students' faces. The system will check the attendance of students in offline classes through an RFID reader and camera which are set up in classrooms. In the case of online study in which students learn from home, the system can use students' cameras directly from their laptops and smartphones to recognize their faces and check attendance. The web-based information system has real-time updates with attendance monitoring that allows the lecturer to review or determine the student's attendance status. In the event of unexpected issues on the student side, the system enables lecturers to check attendance manually after receiving the student's request. Our system, furthermore, can automatically generate a weekly report about student's learning status in each class and provide the overall proportion of students' commitment to attending classes for the lecturer. This paper brings some initial simulations of the system to give a more detailed picture of how the new system works and interacts. Besides, this manuscript provides a detailed performance analysis about the system with RFID and camera, then has an evaluation based on class' learning outcome. The time, precision, and accuracy of our system are considered.