AUTOMATED ATTENDANCE AND ACCESS CONTROL SYSTEM USING REAL-TIME FACE DETECTION BASED ON RASPBERRY PI

Security and access management is one of the most critical problems facing modern society. Traditional methods are inadequate due to both security vulnerabilities and their susceptibility to human error. In this study, it is aimed to provide an innovative and effective solution to the mentioned security problems by using face recognition. Within the scope of the study, an access control and attendance system design developed using Raspberry Pi 5 microcontroller and face recognition. In the developed system, the face data of individuals who want to enter is received in real-time through an integrated camera, and this data is compared with the user face data previously defined in the system. If the algorithm detects the user correctly, the system activates the door lock mechanism and allows physical access. Otherwise, the door remains locked and access is denied. In this way, the system prevents unauthorized access by allowing only authorized individuals to enter and also automatically performs the attendance process. Also, the entry times and identity information of the users are recorded digitally. During the experiments, the system successfully recognized 29 out of 30 valid attempts, while 13 out of 15 unauthorized access attempts were correctly rejected. Based on these results, the system achieved 93.3% accuracy, 93.5% precision, and 96.7% recall. Although the system was built with low cost and easily accessible components, it operates with high accuracy rates and provides a real-time and reliable solution. The results show that face recognition systems can be used effectively for secure access control and user tracking with low cost platforms.