Face Recognition Based Identity Verification and Tracking System Design

The use and importance of various authentication systems are increasing in order to enhance the security of data access processes and to enable authorized logins to work environments. In this study, a facial recognition-based authentication and personnel tracking system automation was developed. The developed system runs on a Raspberry Pi. Images obtained through the camera module are analyzed using facial recognition algorithms. The face detection algorithm was used to determine the location of human faces in the image captured by the camera. This process was performed using the face recognition library's HOG (Histogram of Oriented Gradients) based face detection method. The entry and exit times of identified individuals are automatically recorded, and this data can be viewed via a web-based interface. The system enables the successful generation of detailed reports on information such as employee entry and exit times and break durations. The developed system offers a low-cost, real-time, contactless, and IoT-compatible solution to enhance organizational/data security. The results of the study show that the developed system is applicable to employee tracking applications.