Seamless Attendance Monitoring with Face Recognition and RFID Technology

Reliable and accurate attendance monitoring systems are very essential in modern corporate and educational environments. Traditional methods for monitoring attendance are usually prone to errors, inefficiency, and influential. In order to enhance accuracy, security, and ease, this study provides a seam-less attendance tracking system that combines face recognition technology with Radio Frequency Identification (RFID). The face recognition offers a discrete and legitimate way to identify people, while RFID enables rapid and automatic logging of attendance data. By combining these technologies, a reliable and secure approach to tracking attendance is provided, reducing the possibility of human mistake and resisting attempts by fraudsters to use proxies. To ensure that only authorized people are recorded, the face recognition module uses advanced algorithms such as you Only Look Once (YOLOv8) and Histogram of Oriented gradients (HOG) to detect and recognize faces in real-time. At the same time, the RFID module confirms the existence of people inside the approved area by reading RFID tags included in ID cards. The attendance data are recorded and stored in a central database using Message Queuing Telemetry Transport Protocol (MQTT) making it simple to access and retrieve the information for reporting and analysis. This hybrid method improves security and accuracy while streamlining the attendance procedure. The system is made to be easily scalable, customizable, and suitable for a range of institutional environments. The suggested approach has the potential to replace conventional attendance systems in businesses, educational institutions, and other settings needing accurate attendance monitoring.