IoT Based Attendance Monitoring System Using Facial Recognition
V Darshan, Darren Sherwin Kenny, Shreyas HR, N. Vinay, S. Revathi · 2024
In educational institutions, monitoring student at- tendance is often considered cumbersome and time-consuming. While several systems have been proposed to tackle this issue, such as Radio Frequency Identification (RFID) and Near Field Communication (NFC) for hardware-based solutions, and algorithms like deep facial recognition, Haar Cascading, Local Binary Pattern Histogram (LBPH) Algorithm, and Convolution Neural Network (CNN) for facial recognition, but practical implementations are still limited. This paper presents a novel approach that combines facial recognition algorithms with IoT integration to provide a practical and real-time attendance monitoring solution. The hardware setup consists of a Raspberry Pi 3b paired with a Pi Camera sensor, providing a cost-effective and efficient solution for capturing facial images. On the software side, a web-based user interface hosted on a web server manages data storage on a dedicated database server. This interface provides administrators with real-time access to attendance data, allowing for efficient monitoring and analysis. Compared to existing solutions, our system offers several advantages, including improved accuracy, real-time monitoring capabilities, and seamless integration with existing infrastructure. The system's scalability and ease of use make it suitable for educational institutions of all sizes.