Contactless Attendance System Using Raspberry Pi4

Abstract

Traditional attendance-taking techniques have sev- eral flaws. To address these challenges, most institutions have adopted a contemporary approach and embraced technology for greater accuracy, such as RFID and biometric systems. However, these systems have limitations of their own. For example, RFID identification may be lost or misused, resulting in false identifica- tion, and biometrics can be time-consuming, which is a concern since attendance is typically collected during peak hours. Due to these difficulties, both of these strategies are inefficient. Our project aims to create a contactless attendance system that uses deep learning-based facial recognition. This system will allow various businesses to save time and costs while improving security. Our project is an all-in-one package that includes both hardware and software and can be used without the need for additional devices. This makes our proposed system both independent and user-friendly. The proposed hardware system consists of a Raspberry Pi 4, a camera for facial identification, a keyboard for ease of access, and a touch-enabled screen. We use OpenCV's face detection and the deep learning-based dlib package, which allows our solution to be efficient on a low-power computing device like the Raspberry Pi, making it deployable anywhere.