The task of taking attendance is a crucial daily activity in various educational and professional settings. It is typically done manually by calling out names or roll numbers. To streamline this process and improve time management, a Face Recognition-based attendance system is proposed. This system will automate the manual process by capturing students images, names, roll numbers, class, and section. The instructors name is also added to an Excel spreadsheet that is updated hourly. Open CV is used to extract student images, and a Logitech C270 web camera and NVIDIA Jetson Nano Developer kit are employed for camera and processing. The system detects faces using a Haar cascade classifier and uses the LBPH algorithm to compare histogram data with a pre-defined dataset, resulting in automatic attendance identification. The system updates the instructors information in an Excel file, which is refreshed hourly.