A Review on Face Recognition for Automated Student Attendance System Using IOT

The IoT-based smart attendance system recognises students’ faces using biometrics captured by monitor cameras. Our smart attendance project uses a Raspberry Pi system to quickly and accurately recognise human faces in photos. The traditional approach of calling out students’ names is time-consuming and may result in proxy attendance. The suggested system uses facial recognition to store student attendance records. When taking attendance, the system captures images of attendees and uses face detection and recognition to mark them as present. Attendance is updated with time, name, and register number. We utilised deep learning techniques to create this project. To preserve discipline and allow students to learn the most in schools, colleges, and universities, an attendance system has been implemented. There are two common methods for determining the presence of students in a particular class. The first is by calling the roll number, and the second is by having the pupils sign a piece of paper next to their roll number. As a result, it was important to improve this system so that it was more user-friendly, time-saving, and efficient. It is an automated technology that allows professors to participate in the full class without interruption or loss of time.