FACE ATTENDANCE SYSTEM USING GPS TRACKING IN ANDROID APPLICATIONS

The paper describes the system is a student attendance system that utilizes GPS tracking and multi-CNN (Convolutional Neural Network) technology for face attendance system . The system aims to simplify the attendance process for students and teachers while providing accurate and efficient attendance tracking. The system utilizes GPS tracking to determine the location of the student and confirm their presence in the classroom. The multi-CNN technology is used to enhance the accuracy of the attendance tracking. The multi-CNN system combines several CNN models to improve the accuracy of the attendance tracking process. The system also utilizes facial recognition technology to ensure that the correct student is marked as present. The system comprises of a mobile application for students and a web-based dashboard for teachers. The mobile application is used by students to check-in to their respective classes. The application uses GPS tracking to determine the student’s location and confirms their attendance. The facial recognition technology ensures that the correct student is marked as present. The web-based dashboard is used by teachers to monitor attendance and track the students’ attendance history. The dashboard displays a real-time attendance report, which shows the number of students present and absent in the class. The dashboard also allows teachers to view the attendance history of individual students and generate reports.