FACE RECOGNITION FOR SMART ATTENDANCE
| dc.contributor.author | JANANI A/P MUNUSAMY | |
| dc.date.accessioned | 2026-04-28T02:52:49Z | |
| dc.date.issued | 2025 | |
| dc.description | Attendance tracking is an essential function in educational environments, yet traditional and semi-automated methods like manual registers, QR code scanning, and fingerprint recognition often suffer from inefficiencies and vulnerabilities such as proxy attendance. This project introduces a smart attendance system that integrates facial recognition with QR code scanning and GPS-based location verification to provide a secure, contactless, and accurate attendance process. Developed as a mobile-accessible web application using modern technologies including TensorFlow.js, Vue.js, and Node.js, the system enables role-based access for admins, lecturers, and students. Admins manage users and facial data, lecturers create attendance sessions with QR codes, and students authenticate attendance by scanning QR codes, verifying their location, and performing real-time facial recognition. The system was tested with real users and shown to significantly reduce attendance fraud while improving efficiency and user experience. Limitations include the need for HTTPS and stable internet connectivity. Future enhancements will focus on developing a native mobile app and improving facial recognition in low-light conditions. | |
| dc.identifier.uri | https://scholarhub.unimas.my/handle/123456789/530 | |
| dc.language.iso | English | |
| dc.publisher | UNIVERSITI MALAYSIA SARAWAK | |
| dc.relation.ispartofseries | Faculty of Computer Science and Information Technology | |
| dc.subject | Face recognition, Smart attendance, GPS verification, QR code attendance, web-based system, Real-Time Verification. | |
| dc.title | FACE RECOGNITION FOR SMART ATTENDANCE | |
| dc.type | Final Year Project |