A SURVEY ON FACE RECOGNITION ATTENDANCE SYSTEM USING PYTHON: DESIGN, CHALLENGES AND IMPLEMENTATION
The application allows users to register, log in securely, enroll facial data, mark attendance automatically through face recognition, manage user profiles, and monitor attendance records through an interactive dashboard. The frontend interface is designed using HTML, CSS, JavaScript, and Bootstrap to ensure smooth navigation and a user-friendly experience. The backend server is developed using Python and Django for handling requests, authentication, facial recognition processing, and database communication.
SQLite/MySQL is used as the primary database for storing user information, facial encodings, attendance records, and system-related data securely. Django Authentication System is implemented to provide secure login functionality and protected route access.
The system provides efficient attendance management with real-time face detection and recognition, responsive user interaction, and reliable database operations. The application architecture ensures maintainability, scalability, and efficient communication between frontend and backend components.
jena, A. (2026). A Survey on Face recognition Attendance System Using Python: Design, Challenges and Implementation. International Journal of Science, Strategic Management and Technology, 02(6). https://doi.org/10.55041/ijsmt.v2i6.082
jena, Avijit. "A Survey on Face recognition Attendance System Using Python: Design, Challenges and Implementation." International Journal of Science, Strategic Management and Technology, vol. 02, no. 6, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i6.082.
jena, Avijit. "A Survey on Face recognition Attendance System Using Python: Design, Challenges and Implementation." International Journal of Science, Strategic Management and Technology 02, no. 6 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i6.082.
- S. Shinde, P. R. Patil, “Design and Development of Web-Based Management Systems using MERN Stack,”
International Journal of Computer Applications, 2023, pp. 10– 15.
- R. Joshi, S. K. Singh, “Full Stack Web Development using MongoDB, Express, React and Node.js,” IEEE Conference on Software Engineering, 2022, pp. 45–50.
- Patel, A. Kumar, “Secure Web Applications using JWT Authentication,” International Journal of Advanced Computer Science, 2021, pp. 88–94.
- Gupta, S. Mehta, “RESTful API Design and Implementation in Node.js,” Springer Web Technologies, 2020, pp. 120–128.
- Zhang, Y. Chen, “MongoDB: NoSQL Database for Modern Web Applications,” IEEE Access, 2019, pp. 200– 210.
- Verma, D. Singh, “Frontend Development using React.js for Responsive Web Applications,” International Journal of Web Engineering, 2022, pp. 33–40.
- Brown, “Scalable Web Architecture using Microservices and Node.js,” ACM Computing Surveys, 2021, pp. 55–62.
- H. Rogers, “Modern Full Stack Development Practices and Cloud Deployment,” Journal of Software Engineering Trends, 2023, pp. 70–78.
- Sommerville, Software Engineering, 10th Edition, Pearson, 2016.
- S. Pressman, Software Engineering: A Practitioner’s Approach, McGraw Hill, 2014.
- Freeman, E. Robson, Learning React: Modern Patterns for Web Development, O’Reilly Media, 2020.
- W. Kernighan, D. M. Ritchie, The C Programming Language, Prentice Hall, 1988.
- Chatterjee, Node.js Design Patterns, Packt Publishing, 2022.