Real-Time Internet Based Attendance Using Face Recognition System

  • Authors

    • Yuslinda Wati Mohamad Yusof
    • Muhammad Asyraf Mohd Nasir
    • Kama Azura Othman
    • Saiful Izwan Suliman
    • Shahrani Shahbudin
    • Roslina Mohamad
    2018-08-13
    https://doi.org/10.14419/ijet.v7i3.15.17524
  • Attendance, Face Recognition, Internet of Thing, Raspberry PI, Real Time.
  • This project focuses on face recognition implementation in creating fully automated attendance system with a cloud. Cloud services will provide a useful information regarding the attendance such as attendance summary performance and visualizing the data into graph and chart. In this study, we aim to create an online student attendance database, interfaced with a face recognition system based on raspberry pi 3 model B. A graphical user interface (GUI) will provide ease of use for data analysis on the attendance system. This work used open computer vision library and python for face recognition system combined with SFTP to establish connection to an internet server which runs on PHP and Node.js. The results showed that by interfacing a face recognition system with a server, a real-time attendance system can be built and be monitored remotely.

     

     

  • References

    1. [1] P. Mehta, “An Efficient Attendance Management Sytem based on Face Recognition using Matlab and Raspberry Pi 2,†International Journal of Engineering Technology Science and Research IJETSR, 2016; 3(5): 71–78.

      [2] H. P. LeBlanc, “The Relationship between Attendance and Grades in the College Classroom,†17th Annual Meeting of the International Academy of Business Disciplines, Pittsburg Pennsylvania, 2005; 643(210):1–19.

      [3] A. A. Mohammed and U. Jyothi Kameswari, “Web-Server based Student Attendance System using RFID Technology,†International Journal of Engineering Trends and Technology (IJETT), 2013; 4(5):1559–1563.

      [4] S. C. Gaddam and N. V. K. Ramesh, “Attendance management and user security system’s based on Eigen faces algorithm using Raspberry pi 2 and ethernet,†Indian Journal of Science and Technology, 2016; 9(17): 8107–8112.

      [5] P. S. S. Srivignessh and M. Bhaskar, “RFID and pose invariant face verification based automated classroom attendance system,†International Conference on Microelectronics, Computing and Communication, MicroCom, 2016:1-6.

      [6] V. O. Adeniji, M. S. Scott, and N. Phumzile, “Development of an Online Biometric- enabled Class Attendance Register System,†IST-Africa 2016 Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2016: 1–8.

      [7] J. Lámer, O. Kainz, and F. Jakab, “Marker based attendance systems in education process,†13th International Conference on Emerging eLearning Technologies and Applications (ICETA), 2015.

      [8] S. Maravi, R. Pinter, V. Vojni, V. Tumbas, and Č. Petar, “Smartphone Application for Tracking Students’ Class Attendance,†SISY 2016 IEEE 14th International Symposium on Intelligent Systems and Informatics August, 2016: 227–232.

      [9] J. D. Sweetlin, V. Aswini, and R. Dhanusha, “Speech Based Attendance Application Register,†Fifth International Conference On Recenet Trends In Information Technology, 2016:1-5.

      [10] P. Wagh, “Attendance System based on Face Recognition using Eigen face and peA Algorithms,†International Conference on Green Computing and Internet of Things (ICGCIoT), 2015: 303–308.

      [11] S. Yang, Y. Song, H. Ren, and X. Huang, “An Automated Student Attendance Tracking System Based on Voiceprint and Location,†The 11th International Conference on Computer Science & Education (ICCSE 2016), 2016: 214–219.

      [12] M. Kassim, H. Mazlan, N. Zaini, and M. K. Salleh, “Web-based student attendance system using RFID technology,†2012 IEEE Control and System Graduate Research Colloquium, ICSGRC 2012, 2012: 213–218.

      [13] N. Chhetri, “A Comparative Analysis of Node. Js (Server-Side JavaScript),†Master Thesis St. Cloud State University, 2016: 1-79.

      [14] T. Jędrzejewski, B. Trawiński, and A. Zgrzywa, “The Analysis of Data Collected by Time and Attendance Systems,†Third National Conference on Scientific Data Processing Technologies, 2010: 83-90.

      C. Science and M. Studies, “Development of a Student Attendance Management System,†International Journal of Advance Research in Computer Science and Management Studies, 2014: 109–119.
  • Downloads

  • How to Cite

    Wati Mohamad Yusof, Y., Asyraf Mohd Nasir, M., Azura Othman, K., Izwan Suliman, S., Shahbudin, S., & Mohamad, R. (2018). Real-Time Internet Based Attendance Using Face Recognition System. International Journal of Engineering & Technology, 7(3.15), 174-178. https://doi.org/10.14419/ijet.v7i3.15.17524