AI based contactless attendance monitoring and management system

https://doi.org/10.53730/ijhs.v6nS3.8365

Authors

  • Nithya J. Professor, Department of Information Technology, K.S.Rangasamy College of Technology, Tiruchengode – 637215
  • Vignesh S. R. UG Students, Department of Information Technology, K. S. Rangasamy College of Technology, Tiruchengode – 637215
  • Devadarsan A. UG Students, Department of Information Technology, K.S.Rangasamy College of Technology, Tiruchengode – 637215
  • Venkatesh S. UG Students, Department of Information Technology, K. S. Rangasamy College of Technology, Tiruchengode – 637215

Keywords:

face recognition, RFID, IoT

Abstract

The traditional methods of attendance marking need to be replaced with an Artificial Intelligence based attendance monitoring system. The process of checking attendance using the existing methods is time consuming and open to easy fraud. The usage of Bio-metrics poses the threat of viruses. A contact-less Attendance Management System (CAMS) is proposed to overcome the above challenges. AI based attendance monitoring system will record the students attendance automatically while they enter the class, by recognizing their faces. The in-time and out-time of the students are also recorded on a regular basis. The Holistic Face Matching algorithm is used to compare the facial images. The total time duration, the students were present inside the class can be easily calculated. There is no chance of fake attendance as each student has to record his or her facial identity. The main objective is to achieve reliability, accessibility and security in a very efficient way. The results showed that by interfacing a face recognition system with a server, a real-time attendance system can be built and be monitored automatically. Finally, the student’s attendance details can be updated in the academic management system.

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Published

03-06-2022

How to Cite

Nithya, J., Vignesh, S. R., Devadarsan, A., & Venkatesh, S. (2022). AI based contactless attendance monitoring and management system. International Journal of Health Sciences, 6(S3), 10600–10614. https://doi.org/10.53730/ijhs.v6nS3.8365

Issue

Section

Peer Review Articles