Real-Time Attendance System Using QR-Code and Face Recognition
Abhishek verma
, Virendra Kumar Verma , Priya Gupta
Smartphones now play an important role in our daily lives. It has made life simpler and easier for everyone with various social, commercial, problem-solving, educational, and marketing apps... etc., and in light of the need for social distancing following Covid-19, we have designed a system that addresses the problem of student and employee attendance in various institutions. They were utilizing a paper-based approach to keep track of their attendance. The suggested system is an Internet of Things (IoT)-based attendance system that makes use of Standard for an Architectural Framework for the Internet of Things (IoT) (Face recognition - QR code). Our system may be used in two sorts of organizations: the first is for businesses, where attendance is recorded using one of two characteristics (Face recognition or fingerprint), and the system is also designed to manage employee working hours. The second system is for educational institutions, and it is responsible for managing and analysing all students' attendance. For pupils to take attendance, a (Face recognition& QR code) will be provided. The professor is in charge of determining whether or not all of the pupils in the group or class are present. To authenticate their attendance and exit, users will only need their smartphones.
"Real-Time Attendance System Using QR-Code and Face Recognition ", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.a139-a152, February-2024, Available :https://tijer.org/TIJER/papers/TIJER2402015.pdf
Volume 11
Issue 2,
February-2024
Pages : a139-a152
Paper Reg. ID: TIJER_150693
Published Paper Id: TIJER2402015
Downloads: 0001710
Research Area: Science and Technology
Country: Lucknow, Uttar Pradesh, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
