Smart Attendance Monitoring Technology for Industry 4.0-Reference-Cited by-同舟云学术

Smart Attendance Monitoring Technology for Industry 4.0

Published:2022-06-21 Issue: Volume:2022 Page:1-9
ISSN:1687-4129
Container-title:Journal of Nanomaterials
language:en
Short-container-title:Journal of Nanomaterials

Author:

Nadhan Archana S.¹,Tukkoji Chetana¹,Shyamala Boosi¹,Dayanand Lal N.¹,Sanjeev Kumar A. N.¹,Mohan Gowda V.¹,Adhoni Zameer Ahmed¹,Endaweke Melaku²^ORCID

Affiliation:

1. Department of CSE, GITAM School of Technology, GITAM University Bengaluru, India

2. Department of Food Engineering, Debre Berhan University, Debre Berhan, Ethiopia

Abstract

Keeping track of employee attendance in academic settings can be a difficult task. It frequently wastes a significant percentage of the category’s productive time when done manually. In this study, the OpenCV open-source image processing library presents an effective Raspberry Pi-based methodology that reduces product cost and aids in connecting to heterogeneous devices for attendance. When teaching and testing and collecting employee photos and taking attendance, the system delivers a user-friendly interface that maximizes the user experience. Face detection and recognition are done with LBP histograms, and the database is updated with SQLite (a lightweight version of SQL for the Raspberry Pi) rather than MySQL.

Publisher

Hindawi Limited

Subject

General Materials Science

Link

http://downloads.hindawi.com/journals/jnm/2022/4899768.pdf

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