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Smart Attendance Monitoring Technology for Industry 4.0

Archana S. Nadhan, Chetana Tukkoji, Shyamala Boosi, Niranjan Lal, A. N. Sanjeev Kumar, Mohan Gowda, Zameer Ahmed Adhoni, Melaku Endaweke

2022Journal of Nanomaterials17 citationsDOIOpen Access PDF

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.

Topics & Concepts

Materials scienceAttendanceIndustry 4.0Computer scienceEconomic growthData miningEconomicsFace and Expression RecognitionIoT and GPS-based Vehicle Safety SystemsFace recognition and analysis
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