التفاصيل البيبلوغرافية
| العنوان: |
Smart Attendance Monitoring Technology for Industry 4.0. |
| المؤلفون: |
Nadhan, Archana S., Tukkoji, Chetana, Shyamala, Boosi, Dayanand Lal, N., Sanjeev Kumar, A. N., Mohan Gowda, V., Adhoni, Zameer Ahmed, Endaweke, Melaku |
| المصدر: |
Journal of Nanomaterials; 6/21/2022, p1-9, 9p |
| مصطلحات موضوعية: |
INDUSTRY 4.0, RASPBERRY Pi, ATTENDANCE, LIBRARY technical services, IMAGE processing, HUMAN facial recognition software |
| مستخلص: |
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. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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