Smart Attendance Monitoring Technology for Industry 4.0

被引：0
作者：
Nadhan, Archana S. [1 ]
Tukkoji, Chetana [1 ]
Shyamala, Boosi [1 ]
Lal, N. Dayanand [1 ]
Kumar, A. N. Sanjeev [1 ]
Gowda, V. Mohan [1 ]
Adhoni, Zameer Ahmed [1 ]
Endaweke, Melaku [2 ]
机构：
[1] GTIAM Univ Bengaluru, GITAM Sch Technol, Dept CSE, Bengaluru, India
[2] Debre Berhan Univ, Dept Food Engn, Debre Berhan, Ethiopia
来源：
JOURNAL OF NANOMATERIALS | 2022年 / 2022卷
关键词：
RECOGNITION;
D O I：
10.1155/2022/4899768
中图分类号：
TB3 [工程材料学];
学科分类号：
0805 ; 080502 ;
摘要：
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.
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页数：9
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