Publication | Open Access
Smart Attendance Monitoring Technology for Industry 4.0
17
Citations
15
References
2022
Year
EngineeringBiometricsRaspberry PiWearable TechnologyImage DatabaseEducationFace DetectionFacial Recognition SystemImage AnalysisData SciencePattern RecognitionInternet Of ThingsIndustry 4.0Smart SystemLbp HistogramsIndustrial InformaticsAssistive TechnologyMobile ComputingComputer ScienceComputer VisionEmployee AttendanceTechnology
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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