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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM49402
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This project proposes an Automated Payroll System integrated with GPS Tracking and Image Capture to streamline attendance verification and salary computation, particularly for field-based or remote employees. The system leverages mobile technology to enable employees to clock in and out from their smartphones, using GPS tracking to verify their physical presence at designated work locations. Additionally, image capture functionality ensures identity verification and prevents proxy attendance. The backend processes attendance data in real-time and automatically calculates wages based on hours worked, overtime, and other parameters, ensuring transparency and reducing manual errors. The system also provides administrators with dashboards for monitoring workforce activity and generating reports. This solution not only enhances payroll accuracy and security but also improves accountability and efficiency in workforce management. The system enables employees to log their attendance using a mobile application, which captures their GPS location and a real-time image at the time of check-in and check-out. These two factorsâlocation verification and image-based identity confirmationâact as a dual-authentication method to prevent fraudulent entries and ensure the employee is physically present at the assigned worksite. The system enables employees to log their attendance using a mobile application, which captures their GPS location and a real-time image at the time of check-in and check-out. These two factorsâlocation verification and image-based identity confirmationâact as a dual-authentication method to prevent fraudulent entries and ensure the employee is physically present at the assigned worksite.
KEYWORDS
Publication Date
4/23/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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