Smart Work Monitoring and Automated Payroll System
Smart Work Monitoring and Automated Payroll System
Authors:
Darshan Patil1, Ayush Shaha2, Rupesh Nipanikar3, Yash Shinde4, and Mayuri Shirsath5
1Student, Department of Computer Engineering, TSSMS Bhivarabai Sawant College of Engineering and Research, Pune, Maharashtra, India
2Student, Department of Computer Engineering, TSSMS Bhivarabai Sawant College of Engineering and Research, Pune, Maharashtra, India
3Student, Department of Computer Engineering, TSSMS Bhivarabai Sawant College of Engineering and Research, Pune, Maharashtra, India
4Student, Department of Computer Engineering, TSSMS Bhivarabai Sawant College of Engineering and Research, Pune, Maharashtra, India
5Assistant Professor, Department of Computer Engineering, TSSMS Bhivarabai Sawant College of Engineering and Research, Pune, Maharashtra, India
Abstract—The management of a virtual team is one of the challenging tasks that are hard to manage. Indeed, in such a case, one needs to know whether employees have clocked in, their actual work schedule, and who is sitting at the computer. In addition to this, there is a challenge of accurately calculating salaries on the basis of recorded work hours while avoiding the use of self-reporting timesheets which may cause disputes between managers and employees. This paper outlines a solution that addresses all of the above-mentioned problems. It is a web-based solution created using artificial intelligence. The solution allows verifying identity by face recognition, monitoring work hours through a webcam stream provided by WebRTC, and automatic calculation of salaries on the basis of work hours. The proposed system has been developed using React 19 with TypeScript and Supabase cloud database. face-api.js performs face recognition while jsPDF generates payslips for each month. For testing purposes, we simulated a team of 15 employees working remotely for two weeks. Face verification was successful in 94 percent of cases under normal conditions. All payroll calculations turned out to be correct in each test instance. Both employees and administrators expressed satisfaction with the application, particularly regarding its automation of payroll calculation and monitoring processes. This system is an effective and efficient software solution for small-scale organizations.
Index Terms—Automated Payroll, Face Recognition, React TypeScript, Remote Work Monitoring, Supabase, WebRTC