Facial Recognition Based Temporary Employee Management System

Abstract

In Sri Lanka, 90% of temporary workers are employed in the private sector. Overall, around 60% of employees work as temporary workers; out of all 2.8 million private-sector employees in Sri Lanka. Although these temporary workers get a daily wage, they are not promised with continued work in the future; in other words, their job security is much lower compared to other private sector workers. Two of the key issues with their employment are the temporary nature of their occupations and the difficulty in controlling of these occupations because of the lack of permanent set of rules. In many workplaces- at present, their work is obtained through brokers. Therefore, these temporary employees as well as the companies face many problems. With the intention of overcoming these issues this paper introduce an automated system for factories, to hire and manage temporary workers without the need of an intermediate broker. This application is developed mainly in four modules; employee registration, employee identification and attendance marking, rating the employees according to their performance, and payroll management. Attendance marking is operated using the (LBPH) face recognition technique. It enables the recognition of the real identities of the employees thus achieving a better level of accuracy in both identity recognition as well as attendance marking. After the identification of the employee, the system will display the tasks assigned to them on the particular day. Tasks are assigned considering the rating value of the employee which will be calculated based on their performance and proficiency on allocated work, as recorded in their work history. The sectional heads are responsible for rating the employees. Their arrival time and date are recorded to ensure the smooth functioning of the payroll system.