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@article{185948,
        author = {S.Pavithra and R.Sandhiya and D.Keerthana and Mr.S.Suresh Kumar},
        title = {Smart Employee Management System with Automated Attendance and Payroll},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {5},
        pages = {3779-3793},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185948},
        abstract = {Employee management is one of the most important organizational functions. Conventional payroll and attendance systems use fingerprint devices, RFID cards, or manual registers, all of which are laborious, prone to mistakes, and susceptible to manipulation like proxy attendance. These drawbacks emphasize how urgently an automated, smart, and safe system is needed.
This paper presents a Smart Employee Management System that combines automated payroll processing, secure authentication, and face recognition-based attendance tracking into a single platform. The Spring Boot framework, which guarantees scalability, modular design, and strong backend support, was used in the development of the system. Instead of using expensive biometrics, a webcam interface is used to take pictures during user registration, login, and daily attendance marking.
The FaceNet algorithm, which creates 128-dimensional feature embeddings for every employee face, is used to implement the face recognition module. A highly discriminative representation of facial features is offered by these embeddings. The system determines the Euclidean distance between the stored and real-time embeddings during authentication. The employee is successfully identified if the distance is less than a predetermined threshold, guaranteeing accuracy and avoiding proxyattendance.
The system uses JWT (JSON Web Token) authentication for safe access control. A JWT token is created upon successful login and is necessary for all ensuing client-server transactions. This system guarantees session integrity, stops unwanted access, and permits scalability in multi-user settings. Additionally, a password recovery feature is integrated through SMS and email services, enhancing system dependability and usability.
The system has a payroll computation module that is directly connected to attendance records in addition to attendance. A rule-based formula is used to calculate payroll:
Salary = (Base Salary/Total Days of Work) Days SpenAttending
By eliminating human intervention and reducing calculation errors, this guarantees that salaries are credited proportionately based on employee attendance.
A user-friendly experience is offered by the frontend's static HTML pages, which include the camera interface, profile, login, and register. AuthController, AttendanceController, and FaceRecognitionController are among the Spring Boot controllers and services that make up the backend. Database operations are supported by repositories. The separation of concerns and seamless system operation are guaranteed by this tiered architecture.
Multiple employees participated in an experimental evaluation with different lighting conditions. The system's average face recognition accuracy was 97.8%, its authentication latency was less than two seconds, and its payroll computation accuracy was 100%. These outcomes show how effective, dependable, and useful the suggested system is in actual organizational settings.
In order to facilitate multi-factor authentication, future improvements will concentrate on extending biometric modalities by incorporating fingerprint and iris recognition. To increase accessibility for administrators and staff alike, a cross-platform mobile application is also planned. In order to improve payroll and attendance record management's scalability, security, and transparency, cloud and blockchain integration will also be investigated.},
        keywords = {Face recognition, FaceNet algorithm, Automated attendance, Payroll computation, Employee management system, Spring Boot framework, JWT authentication, Artificial intelligence in HR, Workforce automation},
        month = {October},
        }