Biometric attendance mobile application for workforce management - Nguyen, Tuan Kiet (2025)
This Master’s thesis presents the design, implementation, and deployment of a secure, accurate, and customizable attendance system. The system is composed of three main components: a web-based Admin’s interface for shift management and reporting, a mobile application for employees to record attendance with biometric verification, and a Central Server responsible for core logic and API communication. Additionally, a lightweight Local Server was developed to improve location-based validation using Bluetooth technology. The Admin’s interface allows business owners to assign shifts across multiple workplaces, monitor attendance in real time, and view historical data via a dashboard with flexible date filtering. The Mobile application, deployed to both the Apple App Store and Google Play Store, supports attendance recording with geolocation and biometric authentication, predefined break management, shift pause tracking, and multi-business connectivity. Secure communication is ensured through JWT-signed requests. The Local Server, which can run on low-resource devices like desktops or Raspberry Pi, broadcasts Bluetooth signals to confirm the employee’s physical proximity before permitting attendance actions. The system was developed using modern JavaScript technologies: React for the Admin’s interface, React Native for the mobile app, Node.js for both server components, and MongoDB as the backend database. Functional and non-functional requirements were defined through user research and formalized into user stories, a use case diagram, and a detailed database schema. Wireframes were designed for both the Admin’s interface and mobile app to guide UI implementation. Field-tested at a real grocery store, the system underwent automated and manual testing, successfully meeting all scenarios. The source code is publicly available under the MIT license, with documentation and repository access provided in the appendix.