AI Smart Attendance System Using Full Stack Java: Design, Implementation, and Evaluation

• Author(s): Kuldeep Khalotiya; Manish Rana; Nitin Kumar Singh; Shubham Baisakh; Sonali Kumari
• Paper ID: 1717082
• Page: 3639-3647
• Published Date: 01-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 10 April-2026
• DOI: https://doi.org/10.64388/IREV9I10-1717082

Abstract

Traditional attendance management systems in educational institutions depend heavily on manual roll calls and paper-based registers. These approaches are error-prone, time-intensive, susceptible to proxy attendance, and produce data that is difficult to aggregate or analyse at scale. As institutions accelerate digital transformation, demand for reliable, role-aware, web-based attendance platforms has grown substantially. This paper presents the complete design, implementation, and empirical evaluation of an AI Smart Attendance System developed using Full Stack Java technologies — specifically Spring Boot 3.x, Hibernate ORM 6.x, MySQL 8.0, and a responsive Bootstrap 5 front-end. The system architecture follows the classic three-tier model separating the Presentation Layer (HTML5/CSS3/JavaScript), the Application Layer (Spring Boot MVC with Spring Data JPA), and the Data Layer (MySQL with Hibernate ORM). A RESTful API design pattern provides clean decoupling between client and server, enabling future integration with mobile applications or third-party academic systems without structural changes. Role-based access control (RBAC) is enforced for three user categories — Administrator, Faculty, and Student — each with dedicated dashboards and permission boundaries validated at the API level. Evaluation through functional and performance testing produced a 100% pass rate across all ten planned test cases. REST API GET endpoints averaged under 120 ms and POST endpoints under 200 ms under 50+ concurrent users. Dashboard pages loaded in under 1.8 seconds, and attendance-report database queries completed within 300 ms. The findings validate that a Spring Boot/MySQL full-stack architecture provides a robust, scalable, and maintainable foundation for enterprise-grade educational management systems.

Keywords

Attendance Management System, Bootstrap 5, Educational Technology, Full Stack Java, Hibernate ORM, MySQL, RESTful API, Role-Based Access Control, Spring Boot, Spring Data JPA, SDLC, Web Application

Citations

IRE Journals:
Kuldeep Khalotiya, Manish Rana, Nitin Kumar Singh, Shubham Baisakh, Sonali Kumari "AI Smart Attendance System Using Full Stack Java: Design, Implementation, and Evaluation" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 3639-3647 https://doi.org/10.64388/IREV9I10-1717082

IEEE:
Kuldeep Khalotiya, Manish Rana, Nitin Kumar Singh, Shubham Baisakh, Sonali Kumari "AI Smart Attendance System Using Full Stack Java: Design, Implementation, and Evaluation" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026, doi: https://doi.org/10.64388/IREV9I10-1717082

APA:
Kuldeep Khalotiya, Manish Rana, Nitin Kumar Singh, Shubham Baisakh, Sonali Kumari (2026). AI Smart Attendance System Using Full Stack Java: Design, Implementation, and Evaluation. Iconic Research And Engineering Journals, 9(10). doi: https://doi.org/10.64388/IREV9I10-1717082

MLA:
Kuldeep Khalotiya, Manish Rana, Nitin Kumar Singh, Shubham Baisakh, Sonali Kumari "AI Smart Attendance System Using Full Stack Java: Design, Implementation, and Evaluation" Iconic Research And Engineering Journals, vol. 9, no. 10, Apr. 2026. Crossref, https://doi.org/10.64388/IREV9I10-1717082

BibTeX

@article{1717082,
author = {Kuldeep Khalotiya, Manish Rana, Nitin Kumar Singh, Shubham Baisakh, Sonali Kumari},
title = {AI Smart Attendance System Using Full Stack Java: Design, Implementation, and Evaluation},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {3639-3647},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1717082.pdf},
abstract = {Traditional attendance management systems in educational institutions depend heavily on manual roll calls and paper-based registers. These approaches are error-prone, time-intensive, susceptible to proxy attendance, and produce data that is difficult to aggregate or analyse at scale. As institutions accelerate digital transformation, demand for reliable, role-aware, web-based attendance platforms has grown substantially. This paper presents the complete design, implementation, and empirical evaluation of an AI Smart Attendance System developed using Full Stack Java technologies — specifically Spring Boot 3.x, Hibernate ORM 6.x, MySQL 8.0, and a responsive Bootstrap 5 front-end. The system architecture follows the classic three-tier model separating the Presentation Layer (HTML5/CSS3/JavaScript), the Application Layer (Spring Boot MVC with Spring Data JPA), and the Data Layer (MySQL with Hibernate ORM). A RESTful API design pattern provides clean decoupling between client and server, enabling future integration with mobile applications or third-party academic systems without structural changes. Role-based access control (RBAC) is enforced for three user categories — Administrator, Faculty, and Student — each with dedicated dashboards and permission boundaries validated at the API level. Evaluation through functional and performance testing produced a 100% pass rate across all ten planned test cases. REST API GET endpoints averaged under 120 ms and POST endpoints under 200 ms under 50+ concurrent users. Dashboard pages loaded in under 1.8 seconds, and attendance-report database queries completed within 300 ms. The findings validate that a Spring Boot/MySQL full-stack architecture provides a robust, scalable, and maintainable foundation for enterprise-grade educational management systems.},
keywords = {Attendance Management System, Bootstrap 5, Educational Technology, Full Stack Java, Hibernate ORM, MySQL, RESTful API, Role-Based Access Control, Spring Boot, Spring Data JPA, SDLC, Web Application},
month = {April}
}