International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Attend Eye |
|---|---|
| ABSTRACT | This paper presents the design, development, and implementation of Attend-Eye, a Smart Classroom Attendance Sys-tem using AI-based face recognition. The system is designed to automate attendance management, enhance accuracy, reduce manual effort, and provide real-time monitoring in classrooms. The system captures student images using high-resolution cameras and identifies students automatically using AI al-gorithms. Attendance is recorded in a secure database, eliminating errors and preventing proxy or forged entries. Real-time dashboards provide teachers with instant monitoring capabilities, while automated alerts notify parents if a stu-dent’s attendance falls below a defined threshold, ensuring timely intervention. The integration of AI allows intelligent decision-making, analysing attendance patterns and generating reports to sup-port administrative decisions. The system is scalable, allowing deployment across multiple classrooms or departments, and can be integrated with other smart campus solutions for a complete digital education ecosystem. This design emphasizes seamless coordination between hardware components (cameras, microcontrollers, communica-tion modules) and software algorithms, demonstrating the effectiveness of AI and IoT in improving classroom man-agement. The proposed system provides a reliable, secure, and efficient solution for modern educational institutions, contributing significantly to the advancement of automated and intelligent classroom technologies. |
| AUTHOR | NARAYAN DATTAPRASAD BANDEKAR, PARTH RAMCHANDRA BHAIP, MIHIR SAKHARAM DHARGALKAR, GAURESH DHONDU GAONKAR, A.S. PADWAL Diploma Student, Department of Computer Engineering, Yashwantrao Bhonsle Institute of Technology, Sawantwadi, Maharashtra, India Faculty, Department of Computer Engineering, Yashwantrao Bhonsale Institute of Technology, Sawantwadi, Maharashtra, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401079 |
| pdf/79_Attend Eye.pdf | |
| KEYWORDS | |
| References | 1. Ashesh Kumar et al., “Automated Attendance System Based on Face Recognition Using OpenCV,” in Proceedings of the International Conference on Advanced Computing and Communication Systems (ICACCS), 2023. 2. Kapil Tajane et al., “Analysis of Face Recognition Based Automated Attendance System Using FaceNet,” in Pro-ceedings of the International Conference on Computing, Communication, Control and Automation (ICCUBEA), 2023. 3. Avadhoot Autade et al., “Automated Multi-Face Recognition and Identification Using FaceNet and VGG-16,” in Proceedings of the International Conference on Computing, Communication, Control and Automation (IC-CUBEA), 2023. 4. Vignesh et al., “Smart Attendance System Using Deep Learning,” in Proceedings of the International Conference on Trends in Electronics and Informatics (ICOEI), 2023. 5. Shreyak Sawhney et al., “Real-Time Smart Attendance System Using Face Recognition Techniques,” in Proceed-ings of the 9th International Conference on Cloud Computing, 2023. |
