Soppari, Kavitha and Varun D, Varun D and Eedula, Rithvik and Manchala, Anudeep (2025) Faculty presence detection and alert system. International Journal of Science and Research Archive, 14 (1). pp. 1244-1251. ISSN 2582-8185
![IJSRA-2025-0203.pdf [thumbnail of IJSRA-2025-0203.pdf]](https://eprint.scholarsrepository.com/style/images/fileicons/text.png)
IJSRA-2025-0203.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial Share Alike.
Abstract
The exponential growth of inspection systems has increased the demand for efficient and cost-effective solutions. This project introduces a faculty verification system that uses the webcam of the system and OpenCV for real-time facial recognition. The system integrates a Flask-based web interface to provide an intuitive and dynamic user experience. The key features are live detection and system-level video capture by using the Haar Cascade classifier. It gives more importance to accessibility and user-friendliness. Unlike some solutions that work on an external camera or even a Raspberry Pi module, this system works on solely built-in resources. Therefore, the value is guaranteed. The study evaluates performance in face recognition under varying conditions. Focus has been laid on accuracy, responsiveness, and scalability.
Item Type: | Article |
---|---|
Official URL: | https://doi.org/10.30574/ijsra.2025.14.1.0203 |
Uncontrolled Keywords: | Faculty Monitoring System; OpenCV; Haar Cascade; Flask Framework; Real-time Surveillance; System Webcam |
Depositing User: | Editor IJSRA |
Date Deposited: | 15 Jul 2025 15:19 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/739 |