SEAIT OJT Monitoring System using Face Recognition Technology: Improving Usability and Accessibility
Year: 2025
Type: article
Abstract: This research project focuses on improving the SEAIT OJT Monitoring System by integrating face recognition technology to enhance usability and accessibility. Traditional methods of tracking On-the-Job Training (OJT) attendance are often time-consuming and prone to errors. By implementing a face recognition system, the project aims to automate attendance tracking, reduce human errors, and increase security. The study evaluates the system's performance through usability testing, measuring metrics like accuracy, efficiency, and user satisfaction. Results indicate that the system simplifies attendance monitoring, provides real-time data, and improves overall user experience. However, challenges such as environmental factors and device compatibility were noted. The project demonstrates the potential of face recognition technology to streamline administrative tasks in educational settings while emphasizing the need for further improvements in accessibility and reliability.
Authors: Acain Jay Ronel, Ablayon Anthony, Manaligod Christian, Manrique Lorenz Greg, Morga Arcadio, Cedie E. Gabriel, Reginald S. Prudente
Institution: South East Asian Institute of Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4410903996