• K.Chaitanya
• S.Naga Sindhu
• P.Sushma
• K.Nitheesh Kumar
• G.Mee Sitaram

Maintaining discipline in educational institutions requires strict compliance with uniform policies and effective attendance monitoring. Traditional methods often rely on manual checks, which are time-consuming and prone to human error. To address this, our system leverages computer vision and deep learning to automate uniform compliance verification and attendance tracking. A custom YOLOv8 model ensures consistent detection of students wearing improper attire, while facial recognition accurately identifies individuals. A Flask-based web application provides a secure interface for accessing attendance records, which are safely stored in a CSV file. Authentication mechanisms restrict access to authorized personnel, ensuring data security. To further streamline enforcement, the system integrates Twilio to send automated SMS notifications to students who are out of uniform, reducing the need for manual intervention. This approach enhances scalability, reliability, and efficiency, making it ideal for institutions seeking automated, real-time compliance monitoring. By minimizing human involvement, the system ensures fair enforcement while maintaining discipline in a seamless and effective manner. The combination of deep learning, facial recognition, and web-based authentication results in a comprehensive solution that improves uniform compliance while reducing administrative workload.

Attendance Monitoring, Uniform Compliance, Computer Vision, Deep Learning, YOLOv8, Face Recognition, Flask Web App, Automated, Authentication

"Smart Attendance System With Yolo Based Uniform Compliance Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.e13-e16, March-2025, Available :http://www.jetir.org/papers/JETIR2503415.pdf

"Smart Attendance System With Yolo Based Uniform Compliance Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppe13-e16, March-2025, Available at : http://www.jetir.org/papers/JETIR2503415.pdf