About Our Project
Learn about the Yabatech Facial Recognition System and the talented students behind its development.
The Facial Recognition System
Project Overview
The Yabatech Facial Recognition System is a cutting-edge authentication solution designed specifically for Yaba College of Technology. It provides a secure, efficient, and contactless method for student and staff identification across campus facilities.
Using advanced computer vision and machine learning algorithms, our system can accurately identify registered individuals in real-time, enhancing security while streamlining access to various campus services.
Technology Stack
Next.js
Frontend
Django
Backend
TensorFlow
ML Model
PostgreSQL
Database
Docker
Deployment
AWS
Cloud Infrastructure
Key Features
Real-time Recognition
Fast and accurate facial recognition with response times under 2 seconds, even in challenging lighting conditions.
Secure Authentication
Multi-factor biometric authentication with liveness detection to prevent spoofing attempts.
Privacy Protection
All biometric data is encrypted and stored securely following industry best practices and data protection regulations.
Seamless Integration
Integrates with existing Yabatech systems including student management and access control systems.
Meet the Team
Our talented team of Yabatech students combined their skills and expertise to bring this project to life.
Our Journey
Project Inception
September 2023
The project began as a final year project proposal, aiming to solve the challenges of student identification and authentication on campus.
Research & Planning
October - November 2023
Extensive research on facial recognition technologies, security considerations, and user experience design for biometric systems.
Development Phase
December 2023 - February 2024
Building the core system components, including the facial recognition engine, backend API, and frontend interface.
Testing & Refinement
March - April 2024
Rigorous testing with a diverse group of students and staff, followed by system refinements based on feedback.
Deployment
May 2024
Official launch of the Yabatech Facial Recognition System, with ongoing support and feature enhancements.
Acknowledgements
We extend our sincere gratitude to the following individuals and departments for their support and guidance throughout this project:
Faculty Advisors
Dr. Oluwaseun Adebayo
Prof. Chinedu Eze
Mrs. Folashade Ogunleye
Departments
Computer Science Department
ICT Center
Student Affairs
Special Thanks
Yabatech Management
Student Volunteers
Open Source Community