Project at a Glance
Eagle Eye / Face Hawk required a high-precision facial recognition system to manage attendance, monitor access to restricted areas, and enhance organizational security. The objective was to create a centralized platform capable of accurately identifying personnel, logging attendance, and controlling entry to sensitive zones without relying on manual checks or physical tokens.
We developed a robust web-based platform equipped with AI-powered machine learning facial recognition, machine learning-based anomaly detection, and real-time access management. The system enabled seamless identification and logging of personnel across multiple locations, integrating with existing security infrastructure.
The platform included comprehensive modules for user management, access level assignment, attendance reporting, real-time alerts, activity logs, and system analytics, providing organizations with both operational efficiency and enhanced security.
Solution & Implementation
The solution combined advanced AI algorithms with scalable backend architecture to deliver secure, real-time facial recognition.
Key implementation highlights included:
- AI Facial Recognition Engine: High-accuracy identification of personnel using deep learning models and image processing, even under varying lighting and angles.
- Access Control Management: Granular access assignment to rooms, floors, or restricted zones based on roles and schedules.
- Attendance Tracking: Automated logging of employee attendance with timestamps, eliminating manual entry and errors.
- Admin Dashboard: Centralized control for user enrollment, access permissions, reporting, and real-time monitoring.
- Alert & Notification System: Instant alerts for unauthorized access attempts or anomalies detected by the system.
- Scalable Architecture: Built with Python and Node.js backend, designed to handle large user bases and multiple organizational locations.
Technology Stack
Python
Typescript
PHP
NodeJs
MySQL
AI
Machine Learning
OpenAI
Canva
Project Outcomes
- Delivered a secure, AI-enabled facial recognition system for attendance and access control.
- Eliminated manual attendance tracking and improved compliance with organizational security policies.
- Provided administrators with a centralized, real-time overview of access activity across locations.
- Enhanced operational efficiency while maintaining high accuracy and reliability in identification.
- Established a scalable, future-ready platform capable of integrating with additional organizational security systems.