AI-Based Workforce Monitoring System using CNN-Based Face Recognition and Liveness Detection

AI Workforce monitoring Facial recognition

Intelligent Identity. Real-Time Presence. Zero Compromise.

A deep learning-powered face recognition and liveness detection system built for secure, scalable, and accurate workforce monitoring in real-world environments.

128-D

Facial Embeddings

Generated using FaceNet CNN

< 1 Sec

Real-Time Identification

Instant face recognition & verification

Anti-Spoof

Blink-Based Liveness Detection

Prevents photo and replay attacks

SAB's Workforce Monitoring System

We engineered a real-time workforce monitoring system powered by CNN-based FaceNet recognition and liveness detection. Traditional face recognition approaches often struggle with real-world variations. This solution utilizes deep learning to deliver reliable employee identification with enhanced robustness, scalability, and anti-spoofing capabilities.

Challenge:

High false positives and incorrect identity recognition in traditional face recognition methods.

Accuracy degradation due to:

Lighting changes
Camera angle variations
Background noise
Rapid switching between employee names in real-time video.
Lack of robustness against photo spoofing attacks.
Difficulty in scaling the system for real-world workforce environments.

Solution:

Developed an AI-driven end-to-end monitoring pipeline for workforce environments.
Implemented robust face detection, embedding generation, and liveness checks in real time.
Compared live facial vectors against enrolled employee profiles for accurate verification.
Confirmed identity only after anti-spoof validation to secure attendance and access workflows.

Let's Redefine Workforce Intelligence with Secure AI

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