rtgamerz009/attendance-verifier
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Traditional attendance systems rely on vulnerable processes—roll calls, ID cards, or simple PINs. These are easily exploited, leading to proxy attendance, human error, and massive time consumption.
개요
Traditional attendance systems rely on vulnerable processes—roll calls, ID cards, or simple PINs. These are easily exploited, leading to proxy attendance, human error, and massive time consumption. eliminates these vulnerabilities using multi-layer biometric validation. 🎯 Smart Verification Engine Multi-step validation pipeline that analyzes visual input to confirm identity before allowing a database entry to be written. 👤 Identity Validation & Liveness Uses active challenge-response (e.g., "blink twice") and 3D depth analysis to distinguish a live human from a photograph or screen. ⚡ Automated Logging Zero-click attendance tracking. Once verification is confirmed, timestamps, device IDs, and confidence scores are immediately synced. 📊 Real-Time Analytics Dashboard Administrator portal featuring live verification streams, spoof-attempt alerts, and systemic risk-level monitoring. ➔ User positions face within the camera reticle. ➔ System prompts a random liveness challenge (e.g.
README
원문 README의 일부입니다. 원문 보기.
⚡ Overview: The Proxy Problem
Traditional attendance systems rely on vulnerable processes—roll calls, ID cards, or simple PINs. These are easily exploited, leading to proxy attendance, human error, and massive time consumption. Attendance Verifier eliminates these vulnerabilities using multi-layer biometric validation.
| ❌ The Problem | ✨ The Verifier Solution |
|---|---|
| Proxy Attendance: Students/employees marking peers present using shared IDs. | Identity Validation: Biometric verification ensures the physical presence of the individual. |
| Time Consumption: Manual roll calls eat into productive operational or educational hours. | Automated Logging: Millisecond verification automatically logs timestamps without intervention. |
| Spoofing Attacks: Holding up static photos or phone screens to trick standard cameras. | Liveness Detection: Challenge-response systems block static images and flat-surface reflection. |
🔥 Key Features
🏗️ System Architecture
graph TD;
A[Client Device / WebCam] -->|Live Video Feed| B(Processing Layer)
subgraph Verification Engine
B --> C{Face Detection}추천 도구
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설치
npx skillfish add rtgamerz009/attendance-verifier