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Attendify: Next-generation biometric attendance for modern universities. Experience seamless, secure facial recognition check-ins and intelligent lecturer analytics.

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🛡️ Attendify: Next-Gen Biometric Attendance

Attendify is a high-fidelity facial recognition attendance system designed for modern universities and professional institutions. By leveraging the Google Gemini 3 Vision Engine, Attendify replaces manual roll-calls with a secure, touchless, and instantaneous biometric verification hub.


🚀 Key Features

👨‍🎓 For Students: The Portal

  • One-Tap Verification: Smart camera interface with a high-tech "Biometric HUD" overlay.
  • Liveness Detection: Anti-spoofing logic that prevents the use of photos or screen-captures for fraudulent check-ins.
  • Smart Session Sync: Automatically detects and suggests the closest scheduled course based on the current time and day.
  • Check-In History: A transparent record of all verified presences, lateness, and AI confidence scores.

👩‍🏫 For Lecturers: The Console

  • Intelligent Analytics: Real-time engagement tracking via Recharts-powered data visualization.
  • Punctuality Risk Watch: Automated identification of students with falling attendance rates (below 70%).
  • Advanced Course Config:
    • Recurring Schedules: Set classes for specific days (e.g., Mon/Wed/Fri).
    • Early Buffer: Define how many minutes before class a student can check in.
    • Late Grace Period: Automatically marks students as "LATE" after a defined threshold.
  • Biometric Asset Management: Audit the student database, retake profile photos, or remove biometric tokens.

🛠️ Technical Stack

  • Core: React 19 + TypeScript
  • Styling: Tailwind CSS (Modern, high-contrast "Cyber" aesthetic)
  • AI/Vision Engine: @google/genai (Gemini 3 Flash Preview)
  • Charts: Recharts (Engagement & Traffic metrics)
  • Persistence: Browser-level localStorage (Simulated DB Service)

🧬 How Biometric Verification Works

Attendify utilizes a Zero-Trust Biometric Model:

  1. Asset Retrieval: The system fetches the student's high-resolution reference profile image.
  2. Live Capture: The student performs a live capture via the secure encrypted stream.
  3. Gemini Analysis: Both images are processed by the Gemini Vision Engine to analyze:
    • Identity Match: Facial landmark and vertex comparison.
    • Liveness Score: Detection of screen glares, 2D flat textures, or paper borders.
    • Environmental Context: Ensuring the student is in a legitimate setting.

⚙️ Configuration & Buffers

Lecturers can fine-tune attendance policies per course:

  • Early Buffer (default: 15m): Prevents students from checking in hours before a class starts.
  • Late Grace (default: 10m): If a student checks in within this window after the start time, they are marked PRESENT. After this window, they are marked LATE.

🔒 Privacy & Ethics

Attendify is designed with a "Biometric Privacy First" approach. For this demonstration:

  • All biometric data (Base64) is stored locally in the user's browser.
  • No data is transmitted to third-party servers except for the transient processing via the Google Gemini API.
  • The system includes a "Biometric Bypass" fail-safe for demonstration environments where external image assets might be blocked by CORS.

📦 Installation

Since Attendify is built as a pure ES Module application:

  1. Ensure you have a valid process.env.API_KEY configured in your environment.
  2. Open index.html in any modern evergreen browser.
  3. Grant camera permissions when prompted.

Attendify | Precision Presence. Absolute Integrity.

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Attendify: Next-generation biometric attendance for modern universities. Experience seamless, secure facial recognition check-ins and intelligent lecturer analytics.

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