IntelliPresenceSync

AI-Powered Smart Attendance Platform for Modern Classrooms

Face Recognition • Voice Biometrics • QR Enrollment • Cloud Synchronization

📑 Table of Contents

Overview
Why IntelliPresenceSync?
Project Ecosystem
Project Highlights
Core Features
Live Demonstration
Project Walkthrough
Screenshot Gallery
System Architecture
AI Workflow
Technology Stack
AI Pipeline
Repository Structure
Getting Started
Deployment
Roadmap
Key Learnings
Acknowledgements
Author

📖 Overview

IntelliPresenceSync is an end-to-end AI-powered attendance management ecosystem designed to modernize classroom attendance through intelligent biometric verification.

Instead of relying on traditional roll calls, the platform combines Computer Vision, Voice Biometrics, QR-Based Enrollment, and Cloud Synchronization to create a streamlined attendance workflow for students and educators.

The ecosystem consists of two integrated applications:

🌐 Landing Dashboard

A professional Flask-based product website that introduces IntelliPresenceSync, presents its features and technology, explains the user journey, and provides direct navigation to the AI attendance platform.

🤖 AI Attendance System

A Streamlit-based AI application where students register and enroll in subjects while teachers can manage classrooms, conduct attendance using facial or voice verification, and review attendance records.

Both applications work together with Supabase PostgreSQL as the centralized cloud database.

❓ Why IntelliPresenceSync?

Traditional classroom attendance can introduce several practical challenges.

Traditional Approach	IntelliPresenceSync
Manual roll calls	AI-assisted attendance
Proxy attendance concerns	Biometric verification
Time-consuming verification	Automated recognition
Manual record management	Centralized cloud storage
Repeated enrollment processes	QR-based subject enrollment
Limited accessibility	Web-based experience

Students complete a one-time registration process using their facial and voice information.

Teachers can subsequently verify attendance through:

📸 Classroom photographs
🎙️ Sequential voice recordings

Verified attendance records are then synchronized with Supabase PostgreSQL for centralized management and retrieval.

🚀 Project Ecosystem

                         IntelliPresenceSync
                                │
                 ┌──────────────┴──────────────┐
                 │                             │
                 ▼                             ▼
       Landing Dashboard             AI Attendance System
             Flask                        Streamlit
                 │                             │
                 │                     ┌───────┴───────┐
                 │                     │               │
                 │                     ▼               ▼
                 │              Face Recognition   Voice Biometrics
                 │                     │               │
                 │                     └───────┬───────┘
                 │                             │
                 └──────────────┬──────────────┘
                                ▼
                       Supabase PostgreSQL
                                │
                                ▼
                  Attendance Records & Management

✨ Project Highlights

Dual-biometric attendance verification
Face recognition for classroom photographs
Deep-learning speaker identification
Dynamic QR-based subject enrollment
Student and teacher dashboards
Attendance history and record management
Supabase cloud database integration
Responsive custom interface
Dedicated product landing dashboard
Modular AI pipeline architecture
Separate production deployments for both applications

⭐ Core Features

Feature	Description
📸 Face Recognition	Recognizes multiple enrolled students from classroom photographs using facial embeddings and machine learning classification.
🎙️ Voice Biometrics	Identifies registered speakers using deep-learning voice embeddings and similarity matching.
📲 QR Enrollment	Allows students to enroll into subjects through dynamically generated QR codes or invitation links.
👨‍🏫 Teacher Dashboard	Provides subject management, attendance processing, and attendance record access.
👨‍🎓 Student Dashboard	Provides student registration, subject enrollment, and profile-related functionality.
☁️ Cloud Synchronization	Stores student information, biometric embeddings, subjects, and attendance records through Supabase PostgreSQL.
📱 Responsive Interface	Designed to provide a consistent experience across different screen sizes.
🔐 Authentication	Uses password hashing with `bcrypt` for credential protection.

🎥 Live Demonstration

Resource	Link
🌐 Landing Dashboard	Open Live Dashboard
🤖 AI Attendance Platform	Launch AI Application
🎥 Full Project Demo	View Demo Video
🤖 AI Application Repository	View GitHub Repository
🌐 Landing Dashboard Repository	View GitHub Repository

🎬 Project Walkthrough

The complete demonstration follows the IntelliPresenceSync workflow from platform introduction and student enrollment to AI-powered attendance verification and attendance record management.

Demonstration Flow

Landing Dashboard → Student Registration → Subject Enrollment → Teacher Dashboard → Face Attendance / Voice Attendance → Attendance Records

The project demonstration video is available here:

📸 Screenshot Gallery

The following gallery presents the complete user journey through IntelliPresenceSync.

Each section contains a single full-width screenshot to preserve visual clarity and storytelling.

🌐 Landing Dashboard

The Landing Dashboard acts as the public-facing product experience.

It introduces IntelliPresenceSync, explains the problem being addressed, presents the major features, walks through the user journey, and showcases the technology behind the system.

🏠 Home

📖 Application Overview

✨ Innovative Features

🚀 User Journey

🛠 Technology Stack

👨‍🎓 Student Workflow

The student workflow focuses on one-time registration and subject enrollment.

Students can create their profile, enroll into available subjects, and provide the biometric information required for future attendance verification.

Step 1 — Student Login

Step 2 — Subject Enrollment

Step 3 — Student Dashboard

👩‍🏫 Teacher Workflow

The teacher workflow provides the tools required to create and manage subjects, enroll students, conduct AI-powered attendance, and review stored attendance records.

Step 1 — Teacher Login

Step 2 — Teacher Dashboard

Step 3 — Create Subject

Step 4 — Share QR Code / Invite Link

Step 5 — Voice Attendance

Step 6 — Face Recognition Attendance

Step 7 — Attendance Records

🏗️ System Architecture

IntelliPresenceSync uses two application layers connected through a centralized cloud database.

The Flask dashboard acts as the product-facing entry point, while the Streamlit application handles student management, teacher workflows, biometric processing, and attendance operations.

flowchart TD

A[Landing Dashboard<br>Flask]

A --> B[AI Attendance Platform<br>Streamlit]

B --> C1[Student Portal]

B --> C2[Teacher Portal]

C1 --> D1[Student Registration]

C1 --> D2[Subject Enrollment]

C2 --> D3[Face Recognition Attendance]

C2 --> D4[Voice Biometric Attendance]

C2 --> D5[Attendance Records]

D1 --> E[(Supabase PostgreSQL)]

D2 --> E

D3 --> E

D4 --> E

D5 --> E

E --> F[Student Profiles]

E --> G[Subject Data]

E --> H[Attendance Logs]

🤖 AI Attendance Workflow

The attendance engine combines two biometric pipelines.

Students provide biometric samples during registration. These representations are then used during teacher-initiated attendance verification.

flowchart LR

A[Student Registration]

A --> B[Face Image]

A --> C[Voice Sample]

B --> D[Face Embedding]

C --> E[Voice Embedding]

D --> F[(Supabase)]

E --> F

F --> G[Teacher Starts Attendance]

G --> H[Classroom Photo]

G --> I[Voice Recording]

H --> J[Face Recognition Pipeline]

I --> K[Voice Recognition Pipeline]

J --> L[Attendance Verification]

K --> L

L --> M[Attendance Records]

M --> N[Reports & History]

🧠 Artificial Intelligence Pipeline

📸 Face Recognition

The face pipeline uses facial embeddings and a machine-learning classifier to identify enrolled students.

Pipeline

Classroom Image
      ↓
Face Detection
      ↓
Face Landmark Processing
      ↓
128-Dimensional Face Embedding
      ↓
SVM Classification
      ↓
Student Identification
      ↓
Attendance Record

Components

Face detection
Facial landmark processing
128-dimensional face embeddings
SVM-based classification
Multi-student recognition

🎙️ Voice Biometrics

The voice pipeline uses deep speaker embeddings to identify registered students from voice recordings.

Pipeline

Voice Recording
      ↓
Audio Preprocessing
      ↓
Silence Detection
      ↓
Audio Segmentation
      ↓
256-Dimensional Speaker Embedding
      ↓
Cosine Similarity Matching
      ↓
Speaker Identification
      ↓
Attendance Record

Components

Voice recording
Audio preprocessing
Silence-based segmentation
256-dimensional speaker embeddings
Cosine similarity matching
Sequential speaker identification

🛠️ Technology Stack

Category	Technologies
Programming Language	Python
Landing Dashboard	Flask, HTML5, CSS3, JavaScript
AI Application	Streamlit
Computer Vision	dlib, face_recognition_models, Scikit-Learn
Voice Biometrics	Resemblyzer, Librosa
Database	Supabase PostgreSQL
Authentication	bcrypt
QR Generation	Segno
Image Processing	Pillow
Deployment	Vercel, Streamlit Community Cloud
Version Control	Git & GitHub

☁️ Cloud Infrastructure

Supabase PostgreSQL provides the centralized persistence layer for the attendance ecosystem.

The application uses the database for managing:

Student profiles
Subject information
Enrollments
Biometric embeddings
Attendance records
Attendance history

The deployed applications communicate with the cloud database to maintain synchronized application data.

📌 System Modules

Module	Purpose
🌐 Landing Dashboard	Product presentation and application gateway
👨‍🎓 Student Portal	Student registration, enrollment, and dashboard
👩‍🏫 Teacher Portal	Subject management and attendance operations
📸 Face Recognition Engine	Classroom image-based student verification
🎙️ Voice Recognition Engine	Speaker-based student verification
☁️ Cloud Database	Centralized application persistence
📊 Attendance Records	Attendance history and stored verification results

📂 Repository Structure

IntelliPresenceSync is organized as two separate repositories that together form one complete project ecosystem.

🤖 AI Attendance System

Repository:

https://github.com/mihirgupta665/IntelliPresenceSync

IntelliPresenceSync/
│
├── .streamlit/
│   └── config.toml
│
├── src/
│   ├── components/
│   ├── database/
│   ├── pipelines/
│   ├── screens/
│   └── ui/
│
├── app.py
├── requirements.txt
└── README.md

🌐 Landing Dashboard

Repository:

https://github.com/mihirgupta665/IntelliPresenceSync_LandingDashboard

IntelliPresenceSync_LandingDashboard/
│
├── static/
│   ├── css/
│   ├── img/
│   │   └── demo/
│   ├── banner.png
│   ├── IntelliPresenceSyncGif.gif
│   └── IntelliPresenceSyncVideo.mp4
│
├── templates/
│   ├── base.html
│   ├── index.html
│   ├── features.html
│   ├── journey.html
│   └── tech.html
│
├── app.py
├── requirements.txt
└── README.md

🚀 Getting Started

IntelliPresenceSync contains two applications, so each application can be run independently during local development.

Prerequisites

Python 3.10+
Git
Supabase account
Virtual environment

🤖 Run the AI Attendance System

Clone the AI application:

git clone https://github.com/mihirgupta665/IntelliPresenceSync.git
cd IntelliPresenceSync

Create a virtual environment:

python -m venv venv

Windows

venv\Scripts\activate

macOS / Linux

source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

Configure the required environment variables according to the application configuration.

Run Streamlit:

streamlit run app.py

🌐 Run the Landing Dashboard

Clone the landing application separately:

git clone https://github.com/mihirgupta665/IntelliPresenceSync_LandingDashboard.git
cd IntelliPresenceSync_LandingDashboard

Create a virtual environment:

python -m venv venv

Activate the environment and install dependencies:

pip install -r requirements.txt

Run Flask:

python app.py

The landing dashboard runs locally at:

http://127.0.0.1:5002

🔐 Environment Configuration

The AI attendance application uses Supabase credentials for cloud database connectivity.

Create the required environment configuration according to your local setup.

SUPABASE_URL=YOUR_SUPABASE_URL
SUPABASE_KEY=YOUR_SUPABASE_ANON_KEY

Never commit real credentials or secret keys to GitHub.

🌍 Deployment

The two applications are deployed independently while sharing the same project ecosystem.

Component	Platform	Status
🌐 Landing Dashboard	Vercel	Live
🤖 AI Attendance System	Streamlit Community Cloud	Live
☁️ Database	Supabase PostgreSQL	Cloud

Live Applications

Landing Dashboard

https://intelli-presence-sync-landing-dashb.vercel.app/

AI Attendance System

https://intellipresencesync-mihirlegacy.streamlit.app/

🛣️ Roadmap

Completed

Face Recognition Attendance
Voice Biometric Attendance
QR-Based Subject Enrollment
Student Dashboard
Teacher Dashboard
Attendance Records
Supabase Cloud Synchronization
Responsive Interface
Flask Landing Dashboard
Streamlit AI Application
Vercel Deployment
Streamlit Community Cloud Deployment
Professional Project Documentation

Planned

Face Anti-Spoofing
Liveness Detection
Multi-Camera Attendance
Mobile Application
REST API
Docker Support
CI/CD Pipeline
Advanced Classroom Analytics
Email Notifications
Parent Portal
Classroom Heatmaps
Multi-Institution Support

💡 Key Learnings

Building IntelliPresenceSync provided practical experience across the complete software development lifecycle.

Artificial Intelligence

Computer Vision
Facial Embeddings
Speaker Recognition
Machine Learning Classification
Audio Processing

Software Engineering

Modular Python Architecture
Flask Application Development
Streamlit Application Development
Database Integration
Authentication
Responsive UI Design

Deployment

Vercel Deployment
Streamlit Community Cloud
Supabase Cloud Database
Environment Configuration
Production Dependency Management

Product Development

System Architecture
User Experience Design
Technical Documentation
Project Demonstration
Portfolio Presentation

🙏 Acknowledgements

IntelliPresenceSync builds upon the work of the open-source community.

Special thanks to:

👨‍💻 Author

Mihir Gupta

AI & Machine Learning Engineer • Full Stack Developer

Building intelligent software solutions through Artificial Intelligence, Machine Learning, and modern software engineering.

⭐ Show Your Support

If IntelliPresenceSync was useful, interesting, or inspiring, consider giving the project a ⭐ on GitHub.

Your support helps the project reach more developers and encourages continued experimentation with AI-powered educational technology.

📜 License

This project is licensed under the MIT License.