Edge AI Facial Recognition Lock With 2FA

Facial recognition access control system with ESP32 hardware, AWS cloud services, and real-time web dashboard.

1. Features

• Facial Recognition: AWS Rekognition identity verification
• Two-Factor Authentication: SMS verification via Supabase Auth & Twilio
• IoT Hardware: ESP32 camera capture and servo door lock
• Real-time Dashboard: Vue.js web interface with live monitoring
• Cloud Backend: Supabase database with edge functions

2. System Flow

ESP32-Camera
     ↓
Supabase Edge Functions
     ↓
AWS Lambda (Face Recognition)
     ↓
Database Lookup + SMS Sent
     ↓
User Receives 2FA Code
     ↓
Vue.js Dashboard (User enters code)
     ↓
Socket Server (2FA Verification)
     ↓
ESP32-Lock (Door opens)

3. Project Structure

iot_project/
├── hardware/
│   └── esp32-firmware/         # ESP32 camera and door control
├── backend/
│   ├── aws-lambda/            # AWS facial recognition functions  
│   ├── supabase/              # Database and edge functions
│   └── socket-server/         # Real-time communication
└── frontend/
    └── web-dashboard/         # Vue.js admin interface

4. Tech Stack

• Hardware: ESP32-CAM, Servo Motor
• Recognition: AWS Lambda, AWS Rekognition
• Database: Supabase (PostgreSQL)
• 2FA/SMS: Supabase Auth OTP, Twilio
• Frontend: Vue.js 3, TailwindCSS
• Real-time: Socket.IO

5. Quick Start

5.1 Hardware Setup

# Install libraries: ArduinoHttpClient, MyBase64, esp32-camera
# Update WiFi credentials in hardware/esp32-firmware/iotproject.ino
# Upload to ESP32-CAM

5.2 Backend Setup

# Supabase
cd backend/supabase && supabase start

# Socket Server  
cd backend/socket-server && npm install && node index.js

# Deploy AWS Lambda functions from backend/aws-lambda/

5.3 Frontend Setup

cd frontend/web-dashboard
npm install && npm run dev