SoundSenseHelmet 🛡️🎧

AI-Powered Safety Helmet for the Deaf Community

🏗️ Project Structure

smart_helmet/
├── client/                     # Laptop audio streaming client
│   └── audio_client.py
├── raspberry_pi/               # Core helmet system
│   ├── audio/                  # Audio processing
│   │   ├── audio_server.py         # UDP server
│   │   ├── audio_processor.py      # Chunk handling
│   │   └── features.py             # Spectrogram conversion
│   ├── ml/                     # Machine learning
│   │   ├── inference.py            # Real-time prediction
│   │   ├── model_loader.py         # TFLite integration
│   │   └── models/                 # Pretrained models
│   ├── sensors/                # Sensor interfaces
│   │   ├── force_sensor.py         # Impact detection
│   │   ├── gps.py                  # Location tracking
│   │   └── mpu6050.py              # Head tracking
│   ├── output/                 # User feedback
│   │   ├── haptic.py               # Vibration control
│   │   └── visual.py               # LED patterns
│   ├── utils/                  # Utilities
│   │   ├── alerts.py               # Notification system
│   │   ├── logger.py               # Logging config
│   │   └── config.py               # Hardware pin config
├── model_training/             # ML model development
├── tests/                      # Unit tests
│   ├── test_audio_streaming.py
│   ├── test_ml_inference.py
│   └── test_sensors.py
├── requirements.txt            # Python dependencies
└── README.md

🚀 Key Features

• Real-Time Audio Classification
  • Processes microphone input at 22.05kHz (50ms chunks)
  • Identifies sirens, horns, and emergency sounds
• Multi-Sensor Integration
  • MPU6050 for head orientation tracking
  • Force sensor for crash detection
  • GPS for emergency location logging
• Tactile Feedback System
  • Configurable vibration patterns for different alerts
  • LED visual indicators

📦 Hardware

• Raspberry Pi 4
• MEMS Microphone
• MPU6050 (Head tracking)
• GPS Module (NEO-6M)
• Vibration Motors

System Architecture

🛠️ Setup

# 1. Install dependencies
pip install -r requirements.txt

# 2. Configure hardware pins
nano raspberry_pi/config.py

# 3. Start the system
# On Pi:
python raspberry_pi/main.py

# On laptop:
python client/audio_client.py --pi-ip 192.168.x.x

🧪 Testing

# Run all tests
python -m pytest tests/

# Individual test modules
pytest tests/test_sensors.py
pytest tests/test_ml_inference.py -v

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Recommended Tags

Topics:  
assistive-technology, deaf-community, real-time-audio, raspberry-pi, tensorflow-lite, haptic-feedback, smart-helmet, accessibility