Shreyas2728/The_SmartSheild

🛡️ Smart Helmet Project

Overview

The Smart Helmet is a wearable safety device designed to protect and assist users in high-risk environments such as motorcycling, construction, and industrial work. It integrates sensors, AI, and cloud connectivity to detect accidents, monitor drowsiness, and provide real-time alerts.

This project was developed for a 24-hour hackathon, focusing on accuracy, explainability, and demo-ready visualization to impress judges with both technical depth and societal impact.

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✨ Features

• Impact Detection: Accelerometers and gyroscopes detect crashes or falls.
• Emergency Alerts: Sends GPS location and status to emergency contacts.
• Drowsiness Monitoring: Eye-tracking cameras + ML models to detect fatigue.
• Environmental Awareness: Gas, temperature, and air-quality sensors.
• Connectivity: Bluetooth/Wi-Fi for communication and navigation.
• Explainable AI: Heatmaps and anomaly visualization for transparency.
• Dashboard UI: Real-time sensor data displayed via Streamlit/React.

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⚙️ System Architecture

1. Hardware Layer

   • Helmet with sensors (accelerometer, gyroscope, camera, gas sensor).
   • Raspberry Pi/Arduino for edge data collection.

2. AI Layer

   • Drowsiness detection using OpenCV + dlib.
   • Anomaly detection with deep learning models.
   • Visualization with heatmaps for explainability.

3. Cloud Integration

   • Azure/GCP for storage, dashboards, and emergency notifications.
   • APIs built with FastAPI/Flask for backend services.

4. Frontend

   • Streamlit/React dashboard for judges and demo interaction.
   • Firebase Hosting or Cloud Run for deployment.

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🚀 Getting Started

Prerequisites

• Python 3.8–3.12
• Libraries: opencv-python, dlib, numpy, matplotlib, tensorflow/keras
• Hardware: Raspberry Pi/Arduino, sensors, helmet prototype

Installation

# Clone the repository
git clone https://github.com/your-username/smart-helmet.git
cd smart-helmet

# Install dependencies
pip install -r requirements.txt