ThunAI is an innovative AI-powered safety application designed to proactively detect and respond to threats faced by women in their daily lives. Our solution leverages cutting-edge technologies like computer vision and real-time GPS tracking to create a comprehensive safety network.
- Uses computer vision to analyze facial expressions and surrounding environment
- Detects distress signals automatically without manual intervention
- Continuously monitors user's location
- Shares live updates with trusted contacts and law enforcement
- Provides accurate location data during emergencies
- Works seamlessly with smartphones and wearable devices
- Ensures accessibility in various situations
- One-touch emergency button for immediate alerts
- Automated notifications to emergency contacts and authorities
- AI chatbot provides real-time safety guidance
- Visual representation of risk levels in different areas
- Uses historical incident data to identify high-risk zones
- Cloud-based infrastructure for fast data synchronization
- Real-time collaboration with law enforcement
- Emergency Alerts: Twilio & Firebase Admin
- Location Tracking: Google Maps API & Folium
- Safety Points Locator: Google Maps API
- Community Support: Streamlit & Firebase
- Authentication: Firebase Authentication & Streamlit-JS-Eval
- Time-Based Response: Datetime Module
- Python 3.7+
- Google Maps API key
- Twilio account credentials
- Clone the repository:
git clone https://github.com/yourusername/ThunAI.git
- Install dependencies:
pip install -r requirements.txt
- Configure environment variables:
- Set your Google Maps API key
- Add Twilio credentials (account SID, auth token, phone number)
streamlit run app.py- Offline accessibility for areas with poor network coverage
- AI-driven predictive analytics for personalized risk assessments
- IoT-based wearable safety devices integration
- Biometric authentication for secure access
This project is licensed under the MIT License - see the LICENSE file for details.