Inspiration
Cities need faster emergency response systems. Many emergencies (fire, medical, accidents) waste critical time due to slow reporting. We wanted a system that instantly reports incidents, alerts responders, and visualizes data in real-time.
What it does
Allows users to report emergencies in real-time, automatically notifies nearest responders, and provides dashboards and maps to track incidents and improve city safety.
How we built it
Backend: FastAPI for REST API endpoints (/report-emergency, /recent-emergencies)
Frontend: Streamlit for interactive dashboards, graphs, and maps
Visualization: Matplotlib for graphs, PyDeck for maps
Data Storage: In-memory Python lists (can be upgraded to a database)
Challenges we ran into
Integrating FastAPI backend with Streamlit frontend
Ensuring real-time updates in the dashboard
Handling map visualization and emergency type color coding
Accomplishments that we're proud of
Fully functional real-time emergency reporting system
Interactive dashboard and map visualization
Easy-to-use dark-themed UI
Works on both desktop and mobile
What we learned
How to connect a backend API with a frontend in Python
Real-time data visualization techniques
Designing a user-friendly emergency reporting system
What's next for Smart City Emergency Response System
Add database storage for historical data
Implement notification system for responders
Deploy to cloud for city-wide real-time monitoring
Built With
- amazon-web-services
- and
- apis:
- can-be-replaced-with-any-db)-cloud/hosting:-localhost-(can-deploy-to-heroku
- cloud)
- emergency
- endpoints
- fastapi
- for
- languages:-python-frameworks:-fastapi-(backend)
- or
- pydeck-database/storage:-in-memory-(python-list
- reporting
- rest
- streamlit
- streamlit-(frontend)-data-visualization:-matplotlib
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