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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