A full-stack application that detects stairs using sensor data and provides accessible route planning.
- FastAPI server handling sensor data processing and route calculations
- PostgreSQL database for storing detection events
- AWS Location Service integration for route planning
- ML model for stair detection (placeholder implementation)
- Mobile app for recording sensor data
- Map view showing detected stairs and calculated routes
- Real-time data visualization
- Python 3.8+
- Node.js 16+
- Docker and Docker Compose
- AWS Location Service API key
- Clone the repository:
git clone <repository-url>
cd hackhpi- Set up environment variables:
Create a
.envfile in the root directory:
AWS_LOCATION_SERVICE_API_KEY=your-api-key-here- Start the backend and database using Docker:
docker-compose up --build- Make the backend publicly available by using for example ngrok. Write the URL under which the backend is available in the
./frontend/.envfile as
EXPO_PUBLIC_API_URL=https://your-backend-url- Install frontend dependencies:
cd frontend
npm install- Start the frontend development server:
npm run dev-
Download the Expo Go App on your smartphone, connect to the same network as the machine on which you are running the expo development server and scan the qr code, which appears upon execution of
npm run dev -
After loading the code you can use the app