SamudraSuraksha is a mobile application designed to provide recreational suitability and safety information for beach locations across India. Leveraging real-time data from INCOIS and Windy APIs, this application helps users make informed decisions about their beach visits by providing geospatial visualizations and safety notifications.
- Multi-Platform Support: Available on both Android and iOS.
- Real-Time Data Integration: Fetches and updates data on oceanic and meteorological conditions.
- Machine Learning: Provides safety assessments using ML models.
- Geospatial Visualization: Displays beach locations and data using Mapbox.
- User Notifications: Delivers personalized safety alerts and updates.
- Personalized Profiles: Users can save favorite beaches and track recently visited locations.
- SOS Functionality: Quick access to emergency contacts.
- Search Functionality: Search beaches based on name, location, or safety status.
Below is a high-level architecture diagram showcasing the interaction between various components in SamudraSuraksha:
Below is a high-level workflow diagram showcasing the interaction among the user and the various components in SamudraSuraksha:
- Frontend: React Native
- Backend: Python with FastAPI
- Database: PostgreSQL with PostGIS
- APIs: INCOIS and Windy APIs
- Geospatial Visualization: Mapbox
- Machine Learning: Integrated safety models
- Docker
- Node.js and Yarn for frontend development
- Python 3.10 or higher for backend development
git clone https://github.com/sandeepangh782/literate-octo-fortnight.git
cd sandeepangh782-literate-octo-fortnight- Copy the
.env.examplefile to.envin the project root. - Fill in the required environment variables (e.g.,
DATABASE_URL, API keys, etc.).
-
Build and start the containers:
docker-compose up --build
-
Access the backend API at
http://localhost:8000. -
To stop the containers:
docker-compose down
-
Navigate to the frontend directory:
cd frontend -
Install dependencies:
yarn install
-
Start the development server:
yarn start
-
Follow the instructions to launch the app on your connected device or emulator.
- GET /api/v1/beaches: Fetches nearby beaches based on user location.
- POST /api/v1/favorites: Add a beach to favorites.
- GET /api/v1/notifications: Retrieves user notifications.
The backend includes ML models (e.g., safety_index_model.pkl) for assessing beach safety based on various parameters such as wave height, weather, and UV conditions.
Contributions are welcome! Please fork this repository and create a pull request with your changes.
