Real-Time Weather and Disaster Alert System

A real-time weather and disaster alert system that provides timely and localized severe weather notifications. This system integrates weather data from Weatherbit, push notifications via OneSignal, interactive maps with Google Maps & Geolocation APIs, and robust analytics powered by Pandas. The mobile app is built using React Native with NativeWind CSS and deployed for demos via the Expo Go app.

Table of Contents

• Overview
• Features
• Tech Stack
• Architecture Diagram
• Development Environment Setup
• Technical Challenges & Solutions
• Testing
• Contributing
• License

Overview

The Real-Time Weather and Disaster Alert System is designed to:

• Fetch and process severe weather data in real time using the Weatherbit API.
• Deliver instant push notifications using OneSignal.
• Provide an interactive map interface with Google Maps & Geolocation APIs for hyper-localized alerts.
• Allow users to share alerts with friends and family.
• Process engagement data using Pandas for analytical insights.

Features

Core Weather Alert Integration

• Description: Integrates Weatherbit API to fetch severe weather data, filter relevant alerts, and make them available via a RESTful Flask backend.
• User Benefit: Ensures timely and actionable weather alerts for local residents to take necessary precautions.

Push Notification Service Integration

• Description: Uses OneSignal to deliver real-time push notifications to users' devices.
• User Benefit: Provides immediate alerts and safety instructions during severe weather events.

Interactive Map & Location-Based Alert Filtering

• Description: Leverages Google Maps and Geolocation APIs to display alerts on an interactive map, filtering them based on user-defined proximity.
• User Benefit: Offers hyper-localized weather information to reduce noise and improve preparedness.

Alert Sharing and Contact Management

• Description: Enables users to share alerts with trusted contacts and manage their contact lists within the app.
• User Benefit: Enhances community safety by spreading critical information quickly.

Analytics Dashboard and Engagement Tracking

• Description: Processes engagement logs using Pandas to generate key performance metrics and visual dashboards.
• User Benefit: Allows administrators and data analysts to monitor alert effectiveness and optimize the system based on real usage data.

Tech Stack

• Frontend Framework: React Native with NativeWind CSS (for streamlined styling)
• Backend Technology: Flask (Python)
• Database: PostgreSQL
• APIs & Integrations:
  • Weatherbit API (for severe weather data)
  • Google Maps & Geolocation APIs (for interactive maps and location detection)
  • OneSignal (for push notification delivery)
• Analytics & Data Processing: Pandas (Python)
• Testing & Quality Assurance:
  • pytest (for API, unit, and integration tests)
  • Detox (for end-to-end mobile app testing)
• Deployment:
  • Frontend: Demo deployment via Expo Go app
  • Backend: Flask application on EC2 instance
• CI/CD: GitHub Actions
• Testing: pytest, Detox

Architecture Diagram

Below is a simplified diagram showing how different components of the system interact:

                    +----------------------------------+
                    |         User Devices           |
                    |  (iOS/Android via Expo Go App)   |
                    +---------------+------------------+
                                    |
                                    | (React Native App via Expo)
                                    V
                    +----------------------------------+
                    |         Frontend Layer           |
                    |    React Native with NativeWind  |
                    +---------------+------------------+
                                    |
                                    | REST API Calls
                                    V
                    +----------------------------------+
                    |         Backend API Layer        |
                    |         (Flask Application)      |
                    +---------------+------------------+
                     /      |         \         \
                    /       |          \         \
                   V        V           V         V
       +----------------+ +--------------+  +--------------+  
       | Weatherbit API | |  OneSignal   |  | Google Maps  |  
       | (Weather Data) | | (Push Notif.)|  | & Geolocation|
       +----------------+ +--------------+  +--------------+  
                          \       |        /
                           \      |       /
                            V     V      V
                    +----------------------------------+
                    |         PostgreSQL Database      |
                    | (User Data, Alerts, Engagement   |
                    |  Logs, Preferences & History)    |
                    +----------------------------------+
                                    |
                                    | Analytics Processing
                                    V
                    +----------------------------------+
                    |         Analytics Module         |
                    |         (Pandas Scripts)         |
                    +----------------------------------+

Development Environment Setup

Backend Setup (Flask & PostgreSQL)

1. Clone the Repository:

   git clone <repository-url>
   cd project-directory

2. Create a Python Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Database Setup:

   • Install PostgreSQL and create a new database (e.g., weather_alerts_db).
   • Configure the connection settings in your configuration file (config.py or via environment variables).
   • Run migration scripts (using Alembic or Flask-Migrate).

5. Environment Variables:

   • Create a .env file with variables such as WEATHERBIT_API_KEY, ONESIGNAL_API_KEY, GOOGLE_MAPS_API_KEY, and DATABASE_URL.

Testing Environment Setup

pip install pytest pytest-flask

• Follow Detox documentation for simulator setup.

CI/CD Setup

• Configure a CI pipeline (using GitHub Actions, CircleCI, etc.) to run tests automatically on each commit.
• Securely store your environment variables in your CI/CD tool.

Technical Challenges & Solutions

• Third-Party API Integration:

  • Challenge: Handling rate limits, downtime, or latency issues with Weatherbit, OneSignal, and Google Maps.
  • Solution: Implement robust error handling, retries, caching, and fallback mechanisms.

• Real-Time Data Accuracy:

  • Challenge: Keeping weather alerts updated in near real-time.
  • Solution: Optimize polling frequency, consider webhooks, and apply event-driven updates when available.

• Push Notification Reliability:

  • Challenge: Timely delivery of push notifications across networks.
  • Solution: Utilize OneSignal's retry features, monitor deliveries, and incorporate user feedback.

• Geolocation and Map Rendering:

  • Challenge: Variability in geolocation accuracy and smooth map performance.
  • Solution: Use device-native geolocation APIs, test on various devices, and optimize map rendering with clustering techniques.

• Data Volume and Analytics:

  • Challenge: Efficient processing of large data volumes.
  • Solution: Leverage Pandas for in-memory processing and optimize PostgreSQL queries with indexing.

• Development & Testing Coordination:

  • Challenge: Ensuring seamless collaboration and continuous integration.
  • Solution: Follow Lean Agile principles with shift-left testing, daily stand-ups, and integrated automated tests.

• Expo Demo Constraints:

  • Challenge: Ensuring the app functions seamlessly within the Expo Go environment.
  • Solution: Regularly test on Expo Go, use Expo debugging tools, and refer to the Expo documentation for environment-specific issues.

Testing

• Unit & Integration Testing:
  Use pytest for backend API endpoints and service layers.
• End-to-End Testing:
  Use Detox for React Native app flows.
• Regression Testing:
  Continuously run tests in your CI/CD pipeline to catch regressions.
• Performance Testing:
  Optionally use tools like Locust or JMeter for load testing critical endpoints.

Contributing

1. Fork the Repository

2. Clone your Fork:

   git clone <your-fork-url>

3. Create a Feature Branch:

   git checkout -b feature/your-feature-name

4. Commit and Push your Changes

5. Create a Pull Request detailing your changes.

Please follow our code style guidelines and commit message conventions.

License

This project is licensed under the MIT License.

Happy coding! 🚀