olagold-hackxx/climatewavers

A social media Web app focused on climate change, where users can post details and data about climate-related events, and the application leverages AI-driven analysis.

Climate Waver

This project aims to provide real-time climate change monitoring and disaster response capabilities through an integrated platform. The system utilizes Python and Node.js servers, MySQL for users and communities database, MongoDB for storing third-party datasets, and implements mitigation strategies for the OWASP Top 10 security risks.

1. Project Architecture
2. Technologies Stack
   • Backend
   • Frontend
   • Machine Learning
   • Database
3. Features
4. Setup and Installation
5. OWASP Top 10 Mitigation

Project Architecture

Technologies Used

Backend

Python Server:

Framework: Django
Database: MySQL for user and communities data
Real-time Data Processing: Pandas, NumPy
Real-time Communication: Django-socketio for websocket implementation
APIs: RESTful API endpoints for data retrieval and analysis

Node.js Server

Framework: Express.js
Database: MongoDB for storing third-party datasets
Real-time Communication: Socket.io for websocket implementation
Security: Helmet.js for securing HTTP headers, Express Validator for input validation
APIs: RESTful websocket API endpoints for real time data retrieval, updates and analysis

Machine Learning

TensorFlow

Frontend

Framework: React.js
Data Visualization: D3.js, Chart.js
Mapping: Leaflet.js for interactive maps
User Interface: Material-UI for responsive design\

Databases:

• MySQL

  • Schema: Users, Communities
    Authentication\
  • ORM: SQLAlchemy

• MongoDB:

  • Collections: Third-party datasets, Real-time climate data
    MongoDB Atlas for cloud-based storage

Features

Real-time Climate Monitoring: Utilize satellite data, weather stations, and environmental sensors to provide real-time climate change information.
Disaster Prediction: Implement machine learning models to predict disaster events based on historical data and current climate patterns.
Community Engagement: Allow users to contribute real-time observations, report incidents, and participate in disaster preparedness activities.
Third-party Data Integration: Store and analyze third-party datasets related to climate change, environmental factors, and disaster events using MongoDB.\

OWASP Top 10 Mitigation:

Implement input validation and sanitization to prevent SQL Injection and Cross-site Scripting (XSS) attacks. Secure HTTP headers using Helmet.js to prevent various attacks like Clickjacking. Implement secure authentication mechanisms and use encryption for sensitive data storage to prevent data breaches. Regular security audits and code reviews to identify and fix vulnerabilities.

Setup and Installation

Clone the Repository:

git clone https://https://github.com/IsmaelKiprop/ClimateWavers.git
cd ClimateWavers

Setup Python Server:

1. Clone the Repository:

   cd Django-server

2. Install Dependencies:

   pip install -r requirements.txt

3. Database Setup:

   • Configure the database settings in settings.py.
   • Run migrations:

     python manage.py migrate

4. Static and Media Files:

   • Collect static files:

     python manage.py collectstatic

   • Configure media file settings in settings.py.

5. Run the Django Development Server:

   python manage.py runserver

Setup Node Server:

1. Install Dependencies:

npm install

2. Environment Variables:

   • Create a .env file in the root directory.
   • Define the following environment variables in the .env file:

     PORT=3000
     THIRD_PARTY_API_URL=<third-party-api-url>

3. Run the Node.js Server:

   npm start