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EchoGuard

Predicting fire risks to protect communities worldwide

Overview

EchoGuard is a web application designed to assist authorities and firefighters in predicting fire risks and alerting populations to potential fire hazards. By leveraging location-based data, it empowers proactive fire safety measures across local communities globally.

Live Demo: https://echo-guard-gilt.vercel.app/


Features

  • Fire Risk Prediction: Input a location to assess fire risk, likely using weather, vegetation, and historical data (exact sources TBD).
  • Early Warnings: Enables timely alerts for evacuations and preventive actions in high-risk areas.
  • Resource Optimization: Helps firefighters allocate resources efficiently based on predicted risk levels.
  • User-Friendly Design: Simple interface for professionals and communities to access critical insights.

Installation

  1. Clone the Repository:
    git clone https://github.com/yourusername/echo-guard.git
    cd echo-guard

Install Dependencies:

bash Copy npm install Note: This assumes a Node.js-based project. For other stacks (e.g., Python/Ruby), use appropriate package managers.

Run Locally:

bash Copy npm start Open http://localhost:3000 in your browser.

Usage Enter a location on the homepage to view its fire risk assessment.

Use predictions to plan evacuations, allocate firefighting resources, or implement preventive measures.

Share insights with local authorities or communities for coordinated action.

Contributing We welcome contributions! To contribute:

Fork the repository.

Create a feature branch:

bash Copy git checkout -b feature/your-feature Commit changes:

bash Copy git commit -m "Add your feature" Push to your branch:

bash Copy git push origin feature/your-feature Open a Pull Request.

Please follow our Code of Conduct and report issues via the Issues tab.

Future Plans Integrate real-time data APIs (weather, satellite imagery)

Expand language support beyond Portuguese

Add risk heatmap visualizations

Enhance historical data analysis

License This project is licensed under the MIT License.

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