DenGuard: AI-Powered Dengue Outbreak Prediction and Response 🌐🦠

Table of Contents

• Overview
• Features
• Technologies Used
• Installation
• Usage
• How It Works
• Contributing
• License
• Contact

Overview

DenGuard is an AI-powered web application built on Django. It predicts dengue outbreak risks and suggests smart municipal actions using machine learning. By utilizing real-time weather data, historical case reports, and medical inputs, DenGuard helps citizens and healthcare professionals stay alert and respond proactively to potential dengue threats.

Features

• Predictive Analytics: Uses machine learning algorithms to forecast dengue outbreaks.
• Real-Time Data Integration: Incorporates current weather data and historical case reports.
• User-Friendly Interface: Simple and intuitive design for both citizens and healthcare providers.
• Actionable Insights: Provides recommendations for municipal actions to mitigate risks.
• Alerts and Notifications: Sends alerts based on risk levels to keep users informed.

Technologies Used

• Django: The web framework that powers the application.
• Python: The primary programming language for backend development.
• Machine Learning Libraries: Scikit-learn, TensorFlow for predictive modeling.
• Database: PostgreSQL for storing historical case data.
• APIs: Integration with weather data APIs for real-time information.

Installation

To set up DenGuard on your local machine, follow these steps:

1. Clone the Repository:

   git clone https://github.com/hackerworld7322/DenGuard.git
   cd DenGuard

2. Create a Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install Dependencies:

   pip install -r requirements.txt

4. Set Up the Database:

   • Make sure PostgreSQL is installed and running.
   • Create a new database for DenGuard.
   • Update the database settings in settings.py.

5. Run Migrations:

   python manage.py migrate

6. Start the Development Server:

   python manage.py runserver

Now, you can access the application at http://127.0.0.1:8000/.

Usage

Once the application is running, users can:

1. Register: Create an account to access personalized features.
2. Input Data: Enter relevant health and weather data.
3. View Predictions: Check predicted dengue outbreak risks.
4. Receive Alerts: Get notified about potential outbreaks.
5. Explore Recommendations: View suggested actions for local authorities.

How It Works

DenGuard operates by integrating various data sources to create a comprehensive predictive model. Here’s a breakdown of its functionality:

Data Collection

1. Weather Data: The application fetches real-time weather data using APIs. Factors such as temperature, humidity, and rainfall are crucial for predicting dengue outbreaks.

2. Historical Case Reports: The app analyzes past dengue cases to identify patterns and trends.

3. Medical Inputs: User-submitted health data enhances the model's accuracy.

Machine Learning Model

DenGuard employs both supervised and unsupervised machine learning techniques:

• Supervised Learning: Trains on labeled data to predict future cases based on known outcomes.
• Unsupervised Learning: Identifies hidden patterns in the data without predefined labels.

Prediction and Recommendations

Once the model processes the data, it generates predictions. Users receive alerts based on risk levels, along with actionable recommendations for municipal actions. This helps local authorities take proactive measures.

Contributing

We welcome contributions from the community. To contribute:

1. Fork the Repository: Click on the "Fork" button on the top right.
2. Create a New Branch:

   git checkout -b feature/YourFeatureName

3. Make Changes: Implement your feature or fix.
4. Commit Your Changes:

   git commit -m "Add Your Feature"

5. Push to the Branch:

   git push origin feature/YourFeatureName

6. Open a Pull Request: Go to the original repository and click on "New Pull Request".

License

DenGuard is licensed under the MIT License. See the LICENSE file for details.

Contact

For inquiries, please reach out to:

• Email: your-email@example.com
• GitHub: hackerworld7322

For the latest updates and releases, visit our Releases section.

Topics

• denguard
• dengue-case-prediction
• dengue-cases
• dengue-prediction-website
• dengue-shield
• dengue-virus
• healthcare-application
• prediction-model
• prediction-using-supervised-ml
• prediction-using-unsupervised-ml

Acknowledgments

We thank the contributors and community members for their support. Special thanks to the researchers and developers who made this project possible.

Additional Resources

• Dengue Fever Information
• Machine Learning Basics
• Django Documentation

For any further information or assistance, feel free to contact us.