AquaSense AI is an water quality analysis platform built with Django that leverages multiple machine learning models to provide accurate water quality assessments and remediation recommendations.
- Multi-parameter Analysis: Process 7 critical water parameters (temperature, dissolved oxygen, pH, conductivity, BOD, nitrate, total coliform)
- IoT Integration: Connect with sensor data for 4 key parameters in real-time
- Advanced Prediction System: Gradient Boosting Regression model used for accurate prediction
- Comprehensive Remediation Guidance:
- Ayurvedic treatment recommendations
- Scientific intervention protocols
- Cross-verification techniques
- Educational Resources: Dedicated sections explaining water quality challenges, vision, and mission
- User Support: Firebase-connected contact system for inquiries and feedback
- Backend: Django
- ML Implementation: scikit-learn, pickle for model serialization
- Frontend: HTML, CSS, Bootstrap
- Cloud Services: Firebase (for contact system)
# Clone the repository
git clone https://github.com/Prathameshv07/AquaSense_AI.git
# Navigate to project directory
cd aquasense-ai
# Create and activate virtual environment
python -m venv env
source env/bin/activate # On Windows: env\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Run the application
python manage.py runserver- Enter water parameter values manually or connect IoT sensors
- View ML-powered water quality predictions
- Access remediation recommendations
- Generate comprehensive reports
- Mobile application integration
- Additional parameter support
- Enhanced visualization tools
- Community feature for data sharing
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.
You are free to use, share, and adapt the material for non-commercial and educational purposes, as long as proper credit is given and any changes are noted.
Learn more: http://creativecommons.org/licenses/by-nc/4.0/