This project is an AI/ML-based Water Quality Checker that predicts whether a given water sample is Safe, Moderate, or Unsafe for drinking.
The model uses input parameters such as pH, Hardness, Nitrate, Conductivity, and TDS and classifies the water quality based on trained rules.
This is an ongoing project โ currently showing 30% progress.
- Synthetic Dataset Creation (500 samples with random values for water quality parameters).
- Labeling Function that categorizes water into
Safe,Moderate, orUnsafe. - RandomForest Classifier trained on the dataset.
- Tkinter GUI for user input:
- Enter pH, Hardness, Nitrate, Conductivity, and TDS values.
- Get classification result in a popup window.
- Visualization:
- Displays a bar chart of entered parameters for better understanding.
When you run the program, you will see:
- Input fields for pH, Hardness, Nitrate, Conductivity, TDS.
- A Check Water Quality button.
- Result displayed as Safe, Moderate, or Unsafe.
- A bar chart of entered water sample parameters.
- Replace synthetic dataset with a real-world water quality dataset.
- Improve GUI design with modern styling and icons.
- Add feature to export results as PDF/CSV report.
- Package project into a standalone
.exeapplication. - (Optional ๐) Integrate IoT sensors for real-time water sample input.
- Python 3
- Pandas, NumPy (data handling)
- Scikit-learn (RandomForest model)
- Tkinter (GUI)
- Matplotlib (visualization)
- Clone the repository:
git clone https://github.com/your-username/Water-Quality-AIML.git cd Water-Quality-AIML
2.Install required dependencies:
pip install pandas numpy scikit-learn matplotlib
3.Run the program:
python water_quality_checker.py