Water Quality AI Predictor
Name Water Quality AI Predictor
Description An AI-powered Streamlit application that predicts potential health risks based on water quality parameters. Users can upload CSV files containing water quality data, and the app outputs a risk assessment along with visualizations. This app is designed to be lightweight and offline-first to support users in low-bandwidth areas. It also serves as a corpus collection engine for water quality data analysis.
Visuals
Features
Upload water quality CSV files Predict health risks using AI Interactive visualizations of water parameters Download prediction results Offline-first support for low-internet areas
Installation
Clone the repository:
git clone https://code.swecha.org/shrinityaboini/water_quality_aip.git cd water_quality_aip
Install dependencies:
pip install -r requirements.txt
Requirements
Python 3.9+ Streamlit Pandas, NumPy, Matplotlib Scikit-learn
Usage
Run the application:
streamlit run app.py
Open the app in your browser.
Upload a CSV file with water quality parameters.
View AI-generated health risk predictions.
Download the results for offline reference.
Support For any issues, contact: shrinityaboini@gmail.com
Roadmap
Week 1: MVP completed with CSV upload, AI prediction, and visualization
Week 2: Beta testing and user feedback incorporation
Weeks 3-4: User acquisition campaign and dataset growth
Future: Add multilingual support, real-time IoT integration, and enhanced AI models
Contributing We welcome contributions!
Fork the repository Create a branch for your feature/fix Test thoroughly Submit a pull request
Please follow Python coding standards and comment your code clearly.
Authors and Acknowledgment
Shri Nitya Boini – Project Lead & AI Integration
Pallavi Rajan - Front-end / Streamlit
K Sathwik Reddy - Back-end / Python Logic
A Sai Kirthi - User Testing & Feedback
Pagilla Sreshta Reddy - Documentation & Deployment
Special thanks to Swecha.org and Streamlit community for guidance and support.
License MIT License – see LICENSE file for details.
Project Status Active – development completed and deployed on Streamlit Cloud. Live App: https://waterqualityaip-kn2hjuwdxrdjnxtwzlubbr.streamlit.app/