AI Water Quality Advisor

An AI powered web application that analyzes household water test results and provides safety assessments, possible issues, and treatment recommendations based on international water quality guidelines (WHO/EPA).

Built with AWS Cloud + AI to demonstrate cloud-native architecture, serverless design, and real-world AI integration.

🚀 Features

• User-Friendly Web App: Enter water test values (pH, turbidity, hardness, nitrates, etc.) via a responsive form.

• AI-Powered Analysis: Amazon Bedrock (Claude Sonnet 3.0) interprets results and generates recommendations.

• Cloud-Native Architecture: Serverless backend using AWS Lambda + GraphQL API Gateway (through AWS AppSync).

• Scalable Deployment: Frontend hosted on AWS Amplify.

• CI/CD: AWS Amplify's integration with Github facilitates a CI/CD pipeline to push latest code changes to te hosted application.

• Secure Access: AWS Cognito for user authentication and personal dashboards.

🏗️ Architecture

    [Frontend: React / Amplify] ←→ [Cognito]
        ↓
   [AppSync] (GraphQL API)
        ↓
   [Lambda Functions] → [Amazon Bedrock (AI Model)]
        ↓
   [DynamoDB] (store user inputs + AI reports)

⚙️ Tech Stack

• Frontend: React (Amplify-React UI and Hosting)
• Backend: AWS Lambda + API Gateway
• AI Model: Amazon Bedrock (Anthropic Claude Sonnet 3.0)
• Authentication: AWS Cognito

📊 Application Workflow

• User enters test results (e.g., pH 7.8, Turbidity 10 NTU, Hardness 250 mg/L).
• API Gateway forwards data to Lambda.
• Lambda formats a prompt and sends it to Bedrock.
• Bedrock returns structured insights:

🛠️ Setup & Deployment

Prerequisites:

• AWS account with Bedrock access enabled
• Node.js & npm (for frontend)
• AWS CLI configured
• A Github account

Steps:

1. Create new react application:

    npm create vite@latest ai-recipe-generator -- --template react-ts -y
    cd ai-recipe-generator
    npm install
    npm run dev

2. Install Amplify packages

npm create amplify@latest -y   

3. Initialise Github repository and push code to Github.

4. Deploy App with AWS Amplify.

🎯 Future Improvements

• Implement data persistence with DynamoDB to store test data and AI analysis.
• Add visual graphs for trends (Chart.js + DynamoDB data).
• Multi-language support (via Amazon Translate).
• Exportable PDF reports for users.

📌 Why This Project Matters

This project bridges environmental engineering and cloud AI, showing how AWS can support public health, sustainability, and data-driven decision-making.

It’s not just a coding demo — it’s a real-world application with potential impact.

👨‍💻 Author

Paul Onyebuchi

Cloud Developer | AWS Certified | Chemical Engineering Background