🌊 About AquaPredict

💡 Inspiration

Access to clean and safe water is one of the biggest global challenges. We wanted to build a solution that not only monitors but also predicts water quality trends, empowering communities, policymakers, and individuals to make sustainable water management decisions.

🛠️ How We Built It

• Frontend: Built using Next.js (React framework) with TypeScript for type safety.
  
• Styling: Designed a clean, modern UI with Tailwind CSS.
  
• Prediction Model: Implemented a data-driven model to evaluate and forecast water quality parameters.
  
  • For example, given features like $pH$, turbidity, dissolved oxygen $(DO)$, and temperature $T$,
    our model outputs a water quality index (WQI):
    

$$ WQI = f(pH, \; DO, \; T, \; \text{turbidity}, \ldots) $$

• Deployment: Hosted on Vercel for seamless CI/CD and scalability.
  

📚 What We Learned

• How to integrate data modeling with modern web frameworks.
  
• The importance of UI/UX design in communicating scientific insights clearly.
  
• How to use pnpm and optimize Next.js builds for deployment.
  
• Working as a team under time pressure to ship a product quickly.
  

🚧 Challenges We Faced

• Integrating the prediction model with a fast and scalable frontend.
  
• Handling large datasets and ensuring the app remained performant.
  
• Configuring deployment with pnpm on Vercel.
  
• Balancing between accuracy of predictions and real-time performance.
  

🌍 Impact

AquaPredict demonstrates how technology + data can help tackle real-world problems like water quality and environmental sustainability. It’s a step toward ensuring safe, accessible, and sustainable water for all.

Built With

• ai
• nextjs
• tailwindcss
• typscript
• vercel