Kavu

Predict. Protect. Preserve.

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🌾 About the Project — Kavu: Intelligent Crop Inventory Assistant

🧠 Inspiration

In many parts of the world, farmers suffer massive post-harvest losses due to poor storage, limited weather insights, and lack of timely decision-making. We were inspired to build Kavu to empower smallholder farmers and agricultural managers with a smart, intuitive assistant that predicts spoilage, gives weather-aware recommendations, and tracks potential revenue from stored crops.

🛠️ How We Built It

We developed Kavu as a full-stack application using:

  • React.js for the front-end dashboard
  • Firebase Realtime Database for crop storage
  • Google Gemini API for generating harvest recommendations
  • WeatherAPI for live forecast integration

We also implemented:

  • Real-time crop health tracking
  • Interactive pie and bar charts for storage and revenue visualization
  • A chatbot assistant to answer user questions using real context from their crop data and forecast

📚 What We Learned

  • How to integrate LLMs meaningfully into practical tools
  • Structuring user data for real-time inference and analysis
  • Building a responsive UI with weather and crop data dependencies
  • Handling async operations with conditional rendering in React

🚧 Challenges We Faced

  • Managing async API calls and ensuring consistent data updates
  • Handling malformed or missing crop data and providing fallback UI
  • Filtering and surfacing relevant context to the chatbot
  • Designing for both usability and analytical clarity within a short demo window

🌟 What's Next

We plan to:

  • Add multi-language support for farmers in non-English-speaking regions
  • Incorporate mobile notifications for high spoilage risk
  • Fine-tune the recommendation model based on user feedback and seasonal patterns

“Kavu” means “sacred grove” in certain cultures — a nod to our belief that crops, like code, deserve intelligent care.

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