HydroChain is built using Next.js for the frontend, styled with Tailwind CSS, and connected to our smart contract using Web3.js, deployed on Optimism. The rainfall prediction model is driven by Python, using libraries like rasterio, scikit-learn and ML models like ARIMA to analyze and predict rainfall patterns. The historical data is processed into a smooth and visually interpretable heatmap, providing clear insights at a glance.
The dApp is user-friendly, requiring minimal input while delivering maximum value. Users simply search for their location, and our system does the rest—displaying a clear and detailed prediction map along with a trend graph that highlights key rainfall patterns and projections.
Link to project: https://github.com/kelvinwest156/HydroChain.git
Link to PowerPoint: https://github.com/kelvinwest156/HydroChain/blob/main/HydroChain_Pitch_Deck.pptx