Plow Kingston - Optimal Snowplow Routing System

Winner of the QEC 2025 Programming Competition. This full-stack application addresses snowplow routing optimization in urban environments through an interactive web-based simulation system. The system visualizes real-world road networks using actual geographic road data (GeoJSON format) and implements a dynamic storm simulation that continuously deposits snow across the network. The platform features intelligent routing algorithms including a Finite Horizon Greedy policy that optimizes reward-to-time ratio within a time budget, using depth-first search to evaluate paths and calculate rewards based on importance, snow depth, and road length. The interactive web interface provides real-time map visualization with OpenStreetMap integration, snow depth heatmaps, plow movement tracking, and statistical analysis. Built with Next.js frontend and FastAPI backend, deployed on Vercel with serverless functions.