Inspiration
Most map apps are optimized for directions, not exploration. For people who enjoy walking, biking, or wandering, it can be difficult to judge how accessible or walkable an area is at a glance.
What it does
Web-Sanpo allows users to click any point on a map and instantly see a color-coded walkability score based on the density of amenities like restaurants, parks, and stores. It also highlights nearby locations of interest.
How we built it
- Google Maps API β for location interface
- Overpass API (OpenStreetMap) β for real-world amenity data
- HTML, CSS, JavaScript to create a responsive and dynamic front-end
- Python (Flask) to manage back-end logic and API communication
- Render for deployment and web hosting
Challenges we ran into
- Many of our original ideas were already deployed by map apps.
- Handling inconsistent data from OpenStreetMap (e.g., parks mapped as polygons instead of points)
- Filtering and categorizing raw location data accurately into meaningful walkability metrics
- Integrating multiple APIs (Google Maps + Overpass) and syncing frontend interactions with backend logic
Accomplishments that we're proud of
We built a fully functional, responsive map interface that updates based on user clicks and visualizes accessibility. We're proud of implementing color-coded markers for various amenity types, all using live data and minimal resources.
What we learned
We learned how to work with geospatial APIs like Google Maps and Overpass to display and interact with real-time data. We gained experience handling inconsistencies in open data sources and developed skills in building a frontend-backend pipeline that updates dynamically. Most importantly, we learned the value of designing tools that prioritize exploration, creativity, and user-centric insight, not just efficiency.
What's next for Web-Sanpo
π§ Use graph theory to analyze real-world street/path networks for accessibility π Compare different modes of transport (e.g., walking vs. driving) πΊοΈ Customize scoring based on what the user values most (e.g., quiet parks vs. dense shops)

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