Project Detail
StreetEase
A web-based mapping tool designed to help users understand how steep nearby streets are around a chosen address. The goal is to make it easier for people with mobility limitations, disabilities, or difficulty walking to preview the terrain around a destination before they go.
Problem
Most map tools are designed for navigation, but they do not clearly communicate how physically demanding an area may be to walk.
For someone using a mobility aid or managing limited endurance, street grade can make a major difference in whether a route feels realistic or comfortable.
I wanted to explore how street geometry, elevation data, and mapping could be combined into a tool that makes terrain easier to understand at a glance.
What I've Built So Far
So far, I have built a responsive web prototype using React and Leaflet that allows users to search for a location, preview nearby streets within a selected radius, and view a color-coded street overlay representing grade difficulty.
Current work includes:
- A responsive React frontend built for web-first use
- Interactive map rendering with Leaflet and OpenStreetMap
- Address search with autocomplete suggestions
- Radius-based map preview centered on a selected location
- A color-coded street overlay concept for easier terrain scanning
- A lightweight backend API for search and street-grade requests
- Early caching and fallback handling for unreliable third-party APIs
- Resilience work around street lookup and elevation lookup failures
Technical Challenges
StreetEase has been a strong exercise in working with real-world data constraints. One of the biggest challenges has been reliability. Public mapping and elevation APIs can time out, rate-limit requests, or return incomplete street-naming data, which makes building a smooth experience much more complex than with a static demo. I've been working through those issues by restructuring the app to use a backend, adding caching, improving fallback behavior, and separating the frontend display logic from the data-processing pipeline.
What I'm Learning
This project is helping me deepen my understanding of frontend-to-backend architecture, geospatial data workflows, API resilience, and accessibility-centered product design. It has also reinforced how much product quality depends on gracefully handling messy external data, not just on building a clean interface.
What's Next
Next steps for StreetEase include improving the reliability of street and elevation data, refining how unnamed streets are handled, making the grade overlay denser and more accurate, and continuing to improve the user experience around search, feedback states, and map interactions.