Built a crowdsourced ADA accessibility mapping tool on top of Leaflet/OSM - looking for feedback from this community
Hey all,
I'm a high school student and I built PathAble, a web app for crowdsourcing ADA accessibility features (ramps, curb cuts, elevators, handrails, staircases) and routing around them. Stack-wise it's Leaflet for the map, OSM tiles via CartoDB, OSRM for routing, and Geoapify for geocoding, with a Flask backend and Supabase/PostGIS for storage.
Right now markers are user-submitted rather than pulled from OSM tags directly, users drop a pin, snap a photo, and a vision model auto-tags what's in the image (ramp, staircase, etc). I know OSM already has accessibility tagging conventions (wheelchair=yes/no/limited, tactile_paving, etc) and projects like WheelMap and AccessMap exist in this space already, including one specifically for Seattle.
I'd love feedback from people who actually know this space well:
- Does it make more sense long-term to write accessibility data back into OSM directly instead of a separate database, so it benefits the wider ecosystem instead of being siloed in my app?
- Any obvious gaps in how I'm tagging/categorizing features compared to established OSM accessibility conventions?
- Anyone doing something similar who'd be open to comparing notes?
Live app here if you want to poke at it: https://pathable-mu.vercel.app
Open to any and all criticism, this is very much a work in progress and I'd rather build it right than build it fast.