SCL
MIT

Open Walks

A Crowdsourced Mapping of Sidewalk Accessibility Using Smartphones and Multimodal AI

Sidewalk condition is a key factor for determining whether a city is truly accessible.

Yet most cities lack reliable data. Existing methods of sidewalk monitoring are costly and slow, while satellite or vehicle-captured imagery misses the critical pedestrian perspective.

We propose a new method: Open Walks.

A web app that runs directly in any smartphone browser, bringing sidewalk-accessibility mapping to the hands of the community.

Each step counts in sidewalk analysis. With Open Walks, each step becomes a data point containing:

Building on our existing Sidewalk AI model, we automatically analyze geolocated surface materials, obstacles, and cracks.

A Vision Language Model (VLM) then examines each sidewalk data point to extract additional qualitative accessibility information.

Together, all of these dimensions are combined into an accessbility score tailored to local standards.

Creating a powerful and scalable platform that reveals the full picture of sidewalk accessibility.

Total Width
The full width of the sidewalk including obstacles
Clear Path Width
The actual walkable width of sidewalk

With more than 7.3 billion active smartphones worldwide, every scan contributes to a global, collaborative map of sidewalk accessibility.

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km mapped
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contributors

Contribute to the mission and start mapping your city.

Open Walks

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Team

  • Carlo Ratti Director SCL
  • Diego Morra Lead Research & Developer
  • Martina Mazzarello Research Supervision
  • Fábio Duarte Design Supervision
  • Elizabeth McCaffrey Web & Visualization
  • * We would like to thank lab members, SCL Summer School participants, and colleagues, who have contributed to the global sidewalk scanning presented here.

Publication

Morra, D., Mazzarello, M., Ratti, C. (2026). Open Walks: ..... . Journal Name.

Press

Download the Press Materials

The material on this website can be used freely in any publication provided that:

  • It is duly credited as a project by the MIT Senseable City Lab
  • A PDF copy of the publication is sent to senseable-press@mit.edu

For more information,
senseable-contacts@mit.edu

in collaboration with

seoul ai foundation

with special thanks to