What a school crossing sounds like at 8:12 a.m.
One week of sensor data from an east-London elementary school — and what it reveals about who the sidewalks were built for. The busiest hour is not the one the city planned for.
Our Urban Futures generates the community-centred evidence cities need to plan streets, neighbourhoods, and infrastructure that work for everyone. We run multiple community observation projects across cities — each one generating open data that didn't exist before.
WHAT WE DO
We build sensor networks, conduct street-level audits, and work with communities to generate open, high-quality data about how people move through cities. Then we make that data available to the planners, councillors, and neighbours who need it most.
Active — London, Ontario
A network of AI-assisted traffic sensors deployed in a residential London, Ontario neighbourhood to measure pedestrian, cyclist, and motor vehicle activity.
Learn more →We work with resident volunteers who host sensors on their properties. The data belongs to the community as much as it belongs to the research.
Every dataset we generate is freely available for download. We believe the evidence cities need should not be locked behind paywalls.
We prioritise neighbourhoods that are underserved by existing data infrastructure. Visibility is the first step toward change.
One week of sensor data from an east-London elementary school — and what it reveals about who the sidewalks were built for. The busiest hour is not the one the city planned for.
How edge-AI lets us measure pedestrian volume without ever storing an image of a face. A short explainer on privacy-preserving computer vision.
A policy brief for municipal staff on translating sensor evidence into infrastructure spend — and the political work of making invisible streets visible.
We're always looking for community members in our study areas who would like to participate. It takes about 20 minutes to set up and requires only a power outlet and Wi-Fi.
Get in touch →