Measure traffic speeds.
Demand safer streets.
Open-source speed monitoring for neighbourhood streets
Collect the evidence yourself. velocity.report is free, open-source software that turns a Raspberry Pi and a radar sensor into a speed monitor. Download the Pi image, point it at your street, and get a PDF you can take to City Hall: no cameras, no licence plates, no cloud accounts.
Common Questions
What is this?
An open-source traffic speed monitor. A radar sensor plugged into a Raspberry Pi records how fast vehicles pass, stores the data locally, and generates a professional PDF report: speed distributions, hourly patterns, and percentile breakdowns. No cloud, no cameras, no surveillance.
Who is this for?
You, probably. If you live on a street where traffic moves faster than it should, this is the tool. Parent associations, community groups, neighbourhood watch, residents with a safety concern and nowhere to take it. If you've ever stood at a council meeting and been told to come back with evidence, here's how you get it.
What does it measure?
Vehicle speeds. A radar sensor records how fast vehicles pass and stores the data on a Raspberry Pi. No faces, no licence plates, no images of any kind.
Where does the data go?
Nowhere. It stays on your device, in a local database. There is no cloud account, no upload step, nothing that sends data anywhere without your knowledge. The only way data leaves your network is when you hand (or email) someone the finished PDF.
How do I get started?
Follow the setup guide. You need a Raspberry Pi and an OmniPreSense radar sensor. By the end, you'll have a working speed monitor and a PDF report that holds up in a council meeting.
Raspberry Pi image
Release notes →Requires Raspberry Pi 3+
Raspberry Pi Imager custom repo
Install Raspberry Pi Imager, then run this in a terminal. The --repo flag works on all platforms; the path to the binary varies by OS.
Server downloads
Release notes →Requires Linux ARM64
Requires macOS 15+
Research
The radar setup gives you speed data and a PDF. LiDAR is the next level: see the full scene, identify road users by type, and see how they move around each other. It can answer questions the radar cannot, like how close cars pass cyclists, or how many drivers roll through the intersection (and how fast).
This is research-stage work, and contributions are welcome. The pipeline is open source, the maths are documented, and there's a list of open questions we'd love to hear your thoughts on.
VelocityVisualiser.app: live LiDAR point clouds, tracked objects, and motion trails
Requires macOS 15 · Apple Silicon
Making the Case
at City Hall
"The goal is fewer crashes, fewer injuries, and zero fatalities.
If the speeds don't drop, the work can't stop."