Do you have a problem with drivers speeding down the road? With this Raspberry Pi speed trap project created by Rob Lauer, you can confirm it for yourself. It is powered by machine learning technology to both identify vehicles and capture their current speed.
The project helps makers by tracking the frequency and severity of speeders by logging the traffic data automatically. The Raspberry Pi captures the speed and images of the vehicle then relays the data to a cloud-based dashboard.
To construct the speed trap unit, Lauer opted to use a Raspberry Pi 4. It’s connected to a Raspberry Pi Camera Module V2 for image capturing and a doppler radar sensor for speed data input. A Blues Wireless Raspberry Pi Starter Kit was used for its cellular module.
Lauer created a custom machine learning model for the project using Edge Impulse. For those new to machine learning, a model is essentially a database of reference files or images which in this case help the Pi identify vehicles. The wireless module sends data to the cloud-based dashboard so users can observe traffic and speed data in real time.
The best Raspberry Pi projects are the ones you can recreate yourself—to get a closer look at this project, visit the guide created by Rob Lauer at Hackster.
