Busted! Create an ML-Powered Speed Trap

In this project, I built a portable speed trap that can be used to monitor traffic speed conditions in your neighborhood. By using an ML model to identify vehicles, a doppler radar sensor to detect speed, and a cellular module to relay collected data to the cloud, it was surprisingly easy to build out this IoT solution!

Watch an intro video and then view the complete tutorial over at Hackster.io!

Field deployment 👆

Ubidots dashboard 👆

Hardware:

• Raspberry Pi 4
• Notecard and Notecarrier-PI HAT from Blues Wireless
• PiCamera v2
• OPS243-A Doppler Radar Sensor
• Adafruit Seven-segment Display
• 30000mAh Power Bank
• Enclosure

Software and Services:

• Python
• Notehub.io
• Edge Impulse
• Ubidots