Raspberry Pi Monitors Traffic with AI for Urban Planning and More

Traffic monitoring is a handy tool for a few industries, from urban planning to news stations or anyone interested in the various metrics used to monitor traffic flow. Today, we’ve got a Raspberry Pi project from a maker known over at Hackster as Naveen, who created a traffic monitoring system with some help from a Raspberry Pi CM4.

The Pi in this project is working with BrainChip’s Akida Dev Kit. It has everything Naveem needed to capture images from a video traffic feed for the AI system to evaluate. Data can be stored later or made available in real time. Naveem suggests this could be useful for businesses and government agencies that need to monitor traffic patterns.

The Akida Dev Kit has a custom PCB with a neuromorphic processor. If you haven’t heard of neuromorphic computing, it’s a design method for hardware and software that uses structures resembling what you’d find inside a brain. This additional PCB is responsible for taking some of the performance load off of the Pi.

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This particular kit has a Raspberry Pi Compute Module 4 featuring 8GB of RAM and wireless support. The kit also includes one of the Akida PCIe PCBs from BrainChip. These can be purchased individually for $499, but the board was part of the Raspberry Pi CM4 Dev Kit in this case. You can read more about the Akida PCIe board on the BrainChip website.

The traffic monitoring demo was created using a video from Pexels showing cars passing through an intersection. Using Python, a custom script was created that captures every fifth frame as an image. The images were then used to train the traffic monitoring AI using Edge Impulse Studio.

This is one Raspberry Pi project with plenty of potential for modification depending on what sort of traffic data you need to collect. You can see the demo in action over at Hackster.