Is Your School’s Cafeteria Chaotic and Inefficient? This DIY Device Can Help

In the United States, high schools can have more than 4,000 students in attendance at any given time and many other countries see similar numbers. That is a lot of mouths to feed at lunch time and so running a school cafeteria often requires serious consideration towards logistics. How can administrators figure out the optimal way to space assigned lunch periods in order to achieve efficient traffic flow and nutritional distribution? One way would be to use Aaravsharma23’s Smart Line AI device, which automatically generates valuable cafeteria data.

Smart Line AI is a small and affordable device dedicated to one purpose: observing school cafeteria lunch lines and generating data on the student queue time at given point in the day. It can, for example, tell administrators that at 1:10pm, the average wait time in the lunch line was 95.28 seconds. A simple graph of that data will make it obvious when there are peaks and valleys in the queue time, which would indicate that a revision to the assigned lunch periods might improve efficiently. It could also help cafeteria workers determine the best times to prepare food to meet the demand.

That data could genuinely lower costs while improving the lives of both students and faculty, which is impressive considering how little money it takes to build a Smart Line AI device. The project’s most notable two components are a Raspberry Pi 5 (4GB model) single-board computer and a Raspberry Pi Camera Module 3 (with wide-angle lens). It also needs the typical Raspberry Pi accessories, including a power supply and microSD card. Setup is possible in headless mode, but a keyboard, mouse, and monitor can simplify that setup. The Raspberry Pi and camera fit into a custom 3D-printable enclosure that Aaravsharma23 modeled in Autodesk Fusion.

All of the magic happens thanks to OpenCV and YOLO, the latter being a model that performs object detection in real-time thanks to the use of a CNN (convolutional neural network). That does require footage of the cafeteria for training. But afterwards, Smart Line AI will be able to count the people in frame and within a set boundary, which should enclose the queue area being monitored. Smart Line AI can then gather and present data on that queue.

Aaravsharma23 is a student and developed Smart Line AI for his own school, where it has already done some good. And now other schools can take advantage of Smart Line AI, too.