Web application to control a swarm of Raspberry Pis

Web application to control a swarm of Raspberry Pis

A web-based solution to control a swarm of Raspberry Pis, featuring a real-time dashboard, a deep learning inference engine, 1-click Cloud deployment, and dataset labeling tools.

I recently completed an AI mentorship program at SharpestMinds, of which the central element was to build a project, or even better, a complete product. I choose the latter, and in this article, I write about what I built, how I built it, and what I learned along the way.

Continued from Part 1…


This is the second article of the three-part SorterBot series.


Source code on GitHub:

  • Control Panel: Django backend and React frontend, running on EC2
  • Inference Engine: Object Recognition with PyTorch, running on ECS
  • Raspberry: Python script to control the Robotic Arm
  • Installer: AWS CDK, GitHub Actions and a bash script to deploy the solution
  • LabelTools: Dataset labeling tools with Python and OpenCV

The Robotic Arm

The robot, before assembly (Photo by Author)

The robot arm arrived from AliExpress, it was without a specific brand, advertised as a DIY toy, which made it an affordable option, costing me only $118 (+$40 in tariffs). Since gripping objects with a robot arm requires a lot of precision, which I could not possibly expect from an arm in this price category, I decided to use a magnet to move the objects to the containers. I ordered one from Grove for $11, specifically designed for Raspberry Pi. It came with its own control electronics, so a GPIO (General Purpose Input/Output) pin could be used to turn it off and on. For the camera, I purchased a Pi NoIR Camera V2 for $45, which was also pretty easy to set up. To run my software and control all the above devices, I bought the latest version of the Raspberry Pi, which is the Raspberry Pi 4 Model B with 4 GB of RAM. I ordered it in a package, together with an SD card, housing, heat sinks, and power adapter, for $130. The hardware cost me $344 in total.

robotics deep-learning aws computer-vision raspberry-pi deep learning

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