Summary
In this chapter, we learned how you can use AI to analyze video captured by cameras, to detect objects that potentially represent obstacles for drivers. This was implemented to run at the edge on a Raspberry Pi, using the power of Kubernetes with K3s. With this approach, we created a decoupled system that could be easier to upgrade using containers. We also learned how this kind of system can be used in real-world scenarios to monitor traffic behavior to improve driver safety. Across this implementation, we also learned how this kind of system is distributed across the edge and the cloud to process and show information locally to drivers to improve their driving experience. In the last chapter, we are going to give an easy method to organize and design fast your own edge computing system using a diagram called the edge computing design system canvas.
