Whether you want to create smart insurance contracts, know how long your belongings have traveled, by what means of transport or if they have suffered any shocks, you can now develop embedded machine learning models with breathtaking precision.
Before the arrival of machine learning, recognition and classification of movements were very hard and time-consuming tasks for embedded developers. It was necessary to go through complex decision-tree algorithms based on the activation of specific thresholds at different time intervals. Now it is a completely different story, we can create custom solutions with only a small amount of data in a record time. We will see how to do that with Edge Impulse and the Generic Node.