It can definitely be extended and scaled, because it is possible such functionality when the model can be trained by itself. But, it will require much more effort to do so, but yes it’s possible. For example, using AWS or Azure solutions, the device can update itself using new data and to make the prediction results more precise, or add extra functionality. This might require additional staff, for example to update Amazon Lambda. The algorithm consists of two parts. Lambda has the code written on Python,or node.js, which is then deployed from AWS to the board using Greengrass.
Lambda runs the machine learning model, and collects the prediction data from the sensor.
Lambda then passes this data to the model, and provides the prediction results to the web or video interface.
So in this type of case, additional staff would be needed to ensure the training is running properly and prediction results remain accurate.