IoT needs automated, hardware-based, localized machine learning for wider deployment and usage

Imagine a complex plant or machinery being equipped with all kinds of sensors to monitor and control its performance and to predict potential points of failure. Such plants can range from an oil rig out in the ocean to an automated production line. Or such complex plants can be human beings, perhaps millions of them, who are being monitored with a variety of devices in a hospital or at home. Although we can use some standard models to monitor and compare performance of these physical systems, it would make more sense to either rebuild these models from scratch or adjust them to individual situations. This would be similar to what we do in economics.