Today's vehicle has lots of sensors generating lots of different data which if captured could be used for vehicle monitoring, predictive analytics, finding anomalies and taking corrective actions as needed either locally, remotely or in self-healing manner.
In this demo, we will stream data for many cars into the system, each car sending one event per sec or more. We will use BangDB agent to stream the data into BangDB, and use streaming analysis for these events with 1 day as sliding window length (continuous window).
Further we will use BangDB ML abstractions to train two models, one using existing file and other on data which have been streamed into the database. These models will help us find certain anomalies for further action.