  A digital twin (DT) monitors states of the physical twin (PT) counterpart and
provides a number of benefits such as advanced visualizations, fault detection
capabilities, and reduced maintenance cost. It is the ability to be able to
detect the states inside the DT that enable such benefits. In order to estimate
the desired states of a PT, we propose the use of a Kalman Filter (KF). In this
tutorial, we provide an introduction and detailed derivation of the KF. We
demonstrate the use of KF to monitor and anomaly detection through an incubator
system. Our experimental result shows that KF successfully can detect the
anomaly during monitoring.
