  The damage and the impact of natural disasters are becoming more destructive
with the increase of urbanization. Today's metropolitan cities are not
sufficiently prepared for the pre and post-disaster situations. Digital Twin
technology can provide a solution. A virtual copy of the physical city could be
created by collecting data from sensors of the Internet of Things (IoT) devices
and stored on the cloud infrastructure. This virtual copy is kept current and
up to date with the continuous flow of the data coming from the sensors. We
propose a disaster management system utilizing machine learning called DT-DMS
is used to support decision-making mechanisms. This study aims to show how to
educate and prepare emergency center staff by simulating potential disaster
situations on the virtual copy. The event of a disaster will be simulated
allowing emergency center staff to make decisions and depicting the potential
outcomes of these decisions. A rescue operation after an earthquake is
simulated. Test results are promising and the simulation scope is planned to be
extended.
