Digital Twin Based Disaster Management System Proposal: DT-DMS
This addresses disaster preparedness for emergency center staff in metropolitan cities, but it is incremental as it applies existing Digital Twin technology to a new domain.
The paper tackles disaster management in urban areas by proposing a Digital Twin-based system (DT-DMS) that uses IoT data and machine learning to simulate disasters like earthquakes, with test results showing promise for training emergency staff.
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.