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.
翻译:随着城市化的加剧,自然灾害的破坏和影响越来越具有破坏性。今天的都市城市没有为灾前和灾后情况做好充分的准备。数字双星技术可以提供解决方案。通过从Tings(IoT)装置的互联网传感器收集数据,并储存在云层基础设施上,可以创建一个虚拟城市的复制件。这个虚拟复制件随着传感器数据的持续流动而不断更新并不断更新。我们建议使用称为DT-DMS的机器学习来支持决策机制的灾害管理系统。本研究的目的是展示如何通过模拟虚拟版本的潜在灾害情况来教育和培养应急中心工作人员。将模拟灾害事件,使应急中心工作人员能够做出决策并描述这些决定的潜在结果。模拟地震后救援行动。试验结果很有希望,并计划扩大模拟范围。