Authors: P Dhivagar, Hindusthan College
Blending of Metaverse technology and Digital Twin simulation is an emerging way to revolutionize the management of catastrophe. Its integrated system is a cutting-edge platform for modeling scenarios and response to crisis using virtual representations of actual environments augmented with real-time data. Poor real-time data, reactive response times, and no interactivity simulations used for training as well as making decisions are barriers to conventional systems of disaster management. Particularly in mass disasters, these weaknesses undermine crisis management and preparation. Through the establishment of virtual environments that are analogous to real events, thereby enabling real-time crisis simulation and management, the suggested framework, Digital Twin Simulation Integrated with Metaverse for Crisis Scenario Modeling (MCSM), solves these problems. MCSM provides a live, interactive environment for disaster responders and decision-makers to collaborate and experiment with crisis scenarios using sensor-based real-time data, IoT devices, and satellite imagery. Not only does this virtual environment provide interactive capabilities, but it also makes way for predictive analysis for subsequent events, hence making decision-making more accurate. By exposing teams to a simulation-driven training exercise replicating most crisis situations in an actual but contained setting, MCSM prepares them better. It enhances resource management, coordination of emergency agencies, and decision-making for making crisis response plans. Early results show that the MCSM model shortens reaction times, improves overall preparedness of disaster management teams, and improves effectiveness of decision making. The capability to practice hard situations in the Metaverse results in improved performances in real-life crises, thereby transforming the field of catastrophe management..
Keywords: Metaverse, Digital Twin, Crisis Management, Disaster Response, Simulation, Scenario Modeling, Predictive Analysis.
Published in: 2024 Asian Conference on Communication and Networks (ASIANComNet)
Date of Publication: --
DOI: -
Publisher: IEEE