Virtual Reality Simulation of Earthquake Response of Buildings Using AI

Main Article Content

Ankit Negi

Abstract

Virtual Reality Simulation of Earthquake Response of Buildings using AI is an innovative approach to designing and evaluating the structural performance of buildings during earthquakes. The simulation is based on AI technology, which provides a realistic and immersive experience of earthquake scenarios in a virtual environment. The goal is to understand the behaviour of buildings during an earthquake and identify potential weaknesses in the structure to improve the building's resilience. The VR simulation is designed to identify the physical behaviour of buildings during earthquakes, including their response to ground shaking, vibration, and deformation. The AI algorithms enable the simulation to react in real-time to the user's input and the dynamic response of the building. The simulation generates a visual and audio output that accurately represents the scenario, providing an immersive experience to the user.


The simulation can be used to assess the performance of existing buildings and provide feedback on their resilience to earthquakes. It can also be used in the design and construction of new buildings to identify and mitigate potential risks. The AI algorithms can analyse the data generated by the simulation to provide insights into the building's structural behaviour and suggest improvements. Virtual Reality Simulation of Earthquake Response of Buildings Using AI is a cutting-edge technology that has the potential to revolutionise the way we design and evaluate buildings for earthquake resilience. It provides a safe and cost-effective way to study the behaviour of buildings during earthquakes, which can save lives and prevent property damage in earthquake-prone areas.

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Article Details

How to Cite
Negi, A. . (2018). Virtual Reality Simulation of Earthquake Response of Buildings Using AI. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 9(2), 496–507. https://doi.org/10.17762/turcomat.v9i2.13854
Section
Research Articles