• Title/Summary/Keyword: 코로나19 바이러스

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A Study on Metaverse Construction Based on 3D Spatial Information of Convergence Sensors using Unreal Engine 5 (언리얼 엔진 5를 활용한 융복합센서의 3D 공간정보기반 메타버스 구축 연구)

  • Oh, Seong-Jong;Kim, Dal-Joo;Lee, Yong-Chang
    • Journal of Cadastre & Land InformatiX
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    • v.52 no.2
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    • pp.171-187
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    • 2022
  • Recently, the demand and development for non-face-to-face services are rapidly progressing due to the pandemic caused by the COVID-19, and attention is focused on the metaverse at the center. Entering the era of the 4th industrial revolution, Metaverse, which means a world beyond virtual and reality, combines various sensing technologies and 3D reconstruction technologies to provide various information and services to users easily and quickly. In particular, due to the miniaturization and economic increase of convergence sensors such as unmanned aerial vehicle(UAV) capable of high-resolution imaging and high-precision LiDAR(Light Detection and Ranging) sensors, research on digital-Twin is actively underway to create and simulate real-life twins. In addition, Game engines in the field of computer graphics are developing into metaverse engines by expanding strong 3D graphics reconstuction and simulation based on dynamic operations. This study constructed a mirror-world type metaverse that reflects real-world coordinate-based reality using Unreal Engine 5, a recently announced metaverse engine, with accurate 3D spatial information data of convergence sensors based on unmanned aerial system(UAS) and LiDAR. and then, spatial information contents and simulations for users were produced based on various public data to verify the accuracy of reconstruction, and through this, it was possible to confirm the construction of a more realistic and highly utilizable metaverse. In addition, when constructing a metaverse that users can intuitively and easily access through the unreal engine, various contents utilization and effectiveness could be confirmed through coordinate-based 3D spatial information with high reproducibility.