Metaverse air pollutant concentration inference model based on digital twin technology

Yifei PENG; Zhen YUAN; Xulong ZHANG; Guilin JIANG; Yujiang LIU

doi:10.11959/j.issn.2096-0271.2023005

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Metaverse air pollutant concentration inference model based on digital twin technology

TOPIC: METAVERSE AND BIG DATA | 更新时间：2024-06-05

- Metaverse air pollutant concentration inference model based on digital twin technology
- Big data research Vol. 9, Issue 1, Pages: 38-50(2023)
- 作者机构：
  
  1. 湖南财信数字科技有限公司，湖南长沙 410035
  2. 平安科技（深圳）有限公司，广东深圳 518063
  3. 湖南财信金融控股集团有限公司，湖南长沙 410035
  4. 墨尔本大学，澳大利亚墨尔本 3010
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2023005
  CLC： TP399
- Online First：2023-01，
  
  Published：15 January 2023
- 稿件说明：
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Yifei PENG, Zhen YUAN, Xulong ZHANG, et al. Metaverse air pollutant concentration inference model based on digital twin technology[J]. Big data research, 2023, 9(1): 38-50.
DOI：

Yifei PENG, Zhen YUAN, Xulong ZHANG, et al. Metaverse air pollutant concentration inference model based on digital twin technology[J]. Big data research, 2023, 9(1): 38-50. DOI： 10.11959/j.issn.2096-0271.2023005.

摘要

空气污染与人们的健康和经济社会的发展息息相关。然而，监测站点分布稀疏，无法提供细粒度的空气污染物浓度。此外，现有的空气污染物浓度推断方法缺乏实时处理相关数据的能力，具有滞后性。为了解决上述问题，提出了一种基于数字孪生技术的元宇宙空气污染物浓度推断模型。该模型将现实数据映射到元宇宙空间中，并构建数据仓库，通过构建空气污染物特征库实现对空气污染物浓度的实时精确推断。实验结果表明，该模型能提高空气污染物浓度推断的准确性和有效性。

Abstract

Air pollution is closely related to people's health and economic and social development.However

monitoring sites are sparsely distributed and cannot provide fine-grained air pollutant concentrations.In addition

the existing air pollutant concentration inference methods lack the ability to process relevant data in real time

so they have a hysteresis.To solve the above problems

a metaverse air pollutant concentration inference model based on digital twin technology was proposed.The model maped the real data into the metaverse space

and built a data warehouse to achieve real-time accurate inference of air pollutant concentrations through the construction of an air pollutant feature library.The experimental results show that the model can improve the accuracy and validity of air pollutant concentration inference.

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Keywords

references

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