Metaverse air pollutant concentration inference model based on digital twin technology

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.

Keywords

• air pollution;digital twin;metaverse