Design of metaverse platform framework for smart sewage plants based on digital twin technology

MA Xingguan; MA Yongyang; LIU Jiao; MA Huan

doi:10.13205/j.hjgc.202508025

Volume 43 Issue 8

Aug. 2025

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2025 > 43(8): 270-279

MA Xingguan, MA Yongyang, LIU Jiao, MA Huan. Design of metaverse platform framework for smart sewage plants based on digital twin technology[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(8): 270-279. doi: 10.13205/j.hjgc.202508025

Citation:

MA Xingguan, MA Yongyang, LIU Jiao, MA Huan. Design of metaverse platform framework for smart sewage plants based on digital twin technology[J]. ENVIRONMENTAL ENGINEERING , 2025, 43(8): 270-279. doi: 10.13205/j.hjgc.202508025

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Design of metaverse platform framework for smart sewage plants based on digital twin technology

doi: 10.13205/j.hjgc.202508025

MA Xingguan^1,2,
MA Yongyang^{1
,
,},
LIU Jiao¹,
MA Huan¹

1. School of Municipal and Environmental Engineering, Shenyang Jianzhu University, Shenyang 110168, China;
2. Liaoning Province Liaohe River Basin Water pollution Prevention and Control Research Institute, Shenyang 110168, China

Received Date: 2025-04-19
Accepted Date: 2025-06-06
Rev Recd Date: 2025-05-27

Abstract

Abstract

To synchronously integrate digital twin and virtual reality （VR） technologies into the operation and construction of sewage treatment plants （STPs） and realize the highly intelligent development of STPs， a metaverse system for smart STPs supported by digital twin technology was constructed， and the optimal scheme for integrating virtual-physical interaction technology with smart STPs was explored. Specific implementation approaches are proposed as follows： a multi-modal architecture was adopted to develop digital twin models， a virtual interaction system， and the weighted regularized extreme learning machine （WRELM） deep learning mechanism. On the one hand， this integration serves for fully automated operation monitoring of STPs and the analysis and simulation of wastewater treatment data； on the other hand， it supports immersive virtual-physical interaction and intelligent operation of STPs. By comparing the applicability of various deep learning models in the platform， the WRELM was selected to establish an incremental learning mechanism for the metaverse platform， thereby achieving an optimal configuration of processes and unit parameters in wastewater treatment. This platform enables real-time monitoring， simulation， and immersive virtual-physical interaction of STPs. It not only effectively ensures the efficient and energy-saving operation of the wastewater treatment process， but also realizes intelligent data analysis， process digital twinning， autonomous virtual roaming， and automated fault handling in wastewater treatment.
- sewage plant,
- digital twin,
- metaverse,
- virtual-real interactive,
- WRELM

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References(17)

References

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