Multimodal data visualization method for digital twin campus construction

University campuses, as distinctive yet commonplace urban environments, face similar challenges of high population density and efficient management. Integrating digital twins into smart campus construction is essential for optimizing campus management. Multimodal data integration and visualization are key to building a digital twin campus. Traditional visualization methods often lack effective inter-data relationships, limiting their capacity to support robust multimodal data integration and create a multidimensional, real-time, comprehensive management view. Therefore, this paper proposes a tailored approach for multimodal data integration and visualization in digital twin campus construction. First, a comprehensive analysis of multimodal campus data identifies spatiotemporal associations among datasets. Subsequently, visualization strategies are developed based on these data characteristics and associations, enabling the multidimensional integration of 3D models, video surveillance, and wireless sensor data. Finally, a prototype system is implemented and evaluated through a case study. The results demonstrate that the proposed method efficiently integrates 2D maps, surveillance videos, and sensor data to create a dynamic, interactive, and panoramic campus view, achieving rendering efficiency exceeding 60 frames per second. Moreover, this adaptable framework can be applied to various campus or geographic contexts, offering critical technical support for multimodal visualization in IoT and big data environments.

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Publication Details

Journal
International Journal of Digital Earth
Published
2024-11-21
DOI
https://doi.org/10.1080/17538947.2024.2431624
Citations
5
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
2.45

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article

Multimodal data visualization method for digital twin campus construction

Zhihao Guo, Ni Zhan, Changjian Qiao, Qing Zhu et al.
5 citations
International Journal of Digital Earth
Impact of AI and Big Data on Business and Society
2.45
article

Multimodal data visualization method for digital twin campus construction

Zhihao Guo, Ni Zhan, Changjian Qiao, Qing Zhu, Yakun Xie, Jun Zhu, Junjie Zhan, Bingli Xu
article en
5 citations

Abstract

University campuses, as distinctive yet commonplace urban environments, face similar challenges of high population density and efficient management. Integrating digital twins into smart campus construction is essential for optimizing campus management. Multimodal data integration and visualization are key to building a digital twin campus. Traditional visualization methods often lack effective inter-data relationships, limiting their capacity to support robust multimodal data integration and create a multidimensional, real-time, comprehensive management view. Therefore, this paper proposes a tailored approach for multimodal data integration and visualization in digital twin campus construction. First, a comprehensive analysis of multimodal campus data identifies spatiotemporal associations among datasets. Subsequently, visualization strategies are developed based on these data characteristics and associations, enabling the multidimensional integration of 3D models, video surveillance, and wireless sensor data. Finally, a prototype system is implemented and evaluated through a case study. The results demonstrate that the proposed method efficiently integrates 2D maps, surveillance videos, and sensor data to create a dynamic, interactive, and panoramic campus view, achieving rendering efficiency exceeding 60 frames per second. Moreover, this adaptable framework can be applied to various campus or geographic contexts, offering critical technical support for multimodal visualization in IoT and big data environments.

International Journal of Digital EarthVol. 17(1)
Southwest Jiaotong University (CN), Henan University of Economic and Law (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Sichuan Province, National Postdoctoral Program for Innovative Talents, National Key Research and Development Program of China, Key Research and Development Program of Sichuan Province
Sustainable cities and communities
Openalex Percentile: Top 10%
Impact of AI and Big Data on Business and Society
2.45
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