Computational BIM and Intelligent Operations

Developing campus digital twin using interactive visual analytics approach

Xinyue Ye, Suphanut Jamonnak, Shannon Van Zandt, Galen Newman, Patrick Suermann

Published 2025

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📄 Paper
Digital Twins (DTs) are increasingly recognized for their potential to improve efficiency and decision-making in various domains of the built environment. Despite their promise, challenges like cost, complexity, interoperability, and data integration remain. This paper introduces a novel interactive visual analytics system that tackles these issues, using a case study of simulating class distribution and campus building capacity at a large public university. The system leverages enrollment data, converting it into a spatial-temporal format for interactive exploration and analysis of class distribution and resource utilization. Through case studies, we demonstrate the system's effectiveness, adaptability, and real-world applicability, highlighting its role in practical DT implementation for built environments.

Abstract

Digital Twins (DTs) are increasingly recognized for their potential to improve efficiency and decision-making in various domains of the built environment. Despite their promise, challenges like cost, complexity, interoperability, and data integration remain. This paper introduces a novel interactive visual analytics system that tackles these issues, using a case study of simulating class distribution and campus building capacity at a large public university. The system leverages enrollment data, converting it into a spatial-temporal format for interactive exploration and analysis of class distribution and resource utilization. Through case studies, we demonstrate the system's effectiveness, adaptability, and real-world applicability, highlighting its role in practical DT implementation for built environments.

Topics

AI occupancy modelingBIMCase StudyOccupant Behavior Analysis and Spatial OptimizationPredictive Analytics and Performance OptimizationQuality Control and Validationanomaly detectionbehavior modelingbig data in buildingsbuilding energy forecastingdata qualitydesign automationdigital twinsmodel checkingmovement analysisoccupant behaviorpredictive analyticssensor-driven designspace utilizationspatial analyticstime-series analysis

Cite this paper

@article{87d78b4a, title={Developing campus digital twin using interactive visual analytics approach}, volume={2}, ISSN={2731-6661}, url={https://link.springer.com/10.1007/s44243-024-00033-2}, DOI={10.1007/s44243-024-00033-2},
abstract={Digital Twins (DTs) are increasingly recognized for their potential to improve efficiency and decision-making in various domains of the built environment. Despite their promise, challenges like cost, complexity, interoperability, and data integration remain. This paper introduces a novel interactive visual analytics system that tackles these issues, using a case study of simulating class distribution and campus building capacity at a large public university. The system leverages enrollment data, converting it into a spatial-temporal format for interactive exploration and analysis of class distribution and resource utilization. Through case studies, we demonstrate the system’s effectiveness, adaptability, and real-world applicability, highlighting its role in practical DT implementation for built environments.}, number={1}, journal={Frontiers of Urban and Rural Planning}, author={Ye, Xinyue and Jamonnak, Suphanut and Van Zandt, Shannon and Newman, Galen and Suermann, Patrick}, year={2024}, month={apr}, pages={9}, language={en} }