Digital Twin-Assisted Anomaly Detection for Smarter Built Environment Management: A Literature Review

Improving the reliability and efficiency of anomaly detection is important for establishing and maintaining a resilient built environment. Meanwhile, Digital Twins (DT) have attracted increasing attention in the built environment management. In this study, through a structured literature review, we compiled and categorized existing DT-assisted anomaly detection methods applied in built environment based on three anomaly detection criteria (scope, target, approach) and three key attributes of DT (integration level, fidelity level, and decision speed). In doing so, we presented the current research trends and analyzed how DTs contribute to the built environment management with different anomaly detection approaches. This study lays the foundation for establishing DT-assisted anomaly detection frameworks utilizing Digital Twins of different integration and fidelity levels to tackle anomaly detection problems with different approaches. Moreover, it shows the efficacy of Digital Shadows (one directional DTs) in built environment anomaly detection and calls for future research endeavors in high-integration-level DT applications and DT-assisted hybrid anomaly detection methods.