Sensor-Driven Digital Twins for Bridge Infrastructure: A Critical Review of BIM-Enabled Integration, Monitoring Architectures, and Operational Maturity

Digital Twin (DT) research in civil infrastructure has expanded rapidly, yet its practical maturity in bridge engineering remains uneven. This review examines sensor-driven DT research in bridge infrastructure through a combined bibliometric and systematic approach, with particular emphasis on implementation logic and operational maturity. First, a broad bibliometric analysis was conducted to map the thematic directions, technological clusters, and infrastructure domains structuring DT research across civil infrastructure. Second, a bridge-specific systematic review of implemented and sensor-supported cases was performed to characterize their dominant application domains, technological components, integration logic, and maturity level. The broader civil-infrastructure literature is organized around structural monitoring, lifecycle information management, cyber–physical connectivity, AI-enabled analytics, and digital representation. By contrast, the bridge-specific literature narrows toward model-asset coupling, structural health monitoring, response-based interpretation, and implementation-oriented integration. Across the reviewed bridge cases, the most recurrent layers correspond to sensing, communication, digital representation, and analytical modelling, whereas the decisive features of robust operational twins, namely continuous or recurrent physical coupling, structured data fusion, effective update logic, and explicit decision-support use, remain less consistently implemented and documented. In this sense, the study provides a more discriminating maturity-oriented interpretation of current bridge DT research by connecting bibliometric evolution, architectural configuration, and bridge-specific implementation evidence.