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<p>Unmanned aerial vehicle–based infrared thermography (UAV-IRT) has emerged as a promising approach for non-contact infrastructure inspection, enabling thermal diagnostics across large and difficult-to-access built-environment assets. At the same time, the Architecture, Engineering, Construction, and Facility Management (AEC/FM) industry is increasingly adopting digital technologies such as Building Information Modeling (BIM) and digital twins (DTs) to support data-driven asset management and lifecycle decision-making. However, thermal inspection outputs are often treated as isolated datasets rather than interoperable information linked with digital asset models, limiting their value for monitoring and predictive maintenance and constraining their integration into digital asset management workflows. This study presents a review of research at the intersection of UAV-IRT, BIM, and DT technologies. Based on a structured literature screening of 110 publications, this study covers UAV-enabled inspection, thermal data processing, multimodal sensing, and digital model integration. The review synthesizes research across four themes: UAV-IRT applications, thermal data processing and AI-assisted anomaly detection, BIM-based integration approaches, and digital-twin-enabled monitoring frameworks. The analysis reveals fragmentation across sensing, data processing, and integration workflows, highlighting key challenges that hinder scalable deployment in practical infrastructure inspection and management applications. The paper further discusses key directions for future research, including workflow standardization, multimodal sensing integration, AI-enabled decision support, scalable DT ecosystems, and workforce development. The findings demonstrate how UAV-IRT can support asset management by enabling proactive maintenance and improving inspection efficiency by reducing unnecessary inspection cycles and minimizing redundant field operations. These improvements lower resource consumption and operational costs while supporting more effective lifecycle management of infrastructure systems.</p>

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Integration of UAV-based infrared thermography with building information modeling and digital twins for infrastructure inspection: a review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月4日

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  • Ri Na,
  • Tianjiao Zhao

摘要

Unmanned aerial vehicle–based infrared thermography (UAV-IRT) has emerged as a promising approach for non-contact infrastructure inspection, enabling thermal diagnostics across large and difficult-to-access built-environment assets. At the same time, the Architecture, Engineering, Construction, and Facility Management (AEC/FM) industry is increasingly adopting digital technologies such as Building Information Modeling (BIM) and digital twins (DTs) to support data-driven asset management and lifecycle decision-making. However, thermal inspection outputs are often treated as isolated datasets rather than interoperable information linked with digital asset models, limiting their value for monitoring and predictive maintenance and constraining their integration into digital asset management workflows. This study presents a review of research at the intersection of UAV-IRT, BIM, and DT technologies. Based on a structured literature screening of 110 publications, this study covers UAV-enabled inspection, thermal data processing, multimodal sensing, and digital model integration. The review synthesizes research across four themes: UAV-IRT applications, thermal data processing and AI-assisted anomaly detection, BIM-based integration approaches, and digital-twin-enabled monitoring frameworks. The analysis reveals fragmentation across sensing, data processing, and integration workflows, highlighting key challenges that hinder scalable deployment in practical infrastructure inspection and management applications. The paper further discusses key directions for future research, including workflow standardization, multimodal sensing integration, AI-enabled decision support, scalable DT ecosystems, and workforce development. The findings demonstrate how UAV-IRT can support asset management by enabling proactive maintenance and improving inspection efficiency by reducing unnecessary inspection cycles and minimizing redundant field operations. These improvements lower resource consumption and operational costs while supporting more effective lifecycle management of infrastructure systems.