Construction projects are characterized by long cycles, numerous stakeholders, and constantly shifting site conditions. Managers need current information on progress, safety, and resource use. Traditional methods fall short in meeting these demands. Data acquisition is slow, multi-source integration is weak, and real-time status updating rarely happens. Digital twin (DT) technology links physical engineering assets to digital models and field data. This linkage provides a way to monitor and manage construction processes dynamically. This paper adopts a literature synthesis approach combined with representative case analysis to examine the technical foundations of DT in construction projects. The work summarizes principal applications from three angles: construction progress monitoring, construction safety control, and construction resource coordination. Existing applications show that DT can link building information modeling (BIM) models, sensor data, unmanned aerial vehicle (UAV) imagery, and equipment operation data to actual site conditions. This supports progress deviation identification, safety risk assessment, and resource utilization monitoring. Notably, different scenarios impose different requirements on data types, collection frequency, and model updating methods. Practical applications also face constraints. Data quality, system integration, implementation cost, and continuous model updating are all critical factors. DT in construction projects must be configured to specific management demands and site conditions. Only then does it enhance practical applicability in construction management.
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Juntao Wang (2026) studied this question.
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