A Construction-Phase Digital Twin Framework for Quality Assurance and Decision Support in Civil Infrastructure Projects
The system integrates sensor data and predictive models for real-time quality decisions on bridges and highways.
Deep Dive
Researchers Md Asiful Islam and three colleagues propose a construction-phase digital twin framework for civil infrastructure. It links inspection records, material data, early-age sensing, and predictive strength models to individual elements. By integrating these data streams, the system enables real-time quality assessments and structured release/hold decisions weeks before standard lab tests are available, supplementing existing workflows to reduce rework risk and schedule impacts on large projects.
Why It Matters
Could transform construction from reactive, document-heavy QA to proactive, data-driven decision-making, saving time and costs.