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<p>The existing automated construction progress monitoring (ACPM) frameworks have many limitations and challenges that hinder industry-scale deployment and sustained real-world use, reported in the literature. This study aims to critically examine existing frameworks and methods, identifying their limitations and challenges, while proposing future research directions. A mixed-method review approach was employed, comprising a systematic literature review and bibliometric analysis, synthesizing data from 117 scholarly articles. This study also assessed the Technology Readiness Level (TRL) and Data Interoperability Maturity (DIM) levels of each selected framework to evaluate its potential capability for real-world application in the construction industry. Quantitatively, our TRL assessment of the representative frameworks shows that approximately 88% fall within TRL 5–7 (controlled-environment validation to arbitrary real-site demonstration), with only 18% reaching TRL 7, none reaching TRL 8–9 (industry-scale deployment), and 12% remaining at TRL ≤ 4.5 (early-stage prototypes); in parallel, about 82% of the reviewed frameworks operate at DIM levels 0–1, indicating that integration remains predominantly manual or file-based. Human–human inter-rater agreement on TRL ratings was near-perfect (quadratic-weighted κ = 0.82), and human–AI agreement was strong (Spearman’s ρ = 0.87; MAE = 0.29 TRL units), supporting the robustness of the reported maturity distribution. Our work reveals that several emerging constraints of those existing frameworks impede the scalable, end-to-end industry-scale deployment. These include highly segmented steps, noisy data, task-specific systems, binary progress reporting, site accessibility issues, and the lack of automated decision-making processes. Addressing these limitations through future research is essential for advancing and enabling end-to-end deployment in real projects. This study contributes a concise investigation to the existing body of knowledge, examining the challenges and assessment of the TRL and DIM levels of current ACPM frameworks that integrate Reality Capture Technology (RCT), BIM, Digital Twin (DT), image processing, and advanced computational tools to automate construction progress monitoring.</p>

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A Mixed Review and Technology Readiness Level (TRL) Evaluation of Automated Construction Progress Monitoring (ACPM) Frameworks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月24日

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  • Md Jewel Rana,
  • Hongtao Dang

摘要

The existing automated construction progress monitoring (ACPM) frameworks have many limitations and challenges that hinder industry-scale deployment and sustained real-world use, reported in the literature. This study aims to critically examine existing frameworks and methods, identifying their limitations and challenges, while proposing future research directions. A mixed-method review approach was employed, comprising a systematic literature review and bibliometric analysis, synthesizing data from 117 scholarly articles. This study also assessed the Technology Readiness Level (TRL) and Data Interoperability Maturity (DIM) levels of each selected framework to evaluate its potential capability for real-world application in the construction industry. Quantitatively, our TRL assessment of the representative frameworks shows that approximately 88% fall within TRL 5–7 (controlled-environment validation to arbitrary real-site demonstration), with only 18% reaching TRL 7, none reaching TRL 8–9 (industry-scale deployment), and 12% remaining at TRL ≤ 4.5 (early-stage prototypes); in parallel, about 82% of the reviewed frameworks operate at DIM levels 0–1, indicating that integration remains predominantly manual or file-based. Human–human inter-rater agreement on TRL ratings was near-perfect (quadratic-weighted κ = 0.82), and human–AI agreement was strong (Spearman’s ρ = 0.87; MAE = 0.29 TRL units), supporting the robustness of the reported maturity distribution. Our work reveals that several emerging constraints of those existing frameworks impede the scalable, end-to-end industry-scale deployment. These include highly segmented steps, noisy data, task-specific systems, binary progress reporting, site accessibility issues, and the lack of automated decision-making processes. Addressing these limitations through future research is essential for advancing and enabling end-to-end deployment in real projects. This study contributes a concise investigation to the existing body of knowledge, examining the challenges and assessment of the TRL and DIM levels of current ACPM frameworks that integrate Reality Capture Technology (RCT), BIM, Digital Twin (DT), image processing, and advanced computational tools to automate construction progress monitoring.