A Suitable Scan-to-BIM Process Using OS Software and Low-Cost Sensors: Trend, Solutions and Experimental Validation

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents a well-structured Scan-to-BIM workflow based on low-cost sensors and open-source software, experimentally validated through a cultural heritage case study. The topic is timely and relevant for the AEC and HBIM communities, particularly in the context of democratizing 3D survey technologies and promoting openBIM approaches. The work is methodologically sound, well documented, and supported by an up-to-date literature review.

Overall, the paper demonstrates techhnical maturity and presents consistent results with the stated objectives. The comments below are considered important in order to improve clarity and focus.

• While the workflow is clearly described, the scientific contribution could be more explicitly articulated in the Introduction and Conclusions. In particular, I would suggest the authors to clarify what differentiates this workflow from previously published open-source Scan-to-BIM approaches.
• The comparison between COLMAP,Metashape, and TLS is appropriate, but the interpretation of the results could be slightly expanded. For instance, the practical implications of the reported mean devaitions (~12–18 cm) should be discussed in relation to the intended use cases (visualization, documentation, conceptual BIM). It would be useful to explicitly state whether these values satisfy the previously defined Level of Information Need.
• The case study is well chosen, but the conclusions could adopt a slightly more cautious tone regarding generalization. It is recommended to emphasize that the results are most directly applicable to buildings of similar scale and complexity. I think applications requiring higher geometric precision still benefit from TLS or commercial software solutions.
• Please ensure consistent use of terms such as Scan-to-BIM, Scan2BIM, open-source software, and OSS throughout the manuscript.
• Please verify final formatting consistency (URLs, access dates ).

Author Response

We sincerely thank the reviewer for the positive assessment of the manuscript’s structure, methodology, and relevance. The suggested revisions were carefully considered and addressed.

 

Comments 1: While the workflow is clearly described, the scientific contribution could be more explicitly articulated in the Introduction and Conclusions. In particular, I would suggest the authors to clarify what differentiates this workflow from previously published open-source Scan-to-BIM approaches.

 

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, we have added a paragraph at the end of Introduction part.

“While several Scan-to-BIM studies have explored either open-source photogrammetry, low-cost sensing, or BIM modeling independently, fewer works address the full Scan-to-BIM pipeline in an integrated and standards-aware manner. The scientific contribution of this research lies in proposing an end-to-end, cost-effective Scan-to-BIM workflow that combines low-cost SLAM-based acquisition, open-source photogrammetry (COLMAP), and openBIM modeling tools (BlenderBIM/IfcOpenShell) within a single reproducible framework. Unlike many existing open-source approaches that focus on isolated processing stages or purely experimental pipelines, the proposed method explicitly links data acquisition, verification, and BIM modeling to ISO 19650 principles and ISO 7817 Level of Information Need (LIN). Furthermore, the workflow is experimentally validated through a direct comparison with terrestrial laser scanning (TLS) and commercial photogrammetry software under identical case-study conditions, enabling a transparent assessment of accuracy, limitations, and applicability for different BIM use cases.”.

And a paragraph was added in Conclusion Part:

“The results of this study demonstrate that open-source software combined with low-cost sensing technologies can support effective Scan-to-BIM workflows for visualization-oriented documentation and conceptual BIM applications. However, the findings are most directly applicable to buildings of similar scale, geometry, and complexity to the presented case study. Applications requiring higher geometric precision, such as conservation-grade HBIM or structural analysis, continue to benefit from terrestrial laser scanning and commercial software solutions. The proposed workflow should therefore be regarded as a complementary, rather than substitutive, approach within the broader Scan-to-BIM ecosystem”, After: “Recent studies further confirm this trend, showing how open-source BIM ecosystems underpin new scan-to-BIM workflows and standards-compliant digital construction platforms, making advanced BIM-based processes more accessible and interoperable for the construction industry as a whole [47, 48]”.

 

Comments 2: The comparison between COLMAP, Metashape, and TLS is appropriate, but the interpretation of the results could be slightly expanded. For instance, the practical implications of the reported mean devaitions (~12–18 cm) should be discussed in relation to the intended use cases (visualization, documentation, conceptual BIM). It would be useful to explicitly state whether these values satisfy the previously defined Level of Information Need.

Response 2: We added a paragraph after Figure 14 in the result section:

“The observed mean deviations between the photogrammetry-derived point clouds and the TLS reference dataset indicate the expected geometric fidelity achievable with low-cost sensors and open-source processing pipelines. Specifically, the COLMAP point cloud exhibited a mean deviation of approximately 18 cm, whereas the Metashape dense reconstruction achieved around 12 cm. These results reflect the trade-off between accessibility, affordability, and geometric precision. When evaluated against the predefined Level of Information Need (LIN), these deviation values are sufficient for visualization-oriented documentation, conceptual BIM, and early-stage heritage documentation, where decametric accuracy is acceptable. However, they do not meet the stricter tolerances required for structural analysis or conservation-grade modeling.”

And Also in Discussion Part, a paragraph was added after Figure 18:

“The reported deviations (~12–18 cm) have direct implications for the intended BIM applications. For 3D visualization and dissemination, these deviations are within acceptable limits, allowing the accurate representation of overall building morphology and key architectural elements. For conceptual BIM or volumetric documentation, the deviations are also consistent with ISO 7817 defined Levels of Information Need, ensuring that the resulting models can support early-stage design decisions and heritage asset assessments. Nevertheless, applications requiring high geometric precision would require TLS or higher-end commercial photogrammetry to meet stricter accuracy thresholds. These observations highlight the importance of aligning the chosen data acquisition method with the specific Level of Information Need for each Scan-to-BIM use case.”

 

Comments 3: The case study is well chosen, but the conclusions could adopt a slightly more cautious tone regarding generalization. It is recommended to emphasize that the results are most directly applicable to buildings of similar scale and complexity. I think applications requiring higher geometric precision still benefit from TLS or commercial software solutions.

 

Response 3: The Conclusions have been revised to emphasize that the findings are most directly applicable to buildings of comparable scale, geometry, and complexity, and that applications demanding higher metric reliability still benefit from TLS or commercial solutions.

A paragraph was added in the conclusion part: “Though the proposed low-cost, open-source Scan-to-BIM workflow demonstrated reliable results for the case study presented, these findings should not be generalized to all building types or scales. The workflow is most directly applicable to buildings of moderate scale and architectural complexity, similar to the studied historic manor. Applications requiring higher geometric precision, such as detailed conservation, structural analysis, or high-fidelity HBIM, remain better served by terrestrial laser scanning (TLS) or commercial photogrammetry and BIM software. This cautious framing ensures that the suitability of the workflow is aligned with the intended Level of Information Need and the specific use case.”

 

Comments 4: Please ensure consistent use of terms such as Scan-to-BIM, Scan2BIM, open-source software, and OSS throughout the manuscript.

 

Response 4: The entire manuscript was reviewed to ensure consistent terminology usage throughout all sections.

 

Comments 5: Please verify final formatting consistency (URLs, access dates).

 

Response 5: All URLs, access dates, and formatting issues were checked and standardized according to the journal guidelines.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript addresses an increasingly relevant topic in the AEC sector, the feasibility of combining low cost sensors with open source software for Scan-to-BIM workflows. The subject is timely, and the authors present a well-structured paper with a clear methodological pipeline, a useful state of the art overview, and illustrative figures supporting the experimental process.

However, the study presents important limitations related to the precision of the generated data, the lack of clearly defined information requirements, the absence of quantitative validation for the SLAM data, and a misalignment between the stated objective of “documentation” and the level of precision achieved. As a result, some of the conclusions are not fully supported by the presented results, particularly those concerning the suitability of open-source workflows for documentation purposes.

Some improvements are needed before the manuscript can be considered for publication.

• The manuscript does not justify the selection of the case study building. Although it is described as a historic structure, the criteria for its choice and its relevance to evaluating the proposed Scan-to-BIM workflow are not explained. It would be helpful to explain and describe the characteristics of the case study in more detail.
• The authors state that the model is intended for “documentation and dissemination,” yet no explicit how the level of accuracy are defined. Documentation, especially in heritage contexts, requires clearly stated metric reliability, which is missing. Is the model intended solely for 3D visualization purposes? If so, that needs to be made clearer.
• Although the manuscript includes data acquisition using a SLAM-based system, it does not present any quantitative accuracy metrics or summary reports for the SLAM-generated point cloud. No deviation analysis, error statistics, or validation against the TLS reference are provided, which limits the assessment of the SLAM data quality. Is it possible to access this data?
• The manuscript would benefit from a final comparative table summarizing the key quantitative results of each acquisition method. Such a table could include, for each dataset (TLS, SLAM, open-source photogrammetry, and commercial photogrammetry), the reported accuracy metrics, deviation values, and main limitations. This comparison would improve clarity, allow easier interpretation of the results, and help readers better assess the suitability of each approach for different Scan-to-BIM use cases.
• Although the study focuses exclusively on the building exterior, this is not made explicit in the methodology. There is no data or modeling of the interior spaces, nor discussion of why the analysis was limited to the exterior.
• The manuscript presents the input data and final BIM models but does not discuss the practical modeling experience. No information is provided regarding modeling time, encountered challenges, operator expertise, workflow bottlenecks, or the impact of point cloud quality on modeling efficiency.

Author Response

We thank the reviewer for the detailed and constructive critique, which significantly contributed to strengthening the methodological rigor and interpretative clarity of the manuscript.

 

Comments 1: The manuscript does not justify the selection of the case study building. Although it is described as a historic structure, the criteria for its choice and its relevance to evaluating the proposed Scan-to-BIM workflow are not explained. It would be helpful to explain and describe the characteristics of the case study in more detail.

 

Response 1:

The main objective of the study was to compare different spatial data sources and to perform a qualitative assessment of data acquired using low-cost sensors and open-source software through their confrontation with commercial solutions and high-accuracy reference equipment. For this reason, a case study building with a moderate level of geometric complexity was deliberately selected, while still requiring experience and technical skills in survey planning and data acquisition.

The building is characterized by numerous structural elements, portions located at significant heights, and isolated hard-to-access areas, allowing the evaluation of data acquisition capabilities under constrained conditions, as well as the presence of architectural details and decorative elements. This combination enables a detailed assessment of data quality, 3D reconstruction capability, and BIM object generation, and allows a controlled comparison between terrestrial laser scanning (TLS) and low-cost mobile laser scanning (MLS) technologies.

Furthermore, the building is publicly accessible and does not present significant measurement constraints, which helped minimize external variables unrelated to the tested acquisition methods.

A paragraph was added in Case study Section: “The case study building was selected to enable a structured comparison of spatial data acquired using low-cost sensors and open-source software with commercial solutions and high-accuracy reference data. A building with a moderate level of geometric complexity was chosen to ensure that the proposed Scan-to-BIM process could be evaluated under realistic conditions without introducing excessive geometric or operational constraints. The building includes multiple structural elements, portions located at significant heights, and isolated hard-to-access areas, allowing the assessment of data acquisition and reconstruction capabilities using low-cost and open-source solutions. The analysis was limited to the exterior of the building, including all façades and the roof, as the study focuses on validating Scan-to-BIM workflows for exterior documentation rather than interior modeling.” After: “The research presented below the is focused on a series of measurements using SLAM technology, TLS technology, and Close-Range Photogrammetry, conducted on a building, the former manor palace in Mydlniki (Kraków, Poland).”

 

Comments 2: The authors state that the model is intended for “documentation and dissemination,” yet no explicit how the level of accuracy are defined. Documentation, especially in heritage contexts, requires clearly stated metric reliability, which is missing. Is the model intended solely for 3D visualization purposes? If so, that needs to be made clearer.

 

Response 2:

We agree that, in the original version of the manuscript, the scope and intended use of the generated models were not stated with sufficient clarity, which may have inadvertently suggested a focus on cultural heritage or monument documentation. The manuscript has therefore been revised to explicitly clarify this aspect. The models developed in this study are intended primarily for 3D visualization and as BIM models serving as carriers of comprehensive and coherent information about existing buildings. The objective of the work is not the documentation of cultural heritage assets or heritage-grade modeling, but rather the evaluation of low-cost data sources and open-source software within Scan-to-BIM workflows for existing buildings, regardless of their heritage status. The core objective was to assess whether data acquired using low-cost sensors and processed with open-source tools can produce BIM models that are qualitatively usable in practice, in terms of completeness, information consistency, and interpretability, and to determine to what extent, in which contexts, and for which applications such models can approach those generated using costly commercial hardware and software solutions.

Throughout the study, efforts were made to achieve the highest possible metric accuracy attainable with low-cost technologies, which in practice corresponds to centimetric-level accuracy. However, the primary evaluation criteria were data completeness, information coherence, and the ability to interpret point clouds and generate consistent BIM models, rather than accuracy requirements specific to conservation-oriented or engineering-grade documentation.

A paragraph was added before section 6.3: “The reported deviations (~12–18 cm) have direct implications for the intended BIM applications. For 3D visualization and dissemination, these deviations are within acceptable limits, allowing the accurate representation of overall building morphology and key architectural elements. For conceptual BIM or volumetric documentation, the deviations are also consistent with ISO 7817: 2024 defined Levels of Information Need, ensuring that the resulting models can support early-stage design decisions and herit-age asset assessments. Nevertheless, applications requiring high geometric precision would require TLS or higher-end commercial photogrammetry to meet stricter accu-racy thresholds. These observations highlight the importance of aligning the chosen data acquisition method with the specific Level of Information Need for each Scan-to-BIM use case.”.

Also, in conclusion Part: “The results of this study demonstrate that open-source software combined with low-cost sensing technologies can support effective Scan-to-BIM workflows for visu-alization-oriented documentation and conceptual BIM applications. However, the findings are most directly applicable to buildings of similar scale, geometry, and com-plexity to the presented case study. Applications requiring higher geometric precision, such as conservation-grade HBIM or structural analysis, continue to benefit from ter-restrial laser scanning and commercial software solutions. The proposed workflow should therefore be regarded as a complementary, rather than substitutive, approach within the broader Scan-to-BIM ecosystem.”.

 

Comments 3: Although the manuscript includes data acquisition using a SLAM-based system, it does not present any quantitative accuracy metrics or summary reports for the SLAM-generated point cloud. No deviation analysis, error statistics, or validation against the TLS reference are provided, which limits the assessment of the SLAM data quality. Is it possible to access this data?

 

Response 3:

We agree that in the original version of the manuscript the quantitative information regarding the quality and accuracy of the SLAM-derived data was not presented with sufficient clarity. In the revised version, this limitation has been addressed by extending the description of the accuracy of the employed MLS system and by adding a visual deviation analysis with respect to the TLS reference data.

In this study, the SLAM data were used as a low-cost input source to assess the feasibility of the Scan-to-BIM process, rather than as a reference dataset intended for a full, global validation of geometric accuracy. Due to the nature of SLAM-based systems (particularly their dependence on trajectory estimation and acquisition conditions) a complete quantitative comparison with TLS data without additional geodetic control may lead to ambiguous results.

To complement the assessment of SLAM data quality, a cloud-to-cloud (C2C) analysis between the MLS point cloud and the TLS reference cloud has been added to the manuscript, including deviation maps and a histogram of absolute distances. This analysis serves a supportive role, enabling a qualitative evaluation of the geometric consistency of the SLAM data and the identification of areas with increased discrepancies.

 

A Paragraph was added after Figure 4: “The MLS system based on the Livox Mid-360 sensor provides dense point clouds with centimetric accuracy under typical operating conditions. The sensor is characterized by a ranging error ≤ 0.02 m @ 10 m (down to 0.02 m @ 0.2 m) and an angular error ≤ 0.15°, with a typical output rate of ap-proximately 200,000 points per second at 10 Hz. [45, 46]. Laboratory tests comparing the MandEye MLS system with a Leica P40 TLS reference demonstrated geometric agreement at the 10–15 mm level for cylindrical features and edges, below 10 mm for planar surfaces, and mean absolute reg-istration errors of approximately 0.013 m in static mode and 0.017 m in dynamic acquisition. These results confirm that the MLS sensor head itself delivers stable centimetric accuracy suitable for low-cost Scan-to-BIM workflows [45,46]. Figure 5 shows the result of Cloud to Cloud between MLS to TLS (reference) and histogram distribution of sound values. MLS-TLS data consistency is at the level of single centimeters. In extreme cases, it's at the decimeter level, but this is for noise points and measurement heads that aren't buildings.”

 

Also, Figure 5 was added to explain this data.

 

Figure 5. Distance MLS to TLS (reference) + histogram of value

 

Data: https://drive.google.com/drive/folders/1g05duki4q8yXbnrC5dHlIw3nJHX50wKl?usp=sharing

 

Comments 4: The manuscript would benefit from a final comparative table summarizing the key quantitative results of each acquisition method. Such a table could include, for each dataset (TLS, SLAM, open-source photogrammetry, and commercial photogrammetry), the reported accuracy metrics, deviation values, and main limitations. This comparison would improve clarity, allow easier interpretation of the results, and help readers better assess the suitability of each approach for different Scan-to-BIM use cases.

 

Response 4:

We agree that a final comparative table summarizing the quantitative results of the different acquisition methods significantly improves the clarity and interpretability of the manuscript. In the revised version, a comprehensive comparison table has been added to summarize the key quantitative accuracy metrics, deviation values, and main limitations of all investigated datasets, including TLS, SLAM-based MLS, open-source photogrammetry, and commercial photogrammetry. TLS delivers the most accurate and detailed building representation, with high-density data suitable as a reference for precise BIM modeling. SLAM-based MLS enables rapid data acquisition and reliable modeling of main structural elements but lacks detail for small features and decorations. Photogrammetry provides comprehensive coverage and good overall accuracy, especially for hard-to-access areas, though it also struggles with fine details. TLS is ideal for detailed BIM, MLS for fast conceptual workflows, and photogrammetry for complete exterior documentation and general geometry.

 

A final comparative table has been added before DISCUSSION section to summarize the key quantitative results of all acquisition methods (TLS, SLAM, open-source photogrammetry, and commercial photogrammetry). The table reports deviation values with respect to TLS, achieved accuracy levels, and main strengths and limitations, improving clarity and supporting the assessment of method suitability for different Scan-to-BIM use cases.

 

 

Table 3. Comparative summary of acquisition methods used in the study, including accuracy metrics, deviation from TLS reference, and applicability for Scan-to-BIM workflows.

Acquisition Method	Sensor / Software	Deviation with Respect to TLS	Accuracy Level	Main Advantages	Main Limitations
TLS	Leica ScanStation P40 / Cyclone	Reference dataset	Millimetric (registration error ≈ 0.004 m)	High geometric accuracy and point density; stable and reliable reference	High acquisition and processing costs; longer survey time
SLAM-based MLS	MandEye (Livox Mid-360) / HDMapping	≈ 0.01–0.02 m locally; centimetric at building scale	Centimetric	Rapid acquisition; portability; cost-effective solution	Drift effects in feature-poor areas; reduced detail compared to TLS
Open-source Photogrammetry	COLMAP	Mean deviation ≈ 0.18 m	Decametric	Fully open-source; transparent workflow; low financial cost	Lower geometric accuracy; higher noise; requires careful parameter tuning
Commercial Photogrammetry	Agisoft Metashape	Mean deviation ≈ 0.12 m	High-centimetric	Higher level of automation; improved point cloud density	License cost; limited transparency of processing algorithms

 

 

 

Comments 5: Although the study focuses exclusively on the building exterior, this is not made explicit in the methodology. There is no data or modeling of the interior spaces, nor discussion of why the analysis was limited to the exterior.

 

Response 5:

We agree that in the original version of the manuscript it was not stated with sufficient clarity that the scope of the study is limited exclusively to the exterior of the building. In the revised version, the methodology has been updated to explicitly indicate that the proposed Scan-to-BIM workflow and its experimental validation focus solely on exterior data acquisition and modeling.

 

The exterior-only scope was deliberately adopted to ensure comparable acquisition conditions across TLS, SLAM-based MLS, and photogrammetric methods, and to enable a reliable comparison between low-cost, open-source, and commercial solutions. Interior modeling was not included, as it requires different acquisition strategies and dedicated sensor configurations, and involves specific constraints (e.g., limited applicability of UAVs and photogrammetry), which would significantly broaden the scope of the study.

 

Nevertheless, the reviewer’s comment is highly valuable and has been identified as an important direction for future research. Interior-focused investigations allow for a much higher level of geometric detail but would require a dedicated methodological framework and introduce additional variables beyond the main objective of this work, which is the comparative analysis of sensors, point clouds, and BIM models for exterior building documentation.

 

Comments 6: The manuscript presents the input data and final BIM models but does not discuss the practical modeling experience. No information is provided regarding modeling time, encountered challenges, operator expertise, workflow bottlenecks, or the impact of point cloud quality on modeling efficiency.

 

Response 6:

We acknowledge that the manuscript does not provide a detailed discussion of practical BIM modeling aspects such as modeling time or individual operator skills. This was, however, a deliberate methodological choice, aligned with the primary objective of the study.

 

The main goal of the paper is to compare data sources, point cloud acquisition technologies, and resulting BIM models, and to assess the applicability of low-cost sensors and open-source software within Scan-to-BIM workflows. A detailed discussion of individual modeling skills or software-specific workflow nuances could obscure this objective and introduce user-dependent variability into the comparison.

 

To address the practical dimension without shifting the focus of the study, a comparative table summarizing the main limitations and characteristics of the different point cloud datasets and acquisition technologies has been added to the revised manuscript. This table highlights how data quality and technological constraints influence BIM model generation, directly supporting the comparative nature of the study.

 

All modeling tasks were performed by an experienced operator in order to minimize the influence of human factors and ensure that the observed differences primarily reflect variations in data sources, technologies, and software environments. This approach allows a clearer assessment of whether low-cost sensors and open-source tools can generate BIM models that are practically usable, even if their capabilities differ from those of commercial solutions.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

This paper presents a novel and solid study on converting scanned 3D data into sophisticated BIM models. The authors provide a comprehensive literature review, incorporating suitable and state-of-the-art recent papers and research models proposed by other researchers, and they summarize systematic technological trends in this area.

A few minor revisions are suggested:

• Line 58: This paragraph would benefit from a clear topic sentence to introduce and guide the content.
• Line 104: Please add a citation for “ISO 19650-1.”
• Tables 1 and 2: Adjust the font size and layout so that each table fits within a single page.
• Line 155: Please provide citations for “ISO 19650” and “ISO 7817,” respectively.
• Figure 1: Improve the image resolution and increase the font size for better readability.
• Line 190: Please add a citation for “ISO 7817:2024.”
• Line 198: Please add a citation for “ISO 19650.”
• Line 201: For “TLS,” please spell out the full term at its first occurrence.
• Line 220: “Euro [datcap.eu]”—please clarify whether this is a reference or a notation.
• Figure 17: If the images are reproduced or adapted from other sources, please add the appropriate references.

Author Response

We sincerely thank the reviewer for the positive assessment of the manuscript’s structure, methodology, and relevance. The suggested revisions were carefully considered and addressed.

 

Comments 1: Line 58: This paragraph would benefit from a clear topic sentence to introduce and guide the content.

 

Response 1: A clear topic sentence was added as:

“Recent advances in deep learning have enabled fully automated semantic segmentation of BIM elements directly from point cloud data”. Perez-Perez et al. (2021) [10] propose an innovative end-to-end deep learning framework.

 

Comments 2: Line 104: Please add a citation for “ISO 19650-1.”.

 

Response 2: The reference to ISO 19650-1 has been added to the manuscript. The standard is now included in the reference list as: International Organization for Standardization (ISO). ISO 19650-1:2018. Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM) (Information management using building information modelling) Part 1: Concepts and principles; ISO: Geneva, Switzerland, 2018.

 

Comments 3: Tables 1 and 2: Adjust the font size and layout so that each table fits within a single page.

 

Response 3: Tables 1 and 2 were reformatted to fit within a single page with improved layout and font size.

 

Comments 4: Line 155: Please provide citations for “ISO 19650” and “ISO 7817,” respectively.

 

Response 4: Citations to ISO 19650 and ISO 7817 have been added at the indicated locations in the manuscript. Both standards are now included in the reference list as: International Organization for Standardization (ISO). ISO 19650. Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM); ISO: Geneva, Switzerland, 2018 and International Organization for Standardization (ISO). ISO 7817:2024. Information management (Level of information need) Concepts and principles; ISO: Geneva, Switzerland, 2024.

 

Comments 5: Figure 1: Improve the image resolution and increase the font size for better readability.

 

Response 5:

Figure 1 was Improved with high resolution

 

Comments 6: Line 190: Please add a citation for “ISO 7817:2024.”

 

Response 6: The reference to ISO 7817:2024 has been added to the manuscript. The standard is now included in the reference list as: International Organization for Standardization (ISO). ISO 7817:2024. Information management (Level of information need) Concepts and principles; ISO: Geneva, Switzerland, 2024.

 

Comments 7: Line 198: Please add a citation for “ISO 19650.”

 

Response 7: The reference to ISO 19650 has been added to the manuscript. The standard is now included in the reference list as: International Organization for Standardization (ISO). ISO 19650. Organization and digitization of information about buildings and civil engineering works, including building information modelling (BIM); ISO: Geneva, Switzerland, 2018.

 

Comments 8: Line 201: For “TLS,” please spell out the full term at its first occurrence.

 

Response 8: The acronym TLS is now spelled out at its first occurrence. It was modified as:

In contrast, RBM employs active sensors that deliver a highly detailed and precise representation of a three-dimensional object or structure [7]. A notable example of an active sensor is the Terrestrial Laser Scanner (TLS).

 

Comments 9: Line 220: “Euro [datcap.eu]”—please clarify whether this is a reference or a notation.

 

Response 9: The reference to Euro [datcap.eu] was clarified as a price notation and source. It was modified as:

“The cost of this solution is approximately 5,000 Euro according to the vendor’s official website [datcap.eu]”

 

Comments 10: Figure 17: If the images are reproduced or adapted from other sources, please add the appropriate references.

 

Response 10: Figure 17 is entirely based on our own analysis and was generated by the authors specifically for this study using Microsoft Excel. The images were not reproduced or adapted from external sources; therefore, no additional references are required.

 

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

I'd like to congratulate the authors on the quality of the article and the research developed.
All the points I raised in the first review were addressed by the authors and incorporated into the article.

Author Response

We sincerely thank the Reviewer for the positive evaluation of our work and for the constructive comments provided during the first review round. We are pleased that all raised points have been adequately addressed and incorporated into the revised manuscript. The Reviewer’s feedback significantly contributed to improving the quality and clarity of the article.