Developing a Framework for Data-Driven Generation of Building Information Modeling from Sketches: Enhancing Efficiency in Space Configuration and Building Performance Analysis
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors The study seeks to develop a methodology that translates sketched, data-driven spatial requirements into 3D building components within BIM to enhance spatial comprehension and offer building performance analysis, assisting in budget considerations during the initial design stages. The following comments should be tackled beforce finally publicated by the journal. 1 The study should give enough description about the used deeplearning platform, framework, the hyperparameters, and etc, for the analysis model. 2 The comparison between the trational method of developing 3D buildings and the deep learning method should be conducted and given. 3 How to determine the sketch coordinate before using the deeplearning method. If the coordinate is given, why not directly develop 3D buildings using the commercial software or the BIM software. What is the big difference. Please comment. 4 The significance of the research should be further summarized. Comments on the Quality of English Language1 In the literature review, “[8] and [9] provided an environment that enables the review of circulation, floor and elevation plans, along with construction costs during the initial design phase.”
"[8] and [9]" should be corrected to be "The references [8] and [9]"
Similar problems should be reviewed throught the paper.
Author Response
Title: Developing a Framework for Data-Driven Generation of Building Information Modeling from Sketches: Enhancing Efficiency in Space Configuration and Building Performance Analysis
Journal: applied sciences
Section: Civil Engineering
Special Issue: Advances in BIM-Based Architecture and Civil Infrastructure Systems
Manuscript ID: applsci-2921294
Manuscript Type: Revised Article
Keywords: Building Information Modeling; Deep Learning; Sketched Data Retrieval; Building Performance Analysis; Cost Estimation
Corresponding Author: Dr. Sang-Guk Yum, Ph.D.
Corresponding Author’s Institution: Gangneung-Wonju National University, Korea
First Author: Dr. WoonSeong Jeong, Ph.D.
Second Author: ByungChan Kong
Order of Authors: WoonSeong Jeong, ByungChan Kong, Sang-Guk Yum
Responses to Review Comments
Dear Editor and Reviews,
We have compiled the review comments and addressed all of comments in the following list of responses. For each response, we have made related changes in the revised paper. We have provided the revised paper with tracked changes and numbered comments referring to the review comments. The revised and clean version of the paper is also submitted.
We greatly appreciate the review comments and would be glad to discuss any further issues with the editor and the reviewers.
Please, review the updated manuscripts including the cleaned version and track changed version.
Author Response File: 
Author Response.docx
Reviewer 2 Report
Comments and Suggestions for Authors1. the number of references is not very high - perhaps it would be worth adding something from Europe and America?
https://doi.org/10.1080/13658816.2016.1207775
https://doi.org/10.3390/architecture3030028
https://doi.org/10.5194/isprs-archives-XLII-1-W2-61-2019
https://doi.org/10.5194/isprs-archives-XLIV-4-W1-2020-19-2020
2. it would be good to add some numbers / results in the summary
3. line 247 - what is KRW? currency? this should be added in the text
4. drawings from Dynamo in table 2 are illegible
I think it would be useful to include the answers to the following questions in: the body of the manuscript if they relate to the analyses carried out, or in the summary if they relate to future research.
5. has the method been tested on multilevel sites? if not are there plans to do so?
6. was the level of accuracy/cartometric accuracy of the model checked against the sketch?
7. what about the other objects in the base model - windows, doors?
Author Response
Title: Developing a Framework for Data-Driven Generation of Building Information Modeling from Sketches: Enhancing Efficiency in Space Configuration and Building Performance Analysis
Journal: applied sciences
Section: Civil Engineering
Special Issue: Advances in BIM-Based Architecture and Civil Infrastructure Systems
Manuscript ID: applsci-2921294
Manuscript Type: Revised Article
Keywords: Building Information Modeling; Deep Learning; Sketched Data Retrieval; Building Performance Analysis; Cost Estimation
Corresponding Author: Dr. Sang-Guk Yum, Ph.D.
Corresponding Author’s Institution: Gangneung-Wonju National University, Korea
First Author: Dr. WoonSeong Jeong, Ph.D.
Second Author: ByungChan Kong
Order of Authors: WoonSeong Jeong, ByungChan Kong, Sang-Guk Yum
Responses to Review Comments
Dear Editor and Reviews,
We have compiled the review comments and addressed all of comments in the following list of responses. For each response, we have made related changes in the revised paper. We have provided the revised paper with tracked changes and numbered comments referring to the review comments. The revised and clean version of the paper is also submitted.
We greatly appreciate the review comments and would be glad to discuss any further issues with the editor and the reviewers.
Please, review the updated manuscripts including the cleaned version and track changed version.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsAll comments have been appropriatedly addressed and the quality of the paper has been significantly improved.
