Development of a 3D Digital Model of End-of-Service-Life Buildings for Improved Demolition Waste Management through Automated Demolition Waste Audit

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study predicts the amount of waste from demolished buildings using a 3D model. Current research results should indicate how reliable waste prediction is using 3D models.

It is considered inefficient (low economic feasibility) to apply this technology to small buildings with a total floor area of ​​three stories or less. I'm curious about the author's thoughts.

Is it used to create a demolition scenario when dismantling a building?

Or are you creating a 3D model to predict the amount of waste discharged from buildings?

I am curious about the application and utilization of the results of this study. I think it would be good to mention something about usability in the conclusion.

Author Response

We would like to thank the reviewer for constructive suggestions. Our point to point replies are presented below, with changes to the paper highlighted.

 

This study predicts the amount of waste from demolished buildings using a 3D model. Current research results should indicate how reliable waste prediction is using 3D models.

Authors’ reply:

Currently, there is no application of 3D model in demolition waste prediction, which motivated our research. Therefore, it is not feasible to indicate reliability of waste prediction using 3D models.

As clarification, we have added the following sentences in the introduction of the paper.

As a consequence of the above problems, prediction of demolition waste is grossly inaccurate and contamination of CDWs makes downstream activities of waste identification and sorting very difficult.

 

The most effective way to resolve the above-mentioned problems is to develop a digital platform for construction waste management. Theoretically, precise identification of the location of construction materials has the potential to accurately predict the amount of different streams of demolition waste. However, since the 3D model described in this paper is the first step of this development, the results of the complete digital platform will only be known after implementation in practice.

 

It is considered inefficient (low economic feasibility) to apply this technology to small buildings with a total floor area of ​​three stories or less. I'm curious about the author's thoughts.

Authors’ reply:

The reviewer is correct. We have added the following sentence in the paper for clarification:

It should be pointed out that even though the case study focuses on a small footprint of the building, the method developed in this paper is intended to be easily scalable. Nevertheless, in some cases when the building is small, using this technology may not be necessary. This is at the discretion of the user.

Is it used to create a demolition scenario when dismantling a building?

Authors’ reply:

Yes the model to facilitate improved demolition scenario when dismantling a building. We have added the following paragraph to provide further clarification.

In order to create a demolition scenario (pre-demolition planning), the first step is to carry out an audit of the potential demolition waste. The 3D model will provide all the necessary information to facilitate efficient and systematic identification and examination of different streams of demolition waste to enable automated creation of a demolition scenario.

Or are you creating a 3D model to predict the amount of waste discharged from buildings?

Authors’ reply:

Predicting waste discharge is one output of the 3D model. We have added the following sentence for clarification.

Depending on the pre-demolition plan, some materials may be reused and thus are taken out of waste stream, while others are discharged as construction demolition waste. Not only is the 3D model able to predict their amounts, but it is also able to facilitate a demolition plan that allows the discharged waste to be better identified and separated to minimise contamination and hence to benefit downstream waste management activities.

I am curious about the application and utilization of the results of this study. I think it would be good to mention something about usability in the conclusion.

Authors’ reply: We have added the following paragraph in the paper.

Furthermore, the 3D model of this paper has been developed with usability in mind. However, this paper has only presented the methodology of the 3D model. Application of the 3D model to real buildings will be demonstrated as part of the entire Horizon Europe project RECONMATIC. The results and lessons learned from the demonstrator will be reported in due course.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This is an interesting paper. The proposed digital approach looks promising, the methodology is detailed, the description of the George Building provides a good basis for understanding the context of the study, The 3D digital model correction method is well written. In general, it is a good paper which can be published. I just have some comments below:

1) Although the title is descriptive, it could be simplified to be more impactful and memorable.

2) Although the introduction presents the construction waste problem in detail, it could be more concise.

3) Certain aspects of the statistics presented could be clarified for better understanding, in particular by providing specific references for the figures presented.

4) The proposed digital approach looks promising, but it could be more clearly articulated to explain how it specifically addresses construction waste management challenges.

5) The challenges mentioned in creating the digital model from paper drawings could be further explored to better understand the practical implications and potential obstacles.

6) Although the methodology is detailed, it could be more structured to facilitate understanding, perhaps using subheadings to organize the different stages of the process.

7) The case study is a strong element of the first part of the article, but it could benefit from a more critical analysis of the results obtained and lessons learned.

8) The description of the George Building provides a good basis for understanding the context of the study. However, it might be useful to include additional information on the size and current use of the building to further contextualize the importance of digital modeling.

9) The methodology would be helpful to provide more details on the accuracy and reliability of each step, especially regarding the automation of the conversion process and the necessary manual adjustments.

10) It might be useful to discuss the potential limitations of this methodology, particularly regarding the variability of input data and resulting modeling errors.

11) The 3D digital model correction method is well written, but it requires close human supervision to identify and correct errors.

12) The part about managing IFC files and uploading them to web applications seems too technical and may be difficult to follow for readers who are not familiar with these concepts. It would have been helpful to include simpler explanations or concrete examples to make the content more accessible.

 

Author Response

This is an interesting paper. The proposed digital approach looks promising, the methodology is detailed, the description of the George Building provides a good basis for understanding the context of the study, The 3D digital model correction method is well written. In general, it is a good paper which can be published. I just have some comments below:

We thank the reviewer for encouragement. Our point to point replies are presented below including highlighted changes to the paper.

1) Although the title is descriptive, it could be simplified to be more impactful and memorable.

Authors’ reply: we have revised the title of the paper to be:

Development of a 3D Digital Model of End of Service Life Buildings for Improved Demolition Waste Management through Automated Demolition Waste Audit

2) Although the introduction presents the construction waste problem in detail, it could be more concise.

Authors’ reply: we have now made the introduction much more concise by removing detailed descriptions of the various tasks in the different steps of waste management process. This has shortened the section to be about half of the original version of the paper.

3) Certain aspects of the statistics presented could be clarified for better understanding, in particular by providing specific references for the figures presented.

Authors’ reply: we have now added references to support the statistics.

4) The proposed digital approach looks promising, but it could be more clearly articulated to explain how it specifically addresses construction waste management challenges.

Authors’ reply: our original introduction was too long, as pointed out by the reviewer in comment 2. After making the introduction section much more concise, we believe the construction waste management challenges are now clear, and hence how the digital approach would overcome these challenges, as summarised in the following new paragraphs.

The above features of the construction industry lead to fragmentation, a lack of close cooperation among different stakeholders, a lack of consideration on how to minimise CDWs during the whole life cycle of buildings and infrastructure among some of the stakeholders, reliance on personal knowledge and manually operated processes, conflicting demands and slow processes of manually dealing with different requirements of different stakeholders. As a result, the current practice of conducting a pre-demolition audit is time-consuming and inefficient, with ineffective data capture [18]. There is little transparency of the project. It is difficult to evaluate retrospectively for effectiveness because inadequate project documentation makes it challenging for designers to easily incorporate audit results. There is also no standardised and normalized pre-demolition audit methodology, and different regions and countries may apply different techniques [19, 20]. Depending on the knowledge of the pre-demolition team, the demolition decision-making process and results are different. It is inevitable that the end results of current construction waste management are suboptimal [21].

 

As a consequence of the above problems, prediction of demolition waste is grossly inaccurate and the contamination of CDWs makes downstream activities of waste identification and sorting very difficult.

 

Only an integrated digital platform can overcome the above challenges of construction waste management. Theoretically, precise identification of the location of construction materials has the potential to accurately predict the amount of different streams of demolition waste. However, since the 3D model described in this paper is the first step of this development, the results of the complete digital platform will only be known after implementation in practice.

5) The challenges mentioned in creating the digital model from paper drawings could be further explored to better understand the practical implications and potential obstacles.

Authors’ reply: we have now added a more detailed critical literature review of obstacles in creating digital models from paper drawings, and their practical implications in influencing how we have decided our alternative approach.

However, for various reasons, these existing developments are not suitable to the requirement of the digital platform of this research.

One of the key problems of converting paper-based drawings to digital CAD is recognition of many geometric patterns and symbols in drawings and associate them with building objects, and in understanding text attributes to identify the object’s material, element type, and locational information. Because both sets of data are required to completely draw the digital CAD of an object with properties, the process of distinguishing them as separated layers takes priority [32, 33]. Multiple text and line extraction methods by using heuristic rules to separate data in one image from another are proposed [34], but the application of these method is difficult when line drawings and text overlap or touch each other.

Another approach is to use geometric features and symbols to identify building components. Line segments, being the most common features in 2D building drawings, have been employed to identify walls [35, 36, 37], columns [38], and rooms [39]. Symbols have also been used to detect grid lines, enabling further identification of building elements such as columns, beams, and walls [40, 41]. However, with multiple meanings of some symbols and possible lack of completeness of drawing features and text (e.g. due to damages), this method is prone to false matches. Furthermore, these methods are not suitable for building components with irregular shapes.

With rapid advancement of artificial intelligence (AI), there has been a substantial increase in the application of AI in drawing analysis using Convolution Neural Networks [42, 43]. However, this is still at the early stage of fundamental research and development. Not only does this require advanced expertise and sophisticated supporting tools, the scale of any application is severely limited.

The limited progress in development from paper-based drawing to digital CAD is a result of the existing research investigations aiming to develop the digital CAD of an existing building or its components to the high level of quality and complexity of the CAD as if for new design of the building.

The aim of converting from paper-based drawing to CAD for pre-demolition audit is different from that of the above-mentioned existing research studies. The level of details required for the above developments far surpasses that is required for the purpose of this research, for which simplicity of use and large scale application are essential but the need for precision in many details is modest.

An alternative approach is possible. In this alternative approach, a professional’s ability to quickly understand and identify the important information in paper drawings is combined with computer’s raw power to process information. In this way, human intervention eliminates the need to deal with different drawing conventions, damaged drawings, recognition of symbols and text, so that computer processing can be done quickly to convert paper-based drawing to digital CAD. Although the authors have not fully implemented this approach, section 4.3 of this paper will present the preliminary work by the authors to demonstrate feasibility of this approach.

6) Although the methodology is detailed, it could be more structured to facilitate understanding, perhaps using subheadings to organize the different stages of the process.

Authors’ reply: we have now added a short paragraph to signpost the main sections, as well as using detailed subheadings to show logical organisation of the different stages of the process.

Figure 5 summarises the four main steps of developing a faithful 3D digital model. These steps will be described in detail in Sections 4.3 (step 1 and step 2), 4.4 (step 3), 4.5 (step 4) with section 4.6 providing a critical review of the process and outcomes.

7) The case study is a strong element of the first part of the article, but it could benefit from a more critical analysis of the results obtained and lessons learned.

Authors’ reply: we have now added a new section.

4.6 Critical Review of the Process and Outcomes

The key to development of the 3D digital model of this paper is to take advantage of a small amount of human intervention to solve numerous problems associated with automatic recognition of information by computer. This is mainly manifested in digital location of structural members during the paper drawing to CAD conversion process and in correcting mistakes in the 3D digital model.

For the former, notable challenges in the process of creating a digital CAD from paper-based drawings are the extraction of coordinates of different structural members, the sensitivity of their dimensions to the thickness of lines drawn for them, and the inadequacy of using lines (or other simple shapes such as rectangles) to communicate complex details (such as profiled steel section size). This will be solved by creating an option to input the information in a text box on screen, next to the image showing locations of the structural members for easy referencing. This step is being implemented and the results of this development will be further evaluated.

For the latter, the authors have developed the correction process (which is inevitable due to changes in the lifetime of the building) to ensure that any human intervention is intuitive and minimal. One particular problem with quick measurement of distances is lack of precision, even with inclusion of an intelligent snapping algorithm in the model. Fortunately, for demolition purpose, this lack of precision is generally inconsequential because this would not affect identification of the waste stream and would at most only cause a few percentages in error in prediction of the amount of waste. Nevertheless, this digital model has the potential to be expanded to be very accurate for applications where detailed information is necessary, for example in structural strengthening or refurbishment. This will be the next phase of development of the digital model.

8) The description of the George Building provides a good basis for understanding the context of the study. However, it might be useful to include additional information on the size and current use of the building to further contextualize the importance of digital modeling.

Authors’ reply: we have added the following paragraph.

Figure 3 shows the entrance to the George Begg Building of the University of Manchester, UK. It was built in 1974. It is a 2-storey academic building, consisting of offices, lecture theatres, laboratory, student workspaces, computer labs etc.  The structure of the building is mainly reinforced concrete. There are many non-loadbearing members, including many types of internal walls, doors and windows. Whilst the structural member grids are regular, the internal space layout is highly irregular.

9) The methodology would be helpful to provide more details on the accuracy and reliability of each step, especially regarding the automation of the conversion process and the necessary manual adjustments

Authors’ reply: as we have mentioned in a number of paces in the paper (e.g. in our reply to comment 7), we are not able at this stage to provide details on the accuracy and reliability of each step without applying the model in practice. Although this is part of the overall RECONMATIC project, we will only be able to provide such details afterwards.

10) It might be useful to discuss the potential limitations of this methodology, particularly regarding the variability of input data and resulting modelling errors.

Authors’ reply: as we have indicated above, we are unable to provide details before we have applied the digital model in practice. Nevertheless, we have added the following paragraph to describe potential limitations.

It is important to mention that the effectiveness of the digital model depends on the model having the correct material and product/element information for pre-demolition plan, e.g. with regard to material/product reuse, and on correct extraction of the information for pre-demolition audit. At this stage, the RECONMATIC project team is still defining the required material/product information. However, whatever the required material/product information, this paper has demonstrated that they are correctly extracted in the digital model described in this paper. 

11) The 3D digital model correction method is well written, but it requires close human supervision to identify and correct errors.

Authors’ reply: as we have explained, this step is inevitable. However, we have developed the model so that human supervision is intuitive and minimal. Please see our reply to comment 7.

12) The part about managing IFC files and uploading them to web applications seems too technical and may be difficult to follow for readers who are not familiar with these concepts. It would have been helpful to include simpler explanations or concrete examples to make the content more accessible.

Authors’ reply: the paragraph is intended to describe the programming aspect. We have revised the paragraph to make the explanation more easily understandable by non-specialists.

The first step in the pre-demolition audit process involves the user uploading a 3D digital model that must use the Industry Foundation Classes (IFC) format [46] for outputting material and product information of the building. From the user perspective, this task is simple: a menu will appear in the platform´s interface and the user will select the 3D digital model to be uploaded. However, from the programmer perspective, correct transfer of data is critical, which is achieved by ensuring compatibility of data between the 3D digital model uploaded by the user with web application. To address this challenge, the IFC.js library is used, which is an advanced tool designed to interpret and translate IFC files (as outputted by the user’s 3D model) into a format that can be efficiently managed and displayed in web environments.

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

REVIEW

on article

Development of a 3D Digital Model Combining Augmented Reality

and Paper Based Drawing for End of Service Life Buildings

to Enable Automated Waste Audit

 

Muhammad Omer, Yong C. Wang 1, Mikel Quintana Roma, Stanislav Bedrich, Vaclav Nezerka, Juan Ferriz-Papi, Jesus J. Moros Montanes  and Ines Diez Ortiz

 

SUMMARY

The article submitted for review is relevant and addresses an environmentally important topic, namely the development of a digital 3D model combining augmented reality and paper drawings for end-of-life buildings to enable automated waste auditing.

The authors presented a new platform for developing a digital 3D model of end-of-life buildings based on paper drawings in preparation, automatically combining artificial intelligence, computer-aided design, and augmented reality.

The authors obtained several important new insights that can maximize the value of construction waste through the reuse of elements and the recovery of recycled materials. This is all possible by accurately identifying the types of materials and quantities of construction waste to improve the sorting and classification of demolition waste. The reviewer believes that the study as a whole has an interesting design. The idea of the article is well presented. It has scientific novelty, and the article is consistent with the focus of the journal Environments. The reviewer is generally quite positive about this article, but believes that a number of important points need to be corrected to make the article better. Notes are provided below.

COMMENTS

1. The authors are advised to shorten the title somewhat; it looks too long. It should be noted that authors worked on a 3D model that combines augmented reality and paper drawings to improve the environment. Then the title of the article will be more consistent with the theme of the Environments magazine.

2. It is recommended to supplement the Abstract with a scientific problem formulated in accordance with the problems of the journal “Environments”. For example, that there is currently a lack of scientifically based theories and applied solutions related to digital models combining various mechanisms and tools, such as CAD and artificial intelligence. The authors did not indicate the quantitative expression of the result in their abstract. They reported that their digital model would facilitate waste management decisions. However, this conclusion is not specific. It is necessary to show what specific quantitative result was obtained. For example, how much faster the decision-making process will be. There must be specific numbers.

3. Authors are encouraged to supplement keywords with environmental terms.

4. The presented literature review looks very crumpled. It contains only 6 references to scientific literature and Section 1 does not seem to correspond to the scientific level of the journal. It needs to be enlarged and a detailed analysis of the current state of the waste management issue presented using various digital and other models.

5. Sections 2 and 3 look very rich, but lack a flowchart for conducting the study. Authors need to visualize their idea and methodology. Too much text slightly reduces the value of the engineering value of the article. You need to work with flowcharts and work out the structure of the article. In principle, the authors do this in the fourth section. I recommend the authors to bring this also in the second and third sections.

6. Figures 2 and 3 are of poor quality. Please, improve their quality and check all figures for the journal requirements (1000 pix for the short side and 300 DPI resolution).

6. I recommend the authors to place a discussion of the results obtained in a separate section. In the Discussion section, the authors should present a detailed comparison of your results with the results of other authors.

7. The conclusions are presented in a way that is difficult to understand. They need to be numbered and arranged in the following order: scientific novelty, practical significance, prospects for the development of research in the future, and recommendations for specific applied cases.

8. The list of references contains 26 titles. It's unexpected that such a widely discussed topic as waste management and digital models has so few resources available. This list needs to be expanded to include 35-40 titles.

 

In general, the article needs more careful proofreading, correction of the English language and correction of the presentation style. 

Comments on the Quality of English Language

Moderate editing of English language required. I recommend the authors to improve English.

Author Response

REVIEW

on article

Development of a 3D Digital Model Combining Augmented Reality

and Paper Based Drawing for End of Service Life Buildings

to Enable Automated Waste Audit

 

Muhammad Omer, Yong C. Wang, Mikel Quintana Roma, Stanislav Bedrich, Vaclav Nezerka, Juan Ferriz-Papi, Jesus J. Moros Montanes  and Ines Diez Ortiz

 

SUMMARY

The article submitted for review is relevant and addresses an environmentally important topic, namely the development of a digital 3D model combining augmented reality and paper drawings for end-of-life buildings to enable automated waste auditing.

The authors presented a new platform for developing a digital 3D model of end-of-life buildings based on paper drawings in preparation, automatically combining artificial intelligence, computer-aided design, and augmented reality.

The authors obtained several important new insights that can maximize the value of construction waste through the reuse of elements and the recovery of recycled materials. This is all possible by accurately identifying the types of materials and quantities of construction waste to improve the sorting and classification of demolition waste. The reviewer believes that the study as a whole has an interesting design. The idea of the article is well presented. It has scientific novelty, and the article is consistent with the focus of the journal Environments. The reviewer is generally quite positive about this article, but believes that a number of important points need to be corrected to make the article better. Notes are provided below.

 

We thank the reviewer for encouragement and for constructive comments. Our detailed point to point replies are presented below, including revision of the paper as highlighted.

 

COMMENTS

1. The authors are advised to shorten the title somewhat; it looks too long. It should be noted that authors worked on a 3D model that combines augmented reality and paper drawings to improve the environment. Then the title of the article will be more consistent with the theme of the Environments magazine.

 

Authors’ reply: We have changed the title to Development of a 3D Digital Model of End of Service Life Buildings for Improved Demolition Waste Management through Automated Pre-Demolition Waste Audit

 

 

2. 2. It is recommended to supplement the Abstract with a scientific problem formulated in accordance with the problems of the journal “Environments”. For example, that there is currently a lack of scientifically based theories and applied solutions related to digital models combining various mechanisms and tools, such as CAD and artificial intelligence. The authors did not indicate the quantitative expression of the result in their abstract. They reported that their digital model would facilitate waste management decisions. However, this conclusion is not specific. It is necessary to show what specific quantitative result was obtained. For example, how much faster the decision-making process will be. There must be specific numbers.

 

Authors’ reply: at this stage, our 3D digital model has not been applied in practice. Therefore, it is not feasible for us to provide quantitative information about improvements that could result from using our 3D digital model. However, due to many existing problems with current demolition processes, we expect a step change in the improvement of demolition practice by applying our digital model. Therefore, we have revised the abstract to reformulate the scientific problem in terms of model development, and have identified specific problems of current demolition practice that could be eliminated by the application of our model.

 

This paper presents the development of a 3D digital model of end of service life buildings to facilitate a step change in preparation of pre-demolition protocols that can eliminate problems of inadequate documentation and extensive time spent in preparing pre-demolition audits. The 3D digital model consists of the following four main components: (i) digitization of paper-based drawings and its conversion to CAD; (ii) automated generation of a 3D digital model from CAD; (iii) corrections to the 3D digital model to account for changes in the lifetime of a building; (iv) a sub-model for performing pre-demolition audit. This paper proposes innovative approaches of incorporating a minimal amount of human intervention to overcome numerous difficulties in automated drawing analysis, application of Augmented Reality (AR) in corrections to the 3D digital model, and data compatibility for pre-demolition audit. These processes are demonstrated using one building as case study. Using the digital model, a pre-demolition audit can be prepared in minutes, rather than many days in current practice without a digital model. The accurate quantification of the quantities and locations of different demolition waste materials and products in buildings to be demolished will enable a systematic and quantitative evaluation of potentials of material and product reuse, and eliminate contamination of different demolition waste streams (which may contain hazardous waste) which is the main cause of environmental degradation and downcycling of demolition waste materials.

 

3. Authors are encouraged to supplement keywords with environmental terms.

 

Authors’ reply: we have added the following two additional keywords with environmental terms:

 

Circular economy, Sustainable demolition

 

4. The presented literature review looks very crumpled. It contains only 6 references to scientific literature and Section 1 does not seem to correspond to the scientific level of the journal. It needs to be enlarged and a detailed analysis of the current state of the waste management issue presented using various digital and other models.

 

Authors’ reply: We have added many more references to the scientific literature in section 2, and cited them in our critical review of the related topics including current state of waste management, and challenges related to development of digital models.

 

We have also made section 1 of the paper more concise to be consistent with the high quality of a scientific journal paper.

 

Additional text in literature review:

 

On current state of waste management:

In the traditional approach of construction demolition waste management, a large number of stakeholders are involved [12] including the property owner, the contractor, the national administration (building authority), the auditor, the waste manager, the products manufacturer, the designer/consultant planning the demolition or renovation works, and the designer/consultant planning new buildings or infrastructures.

In the entire demolition waste management cycle, there are many work items associated with several stages of the process, as summarised in Figure 1. The different aforementioned stakeholders may be engaged at different stages of the process.

 

Fig 1. Summary of a waste audit process [13]

Throughout the different stages of the process, a large amount of data and information should be collected. They include the age of the building or infrastructure; design documents; documentation of use; a list of hazardous substance; agressiveness of the surrounding area; location, volulme, quantity and waste code of materials; details of construction elements (e.g. structural loadbearing members such as columns, beams, walls, slabs and non-loadbearing elements such as floor coverings, lighting units, interior walls, false ceilings) in a systematic manner (e.g. on a room by room basis on different floors, or the total amount of the different types of materials and their current quality [14, 15]); non-destructive and destructive test results on samples of materials and construction elements [16, 17].

The above features of the construction industry lead to fragmentation, a lack of close cooperation among different stakeholders, a lack of consideration on how to minimise CDWs during the whole life cycle of buildings and infrastructure among some of the stakeholders, reliance on personal knowledge and manually operated processes, conflicting demands and slow processes of manually dealing with different requirements of different stakeholders. As a result, the current practice of conducting a pre-demolition audit is time-consuming and inefficient, with ineffective data capture [18]. There is little transparency of the project. It is difficult to evaluate retrospectively for effectiveness because inadequate project documentation makes it challenging for designers to easily incorporate audit results. There is also no standardised and normalized pre-demolition audit methodology, and different regions and countries may apply different techniques [19, 20]. Depending on the knowledge of the pre-demolition team, the demolition decision-making process and results are different. It is inevitable that the end results of current construction waste management are suboptimal [21].

As a consequence of the above problems, prediction of demolition waste is grossly inaccurate and the contamination of CDWs makes downstream activities of waste identification and sorting very difficult.

Only an integrated digital platform can overcome the above challenges of construction waste management. Theoretically, precise identification of the location of construction materials has the potential to accurately predict the amount of different streams of demolition waste. However, since the 3D model described in this paper is the first step of this development, the results of the complete digital platform will only be known after implementation in practice.

On creating digital models:

However, for various reasons, these existing developments are not suitable to the requirement of the digital platform of this research.

One of the key problems of converting paper-based drawings to digital CAD is recognition of many geometric patterns and symbols in drawings and associate them with building objects, and in understanding text attributes to identify the object’s material, element type, and locational information. Because both sets of data are required to completely draw the digital CAD of an object with properties, the process of distinguishing them as separated layers takes priority [32, 33]. Multiple text and line extraction methods by using heuristic rules to separate data in one image from another are proposed [34], but the application of these method is difficult when line drawings and text overlap or touch each other.

Another approach is to use geometric features and symbols to identify building components. Line segments, being the most common features in 2D building drawings, have been employed to identify walls [35, 36, 37], columns [38], and rooms [39]. Symbols have also been used to detect grid lines, enabling further identification of building elements such as columns, beams, and walls [40, 41]. However, with multiple meanings of some symbols and possible lack of completeness of drawing features and text (e.g. due to damages), this method is prone to false matches. Furthermore, these methods are not suitable for building components with irregular shapes.

With rapid advancement of artificial intelligence (AI), there has been a substantial increase in the application of AI in drawing analysis using Convolution Neural Networks [42, 43]. However, this is still at the early stage of fundamental research and development. Not only does this require advanced expertise and sophisticated supporting tools, the scale of any application is severely limited.

The limited progress in development from paper-based drawing to digital CAD is a result of the existing research investigations aiming to develop the digital CAD of an existing building or its components to the high level of quality and complexity of the CAD as if for new design of the building.

The aim of converting from paper-based drawing to CAD for pre-demolition audit is different from that of the above-mentioned existing research studies. The level of details required for the above developments far surpasses that is required for the purpose of this research, for which simplicity of use and large scale application are essential but the need for precision in many details is modest.

 

5. Sections 2 and 3 look very rich, but lack a flowchart for conducting the study. Authors need to visualize their idea and methodology. Too much text slightly reduces the value of the engineering value of the article. You need to work with flowcharts and work out the structure of the article. In principle, the authors do this in the fourth section. I recommend the authors to bring this also in the second and third sections.

 

Authors’ reply: we have now added section and sub-section headings in Section 2. We have also included a short paragraph to signpost the main sub-sections, as well as using detailed subheadings to show logical organisation of the different stages of the process in the two content-rich sections (4 & 5).

Figure 5 summarises the four main steps of developing a faithful 3D digital model. These steps will be described in detail in Sections 4.3 (step 1 and step 2), 4.4 (step 3), 4.5 (step 4) with section 4.6 providing a critical review of the process and outcomes.

 

6. Figures 2 and 3 are of poor quality. Please, improve their quality and check all figures for the journal requirements (1000 pix for the short side and 300 DPI resolution).

 

Authors’ reply: we will submit new high quality Figures 2 and 3 as separate files.

 

6. I recommend the authors to place a discussion of the results obtained in a separate section. In the Discussion section, the authors should present a detailed comparison of your results with the results of other authors.

 

Authors’ reply: we have added a new section (section 4.6) as discussion of the results. However, as we have pointed out in the paper in a number of places, we are at this stage not able to make detailed quantitative comparisons of our results with the results of others because our model is yet to be applied in practice.

 

4.6 Critical Review of the Process and Outcomes

The key to development of the 3D digital model of this paper is to take advantage of a small amount of human intervention to solve numerous problems associated with automatic recognition of information by computer. This is mainly manifested in digital location of structural members during the paper drawing to CAD conversion process and in correcting mistakes in the 3D digital model.

For the former, notable challenges in the process of creating a digital CAD from paper-based drawings are the extraction of coordinates of different structural members, the sensitivity of their dimensions to the thickness of lines drawn for them, and the inadequacy of using lines (or other simple shapes such as rectangles) to communicate complex details (such as profiled steel section size). This will be solved by creating an option to input the information in a text box on screen, next to the image showing locations of the structural members for easy referencing. This step is being implemented and the results of this development will be further evaluated.

For the latter, the authors have developed the correction process (which is inevitable due to changes in the lifetime of the building) to ensure that any human intervention is intuitive and minimal. One particular problem with quick measurement of distances is lack of precision, even with inclusion of an intelligent snapping algorithm in the model. Fortunately, for demolition purpose, this lack of precision is generally inconsequential because this would not affect identification of the waste stream and would at most only cause a few percentages in error in prediction of the amount of waste. Nevertheless, this digital model has the potential to be expanded to be very accurate for applications where detailed information is necessary, for example in structural strengthening or refurbishment. This will be the next phase of development of the digital model.

7. The conclusions are presented in a way that is difficult to understand. They need to be numbered and arranged in the following order: scientific novelty, practical significance, prospects for the development of research in the future, and recommendations for specific applied cases.

 

Authors’ comments: we have numbered the conclusions and have made the conclusions more specific and in the format of the recommended ordering.

 

The main contributions of this paper are as follows:

• It proposes and demonstrates an approach that takes advantage of a very small amount of human intervention to overcome numerous challenges associated with automated recognition of paper-based information by computer.
• It describes in detail an intuitive approach that incorporates augmented reality for correcting mistakes in the digital model that are a result of changes in the lifetime of buildings.
• It demonstrates the implementation of a pre-demolition audit that allows building materials and products to be examined in details in different ways (individually, collectively either by locations such as on the same floor or by groups such as beams/columns/walls/floors).
• The developed digital model is an essential part of a digital platform that allows integrated decision making for optimal demolition waste management by minimising or eliminating problems brought about due to fragmentation of the construction industry and scattered knowledge of the history of the EoSL building. The digital platform will enable demolition contractors to drastically improve onsite operations, including waste classification and sorting, so as to minimise waste contamination, and will inform downstream product manufacturers to achieve the highest reuse of materials and products and to extract the highest possible values for the recycled materials.
• The integrated digital model is ideal for transparency and quality assurance of demolition waste management.
• However, the digital model presented in this paper is the first stage of developing the digital platform. Its application in planned demonstration cases of the Horizon Europe project RECONMATIC will test its effectiveness and advantages compared to existing models of demolition waste management.
• The development reported in this paper is for the purpose of dismantling buildings at end of service life. Therefore, the required precision of information (such as element dimensions & their connectivity) is not particularly high. Although this development has the potential to be used for other purposes such as structural strengthening and refurbishment, further research is needed to investigate how to efficiently gather more detailed information.

 

 

8. The list of references contains 26 titles. It's unexpected that such a widely discussed topic as waste management and digital models has so few resources available. This list needs to be expanded to include 35-40 titles.

 

Authors’ reply: we have expanded the reference list to 48 titles. We have used them to improve the literature review, as mentioned in our reply to comment 4.

 

In general, the article needs more careful proofreading, correction of the English language and correction of the presentation style. 

 

Comments on the Quality of English Language

Moderate editing of English language required. I recommend the authors to improve English.

Authors’ reply: we have thoroughly reviewed the paper and corrected any grammatical mistakes.

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

All my comments were considered and corrections were done. The article looks much better.

I recommend the article for publishing.