Peer Reviewed Publications

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Title	Year	Description	Download File
BIM-based Simulation of Construction Robotics in the Assembly Process of Wood Frames	2022	Appears in Automation in Construction This paper provides a new simulation framework integrating BIM & robotics for construction automation, and offers a tool to automatically generate data from BIM as input for robotic operational analysis.	https://doi.org/10.1016/j.autcon.2022.104194
Regulatory Information Transformation Ruleset Expansion to Support Automated Building Code Compliance Checking	2022	Appears in Automation in Construction The state-of-the-art NLP-based full automation of building code compliance checking had limited code requirements coverage. An information transformation ruleset expansion method is proposed to support expansion of checkable code requirements. The expanded ruleset from the proposed method significantly increased the F1-score of code requirements generation.	https://doi.org/10.1016/j.autcon.2022.104230
Constructing Invariant Signatures for AEC Objects to Support BIM-Based Analysis Automation through Object Classification	2022	Appears in Journal of Computing in Civil Engineering In order to support seamless interoperability of BIM applications, the authors have proposed invariant signatures that uniquely define each AEC object and capture their intrinsic properties. In this paper, the authors combine the use of invariant signatures together with a machine learning approach to address BIM object classification. Results show that the use of proposed invariant signatures and machine learning algorithms in BIM applications is promising.	https://doi.org/10.1061/(ASCE)CP.1943-5487.0001012
Model Validation Using Invariant Signatures and Logic-Based Inference for Automated Building Code Compliance Checking	2022	Appears in Journal of Computing in Civil Engineering The authors propose a new method for BIM model validation to validate an input Industry Foundation Classes (IFC) model with regard to building code concepts. This validation method was supported by creating invariant signatures of architecture, engineering, and construction objects that capture the geometric nature of the objects.	https://doi.org/10.1061/(ASCE)CP.1943-5487.0001002
Framework for Developing IFC-Based 3D Documentation from 2D Bridge Drawings	2022	Appears in Journal of Computing in Civil Engineering This paper proposes a framework for automatically processing existing 2D bridge drawings for bridges built pre-BIM adoption in the architecture, engineering, and construction industry; converting these record drawings into three-dimensional (3D) information models; and converting 3D information models into industry foundation class (IFC) files.	https://doi.org/10.1061/(ASCE)CP.1943-5487.0000986
Semiautomated Generation of Logic Rules for Tabular Information in Building Codes to Support Automated Code Compliance Checking	2022	Appears in Journal of Computing in Civil Engineering The authors propose a semiautomated information extraction and transformation method, which can extract building code requirements in tables and convert extracted information to logic rules. The proposed method includes two main steps: tabular information extraction, and rule generation.	https://doi.org/10.1061/(ASCE)CP.1943-5487.0001000
Smart Construction Scheduling Monitoring Using YOLOv3-based Activity Detection and Classification	2022	Appears in Journal of Information Technology in Construction Increasing efficiency and adhering to a schedule are prominent issues faced by many construction projects. This research aims to analyze and compare the efficiency and accuracy of different computer-vision based activity recognition algorithms that are used on construction sites. The authors propose a method which involves the use of YOLOv3 to perform activity recognition on construction sites, and compare the accuracy of this method to existing algorithms.	https://itcon.org/paper/2022/12
Design Information Extraction from Construction Specifications to Support Cost Estimation	2021	Appears in Automation in Construction A new semantic NLP-based method for developing construction specifications information extraction and matching algorithms. This method supports construction cost estimation automation, reducing manual efforts, improving efficiency & objectivity.	https://doi.org/10.1016/j.autcon.2021.103835
Semantic Rule-Based Construction Procedural Information Extraction to Guide Jobsite Sensing and Monitoring	2021	Appears in Journal of Computing in Civil Engineering To reduce manual efforts in collecting information from construction procedural documents, selecting appropriate sensing techniques to collect data on the jobsite, and giving in-time feedback for progress monitoring and compliance checking, the authors propose a semantic rule-based information extraction method to extract construction execution steps from construction procedural documents automatically. In addition, they develop a construction procedure and data collection ontology to classify construction site information and provide guidance on selecting sensing techniques for collecting jobsite data based on the extracted information, and propose a construction procedural data integration (CPDI) framework.	https://doi.org/10.1061/(ASCE)CP.1943-5487.0000971
Logic Representation and Reasoning for Automated BIM Analysis to Support Automation in Offsite Construction	2021	Appears in Automation in Construction First-order and second-order logic were used to analyze IFC-based BIM models, and the implementation of the developed logic ruleset achieved a recall of 90.3% and higher. Logic representation and reasoning were demonstrated to be effective for automated BIM analysis in the AEC domain. Construction information were derived from BIM that can support analysis of offsite construction automation.	https://doi.org/10.1016/j.autcon.2021.103756

Title

Year

Description

Download File

2022

Appears in Automation in Construction
This paper provides a new simulation framework integrating BIM & robotics for construction automation, and offers a tool to automatically generate data from BIM as input for robotic operational analysis.

https://doi.org/10.1016/j.autcon.2022.104194

2022

Appears in Automation in Construction
The state-of-the-art NLP-based full automation of building code compliance checking had limited code requirements coverage. An information transformation ruleset expansion method is proposed to support expansion of checkable code requirements. The expanded ruleset from the proposed method significantly increased the F1-score of code requirements generation.

https://doi.org/10.1016/j.autcon.2022.104230

Constructing Invariant Signatures for AEC Objects to Support BIM-Based Analysis Automation through Object Classification

2022

Appears in Journal of Computing in Civil Engineering
In order to support seamless interoperability of BIM applications, the authors have proposed invariant signatures that uniquely define each AEC object and capture their intrinsic properties. In this paper, the authors combine the use of invariant signatures together with a machine learning approach to address BIM object classification. Results show that the use of proposed invariant signatures and machine learning algorithms in BIM applications is promising.

https://doi.org/10.1061/(ASCE)CP.1943-5487.0001012

Model Validation Using Invariant Signatures and Logic-Based Inference for Automated Building Code Compliance Checking

2022

Appears in Journal of Computing in Civil Engineering
The authors propose a new method for BIM model validation to validate an input Industry Foundation Classes (IFC) model with regard to building code concepts. This validation method was supported by creating invariant signatures of architecture, engineering, and construction objects that capture the geometric nature of the objects.

https://doi.org/10.1061/(ASCE)CP.1943-5487.0001002

Framework for Developing IFC-Based 3D Documentation from 2D Bridge Drawings

2022

Appears in Journal of Computing in Civil Engineering
This paper proposes a framework for automatically processing existing 2D bridge drawings for bridges built pre-BIM adoption in the architecture, engineering, and construction industry; converting these record drawings into three-dimensional (3D) information models; and converting 3D information models into industry foundation class (IFC) files.

https://doi.org/10.1061/(ASCE)CP.1943-5487.0000986

Semiautomated Generation of Logic Rules for Tabular Information in Building Codes to Support Automated Code Compliance Checking

2022

Appears in Journal of Computing in Civil Engineering
The authors propose a semiautomated information extraction and transformation method, which can extract building code requirements in tables and convert extracted information to logic rules. The proposed method includes two main steps: tabular information extraction, and rule generation.

https://doi.org/10.1061/(ASCE)CP.1943-5487.0001000

Smart Construction Scheduling Monitoring Using YOLOv3-based Activity Detection and Classification

2022

Appears in Journal of Information Technology in Construction
Increasing efficiency and adhering to a schedule are prominent issues faced by many construction projects. This research aims to analyze and compare the efficiency and accuracy of different computer-vision based activity recognition algorithms that are used on construction sites. The authors propose a method which involves the use of YOLOv3 to perform activity recognition on construction sites, and compare the accuracy of this method to existing algorithms.

https://itcon.org/paper/2022/12

Design Information Extraction from Construction Specifications to Support Cost Estimation

2021

Appears in Automation in Construction
A new semantic NLP-based method for developing construction specifications information extraction and matching algorithms.
This method supports construction cost estimation automation, reducing manual efforts, improving efficiency & objectivity.

https://doi.org/10.1016/j.autcon.2021.103835

Semantic Rule-Based Construction Procedural Information Extraction to Guide Jobsite Sensing and Monitoring

2021

Appears in Journal of Computing in Civil Engineering
To reduce manual efforts in collecting information from construction procedural documents, selecting appropriate sensing techniques to collect data on the jobsite, and giving in-time feedback for progress monitoring and compliance checking, the authors propose a semantic rule-based information extraction method to extract construction execution steps from construction procedural documents automatically. In addition, they develop a construction procedure and data collection ontology to classify construction site information and provide guidance on selecting sensing techniques for collecting jobsite data based on the extracted information, and propose a construction procedural data integration (CPDI) framework.

https://doi.org/10.1061/(ASCE)CP.1943-5487.0000971

Logic Representation and Reasoning for Automated BIM Analysis to Support Automation in Offsite Construction

2021

Appears in Automation in Construction
First-order and second-order logic were used to analyze IFC-based BIM models, and the implementation of the developed logic ruleset achieved a recall of 90.3% and higher. Logic representation and reasoning were demonstrated to be effective for automated BIM analysis in the AEC domain. Construction information were derived from BIM that can support analysis of offsite construction automation.

https://doi.org/10.1016/j.autcon.2021.103756