Peer Reviewed Publications
Title | Year | Description | Download File |
Regulatory Information Transformation Ruleset Expansion to Support Automated Building Code Compliance Checking |
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Appears in Automation in Construction |
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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 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. |
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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 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 |
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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. |
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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. |
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Design Information Extraction from Construction Specifications to Support Cost Estimation | 2021 |
Appears in Automation in Construction |
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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. |
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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. |
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Risk-Managed Lifecycle Costing for Asphalt Road Construction and Maintenance Projects under Performance-Based Contracts |
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Appears in ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems A risk management tool can provide contractors with a better understanding of the most probable sensitive risks that they may encounter during the construction and maintenance phases with the emphasis on the ranges of risks they can take or the contingencies they need. |
https://ascelibrary.org/doi/10.1061/AJRUA6.0000888 |