• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.76-77
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• 2016

This paper presents an automated construction quality nonconformity control method. Existing quality control process are confined attributed to the dependence on human quality personnels. They are inefficiency for continuos quality improvements and may cause project schedule delays when any nonconformity is handled timely fashion. For sure, It is important to identify the add hoc quality nonconformity control processes and to implement them into an automated system that controls its' work-flow. It would be desirable to develop the construction project quality nonconformity control system using Building information modeling(BIM) and Information and Communications Technologies(ICT). It may provide an effective platform to prevent quality issues that exist in the existing quality management practice.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.69-77
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• 2017

The information related to legislation is massive, and it takes much time and effort to manually build the legislation ontology. Thus, studies on machine-based automated building methods are underway. However, the studies to automatically construct such systems focus on using TBox construction, and those based on automated ABox construction, which corresponds to instances, theoretical systems and data building cases, has not yet been sufficiently developed. Therefore, this paper suggests using a semi-automatic ABox construction method based on sentence patterns to automatically build the ontology for the legislation of the Republic of Korea. Precision and Recall experiments were conducted to further discuss the performance of the suggested method. These experiments provide a comparison between the manual classification, and the triples built by the machines of the legal information by assessing the corresponding numerical values.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.255-258
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• 2015

Scaffolds are frequently used in construction projects. Despite the impact on the entire safety, scaffolds are rarely analyzed as part of the safety planning. While recent advances in BIM (Building Information Modeling) provides opportunity to address potential safety issues in the early planning stages, it is still labor-intensive and challenging to incorporate scaffolds into current manual jobsite safety analysis which is time-consuming and error-prone. Consequently, potential safety hazards related to scaffolds are identified and presented during the construction phase. The objective of this research is to integrate scaffolds into automated safety analysis using BIM. A safety checking system was created to simulate the movements of scaffolds along the paths of crews using the scaffolds. Algorithms in the system automatically identify safety hazards related to activities working on scaffolds. Then, the system was implemented in a commercially available BIM software program for case studies. The results show that the algorithms successfully identified safety hazards that were not noticed by project managers of the projects. The results were visualized in BIM to facilitate early safety communications.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.744-751
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• 2022

Construction is among the most dangerous industries with numerous accidents occurring at job sites. Following an accident, an investigation report is issued, containing all of the specifics. Analyzing the text information in construction accident reports can help enhance our understanding of historical data and be utilized for accident prevention. However, the conventional method requires a significant amount of time and effort to read and identify crucial information. The previous studies primarily focused on analyzing related objects and causes of accidents rather than the construction activities. This study aims to extract construction activities taken by workers associated with accidents by presenting an automated framework that adopts a deep learning-based approach and natural language processing (NLP) techniques to automatically classify sentences obtained from previous construction accident reports into predefined categories, namely TRADE (i.e., a construction activity before an accident), EVENT (i.e., an accident), and CONSEQUENCE (i.e., the outcome of an accident). The classification model was developed using Convolutional Neural Network (CNN) showed a robust accuracy of 88.7%, indicating that the proposed model is capable of investigating the occurrence of accidents with minimal manual involvement and sophisticated engineering. Also, this study is expected to support safety assessments and build risk management systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.264-279
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• 2021

Most automated vehicle evaluation scenarios are developed based on the typical driving situations that automated vehicles will face. However, various situations occur during actual driving, and sometimes complex judgments are required. This study is to define a situation that requires complex judgment for safer driving of an automated vehicle as a dilemma situation, and to suggest a driving strategy necessary to secure driving safety in each situation. To this end, we defined dilemma situations based on the automated vehicle ethics guidelines, the criteria for recognition of error rate in automobile accidents, and suggestions from the automated vehicle developers. In addition, in the defined dilemma situations, the factors affecting movement for establishing driving strategies were explored, and the priorities of factors affecting driving according to the Road Traffic Act and driving strategies were derived accordingly.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.690-693
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• 2008

Recently, the trend has been for buildings to become larger and more sophisticated, and this has created safety issues. Because the buildings are big it takes lots of time to check building codes related to anti-disaster and safety manually, and there is the high possibility of making mistakes. Due to these problems, according to a study, 83% of architecture and construction workers believe that an automated code-checking system is needed. This study researches past automated code checking systems and research activity, and using Building Information Model (BIM) technology, determines the feasibility of developing a system to automatically check domestic codes related to egress and anti-disaster. This paper describes the necessity of an automated building code checking system and expected effects. It then reports whether the methods used in previous studies can be deployed in domestic building code checking and discusses problems and limitations. It also suggests an alternative approach. Although this study covers limited codes related to egress, we need to find out what is needed for automatic general code checking system and do further studies for that.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.6-13
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• 2022

The Ministry of Land, Infrastructure and Transport (MoLIT) and the Korean Automobile Testing and Research Institute (KATRI) are supporting the development of Lv.3 automated vehicle (hereinafter, AV) technology by constructing an automated driving pilot city (as known as K-City) equipped with total 5 evaluation environments (urban, motorway, suburban, community road, and autonomous parking facility) which is a test bed exclusively for AV (2017~2018). An upgrade project is in a progress to materialize harsh environments such as bad weather (rain, fog, etc.) and reproduction of communication jamming (GPS blocking, etc.) with the purpose of supporting the development of Lv.4 connected & automated vehicle (hereinafter, CAV) technology (2019~2022). We intend to proactively establish a national level standard for CAV test-bed and test road requirements, test method, etc. for establishment of a road map for the construction of the test bed which is being promoted step by step and analyze and, when required, benchmark the case of China that has announced and is utilizing it. Through this, we plan to define standardized requirements (evaluation facility, evaluation system, etc.) on the test bed for the development of Lv.4/4+ CAV technology and utilize the same for the design and construction of a test bed, establishment of a road map for the construction of a real car-based test environment related to the support for autonomous driving service substantiation, etc. through provision of an evaluation environment utilizing K-City, and the establishment of a K-City upgrade strategies, etc.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.235-239
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• 2009

As robotic technologies have become more actively utilized to automate many construction tasks, they have been able to improve the construction productivity, quality, and worker's safety on site. A new advanced system, Robot-based Construction Automation (RCA) system, is currently being developed. To accomplish RCA system effectively, Design for automation (DFA) should be performed in automation system developing phase. The performance criteria of this system are a major cause of design changes. It is required exhaustive review for development new system. This research analyzed the design changes of Climbing Hydraulic Robot system and Construction Factory (CF), being currently developed in the field of applied RCA systems. And the design change matters according to performance criteria in each system's design-by-step were analyzed. The purpose of this research is developing the performance criteria in the developing phase of RCA system, and then will be served as basis for system design in similar projects.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.399-408
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• 2020

The construction industry is suffering from aging workers, frequent accidents, as well as low productivity. With the rapid development of information technologies in recent years, automatic construction, especially automatic cranes, is regarded as a promising solution for the above problems and attracting more and more attention. However, in practice, limited by the complexity and dynamics of construction environment, manual inspection which is time-consuming and error-prone is still the only way to recognize the search object for the operation of crane. To solve this problem, an image-processing-based automated object recognition approach is proposed in this paper, which is a fusion of Convolutional-Neutral-Network (CNN)-based and traditional object detections. The search object is firstly extracted from the background by the trained Faster R-CNN. And then through a series of image processing including Canny, Hough and Endpoints clustering analysis, the vertices of the search object can be determined to locate it in 3D space uniquely. Finally, the features (e.g., centroid coordinate, size, and color) of the search object are extracted for further recognition. The approach presented in this paper was implemented in OpenCV, and the prototype was written in Microsoft Visual C++. This proposed approach shows great potential for the automatic operation of crane. Further researches and more extensive field experiments will follow in the future.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.188-191
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• 2002

This paper concerns 3-D graphical modeling and simulation techniques for design and control of automated equipment for construction and facility maintenance. A case study on the use of 3-D graphics techniques for developing a power plant maintenance robot is presented. By simulating equipment operation within the 3-D geometry models of the work environment the environment design was improved. The 3-D graphical models of the equipment and the work environment were further utilized for the control of the robot from a remote distance. By presenting the real-time updated equipment configuration and the work environment to the operator, the graphical model-based equipment control system helped the operator overcome the problems associated with spatial perception. The collision between the robot and the plant structures was also avoided based the real-time analysis of the dynamically updated graphical models.