• Title/Summary/Keyword: Project Network

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Online Monitoring of Ship Block Construction Equipment Based on the Internet of Things and Public Cloud: Take the Intelligent Tire Frame as an Example

  • Cai, Qiuyan;Jing, Xuwen;Chen, Yu;Liu, Jinfeng;Kang, Chao;Li, Bingqiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.3970-3990
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    • 2021
  • In view of the problems of insufficient data collection and processing capability of multi-source heterogeneous equipment, and low visibility of equipment status at the ship block construction site. A data collection method for ship block construction equipment based on wireless sensor network (WSN) technology and a data processing method based on edge computing were proposed. Based on the Browser/Server (B/S) architecture and the OneNET platform, an online monitoring system for ship block construction equipment was designed and developed, which realized the visual online monitoring and management of the ship block construction equipment status. Not only that, the feasibility and reliability of the monitoring system were verified by using the intelligent tire frame system as the application object. The research of this project can lay the foundation for the ship block construction equipment management and the ship block intelligent construction, and ultimately improve the quality and efficiency of ship block construction.

Prediction of duration and construction cost of road tunnels using Gaussian process regression

  • Mahmoodzadeh, Arsalan;Mohammadi, Mokhtar;Abdulhamid, Sazan Nariman;Ibrahim, Hawkar Hashim;Ali, Hunar Farid Hama;Nejati, Hamid Reza;Rashidi, Shima
    • Geomechanics and Engineering
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    • v.28 no.1
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    • pp.65-75
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    • 2022
  • Time and cost of construction are key factors in decision-making during a tunnel project's planning and design phase. Estimations of time and cost of tunnel construction projects are subject to significant uncertainties caused by uncertain geotechnical and geological conditions. The Gaussian Process Regression (GPR) technique for predicting ground condition and construction time and cost of mountain tunnel projects is used in this work. The GPR model is trained with data from past mountain tunnel projects. The model is applied to a case study in which the predicted time and cost of tunnel construction using the GPR model are compared with the actual construction time and cost for model validation and reducing the uncertainty for the future projects. In addition, the results obtained from the GPR have been compared with to other models of artificial neural network (ANN) and support vector regression (SVR) that the GPR model provides more accurate results.

Summarize Water-soluble Ions of $PM_{2.5}$ in Northeastern Asia

  • Z. He;Seong Y. Ryu;Kim, Jeong E.;K. O. Ogunjobi;Kim, Young J.
    • Proceedings of the Korea Air Pollution Research Association Conference
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    • 2003.11a
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    • pp.400-401
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    • 2003
  • Atmospheric fine aerosol particles play an important role in controlling a number of atmospheric processes, such as the deposition of different compounds, the optical properties etc. (Molnar et al., 1999). In this report, water-soluble species of PM$_{2.5}$ obtained from simultaneous measurements at four Asia sites (Beijng (39.56$^{\circ}$N, 116.17$^{\circ}$E), China; Gwangju (35.10$^{\circ}$N, 126.53$^{\circ}$E), South Korea; Kyoto (35.01$^{\circ}$N, 135.44$^{\circ}$E), Japan; and Ulan-Bator (47.55$^{\circ}$N, 106.52$^{\circ}$E), Mongolia) during the periods of 14-22 August, 30 October-06 November 2000, 14-21 January 2001, 23 July-02 August and 05-16 November 2002, within the framework of an APN (The Asia-Pacific Network for Global Change Research) project are reported. Ion components in 23 July-02 August 2002 were not obtained because of the technical problem of equipments.s.

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Optical follow-up observation of three long GRBs with SomangNet facilities

  • Paek, Gregory S.H.;Im, MyungShin;Kim, Joonho;Lim, Gu;Jeong, Mankeun;Kang, Wonseok;Kim, Taewoo;Burkhonov, Otabek;Mirazaqulov, Davron;Ehgamberdiev, Shyhrat A.;Seo, Jinguk;Lee, Chung-Uk;Kim, Seung-Lee;Sung, Hyung-Il
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.1
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    • pp.49.5-50
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    • 2021
  • We report the optical follow-up observations of three long γ-ray burst events, GRB 201020A, GRB 201103B and GRB 210104A by the network of telescopes in the SomangNet project. We show light curves, color evolution and SED evolution, and fit them to a single power law function to derive decay index and compare their properties with other long GRBs samples. Also, we show a good observational example that 0.4-1m class telescopes in SomangNet have potential to catch dim light from high red shift object (R>22 mag) by deep imaging. In conclusion, we found that three GRBs have optical afterglow properties of long GRB and our results are consistent with the reports of high energy analysis.

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A Study on a Systematization of Preliminary Construction Control for the Quality and Schedule Management of APT Construction (품질확보 및 공기지연예방을 위한 공사관리 체계화에 관한 연구)

  • Park, Hong Tae;Lee, Yang Kyoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.3D
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    • pp.347-353
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    • 2008
  • Generally speaking, it is important to know the activities itself exactly and to control the activities correctly so as to assure timely progress and the quality of any project. In order to progress smoothly in accordance with construction schedule, it is important to systematize the preliminary arrangements necessary for each process and then manage them. In this study, in order to progress smoothly the quality and schedule management of the construction, we can be made systematically pre-works in accordance with construction schedule by the civil construction items of the apartment house construction. we suggested pre-construction control item by the workers through experiential method of construction engineers in accordance with network schedule.

Classification of Construction Worker's Activities Towards Collective Sensing for Safety Hazards

  • Yang, Kanghyeok;Ahn, Changbum R.
    • International conference on construction engineering and project management
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    • 2017.10a
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    • pp.80-88
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    • 2017
  • Although hazard identification is one of the most important steps of safety management process, numerous hazards remain unidentified in the construction workplace due to the dynamic environment of the construction site and the lack of available resource for visual inspection. To this end, our previous study proposed the collective sensing approach for safety hazard identification and showed the feasibility of identifying hazards by capturing collective abnormalities in workers' walking patterns. However, workers generally performed different activities during the construction task in the workplace. Thereby, an additional process that can identify the worker's walking activity is necessary to utilize the proposed hazard identification approach in real world settings. In this context, this study investigated the feasibility of identifying walking activities during construction task using Wearable Inertial Measurement Units (WIMU) attached to the worker's ankle. This study simulated the indoor masonry work for data collection and investigated the classification performance with three different machine learning algorithms (i.e., Decision Tree, Neural Network, and Support Vector Machine). The analysis results showed the feasibility of identifying worker's activities including walking activity using an ankle-attached WIMU. Moreover, the finding of this study will help to enhance the performance of activity recognition and hazard identification in construction.

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Tack Coat Inspection Using Unmanned Aerial Vehicle and Deep Learning

  • da Silva, Aida;Dai, Fei;Zhu, Zhenhua
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.784-791
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    • 2022
  • Tack coat is a thin layer of asphalt between the existing pavement and asphalt overlay. During construction, insufficient tack coat layering can later cause surface defects such as slippage, shoving, and rutting. This paper proposed a method for tack coat inspection improvement using an unmanned aerial vehicle (UAV) and deep learning neural network for automatic non-uniform assessment of the applied tack coat area. In this method, the drone-captured images are exploited for assessment using a combination of Mask R-CNN and Grey Level Co-occurrence Matrix (GLCM). Mask R-CNN is utilized to detect the tack coat region and segment the region of interest from the surroundings. GLCM is used to analyze the texture of the segmented region and measure the uniformity and non-uniformity of the tack coat on the existing pavements. The results of the field experiment showed both the intersection over union of Mask R-CNN and the non-uniformity measured by GLCM were promising with respect to their accuracy. The proposed method is automatic and cost-efficient, which would be of value to state Departments of Transportation for better management of their work in pavement construction and rehabilitation.

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Potential of an Interactive Metaverse Platform for Safety Education in Construction

  • Yoo, Taehan;Lee, Dongmin;Yang, Jaehoon;Kim, Dohyung;Lee, Doyeop;Park, Chansik
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.516-524
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    • 2022
  • The construction industry is considered the most hazardous industry globally. Therefore, safety education is crucial for raising the safety awareness of construction workers working at construction sites and creating a safe working environment. However, the current safety education method and tools cannot provide trainees with realistic and practical experiences that might help better safety awareness in practice. A metaverse, a real-time network of 3D virtual worlds focused on social connection, was created for more interactive communication, collaboration, and coordination between users. Several previous studies have noted that the metaverse has excellent potential for improved safety education performance, but its required functions and practical applications have not been thoroughly researched. In order to fill the research gap, this paper reviewed the potential benefits of a metaverse based on the current research and suggested its application for safety education purposes. This paper scrutinized the metaverse's key functions, particularly its information and knowledge sharing function and reality capture function. Then, the authors created a metaverse prototype based on the two key functions described above. The main contribution of this paper is reviewing the potential benefits of a metaverse for safety education. A realistic and feasible metaverse platform should be developed in future studies, and its impact on safety education should be quantitatively verified.

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Development of a Collaboration Recommendation Model between Global Consulting Firms using Link Prediction

  • Yu, Young-su;Koo, Bon-sang
    • International conference on construction engineering and project management
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    • 2020.12a
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    • pp.381-386
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    • 2020
  • Global construction and engineering consulting (E&C) firms are actively seeking entry into overseas markets based on loan projects from multilateral development banks to provide a basis for entry into overseas markets and sustainable growth. Bids on these projects are competitive between global top firms in terms of the technical level and price due to the limited number of projects; thus, developing a successful partnership to complement competence has become an essential element to win bids. In this regard, many studies have analyzed enterprises through characteristic analyses or the derivation of influential factors from the past social networks based on social network analysis (SNA). However, few studies have been conducted to reflect the process of changes to analyze collaborative relationships. Thus, this study aims to identify dynamic changes in past social networks and develop a model that can predict changes in the relationships between E&C firms based on similarities or differences between firms, presenting a methodology to target firms for appropriate collaboration. The analysis results demonstrate that the sensitivity of the developed prediction model was 70.26%, which could accurately predict 163 out of 232 actual cooperative cases.

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Image Processing-based Object Recognition Approach for Automatic Operation of Cranes

  • Zhou, Ying;Guo, Hongling;Ma, Ling;Zhang, Zhitian
    • 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.

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