• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Journal of the Korea Institute of Building Construction
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• v.2 no.3
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• pp.155-162
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• 2002

The Ministry of Construction-Transportation released a plan about EVMS in 1993 in order to prepare measures for an efficient public construction project, and prepared an enforcement proposal concretely in June for 2000 years, and have enforce a public project by an example with a target. Therefore, accurate analysis and evaluation about field progress are required for efficient management of a building construction, and must be established building construction management system for fast action about a problem However, unified management cannot be consisting because a work progress system is different from details estimate system within a country. and There is not still a definite standard in progress measurement for an application of EVMS. A purpose of this study is to present an improvement about a problem of progress measurement for an application of EVMS. The contents of a study, inquired into a progress measurement method and a standard to use in the field of a public construction and private construction and Checks a problem and presented an improvement item necessary for and is as follows. $\circled1$ must establishes a control account and progress measurement standard. $\circled2$ must manage progress in a activity viewpoint. $\circled3$ must use an accurate CPM process management technique.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1068-1074
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• 2009

The progress is widely used as a critical index for successful construction project management. In spite of the importance of progress measurement, the excessive management effort to collect and maintain detailed data has been highlighted as a major barrier to measurement of highly accurate progress. In order to reduce the required workload and to enhance accuracy, several researches have been conducted. These researches can be categorized into two groups. First group focuses on automated data collection utilizing advanced technologies only for limited construction tasks. The second group is a research area where the standard progress measurement methodologies encompassing entire construction tasks are investigated. Topics include the adjusting the level of details, standardizing work processes, and applying flexible WBS. However, the techniques for automated data collection are not fully investigated yet in the second group. Combining these two research areas can provide a solution for more effective progress management in terms of enhancing accuracy and optimizing workload. However, there has been no comprehensive research addressing these two research groups in an integrated manner. In this context, the purpose of this paper is to propose a methodology that identifies the most suitable measurement method and data acquisition technology (e.g., GPS, RFID, etc.) for entire construction tasks of a project. The proposed methodology in this paper will be able to facilitate the selection process of data acquisition technologies for entire construction tasks of a project and to support the overall enhancement of automated progress management.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1073-1080
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• 2024

The imperative for real-time automatic construction progress monitoring (ACPM) to avert project delays is widely acknowledged in construction project management. Current ACPM methodologies, however, face a challenge as they rely on collecting data from construction sites and processing it offline for progress analysis. This delayed approach poses a risk of late identification of critical construction issues, potentially leading to rework and subsequent project delays. This research introduces a real-time construction progress monitoring framework that integrates cutting-edge semantic Simultaneous Localization and Mapping (SLAM) techniques. The innovation lies in the framework's ability to promptly identify structural components during site inspections conducted through a robotic system. Incorporating deep learning models, specifically those employing semantic segmentation, enables the system to swiftly acquire and process real-time data, identifying specific structural components and their respective locations. Furthermore, by seamlessly integrating with Building Information Modeling (BIM), the system can effectively evaluate and compare the progress status of each structural component. This holistic approach offers an efficient and practical real-time progress monitoring solution for construction projects, ensuring timely issue identification and mitigating the risk of project delays.

• Journal of the Korean Institute of Landscape Architecture
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• v.20 no.4
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• pp.93-101
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• 1993

The purpose of this study is to analyze th especificity of landscape construction progress in order to develop the model of landscape construction schedule management. Nine case study area in housing complex was selected and the graphic curve of the accumulative payment by landscape construction schedule was analyzed. And the results are as follows: The graphic curve of common construction progress is S-curve but that of landscape construction progress is parabolic-curve, because landscape construction concentrally progress in last period of construction schedule. And particularly parabolic-curve seems to rise up suddenly in the last period when landscape construction amount is small.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.130-131
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• 2015

Accurate construction progress measurement is an important issue for successful project delivery. This paper presents a method that keeps track of the progress measurement involved in construction operations and facilities visualization of the data using BIM and IOT. To verify the method, a residential house project was used for the case study. Test case verifies the usability and validity of the method implemented in the system.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.920-927
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• 2009

Many schedule delays and cost overruns in interior construction are caused by a lack of understanding in detailed and complicated interior works. To minimize these potential impacts in interior construction, a systematic approach for project managers to detect discrepancies at early stages and take corrective action through use of visualized data is required. This systematic implementation is still challenging: monitoring is time-consuming due to the significant amount of as-built data that needs to be collected and evaluated; and current interior construction progress reports have visual limitations in providing spatial context and in representing the complexities of interior components. To overcome these issues, this research focuses on visualization and computer vision techniques representing interior construction progress with photographs. The as-planned 3D models and as-built photographs are visualized in a 3D walk-through model. Within such an environment, the as-built interior construction elements are detected through computer vision techniques to automatically extract the progress data linked with Building Information Modeling (BIM). This allows a comparison between the as-planned model and as-built elements to be used for the representation of interior construction progress by superimposing over a 3D environment. This paper presents the process of representing and detecting interior construction components and the results for an ongoing construction project. This paper discusses implementation and future potential enhancement of these techniques in construction.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2010.05b
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• pp.99-102
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• 2010

Today's construction is higher and more complex. So types and amounts of needed materials for construction project are increasing and those are occurred problems in construction site such as insufficient working space, confusion of materials handling order and working circulation. Because of those problems, research of progress management system using RFID+4D has been studied, but it is impossible to manage progress and material statement in real-time. So this study analyzed problems of current research and suggested VRML based RFID+4D Progress Management System. This Study focused on system basic concept and interface is designed for system development. This research is still progressing, so it has to do more development and research. However, it could be expected construction management efficiency and automation of management tasks.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.181-187
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• 2013

The construction market condition is getting worse because of global constructions slow down, low profit, market contraction and so on. For these reason, most construction companies depend on public construction projects which possible to protect construction fee, known as progress payment, by laws. Despite this law, problems of progress payment are constantly occurring and it has been main factors that hinder the construction cost's cash-flow in construction project. To solve this problem, many researchers suggested various solutions but most of solutions were focused on specific target as owner, general contractor, and subcontractor. So, most of solutions were insufficient consider about interaction between contractors. Because of these reasons, it was hard to reflected policy. This research aimed to use system dynamics to develop the model for the application and payment based on the regulations and papers. Also, performed a developed model's verification based on progress payment regulation's basic objectives.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.317-320
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• 2015

Documenting work-in-progress on construction sites using images captured with smartphones, point-and-shoot cameras, and Unmanned Aerial Vehicles (UAVs) has gained significant popularity among practitioners. The spatial and temporal density of these large-scale site image collections and the availability of 4D Building Information Models (BIM) provide a unique opportunity to develop BIM-driven visual analytics that can quickly and easily detect and visualize construction progress deviations. Building on these emerging sources of information this paper presents a pipeline for model-driven visual analytics of construction progress. It particularly focuses on the following key steps: 1) capturing, transferring, and storing images; 2) BIM-driven analytics to identify performance deviations, and 3) visualizations that enable root-cause assessments on performance deviations. The information requirements, and the challenges and opportunities for improvements in data collection, plan preparations, progress deviation analysis particularly under limited visibility, and transforming identified deviations into performance metrics to enable root-cause assessments are discussed using several real world case studies.