• International conference on construction engineering and project management
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• 2015.10a
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• pp.10-14
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• 2015

Unsafe behavior is one of the major causes of construction accidents. Managing the behavior of workers in real-time is difficult and requires huge manpower. In this paper, a new real-time locating framework is proposed to improve safety management by collecting and analyzing data describing the behavior of workers to identify habits that may lead to accidents. The aim of the study is to identify working habits of workers based on their location history. Location data is used to compare with that of other workers and equipment. The results indicate that the reuse of real-time location data can provide extra safety information for safety management and that the proposed system has the potential to prevent struck-by accidents and caught-in between accidents by predicting unwanted interaction between workers and equipment. This adds to current research aimed at automating construction safety to the point where the continuous monitoring, managing and protection of site workers on site is possible.

• Journal of Construction Engineering and Project Management
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• v.3 no.4
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• pp.1-4
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• 2013

Excavation is most commonly used activity in all construction projects. All contracting agencies prefer to use bigger and heavier excavators and dumpers on site to do excavations if quantity of excavation is huge. Estimation of required number of excavators and dumpers for completion of excavation could be rather a tedious process involving repetitive calculation on which professionals spend their valuable time. As the Information Technology is highly involved in construction section there os need to have IT model for estimation of number of excavators and dumpers. The developed model is useful to calculate required equipments within short period of time. The purpose of the developed IT model is to save the time and efforts of the construction professional. The paper discusses about model which can be used on site to estimate numbers of excavators and dumpers required for completion of certain quantity of excavation within the given time. The calculation considers various existing formulas and method to generate the output. This information could certainly be useful in planning equipments on construction project sites. The tool is user friendly where any non IT background person can use it on construction sites.

• Journal of KIBIM
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• v.11 no.2
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• pp.24-32
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• 2021

Recently, starting with smart construction research, interest in technology that automates construction site management using artificial intelligence technology is increasing. In order to automate construction site management, it is necessary to recognize objects such as construction equipment or workers, and automatically analyze the relationship between them. For example, if the relationship between workers and construction equipment at a construction site can be known, various use cases of site management such as work productivity, equipment operation status monitoring, and safety management can be implemented. This study derives a real-time object detection platform architecture that is required when performing construction site management using deep learning technology, which has recently been increasingly used. To this end, deep learning models that support real-time object detection are investigated and analyzed. Based on this, a deep learning model development process required for real-time construction site object detection is defined. Based on the defined process, a prototype that learns and detects construction site objects is developed, and then platform development considerations and architecture are derived from the results.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.316-322
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• 2002

In case of reducing working time, it is difficult that the construction industry is analyzed far-reaching effects caused by a reduction of working time, by approaching with just the total amount of work. Because it has the properties such as the singularity, the outdoor using, a sense of the season unlike other industries. In order to analyze the effect of a reduction of working time on the construction industry, the example of a reduction of working time in domestic other industries related with it was analyzed intensively first. And an example in Japan, which is similar to our existing related laws and industrial structure among foreign construction industries was analyzed, and a relation with the domestic construction industries and an issue were drown a conclusion. This was applied to a field worker and a related main group participating in a real production. And it showed the prediction model for a working pattern and a dealing plan to prepare in a construction site by predicting a working pattern in the management side of a construction site annually.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.27-29
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• 2009

Real-time control of on-site construction, based on high quality data, is essential to identify discrepancies between actual and planned performances. Additionally, real-time control enables timely corrective measures to be taken when needed to reduce the damages caused by the discrepancies. The focus of the presentation will be on our work, which uses automated data technologies to collect data needed for real time control.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.114-116
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• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• Journal of Construction Engineering and Project Management
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• v.10 no.1
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• pp.16-32
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• 2020

Cost and time control of projects is important in preventing project failure. However, achieving effective cost and time control in practice is often challenging. The challenges of project cost and time control in practice are investigated by carrying out a questionnaire survey on the top 150 construction contractors in the UK followed by in-depth semi-structured interviews of practitioners from 15 construction companies in the country. Quantitative analysis reveals that design change is the most important factor inhibiting the ability of UK contractors from effectively controlling both the cost and time of construction projects. Four of the top five factors inhibiting effective cost control are also the top factors inhibiting effective time control albeit in a different order. These top factors-design changes, inaccurate evaluation of project time/duration, risk and uncertainty, non-performance of subcontractors and nominated suppliers were also found to be endogenous factors to the project. Additionally, qualitative analysis of the interviews reveals 16 key challenges to prevent for effective project cost and time control in practice. These are classified into four categorised based on where they stem from as follows; from the organisation (1. Lack of integration of cost and time during project control, 2. lack of management buy-in, 3. complicated project control systems and processes, 4. lack of a project control training regime); from the construction management/project management approach (5. Lapses in integration of interfaces, 6. project control not being implemented from the early stages of a project, 7. inefficient utilisation and control of labour, 8. limited time devoted to planning how a project will be controlled at the outset); from the client; (9. Excessive authorisation gates, 10. use of adversarial and non-collaborative forms of contracts, 11. communication problems within client set-up, 12. obstructive client representatives) and; from the project team (13. Lack of detailed/complete design, 14. lack of trust among the project partners, 15. limited time devoted to project control on site, 16. non-factual reporting). The study posits that knowledge of these project control inhibiting factors and challenges is the first step at ensuring they are avoided and enable the implementation of a more effective project cost and time control process in practice.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.1-6
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• 2011

As large-scale building projects have recently increased for the residential, commercial and office facilities, construction costs for these projects have become a matter of great concern, due to their significant construction cost implications, as well as unpredictable market conditions and fluctuations in the rate of inflation during the projects' long-term construction periods. In particular, recent volatile fluctuations of construction material prices fueled such problems as cost forecasting. This research develops a time series model using the Box-Jenkins approach and material price time series data in Korea in order to forecast trends in the unit prices of required materials. Building information modeling (BIM) approaches are also used to analyze injection times of construction resources and to conduct quantity take-off so that total material prices can be forecast. To determine an optimal time series model for forecasting price trends, comparative analysis of predictability of tentative autoregressive integrated moving average (ARIMA) models is conducted. The proposed BIM-based time series forecasting model can help to deal with sudden changes in economic conditions by estimating material prices that correspond to resource injection times.

• Korean Journal of Construction Engineering and Management
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• v.13 no.6
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• pp.33-44
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• 2012

This study is as to payment improvement method of additional incidental cost to be occurred upon extension of public construction time. According to the result of analysis about the cause of non-payment of additional incidental cost of construction time extension through site examples, it was found that difficulties exist in disputes & proofing over the scope of actual cost recognition, and in this regard the result of experts opinion indicated that a construction extension pre-agreement system can be executed which agrees the scope of recognition of additional incidental cost of construction time extension once the statistical standard is clear and accurate. Accordingly, in this study, by totalling multiple sites data, calculations were implemented in terms of type of construction projects, amount of constructions, period of constructions. According to the result of calculation, the element of type of construction project and construction period appears to have none direct effect to the occurrence of additional cost of construction time extension, but direct relationship was indicated related to the contract amount element. In view of above, in this study a standard additional incidental cost of construction time extension was proposed, and presented a system improvement plan to implement the construction extension pre-agreement system.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.64-71
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• 2002

This research developed construction cost forecasting model using Building Construction Cost Index, time series analysis and Artificial Neural Networks. By this model, we could calculate the forecasted values of construction cost precisely and efficiently. And we also could find out that the standard deviation of forecasted values is 0.375 and it is a very exact result, so the standard deviation is just 0.33 percent of 112.28, the average of Building Construction Cost Index. And it show more exact forecasting result in comparison with Time Series Analysis.