• International conference on construction engineering and project management
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• 2015.10a
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• pp.669-670
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• 2015

Efficient management of the construction heavy equipment is required to reduce the rate of carbon emissions and on-site accidents. The intelligent excavation system (IES) will improve the construction quality and productivity through information technologies and efficient equipment operation, especially in large earthwork projects. Three-dimensional digitized ground data should be required for identifying the path of heavy equipment and work-site environment. Rapid development of terrain laser scanners (TLS) is more readily to acquire the digital data. This study suggests the '3D ground terrain processing platform (3DGTPP)' including data manipulating module and analyzing module of the scanned data for intelligent earthmoving equipment operation. The processing platform consists of six modules, including scanning, registering, manipulating, analyzing, transmitting, and storing. 3D ground terrain processing platform presented in this study will provide fundamental information for intelligent excavation system (IES), which will increase the efficiency of earthworks and safety of workers in significant.

• 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.

• Journal of Drive and Control
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• v.20 no.4
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• pp.133-139
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• 2023

A weighing system calculates the bucket's excavation amount of an excavator. Usually, the excavation amount is computed by the excavator's motion equations with sensing data. But these motion equations have computing errors that are induced by assumptions to the linear systems and identification of the equation's parameters. To reduce computing errors, some commercial weighing system incorporates particular motion into the excavation process. This study introduces a linear regression model on an artificial neural network that has fewer predicted errors and doesn't need a particular pose during an excavation. Time serial data were gathered from a 30tons excavator's loading test. Then these data were preprocessed to be adjusted by MPL (Multi Layer Perceptron) or CNN (Convolutional Neural Network) based linear regression models. Each model was trained by changing hyperparameter such as layer or node numbers, drop-out rate, and kernel size. Finally ID-CNN-based linear regression model was selected.

• Journal of Drive and Control
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• v.12 no.1
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• pp.29-33
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• 2015

• International conference on construction engineering and project management
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• 2009.05a
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• pp.472-478
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• 2009

The scopes of the supply chain management in construction projects has expanded from the field management focusing on field storage, transportation, and lifting to the whole supply chain from the materials to field. The expansion of the supply chain management can raise the possibilities of leaner production, which enables shortened lead time of the difficult-to-operate materials, and prevents the work interference or delay. However, the expanded management range requires more information and management than an existing management style currently used for factory production of iron frame, curtain wall, PC, etc. In addition, there are limitations that expand the existing management style into the new supply chain management in construction projects and therefore it is required to automate the existing management style in order to extend the management range. The objective of this study is to propose the process and equipment that can manage the supply chain of the materials which range from the factory production to the field storage based on RFID/USN techniques, introducing small-sized transportation equipment(intelligent pallet), the vehicle tool kit(intelligent trailer), and in-and-out management equipment(Gate Sensor) as a prototype to effectively develop the appliances for operating the proposed process, and present the application possibility of the appliances. The full paper will present then the test results that the proposed appliances for the supply chain management automatically transmit and receive the generated information between the appliances or the appliance and sever under various wireless network circumstances such as zigbee, wibro, Wi-Fi, and CDMA.

• Journal of Drive and Control
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• v.17 no.4
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• pp.8-14
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• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.

• Journal of Drive and Control
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• v.17 no.1
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• pp.37-43
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• 2020

An intelligent excavator can be divided into Machine Guidance (MG), semi-automatic, and unmanned by technology. The MG technology excavator is equipped with a tilt sensor on each link of the excavator and a GPS is installed on the excavator body to inform the user of the position of the excavator bucket end. Machine control (MC) technology that assists the user's work can be divided into semi-automatic and fully automatic technology. The semi-automatic MC equipment has already been commercialized by Komatsu and Caterpillar. The MC excavator is equipped with an electro-hydraulic system, sensors and controllers to control the excavator bucket end according to the user's needs. In this study, the semi-automated excavator modified based on manual excavator, is equipped with an electro-hydraulic system, a controller system, multi-sensors and a control algorithm is developed to assist in excavation work such as leveling and grading. By applying the developed technology, it was possible to confirm productivity improvement compared to manual digging and leveling work. In the future, further research to improve the accuracy of the hydraulic precision control and collaborative work with heterogeneous construction equipment such as dump truck and automated collaboration tasks technology could be developed.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.736-743
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• 2022

Construction workers experience a high rate of fatal incidents from mobile equipment in the industry. One of the major causes is the decline in the acoustic condition of workers due to the constant exposure to construction noise. Previous studies have proposed various ways in which audio sensing and machine learning techniques can be used to track equipment's movement on the construction site but not on the audibility of safety signals. This study develops a novel framework to help automate safety surveillance in the construction site. This is done by detecting the audio sound at a different signal-to-noise ratio of -10db, -5db, 0db, 5db, and 10db to notify the worker of imminent dangers of mobile equipment. The scope of this study is focused on developing a signal processing model to help improve the audible sense of mobile equipment for workers. This study includes three-phase: (a) collect audio data of construction equipment, (b) develop a novel audio-based machine learning model for automated detection of collision hazards to be integrated into intelligent hearing protection devices, and (c) conduct field experiments to investigate the system' efficiency and latency. The outcomes showed that the proposed model detects equipment correctly and can timely notify the workers of hazardous situations.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.209-212
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• 2013

Global warming and climate change is now an important issue in every industry. Construction is not an exception. Greenhouse Gases (GHG) are emitted by construction activities such as fuel usage in construction equipment and so on. In light of this, Intelligent Excavating System (IES), which is a robotic excavator with site modeling capability, is developed by a research consortium formed in Korea to improve productivity, quality, and safety of the traditional earthwork. This paper presents that energy saving effect of IES in comparison to traditional method. Through this review, we propose a research strategy to achieve carbon reduction goals in construction industry.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.305-310
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• 2008

A lot of changes are required in a management method of a project because the character of construction projects gets bigger and higher gradually. Especially, for the efficiency of the management method the plans of various viewpoints focused on the construction supply chain field that the technical application of Ubiquitous Technologies such as RFID/USN is being advanced actively are presented. Recently, the introduction of the intelligent equipment which is developed for intelligence of construction site requires the new process model in the construction supply chain management on the construction site. Therefore, this study is to propose the intelligent construction supply chain reference model development in order to provide the guide that the numerous materials for construction could easily be applied in the changed process, as mentioned above, by overcoming the limit of the existing construction supply chain process which is proposed as bar codes and RFID/USN based individual material types and reflecting the change factors like the intelligent equipment of construction supply chain management.