• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.9
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• pp.1063-1070
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• 2011

The manufacturing execution system (MES) for product production handles different production processes according to the product characteristics and different types of data according to the process being considered. For efficiently providing the data pertaining to production equipment to production systems such as the MES, data collection through the equipment interface is required for obtaining the production data pertaining to field equipment. In this paper, a method is proposed for collecting the production data through the equipment interface in order to collect the various types of production-equipment data from the field. The proposed method is applied to a real manufacturing system to verify its efficiency. A more powerful MES can be constructed with a data acquisition system that acquires the status data at the shop-floor level.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.10
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• pp.914-922
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• 2004

In this study, measurement and analysis of energy consumption of a research building have been conducted. The energy audit procedure includes monitoring of electricity and LNG consumption over a period of three yews from 2000 to 2002. Data acquisition system for collecting energy consumption data of HVAC equipment such as chillers, fan filter units, AHUs, cooling towers, boilers, pumps, fan coil units, air compressors and etc. has been installed in a building located in Seoul. Data collected at an interval of 1 minute are analyzed for studying the energy consumption pattern of a research building. Percentage of energy consumption of all HVAC equipment is $51.0\%$ in 2000, $55.4\%$ in 2001, and $62.3\%$ in 2002, respectively. Electricity consumption of chillers accounts for $17.6\%$ of the total energy consumption, which is the largest. Annual energy consumption-rate per unit area is $840.5Mcal/m^2{\cdot}y$ in 2000, $1,064.8Mcal/m^2{\cdot}y$ in 2001, and $1,393.0Mcal/m^2{\cdot}y$ year 2002, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.321-322
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• 2022

Recently, in the field of health care, health management topics are being dealt with a lot. In particular, services are concentrated in the field of exercise, and many exercise equipment fused with the 4th industry-based technology are also appearing. In general, a form of collecting user's exercise information by mounting various sensors on exercise equipment and linking services based on this is representative. In this paper, we propose an efficient data transmission based on the design in the process of transmitting the exercise data generated by the equipment to the smartphone through the Bluetooth-based IoT sensor and transmitting it back to the exercise information analysis platform.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.515-524
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• 2022

To effectively collect, manage, and share the maritime traffic information, it is necessary to identify the technology trends concerning this particular information and analyze its current status and problems. Therefore, this study observes the domestic and foreign technology trends involving maritime traffic information while analyzing and summarizing the current status and problems in collecting, managing, and sharing it. According to the data analysis, the problems in the collecting stage are difficulties in collecting visual information from long-distance radars, CCTVs, and cameras in areas outside the LTE network coverage. Notably, this explains the challenges in detecting smuggling ships entering the territorial waters through the exclusive economic zone (EEZ) in the early stage. The problems in the management stage include difficult reductions and expansions of maritime traffic information caused by the lack of flexibility in storage spaces mostly constructed by the maritime transportation system. Additionally, it is challenging to deal with system failure with system redundancy and backup as a countermeasure. Furthermore, the problems in the sharing stage show that it is difficult to share information with external operating organizations since the internal network is mainly used to share maritime transportation information. If at all through the government cloud via platforms such as LRIT and SASS, it often fails to effectively provide various S/W applications that help use maritime big data. Therefore, it is suggested that collecting equipment such as unmanned aerial vehicles and satellites should be constructed to expand collecting areas in the collecting stage. In the management and sharing stages, the introduction and construction of private clouds are suggested, considering the operational administration and information disclosure of each maritime transportation system. Through these efforts, an enhancement of the expertise and security of clouds is expected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.681-691
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• 2017

This empirical study evaluated the 2016 Cheonan KIEMSTA(Korea International Exhibition of Machinery, Equipment, Science and Technology for Agriculture) based on an exhibitor's view. A total of 15 items of importance and performance were selected and 4 quadrants were analyzed for further analysis. The results revealed the following significant factors:concentration region with generating sales, exploring market opportunities in a new region, and meeting key decision makers; the Overkill region with collecting information regarding thecompetitor's product, demonstrating thecompany's capability, increasing staff's trade show experience, and training the sales teams; Low priority region with discovering new products, exploring export opportunities in a foreign market, and gaining an edge over competitors who are not exhibiting; and Keep up the work region bymaintaining relationships with existing customers, collecting market information, benchmarking competitor's position, introducing new product, and motivating sales people.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.75-80
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• 2017

Recently, there has been growing interest in spatial data that combines information and communication technology with smart cities. The high-precision LiDAR (Light Dectection and Ranging) equipment is mainly used to collect three-dimensional spatial data, and the acquired data is also used to model geographic features and to manage plant construction and cultural heritages which require precision. The LiDAR equipment can collect precise data, but also has limitations because they are expensive and take long time to collect data. On the other hand, in the field of computer vision, research is being conducted on the methods of acquiring image data and performing 3D reconstruction based on image data without expensive equipment. Thus, precise 3D spatial data can be constructed efficiently by collecting and processing image data using CCTVs which are installed as infrastructure facilities in smart cities. However, this method can have an accuracy problem compared to the existing equipment. In this study, experiments were conducted and the results were analyzed to increase the number of extracted matching points by applying the feature-based method and the area-based method in order to improve the precision of 3D spatial data built with image data acquired from stereo CCTVs. For techniques to extract matching points, SIFT algorithm and PATCH algorithm were used. If precise 3D reconstruction is possible using the image data from stereo CCTVs, it will be possible to collect 3D spatial data with low-cost equipment and to collect and build data in real time because image data can be easily acquired through the Web from smart-phones and drones.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.149-156
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• 2011

There is much information of equipment in shop floor because the manufacturing processes are different as the equipment within the manufacturing process is varied. To provide effective process information to MES and other production systems, the DAS requires an equipment monitoring system that takes into account the characteristics of the equipment on the shop floor. In this study, we proposed some methods for collecting the required information about various equipments on a shop floor. The equipments such as CNC can be interfaced with the DAS by using a PLC-based method and a sensor-based interface board can be used to interface general equipments. The proposed methods can be used to collect information on the shop floor in real-time. Moreover these methods are very adaptive and can be easily modified according to the changes made to the shop floor. The information about a real shop floor acquired by employing these methods is saved in a database and the can be provided to a supervisor and MES so that they are aware of the status of the shop floor.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.5
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• pp.35-42
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• 2018

In order to seek out methods to reduce safety accidents caused by construction machinery and equipment, this study collects data about safety accidents and draws main risk factors by construction from the data, through SNA. It aimed to suggest safety management points to be used in future construction fields, by analyzing risk index of such factors. The finding can be summarized: First, Backhoe Bucket is the risk factor for crash accidents of average workers in earth works; boring machines-maintenance is the risk factor for fall accidents of construction machinery operators in foundation works; bending machine-reinforcing rod processing is the risk factor for jamming accidents of reinforcing rod engineers in frame works; and mobile crane-hook is the risk factor for crash accidents of average workers in lifting works. Second, works can be arranged in turn, according to the risk index: earth, lifting, frame and foundation works. Risk factors can be also arranged according to the risk index: Backhoe in earth works, pile drivers in foundation works, bending machines in frame works and mobile cranes in lifting works. This study has some limits, in that it only analyzed main machinery/equipment, among various kinds of them, for earth, foundation, frame and temporary works (lifting works) and used data collected over three years. Therefore, it is necessary to conduct an analysis using big data, by collecting additional data about a lot of machinery/equipment in future construction fields.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3898-3906
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• 2023

The paper notes that the most common way of handling spent nuclear fuel (SNF) of power reactors is its temporary long-term dry storage. At the same time, the operation of the dry spent fuel storage facilities almost never use the modern capabilities of information systems in safety control and collecting information for the next studies under implementation of aging management programs. The author proposes a structure of an information system that can be implemented in a dry spent fuel storage facility with ventilated storage containers. To control the thermal component of spent fuel storage safety, a database structure has been developed, which contains 5 tables. An algorithm for monitoring the thermal state of spent fuel was created for the proposed information system, which is based on the comparison of measured and forecast values of the safety criterion, in which the level of heating the ventilation air temperature was chosen. Predictive values of the safety criterion are obtained on the basis of previously published studies. The proposed algorithm is an implementation of the information function of the system. The proposed information system can be used for effective thermal monitoring and collecting information for the next studies under the implementation of aging management programs for spent fuel storage equipment, permanent control of spent fuel storage safety, staff training, etc.