• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.83-98
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• 2021

The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.120-127
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• 2016

Due to the enlargement and high-rise of reinforced concrete structure, the application of high functional material is required. However, high-strength bar is recently introduced to the country and the material is insufficient to measure the variation of quantity of rebar quantitatively when using high-strength bar. For these reasons, this study is to provide useful data in cost decision making when applying high-strength bar at a stage of architectural project planning. For residence-commerce complex buildings, we set up six types of conditions such as in case of using only rebar, in case of using only high-strength bar, in case of using rebar mixed with high-strength bar and so on. With the standard of study model 1 that applies only SD400 regardless of rebar diameter, the analyzed result of rebar variation and the cost change of construction in other study model is as follows. When the rebar amount and cost in study model I was 100%, each ratio was 88.3% and 90.5% in study model II, 80.2% and 83.4% in study model III, 91.9% and 93.5% in study model IV, 88.9% and 87.7% in study model V and 82.4% and 85.5% in study model VI. Therefore, in case of rebar amount and construction cost, study model III was evaluated as the best that was applied only SD600.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.50-60
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• 2015

Pedestrians not only walk along roads, but also pass through buildings or across open spaces. This study defines these unusual walk routes as social path. Social path is an informal pedestrian route that is not considered in a pedestrian network, even though it should be regarded as pedestrian route considering the fact that many people actually use this path. In response, current study related to travel behavior cannot evaluate properly due to lack of consideration for realistic travel behavior such as social path. In order to deal with this situation, this study analyzes the effect of social path at two complex centers in Seoul. Evaluation indices are service area analysis and urban network analysis which is one of the spatial network analysis. In particular, we subdivide the network into three steps by the level of network building and analyze each step. As a result, it is revealed that step three which includes social path shows the greatest improvement in pedestrian accessibility. In this regard, we confirm that social path should be considered when evaluating pedestrian accessibility in further studies. Furthermore, a lot of undervalued facilities will be re-appraised in the field of travel behavior.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.227-239
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• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.