• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.55-68
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• 2014

Some infrastructure these days is usually constructed under the ground for it to not interfere the foot-traffic of pedestrians, and thus, it is difficult to visually confirm the accurate location of the site where the establishments must be buried. These technical difficulties increase the magnitude of the problems that could arise from over-reliance on the experience of the worker or a mere blueprint. Such problems include exposure to flood and collapse. This paper proposes a constructor-oriented visualization system via mobile gadgets in general construction sites with occluded structures. This proposal is consisted with three stages. First, "Stage of detecting manhole and extracting features" detects and extracts the basis point of occluded structures which is unoccluded manhole. Next, "Stage of tracking features" tracks down the extracted features in the previous stage. Lastly, "Stage of visualizing occluded constructions" analyzes and synthesizes the GPS data and 3D objects obtained from mobile gadgets in the previous stages. This proposal implemented ideal method through parallel analysis of manhole detection, feature extraction, and tracking techniques in indoor environment, and confirmed the possibility through occluded water-pipe augmentation in real environment. Also, it offers a practical constructor-oriented environment derived from the augmented 3D results of occluded water-pipings.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.1-9
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• 2022

Localization systems can be used with various circumstances like measuring population movement and rescue technology, even in security technology (like infiltration detection system). Vision sensors such as camera often used for localization is susceptible with light and temperature, and can cause invasion of privacy. In this paper, we used ultra-wideband radar technology (which is not limited by aforementioned problems) and machine learning techniques to measure the number and location of occupants in other indoor spaces behind the wall. We used four different algorithms and compared their results, including extremely randomized tree for four different situations; detect the number of occupants in a classroom, split the classroom into 28 locations and check the position of occupant, select one out of the 28 locations, divide it into 16 fine-grained locations, and check the position of occupant, and checking the positions of two occupants (existing in different locations). Overall, four algorithms showed good results and we verified that detecting the number and location of occupants are possible with high accuracy using machine learning. Also we have considered the possibility of service expansion using the oneM2M standard platform and expect to develop more service and products if this technology is used in various fields.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.5
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• pp.128-134
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• 2014

Recently, design and construction of street tunnels tend to focus on cost reduction and preservation of nature. Accordingly, research is actively being carried out to quickly detect fires when they occur in tunnels, which have partially closed structures. Among such research, fire detection methods using optical fiber sensors have a wide bandwidth and fast transmission speed, while using light as a medium. Therefore, it does not receive electrical interference and there is almost no loss of information during transmission, while also having little noise as well. In relation to this, a fire monitoring system that can accurately detect the location of fires in real time using shape memory alloy and optical cables was developed in this study. In order to verify the developed method, light loss measurement test was conducted according to indoor temperature changes, while also conducting fire simulation tests by installing test beds in common underground zones with different external environments of temperature and distance. Upon carrying out experiments, the fire monitoring system developed in this study was found to be able to detect fires in long distance sections in real time.