• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.297-311
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• 2021

Around the world, there is an increasing interest in Digital Twin cities. Although geospatial data is critical for building a digital twin city, currently-established spatial data cannot be used directly for its implementation. Integration of geospatial data is vital in order to construct and simulate the virtual space. Existing studies for data integration have focused on data transformation. The conversion method is fundamental and convenient, but the information loss during this process remains a limitation. With this, standardization of the data model is an approach to solve the integration problem while hurdling conversion limitations. However, the standardization within indoor space data models is still insufficient compared to 3D building and city models. Therefore, in this study, we present a comparative analysis of data models commonly used in indoor space modeling as a basis for establishing a generic indoor space feature model. By comparing five models of IFC (Industry Foundation Classes), CityGML (City Geographic Markup Language), AIIM (ArcGIS Indoors Information Model), IMDF (Indoor Mapping Data Format), and OmniClass, we identify essential elements for modeling indoor space and the feature classes commonly included in the models. The proposed generic model can serve as a basis for developing further indoor feature models through specifying minimum required structure and feature classes.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.184-188
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• 2021

In general, digital signage is a next-generation smart media that provides various information and advertisement services to many people indoors or outdoors using the Internet. Recently, digital signage is rapidly spreading in such a small indoor environment, that is, in an area closely related to daily life, for example, inside an elevator. However, in this kind of indoor environment where the stay time of persons is extremely limited, it would be not easy for them to keep advertisements in the user memory for a long time. In the digital signage display installed in an indoor environment, it is possible to think about the possibility for a function such as expanding the screen to a user's smartphone, which is now widely spread, to contain, store, and use the transmitted content. In this paper, we propose a method to extend the display of digital signage contents to personal smart phones with interaction function in such a limited environment. In order to make the system operation, the proposed system was verified by confirming the result of dual screen implementation in a smart phone through the prototype implementation of a digital signage system in an embedded Linux environment.

• Journal of Korea Game Society
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• v.21 no.2
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• pp.33-42
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• 2021

Despite people's expectation, COVID-19 has turned out to be a burden people have to carry for a while. The age of "Untact" has come. While many outdoor activites have been restricted, it is crucial to find other ways to maintain physical/mental health ideally indoors. As a mediative gesture, people are now taking notice of 'Console games', through which they can party, travel, and exercise in virtual reality even harder than in real life. In thesis, we will examine Nintendo Switch Consoles in relation to direction Korean game industry has to take to maintain people's physical/mental health.

• Journal of the Korean Wood Science and Technology
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• v.47 no.6
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• pp.761-769
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• 2019

In modern societies, people spend most of their time indoors and the temperature and humidity controlled by electrical appliances have a considerable effect on their emotions and health. However, improper operation of the artificial facilities frequently creates substances that are harmful to our body. The importance of controlling the natural humidity of interior materials has therefore attracted significant attention. This study was aimed at quantifying the hygroscopic property of some interior finishing wooden materials. Dried and heat-treated yellow poplar (Liriodendron tulipifera) lumbers, oriented strand board, and plywood were selected for this experiment. The moisture adsorption and desorption rates of wooden materials were measured (ISO 24353). Furthermore, the effects of morphological, physical and chemical factors, such as surface microstructure, roughness, and functional groups, on the hygroscopicity were evaluated. The results of this study should contribute to improved accuracy of hygroscopic-property assessments performed on wooden interior materials.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.403-406
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• 2009

In this paper, we propose a method for deciding permission from the ATM(Automated Teller Machine) using face detection. First, we extract skin areas and make candidate face images from an input image, and then detect a face using Adaboost(Adaptive Boosting) algorithm. Next, proposed method executes a template matching for making a decision on whether to wear accessories like sunglasses or a mask in detected face image. Finally, this method decides whether to permit ATM service using this result. Experimental results show that proposed method performed well at indoors ATM environment for detecting whether to wear accessories.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.62-63
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• 2019

Currently, polymer-based tile cement (Thin-bed method) and epoxy adhesive (Thick-bed method) are mainly used as tile adhesive for polishing and porcelain. In the case of epoxy adhesive, there is a low economic efficiency, there is a problem that the work efficiency is reduced by mixing the resin and the hardener. In particular, the epoxy contains a bisphenol A and amine component, there is a risk of workable disease when a worker is exposed to odor and harmful gases generated in the epoxy adhesive for a long time. Against this background, it is necessary to analyze the hazards of using epoxy adhesives indoors, and develop cementitious high performance tile adhesive products with significantly lower hazards than epoxy adhesives.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.191-196
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• 2021

In this paper, we implemented an image sensor module possible of detecting color temperature in an indoor environment. The color temperature information in the video information acquired by the image sensor was matched with a color difference illuminometer to produce an LUT. An algorithm was developed so that color temperature information according to the received RGB values can be automatically calculated. As a result of measuring the color temperature with an image sensor indoors, an accurate result of less than 5.91% was obtained compared to the reference value. It was confirmed that the uniformity of 23.5% or more was excellent compared to the color temperature measurement result using a color sensor.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.260-267
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• 2021

In this paper, we intend to use a new mixed model of YoloV5 and DeepSort. For fire detection, we want to increase the accuracy by automatically extracting the characteristics of the flame in the image from the training data and using it. In addition, the high false alarm rate, which is a problem of fire detection, is to be solved by using this new mixed model. To confirm the results of this paper, we tested indoors and outdoors, respectively. Looking at the indoor test results, the accuracy of YoloV5 was 75% at 253Frame and 77% at 527Frame, and the YoloV5+DeepSort model showed the same accuracy at 75% at 253 frames and 77% at 527 frames. However, it was confirmed that the smoke and fire detection errors that appeared in YoloV5 disappeared. In addition, as a result of outdoor testing, the YoloV5 model had an accuracy of 75% in detecting fire, but an error in detecting a human face as smoke appeared. However, as a result of applying the YoloV5+DeepSort model, it appeared the same as YoloV5 with an accuracy of 75%, but it was confirmed that the false positive phenomenon disappeared.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.37-44
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• 2022

With the outbreak of COVID-19, non-face-to-face activities such as remote learning and telecommuting have increased rapidly. As a result, the number of people staying at home and the number of hours spent inside the house have also increased since the pandemic. Our team had previously worked on methods for detecting abnormal conditions in a person's health in various circumstances within the house by converging single sensor-based algorithms. In our previous research, we installed IoT sensors indoors to detect people emergency situations requiring aids, the scope of detection was limited to indoor space due to the limitation in sensors. In this study, we have come up with a system that integrates our previous study with a new method for detecting abnormal conditions in outdoor environments using outdoor security cameras and wearable devices. The proposed system enables users to be notified of emergency situations in both indoor and outdoor areas and respond to them as quickly as possible.

• Korean Journal of Artificial Intelligence
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• v.11 no.1
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• pp.25-29
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• 2023

In this paper, the purpose is to create a standard of AI training dataset type for commercial space design. As the market size of the field of space design continues to increase and the time spent increases indoors after COVID-19, interest in space is expanding throughout society. In addition, more and more consumers are getting used to the digital environment. Therefore, If you identify trends and preemptively propose the atmosphere and specifications that customers require quickly and easily, you can increase customer trust and conduct effective sales. As for the data set type, commercial districts were divided into a total of 8 categories, and images that could be processed were derived by refining 4,009,30MB JPG format images collected through web crawling. Then, by performing bounding and labeling operations, we developed a 'Dataset for AI Training' of 3,356 commercial space image data in CSV format with a size of 2.08MB. Through this study, elements of spatial images such as place type, space classification, and furniture can be extracted and used when developing AI algorithms, and it is expected that images requested by clients can be easily and quickly collected through spatial image input information.