• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.883-887
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• 2011

Location-based service (LBS) is becoming an important part of the information technology (IT) business. Localization is a core technology for LBS because LBS is based on the position of each device or user. In case of outdoor, GPS - which is used to determine the position of a moving user - is the dominant technology. As satellite signal cannot reach indoor, GPS cannot be used in indoor environment. Therefore, research and study about indoor localization technology, which has the same accuracy as an outdoor GPS, is needed for "seamless LBS". For indoor localization, we consider the IEEE802.11 WLAN environment. Generally, received signal strength indicator (RSSI) is used to obtain a specific position of the user under the WLAN environment. RSSI has a characteristic that is decreased over distance. To use RSSI at indoor localization, a mathematical model of RSSI, which reflects its characteristic, is used. However, this RSSI of the mathematical model is different from a real RSSI, which, in reality, has a sensitive parameter that is much affected by the propagation environment. This difference causes the occurrence of localization error. Thus, it is necessary to set a proper RSSI model in order to obtain an accurate localization result. We propose a method in which the parameters of the propagation environment are determined using only RSSI measurements obtained during localization.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.3
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• pp.251-258
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• 2001

Indoor and outdoor nitrogen dioxide(NO$_2$) concentrations of 122 houses were measured and compared with measurements of personal NO$_2$ exposure simultaneously . Time activity patterns were used to determine the impacts on NO$_2$ exposure assessment and time weighed average model to estimate the personal NO$_2$ exposure. Most people spent their times more than 80% of indoor and more than 50% in home, respectively. Personal NO$_2$ esposure was found to be significantly associated with both indoor NO$_2$ concentration(r=0.70) and outdoor NO$_2$ concentration (r=0.68). Using time weighted average model, personal NO$_2$ exposure was estimated with NO$_2$ measurements in indoor home, indoor workplace and outdoor home. The estimated NO$_2$ measurements were significantly correlated with measured personal exposures(r=0.69, N=122). For the difference between measured and estimated NO$_2$ exposures by multiple regression analysis showed that NO$_2$ concentrations in near workplace and other outdoors of no NO$_2$ measurements affected the personal NO$_2$ exposures(p=0.023).

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.47-55
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• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.

• Spatial Information Research
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• v.22 no.2
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• pp.31-44
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• 2014

According to the purpose of applications, the application program will utilize the most suitable data model and 3D modeling data would be generated based on the selected data model. In these reasons, there are various data sets to represent the same geographical features. The duplicated data sets bring serious problems in system interoperability and data compatibility issues, as well in finance issues of geo-spatial information industries. In order to overcome the problems, this study proposes a spatial data fusion method using topological relationships among spatial objects in the feature classes, called Topological Relation Model (TRM). The TRM is a spatial data fusion method implemented in application-level, which means that the geometric data generated by two different data models are used directly without any data exchange or conversion processes in an application system to provide indoor LBSs. The topological relationships are defined and described by the basic concepts of IndoorGML. After describing the concepts of TRM, experimental implementations of the proposed data fusion method in 3D GIS are presented. In the final section, the limitations of this study and further research are summarized.

• 한국디지털정책학회:학술대회논문집
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• 2005.06a
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• pp.277-283
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• 2005

In this paper, the performance of high data rate-wirelesss personal area network(HDR-WPAN) system is analyzed under multi-path indoor channel. In the analysis, Saleh and Valenzuel channel model is used for the multi-path indoor channel. From the results, HDR-WPAN system has reliability of 10-5 at Eb/No = 18.5dB in multi-path indoor channel. It is a suitable performance for high data rate personal area network applications.

• Journal of the Ergonomics Society of Korea
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• v.18 no.2
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• pp.91-102
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• 1999

There are various kinds of good feelings in indoor environment such as comfort, pleasure, delight, refreshment, geniality, etc. Each feeling is interrelated with other complex elements of senses such as warmth, coldness, calmness, clearness, brightness, etc. In this paper, we described what is good feeling in indoor environment, and developed elements of good feelings using Emotion & Sensibility engineering approach. Resultant elements of good feelings were "comfort," "refreshment," and "freshness." Secondary, we investigated the relationships of these elements with certain elements of senses. "Comfort" is related with "warmth, calmness, brightness, and very clearness in indoor air." "Refreshment" and "freshness" are related with "coldness, moderately calmness, very brightness, and very clearness in indoor air." The relationships were formulated as a fuzzy model. By applying human intuition to this model, we could determine physical ranges of "comfort, refreshment, and freshness."

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.5
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• pp.373-381
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• 2002

Benzene, Ethyl-benzene, Toluene and Xylene (BTEX) can be released to a groundwater in case of the oil leakage from underground storage tank of a gas station. These chemicals are found to contribute to the total inhalation risk from contaminated indoor air. This study presents the assessment of a human exposure to such chemicals released from the groundwater into indoor air. At first, a 2-compartment model is developed to describe the transfer and distribution of the chemicals released from groundwater in a house through showering, washing clothes, and flushing toilets. The model is used to estimate a daily human exposure through inhalation of such BTEX for adults based on two sets of exposure scenarios. Finally, a sensitivity analysis is used to identify important parameters. The results obtained from the study would help to increase the understanding of risk assessment issues associated with the indoor pollution by BTEX released from contaminated groundwater.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.3
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• pp.217-223
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• 2001

There exist a number of approaches which can evaluate ventilation and indoor air quality. The measurement and analysis of indoor carbon dioxide concentrations can be useful for evaluating indoor air quality and ventilation. This paper describes a numerical analysis of carbon dioxide concentrations for evaluating indoor air quality and ventilation and the factors the need to be considered in their use. The conditions of this numerical analysis are tow types of positions and inlet velocities of ventilation system in a two-dimensional model of an apartment house. The simulation results could be used as a base data for further analysis for ventilation design of other industrial processes producing a proper ventilation system for a healthier and more comfortable environment in a building.

• ETRI Journal
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• v.28 no.2
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• pp.247-249
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• 2006

In the development of a new wireless communications system, a versatile and accurate radio channel for indoor communications is needed. In particular, the investigation of radio transmission into buildings is very important. In this letter, we present an improved three-dimensional electromagnetic wave propagation prediction model for indoor wireless communications that takes into consideration building penetration loss. A ray tracing technique based on an image method is also employed in this study. Three-dimensional models can predict any complex indoor environment composed of arbitrarily shaped walls. A speed-up algorithm, which is a modified deterministic ray tube method, is also introduced for efficient prediction and computation.

• KIEAE Journal
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• v.10 no.6
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• pp.67-72
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• 2010

This study was conducted to examine the change of heating environment with the creation of an indoor water space. Living environments and comfort of dwellers can be improved by utilizing the physical properties of water effectively. This study focuses on the basic examination of the effect of water space and the environmental effects of water space by experiment. Two identical models were fabricated to compare the changes in indoor temperature and humidity with and without a water space. With the water space, temperature was reduced by an average of $0.55^{\circ}C$ a day and moisture content increased by an average of 4%. As a result, it was possible to obtain quantitative data on water space's temperature reduction and humidity control capacities. This study is expected to provide basic information for further studies on the effect of water spaces in various buildings.