• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.131-140
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• 2013

Due to the limitations of the existing indoor positioning system depending on the radio wave, at present, it is required to introduce a new method in order to improve the accuracy in indoor environment. Recently, bio-inspired technology has become the future core technology. Thus, this study examined the accurate positioning method applying the abilities that animals with homing instinct measure their position by searching geomagnetic field with the use of their biomagnets. In order to confirm the applicability of geomagnetic field, a new source for indoor positioning, this study separated the constituent materials and building structure and designed the structures that can carry the actual magnetic field sensor and the data collection module. Subsequently, this study investigated the applicability of geomagnetic field as a positioning source by establishing the positioning system of Fingerprint method. In performance evaluation of the positioning system, the geomagnetic strength-based positioning system was similar to or approximately 20 percent higher than the wireless LAN-based positioning system in the buildings with the existing wireless LAN. Thus, in the environment without infrastructure for indoor positioning, the geomagnetic, an independent earth resource, can make it possible to realize the indoor positioning.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.91-100
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• 2023

The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.

• KIEAE Journal
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• v.15 no.5
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• pp.107-112
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• 2015

Purpose: This study desires to investigate an effect of indoor temperature, humidity, and illuminance targeting a planting system of double-skin facade and cavity space adjacent to the outside within a certain period of winter. Through this, the study suggests a basic material about an energy conservation effect of double window system using planting to reduce heating load of a building in winter, so desires to contribute to indoor thermal comfort effect and illuminance correction study of double window and indoor plant. Method: Considering effects such as day and night climatic elements and air conditions in winter, illuminance measurement was conducted through a double-skin facade of space, a subject of the measurement, on the basis of practical residence time of a resident, and this study analyzed characteristics of indoor illuminance about this. The study measured and compared a change of insolation, dry-bulb temperature, and relative humidity at each indoor-outdoor measuring point, so measured and compared characteristics of an indoor temperature effect by elements of double-skin facade and indoor plant. Result: Through this study, the researcher could determine that indoor plant within double window in winter not only blocks solar radiation but also photosynthesizes, so is somewhat disadvantageous to winter thermal comfort reducing heating load. In addition, solar radiation going through interior plays a role to bring down somewhat high humidity to about 50% of reasonable humidity, so plays a direct role of maintenance of comfortable indoor space. Although there are effects such as blocking of solar radiation and temperature reduction, this has a positive influence on humidity control and proper illuminance distribution. The researcher could determine that illuminance, temperature, and humidity by solar radiation penetration for the whole measuring time play a role to supplement indoor environment mutually.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.1
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• pp.25-37
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• 2002

The purpose of the study was to survey the distribution patterns of inorganic elements of PM-10 in the various indoor environments and analyze the pollution patterns of aerosol in various places of indoor environment using a pattern recognition method based on cluster analysis and disjoint principal component analysis. A total of 40 samples in the indoor had been collected using mini-vol portable samplers. These samples were analyzed for their 19 bulk inorganic compounds such as B, Na, Mg, Al, K, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Ce, and Pb by using an ICP-MS. By applying a disjoint principal component analysis, four patterns of the indoor air pollutions were distinguished. The first pattern was identified as a group with high concentrations of PM-10, Na, Mg, and Ca. The second pattern was identified as a group with high concentrations B, Mg, At, Ca, Fe, Cu, and Ba. The third pattern was a group of sites with high concentrations of K, Zn. Cd. The fourth pattern was a group with low concentrations PM-10 and all inorganic elements. This methodology was found to be helpful enough to set the criteria standard of indoor air quality, corresponding pollutants, and classification of indoor environment categories when making an indoor air quality law.

• KIEAE Journal
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• v.15 no.2
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• pp.117-122
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• 2015

Purpose: Generally, 30% of the total energy consumption in office building is used for artificial indoor lightings, and almost 75-85% of electric power in fluorescent and Light-Emitting Diode (LED) lightings can be dissipated as a form of heat into indoor environment. The heat generated by indoor lightings can cause the increase of cooling load in office buildings. Thus, it its important to consider indoor lightings as a heat and light source, simultaneously. Method: In this study, we installed two kinds of indoor lightings including fluorescent and LED lightings and measured surface temperature of both indoor lightings. In addition, we obtained ambient temperature of indoor space and finally calculated total heat dissipated from plenum area and surface of lightings. Result: Total indoor heat gain was 87.17Wh and 201.36Wh in cases of six 40W-LED lightings and 64W-fluorescent lightings, respectively.

• Analytical Science and Technology
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• v.19 no.6
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• pp.544-552
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• 2006

Emission tests were carried out to investigate the characteristics of concentration according to flooring sort using small chamber method. The target Volatile Organic Compounds (VOC) included 27 individual compounds of environmental concern, which were determined by adsorption sampling and thermal desorption coupled with GC/MS method and by DNPH cartridge/HPLC method. The emission factor of Total Volatile Organic Compounds (TVOC) and Formaldehyde (HCHO) was detected $0.3mg/m^2{\cdot}h$ and $0.2mg/m^2{\cdot}h$ respectively, and the floorings of 37 (9 PVC Tile, 10 PVC Sheet, 18 Flooring) were satisfied emission standard. TVOC emission factor appeared in order of concentration of PVC Sheet, PVC Tile, and floor flooring, while HCHO was detected very high emission factor (as $0.4mg/m^2{\cdot}h$) at floor flooring above PVC series (as $0.001mg/m^2{\cdot}h$).

• Spatial Information Research
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• v.22 no.6
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• pp.33-43
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• 2014

As the number of people who live indoor space has been increased, the interest in 3D indoor spatial information has been grown. Object-Oriented 3D indoor space modeling including indoor spatial information has performed in level of detail 4, and modeling data is able to be constructed based on various raw data which are as-built drawing, laser scanning, BIM data, and camera. 3D indoor space modeling has been worked based on established indoor space modeling process, and the result can be used for various application fields such as indoor space pedestrian navigation, facility management, disaster management, and so on. However, the modeling process has limitations to perform indoor space modeling efficiently, because the process is complicated and wastes time at modeling work. In this paper, we propose evaluation on practical use of raw data for 3D indoor space modeling purpose on supporting efficient indoor space modeling through analyzing the established process. Therefore, we define the requirements to evaluate the practical use of raw data and propose the verification method. In addition, as-built drawing which has been used in Seoul 3D indoor space modeling project will be applied to proposed method as a raw data.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.8
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• pp.742-747
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• 2004

Outdoors we can easily acquire our accurate location by GPS. However, the GPS signal can't be acquired indoors because of its weak signal power level. Adequate positioning method is demanded for many indoor positioning applications. At present, wireless local area network (WLAN) is widely installed in various areas such as airport, campus, and park. This paper proposes a positioning algorithm using WLAN signal strength to provide the position of the WLAN user indoors. There are two methods for WLAN based positioning, the signal propagation method uses signal strength model over space and the empirical method uses RF power propagation database. The proposed method uses the probability distribution of the power propagation and the maximum likelihood estimation (MLE) algorithm based on power strength DB. Test results show that the proposed method can provide reasonably accurate position information.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1483-1495
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• 2007

Thanks to IEEE 802.11 technique, accessing Internet through a wireless LAN(Local Area Network) is possible in the most of the places including university campuses, shopping malls, offices, hospitals, stations, and so on. Most of the APs(access points) for wireless LAN are supporting 2.4 GHz band 802.11b and 802.11g protocols. This paper is introducing a C# library function which can be used to read RSSIs(Received Signal Strength Indicator) from APs. An LBS(Location Based Service) estimates the current location of the user and provides useful user's location-based services such as navigation, points of interest, and so on. Therefore, indoor, LBS is very desirable. However, an indoor LBS cannot be realized unless indoor position ing is possible. For indoor positioning, techniques of using infrared, ultrasound, signal strength of UDP packet have been proposed. One of the disadvantages of these techniques is that they require special equipments dedicated for positioning. On the other hand, wireless LAN-based indoor positioning does not require any special equipments and more economical. A wireless LAN-based positioning cannot be realized without reading RSSIs from APs. Therefore, our C# library function will be widely used in the field of indoor positioning. In addition to providing a C# library function of reading RSSI, this paper introduces implementation of indoor positioning modules making use of the library function. The methods used in the implementation are K-NN(K Nearest Neighbors), Bayesian and trilateration. K-NN and Bayesian are kind of fingerprinting method. A fingerprint method consists of off-line phase and realtime phase. The process time of realtime phase must be fast. This paper proposes a decision tree method in order to improve the process time of realtime phase. Experimental results of comparing performances of these methods are also discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.146-151
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• 2013

With the development of mobile internet, requirements of positioning accuracy for the LBS (Location Based Service) are becoming more and more higher. The LBS is based on the position of each mobile device. So, it requires a proper acquisition of accurate user's indoor position. Thus indoor positioning technology and its accuracy is crucial for various LBS. In general, RSSI (Received Signal Strength Indicator) measurements are used to obtain the position information of mobile unit under WLAN environment. However, indoor positioning error increases as multiple AP's configurations are becoming more complex. To overcome this problem, an enhanced indoor localization method by AP (Access Point) selection criteria adopting DOP (Dilution of Precision) is proposed.