• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.207-214
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• 2016

RFID technology is a technology perceiving information with the device called reader and tag which is now used in public transportation such as Hi-pass. In this paper, we design a system which tracks indoor location using this technology. GPS, the most frequently used location-tracking system, has a defect that its accuracy decreases when the device is indoor. In suggested experiment, we simulate signals according to the moving of located objects, then compare with the result of the experiment. Based on the extracted data, we inform data which is for the purpose of tracking system based on analysis of the route and errors. Simulations for the tracking were performed with relocation of real objects. In the real experiment, we arrange the readers around the room and move the tagged object that we like to know the location, then analyze the data from the equipment. This paper suggests the analyzed data for the future indoor tag tracking applications. We expect that the RFID based location positioning data will be used for other indoor positioning research and development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.348-353
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• 2008

Despite the increasing popularity of wireless sensor network, indoor positioning using low power IEEE 802.15.4 compliant radio had attracted an interest of many researchers in the last decade. Old fashionable indoor location sensing information has been presented in dull and unpleasant 2D image standard. This paper focused on visualizing high precision 3 dimensional RSSI-based (received signal strength indication) spatial sensing information in an interactive virtual reality on PDA. The developed system operates by capturing and extracting signal strength information at multiple pre-defined reference nodes to provide information in the area of interest, thus updating user's location in 3D indoor virtual map. VRML (Virtual Reality Modeling Language) which specifically developed for 3D objects modeling is utilized to design 3D indoor environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.326-327
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• 2016

A study on Ontology-based indoor positioning techniques using BLE Beacon. Recently BLE beacon has been widely used as a technique for measuring the indoor location. But it requires a filtering technique for the measurement of the correct position, and uses the most fixed beacon. It is not accurate that calculates the position information through the identification of the beacon signal. Therefore, filtering is important. So it takes a lot of time, position measurement and filtering. Thus, we is to measure the exact position at the indoor using a mobile beacon. The measured beacon signal is composed of an ontology for reuse in the same pattern. RSSI is measured the receiver is the distance of the beacon. And this value configure the location ontology to be normalized by the relationship analysis between the values. The ontology is a method for calculating the position information of the moving beacon. It may be detected fast and accurate indoor position information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1317-1340
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• 2024

With the rapid development of information technology, people's demands on precise indoor positioning are increasing. Wireless sensor network, as the most commonly used indoor positioning sensor, performs a vital part for precise indoor positioning. However, in indoor positioning, obstacles and other uncontrollable factors make the localization precision not very accurate. Ultra-wide band (UWB) can achieve high precision centimeter-level positioning capability. Inertial navigation system (INS), which is a totally independent system of guidance, has high positioning accuracy. The combination of UWB and INS can not only decrease the impact of non-line-of-sight (NLOS) on localization, but also solve the accumulated error problem of inertial navigation system. In the paper, a fused UWB and INS positioning method is presented. The UWB data is firstly clustered using the Fuzzy C-means (FCM). And the Z hypothesis testing is proposed to determine whether there is a NLOS distance on a link where a beacon node is located. If there is, then the beacon node is removed, and conversely used to localize the mobile node using Least Squares localization. When the number of remaining beacon nodes is less than three, a robust extended Kalman filter with M-estimation would be utilized for localizing mobile nodes. The UWB is merged with the INS data by using the extended Kalman filter to acquire the final location estimate. Simulation and experimental results indicate that the proposed method has superior localization precision in comparison with the current algorithms.

• Journal of Environmental Health Sciences
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• v.41 no.6
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• pp.389-396
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• 2015

Objectives: A hospital is a complex building that serves many different purposes. It has a major impact on patient's well-being as well as on the work efficiency of the hospital staff. Thermal comfort is one of the major factors in indoor comfort. The purpose of this study was to determine thermal comfort in various locations in a hospital. Methods: Various indoor environmental conditions in a general hospital were measured in February 2014. The predicted mean vote (PMV) and carbon dioxide ($CO_2$) concentration were measured simultaneously in the lobby, office, restaurant, and ward. Results: The ward was the most thermally comfortable location (PMV=0.44) and the lobby was the most uncomfortable (PMV = -1.39). However, the $CO_2$ concentration was the highest in the ward (896 ppm) and the lowest in the lobby (572 ppm). The average PMV value was the most comfortable in the ward and the lowest in the lobby. In contrast, for concentration of carbon dioxide, the highest average was in the ward and the lowest in the lobby. Due to air conditioner operation, during operating hours the PMV showed values close to 0 compared to the non-operating time. Correlation between PMV and $CO_2$ differed by location. Conclusion: The PMV and concentration of carbon dioxide of the hospital lobby, office, restaurant and ward varied. The relationship between PMV and carbon dioxide differed by location. Consideration of how to apply PMV and carbon dioxide is needed when evaluating indoor comfort.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.564-573
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• 2015

GPS is the representative positioning technology for providing the location information. This technique has the disadvantage that does not operate in the shadow areas, such as urban or dense forest and the interior. This paper proposes a hybrid indoor positioning algorithm, which estimates a more accurate location of the terminal using strength of the Wi-Fi signal from the indoor AP. To determine the location of the user, we establish the most appropriate path loss model for the measurement environment. by using the RSSI value measured in a variety of environment such as building structure, person, distance, etc. The path loss exponent obtained by the path loss model is changed according to the environment. REKF, PF estimate the position of the terminal by using measured value from the AP with path loss exponent. For more accurate position estimation, we select positioning system by the value of threshold measured by experiments rather than a single positioning system. Experimental results using the proposed hybrid algorithm show that the performance is improved by about 17% than the conventional single positioning method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.109-117
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• 2010

With the advent of new technologies such as HSDPA, WiBro(Wireless Broadband) and personal devices, we can access various contents and services anytime and anywhere. A location based service(LBS) is essential for providing personalized services with individual location information in ubiquitous computing environment. In this paper, we propose mapping algorithm for error compensation of indoor localization system. Also we explain filter and indoor localization system. we have developed mapping algorithms composed of a map recognition method and a position compensation method. The map recognition method achieves physical space recognition and map element relation extraction. We improved the accuracy of position searching. In addition, we reduced position errors using a dynamic scale factor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1442-1447
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• 2018

Since the indoor location recognition system using RFID is a method for predicting the indoor position, an error occurs due to the surrounding environment such as an obstacle. In this paper, we plan to reduce errors using back propagation neural networks. The neural network adjusts and trains the connection values between the layers to reduce the error between the actual position of the object with the reader and the expected position of the object through the experiment. In this paper, we propose a method that uses the median method and the radiation method as input to the neural network. Among the two methods, we want to find out which method is more effective in recognizing the actual position in an environment with obstacles and reduce the error. Consequently, the method using the median has less error, and we confirmed that the more the number of data, the smaller the error.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.5
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• pp.397-403
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• 2005

The thermal comfort of occupants is directly related to several environmental factors such as velocity of air flow, turbulence intensity and temperature distribution of indoor air. The purpose of this study is to evaluate the indoor air flow and temperature distribution in office area using under-floor air-conditioning system (UFAC System) based on the results from physical measurements and to perform a Computer Fluid Dynamics (CFD) under the same condition of inlet and outlet as field measurement. The results from the CFD simulation are similar to those from the field measurement. The results show that UFAC system is provide proper indoor condition for occupants.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.205-211
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• 2020

In this paper, we propose a modified ORB-SLAM (Oriented FAST and Rotated BRIEF Simultaneous Localization And Mapping) for precise indoor navigation of a mobile robot. The exact posture and position estimation by the ORB-SLAM is not possible all the times for the indoor navigation of a mobile robot when there are not enough features in the environment. To overcome this shortcoming, additional IMU (Inertial Measurement Unit) and encoder sensors were installed and utilized to calibrate the ORB-SLAM. By fusing the global information acquired by the SLAM and the dynamic local location information of the IMU and the encoder sensors, the mobile robot can be obtained the precise navigation information in the indoor environment with few feature points. The superiority of the modified ORB-SLAM was verified to compared with the conventional algorithm by the real experiments of a mobile robot navigation in a corridor environment.