• KIEAE Journal
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• v.10 no.3
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• pp.3-10
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• 2010

As indoor air quality directly affects health and comforts of the residents, researchers from different countries have continued to explore criteria by which indoor air quality can be indicated in a scientific and quantitative manner over the past several decades. However, there are many possibilities that can deteriorate indoor air quality. Due to the uncertainty of influence factors, it is quite difficult to develop a correct evaluation model and quantitative method. Furthermore, the effects from the indoor air pollutants have different levels, leading to the difficulties to apply the regular standard. This study aims to propose evaluation criteria by using the FD-AHP analysis. Obtained findings will be beneficial to construct apartment buildings, commercial buildings and others health performance evaluation framework.

• Journal of the Ergonomics Society of Korea
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• v.34 no.3
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• pp.265-278
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• 2015

Objective:To study the sources of indoor noise, its effects on human health, noise assessment and regulation through the use of standards, and techniques used to reduce noise. Background: Noise significantly affects the living environment, and there are an increasing number of reports of its impacts on human health. Method: We reviewed domestic and foreign data regarding environmental noise, and examined its effects and the standards used to regulate noise levels. Results: We describe the major sources of indoor noise and suggest possible legal standards, as well as recommended criteria for the control of noise. Conclusion: South Korea has higher legal standards of environmental noise than international standards in terms of threshold values. People in Korea are exposed to various sources of noise, and therefore the reduction of noise is urgently required. Application: Depending on the features of indoor spaces, an appropriate degree of indoor noise can be determined and techniques to reduce excess noise are required.

• International Journal of Air-Conditioning and Refrigeration
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• v.9 no.3
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• pp.36-45
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• 2001

During the last decade, an increasing interest in Underfloor Air-Conditioning (UFAC) systems has emerged. The purpose of this paper is to evaluate the indoor environmental performance of office buildings with UFAC system in order to develope the design prototype of this system. The physical measurements and the Interviewing survey of occupant's sensation responses to the environment were carried out. Measurements and survey were made of the thermal environmental factors such as air temperature, relative humidity, air velocity, globe temperature, and the other several environmental factors such as the sound level and the illuminance of working plane, etc. And, the air quality was evaluated by measuring the concentration of suspended particles, carbon monoxide, and carbon dioxide in the room. Furthermore, the paper appraises the various indoor environmental factors of the room by using post-occupancy evaluation (POE) method in office building with UFAC system, and thus, it suggests the basic data for assessing the indoor comfort based on field measurements and survey .

• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.586-591
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• 2015

In recent years, along with the rapid development of LED technology, indoor positioning systems based on visible light communication (VLC) have been researched. In this paper, we propose an accurate indoor positioning method using white-light LEDs and a dual image sensor. Indoor LED lights are located at the ceiling in a room and broadcast information on their positions using VLC technology. A mobile device with a dual image sensor receives LED position information by VLC and estimates its position and azimuth angle. Simulation and experimental results are given to show the performance of the proposed indoor positioning system.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1654-1659
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• 2003

In this paper, the performance evaluation of the JADE-MUSIC estimation based on the indoor channel is presented. By means of the JADE-MUSIC algorithm, DOA and time delay can be obtained simultaneously. In the JADE-MUSIC method, the channel impulse response is first estimated from the received samples and then this impulse response is employed to estimate DOAs and time delays of multipath waves. Moreover, according to the JADE-MUSIC characteristics, it can work in cases when the number of impinging waves is more than the number of antenna elements, unlike the traditional parametric subspace-based method, such a case is not true. Therefore, we employ the JADE-MUSIC algorithm applying for the real indoor environment where is rich of the multipath propagation waves and can imply that the number of waves is very possibly higher than that of the array element. The experiment is carried out in our laboratory considered to be the real indoor environment. The performance of the JADE-MUSIC algorithm is evaluated in terms of the comparison between the simulation and experiment results by using the simulated channel model and the real indoor channel model, respectively. It is clear that the joint angle and delay estimation using the simulated channel model are in good agreement with the estimation using the real indoor channel model. Therefore, we can say that the JADE-MUSIC algorithm accomplishes the high performance to jointly estimate the angle and delay of the arriving signal for the indoor environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.243-257
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• 2010

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

• The Journal of Korean Institute of Information Technology
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• v.17 no.2
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• pp.71-77
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• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.173-182
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• 2012

A recent advance in smart phones is increasing utilization of location information. Existing positioning system was using GPS location for positioning. However, the GPS cannot be used indoors, if GPS location has an incorrectly problem. In order to solve indoor positioning problems of indoor location-based positioning techniques have been investigated. There are a variety of techniques based on indoor positioning techniques like as RFID, UWB, WLAN, etc. But WLAN location positioning techniques take advantage the bond in real life. WLAN indoor positioning techniques have a two kind of method that is centroid and fingerprint method. Among them, the fingerprint technique is commonly used because of the high accuracy. In order to use fingerprinting techniques make a WLAN signal map building that is need to lot of resource. In this paper, we try to solve this problem in an Indoor environment for WLAN-based fingerprint of a virtual building technique, which is proposed. Proposed technique is classified Cell environment in existed Indoor environment, all of fingerprint points are shown virtual grid map in each Cell. Its method can make fingerprint grid map very quickly using estimate virtual signal value. Also built signal value can take different value depending of the real estimate value. To solve this problem using a calibration technique for the Splite-tree is proposed. Through calibration technique that improves the accuracy for short period of time. It also is improved overall accuracy using predicted value of around position in cell.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.3-7
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• 2006

Indoor localization is getting more and more importance with the increasing demand for location based service. Location based service necessarily requires the information about customers' locations to provide them the right service according to their changing locations. To satisfy that requirement, GPS is used to achieve outdoor localization. However, there is no leading technology to achieve indoor localization. Indoor localization through UWB wave and TDOA algorithm is considered as the most accurate method until now. In implementing that method, configuration of base stations that serve as control points affects the localization accuracy. Thus, this paper discusses about optimal configuration of base stations. The variation in localization accuracy according to spatial relationship between an object and base stations Is mentioned through SEP also.