• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.529-531
• /
• 2004

For localization, it is very important for an autonomous mobile robot to be able to recognize indoor environment and match an object it detect to an object within a map developed either online or offline. Given the map defining the locations of geometric beacons like wall and comer existing in the robot operation environment, this paper presents a stereo ultrasonic sensor based method that can be conveniently used in recognizing the geometric beacons. The stereo ultrasonic sensor used in the experiment consists of an ultrasonic transmitter and two ultrasonic receivers placed symmetrically about the transmitter. Experiment shows that the proposed method is more efficient in recognizing wall and coner than the conventional method of using multiple number of transmitter-receiver pairs.

• The Journal of Korea Robotics Society
• /
• v.4 no.4
• /
• pp.305-311
• /
• 2009

FastSLAM is a factored solution to SLAM problem using a Rao-Blackwellized particle filter. In this paper, we propose a practical FastSLAM implementation method using an infrared camera for indoor environments. The infrared camera is equipped on a Pioneer3 robot and looks upward direction to the ceiling which has infrared tags with the same height. The infrared tags are detected with theinfrared camera as measurements, and the Nearest Neighbor method is used to solve the unknown data association problem. The global map is successfully built and the robot pose is predicted in real time by the FastSLAM2.0 algorithm. The experiment result shows the accuracy and robustness of the proposed method in practical indoor environment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.4
• /
• pp.445-450
• /
• 2009

This paper presents a new mobile robot localization method for indoor robot navigation. The method uses hexagon distributed color-coded patches on the ceiling and a camera is installed on the robot facing the ceiling to recognize these patches. The proposed "cell-coded map", with the use of only seven different kinds of color-coded landmarks distributed in hexagonal way, helps reduce the complexity of the landmark structure and the error of landmark recognition. This technique is applicable for navigation in an unlimited size of indoor space. The structure of the landmarks and the recognition method are introduced. And 2 rigid rules are also used to ensure the correctness of the recognition. Experimental results prove that the method is useful.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.559-567
• /
• 2018

In this paper, we propose a new load forecasting method for smart air conditioning (A/C) based on the modified thermodynamics of indoor temperature and the unbiased finite memory estimator (UFME). Based on modified first-order thermodynamics, the dynamic behavior of indoor temperature can be described by the time-domain state-space model, and an accurate estimate of indoor temperature can be achieved by the proposed UFME. In addition, a reliable A/C load forecast can be obtained using the proposed method. Our study involves the experimental validation of the proposed A/C load forecasting method and communication construction between DR server and HEMS in a test bed. Through experimental data sets, the effectiveness of the proposed estimation method is validated.

• Journal of IKEEE
• /
• v.20 no.1
• /
• pp.1-8
• /
• 2016

In this paper, we propose an effective time-of-arrival (TOA)-based localization method with adaptive bias computation in indoor environments. The goal of the localization is to estimate an accurate target's location in wireless localization system. However, in indoor environments, non-line-of-sight (NLOS) errors block the signal propagation between target device and base station. The NLOS errors have significant effects on ranging between two devices for wireless localization. In TOA-based localization, finding the target's location inside the overlapped area in the TOA-circles is difficult. We present an effective localization method using compensated distance with adaptive bias computation. The proposed method is possible for the target's location to estimate an accurate location in the overlapped area using the measured distances with subtracted adaptive bias. Through localization experiments in indoor environments, estimation error is reduced comparing to the conventional localization methods.

• Journal of the Korean Solar Energy Society
• /
• v.32 no.1
• /
• pp.40-47
• /
• 2012

According to the advancement of computer and simulation method, it becomes possible to predict indoor climate precisely by using CFD simulation coupled with heat conduction, convection, and radiation. However, predicting the indoor climate is generally conducted by using a simplified CFD coupled simulation method since it takes quite long time to use a general CFD simulation method. In this study, a simplified CFD coupled simulation was conducted in order to find out the effect of natural ventilation by wind-driven in atrium. As a result of calculation, it was clarified that the natural ventilation driven by temperature difference was not enough to remove the accumulated heat of upper zone and the natural ventilation by wind-driven was needed. Finally, it is required to decide the window direction and size based on correct indoor climate prediction method for the effective use of natural ventilation by wind-driven.

• Analytical Science and Technology
• /
• v.18 no.4
• /
• pp.344-354
• /
• 2005

This study was carried out to evaluate the performance of a small chamber sampling and analytical method for the measurement of total volatile organic compounds (TVOC) and formaldehyde (HCHO) emission from building materials. While VOC was determined by the adsorbent tube sampling and sequential thermal desorption coupled with GC/MSD analysis, formaldehyde sampled with DNPH-silica cartridge was analyzed by HPLC. Wide-range performance criteria such as repeatability, desorption efficiency, emission chamber recovery test, duplicate precision, breakthrough volume and method detection limits were investigated for the evaluation of small chamber method. The overall precision of the small chamber sampling and analytical methods was estimated within 20~30% for target compounds. In conclusion, this study demonstrated that the small chamber sampling and analytical method can be reliably applied for the measurement of building materials pollutants.

• Journal of Broadcast Engineering
• /
• v.23 no.1
• /
• pp.154-161
• /
• 2018

As the number of smartphone users increases, research on indoor location recognition service is necessary. Access to indoor locations is predominantly WiFi, Bluetooth, etc., but in most quarters, WiFi is equipped with WiFi functionality, which uses WiFi features to provide WiFi functionality. The study uses the random forest algorithm, which employs the fingerprint index of the acquired WiFi and the use of the multI-value classification method, which employs the receiver signal strength of the acquired WiFi. As the data of the fingerprint, a total of 4 radio maps using the Mac address together with the received signal strength were used. The experiment was conducted in a limited indoor space and compared to an indoor location recognition system using an existing random forest, similar to the method proposed in this study for experimental analysis. Experiments have shown that the system's positioning accuracy as suggested by this study is approximately 5.8 % higher than that of a conventional indoor location recognition system using a random forest, and that its location recognition speed is consistent and faster than that of a study.

• Research in Community and Public Health Nursing
• /
• v.13 no.1
• /
• pp.79-88
• /
• 2002

Purpose: The purpose of this study was to identify the indoor environment i.e. house type and age, ventilation method, use of bed & sofa, cockroach, ants, etc. on HDM (House dust mites), especially Der fI allergen. Method: Samples of dust from mattresses, pillows and the floor were collected by using a vacuum cleaner from April. 2000. The amount of Group I allergen(Der. fI) of HDM (house dust mites) were measured by two-site ELISA. Indoor Environmental characteristics were accessed by using questionnaires on 178 house wives living in the Seoul area. Results: The amount of HDM allergen (Der fI) was higher in sofa using house. There were higher concentrations of HDM allergen (Der fI) in sofas made from quilt material than for those that were made from leather. Homes that had pets like dogs living in them had higher concentrations of HDM allergen (Der fI) than without dogs. Conclusion: The photophobic mites thrive in dark. warm and humid environments; Items such as pillows. mattresses, box springs, blankets. carpets. and upholstered furniture should be considered ideal environments for the mite. Therefore, an indoor environmental control program should be carried out to avoid the HDM allergen.

• Journal of Environmental Science International
• /
• v.13 no.3
• /
• pp.215-222
• /
• 2004

This study was conducted to evaluate the characterization of airborne bioaerosol in public facilities in Seoul. A total of 17 public facilities were investigated from December, 2002 to February, 2003. As results of the survey, the mean concentrations of bacteria and fungi in indoor air of public facilities were $378.08\pm296.33$ CFU/㎥ by RCS and $106.38\pm171.63$ CFU/㎥ and $347.46\pm335.32$ CFU/㎥ and $95.23\pm62.61$ CFU/㎥, by Six-stage cascade air sampler respectively. The mean concentrations of bacteria in indoor air (by ventilation method) were $517.14\pm343.93$ CFU/㎥ of natural ventilation and $215,83\pm100.71$ CFU/㎥ of mechanical ventilation. The mean concentrations of fungi in indoor air (by ventilation method) were $83.14\pm79.16$ CFU/㎥ of natural ventilation and $133.50\pm248.07$ CFU/㎥ of mechanical ventilation. The mean concentrations of bacteria in indoor air were 449.44 CFU/㎥ for the ground and $217.50\pm103.68$ CFU/㎥ for the underground. The mean concentrations of fungi in indoor air were $63.89\pm77.66$ CFU/㎥ for the ground and $202.00\pm290.08$ CFU/㎥ for the underground.