• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.141-146
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• 2018

Recently, location recognition technology has attracted much attention, especially for locating people or objects in an indoor environment without being influenced by the surrounding environment GPS technology is widely used as a method of recognizing the position of an object or a person. GPS is a very efficient, but it does not allow the positions of objects or people indoors to be determined. RFID is a technology that identifies the location information of a tagged object or person using radio frequency information. In this study, an RFID system is constructed and the position is measured using tags. At this time, an error occurs between the actual and measured positions. To overcome this problem, a neural network is trained using the measured and actual position data to reduce the error. In this case, since the number of read tags is not constant, they are not suitable as input values for training the neural network, so the neural network is trained by converting them into center-of-gravity inputs and median value inputs. This allows the position error to be reduce by the neural network. In addition, different numbers of trained data are used, viz. 50, 100, 200 and 300, and the correlation between the number of data input values and the error is checked. When the training is performed using the neural network, the errors of the center-of-gravity input and median value input are compared. It was found that the greater the number of trained data, the lower the error, and that the error is lower when the median value input is used than when the center-of-gravity input is used.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.807-810
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• 2011

The sensor network technology for core technology of ubiquitous computing is in the spotlight recently, the research on sensor network is proceeding actively which is composed many different sensor node. USN(Ubiquitous Sensor Network) is the network that widely applies for life of human being. It works out to sense, storage, process, deliver every kind of appliances and environmental information from the stucktags and sensors. And it is possible to utilize to measure and monitor about the place of environmental pollution which is difficult for human to install. It's studied constantly since it be able to compose easily more subminiature, low-power, low-cost than previous one. And also it spotlights an important field of study, graft the green IT and IT of which the environment and IT unite stragically onto the Network. The problem for the air pollution in the office or the indoor except a specific working area is the continuously issue since the human beings have lived in the dwelling facilities. Measures for that problem are urgently needed. It's possible to solve for the freshair of outside with enough ventilation but that is the awkward situation to be managed by person. This study is the system engineering to management for indoor air condition under the sensor network. And research for efficiently manage an option.

• Journal of the Korean Society of Safety
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• v.27 no.1
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• pp.1-6
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• 2012

In crowded subway stations indoor air quality (IAQ) is a key factor for ensuring the safety and health of passengers. Since physical variables that describing IAQ such as the concentration of particulate, $CO_2$, VOCs and biological agents need to be closely monitored and controlled in multiple locations within subway stations and in remote sites, concept of web-based monitoring and control network using both wireless and wired media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated, distributed monitoring and control performance. In this study, performance of wireless and wired network in VDN for monitoring and control of IAQ in subway stations is evaluated. Specifically, delay induced in wireless and wired networks, and data transmission rate are evaluated. A key parameter is identified in assuring safety and health of passengers in subway stations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1702-1707
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• 2010

As quantities of the data that transmitting by the wireless are more increased, the interest and application are extending about 802.11n that uses by combination two existing 20MHz wireless LAN Channel. 802.11n use dual band of 2.4GHz band and 5.8GHz. So this is expected in mass wireless transmission method because of interference evasion effect in compliance with the radio communication of existing 2GHz neighborhood band. Like this 802.11n uses the radio as well and transmits information there is not only a possibility of undergoing an influence in radio wave environment of circumference. Specially the interior environment and outdoor environment is a possibility of saying that will be defined with each other different modeling as affects in radio communication is different. In this paper, we'll compare the influence to RF feature (802.11n) by (Indoor/Outdoor) environment difference through compared with 802.11n RF feature and Network feature in (Indoor/Outdoor) environment and also examine the correlation between RF feature and Network feature.

• Journal of Communications and Networks
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• v.1 no.3
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• pp.166-181
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• 1999

The object of this paper is to investigate the influence of antenna pattern on indoor radio channel characteristics. Different from previous works where this analysis was carried out at a fixed frequency using different antennas, in the present paper (where measurements were taken in a wide frequency range) the variation of the radiation pattern was caused by two factors: the change of the radiation pattern when the same antenna was used at different frequenicies and the use of different type of antennas. To carry out this analysis, frequency domain measurements of the indoor radio channel at 1 GHz, 5.5 GHz, 10 GHz and 18 GHz were collected. Measurements were taken using a network analyzer. Serveral re-alizations of the channel transfer function were obtained varying, for each measurement, the positon of the transmitter and keep-ing the receiver fixed. Estimate of the channel impulse response was obtained from the Inverse Fourier Transform (IFT) of the fre-quency response. The measurements were performed in an office enviroment with mostly metallic walls and inner separations. The obtained data were elaborated to obtain the power versus distance relationship, the Cummulative Distribution Functions(CDFs) of rms Delay Spread(DS) and of the 3 dB frequency correlation band-width. Finally, the 3 dB width of the frequency correlation func-tion has been empirically related to the inverse of the rms DS of the impulse response.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.43-48
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• 2018

In this paper, we propose an indoor-space recognition using DNN and super-pixel. In order to recognize the indoor space from the image, segmentation process is required for dividing an image Super-pixel is performed algorithm which can be divided into appropriate sizes. In order to recognize each segment, features are extracted using a proposed method. Extracted features are learned using DNN, and each segment is recognized using the DNN model. Experimental results show the performance comparison between the proposed method and existing algorithms.

• KIEAE Journal
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• v.10 no.6
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• pp.123-130
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• 2010

Indoor air quality has attracted great attention in recent years and thus the importance of managing finishing materials in terms of pollutant source control is being emphasized. Managing the finishing material at the design stage maximizes the efficiency of IAQ control at the following construction stage. However, there are insufficient investigations on the application of a specific finishing material management process, a database management system or a finishing material management process network. As a result, the main purposes of this study comprise comprehensive evaluation of IAQ performance from the selected finishing materials and auxiliary materials, application of the material management system basing on the types and characteristics of toxic substances generated from the indoor finishing materials, investigation of IAQ evaluation standard, and the overall IAQ evaluation method for the design parts. The result of this study will be the basic data to construct DBMS for management of finishing materials with respect to IAQ.

• Journal of KIISE:Information Networking
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• v.36 no.4
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• pp.330-338
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• 2009

Various applications based on the location information of things are developed as entering by the ubiquitous computing age. Wireless sensor networks are suitable to indoor location-based service because of the important features such as low-power consumption, low-cost, easy deployment, etc. To recognize the distance between nodes, the indoor location-based system transmits both ultrasound signal and radio signal periodically. However, increment of the number of deployed sensor nodes make lots of collision and interference among the signals and it can degrade the accuracy of location-based system. In this paper, we propose a beacon management mechanism to increase the probability of transmission chance to the nearest beacon from the listener. It can minimize collision and interference and reduce the error probability due to the characteristics of ultrasound.

• Journal of the Korean Society of Visualization
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• v.20 no.2
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• pp.21-27
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• 2022

Air purifiers can be placed where the air cleaning is required, making it easy to manage indoor air quality. The position of the air purifier affects the indoor airflow pattern, resulting in different air cleaning efficiency. Many efforts and strategies have been examined through numerical simulations and experiments to find the proper location of the air purifier, but problems still remain due to the various geometrical indoor spaces and arrangements. Herein, we develop an artificial intelligence model to predict the performance of an air purifier depending on the installation location. To obtain the training data, numerical simulations were performed on the different locations of the air purifiers and airflow patterns. The trained artificial intelligence model predicted the air exchange performance depending on the installation location of the air purifier with a prediction accuracy of 92%.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.399-408
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• 2023

In this paper, we propose a solution that enables continuous indoor/outdoor positioning of smartphone users through the integration of Pedestrian Dead Reckoning (PDR) and GPS/WiFi signals. Considering that accurate step detection affects the accuracy of PDR, we propose a Deep Neural Network (DNN)-based technology to distinguish between walking and non-walking signals such as walking in place. Furthermore, in order to integrate PDR with GPS and WiFi signals, a technique is used to select a proper measurement by distinguishing between indoor/outdoor environments based on GPS Dilution of Precision (DOP) information. In addition, we propose a technology to adaptively change the measurement error covariance matrix by detecting measurement outliers that mainly occur in the indoor/outdoor transition section through a residual-based χ² test. It is verified through experiments on a testbed that these technologies significantly improve the performance of PDR and PDR/GPS/WiFi fingerprinting-based integrated pedestrian navigation.