• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.982-990
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• 2009

The IEEE 802.15.4 wireless sensor network is composed of the unique sensor devices to monitor and collect physical or environmental conditions. The interests in a positioning technology, which is one of the environment monitoring technologies, are gradually increased according to the development of the sensor technology and IT infrastructure. Generally, it is difficult for the positioning system using RSSI (Received Signal Strength Indication) based implementation to get accurate position because of obstacles, RF wave's delay and multipath. Therefore, in this paper, we investigate the improved positioning technologies for RSSI-based positioning system. This paper also proposes the enhanced scheme to improve the accuracy of positioning system by applying the Gaussian Filter algorithm, which is widely used for enhancing the performance of image processing system. For the implementation of proposed scheme, we firstly make a look-up tables, which represent the distance between target node and master node and corresponding RSSI value of each target node which are recorded as an average value after investigating the characteristics of attenuation of transmitted signal By applying the pre-determined look-up tables and Gaussian Filtering in the proposed scheme, we analyzed the positioning performance and compared with other conventional RSSI-based positioning algorithms.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.182-196
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• 2008

The location estimation using sensor network has been considerably researched. The methods taking the differences of the forms of location estimation between indoors and outdoors into consideration have been studied. While it is possible for outdoor location to be estimated because outdoor location estimation has a consistent distribution during unit period through the value of RSSI(Received Signal Strength Indication) on outdoor location estimation, Indoor location estimation is difficult since multi-path and interference indoors are higher than those outdoors and indoor location estimation can be affected by other factors. In this paper, we revise the information of RSSI changed by multi-path and interference through the Moving Average method and K-means algorithm and propose the method of estimation for the value of RSSI with reliability in the group of signals received during unit period. We also suggest the way to put some weights on fixed nodes in network using a snooping node on location estimation and then evaluate the efficiency of location awareness as compared with the existing method by implementing proposed method on system through the reconfiguration of network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.147-153
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• 2018

Beacon enables one to measure distance indoors based on low-power Bluetooth low energy (BLE) technology, while GPS (Global Positioning System) only can be used outdoors. In measuring indoor distance using Beacon, RSSI (Received Signal Strength Indication) is considered as the one of the key factors, however, it is influenced by various environmental factors so that it causes the huge gap between the estimated distance and the real. In order to handle this issue, we propose the adaptive ANN (Artificial Neural Network) based approach to measuring the exact distance using Beacon. First, we has carried out the preprocessing of the RSSI signals by applying the extended Kalman filter and the signal stabilization filter into decreasing the noise. Then, we suggest the multi-layered ANNs, each of which layer is learned by specific training data sets. The results showed an average error of 0.67m, a precision of 0.78.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.3
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• pp.102-106
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• 2015

In order to avoid the electrical fire, AFCI(Arc Fault Cirruit Interrupter) has been obligated to be adopted in the United States of America since 2002. A study was carried out on how to detect Arc. In this paper, The propose is high-frequency signal detection methods and RSSI(Received Signal Strength Indication) signal processing algorithm for Arc detection. and the electrical characteristics were verifying.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.195-200
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• 2021

In this paper, we propose a method for a mobile robot to estimate a specific location of a service provision target using a beacon-tag for the purpose of providing location-based services (LBS) to users in an indoor environment. To estimate the location, the irregular characteristics and error factors of the received signal strength indicator (RSSI) generated from the beacon are analyzed, and the distance conversion function is derived from the RSSI data extracted by applying a Gaussian filter. Then, the distance data converted from the plurality of beacons estimates an indoor location through a triangulation technique. After that, the improvement in the location estimation is analyzed by applying the temporal confidence reasoning technique. The possibility of providing a LBS of a mobile robot was confirmed through a location estimation experiment for a plurality of designated locations in an indoor environment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.13-14
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• 2019

비콘을 이용해서 위치를 측정하기 위해서는 안정적인 RSSI 수치가 필요하다. 그러나 실제 수집된 RSSI 수치는 불규칙적이고, 이상치가 많은 형태를 취한다. 이에 수집된 RSSI 수치를 바로 적용하게 된다면, 이상치가 많이 발생하는 RSSI 특성상 위치 측정의 정확성이 많이 떨어지게 된다. 본 논문에서는 이를 해결하기 위하여 수집된 RSSI 수치에 칼만 필터링과 이동평균을 동시에 적용하였다. 이를 통해 더 안정적이고 더 믿을 수 있는 RSSI 수치를 얻을 수 있었다. 이 방법을 통해서 더 정확한 측정이 가능하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2550-2556
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• 2012

We proposed the energy-efficient routing algorithm ALPS (Ad hoc network Localized Positioning System) algorithm that is range-free based on the distance information. The routing coordinate method of ALPS algorithm consists of hierarchical cluster routing that provides immediately relative coordinate location using RSSI(Received Signal Strength Indication) information. Existing conventional DV-hop algorithm also to manage based on normalized the range free method, the proposed hierarchical cluster routing algorithm simulation results show more optimized energy consumption sustainable path routing technique to improve the network management.

• Journal of Digital Contents Society
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• v.14 no.3
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• pp.349-356
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• 2013

Products of Wi-Fi devices in recent years offer higher throughput and have longer signal coverage which also bring unnecessary signal interference to neighboring wireless networks, and result in decrease of network throughput. Signal interference is an inevitable problem because of the broadcast nature of wireless transmissions. However it could be optimized by reducing signal coverage of wireless devices. On the other hand, smaller signal coverage also means lower transmission power and lower data throughput. Therefore, in this paper, we analyze the relationship among signal strength, coverage and interference of Wi-Fi networks, and as a tradeoff between transmission power and data throughput, we propose a range-aware Wi-Fi network scheme which controls transmission power according to positions and RSSI(Received Signal Strength Indication) of Wi-Fi devices and analyze the efficiency of the proposed scheme by simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.2
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• pp.85-93
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• 2012

In this paper, we proposed Wireless LAN (WLAN) localization method that enhances database construction based on weighting factor and analyse the characteristic of the WLAN received signals. The weighting factor plays a key role as it determines the importance of Received Signal Strength Indication (RSSI) value from number of received signals (frequency). The fingerprint method is the most widely used method in WLAN-based positioning methods because it has high location accuracy compare to other indoor positioning methods. The fingerprint method has different location accuracies which depend on training phase and positioning phase. In training phase, intensity of RSSI is measured under the various. Conventional systems adapt average of RSSI samples in a database construction, which is not quite accurate due to variety of RSSI samples. In this paper, we analyse WLAN RSSI characteristic from anechoic chamber test, and analyze the causes of various distributions of RSSI and its influence on location accuracy in indoor environments. In addition, we proposed enhanced weighting factor algorithm for accurate database construction and compare location accuracy of proposed algorithm with conventional algorithm by computer simulations and tests.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.2
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• pp.1-9
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• 2012

Wireless sensor nodes are widely used for various applications such as environmental monitoring. In this paper, the RSSI and PER are measured for the indoor environment with the various interferences such as obstacles(concrete walls, steel doors) and the 2.4GHz wireless LAN interference. Also, the RSSI and PER are measured for the outdoor environments. From the measured values of the RSSI and PER, the guideline for the stable operation of the wireless sensor network is suggested.