• Title/Summary/Keyword: Received Signal Strength

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The Fire Detection Scheme Utilizing Received Signal Variation (수신 신호 변화를 활용한 화재 감지 기법)

  • Ha, Kyunguk;Kim, Dongwan
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.251-254
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    • 2018
  • Research about IoT system that utilizes variation of wireless received signal according to the changing of the surrounding environment are actively being studied. In this paper, firstly we proved that the received signal strength changes according to the ambient temperature variation. Then, we proposed the fire detection scheme by using received signal strength variation when the signal exchange between fixed transmitter and receiver periodically. The proposed scheme consists of the received signal strength change detection unit and the internal receiver temperature detection unit which prevents misunderstanding the received signal strength variation by the changing of wireless channel environment as outbreak of fire. The proposed scheme has the advantage of being able to support the existing receiver through software upgrade without additional device.

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A study of obstacles detection using RSS(Received Signal Strength) (RSS(Received Signal Strength)를 이용한 장애물 판단에 관한 연구)

  • Hong, Seok Mi
    • Journal of Digital Convergence
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    • v.11 no.11
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    • pp.321-326
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    • 2013
  • GPS reception rate in the room has less features. To overcome these shortcomings, the AP positioning using RSS technology research and development is being done. If we use positioning technology and signal strength in order to detect a obstacles, it has the advantage of no-cost in terms of utilization and efficiency when we do this applied service. In this paper, We are presented method to determine the obstacles using RSS(Received Signal Strength).

A Distance Estimation Algorithm Based on Multi-Code Ultrasonic Sensor and Received Signal Strength (다중 코드 초음파와 전파 신호 강도를 이용한 거리 측정)

  • Cho, Bong-Su;Kim, Phil-Soo;Moon, Woo-Sung;Baek, Kwang-Ryul
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.2
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    • pp.149-156
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    • 2011
  • This paper reveals a distance estimation algorithm based on multi-code ultrasonic and wireless sensor network. For measuring the distances among the sensor nodes, each ultrasonic transmitter transmits multi-code ultrasonic signal simultaneously. Receivers use cross correlation method to separate the coded signals. The information of measured distances is broadcasted to each sensor node by wireless sensor network. The wireless sensor network measures the distance among the sensor nodes using the received signal strength of the broadcasting. The multi-code ultrasonic have a limitation of measurable distance. And the received signal strength is affected from an environment. This paper measures a distance using ultrasonic and a received signal strength in short range. These measured data are applied to the least square estimation algorithm. By the expansion of the fitting curve, a distance measurement in long range using the received signal strength is compensated. The coupled system reduce the error to an acceptable level.

Performance Comparison of Machine Learning Algorithms for Received Signal Strength-Based Indoor LOS/NLOS Classification of LTE Signals

  • Lee, Halim;Seo, Jiwon
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.4
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    • pp.361-368
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    • 2022
  • An indoor navigation system that utilizes long-term evolution (LTE) signals has the benefit of no additional infrastructure installation expenses and low base station database management costs. Among the LTE signal measurements, received signal strength (RSS) is particularly appealing because it can be easily obtained with mobile devices. Propagation channel models can be used to estimate the position of mobile devices with RSS. However, conventional channel models have a shortcoming in that they do not discriminate between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions of the received signal. Accordingly, a previous study has suggested separated LOS and NLOS channel models. However, a method for determining LOS and NLOS conditions was not devised. In this study, a machine learning-based LOS/NLOS classification method using RSS measurements is developed. We suggest several machine-learning features and evaluate various machine-learning algorithms. As an indoor experimental result, up to 87.5% classification accuracy was achieved with an ensemble algorithm. Furthermore, the range estimation accuracy with an average error of 13.54 m was demonstrated, which is a 25.3% improvement over the conventional channel model.

A Probabilistic Broadcasting Mechanism based on Cross Layer Model Deliberating Received Signal Strength Ratio in Mobile Ad Hoc Networks

  • Kim, Jae-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.3
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    • pp.25-32
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    • 2016
  • Mobile Ad Hoc Networks(MANETs) consists of mobile nodes which communicate with each other without any centralized infrastructure. Message broadcasting by flooding for route discovery in MANET can result in high redundant retransmission, contention and collision of broadcasting packet, known as the broadcast storm problem collectively. The cross-layer design is adopted in this paper, which lets routing layer share the received signal strength information at MAC layer. Also this paper proposes a new probabilistic approach that dynamically adjusts the rebroadcasting probability of a node for routing request packets (RREQs) according to the received signal strength. The simulation results show that the proposed approach demonstrates better performance than blind flooding, fixed probabilistic broadcasting approaches.

Analysis of Absorption Loss by a Human Body in On-to-Off Body Communication at 2.45 GHz

  • Jeon, Jaesung;Lee, Sangwoo;Choi, Jaehoon;Kim, Sunwoo
    • Journal of electromagnetic engineering and science
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    • v.15 no.2
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    • pp.97-103
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    • 2015
  • This paper investigates the effect of absorption loss by a human body to the received signal strength with respect to on-body transmitting antenna positions in on-to-off wireless body area networks. This investigation is based on measurement results obtained from experiments performed on human bodies (male and female) using planar inverted-F antennas in an anechoic chamber. The total absorption loss by the human body is also presented through the SEMCAD-X simulations. Our investigation showed that the received signal strength becomes lower when the transmitting antenna is mounted at a specific position where more absorption loss is experienced. The statistical analyses of on-to-off body channel characteristics based on the measurement results are presented.

RSSI-based Indoor Location Tracking System using Wireless Sensor Networks (무선 센서 네트워크를 이용한 RSSI 기반의 실내 위치 추적 시스템)

  • Jung, Kyung-Kwon;Park, Hyun-Sik;Choi, Woo-Seung
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.7
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    • pp.67-73
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    • 2008
  • This paper describes a system for location tracking wireless sensor nodes in an indoor environment. The sensor reading used for the location estimation is the received signal strength indication (RSSI) as given by an RF interface. By tagging users with a mobile node and deploying a number of reference nodes at fixed position in the room, the received signal strength indicator can be used to determine the position of tagged users. The system combines Euclidean distance technique with signal strength obtained by measurement driven log-normal path loss model of 2.4 GHz wireless channel. The experimental results demonstrated the ability of this system to estimate the location with a error less than 1.3m.

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Analysis of Received Signal Strength Index from Bluetooth Beacons to Develop Proximity Warning Systems for Underground Mines (지하광산용 근접경고시스템 개발을 위한 블루투스 비콘 신호의 수신 강도 분석)

  • Baek, Jieun;Suh, Jangwon;Choi, Yosoon
    • Journal of the Korean Society of Mineral and Energy Resources Engineers
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    • v.55 no.6
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    • pp.604-613
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    • 2018
  • In this study, we analyzed the variations in the received signal strength index (RSSI) measured from Bluetooth beacons based on the strength and propagation direction of Bluetooth low energy (BLE) signal. Using a smartphone, we performed field experiments to investigate RSSI variations in the BLE signal transmitted by non-directional and directional beacons in an amethyst mine. In case of non-directional beacons, as the distance between the Bluetooth beacon and smartphone decreased, the RSSI increases, whereas as the BLE signal strength increased, the RSSI average gradually increased. The mean value of RSSI measured from the directional beacons was changed without relation to the facing angle between the Bluetooth beacon and smartphone. The results of this study can be used as basic data for developing a Bluetooth beacon-based proximity warning system for underground mines.

Estimating the Position of Mobiles by Multi-Criteria Decision Making

  • Lee, Jong-Chan;Ryu, Byung-Han;Ahn, Jee-Hwan
    • ETRI Journal
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    • v.24 no.4
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    • pp.323-327
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    • 2002
  • In this study, we propose a novel mobile tracking method based on Multi-Criteria Decision Making (MCDM), in which uncertain parameters-the received signal strength, the distance between the mobile and the base station, the moving direction, and the previous location-are used in the decision process using the aggregation function in the fuzzy set theory. Through numerical results, we show that our proposed mobile tracking method provides a better performance than the conventional method using the received signal strength.

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Spatiotemporal Location Fingerprint Generation Using Extended Signal Propagation Model

  • Kim, Hee-Sung;Li, Binghao;Choi, Wan-Sik;Sung, Sang-Kyung;Lee, Hyung-Keun
    • Journal of Electrical Engineering and Technology
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    • v.7 no.5
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    • pp.789-796
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    • 2012
  • Fingerprinting is a widely used positioning technology for received signal strength (RSS) based wireless local area network (WLAN) positioning system. Though spatial RSS variation is the key factor of the positioning technology, temporal RSS variation needs to be considered for more accuracy. To deal with the spatial and temporal RSS characteristics within a unified framework, this paper proposes an extended signal propagation mode (ESPM) and a fingerprint generation method. The proposed spatiotemporal fingerprint generation method consists of two algorithms running in parallel; Kalman filtering at several measurement-sampling locations and Kriging to generate location fingerprints at dense reference locations. The two different algorithms are connected by the extended signal propagation model which describes the spatial and temporal measurement characteristics in one frame. An experiment demonstrates that the proposed method provides an improved positioning accuracy.