• Title/Summary/Keyword: received signal strength indicator

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RFID System with Localization Function Based on Zigbee RSSI (Zigbee RSSI 기반의 위치추정 기능을 탑재한 RFID 시스템)

  • Kim, Tae-Yun;Hwang, Suk-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.12
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    • pp.1201-1208
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    • 2016
  • Radio Frequency Identification (RFID) technology has a significant attraction throughout various industry sites, along with the development of wireless communication technologies. The typical applications of RFID include medical, logistics, and distribution, and, specially, it is effectively applied to non-contact environments, because it employs radio waves. Although, recently, construction cases of the RFID management systems for the inventory management of the construction materials have been increased, the related researches and experiments for the reused materials are not actively performed. In this paper, we propose the RFID system with the localization function for effectively managing the reuse of the construction materials, adding to the conventional inventory management system. The proposed system consists of a RFID reader unit and a receiver unit, and the location information of the material with the attached RFID tag is obtained by estimating the position of a RFID reader. The distance value for estimating the reader position is calculated using the Received Signal Strength Indicator (RSSI) value of Zigbee, and the performance evaluation of the proposed system is performed in the indoor space of $5m{\times}5m$.

GPS Accuracy Revision Using RSSI and AoA in Wireless Sensor Network (무선 센서 네트워크에서 RSSI와 AoA를 활용한 GPS 정밀도 향상 방안)

  • Cho, Hae-Min;Kwon, Tae-Wook
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.5
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    • pp.889-896
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    • 2022
  • Data required in a wireless sensor network environment requires more accurate figures as technology advances and its complexity increases. However, in the case of operating a large number of sensor nodes in a large area, the balance between the power consumed and the data quality that can be acquired accordingly should be considered for that purpose. In particular, in complex, densely populated urban areas or military operations with specific goals, location data requires increasingly detailed and high accuracy over a wide range. In this paper, we propose a method of mounting a Global Positioning System(: GPS) only on some of the sensor nodes deployed in the wireless sensor network and improving the error of GPS location data measured on that sensor node through Angle of Arrival(: AoA) and Received Signal Strength Indicator(: RSSI).

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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Comparison of the Frequency Bands for the Wireless Sensor Networks in the Building Environment

  • Lee, Eunae;Lee, Jeongmin;Kim, Dong Sik
    • International Journal of Internet, Broadcasting and Communication
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    • v.8 no.2
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    • pp.23-30
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    • 2016
  • In this paper, for the pratical building envoronments, the propagation properties of the electromagnetic waves of the sub-1GHz bands, including the 447MHz, 868MHz, and 715MHz, and the 2.4GHz band are experimentally observed in therms of the received signal strength indicator (RSSI) value. The compasion of the frequency bands can be utilized to efficiently construct the wireless sensor networks (WSN) for the building automation control. In order to measure the RSSI values in the building, an RSSI measurement system is first designed, in which the master part can transmit data packets and measure the corresponding RSSI values, and the slave part can respond the received data packets. Using the measurement system, the RSSI values are then experimentally measured at four types of building enviroments. From the experimental result analysis, we could notice that the sub-1GHz, especially the 447MHz band, showd a good communication performance for the building environment and could provide an efficient WSN construction when the data rate is relatively low.

Adaptive Parameter Estimation Method for Wireless Localization Using RSSI Measurements

  • Cho, Hyun-Hun;Lee, Rak-Hee;Park, Joon-Goo
    • Journal of Electrical Engineering and Technology
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    • v.6 no.6
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    • pp.883-887
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    • 2011
  • Location-based service (LBS) is becoming an important part of the information technology (IT) business. Localization is a core technology for LBS because LBS is based on the position of each device or user. In case of outdoor, GPS - which is used to determine the position of a moving user - is the dominant technology. As satellite signal cannot reach indoor, GPS cannot be used in indoor environment. Therefore, research and study about indoor localization technology, which has the same accuracy as an outdoor GPS, is needed for "seamless LBS". For indoor localization, we consider the IEEE802.11 WLAN environment. Generally, received signal strength indicator (RSSI) is used to obtain a specific position of the user under the WLAN environment. RSSI has a characteristic that is decreased over distance. To use RSSI at indoor localization, a mathematical model of RSSI, which reflects its characteristic, is used. However, this RSSI of the mathematical model is different from a real RSSI, which, in reality, has a sensitive parameter that is much affected by the propagation environment. This difference causes the occurrence of localization error. Thus, it is necessary to set a proper RSSI model in order to obtain an accurate localization result. We propose a method in which the parameters of the propagation environment are determined using only RSSI measurements obtained during localization.

Establishing Best Power Transmission Path using Receiver Based on the Received Signal Strength

  • Eom, Jeongsook;Son, Heedong;Park, Yongwan
    • Journal of Internet Computing and Services
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    • v.18 no.6
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    • pp.15-23
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    • 2017
  • Wireless power transmission (WPT) for wireless charging is currently attracting much attention as a promising approach to miniaturize batteries and increase the maximum total range of an electric vehicle. The main advantage of the laser power beam (LPB) approach is its high power transmission efficiency (PTE) over long distance. In this paper, we present the design of a laser power beam based WPT system, which has a best WPT channel selection technique at the receiver end when multiple power transmitters and single power receiver are operated simultaneously. The transmitters send their transmission channel information via optically modulated laser pulses. The receiver uses the received signal strength indicator and digitized data to choose an optimum power transmission path. We modeled a vertical multi-junction photovoltaic cell array, and conducted an experiment and simulation to test the feasibility of this system. From the experimental result, the standard deviation between the mathematical model and the measured values of normalized energy distribution is 0.0052. The error between the mathematical model and measured values are acceptable, thus the validity of the model is verified.

Indoor Positioning System Using Robust Outlier Extended Kalman Filter (이상 잡음에 강인한 확장 칼만 필터를 이용한 실내 위치 추정 시스템)

  • Kim, Dong-Seon;Yeom, Hak-Sun;Kim, Sun-Woo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.20 no.9
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    • pp.954-960
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    • 2009
  • In this paper, Indoor Positioning System based on Wi-Fi system which is one of the key technology in LBS(Location Based Service) is proposed. The proposed system estimates distance between MS(Mobile Station) and AP(Access Point) using RSSI(Received Signal Strength Indicator). RSSI is affected by outlier that originate from indoor environment complexity and obstacle. In this paper, we introduce a Robust outlier Extended Kalman Filter that can ignore, real-time outlier in the observations. To demonstrate performance of proposed indoor positioning system, we used a PDA as the MS.

Efficient Handoff Time Decision Algorithm using Differential RSSI (차등 RSSI를 이용한 효율적인 핸드오프 시점 결정 알고리즘)

  • Kwon Young-Hwan;Choi Seong-Gon;Choi Jun-Kyun
    • The KIPS Transactions:PartC
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    • v.13C no.3 s.106
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    • pp.323-330
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    • 2006
  • This paper proposes a handoff time decision mechanism to utilize resource efficiently by using Differential Received Signal Strength Indicator (DRSSI). DRSSI can be used to predict the movement direction of Mobile Station (MS). In other words, DRSSI changes its sign (+ or -) when a MS changes movement direction. This mechanism maximizes resource availability of Base Station (BS) by predicting resource reservation of MS and by giving priority of resource to MS. It is possible when a BS predicts the behavior of MSs by monitoring the DRSSI of MSs in overlapped region among cells. Additionally, we show that our proposed mechanism has better handoff blocking probability than existing mechanism with numerical modeling and analysis.

Infrastructure-based Localization System using Underwater Wireless Sensor Network (구조화된 공간에서의 수중 무선 센서 네트워크를 이용한 위치 추정 시스템)

  • Park, Dae-Gil;Kwak, Kyung-Min;Chung, Wan-Kyun;Kim, Jin-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.8
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    • pp.699-705
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    • 2012
  • In this paper, an infrastructure-based localization method using underwater wireless sensor network (UWSN) is addressed. A localization using the UWSN is necessary to widen the usage of underwater applications, however it is very difficult to establish the UWSN due to the restrictions of water. In this paper, to extend the usage of UWSN at the infrastructure, we propose a sophisticated UWSN localization method using the Received Signal Strength Indicator (RSSI) of the electromagnetic waves. During the electromagnetic waves propagating in underwater, there arises a lot of attenuation according to the distance, while the attenuation shows uniformity according to the distance. Using this characteristics, the localization system in underwater infrastructure is proposed and the experimental results show the effectiveness.

A Novel Jamming Detection Technique for Wireless Sensor Networks

  • Vijayakumar, K.P.;Ganeshkumar, P.;Anandaraj, M.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.10
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    • pp.4223-4249
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    • 2015
  • A novel jamming detection technique to detect the presence of jamming in the downstream direction for cluster based wireless sensor networks is proposed in this paper. The proposed technique is deployed in base station and in cluster heads. The proposed technique is novel in two aspects: Firstly, whenever a cluster head receives a packet it verifies whether the source node is legitimate node or new node. Secondly if a source node is declared as new node in the first step, then this technique observes the behavior of the new node to find whether the new node is legitimate node or jammed node. In order to monitor the behavior of the existing node and new node, the second step uses two metrics namely packet delivery ratio (PDR) and received signal strength indicator (RSSI). The rationality of using PDR and RSSI is presented by performing statistical test. PDR and RSSI of every member in the cluster is measured and assessed by the cluster head. And finally the cluster head determines whether the members of the cluster are jammed or not. The CH can detect the presence of jamming in the cluster at member level. The base station can detect the presence of jamming in the wireless sensor network at CH level. The simulation result shows that the proposed technique performs extremely well and achieves jamming detection rate as high as 99.85%.