• Title/Summary/Keyword: Beacon Tracking

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A Study on Development of Indoor Object Tracking System Using N-to-N Broadcasting System (N-to-N 브로드캐스팅 시스템을 활용한 실내 객체 위치추적 시스템 개발에 관한 연구)

  • Song, In seo;Choi, Min seok;Han, Hyun jeong;Jeong, Hyeon gi;Park, Tae hyeon;Joeng, Sang won;Kwon, Jang woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.192-207
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    • 2020
  • In industrial fields like big factories, efficient management of resources is critical in terms of time and expense. So, inefficient management of resources leads to additional costs. Nevertheless, in many cases, there is no proper system to manage resources. This study proposes a system to manage and track large-scale resources efficiently. We attached Bluetooth 5.0-based beacons to our target resources to track them in real time, and by saving their transportation data we can understand flows of resources. Also, we applied a diagonal survey method to estimate the location of beacons so we are able to build an efficient and accurate system. As a result, We achieve 47% more accurate results than traditional trilateration method.

Localization Algorithm in Wireless Sensor Networks using the Acceleration sensor (가속도 센서를 이용한 무선 센서 네트워크하에서의 위치 인식 알고리즘)

  • Hong, Sung-Hwa;Jung, Suk-Yong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.4
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    • pp.1294-1300
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    • 2010
  • In an environment where all nodes move, the sensor node receives anchor node's position information within communication radius and modifies the received anchor node's position information by one's traveled distance and direction in saving in one's memory, where if there at least 3, one's position is determined by performing localization through trilateration. The proposed localization mechanisms have been simulated in the Matlab. In an environment where certain distance is maintained and nodes move towards the same direction, the probability for the sensor node to meet at least 3 anchor nodes with absolute coordinates within 1 hub range is remote. Even if the sensor node has estimated its position with at least 3 beacon information, the angle ${\theta}$ error of accelerator and digital compass will continuously apply by the passage of time in enlarging the error tolerance and its estimated position not being relied. Dead reckoning technology is used as a supplementary position tracking navigation technology in places where GPS doesn't operate, where one's position can be estimated by knowing the distance and direction the node has traveled with acceleration sensor and digital compass. The localization algorithm to be explained is a localization technique that uses Dead reckoning where all nodes are loaded with omnidirectional antenna, and assumes that one's traveling distance and direction can be known with accelerator and digital compass. The simulation results show that our scheme performed better than other mechanisms (e.g. MCL, DV-distance).

A Study on Indoor Position-Tracking System Using RSSI Characteristics of Beacon (비콘의 RSSI 특성을 이용한 실내 위치 추적 시스템에 관한 연구)

  • Kim, Ji-seong;Kim, Yong-kab;Hoang, Geun-chang
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.5
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    • pp.85-90
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    • 2017
  • Indoor location-based services have been developed based on the Internet of Things technologies which measure and analyze users who are moving in their daily lives. These various indoor positioning technologies require separate hardware and have several disadvantages, such as a communication protocol which becomes complicated. Based on the fact that a reduction in signal strength occurs according to the distance due to the physical characteristics of the transmitted signal, RSSI technology that uses the received signal strength of the wireless signal used in this paper measures the strength of the transmitted signal and the intensity of the attenuated received signal and then calculates the distance between a transmitter and a receiver, which requires no separate costs and makes to implement simple measurements. It was applied calculating the value for the average RSSI and the RSSI filtering feedback. Filtering is used to reduce the error of the RSSI values that are measured at long distance.It was confirmed that the RSSI values through the average filtering and the RSSI values measured by setting the coefficient value of the feedback filtering to 0.5 were ranged from -61 dBm to - 52.5 dBm, which shows irregular and high values decrease slightly as much as about -2 dBm to -6 dBm as compared to general measurements.