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Design and Implementation of Indoor Positioning & Shortest Path Navigation System Using GPS and Beacons in Narrow Buildings

  • Sang-Hyeon, Park;Huhnkuk, Lim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.3
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    • pp.11-16
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    • 2023
  • As techniques for indoor positioning, fingerprinting, indoor positioning method using trilateration, and utilizing information obtained from equipments by Wi-Fi/Bluetooth, etc are common and representative methods to specify the user's indoor position. However, in these methods, an indoor space should be provided with enough space to install a large number of equipment (AP, Beacon). In this paper, we propose a technique that can express the user's location within a building by simultaneously using the GPS signal and the signal transmitted from the beacon in a building structure where the conventional method cannot be applied, such as a narrow building. A shortest path search system was designed and implemented by applying the Dijkstra Algorithm, one of the most representative and efficient shortest path search algorithms for shortest path search. The proposed technique can be considered as one of the methods for measuring the user's indoor location considering the structural characteristics of a building in the future.

Research of Error Optimization Techniques according to RSSI Differences between Beacons (비콘 간 RSSI 차이에 따른 오차 최적화 기법의 연구)

  • Yoon, Dong-Eon;Ban, Min-A;Park, Jung-Eun;Jeong, Ga-Yeon;Oh, Am-Suk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.243-245
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    • 2021
  • Existing beacons are suitable for providing untact services, but they have the disadvantage of difficulty in accurate indoor positioning because the deviation in signal strength increases depending on the environment. In general, trilateration technique can reduce deviation, but if the distance between beacons is quite irregular, it becomes difficult to apply the algorithm. Therefore, in this paper, we studied how to reduce the signal power measurement error between beacons. First, we transformed the distance measurement formula using RSSI, assuming that the TX values were the same. In addition, we compared measurement errors with existing beacons by searching beacons with beacons scanner applications implemented with Android. As a result, it was confirmed that if a certain distance was further away, the measurement was measured more accurately than the non-changing beacon. Through this, accurate indoor positioning will be possible even in various disability situations. It is also expected that there will be more cases of establishing services that combine beacon with non-face-to-face services.

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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).

Fixed node reduction technique using relative coordinate estimation algorithm (상대좌표 추정 알고리즘을 이용한 고정노드 저감기법)

  • Cho, Hyun-Jong;Kim, Jong-Su;Lee, Sung-Geun;Kim, Jeong-Woo;Seo, Dong-Hoan
    • Journal of Advanced Marine Engineering and Technology
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    • v.37 no.2
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    • pp.220-226
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    • 2013
  • Recently, with the rapid development of factory automation and logistics system, a few workers were able to manage the broad workplace such as large vessels and warehouse. To estimate the exact location of these workers in the conventional wireless indoor localization systems, three or more fixed nodes are generally used to recognize the location of a mobile node consisting of a single node. However, these methods are inefficient in terms of node deployment because the broad workplace requires a lot of fixed nodes compared to workers(mobile nodes). Therefore, to efficiently deploy fixed nodes in these environments that need a few workers, this paper presents a novel estimation algorithm which can reduce the number of fixed nodes by efficiently recognizing the relative coordinates of two fixed nodes through a mobile node composed of three nodes. Also, to minimize the distance errors between mobile node and fixed node, rounding estimation(RE) technique is proposed. Experimental results show that the error rate of localization is improved, by using proposed RE technique, 90.9% compared to conventional trilateration in the free space. In addition, despite the number of fixed nodes can be reduced by up to 50% in the indoor free space, the proposed estimation algorithm recognizes precise location which has average error of 0.15m.