RFID Based Indoor Positioning System Using Event Filtering

被引:7
作者
Bok, Kyoungsoo [1 ]
Yoo, Jaesoo [1 ]
机构
[1] Chungbuk Natl Univ, Sch Informat & Commun Engn, Cheongju, South Korea
关键词
LBS; Indoor; RFID; Event filtering; Location tracking; Location update; KALMAN FILTER; LOCALIZATION; WIFI;
D O I
10.5370/JEET.2017.12.1.335
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Recently, location systems using RFID technology have been studied in indoor environments. However, the existing techniques require high computational cost to compute the location of a moving object because they compare the location proximity of all reference tags and objects. In this paper, we propose an RFID based location positioning scheme using event filtering, which reduces the computation cost of calculating the locations of moving objects while maintaining the accuracy of location estimation. In addition, we propose an incremental location update policy to reduce the location update cost for moving objects. We also compare the proposed scheme with one of the localization schemes, LANDMARC using a performance evaluation. As a result, the proposed scheme outperforms LANDMARC in terms of the computational cost of location estimation. The proposed scheme also reduces the cost of location update by using the RFID-based update policy.
引用
收藏
页码:335 / 345
页数:11
相关论文
共 28 条
  • [1] Using Kalman Filters to Reduce Noise from RFID Location System
    Abreu, Pedro Henriques
    Xavier, Jose
    Silva, Daniel Castro
    Reis, Luis Paulo
    Petry, Marcelo
    [J]. SCIENTIFIC WORLD JOURNAL, 2014,
  • [2] RFID Localization Using Angle of Arrival Cluster Forming
    Alsalih, Waleed
    Alma'aitah, Abdallah
    Alkhater, Wadha
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2014,
  • [3] A Cooperative Localization Algorithm for UWB Indoor Sensor Networks
    Arias-de-Reyna, Eva
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2013, 72 (01) : 85 - 99
  • [4] Bahl P., 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064), P775, DOI 10.1109/INFCOM.2000.832252
  • [5] Efficient Complex Event Processing over RFID Streams
    Bok, Kyoung Soo
    Yeo, Myung Ho
    Lee, Byoung Yeop
    Yoo, Jae Soo
    [J]. INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS, 2012,
  • [6] Chen LC, 2006, LECT NOTES COMPUT SC, V3842, P383
  • [7] Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization
    Chen, Zhenghua
    Zou, Han
    Jiang, Hao
    Zhu, Qingchang
    Soh, Yeng Chai
    Xie, Lihua
    [J]. SENSORS, 2015, 15 (01): : 715 - 732
  • [8] Civilis AI, 2004, PROCEEDINGS OF MOBIQUITOUS 2004, P164
  • [9] Extended Kalman Filter for Real Time Indoor Localization by Fusing WiFi and Smartphone Inertial Sensors
    Deng, Zhi-An
    Hu, Ying
    Yu, Jianguo
    Na, Zhenyu
    [J]. MICROMACHINES, 2015, 6 (04): : 523 - 543
  • [10] Data management in location-dependent information services
    Lee, Dik Lun
    Lee, Wang-Chien
    Xu, Jianliang
    Zheng, Baihua
    [J]. IEEE Pervasive Computing, 2002, 1 (03) : 65 - 72