Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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A Position Tracking System Using Pattern Matching and Regression Curve

RFID 태그를 이용한 실내 위치 추적 시스템에 관한 연구

  • Cho, Jaehyung (Department of Industrial Engineering, Dankook University)
  • Received : 2019.10.11
  • Accepted : 2019.12.20
  • Published : 2019.12.28
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Abstract

Location positioning systems are available in applications such as mobile, robotic tracking systems and Wireless location-based service (LBS) applications. The GPS system is the most well-known location tracking system, but it is not easy to use indoors. The method of radio frequency identification (RFID) location tracking was studied in terms of cost-effectiveness for indoor location tracking systems. Most RFID systems use active RFID tags using expendable batteries, but in this paper, an inexpensive indoor location tracking system using passive RFID tags has been developed. A pattern matching method and a system for tracing location by generating regression curves were studied to use precision tracking algorithms. The system was tested by verifying the level of error caused by noise. The three-dimensional curves are produced by the regression equation estimated the statistically meaningful coordinates by the differential equation. The proposed system could also be applied to mobile robot systems, AGVs and mobile phone LBSs.

무선 위치 추적 시스템은 모바일, 로봇 추적 시스템 및 인터넷 위치 기반 서비스(LBS) 애플리케이션과 같은 응용분야에서 사용할 수 있다. GPS 시스템은 가장 잘 알려진 위치 추적 시스템이지만 실내에서의 사용이 용이하지 않다. 실내 위치 추적 시스템에 대한 비용 효율적인 측면에서 무선 주파수 식별(RFID) 위치 추적 방법을 연구하였다. RFID 시스템 대부분은 소모성 배터리를 사용하는 능동형 RFID 태그를 사용지만, 본 논문에서는 패시브 RFID 태그를 사용하는 저렴한 실내 위치 추적 시스템을 개발하였다. 정밀한 추적 알고리즘을 사용하기 위하여 패턴인식에 의한 위치 추적 방법과 회귀곡선을 생성하여 위치를 추적하는 시스템을 연구하였다. 시스템은 잡음으로 인한 오류 수준을 검증하여 테스트하였다. 회귀식에 의해 생성된 3차원 곡선은 미분방정식에 의해서 확률적으로 설명력이 높은 좌표를 추정하였다. 이 제안된 시스템은 모바일 로봇 시스템, AGV 및 휴대전화 LBS에도 적용될 수 있다.

Keywords

References

  1. H. Bekkali, M. Sanson & Matsumoto (2007). RFID indoor positioning based on probabilistic RFID map and kalman filtering, Proceedings of the WiMOB. DOI: 10.1109/WIMOB.2007.4390815
  2. J. Na. (2006). The blind interactive guide system using RFID-based indoor positioning system, Proceedings of the ICCHP, 1298-1305.
  3. A. Oh. (2015). Smart Factory Logistics Management System Using House Interior Position Tracking Technology Based on Bluetooth Beacon. Journal of the Korea Institute of Information and Communication Engineering. 19(11), 2677-2682. https://doi.org/10.6109/jkiice.2015.19.11.2677
  4. M. J. Hyun & B. H. Kim. (2018). Study on the Beacon Signal Characteristic for Efficiency Analysis of Indoor Positioning. Journal of the Korea Convergence Society, 9(11), 1-7. https://doi.org/10.15207/JKCS.2018.9.11.001
  5. H. D. Park. (2014). Sensor Node Control Considering Energy Efficiency in Wireless Sensor Networks, Journal of Digital Convergence, 12(2), 271-276. https://doi.org/10.14400/JDC.2014.12.2.271
  6. B. Kang, S. Choi, G. Kim & Y. Park. (2014). A Study on a 3-Dimensional Positioning System over Indoor Wireless Environments, Journal of Digital Convergence, 12(11), 273-279. https://doi.org/10.14400/JDC.2014.12.11.273
  7. Y. Jung. (2017). A Study on Improving Manufacturing Environment Using Iot Technology in Small Business Environment, Journal of Convergence for Information Technology, 7(2), 83-90.
  8. Y. Jung. (2018). Linking Algorithm Between Iot Devices for Smart Factory Environment of SMEs, Journal of Convergence for Information Technology, 8(2), 233-238. https://doi.org/10.22156/CS4SMB.2018.8.2.233
  9. H. K. Ryu & T. W. Kim. (2019). Development of a Safety Accident Prevention System for Construction Equipment Utilizing Ilt and RTLS Technology, Journal of the Korea Convergence society, 10(9), 179-186.
  10. A. Cangialosi, J. E. Monaly & S. C. Yang. (2007). Leveraging RFID in hospitals: Patient life cycle and mobility perspectives, IEEE Communications Magazine, 45(9), 18-23. https://doi.org/10.1109/MCOM.2007.4342874
  11. T. Mori, C. Siridanupath, H. Noguchi & T. Sato. (2008). Active RFID-based indoor object management system in sensor - embedded environment, Proceedings of the 5th International Conference on Networked Sensing Systems 2008, Kanazawa, Japan, 17-19.
  12. A. Fu & G. Retscher. (2009). Active RFID Trilaternation and Location Fingerprinting Based on RSSI for Pedestrian Navigation, Journal of Navigation, 62(2), 323-340. https://doi.org/10.1017/S0373463308005195
  13. L. Ni, M. Yunhao, L. Cho, Yiu & A. Patil. (2003). LandMarc: indoor location sensing using active RFID, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom 2003), 407-415.
  14. S. Ting, L. Kwok, S. Tsang, H. Albert, C. Ho & T. George. (2011). The study on using passive RFID tags for indoor positioning, International Journal of Engineering Business Management, 3(1), 9-15.
  15. Y. Kim, Y. Jeong & G. C. Park. (2014). Energy-efficient Routing Protocol based on Localization Identification and RSSI Value in Sensor Network, Journal of Digital Convergence, 12(1), 339-345. https://doi.org/10.14400/JDPM.2014.12.1.339
  16. S. Mazuelas, A. Bahillo, R. M. Lorenzo, P. Fernandez, F. A. Lago, E. Garcia, J. Blas & E. J. Abril. (2009). Robust indoor positioning provided by real-time RSSI values in unmodified WLAN networks, IEEE J. Sel. Topics Signal Process, 3(5), 821-831. https://doi.org/10.1109/JSTSP.2009.2029191
  17. A. Ramon, J. Ruiz, F. Granja, J, Carlos, P. Honorato, I. Jorge & G. Rosas. (2012). Accurate Pedestrian Indoor Navigation by Tightly Coupling Foot-Mounted IMU and RFID Measurements, IEEE Transactions on Instrumentation and Measurement, 178-189.
  18. Y. Zhang, M. Amin & S. Kaushik. (2007). Localization and Tracking of Passive RFID Tags Based on Direction Estimation, International Journal of Antennas and Propagation.