DOI QR코드

DOI QR Code

상설 네트워크 인프라가 없는 실내 공간에서 재난시 IoT 기기를 활용한 부착형 실내 위치 추적 기술 연구

A Study of Temporary Positioning Scheme with IoT devices for Disastrous Situations in Indoor Spaces Without Permanent Network Infrastructure

  • Lee, Jeongpyo (Department of Electronic Engineering, University of Kwangwoon) ;
  • Yun, Younguk (Department of Electronic Engineering, University of Kwangwoon) ;
  • Kim, Sangsoo ;
  • Kim, Youngok (Department of Electronic Engineering, University of Kwangwoon)
  • 투고 : 2018.05.20
  • 심사 : 2018.09.22
  • 발행 : 2018.09.30

초록

연구목적: 본 논문에서는 상설 네트워크가 없는 장소에 Internet of things (IoT) 기기를 활용하여 이를 부착하는 것만으로도 실내 위치를 추적할 수 있는 측위기법을 제안한다. 연구방법: 본 논문의 제안기법은 단순한 계산을 통해 대상의 위치를 추정할 수 있는 weighted centroid localization을 활용한다. 연구결과: 일반 건물의 상설 네트워크가 없는 지하 주차장에서 제안하는 기법을 활용하여 실험을 진행하였고, 실험한 결과로 $82.5m{\times}56.4m$ 지하 공간에서 약 10m 이내의 위치 정확도를 확인하였다. 결론: 본 논문의 제안기법은 주차장, 창고, 공장 등과 같이 상설 네트워크 인프라가 없는 장소에서도 재난, 응급, 군사 작전 등과 같이 신속한 위치 추적을 필요로 하는 상황에 적용 가능하다.

Purpose: This paper propose a temporary indoor positioning scheme with devices of internet of things (IoT) for disastrous situations in places without the infrastructure of networks. Method: The proposed scheme is based on the weighted centroid localization scheme that can estimate the position of a target with simple computation. Results: It also is implemented with the IoT devices at the underground parking lot, where the network is not installed, of general office building. According to the experiment results, the positioning error was around 10m without a priori calibration process at $82.5m{\times}56.4m$ underground space. Conclusion: The proposed scheme can be deployed many places without the infrastructure of networks, such as parking lots, warehouses, factory, etc.

키워드

참고문헌

  1. Chang, C.Y.; Lin, C.Y.; Chang, C.T. Tone-based localization for distinguishing relative locations in wireless sensor networks. IEEE Sensors Journal 2012, 12, 1058-1070. https://doi.org/10.1109/JSEN.2011.2163503
  2. Nguyen, H.A.; Guo, H.; Low, K.S. Real-time estimation of sensor node's position using particle swarm optimization with log-barrier constraint. IEEE Transactions on Instrumentation and Measurement 2011, 60, 3619-3628. https://doi.org/10.1109/TIM.2011.2135030
  3. Meng, W.; Xiao, W.; Xie, L. An efficient EM algorithm for energy-based multisource localization in wirelesssensornetworks. IEEE Transactions on Instrumentation and Measurement 2011, 60, 1017-1027. https://doi.org/10.1109/TIM.2010.2047035
  4. Mo, L.; He, Y.; Liu, Y.; Zhao, J.; Tang, S.J.; Li, X.Y.; Dai, G. Canopy closure estimates with greenorbs: Sustainable sensing in the forest. Proceedings of the 7th ACM Conference on Embedded NetworkedSensorSystems. ACM, 2009, pp.99-112.
  5. QIU, Chen.; MUTKA, Matt W. Cooperation among smartphones to improve indoor position information. In: World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2015 IEEE 16th International Symposium on a. IEEE, 2015. p. 1-9.
  6. Akyildiz, I.F.; Su, W.; Sankarasubramaniam, Y.; Cayirci, E. A survey on sensor networks. IEEE Communications magazine 2002, 40, 102-114.
  7. Salvadori, F.; de Campos, M.; Sausen, P.S.; de Camargo, R.F.; Gehrke, C.; Rech, C.; Spohn, M.A.; Oliveira, A.C. Monitoring in industrial systems using wireless sensor network with dynamic power management. IEEE Transactions on Instrumentation and Measurement 2009, 58, 3104-3111. https://doi.org/10.1109/TIM.2009.2016882
  8. Liu, H.; Darabi, H.; Banerjee, P.; Liu, J. Survey of wireless indoor positioning techniques and systems. IEEETransactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 2007, 37, 1067-1080. https://doi.org/10.1109/TSMCC.2007.905750
  9. Deak, G.; Curran, K.; Condell, J. A survey of active and passive indoor localisation systems. Computer Communications 2012, 35, 1939-1954. https://doi.org/10.1016/j.comcom.2012.06.004
  10. Jianyong, Z.; Haiyong, L.; Zili ,C.; Zhaohui L. RSSI based Bluetooth low energy indoor positioning. In: Indoor Positioning and Indoor Navigation (IPIN), 2014 International Conference on. IEEE, 2014. p. 526-533.
  11. Fard, H.K.; Chen, Y.; Son, K.K.; Indoor positioning of mobile devices with agile iBeacon deployment. In: Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference on. IEEE, 2015. p. 275-279.
  12. Gomez, J.; Tayebi, A.; del Corte, A.; Gutierrez, O.; Gomez, J. M.; Saez de Adana. F. A comparative study of localization methods in indoor environments. Wireless personal communications 2013, 72.4: 2931-2944. https://doi.org/10.1007/s11277-013-1189-6
  13. Gustafsson, F.; Gunnarsson, F.; Mobile positioning using wireless networks: Possibilities and fundamental limitations based on available wireless network measurements. IEEE Signal Processing Magazine 2005, 22, 41-53. https://doi.org/10.1109/MSP.2005.1458284
  14. Jeon, H.; Jo, U.; Jo, M.; Kim, N.; Kim, Y.; An Adaptive AP Selection Scheme Based on RSS for Enhancing Positioning Accuracy. Wireless Personal Communications 2013, 69, 1535-1550. https://doi.org/10.1007/s11277-012-0649-8
  15. Kim, N.; Jo, U.; Yun, K.; Jeon, H.; Kim, Y.; A Hybrid Positioning Scheme Exploiting Sensors and RSS of Wi-Fi Signals. Wireless Personal Communications 2015; 85, 1111-1121. https://doi.org/10.1007/s11277-015-2829-9
  16. Blumenthal, J.; Grossmann, R.; Golatowski, F.; Timmermann, D.; Weighted Centroid Localization in Zigbee-based Sensor Networks. Intelligent Signal Processing, WISP International Symposium on, IEEE, 2008. Alcala de Henares, Spain.
  17. Dong, Quande, and Xu Xu.; A novel weighted centroid localization algorithm based on RSSI for an outdoor environment, Journal of Communications 2014, 9.3: 279-285. https://doi.org/10.12720/jcm.9.3.279-285
  18. Kraus, J.D. Antennas, 2nd Ed.; McGraw-Hill: New York, NY, USA, 1988.

피인용 문헌

  1. 목조건축유산 화재와 방재에 관한 연구: 당진지역 목조 공소건축을 중심으로 vol.7, pp.4, 2018, https://doi.org/10.20465/kiots.2021.7.4.015