Abstract
RFID (Radio Frequency Identification) technology, with its multiple advantages, such as low power consumption, non-line-of-sight, non-contact, has been playing an important role in large-scale storage systems, underground parking systems, exhibition halls, supermarkets, construction sites and other scenarios. Many of those scenarios also require indoor positioning technologies, for example, warehouse goods positioning, item positioning in production assembly lines, worker positioning in construction sites. However, related researches about indoor positioning using RFID system has been having trouble in improving positioning accuracy, especially when tracking a randomly moving target. In this paper, we propose PTrack, a track prediction algorithm for tracking moving targets in indoor positioning systems which is based on RFID technology and the correspondences between the RSSI (Received Signal Strength Indicator) changes and the moving status of the target. Results show that the proposed algorithm effectively improves the positioning accuracy and achieves 1.7 m localization error in indoor environments, which makes a promising technology to support future pervasive RFID-based tracking applications.
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References
Azizyan, M., Constandache, I., Roy Choudhury, R.: Surround-sense: mobile phone localization via ambience fingerprinting. In: International Conference on Mobile Computing and Networking, MOBICOM 2009, Beijing, China, pp. 261–272, September 2010
Bahl, P., Padmanabhan, V.N.: Radar: an in-building RF-based user location and tracking system. In: Institute of Electrical & Electronics Engineers Inc., vol. 2, pp. 775–784 (2000)
Chae, H., Han, K.: Combination of RFID and vision for mobile robot localization. In: International Conference on Intelligent Sensors, Sensor Networks and Information Processing Conference, pp. 75–80 (2005)
Gai, K., Qiu, M., Zhao, H.: Cost-aware multimedia data allocation for heterogeneous memory using genetic algorithm in cloud computing, p. 1 (2016)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural Networks, Proceedings, vol. 4, pp. 1942–1948 (1995)
Lockman, M.T., Selamat, A.: Multi-agent verification and validation for RFID system architecture. In: International Conference on Electronic Design, ICED 2008, pp. 1–5. IEEE (2008)
Ni, L.M., Liu, Y., Lau, Y.C., Patil, A.P.: Landmarc: indoor location sensing using active rfid. Wirel. Netw. 10(6), 701–710 (2004)
Pinto, A.M., Moreira, A.P., Costa, P.G.: A localization method based on map-matching and particle swarm optimization. J. Intell. Robot. Syst. 77(2), 313–326 (2015)
Qiu, M., Zhong, M., Li, J., Gai, K., Zong, Z.: Phase-change memory optimization for green cloud with genetic algorithm. IEEE Trans. Comput. 64(12), 1 (2015)
Rai, A., Chintalapudi, K.K., Padmanabhan, V.N., Sen, R.: Zee: zero-effort crowdsourcing for indoor localization, pp. 293–304 (2012)
Sen, S., Radunovic, B.R., Choudhury, R.R., Minka, T.: You are facing the Mona Lisa: spot localization using PHY layer information. In: International Conference on Mobile Systems, Applications, and Services, pp. 183–196 (2012)
Stoleru, R., He, T., Stankovic, J.A.: Walking GPS: a practical solution for localization in manually deployed wireless sensor networks. In: 29th Annual IEEE International Conference on Local Computer Networks, pp. 480–489. IEEE (2004)
Student, S.H., Connell, S., Milligan, I., Austin, D., Hayes, T.L., Chiang, P.: Indoor localization using pedestrian dead reckoning updated with RFID-based fiducials. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 7598–7601, August 2011
Wang, H.: An Application of PSO algorithm in indoor positioning system. Master’s thesis, Xidian University (2009)
Wang, Y., Jia, X., Lee, H., Li, G.: An indoors wireless positioning system based on wireless local area network infrastructure. In: 6th International Symposium on Satellite Navigation Technology Including Mobile Positioning & Location Services, no. 54 (2003)
Yang, L., Chen, Y., Li, X.Y., Xiao, C., Li, M., Liu, Y.: Tagoram: real-time tracking of mobile RFID tags to high precision using cots devices. In: Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, pp. 237–248. ACM (2014)
Youssef, M., Agrawala, A.: The Horus wlan location determination system. In: International Conference on Mobile Systems, Applications, and Services, pp. 205–218 (2005)
Acknowledgements
The authors gratefully acknowledge the contribution of the National Science Foundation of China [61572330][61472258], the Natural Science foundation of Guangdong Province [2014A030313554], and the Technology Planning Project (Grant No. 2014B010 118005) from Guangdong Province.
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Feng, G., Li, Jq., Luo, C., Ming, Z. (2017). PTrack: A RFID-based Tracking Algorithm for Indoor Randomly Moving Targets. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2016. Lecture Notes in Computer Science(), vol 10135. Springer, Cham. https://doi.org/10.1007/978-3-319-52015-5_15
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DOI: https://doi.org/10.1007/978-3-319-52015-5_15
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