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access icon openaccess Automated UHF RFID-based book positioning and monitoring method in smart libraries

In this study, a method is proposed for ultra high frequency radio frequency identification (UHF RFID)-based book positioning and counting developed for smart libraries. In the experimental setup created, RFID tags placed in books were automatically detected using three RFID antennas. Using received signal strength indicator information from each antenna for each book, the locations of the books are determined. In addition, classification was made by using machine learning approaches for the study. For this purpose, the best result for sequence determination in the classification study using ensemble trees, K nearest neighbours (KNN), and support vector machine algorithms was obtained with the ensemble subspace KNN algorithm with 94.1%. The best result for cabinet detection was obtained in the study using the ensemble subspace KNN algorithm and a 78.5% accuracy rate was achieved. The best result for rack detection was obtained with the ensemble subspace KNN algorithm with 95.4%. The study is thought to be useful in the automatic determination of the row, cabinet, and rack of books in smart libraries.

References

    1. 1)
      • 10. Dhanalakshmi, M., Mamatha, U.: ‘RFID based library management system’, Proc. of ASCNT 2009, CDAC, 2009, 2, (1), pp. 227234.
    2. 2)
      • 1. Chen, Z., Wang, C.: ‘Modeling RFID signal distribution based on neural network combined with continuous ant colony optimization’, Neurocomputing, 2014, 123, pp. 354361.
    3. 3)
      • 14. Ting, S.L., Kwok, S.K., Tsang, A.H.C., et al: ‘The study on using passive RFID tags for indoor positioning’, Int. J. Eng. Bus. Manage., 2011, 3, (1), p. 8.
    4. 4)
      • 22. Michael, M.P., Darianian, M.: ‘Architectural solutions for mobile RFID services for the internet of things’. Proc. – 2008 IEEE Congress on Services, SERVICES 2008, Honolulu, HI, USA, 2008, PART 1, pp. 7174.
    5. 5)
      • 24. Lau, B.P.L., Marakkalage, S.H., Zhou, Y., et al: ‘A survey of data fusion in smart city applications’, Inf. Fusion, 2019, 52, (May), pp. 357374.
    6. 6)
    7. 7)
      • 20. Xianming, Q., Zhi, N.C., Ailian, C.: ‘Multi-loop antenna for high frequency RFID smart shelf application’. IEEE Antennas and Propagation Society, AP-S Int. Symp. (Digest), Honolulu, HI, USA, 2007, pp. 54675470.
    8. 8)
      • 3. Bansode, S.Y., Desale, S.K.: ‘Implementation of RFID technology in University of Pune Library’, Program, 2009, 43, (2), pp. 202214.
    9. 9)
      • 17. Shangguan, L., Yang, Z., Liu, A.X., et al: ‘STPP: spatial-temporal phase profiling-based method for relative RFID tag localization’, IEEE/ACM Trans. Netw., 2017, 25, (1), pp. 596609.
    10. 10)
      • 15. Xu, H., Ding, Y., Li, P., et al: ‘An RFID indoor positioning algorithm based on Bayesian probability and K-nearest neighbor’, Sensors (Switzerland), 2017, 17, (8), pp. 117.
    11. 11)
      • 11. Sai Krisha, C., Sumanth, N., Raghava Prasad, C.: ‘RFID based student monitoring and attendance tracking system’. 2013 Fourth Int. Conf. on Computing, Communications and Networking Technologies (ICCCNT), Tiruchengode, India, 2013, pp. 15.
    12. 12)
      • 19. Zhang, M., Li, W., Wang, Z., et al: ‘A RFID-based material tracking information system’. Proc. of the IEEE Int. Conf. on Automation and Logistics, ICAL 2007, Jinan, China, 2007, pp. 29222926.
    13. 13)
      • 2. Moreno-Cano, M.V., Zamora-Izquierdo, M.A., Santa, J., et al: ‘An indoor localization system based on artificial neural networks and particle filters applied to intelligent buildings’, Neurocomputing, 2013, 122, pp. 116125.
    14. 14)
      • 12. Bayani, M., Segura, A., Alvarado, M., et al: ‘IoT-based library automation & monitoring system: developing an implementation framework’, E-Ciencias de la Inf., 2017, 8, (1), pp. 83100.
    15. 15)
      • 21. Al-Ali, A.R., Aloul, F.A., Aji, N.R., et al: ‘Mobile RFID tracking system’. 2008 3rd Int. Conf. on Information and Communication Technologies: From Theory to Applications, ICTTA, Damascus, Syria, 2008, pp. 03.
    16. 16)
      • 23. Yassin, A., Nasser, Y., Awad, M., et al: ‘Recent advances in indoor localization: a survey on theoretical approaches and applications’, IEEE Commun. Surv. Tutor., 2017, 19, (2), pp. 13271346.
    17. 17)
      • 25. Shen, L., Zhang, Q., Pang, J., et al: ‘PRDL: relative localization method of RFID tags via phase and RSSI based on deep learning’, IEEE Access, 2019, 7, pp. 2024920261.
    18. 18)
      • 16. Chen, Y., Luo, R.: ‘Design and implementation of a WiFi-based local locating system’. 2007 IEEE Int. Conf. on Portable Information Devices, Orlando, FL, USA, 2007, pp. 15.
    19. 19)
      • 4. Jin, X.-B., Dou, C., Su, T., et al: ‘Parallel irregular fusion estimation based on nonlinear filter for indoor RFID tracking system’, Int. J. Distrib. Sens. Netw., 2016, 12, (5), p. 1472930.
    20. 20)
      • 30. Xue, F., Zhao, J., Li, D.: ‘Precise localization of RFID tags using hyperbolic and hologram composite localization algorithm’, Comput. Commun., 2020, 157, (April), pp. 451460.
    21. 21)
      • 6. Younis, M.I.: ‘SLMS: a smart library management system based on an RFID technology’, Int. J. Reason.-Based Intell. Syst., 2012, 4, (4), p. 186.
    22. 22)
      • 9. Curran, K., Norrby, S.: ‘RFID-enabled location determination: within indoor environments’, Int. J. Ambient Comput. Intell., 2009, 1, (4), pp. 6386.
    23. 23)
      • 7. Sue, K.-L., Lo, Y.-M.: ‘BLOCS: A smart book-locating system based on RFID in libraries’. 2007 Int. Conf. on Service Systems and Service Management’, Chengdu, China, 2007, pp. 16.
    24. 24)
      • 13. Choi, J.-W., Oh, D.-I., Song, I.-Y.: ‘R-LIM: an affordable library search system based on RFID’. 2006 Int. Conf. on Hybrid Information Technology, Cheju Island, South Korea, 2006, pp. 103108.
    25. 25)
      • 26. Tags, R., Shen, L., Zhang, Q., et al: ‘ANTspin: Efficient Absolute Localization Method of RFID Tags via Spinning Antenna’, Sensors, 2019, 19, (4), pp. 120.
    26. 26)
      • 28. Shi, W., Du, J., Cao, X., et al: ‘IKULDAS: an improved kNN-based UHF RFID indoor localization algorithm for directional radiation scenario’, Sensors (Switzerland), 2019, 19, (4), pp. 118.
    27. 27)
      • 29. Cheng, S., Wang, S., Guan, W., et al: ‘3DLRA: an RFID 3D indoor localization method based on deep learning’, Sensors (Switzerland), 2020, 20, (9), pp. 116.
    28. 28)
      • 8. Brian, A.L.A., Arockiam, L., Malarchelvi, P.D.S.K.: ‘An IoT based secured smart library system with NFC based book tracking’, Int. J. Emerg. Technol. Comput. Sci. Electron. (IJETCSE), 2014, 11, (5), pp. 1821.
    29. 29)
      • 18. Ajana, M.E., Harroud, H., Boulmalf, M., et al: ‘FlexRFID: a flexible middleware for RFID applications development’. 2009 IFIP Int. Conf. on Wireless and Optical Communications Networks, WOCN 2009, Cairo, Egypt, 2009, pp. 15.
    30. 30)
      • 5. Chapter 1: ‘Library RFID systems for identification, security, and materials handling’, Libr. Technol. Rep., 2012, 48, (5), pp. 916.
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