http://iet.metastore.ingenta.com
1887

access icon openaccess Machine-learning-based system for multi-sensor 3D localisation of stationary objects

  • HTML
    89.8779296875Kb
  • XML
    83.0615234375Kb
  • PDF
    3.0373992919921875MB
Loading full text...

Full text loading...

/deliver/fulltext/iet-cps/3/2/IET-CPS.2017.0067.html;jsessionid=2fu256f4nc1rr.x-iet-live-01?itemId=%2fcontent%2fjournals%2f10.1049%2fiet-cps.2017.0067&mimeType=html&fmt=ahah

References

    1. 1)
      • 1. Pahlavan, K., Makela, J.: ‘Indoor geolocation science and technology’, IEEE Commun. Mag., 2002, 40, (2), pp. 112118.
    2. 2)
      • 2. Gu, Y., Lo, A., Niemegeers, I.: ‘A survey of indoor positioning systems for wireless personal networks’, IEEE Commun. Surv. Tutor., 2009, 11, (1), pp. 1332.
    3. 3)
      • 3. Sample, A.P., Macomber, C., Jiang, L.T., et al: ‘Optical localization of passive UHF RFID tags with integrated LEDs’. 2012 IEEE Int. Conf. RFID (RFID), 2012, pp. 116123.
    4. 4)
      • 4. Ni, L., Zhang, D., Souryal, M.: ‘RFID-based localization and tracking technologies’, IEEE Wirel. Commun., 2011, 18, (2), pp. 4551.
    5. 5)
      • 5. Farid, Z., Nordin, R., Ismail, M.: ‘Recent advances in wireless indoor localization techniques and system’, J. Comput. Netw. Commun., 2013, 2013, pp. 112.
    6. 6)
      • 6. Belhadi, Z., Fergani, L.: ‘Fingerprinting methods for RFID tag indoor localization’. 2014 Int. Conf. Multimedia Computing and Systems (ICMCS), 2014, pp. 717722.
    7. 7)
      • 7. Ni, L.M., Liu, Y., Lau, Y.C., et al: ‘LANDMARC: indoor location sensing using active RFID’, Wirel. Netw., 2004, 10, (6), pp. 701710.
    8. 8)
      • 8. Chattopadhyay, A., Harish, A.R.: ‘Analysis of low range indoor location tracking techniques using passive UHF RFID tags’. 2008 IEEE Radio and Wireless Symp., 2008, pp. 351354.
    9. 9)
      • 9. Kung, H., Chaisit, S., Phuong, N.T.M.: ‘Optimization of an RFID location identification scheme based on the neural network’, Int. J. Commun. Syst., 2015, 28, (4), p. 20, doi: 10.1002/dac.2692.
    10. 10)
      • 10. Goller, M., Feichtenhofer, C., Pinz, A.: ‘Fusing RFID and computer vision for probabilistic tag localization’. 2014 IEEE Int. Conf. RFID (IEEE RFID), 2014, pp. 8996.
    11. 11)
      • 11. Berz, E.L., Tesch, D.A., Hessel, F.P.: ‘RFID indoor localization based on support vector regression and k-means’. 2015 IEEE 24th Int. Symp. Industrial Electronics (ISIE), 2015, pp. 14181423.
    12. 12)
      • 12. Berz, E.L., Tesch, D.A., Hessel, F.P.: ‘A hybrid RFID and CV system for item-level localization of stationary objects’. 2017 18th Int. Symp. Quality Electronic Design (ISQED), 2017, pp. 331336.
    13. 13)
      • 13. Wang, C., Cheng, L.: ‘RFID & vision based indoor positioning and identification system’. 2011 IEEE Third Int. Conf. Communication Software and Networks, 2011, pp. 506510.
    14. 14)
      • 14. Nick, T., Cordes, S., Gotze, J., et al: ‘Camera-assisted localization of passive RFID labels’. 2012 Int. Conf. Indoor Positioning and Indoor Navigation (IPIN), 2012, pp. 18.
    15. 15)
      • 15. Deyle, T., Nguyen, H., Reynolds, M., et al: ‘RF vision: RFID receive signal strength indicator (RSSI) images for sensor fusion and mobile manipulation’. 2009 IEEE/RSJ Int. Conf. Intelligent Robots and Systems, 2009, pp. 55535560.
    16. 16)
      • 16. Clark, R.: ‘A MATLAB implementation of support vector regression (SVR)’, http://www.mathworks.com/matlabcentral/fileexchange/43429-supportvector-regression, accessed November 2014.
    17. 17)
      • 17. The MathWorks Inc.: ‘MATLAB neural network toolbox’, https://www.mathworks.com, accessed December 2014.
    18. 18)
      • 18. Ng, W.W.Y., Qiao, Y., Lin, L., et al: ‘Intelligent book positioning for library using RFID and book spine matching’. 2011 Int. Conf. Machine Learning and Cybernetics, 2011, pp. 465470.
    19. 19)
      • 19. Martínez-Sala, A., Guzmán-Quirós, R., Egea-López, E.: ‘Active RFID reader clustering and neural networks for indoor positioning’. The third Int. EURASIP Workshop on RFID Technology, 2010.
    20. 20)
      • 20. Wille, A., Broll, M., Winter, S.: ‘Phase difference based RFID navigation for medical applications’. 2011 IEEE Int. Conf. RFID, 2011, pp. 98105.
    21. 21)
      • 21. Smola, A.J., Schölkopf, B.: ‘A tutorial on support vector regression’, 1998.
    22. 22)
      • 22. Zhang, L., Zhou, W., Jiao, L.: ‘Wavelet support vector machine’, IEEE Trans. Syst. Man Cybern. B, Cybern., 2004, 34, (1), pp. 3439.
    23. 23)
      • 23. Cristianini, N., Shawe-Taylor, J.: ‘An introduction to support vector machines and other kernel-based learning methods’ (Cambridge University Press, New York, NY, USA, 2000).
    24. 24)
      • 24. Hightower, J., Borriello, G.: ‘Location systems for ubiquitous computing’, Computer, 2001, 34, (8), pp. 5766.
    25. 25)
      • 25. http://www.emgu.com, accessed December 2014.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cps.2017.0067
Loading

Related content

content/journals/10.1049/iet-cps.2017.0067
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address