Advertisement

Multiagent Application in Mobile Environments to Data Collection in Park Zones

  • María NavarroEmail author
  • Fernando de la Prieta
  • Gabriel Villarrubia
  • Mohd Saberi Mohamad
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 290)

Abstract

This paper presents an application of automatic parking which assists users. For this, recognition techniques are used, such as the algorithm to recognize a license plate from a photograph or the use of NFC protocol to identify an object in the environment. As well, multiagent system integration will be necessary in order to communicate the different devices and data providers involved in this system. We obtain a system that assists the users in his payments and vehicle identification in an efficient way.

Keywords

Virtual organizations NFC protocol OCR techniques neural nets morphologic operations agent system clustering 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    López Fernández, J.M.: Software para el reconocimiento automático de matrículas (2006)Google Scholar
  2. 2.
    Vázquez, N., Nakano, M., Pérez-Meana, H.: Automatic system for localization and recognition of vehicle plate numbers. Journal of Applied Research and Technology (2002)Google Scholar
  3. 3.
    Rodrguez, S., de Paz, Y., Bajo, J., Corchado, J.: Social-based planning model for multiagent systems. Expert Systems with Applications 10(38), 13005–13023 (2010)Google Scholar
  4. 4.
    Corchado, J., Fyfe, C.: Unsupervised neural method for temperature forecasting. Artificial Intelligence in Engineering 4(13), 351–357 (1999)CrossRefGoogle Scholar
  5. 5.
    Tapia, D., Abraham, A., Corchado, J., Alonso, R.: Agents and ambient intelligence: case studies. Journal of Ambient Intelligence and Humanized Computing 2(1), 85–93 (2010)CrossRefGoogle Scholar
  6. 6.
    Fdez-Riverola, F., Corchado, J.: Cbr based system for forecasting red tides. Knowledge-Based Systems 5(16), 321–328 (2003)CrossRefGoogle Scholar
  7. 7.
    Patrick, K., Griswold, G., Raab, F., Intille, S.S.: Health and the mobile phone. Technical report (2008)Google Scholar
  8. 8.
    Morak, J., Kumpusch, H., Hayn, D., Modre-Osprian, R., Schreier, G.: Design and evaluation of a telemonitoring concept based on nfc. Enabled Mobile Phones and Sensor Devices. IEEE Transactions on Information Technology in BiomedicineGoogle Scholar
  9. 9.
    Haselsteiner, E., Breitfuss, K.: Security in near field communication. strengths and weakness. Technical report (2012)Google Scholar
  10. 10.
    Shyang-Lih, C., Sei-Wan, C.: Automatic license plate recognition. IEEE Trans. on Intelligent Transportation SystemsGoogle Scholar
  11. 11.
    Martín, F., Borges, D.: Automatic car plate recognition using partial segmentation algorithm. In: SPPRAGoogle Scholar
  12. 12.
    Venturini, V., Carbo, J., Molina, J.M.: Methodological design and comparative evaluation of a mas providing ami. Expert Systems with Applications 39(12), 10656–10673 (2012)CrossRefGoogle Scholar
  13. 13.
    Argente, E., J. Botti, I.V.: GORMAS: Guía para el desarrollo de sistemas multiagente abiertos basados en organizaciones. PhD thesis (2008)Google Scholar
  14. 14.
    Zato, C., et al.: PANGEA - Platform for Automatic coNstruction of orGanizations of intElligent Agents. In: Omatu, S., Paz Santana, J.F., González, S.R., Molina, J.M., Bernardos, A.M., Rodríguez, J.M.C. (eds.) Distributed Computing and Artificial Intelligence. AISC, vol. 151, pp. 229–239. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  15. 15.
    De la Prieta, F., Rodríguez, S., Bajo, J., Corchado, J.M.: A Multiagent System for Resource Distribution into a Cloud Computing Environment. In: Demazeau, Y., Ishida, T., Corchado, J.M., Bajo, J. (eds.) PAAMS 2013. LNCS (LNAI), vol. 7879, pp. 37–48. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  16. 16.
    Bradski, G., Kaehler, A.: Computer vision with the opencv library. Technical report (2008)Google Scholar
  17. 17.
    Dhillon, I.S., Guan, Y., Kulis, B.: Kernel k-means: spectral clustering and normalized cuts. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 551–556. ACM (2004)Google Scholar
  18. 18.
    Wahl, F.M.: Image preprocessing procedure for noise removal US Patent 4,747,156 (May 24, 1988)Google Scholar
  19. 19.
    Holley, R.: How good can it get? analysing and improving ocr accuracy in large scale historic newspaper digitisation programs. D-Lib Magazine 15(3/4) (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • María Navarro
    • 1
    Email author
  • Fernando de la Prieta
    • 1
  • Gabriel Villarrubia
    • 1
  • Mohd Saberi Mohamad
    • 1
  1. 1.Department of Computer ScienceUniversity of SalamancaSalamancaSpain

Personalised recommendations