International Conference on Ubiquitous Computing and Ambient Intelligence

Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information pp 413-424 | Cite as

An Integrated Framework for Enabling End-User Configuration of AmI Simulations for Open Wide Locations

  • Ramón Alcarria
  • Emilio Serrano
  • Jorge Gómez Sanz
  • Alberto Fernández
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9454)

Abstract

The deployment of AmI technologies in large facilities sets new challenges due to the difficulty to perform experiments in physical large settings, with high number of users. We propose a framework for such domain using simulations that combine social simulation techniques, specialized in assessing large population behaviors, along with experience in AmI systems simulations, specialized in considering sensor and actuator networks embedded in a physical environment. The framework will allow the configuration of simulation features and options according to user and device models defined by domain experts, as well as the interaction between the proposed simulator and a context generated by external sources (other simulators or AmI infrastructures). This paper also proposes the first steps towards an implementation of this architecture through contributions on known simulators.

Keywords

End-user configuration Ambient intelligence Simulation Open wide locations 

References

  1. 1.
    Cook, D.J., Augusto, J.C., Jakkula, V.R.: Ambient intelligence: technologies, applications, and opportunities. Pervasive Mob. Comput. 5(4), 277–298 (2009)CrossRefGoogle Scholar
  2. 2.
    Ruiz del Árbol, A.: Two thousand extras will test the new Barajas. Cinco Días, August 2005. (in Spanish)Google Scholar
  3. 3.
    Norwood, A.E.: Debunking the myth of panic. Psychiatry 68(2), 114 (2005). (Interpersonal and Biological Processes)CrossRefGoogle Scholar
  4. 4.
    Friesen, C.K., Kingstone, A.: The eyes have it!: reflexive orienting is triggered by nonpredictive gaze. Psychon. Bull. Rev. 5, 490–495 (1998)CrossRefGoogle Scholar
  5. 5.
    Chatzigiannakis, I., Fischer, S., Koninis, C., Mylonas, G., Pfisterer, D.: WISEBED: an open large-scale wireless sensor network testbed. In: Komninos, N. (ed.) SENSAPPEAL 2009. LNICST, vol. 29, pp. 68–87. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  6. 6.
    Bouckaert, S., Vandenberghe, W., Jooris, B., Moerman, I., Demeester, P.: The w-iLab.t testbed. In: Magedanz, T., Gavras, A., Thanh, N.H., Chase, J.S. (eds.) TridentCom 2010. LNICST, vol. 46, pp. 145–154. Springer, Heidelberg (2011)Google Scholar
  7. 7.
    Burin des Rosiers, C., Chelius, G., Fleury, E., Fraboulet, A., Gallais, A., Mitton, N., Noël, T.: SensLAB. In: Korakis, T., Li, H., Tran-Gia, P., Park, H.-S. (eds.) TridentCom 2011. LNICST, vol. 90, pp. 239–254. Springer, Heidelberg (2012)Google Scholar
  8. 8.
    Sridharan, M., Zeng, W., Leal, W., Ju, X., Ramnath R., Zhang, H., Arora, A.: Kanseigenie: software infrastructure for resource management and programmability of wireless sensor network fabrics. In: Next Generation Internet Architectures and Protocols. Cambridge University Press, Cambridge (2010)Google Scholar
  9. 9.
    Handziski, V., Köpke, A., Willig, A., Wolisz, A.: Twist: a scalable and reconfigurable testbed for wireless indoor experiments with sensor networks. In: REALMAN 2006 Proceedings of the 2nd International Workshop on Multi-hop Ad Hoc Networks: From Theory to Reality, pp. 63–70 (2006)Google Scholar
  10. 10.
    Barton, J., Vijayaraghavan, V.: Ubiwise: A Simulator for Ubiquitous Computing Systems Design. HP Labs, Palo Alto (2003)Google Scholar
  11. 11.
    O’Neill, E., Klepal, M., Lewis, D., O’Donnell, T., O’Sullivan, D., Pesch, D.: A testbed for evaluating human interaction with ubiquitous computing environments. In: Testbeds and Research Infrastructures for the Development of Networks and Communities, TRIDENTCOM 2005, Washington, DC, USA, pp. 60–69. IEEE Computer Society (2005)Google Scholar
  12. 12.
    Nishikawa, H., Yamamoto, S., Tamai, M., Nishigaki, K., Kitani, T., Shibata, N., Yasumoto, K., Ito, M.: UbiREAL: realistic smartspace simulator for systematic testing. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, pp. 459–476. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Tang, L., Zhou, X., Becker, C., Yu, Z., Schiele, G.: Situation-based design: a rapid approach for pervasive application development. In: 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing (UIC/ATC), pp. 128–135 (2012)Google Scholar
  14. 14.
    Nieto-Hidalgo, M., Ferrández-Pastor, F.J., García-Chamizo, J.M., Flórez-Revuelta, F.: DAI virtual lab: a virtual laboratory for testing ambient intelligence digital service. In: Proceedings of V Congreso Internacional de Diseño, Redes de Investigación y Tecnología para Todos, DRT4ALL, Madrid (2013)Google Scholar
  15. 15.
    Serrano, E., Botía, J.A.: Validating ambient intelligence based ubiquitous computing systems by means of artificial societies. Inf. Sci. 222, 3–24 (2013)CrossRefGoogle Scholar
  16. 16.
  17. 17.
    Campillo-Sanchez, P., Gómez-Sanz, J.J., Botía, J.A.: PHAT: physical human activity tester. In: Pan, J.-S., Polycarpou, M.M., Woźniak, M., de Carvalho, A.C.P.L.F., Quintián, H., Corchado, E. (eds.) HAIS 2013. LNCS, vol. 8073, pp. 41–50. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  18. 18.
    Ossowski, S. (ed.): Agreement Technologies. Law, Governance and Technology Series, vol. 8. Springer, Heidelberg (2013)Google Scholar
  19. 19.
    Euzenat, J., Shvaiko, P.: Ontology Matching. Springer, Heidelberg (2007)MATHGoogle Scholar
  20. 20.
    Jennings, N.R., Faratin, P., Lomuscio, A.R., Parsons, S., Wooldridge, M.J., Sierra, C.: Automated negotiation: prospects, methods and challenges. Int. J. Group Decis. Negot. 10(2), 199–215 (2001)CrossRefGoogle Scholar
  21. 21.
    Ferber, J., Gutknecht, O., Michel, F.: From agents to organizations: an organizational view of multi-agent systems. In: Giorgini, P., Müller, J.P., Odell, J.J. (eds.) AOSE 2003. LNCS, vol. 2935, pp. 214–230. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  22. 22.
    Sierra, C., Debenham, J.: Trust and honour in information- based agency. In: Proceedings of the 5th International Conference on Autonomous Agents and Multi Agent Systems, pp. 1225–1232. ACM, New York (2006)Google Scholar
  23. 23.
    Macal, C.M., North, M.J.: Tutorial on agent-based modelling and simulation. J. Simul. 4, 151–162 (2010)CrossRefGoogle Scholar
  24. 24.
    North, M.J., Macal, C.M.: Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation. Oxford University Press, Oxford (2007)CrossRefGoogle Scholar
  25. 25.
    Marsh, W.E., Hill, R.R.: An initial agent behavior modeling and definition methodology as applied to unmanned aerial vehicle simulation. Int. J. of Simul. Process Model. 4(2), 119–129 (2008)CrossRefGoogle Scholar
  26. 26.
    Ginot, V., Le Page, C., Souissi, S.: A multi-agents architecture to enhance end-user individual-based modelling. Ecol. Model. 157(1), 23–41 (2002)CrossRefGoogle Scholar
  27. 27.
    Stav, E., Floch, J., Khan, M.U., Sætre, R.: Using meta-modelling for construction of an end-user development framework. In: Dittrich, Y., Burnett, M., Mørch, A., Redmiles, D. (eds.) IS-EUD 2013. LNCS, vol. 7897, pp. 72–87. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  28. 28.
    Repast Suite home page. http://repast.sourceforge.net/
  29. 29.
    GMU (George Mason University): MASON home page. http://cs.gmu.edu/~eclab/projects/mason/
  30. 30.
    SDG (Swarm Development Group): Swarm development group home page. http://savannah.nongnu.org/projects/swarm
  31. 31.
  32. 32.
    Pax, R., Pavón, J.: Agent-based simulation of crowds in indoor scenarios. In: 9th International Symposium on Intelligent Distributed Computing (IDC 2015), Guimaraes, Portugal (2015)Google Scholar
  33. 33.
    CeDInt-UPM: Centro de Domótica integral – research centre for smart buildings and energy efficiency. http://www.cedint.upm.es/
  34. 34.
    GSI UPM: EscapeSim: ambient intelligence services with participatory simulations. https://www.youtube.com/watch?v=7ZHcpNjjO8c. Accessed February 2015
  35. 35.
    Serrano, E.: UbikSim web service. https://github.com/emilioserra/UbikSimWebService

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ramón Alcarria
    • 1
  • Emilio Serrano
    • 1
  • Jorge Gómez Sanz
    • 2
  • Alberto Fernández
    • 3
  1. 1.Universidad Politécnica de MadridMadridSpain
  2. 2.Universidad Complutense de MadridMadridSpain
  3. 3.Universidad Rey Juan CarlosMadridSpain

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