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Service Modeling for Situation-Aware Communication Method Decision

  • Jungkih Hong
  • Scott SongEmail author
  • Minseok Kim
  • Wonseok Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9748)

Abstract

The expansion of wireless communication networks based on the development of diverse device technologies can promote an environment in which smart phones, tablet PCs, cars can be collaboratively communicated with each other anytime and anywhere. To meet such future expectations, communication is growing in order to enhance various possible interactions between smart devices. In the future, we may use truly immersive ways, which may be virtually indistinguishable from face-to-face meetings, to communicate with other people at a distance [1]. Whilst we develop communication technologies toward that vision, the interface between users and communication devices/systems needs to be advanced. In this paper, we discuss human-communication from the perspective of computers that can proactively learn and know about users. In other words, we want computers of communication system and devices that are well aware of users [2]. Therefore, we propose new models and systematic ways to design and implement the user- and situation-aware communication [3].

Keywords

Intelligent system Context-aware Situational-aware Communication channel Alternative communication 

References

  1. 1.
    Lyytinen, K., Yoo, Y.: Ubiquitous computing. Commun. ACM 45(12), 63–96 (2002)CrossRefGoogle Scholar
  2. 2.
    Schilit, B., Adams, N., Want, R.: Context-aware computing applications. In: First Workshop on Mobile Computing Systems and Applications, WMCSA 1994, pp. 85–90. IEEE (1994)Google Scholar
  3. 3.
    Endsley, M.R.: Toward a theory of situation awareness in dynamic systems. Hum. Factors 37, 32–64 (1995)CrossRefGoogle Scholar
  4. 4.
    Nofi, A.A.: Defining and Measuring Shared Situational Awareness (No. CRM-D0002895. A1). Center for Naval Analyses Alexandria, Alexandria (2000)Google Scholar
  5. 5.
    Csikszentmihalyi, M., Larson, R.: Validity and reliability of the experience-sampling method. J. Nerv. Ment. Dis. 175(9), 526–536 (1987)CrossRefGoogle Scholar
  6. 6.
    Guye-Vuillème, A., Capin, T.K., Pandzic, S., Thalmann, N.M., Thalmann, D.: Nonverbal communication interface for collaborative virtual environments. Virtual Reality 4(1), 49–59 (1999)CrossRefGoogle Scholar
  7. 7.
    Vanderheyden, P.B., Pennington, C.A.: An augmentative communication interface based on conversational schemata. In: Mittal, V.O., Yanco, H.A., Aronis, J., Simpson, R.C. (eds.) Assistive Technology and AI. LNCS (LNAI), vol. 1458, pp. 109–125. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  8. 8.
    Nonaka, H.: Communication interface with eye-gaze and head gesture using successive DP matching and fuzzy inference. J. Intell. Inf. Syst. 21(2), 105–112 (2003)CrossRefGoogle Scholar
  9. 9.
    Eklund, A., Andersson, M., Ohlsson, H., Ynnerman, A., Knutsson, H.: A brain computer interface for communication using real-time fMRI. In: 2010 20th International Conference on Pattern Recognition (ICPR), pp. 3665–3669. IEEE, August 2010Google Scholar
  10. 10.
    Akyildiz, I.F., Brunetti, F., Blázquez, C.: Nanonetworks: a new communication paradigm. Comput. Netw. 52(12), 2260–2279 (2008)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jungkih Hong
    • 1
  • Scott Song
    • 1
    Email author
  • Minseok Kim
    • 1
  • Wonseok Lee
    • 1
  1. 1.Samsung Electronics Co., Ltd.Suwon-siKorea

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