Use Case Scenarios of Dynamically Integrated Devices for Improving Human Experience in Collective Computing

  • Rustam Kamberov
  • Carlos Granell
  • Vitor Santos
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 746)


Smart city concept emerged as a technology supported response to challenges posed by growing cities. To provide ambient intelligence smart cities rely on ubiquitous and context-aware computing. Given the ubiquity of computing devices, the ability to connect objects and people into a smart context-aware system is one contemporary challenge. Our early research proposed a novel approach for dynamic integration of devices into a system with context-aware behavior inspired by concepts used in role theory. The idea behind our model is to embed the predefined internal structure of a system given the context into a mobile device to allow it owing a certain role in that system. The objective of the present paper is to prepare the ground for further prototyping of the model. We present ontology-based use-case scenarios utilizing the model to demonstrate the capabilities of the model.


Context-aware computing Dynamic integration of devices Role theory Ambient intelligence Collective computing 



The authors gratefully acknowledge funding from the European Commission through the GEO-C project (H2020-MSCA-ITN-2014, Grant Agreement Number 642332, Carlos Granell has been partly funded by the Ramón y Cajal Programme (grant number RYC-2014-16913).


  1. 1.
    Vestergaard, L.S., Fernandes, J., Presser, M.A.: Towards smart city democracy. PersPektiv 25, 38–43 (2015)Google Scholar
  2. 2.
    Albino, V., Berardi, U., Dangelico, R.M.: Smart cities: definitions, dimensions, performance, and initiatives. J. Urban Technol. 22(1), 3–21 (2015)CrossRefGoogle Scholar
  3. 3.
    Bakici, T., Almirall, E., Wareham, J.: A smart city initiative: the case of Barcelona. J. Knowl. Econ. 4(2), 135–148 (2013)CrossRefGoogle Scholar
  4. 4.
    Caragliu, A., Del Bo, C., Nijkamp, P.: Smart cities in Europe. J. Urban Technol. 18(2), 65–82 (2011)CrossRefGoogle Scholar
  5. 5.
    Washburn, D., Sindhu, U.: Helping CIOs understand ‘smart city’ initiatives. Growth 17(2), 1–17 (2009)Google Scholar
  6. 6.
    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
  7. 7.
    Shadbolt, N.: Ambient intelligence. IEEE Intell. Syst. 18(4), 2–3 (2003)CrossRefGoogle Scholar
  8. 8.
    Punie, Y.: The future of ambient intelligence in Europe: the need for more everyday life. Commun. Strateg. 1(57), 141–165 (2005)Google Scholar
  9. 9.
    Alfonso-Cendón, J., Fernández-de-Alba, J.M., Fuentes-Fernández, R., Pavón, J.: Implementation of context-aware workflows with multi-agent systems. Neurocomputing 176, 91–97 (2016)CrossRefGoogle Scholar
  10. 10.
    Abowd, G.D.: What next, ubicomp? In: Proceedings of 2012 ACM Conference on Ubiquitous Computing - UbiComp 2012, p. 31 (2012)Google Scholar
  11. 11.
    Weiser, M.: The computer for the 21 century. Sci. Am. 265, 94–104 (1991)CrossRefGoogle Scholar
  12. 12.
    Abowd, G.D.: Beyond weiser: from ubiquitous to collective computing. Computer (Long. Beach. Calif) 49(1), 17–23 (2016)Google Scholar
  13. 13.
    Marques, G., Garcia, N., Pombo, N.: Advances in mobile cloud computing and big data in the 5G era, vol. 22 (2017)Google Scholar
  14. 14.
    Santos, V.: Use of social paradigms in mobile context-aware computing. Procedia Technol. 9, 100–113 (2013)CrossRefGoogle Scholar
  15. 15.
    Kamberov, R., Santos, V., Granell, C.: Toward social paradigms for mobile context-aware computing in smart cities: position paper. In: 2016 11th Iberian Conference on Information Systems and Technologies (CISTI), pp. 1–6 (2016)Google Scholar
  16. 16.
    Kamberov, R., Granell, C., Santos, V.: Sociology paradigms for dynamic integration of devices into a context-aware system. J. Inf. Syst. Eng. Manag. 2(1), 1–11 (2017)Google Scholar
  17. 17.
    Dameri, R.P.: Using ICT in smart city. In: Smart City Implementation, pp. 45–65. Springer International Publishing, Cham (2017)Google Scholar
  18. 18.
    Anttiroiko, A.V.: U-cities reshaping our future: reflections on ubiquitous infrastructure as an enabler of smart urban development. AI Soc. 28(4), 491–507 (2013)CrossRefGoogle Scholar
  19. 19.
    Nieuwdorp, E.: The pervasive discourse. Comput. Entertain. 5(2), 13 (2007)CrossRefGoogle Scholar
  20. 20.
    Satyanarayanan, M.: Pervasive computing: vision and challenges. IEEE Pers. Commun. 8(4), 10–17 (2001)CrossRefGoogle Scholar
  21. 21.
    Schilit, B.N., Adams, N., Want, R.: Context-aware computing applications. In: Proceedings of 1994 First Workshop Mobile Computing Systems and Applications, pp. 85–90 (1994)Google Scholar
  22. 22.
    Baldauf, M., Dustdar, S., Rosenberg, F.: A survey on context-aware systems. Int. J. Ad Hoc Ubiquitous Comput. 2(4), 263 (2007)CrossRefGoogle Scholar
  23. 23.
    Fischer, G.: Context-aware systems. In: Proceedings of International Workshop on Conference on Advanced Visual Interfaces - AVI 2012, p. 287 (2012)Google Scholar
  24. 24.
    Dey, A.K.: Understanding and using context. Pers. Ubiquitous Comput. 5(1), 4–7 (2001)CrossRefGoogle Scholar
  25. 25.
    Markopoulos, P.: Ambient intelligence: vision, research, and life. J. Ambient Intell. Smart Environ. 8(5), 491–499 (2016)CrossRefGoogle Scholar
  26. 26.
    Olaru, A., Florea, A.M., Seghrouchni, A.E.F.: A context-aware multi-agent system as a middleware for ambient intelligence. Mob. Netw. Appl. 18(3), 429–443 (2013)CrossRefGoogle Scholar
  27. 27.
    Bartelt, C., Fischer, T., Niebuhr, D., Rausch, A., Seidl, F., Trapp, M.: Dynamic integration of heterogeneous mobile devices. In: Proceedings of 2005 Workshop on Design and Evolution of Autonomic Application Software, pp. 1–7 (2005)Google Scholar
  28. 28.
    Strohbach, M., Gellersen, H., Kortuem, G., Kray, C.: Cooperative artefacts: assessing real world situations with embedded technology. In: International Conference on Ubiquitous Computing, pp. 250–267 (2004)CrossRefGoogle Scholar
  29. 29.
    Strohbach, M., Kortuem, G., Gellersen, H., Kray, C.: Using cooperative artefacts as basis for activity recognition. In: European Symposium on Ambient Intelligence, pp. 49–60 (2004)Google Scholar
  30. 30.
    Strohbach, M., Gellersen, H.W., Kortuem, G., Kray, C.: Cooperative artefacts. a framework for embedding knowledge in real world objects. In: International Conference on Ubiquitous Computing, pp. 250–267 (2005)Google Scholar
  31. 31.
    Sinha, A., Couderc, P.: A framework for interacting smart objects. In: Internet of Things, Smart Spaces, and Next Generation Networking, pp. 72–83 (2013)CrossRefGoogle Scholar
  32. 32.
    Erickson, T.: Some problems with the notion of context-aware computing. Commun. ACM 45(2), 102–104 (2002)CrossRefGoogle Scholar
  33. 33.
    Jander, K., Lamersdorf, W.: GPMN-edit: high-level and goal-oriented workflow modeling. In: Electronic Communications of the EASST, vol. 37 (2011)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.NOVA Information Management SchoolUNLLisbonPortugal
  2. 2.GEOTEC Research GroupUJICastellón de la PlanaSpain

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