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

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 746)

Abstract

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.

Keywords

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

Notes

Acknowledgement

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

References

  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

Personalised recommendations