Abstract
Current article discusses the human centered perspective adopted in the European project SandS within the Internet of Things (IoT) framework. SandS is a complete ecosystem of users within a social network developing a collective intelligence and adapting its operation through appropriately processed feedback. In the research work discussed in this paper we will investigate SandS from the user perspective and how users can be modeled through a number of fuzzy knowledge formalism through stereotypical user profiles. Additionally, context modeling in pervasive computing systems and especially in the SandS smart home paradigm is examined through appropriate representation of context cues during overall interaction.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ambient intelligence datasets, http://www.cise.ufl.edu/~prashidi/Datasets/ambientIntelligence.html
Amershi, S., Conati, C.: Unsupervised and supervised machine learning in user modeling for intelligent learning environments. In: Proceedings of the 12th International Conference on Intelligent user Interfaces, pp. 72–81. ACM (2007)
Baader, F., Calvanese, D., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F.: The Description Logic Hand-book: Theory, Implementation and Application. Cambridge University Press (2002)
Baldauf, M., Dustdar, S., Rosenberg, F.: A survey on context-aware systems. Int. J. Ad Hoc Ubiquitous Comput. 2(4), 263–277 (2007), http://dx.doi.org/10.1504/IJAHUC.2007.014070 , doi:10.1504/IJAHUC.2007.014070
Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A., Riboni, D.: A survey of context modelling and reasoning techniques. Pervasive and Mobile Computing 6(2), 161–180 (2010), http://www.sciencedirect.com/science/article/pii/S1574119209000510 , doi:10.1016/j.pmcj.2009.06.002; Context Modelling, Reasoning and Management
Bolchini, C., Curino, C.A., Quintarelli, E., Schreiber, F.A., Tanca, L.: A data-oriented survey of context models. SIGMOD Rec. 36(4), 19–26 (2007), http://doi.acm.org/10.1145/1361348.1361353 , doi:10.1145/1361348.1361353
Boxlab wiki page, http://boxlab.wikispaces.com/List+of+Home+Datasets
Castells, P., Fernandez, M., Vallet, D.: An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval. IEEE Transactions on Knowledge and Data Engineering 19(2) (February 2007); Special issue on Knowledge and Data Engineering in the Semantic Web Era
Castells, P., Fernández, M., Vallet, D., Mylonas, P., Avrithis, Y.: Self-tuning Personalized Information Retrieval in an Ontology-Based Framework. In: Meersman, R., Tari, Z. (eds.) OTM 2005 Workshops. LNCS, vol. 3762, pp. 977–986. Springer, Heidelberg (2005)
Chen, H.: An Intelligent Broker Architecture for Pervasive Context-Aware Systems. PhD thesis, University of Maryland, Baltimore County (2004)
Context database, http://www.pervasive.jku.at/Research/Context_Database/
Contextphone, http://www.cs.helsinki.fi/group/context/#data
Crew cognitive radio experimentation world, http://www.crew-project.eu/
Dey, A.K.: Understanding and using context. Personal and Ubiquitous Computing 5, 4–7 (2001)
European network of living labs, http://www.openlivinglabs.eu/news/enoll-mou-partners
Gauch, S., Chaffee, J., Pretschner, A.: Ontology-Based Personalized Search and Browsing. Web Intelligence and Agent Systems 1(3-4), 219–234 (2004)
Gruber, T.R.: A Translation Approach to Portable Ontology Specification. Knowledge Acquisition 5, 199–220 (1993)
Henricksen, K., Indulska, J., Rakotonirainy, A.: Modeling context information in pervasive computing systems. In: Mattern, F., Naghshineh, M. (eds.) PERVASIVE 2002. LNCS, vol. 2414, p. 167. Springer, Heidelberg (2002), http://dx.doi.org/10.1007/3-540-45866-2_14
Homedata, https://github.com/smakonin/HomeData
Hong, J., Suh, E., Kim, S.: Context-aware systems: A literature review and classification. Expert Systems with Applications 36(4), 8509–8522 (2009)
Junior, P., Filgueiras, L.: User modeling with personas. In: Proceedings of the 2005 Latin American Conference on Human-Computer Interaction, pp. 277–282. ACM (2005)
Klir, G., Bo, Y.: Fuzzy Sets and Fuzzy Logic, Theory and Applications. Prentice Hall, New Jersey (1995)
Kobsa, A.: Generic user modeling systems. User Modeling and User-Adapted Interaction 11(1), 49–63 (2001)
Kiryakov, A., Popov, B., Terziev, I., Manov, D., Ognyanoff, D.: Semantic Annotation, Indexing, and Retrieval. Journal of Web Sematics 2(1), 47–49 (2004)
Miyamoto, S.: Fuzzy Sets in Information Retrieval and Cluster Analysis. Kluwer Academic Publishers, Dordrecht (1990)
Nodobo dataset, http://nodobo.com/release.html
Onelab, https://www.onelab.eu/
Openlab, http://www.ict-openlab.eu/
Planetlab europe, http://www.planet-lab.eu/
Popov, B., Kiryakov, A., Ognyanoff, D., Manov, D., Kirilov, A.: KIM - A Semantic Platform for Information Extraction and Retrieval. Journal of Natural Language Engineering 10(3-4), 375–392 (2004)
Smart* data set, http://traces.cs.umass.edu/index.php/Smart/Smart
W3C Recommendation, OWL Web Ontology Language Reference (February 10, 2004), http://www.w3.org/TR/owl-ref/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Caridakis, G., Siolas, G., Mylonas, P., Kollias, S., Stafylopatis, A. (2013). Intelligent and Adaptive Pervasive Future Internet: Smart Cities for the Citizens. In: Iliadis, L., Papadopoulos, H., Jayne, C. (eds) Engineering Applications of Neural Networks. EANN 2013. Communications in Computer and Information Science, vol 384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41016-1_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-41016-1_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41015-4
Online ISBN: 978-3-642-41016-1
eBook Packages: Computer ScienceComputer Science (R0)