Understanding and Designing Situation-Aware Mobile and Ubiquitous Computing Systems

Authors: Kai Häussermann, Christoph Hubig, Paul Levi, Frank Leymann, Oliver Siemoneit, Matthias Wieland, Oliver Zweigle

Abstract:

Using spatial models as a shared common basis of information about the environment for different kinds of contextaware systems has been a heavily researched topic in the last years. Thereby the research focused on how to create, to update, and to merge spatial models so as to enable highly dynamic, consistent and coherent spatial models at large scale. In this paper however, we want to concentrate on how context-aware applications could use this information so as to adapt their behavior according to the situation they are in. The main idea is to provide the spatial model infrastructure with a situation recognition component based on generic situation templates. A situation template is – as part of a much larger situation template library – an abstract, machinereadable description of a certain basic situation type, which could be used by different applications to evaluate their situation. In this paper, different theoretical and practical issues – technical, ethical and philosophical ones – are discussed important for understanding and developing situation dependent systems based on situation templates. A basic system design is presented which allows for the reasoning with uncertain data using an improved version of a learning algorithm for the automatic adaption of situation templates. Finally, for supporting the development of adaptive applications, we present a new situation-aware adaptation concept based on workflows.

Keywords: context-awareness, ethics, facilitation of system use through workflows, situation recognition and learning based on situation templates and situation ontology's, theory of situationaware systems

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1063022

References:

[1] R. Lange, N. Cipriani, L. Geiger, M. Großmann, H. Weinschrott, A. Brodt, M. Wieland, S. Rizou, and K. Rothermel. Making the world wide space happen: New challenges for the nexus context platform. In Proceedings of the 7th Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2009), Galveston, TX, USA, 2009.
[2] M. Großmann, M. Bauer, N. Hoenle, U.-P. Kaeppeler, D. Nicklas, and T. Schwarz. Efficiently managing context information for large-scale scenarios. In Proceedings of the 3rd IEEE International Conference on Pervasive Computing and Communications, 2005.
[3] K. Henricksen and J. Indulska. A software engineering framework for context-aware pervasive computing. In Proceedings of the 2nd IEEE International Conference on Pervasive Computing and Communications, 2004.
[4] M. Roman and R. H. Campbell. Gaia: Enabling active spaces. In Proceedings of the 9th ACM SIGOPS European Workshop, Kolding, 2000.
[5] D. Salber, A., K. Dey, and G. D. Abowd. The Context Toolkit: Aiding the development of context-enabled applications. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: The CHI is the Limit, 1999.
[6] A.K. Dey and G. D. Abowd. Towards a better understanding of context and context-awareness. In Proceedings of the Workshop on The What, Who, Where, When, and How of Context-Awareness, as part of the 2000 Conference on Human Factors in Computing Systems (CHI 2000), The Hague, The Netherlands, April 3, 2000.
[7] L. Wetzel. Types and Tokens. In the Stanford Encyclopedia of Philosophy (Winter 2008 Edition), Edward N. Zalta (ed.), URL=http://plato.stanford.edu/archives/win2008/entries/types-tokens/
[8] C.S. Peirce. Collected Papers. Harvard University Press.
[9] C. Hubig. Die Kunst des Möglichen. Band 1: Technikphilosophie als Reflexion der Medialit├ñt. Transcript.
[10] C. Hubig. Abduktion - Das implizite Voraussetzen von Regeln. In G. J├╝ttemann (ed.), Individuelle und soziale Regeln des Handelns, pp. 157- 167, Asanger.
[11] C. Hubig. Interdisziplinarität und Abduktionenwirrwarr. In N. Gottschalk-Mazouz/N. Mazouz (eds.), Nachhaltigkeit und globaler Wandel. pp. 319-340. Campus.
[12] G. Schurz. Patterns of Abduction. In Synthese Vol. 164, No. 2, 2008, pp. 201-234
[13] K.R. Popper. The Logic of Scientific Discovery. Routledge.
[14] G.I. Rochlin. Iran Air Flight 655 and the USS Vincent. In T.R. La Porte (ed.), Social Responses to large scale technical systems. pp. 99-125. Kluwer.
[15] G.I. Rochlin. Trapped in the net. The unanticipated consequences of computerization. Princeton University Press.
[16] J Weyer. Die Risiken der Automatisierungsarbeit. Mensch-Maschine- Interaktion und Störfallmanagement in hochautomatisierten Verkehrsflugzeugen. In Zeitschrift f├╝r Soziologie, Vol. 25, 1997, pp. 239-257.
[17] C. Hubig. Selbstständige Nutzer oder verselbstständigte Medien. Die neue Qualität der Vernetzung. In F. Mattern (ed.), Total vernetzt. Szenarien einer informatisierten Welt. pp. 211-230. Springer.
[18] C. Hubig. Die Kunst des Möglichen. Band 2: Ethik der Technik als provisorische Moral. Transcript.
[19] G. D. Abowd, A. K. Dey, P. J. Brown, N. Davies, M. Smith, and P. Steggles. Towards a better understanding of context and contextawareness. In HUC -99: Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing, pages 304-307, London, UK, 1999. Springer-Verlag.
[20] S. McKeever, J. Ye, L. Coyle, and S. Dobson. A context quality model to support transparent reasoning with uncertain context. In 1st International Workshop on Quality of Context (QuaCon), Stuttgart, Germany, 2009.
[21] Zweigle, Oliver; Häussermann, Kai; Käppeler, Uwe-Philipp; Levi, Paul: Extended TA Algorithm for adapting a Situation Ontology. In: Proceedings of the FIRA RoboWorld Congress 2009, Progress in Robotics. Communications in Computer and Information Science; 44, pp. 364-371, Incheon, Korea: Springer Verlag, August 18, 2009.
[22] de Kleer, J. Using crude probability estimates to guide diagnosis. pages 118-123, 1992.
[23] de Kleer, J. and Williams, B.C. Diagnosing multiple faults. pages 372- 388, 1987.
[24] Mayrhofer, Rene; Radi, Harald and Ferscha, Alois. A.: Recognizing and predicting context by learning from user behavior. pages 25-35, 2003.
[25] Reiter, R. A theory of diagnosis from first principles. Artif. Intell., 32(1):57-95,1987.
[26] Hou, Aimin. A theory of measurement in diagnosis from first principles. Artif.Intell., 65(2):281-328, 1994.
[27] Cheng, R; Prabhakar, S: Managing uncertainty in sensor database. SIGMOD Rec., 32(4):41-46, 2003.
[28] Chen, H. and Finin, T. and Joshi, A.: An ontology for context-aware pervasive computing environments, In: The Knowledge Engineering Review, vol. 18, no 3, pages 197-207, 2004
[29] Wang, X.H. and Zhang, D.Q. and Gu, T. and Pung, H.K.: Ontology based context modeling and reasoning using OWL, In: Proceedings of the second IEEE annual conference on pervasive computing and communications workshops, Vol. 18, 2004
[30] Henricksen, K. and Indulska, J. and Rakotonirainy, A.: Modeling context information in pervasive computing systems, in: Lecture notes in computer science, pages 167-180,2002
[31] B. Brumitt, B. Meyers, J. Krumm, A. Kern, and S. Shafer. Easyliving: Technologies for intelligent environments. pages 12-29. Springer Verlag, 2000.
[32] S. Pado and M. Lapata. Constructing semantic space models from parsed corpora, 2003.
[33] J. Pearl. Probabilistic Reasoning in Intelligent Systems : Networks of Plausible Inference. Morgan Kaufmann, September 1988.
[34] Sowmya Ramachandran, Raymond J. Mooney: Revising Bayesian Network Parameters Using Backpropagation, IN: Proceedings of the 1996 IEEE International Conference on Neural Networks, pp.82-87, Washington D.C., June 1996.
[35] R.M. Neal: Connectionist learning of belief networks, In: Artificial Intelligence, vol. 56, pp. 71-113, 1992.
[36] L.K. Saul, T. Jaakkola, and M.I. Jordan: "Mean field theory for sigmoid belief networks", Technical Report 9501, Computational Cognitive Science, MIT, 1995.
[37] W. Buntine: Operations for learning with graphical models, In: Journal of Artificial Intelligence Research, vol. 2, pp. 159-225, 1994.
[38] M.A. Tanner, Tools for Statistical Inference, Springer-Verlag, New York, second edition, 1993.
[39] R.E. Kass and A.E. Raftery, \Bayes factors and model uncertainty", Journal of the American Statistical Association, vol. 90, pp. 773-795, 1995.
[40] D. Edwards, \Hierarchical interaction models", Journal of the Royal Statistical Society B, vol. 51, no. 3, 1989.
[41] R. Jirousek and S. Preucil: On the effective implementation of the iterative proportional fitting procedure", Computational Statistics and Data Analysis, vol. 19, no. 2, pp. 177-189, 1995.
[42] S.L. Lauritzen: The EM algorithm for graphical association models with missing data, Computational Statistics and Data Analysis, vol. 19, no. 2, pp. 191-201, 1995.
[43] A.P. Dempster, N.M. Laird, and D.B. Rubin: Maximum likelihood from incomplete data via the EM algorithm, In: Journal of the Royal Statistical Society B, vol. 39, pp. 1-38, 1977.
[44] Myers, J.W. and Laskey, K.B. and DeJong, K.A.: Learning bayesian networks from incomplete data using evolutionary algorithms, In: Proceedings of the Genetic and Evolutionary Computation Conference, vol 1,pp:458-465, 1999
[45] Tian, F. and Lu, Y. and Shi, C.: Learning Bayesian networks with hidden variables using the combination of EM and evolutionary algorithms,In: Lecture notes in computer science,pp:568-574, 2001