Abstract
A major issue in Pervasive Computing in order to design and implement context–aware applications is to correlate heterogeneous information acquired by distributed devices to provide a more comprehensive view of the context they inhabit. Although information can be geo-referenced according to quantitative models there are a number of reasons for which Qualitative Spatial Representations can be preferred in such context. The paper presents a knowledge-based approach to correlation of information coming from different sources based on Logical Commonsense Spatial Reasoning. In particular a class of models that can be exploited for reasoning about correlation is presented and a framework to provide the desired inferences within a Hybrid Logic framework is given. This framework is claimed to be enough flexible to be exploited in different application domains and an example for a Smart Home application is discussed.
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
Aiello, M., and J. van Benthem (2002): A Modal Walk Through Space. Journal of Applied Non-Classical Logics Vol. 12 No. (3-4), pp. 319-364
Bandini, S., Bogni, D., and Manzoni, S. (2002): Alarm Correlation in Traffic Monitoring and Control Systems: a Knowledge-Based Approach. In: Proceedings of the 15th European Conference on Artificial Intelligence, July 21-26 2002, Lyon (F). Amsterdam: IOS Press, pp. 638–642.
Bandini, S., Alessandro M., Palmonari, M., and Sartori, F. (2004): A Conceptual Framework for Monitoring and Control System Development. In Ubiquitous Mobile Information and Collaboration Systems (UMICS’04), LNCS, Vol. 3272. Springer-Verlag, pp. 112-125.
Bandini, S., Bogni, D., Manzoni, S., and Mosca, A. (2005a): A ST-Modal Logic Approach to Alarm Correlation in Monitoring and Control of Italian Highways Traffic. In Proceedings of The 18th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems. Bari, June 22-25, 2005. Springer-Verlag, pp. 819–828.
Bandini, S., Mosca, A., and Palmonari, M. (2005b): Commonsense Spatial Reasoning for Context–Aware Pervasive Systems. Location- and Context-Awareness, First International Workshop, LoCA 2005, LNCS Vol. 3479. Springer-Verlag, pp. 180–188.
Bandini, S., Mosca, A., and Palmonari, M. (2005c): A Hybrid Logic for Commonsense Spatial Reasoning. Proceedings of the 9th Congress of the Italian Association for Artificial Intelligence. LNAI 3673, Springer-Verlag, pp. 25–37.
Bennett, B. (1996): Modal Logics for Qualitative Spatial Reasoning. Journal of the Interest Group in Pure and Applied Logic. Vol. 4, No. 1. pp. 23-45.
Bennett, B., Cohn, A. G., Wolter, F., and Zakharyaschev, M. (2002): Multi-Dimensional Modal Logic as a Framework for Spatio-Temporal Reasoning. Applied Intelligence 17 (3), pp. 239–251.
Blackburn, P. (2000): Representation, Reasoning and Realtional Structures: a Hybrid Logic Manifesto. Logic Journal of the IGPL, Vol 8 No. 3, pp. 339–365.
Blackburn, P., de Rijke, M., and Venema, Y., (2000): Modal Logic. Cambridge University Press.
Carvalho, H.S., Heinzelman, W.B., Murphy, A.L., and Coelho, C.J.N. (2003): A General Data Fusion Architecture. Proceedings of the 6th International Conference on Information Fusion (Fusion). Cains, Australia, pp. 1465- 1472.
Casati, R., and Varzi, A. (1999): Parts and places: the structures of spatial representation. Cambridge, MA and London: MIT Press.
Chen, H., Finin, T., and Joshi, A. (2004): An Ontology for Context-Aware Pervasive Computing Environments. Knowledge Engineering Review, Vol. 18 No. 3, pp. 197–207.
Christopoulou, E., Goumoupoulos, C., and Kameas, A. (2005): An ontology-based context management and reasoning process for UbiComp applications. In Joint conference on Smart Objects and Ambient Intelligence (sOc-EUSAI). ACM Press, pp. 183–188.
Cohn, A. G, and Hazarika, S. M. (2001): Qualitative Spatial Representation and Reasoning: An Overview. Fundamenta Informaticae, Vol. 46 No. (1-2):, pp.1–29.
Dey, A. K., (2001). Understanding and Using Context. Personal and Ubiquitous Computing, Vol. 5 No. 1, pp. 4–7.
Egenhofer, M. J., and Mark, D. M. (1995): Naive Geography. In Spatial Information Theory - A Theoretical Basis for GIS (COSIT’95), edited by A. U. Frank and W. Kuhn, Berlin, Heidelberg: Springer, pp. 1–15.
Fonseca, F. T., Max, J., Egenhofer, C., Davis, A., and Câmara. G. (2002): Semantic Granularity in Ontology-Driven Geographic Information Systems. Annals of. Mathematics and Artificial Intelligence, Vol. 36 No. (1-2), pp. 121–151.
Ossowski, S., Hernández, J., Belmonte, M., Maseda, J., Fernandez, A., GarcĂa-Serrano, A., Triguero Ruiz, F., Serrano, J. M., and PĂ©rez de-la Cruz, J. L. (2004): Multi-Agent Systems For Decision Support: A Case Study In The Transportation Management Domain. Applied Artificial Intelligence, Vol. 18 No. (9-10), pp. 779–795.
Randell, D. A., Cui, Z., and Cohn, A. G. (1992): A Spatial Logic Based on Regions and Connection. Proceedings of the 3rd Internationa Conference on Knowledge Representation and Reasoning. San Mateo, CA: Morgan Kaufmann, pp. 165–176.
Zambonelli, F., and Parunak, H.V.D. (2002): Signs of a Revolution in Computer Science and Software Engineering. Proceedings of Engineering Societies in the Agents World III (ESAW2002), Volume 2577. Springer-Verlag, pp. 13–28.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Palmonari, M., Bandini, S. (2008). Context-Aware Applications Enhanced with Commonsense Spatial Reasoning. In: Meng, L., Zipf, A., Winter, S. (eds) Map-based Mobile Services. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37110-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-37110-6_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37109-0
Online ISBN: 978-3-540-37110-6
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)