Abstract
Research in indoor location has acquired a growing importance during the recent years. The main objective is to obtain functional systems able of providing the most precise location, identification and guidance in real time. Currently, none of the existing indoor solutions have obtained location or navigation results as precise as the ones provided by the analog systems used outdoor, such as GPS. This paper presents an indoor location system based on Wi-Fi technology which, from the use of intensity maps and classifiers, allows effective and precise indoor location.
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References
Bouckaert, R.R.: Bayesian Belief Networks: from Construction to Inference, Utrecht, Netherlands (1995)
Verma, T., Pearl, J.: An algorithm for deciding if a set of observed independencies has a causal explanation. In: Proc. of the Eighth Conference on Uncertainty in Artificial Intelligence, pp. 323–330 (1992)
Friedman, N., Geiger, D., Goldszmidt, M.: Bayesian Network Classifiers. Machine Learning 29, 131–163 (1997)
Glassner, A.: Principles of digital image synthesis. Morgan Kaufmann (1995)
Georgé, J.P., Gleizes, M.P., Glize, P.: Emergence of organisations, emergence of functions. In: Symposium on Adaptive Agents and Multi-Agent Systems, pp. 103–108 (2003)
De Paz, J.F., Rodríguez, S., Bajo, J., Corchado, J.M.: Multi-agent system for security control on industrial environments. International Transactions on System Science and Applications Journal 4(3), 222–226 (2008)
Chen, Y.-C., Chiang, J.-R., Chu, H.-H., Huang, P., Tsuid, A.W.: Sensor-Assisted Wi-Fi Indoor Location System for Adapting to Environmental Dynamics (2011)
Razavi, R.S., Perrot, J.-F., Guelfi, N.: Adaptive modeling: An approach and a method for implementing adaptive agents. In: Ishida, T., Gasser, L., Nakashima, H. (eds.) MMAS 2005. LNCS (LNAI), vol. 3446, pp. 136–148. Springer, Heidelberg (2005)
Giunchiglia, F., Mylopoulos, J., Perini, A.: The tropos software development methodology: Processes, models and diagrams. In: AAMAS 2002 Workshop on Agent Oriented Software Engineering (AOSE 2002), pp. 63–74 (2002)
Tapia, D.I., De Paz, J.F., Rodríguez, S., Bajo, J., Corchado, J.M.: Multi-Agent System for Security Control on Industrial Environments. International Transactions on System Science and Applications Journal 4(3), 222–226 (2008)
Duda, R.O., Hart, P.: Pattern classification and Scene Analysis. John Wisley & Sons, New York (1973)
John, C.: Platt Fast training of support vector machines using sequential minimal optimization. In: Advances in Kernel Methods, pp. 185–208 (1999)
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Villarubia, G., Rubio, F., De Paz, J.F., Bajo, J., Zato, C. (2013). Applying Classifiers in Indoor Location System. In: Pérez, J., et al. Trends in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent Systems and Computing, vol 221. Springer, Cham. https://doi.org/10.1007/978-3-319-00563-8_7
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DOI: https://doi.org/10.1007/978-3-319-00563-8_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00562-1
Online ISBN: 978-3-319-00563-8
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