Abstract
Indoor locating systems (RTLS), have notably advanced during recent years, becoming one of the main challenges for several research teams. The main objective of indoor locating systems is to obtain functional systems able to locate different elements in those environment where GPS (Global Positioning System) is limited. The growing use of mobile devices in the information society provides a powerful mechanism to obtain geographical data and has led to new algorithms aimed at facilitating object positioning with easonable power consumption. In this paper we propose an innovative indoor location architecture that makes use of the data provided by mobile devices to locate objects. The architecture is applied to a case study in a real environment focused on obtaining the location of security staff in the subway network in a city in the north of Spain.
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Anand, P., Siva Prasad, B.V., Venkateswarlu, C.: Modeling and optimization of a pharmaceutical formulation system using radial basis function network. International Journal of Neural Systems 19(2), 127–136 (2009)
Carnicer, J.M.C., García-Esnaola, M.: Lagrange interpolation on conics and cubics. Comput. Aided Geom. Design. 19, 313–326 (2002)
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)
Huang, C.N., Chan, C.T.: ligBee-based indoor location system by k-nearest neighbor algorithm with weighted RSSI. Procedia Computer Science 5, 58–65 (2011)
Tesoriero, R., Tebar, R., Gallud, J.A., Lozano, M.D., Penichet, V.M.R.: Improving location awareness in indoor spaces using RFID technology. Expert Systems with Applications 37(1), 894–898 (2010)
Hui, L., Darabi, H., Banerjee, P., Liu, J.: Survey of Wireless Indoor Positioning Techniques and Systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 37(6), 1067–1080 (2007)
Web, http://stephendnicholas.com/archives/1217 (last visited January 14, 2014)
Tapia, D., Bajo, J., De Paz, J.F., Alonso, R.S.: Using Multi-Layer Perceptrons to Enhance the Performance of Indoor RTLS (2011)
Web, http://nodejs.org (last visited January 14, 2014)
Corchado, J.M., Fyfe, C.: Unsupervised neural method for temperature forecasting. Artificial Intelligence in Engineering 13(4), 351–357 (1999)
Fdez-Riverola, F., Corchado, J.M.: CBR based system for forecasting red tides. Knowledge-Based Systems 16(5), 321–328 (2003)
Tapia, D.I., Abraham, A., Corchado, J.M., Alonso, R.S.: Agents and ambient intelligence: case studies. Journal of Ambient Intelligence and Humanized Computing 1(2), 85–93 (2010)
Corchado, J.M., Lees, B.: Adaptation of cases for case based forecasting with neural network support. In: Soft Computing in Case Based Reasoning, pp. 293–319 (2001)
Corchado Rodríguez, J.M.: Redes Neuronales Artificiales: un enfoque práctico. Servicio de Publicacións da Universidade de Vigo, Vigo (2000)
Bajo, J., Corchado, J.M.: Evaluation and monitoring of the air-sea interaction using a CBR-Agents approach. In: Muñoz-Ávila, H., Ricci, F. (eds.) ICCBR 2005. LNCS (LNAI), vol. 3620, pp. 50–62. Springer, Heidelberg (2005)
Fraile, J.A., Bajo, J., Corchado, J.M., Abraham, A.: Applying wearable solutions in dependent environments. IEEE Transactions on Information Technology in Biomedicine 14(6), 1459–1467 (2011)
Corchado, J.M., De Paz, J.F., Rodríguez, S., Bajo, J.: Model of experts for decision support in the diagnosis of leukemia patients. Artificial Intelligence in Medicine 46(3), 179–200 (2009)
De Paz, J.F., Rodríguez, S., Bajo, J., Corchado, J.M.: Case-based reasoning as a decision support system for cancer diagnosis: A case study. International Journal of Hybrid Intelligent Systems 6(2), 97–110 (2009)
Tapia, D.I., Rodríguez, S., Bajo, J., Corchado, J.M.: FUSION@, a SOA-based multi-agent architecture. In: International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008), pp. 99–107 (2008)
Corchado, J.M., Aiken, J.: Hybrid artificial intelligence methods in oceanographic forecast models. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 32(4), 307–313 (2002)
Corchado, J.M., Aiken, J., Rees, N.: Artificial intelligence models for oceanographic forecasting. Plymouth Marine Laboratory (2001)
Rodríguez, S., Pérez-Lancho, B., De Paz, J.F., Bajo, J., Corchado, J.M.: Ovamah: Multiagent-based adaptive virtual organizations. In: 12th International Conference on Information Fusion, FUSION 2009, pp. 990–997 (2009)
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)
Borrajo, M.L., Baruque, B., Corchado, E., Bajo, J., Corchado, J.M.: Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises. International Journal of Neural Systems 21(04), 277–296 (2011)
De Paz, J.F., Rodríguez, S., Bajo, J., Corchado, J.M.: Mathematical model for dynamic case-based planning. International Journal of Computer Mathematics 86(10-11), 1719–1730 (2009)
Bajo, J., De Paz, J.F., Rodríguez, S., González, A.: Multi-agent system to monitor oceanic environments. Integrated Computer-Aided Engineering 17(2), 131–144 (2010)
Tapia, D.I., Alonso, R.S., De Paz, J.F., Corchado, J.M.: Introducing a distributed architecture for heterogeneous wireless sensor networks. In: Omatu, S., Rocha, M.P., Bravo, J., Fernández, F., Corchado, E., Bustillo, A., Corchado, J.M. (eds.) IWANN 2009, Part II. LNCS, vol. 5518, pp. 116–123. Springer, Heidelberg (2009)
Rodríguez, S., de Paz, Y., Bajo, J., Corchado, J.M.: Social-based planning model for multiagent systems. Expert Systems with Applications 38(10), 13005–13023 (2011)
Pinzón, C.I., Bajo, J., De Paz, J.F., Corchado, J.M.: S-MAS: An adaptive hierarchical distributed multi-agent architecture for blocking malicious SOAP messages within Web Services environments. Expert Systems with Applications 38(5), 5486–5499
Corchado, J.M., Bajo, J., De Paz, J.F., Rodríguez, S.: An execution time neural-CBR guidance assistant. Neurocomputing 72(13), 2743–2753 (2009)
Gómez, J., Patricio, M.A., García, J., Molina, J.M.: Communication in distributed tracking systems: an ontology-based approach to improve cooperation. Expert Systems 28(4), 288–305 (2011)
Pavon, J., Sansores, C., Gomez-Sanz, J.J.: Modelling and simulation of social systems with INGENIAS. International Journal of Agent-Oriented Software Engineering 2(2), 196–221 (2008)
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De Paz, J.F., Villarrubia, G., Bajo, J., Sirvent, G., Li, T. (2014). RETRACTED CHAPTER: Indoor Location System for Security Guards in Subway Stations. In: Bajo Perez, J., et al. Trends in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. Advances in Intelligent Systems and Computing, vol 293. Springer, Cham. https://doi.org/10.1007/978-3-319-07476-4_14
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DOI: https://doi.org/10.1007/978-3-319-07476-4_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07475-7
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