Advertisement

Blockchain Technology for Luggage Tracking

  • Alberto Rodríguez Ludeiro
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 801)

Abstract

Lost luggage is one of the main fears when boarding a plane, especially on long flights. Around 10,000 suitcases are lost every day at airports around the world. The proposed solution is to locate much faster and more efficiently the lost object. There are currently a multitude of players involved in this process, who could synchronize by sharing information, which would save airlines costs. This way, the customer and the airline can know where the luggage is at any time.

Keywords

Blockchain Tracking Sharing information 

Notes

Acknowledgements

This work has been supported by project “IOTEC: Development of Technological Capacities around the Industrial Application of Internet of Things (IoT)”. 0123_IOTEC_3_E. Project financed with FEDER funds, Interreg Spain-Portugal (PocTep).

References

  1. 1.
    Li, T., Sun, S., Bolić, M., Corchado, J.M.: Algorithm design for parallel implementation of the SMC-PHD filter. Sig. Process. 119, 115–127 (2016).  https://doi.org/10.1016/j.sigpro.2015.07.013CrossRefGoogle Scholar
  2. 2.
    Lima, A.C.E.S., De Castro, L.N., Corchado, J.M.: A polarity analysis framework for Twitter messages. Appl. Math. Comput. 270, 756–767 (2015).  https://doi.org/10.1016/j.amc.2015.08.059. Redondo-Gonzalez, E., De Castro, L.N., Moreno-Sierra, J., Maestro De Las Casas, M.L., Vera-Gonzalez, V., Ferrari, D.G., Corchado, J.M.: Bladder carcinoma data with clinical risk factors and molecular markers: a cluster analysis. BioMed Res. Int. 2015 (2015).  https://doi.org/10.1155/2015/168682
  3. 3.
    Li, T., Sun, S., Corchado, J.M., Siyau, M.F.: Random finite set-based Bayesian filters using magnitude-adaptive target birth intensity. In: FUSION 2014 - 17th International Conference on Information Fusion (2014). https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910637788&partnerID=40&md5=bd8602d6146b014266cf07dc35a681e0. Choon, Y.W., Mohamad, M.S., Deris, S., Illias, R.M., Chong, C.K., Chai, L.E., Corchado, J.M.: Differential bees flux balance analysis with OptKnock for in silico microbial strains optimization. PLoS ONE 9(7) (2014).  https://doi.org/10.1371/journal.pone.0102744CrossRefGoogle Scholar
  4. 4.
    Li, T., Sun, S., Corchado, J.M., Siyau, M.F.: A particle dyeing approach for track continuity for the SMC-PHD filter. In: FUSION 2014 - 17th International Conference on Information Fusion (2014). https://www.scopus.com/inward/record.uri?eid=2-s2.0-84910637583&partnerID=40&md5=709eb4815eaf544ce01a2c21aa749d8f
  5. 5.
    García Coria, J.A., Castellanos-Garzón, J.A., Corchado, J.M.: Intelligent business processes composition based on multi-agent systems. Expert Syst. Appl. 41(4 PART 1), 1189–1205 (2014).  https://doi.org/10.1016/j.eswa.2013.08.003. Tapia, D.I., Fraile, J.A., Rodríguez, S., Alonso, R.S., Corchado, J.M.: Integrating hardware agents into an enhanced multi-agent architecture for Ambient Intelligence systems. Inf. Sci. 222, 47–65 (2013).  https://doi.org/10.1016/j.ins.2011.05.002. Costa, Â., Novais, P., Corchado, J.M., Neves, J.: Increased performance and better patient attendance in an hospital with the use of smart agendas. Logic J. IGPL 20(4), 689–698 (2012).  https://doi.org/10.1093/jigpal/jzr021
  6. 6.
    García, E., Rodríguez, S., Martín, B., Zato, C., Pérez, B.: MISIA: middleware infrastructure to simulate intelligent agents. In: Advances in Intelligent and Soft Computing, vol. 91 (2011).  https://doi.org/10.1007/978-3-642-19934-9_14Google Scholar
  7. 7.
    Rodríguez, S., De La Prieta, F., Tapia, D.I., Corchado, J.M.: Agents and computer vision for processing stereoscopic images. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (LNAI), vol. 6077 (2010).  https://doi.org/10.1007/978-3-642-13803-4_12Google Scholar
  8. 8.
    Rodríguez, S., Gil, O., De La Prieta, F., Zato, C., Corchado, J.M., Vega, P., Francisco, M.: People detection and stereoscopic analysis using MAS. In: INES 2010 - 14th International Conference on Intelligent Engineering Systems, Proceedings (2010).  https://doi.org/10.1109/INES.2010.5483855. Baruque, B., Corchado, E., Mata, A., Corchado, J.M.: A forecasting solution to the oil spill problem based on a hybrid intelligent system. Inf. Sci. 180(10), 2029–2043 (2010).  https://doi.org/10.1016/j.ins.2009.12.032
  9. 9.
    Tapia, D.I., Corchado, J.M.: An ambient intelligence based multi-agent system for alzheimer health care. Int. J. Ambient Comput. Intell. 1(1), 15–26 (2009).  https://doi.org/10.4018/jaci.2009010102. Mata, A., Corchado, J.M.: Forecasting the probability of finding oil slicks using a CBR system. Expert Syst. Appl. 36(4), 8239–8246 (2009).  https://doi.org/10.1016/j.eswa.2008.10.003
  10. 10.
    Glez-Peña, D., Díaz, F., Hernández, J.M., Corchado, J.M., Fdez-Riverola, F.: geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research. BMC Bioinf. 10 (2009).  https://doi.org/10.1186/1471-2105-10-187CrossRefGoogle Scholar
  11. 11.
    Fernández-Riverola, F., Díaz, F., Corchado, J.M.: Reducing the memory size of a fuzzy case-based reasoning system applying rough set techniques. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 37(1), 138–146 (2007).  https://doi.org/10.1109/TSMCC.2006.876058CrossRefGoogle Scholar
  12. 12.
    Méndez, J.R., Fdez-Riverola, F., Díaz, F., Iglesias, E.L., Corchado, J.M.: A comparative performance study of feature selection methods for the anti-spam filtering domain. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), LNAI, vol. 4065, pp. 106–120 (2006). https://www.scopus.com/inward/record.uri?eid=2-s2.0-33746435792&partnerID=40&md5=25345ac884f61c182680241828d448c5CrossRefGoogle Scholar
  13. 13.
    Méndez, J.R., Fdez-Riverola, F., Iglesias, E.L., Díaz, F., Corchado, J.M.: Tracking concept drift at feature selection stage in SpamHunting: an anti-spam instance-based reasoning system. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), LNAI, vol. 4106, 504–518 (2006). https://www.scopus.com/inward/record.uri?eid=2-s2.0-33750974465&partnerID=40&md5=f468552f565ecc3af2d3ca6336e09cc2Google Scholar
  14. 14.
    Fdez-Rtverola, F., Corchado, J.M.: FSfRT: forecasting system for red tides. Appl. Intell. 21(3), 251–264 (2004).  https://doi.org/10.1023/B:APIN.0000043558.52701.b1CrossRefGoogle Scholar
  15. 15.
    Corchado, J.M., Pavón, J., Corchado, E.S., Castillo, L.F.: Development of CBR-BDI agents: a tourist guide application. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3155, pp. 547–559 (2004).  https://doi.org/10.1007/978-3-540-28631-8
  16. 16.
    Laza, R., Pavn, R., Corchado, J.M.: A reasoning model for CBR_BDI agents using an adaptable fuzzy inference system. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3040, pp. 96–106. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  17. 17.
    Corchado, J.A., Aiken, J., Corchado, E.S., Lefevre, N., Smyth, T.: Quantifying the Ocean’s CO2 budget with a CoHeL-IBR system. In: Advances in Case-Based Reasoning, Proceedings, vol. 3155, pp. 533–546 (2004)Google Scholar
  18. 18.
    Corchado, J.M., Borrajo, M.L., Pellicer, M.A., Yáñez, J.C.: Neuro-symbolic system for business internal control. In: Industrial Conference on Data Mining, pp. 1–10 (2004).  https://doi.org/10.1007/978-3-540-30185-1_1Google Scholar
  19. 19.
    Corchado, J.M., Corchado, E.S., Aiken, J., Fyfe, C., Fernandez, F., Gonzalez, M.: Maximum likelihood Hebbian learning based retrieval method for CBR systems. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2689, pp. 107–121 (2003).  https://doi.org/10.1007/3-540-45006-8_11
  20. 20.
    Fdez-Riverola, F., Corchado, J.M.: CBR based system for forecasting red tides. Knowl. Based Syst. 16(5–6 SPEC), 321–328 (2003).  https://doi.org/10.1016/S0950-7051(03)00034-0CrossRefGoogle Scholar
  21. 21.
    Glez-Bedia, M., Corchado, J.M., Corchado, E.S., Fyfe, C.: Analytical model for constructing deliberative agents. Int. J. Eng. Intell. Syst. Electr. Eng. Commun. 10(3) (2002)Google Scholar
  22. 22.
    Corchado, J.M., Aiken, J.: Hybrid artificial intelligence methods in oceanographic forecast models. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 32(4), 307–313 (2002).  https://doi.org/10.1109/tsmcc.2002.806072CrossRefGoogle Scholar
  23. 23.
    Li, T.-C., Su, J.-Y., Liu, W., Corchado, J.M.: Approximate Gaussian conjugacy: parametric recursive filtering under nonlinearity, multimodality, uncertainty, and constraint, and beyond. Front. Inf. Technol. Electron. Eng. 18(12), 1913–1939 (2017)CrossRefGoogle Scholar
  24. 24.
    Wang, X., Li, T., Sun, S., Corchado, J.M.: A survey of recent advances in particle filters and remaining challenges for multitarget tracking. Sensors (Switzerland) 17(12) (2017). Art. no. 2707CrossRefGoogle Scholar
  25. 25.
    Morente-Molinera, J.A., Kou, G., González-Crespo, R., Corchado, J.M., Herrera-Viedma, E.: Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic modelling methods. Knowl. Based Syst. 137, 54–64 (2017)CrossRefGoogle Scholar
  26. 26.
    Pinto, T., Gazafroudi, A.S., Prieto-Castrillo, F., Santos, G., Silva, F., Corchado, J.M., Vale, Z.: Reserve costs allocation model for energy and reserve market simulation. In: 2017 19th International Conference on Intelligent System Application to Power Systems, ISAP 2017 (2017). Art. no. 8071410Google Scholar
  27. 27.
    Fyfe, C., Corchado, J.: A comparison of Kernel methods for instantiating case based reasoning systems. Adv. Eng. Inf. 16(3), 165–178 (2002).  https://doi.org/10.1016/S1474-0346(02)00008-3CrossRefGoogle Scholar
  28. 28.
    Chamoso, P., Rivas, A., Martín-Limorti, J.J., Rodríguez, S.: A hash based image matching algorithm for social networks. In: Advances in Intelligent Systems and Computing, vol. 619, pp. 183–190 (2018).  https://doi.org/10.1007/978-3-319-61578-3_18Google Scholar
  29. 29.
    Sittón, I., Rodríguez, S.: Pattern extraction for the design of predictive models in industry 4.0. In: International Conference on Practical Applications of Agents and Multi-agent Systems, pp. 258–261 (2017)Google Scholar
  30. 30.
    García, O., Chamoso, P., Prieto, J., Rodríguez, S., De La Prieta, F.: A serious game to reduce consumption in smart buildings. In: Communications in Computer and Information Science, vol. 722, pp. 481–493 (2017).  https://doi.org/10.1007/978-3-319-60285-1_41Google Scholar
  31. 31.
    Palomino, C.G., Nunes, C.S., Silveira, R.A., González, S.R., Nakayama, M.K.: Adaptive agent-based environment model to enable the teacher to create an adaptive class. In: Advances in Intelligent Systems and Computing, vol. 617 (2017).  https://doi.org/10.1007/978-3-319-60819-8_3Google Scholar
  32. 32.
    Canizes, B., Pinto, T., Soares, J., Vale, Z., Chamoso, P., Santos, D.: Smart city: a GECAD-BISITE energy management case study. In: 15th International Conference on Practical Applications of Agents and Multi-agent Systems PAAMS 2017, Trends in Cyber-Physical Multi-Agent Systems, vol. 2, pp. 92–100 (2017).  https://doi.org/10.1007/978-3-319-61578-3_9Google Scholar
  33. 33.
    Chamoso, P., de La Prieta, F., Eibenstein, A., Santos-Santos, D., Tizio, A., Vittorini, P.: A device supporting the self management of tinnitus. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2017)CrossRefGoogle Scholar
  34. 34.
    Prieto, J., Mazuelas, S., Bahillo, A., Fernández, P., Lorenzo, R.M., Abril, E.J.: On the minimization of different sources of error for an RTT-based indoor localization system without any calibration stage. In: 2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–6 (2010)Google Scholar
  35. 35.
    del Rey, ÁM., Batista, F.K., Dios, A.Q.: Malware propagation in Wireless Sensor Networks: global models vs Individual-based models. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. Salamanca 6(3) (2017)Google Scholar
  36. 36.
    Kushch, S., Castrillo, F.P.: A review of the applications of the Block-chain technology in smart devices and distributed renewable energy grids. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. Salamanca 6(3) (2017)CrossRefGoogle Scholar
  37. 37.
    Pinto, A., Costa, R.: Hash-chain-based authentication for IoT. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. Salamanca 5(4) (2016)Google Scholar
  38. 38.
    García-Valls, M.: Prototyping low-cost and flexible vehicle diagnostic systems. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. Salamanca 5(4) (2016)CrossRefGoogle Scholar
  39. 39.
    Fernández-Fernández, A., Cervelló-Pastor, C., Ochoa-Aday, L.: Energy-aware routing in multiple domains software-defined networks. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. Salamanca 5(3) (2016)CrossRefGoogle Scholar
  40. 40.
    Koskimaki, H., Siirtola, P.: Accelerometer vs. electromyogram in activity recognition. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. Salamanca 5(3) (2016)CrossRefGoogle Scholar
  41. 41.
    Herrero, J.R., Villarrubia, G., Barriuso, A.L., Hernández, D., Lozano, Á., De La Serna González, M.A.: Wireless controller and smartphone based interaction system for electric bicycles. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. Salamanca 4(4) (2015)Google Scholar
  42. 42.
    OMS (ed.): Active Ageing: A Policy Framework. Organización Mundial de la Salud (2002). http://goo.gl/oG5w8M. Accessed 18 Feb 2018
  43. 43.
    VVAA: Plan Integral para la actividad física y el deporte en personas mayores. Ministerio de Cultura (2009)Google Scholar
  44. 44.
    VVAA: Libro blanco del envejecimiento activo, CSD. Ministerio de Educación y Cultura (2010)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.BISITE Digital Innovation HubUniversity of Salamanca. Edificio Multiusos I+D+ISalamancaSpain

Personalised recommendations