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Cultural IoT Framework Focusing on Interactive and Personalized Museum Sightseeing

  • Sotirios Kontogiannis
  • George KokkonisEmail author
  • Ioannis Kazanidis
  • Michael Dossis
  • Stavros Valsamidis
Chapter
  • 16 Downloads
Part of the Internet of Things book series (ITTCC)

Abstract

Museum visitors are very focused and demanding. Immersive technologies as virtual and augmented reality, interactive haptics, 3D scanning and plotting, content digitization, and personalized automatic navigation must be exploited by museums in order to stimulate museum visitors and extract their attention. The authors of this work propose an open source IoT InteRactive Museum Experience (IRME) framework. IRME offers information classified in thematic sections. The visitors have the opportunity to explore specific thematic sections of interest. Navigation instructions and artwork guidelines are obtained with the help of a smart phone application. Data-mining, artificial intelligence and cognitive services offer the ability to learn from visitor’s preferences and respond more accurately to future requests and in this way enhance visitor’s experience in the museum. IRME provides a real-time, responsive and personalized navigation to museum visitors. It includes indoor positioning technology, IoT sensors and actuators, haptic devices orchestrated over cloud services. Wherever possible, IRME uses low power technology such as Bluetooth Low Energy devices, led plates-spots-cubes and 3D printing modeling capabilities, in order to promote museum artifacts and to enhance the visitors’ knowledge acquisitions and entertainment. Moreover, the reflection of such recreational improvements to the visitors is also measured using IoT sensors and the results are used as feedback for future thematic land planning, and IoT illustration techniques.

Keywords

IoT IoT protocols BLE technology Haptics Indoor positioning beacons Smart agents Cognitive services Chat-bots Classification algorithms Data mining algorithms Mobile phone applications Museums 

References

  1. 1.
    Oh, S.Y., Bailenson, J.: Virtual and augmented reality. Int. Encycl. Media Eff. 1–16 (2017)Google Scholar
  2. 2.
    Chatzopoulos, D., Bermejo, C., Huang, Z., Hui, P.: Mobile augmented reality survey: from where we are to where we go. IEEE Access 5(1), 6917–6950 (2017)CrossRefGoogle Scholar
  3. 3.
    Milgram, P., Kishino, F.: A taxonomy of mixed reality visual displays. IEICE Trans. Inf. Syst. 77(12) (1994)Google Scholar
  4. 4.
    Gleb, B. (2018). https://rubygarage.org/blog/difference-between-ar-vr-mr. Accessed March 2018
  5. 5.
    Schnabel, M.A., Wang, X., Seichter, H., Kvan, T.: From virtuality to reality and back. Proc. Int. Assoc. Soc. Des. Res. 1(15), 115–129 (2007)Google Scholar
  6. 6.
    Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of things (IoT): a vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013)CrossRefGoogle Scholar
  7. 7.
    Vermesan, O., Friess, P. (eds.): Internet of things: converging technologies for smart environments and integrated ecosystems. River Publ. (2013). ISBN: 8792982859Google Scholar
  8. 8.
    Sornalatha, K., Kavitha, V.R.: A smart museum using internet of things. Int. Res. J. Eng. Technol. 3(1), 750–754 (2016)Google Scholar
  9. 9.
    Chianese, A., Piccialli, F.: Improving user experience of cultural environment through IoT: the beauty or the truth case study. In: Intelligent Interactive Multimedia Systems and Services, vol. 1, no 1, pp. 11–20. Springer, Cham (2015)Google Scholar
  10. 10.
    Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)CrossRefGoogle Scholar
  11. 11.
    Lee, I., Lee, K.: The internet of things (IoT): applications, investments, and challenges for enterprises. Bus. Horiz. 58(4), 431–440 (2015)CrossRefGoogle Scholar
  12. 12.
    Kokkonis, G., Psannis, E.K., Roumeliotis, M., Ishibashi, Y.: Efficient algorithm for transferring a real-time HEVC stream with haptic data through the internet. J. Real-Time Image Proc. 12(2), 343–355 (2016)CrossRefGoogle Scholar
  13. 13.
    Kuflik, T., Stock, O., Zancanaro, M., Gorfinkel, A., Jbara, S., Kats, S., Kashtan, N.: A visitor’s guide in an active museum: presentations, communications, and reflection. J. Comput. Cult. Herit. (JOCCH) 3(3), 11 (2011)Google Scholar
  14. 14.
    Kuflik, T., Wecker, A.J., Lanir, J., Stock, O.: An integrative framework for extending the boundaries of the museum visit experience: linking the pre, during and post visit phases. Inf. Technol. Tour. 15(1), 17–47 (2015)Google Scholar
  15. 15.
    Gite, B.B., Pandey, S.: An indoor IoT based location aware system. Int. J. Adv. Res. Comput. Commun. Eng. 5(12), 253–254 (2016)CrossRefGoogle Scholar
  16. 16.
    Solima, L., Della Peruta, M.R., Maggioni, V.: Managing adaptive orientation systems for museum visitors from an IoT perspective. Bus. Process. Manag. J. 22(2), 285–304 (2016)Google Scholar
  17. 17.
    Chianese, A., Piccialli, F.: Designing a smart museum: when cultural heritage joins IoT. In: Proceedings—2014 8th International Conference on Next Generation Mobile Applications, Services and Technologies, pp. 300–306 (2014)Google Scholar
  18. 18.
    Rostamian, M., Parsa, M., Groza, V.: Design and fabrication of a smart electronic guide for museums. In: Applied Computational Intelligence and Informatics (SACI), 7th IEEE International Symposium, IEEE, pp. 439–444 (2012)Google Scholar
  19. 19.
    Mohammadi, M., Al-Fuqaha, A., Guizani, M., Oh, J.S.: Semisupervised deep reinforcement learning in support of IoT and smart city services. IEEE Internet Things J. 5(2), 624–635 (2018)Google Scholar
  20. 20.
    Alleto, S., Cucchiara, R., Del Fiore, G., Mainetti, L., Mighali, V., Patrono, L., Serra, G.: An indoor location-aware system for an IoT-based smart museum. IEEE Internet Things J. 3(2), 244–253 (2016)CrossRefGoogle Scholar
  21. 21.
    Chen, C.Y., Chang, B.R., Huang, P.S.: Multimedia augmented reality information system for museum guidance. Pers. Ubiquit. Comput. 18(2), 315–322 (2014)Google Scholar
  22. 22.
    Kuusik, A., Roche, S., Weis, F.: Smartmuseum: cultural content recommendation system for mobile users. In: 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology, IEEE, pp. 477–482 (2009)Google Scholar
  23. 23.
    Amato, F., Chianese, A., Mazzeo, A., Moscato, V., Picariello, A., Piccialli, F.: The talking museum project. Procedia Comput. Sci. 21, 114–121 (2013)Google Scholar
  24. 24.
    Marshall, M.T., Dulake, N., Ciolfi, L., Duranti, D., Kockelkorn, H., Petrelli, D.: Using tangible smart replicas as controls for an interactive museum exhibition. In: Proceedings of the TEI’16: Tenth International Conference on Tangible, Embedded, and Embodied Interaction, ACM, pp. 159–167 (2016)Google Scholar
  25. 25.
    Korzun, D., Varfolomeyev, A., Yalovitsyna, S., Volokhova, V.: Semantic infrastructure of a smart museum: toward making cultural heritage knowledge usable and creatable by visitors and professionals. Pers. Ubiquit. Comput. 21(2), 345–354 (2017)CrossRefGoogle Scholar
  26. 26.
    Wu, Q., Ding, G., Xu, Y., Feng, S., Du, Z., Wang, J. Long, K.: Cognitive internet of things: a new paradigm beyond connection. IEEE Internet Things J. 1(2), 129–143 (2014)Google Scholar
  27. 27.
    Foteinos, V., Kelaidonis, D., Poulios, G., Vlacheas, P., Stavroulaki, V., Demestichas, P.: Cognitive management for the internet of things: a framework for enabling autonomous applications. IEEE Veh. Technol. Mag. 8(4), 90–99 (2013)Google Scholar
  28. 28.
    Haykin, S.: Cognitive dynamic systems: radar, control, and radio [point of view]. Proc. IEEE 100(7), 2095–2103 (2012A)Google Scholar
  29. 29.
    Haykin, S.: Cognitive dynamic systems: perception-action cycle, radar and radio. Cambridge University Press, New York (2012B)Google Scholar
  30. 30.
    Feng, S., Setoodeh, P., Haykin, S.: Smart home: cognitive interactive people-centric internet of things. IEEE Commun. Mag. 55(2), 34–39 (2017)Google Scholar
  31. 31.
    Tsai, C.-W., Lai, C.-F., Vasilakos, A.V.: Future internet of things: open issues and challenges. Wtrel. Netw. 20(8), 2201–2217 (2014)Google Scholar
  32. 32.
    Tahyudin, I., Saputra, D.I.S., Haviluddin, H.: An interactive mobile augmented reality for tourism objects at Purbalingga district. Indones. J. Electr. Eng. Comput. Sci. 1(2), 375–380 (2016)CrossRefGoogle Scholar
  33. 33.
    Jinu, S., Gracia, S., Deepika, S.: An indoor location aware architecture IOT based heterogeneity smart museum. J. Chem. Pharm. Sci. 11(1), 71–73 (2017)Google Scholar
  34. 34.
    Skamantzari M., Kontogianni G., Georgopoulos A., Kazanis S.: Developing a virtual museum for the Stoa of Attalos. 2017 9th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games), Athens, pp. 260–263 (2017)Google Scholar
  35. 35.
    Eddystone protocol specification, Beacon platform and Proximity beacons API. https://github.com/google/eddystone, https://developers.google.com/beacons/, Google Inc. (2017)
  36. 36.
    Wirola, L., Laine, T., Syrjärinne J.: Mass market considerations for indoor positioning and navigation. In: Proceedings of the 2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 15–17 Sept 2010, Campus Science City, ETH Zurich, SwitzerlandGoogle Scholar
  37. 37.
    EvAAL-Evaluating Ambient Assisted Living systems. http://evaal.aaloa.org/. Last accessed 20 Nov 2017
  38. 38.
    Sakpere, W., Adeyeye-Oshin, M., Mlitwa, N.B.W.: A state of the art survey of indoor positioning and navigation systems and technologies. SACJ 29(3) (2017). ISSN: 2313–7835Google Scholar
  39. 39.
    Zhuang, Y., Yang., J, Li., Y, Qi, L., El-Sheimy N.: Smartphone-based indoor localization with bluetooth low energy beacons. Sensors 16(5), 1–20 (2016).  https://doi.org/10.3390/s16050596
  40. 40.
    Geoserver: An open source server for sharing geospatial data (2009). https://geoserver.org. Accessed Sept 2012
  41. 41.
    Microsoft Azure cognitive services., Azure Bot Service and Language Understanding (LUIS) (2017). https://azure.microsoft.com/en-in/updates/azure-bot-service-and-language-understanding-luis/
  42. 42.
    Massie, T.H., Salisbury, J.K.: The phantom haptic interface: a device for probing virtual objects. In: Proceedings of the ASME Winter Annual Meeting, Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, vol. 55, no. 1, pp. 295–300 (1994)Google Scholar
  43. 43.
    Turner, M., Gomez, D., Tremblay, M., Cutkosky, M.: Preliminary tests of an arm grounded haptic feedback device in tele manipulation. In: Proceedings of the ASME Dynamic Systems and Control Division, vol. DSC-64, pp. 145–149 (1998)Google Scholar
  44. 44.
    Bouzit, M., Popescu, G., Burdea, G., Boian, R.: The rutgers master II-ND force feedback glove. In: Proceedings of IEEE VR 2002 Haptics Symposium, Orlando FL, March 2002Google Scholar
  45. 45.
    Bluetooth Core Specification, ver. 5, Bluetooth SIG, December 2016. https://www.bluetooth.com/specifications/bluetooth-core-specification
  46. 46.
    Gomez, C., Oller, J., Paradells, J.: Overview and evaluation of Bluetooth low energy: an emerging low-power wireless technology. Sensors 12(9) (2012)Google Scholar
  47. 47.
    Blasio, D.G., Quesada-Arencibia, A., Garcia, R.C., Rodriguez, C.J., Moreno-Diaz, R.: A protocol-channel-based indoor positioning performance study for bluetooth low energy. IEEE Access 6, 33440–33450 (2018).  https://doi.org/10.1109/ACCESS.2018.2837497
  48. 48.
    Hernandez-Rojas, L.D., Fernandez-Carames, M.T., Fraga-Lamas, P., Escudero, J.C.: Design and practical evaluation of a family of lightweight protocols for heterogeneous sensing through BLE beacons in IoT telemetry applications. Sensors 57(18) (2018).  https://doi.org/10.3390/s18010057
  49. 49.
    Shelby, Z., Hartke, K., Bormann, C.: Constrained application protocol (CoAP) (2013). http://coap.technology. Accessed March 2015
  50. 50.
    Tanganelli, G., Vallati, C., Mingozzi, E.: CoAPthon: easy development of CoAP-based IoT applications with Python. In: IEEE World Forum on Internet of Things (WF-IoT 2015) (2015).  https://doi.org/10.1109/wf-iot.2015.7389028
  51. 51.
    Ishibashi, Y., Kanbara, T., Tasaka, S.: Inter-stream synchronization between haptic media and voice in collaborative virtual environments. In: Proceedings of 12th Annual of ACM International Conference on Multimedia, New York, pp. 604–611 (2004)Google Scholar
  52. 52.
    Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, A., Peterson, J., Sparks, R., Schooler, E.: SIP: session initiation protocol. RFC 3261 (2002)Google Scholar
  53. 53.
    Kokkonis, G., Psannis, K.E., Roumeliotis, M., Ishibashi, Y., Kim, B.G., Constantinides, A.G.: Transferring wireless high update rate supermedia streams over IoT. In: New Advances in the Internet of Things, pp. 93–103. Springer (2018)Google Scholar
  54. 54.
    Meshroom, open-source 3D Reconstruction Software based on the AliceVision framework (2017). https://github.com/alicevision/meshroom. Accessed June 2018
  55. 55.
    AliceVision Framework, A Photogrammetric Computer Vision Framework which provides a 3D Reconstruction and Camera Tracking algorithms. https://github.com/alicevision/AliceVision (2012)
  56. 56.
    Regard3D, a free and open source structure-from-motion program (2017). http://www.regard3d.org/. Accessed June 2018

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Sotirios Kontogiannis
    • 1
  • George Kokkonis
    • 2
    Email author
  • Ioannis Kazanidis
    • 1
  • Michael Dossis
    • 3
  • Stavros Valsamidis
    • 4
  1. 1.Laboratory of Distributed Microcomputer Systems, Department of MathematicsUniversity of IoanninaIoanninaGreece
  2. 2.Department of Business AdministrationWestern Macedonia University of Applied SciencesGrevenaGreece
  3. 3.Department of Computer ScienceWestern Macedonia University of Applied SciencesKastoriaGreece
  4. 4.Department of Accounting and FinanceTechnological Educational Institute of Eastern MacedoniaKavalaGreece

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