Nothing Special   »   [go: up one dir, main page]

Skip to main content

The Models of Moving Users and IoT Devices Density Investigation for Augmented Reality Applications

  • Conference paper
  • First Online:
Internet of Things, Smart Spaces, and Next Generation Networks and Systems (ruSMART 2017, NsCC 2017, NEW2AN 2017)

Abstract

Applications of augmented reality penetrate into all spheres of human life. With the emergence of glasses of augmented reality, the introduction of this technology in VANET (Vehicular ad hoc network), etc. a number of interesting questions arise. For example, the amount of data that a user can perceive and understand the significance of the received content. The article develops a user perception model, which depends on the type of data, the amount of information and the significance of the data. The user is a queuing system object that receives various data from the surrounding objects. The data is ranked according to the priorities for which the transmission characteristics are determined. With the movement of the user, objects in his environment change. The user perception model defines the requirements for the service delivery model, which will allow the maximization of information that the user can perceive.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Kirichek, R., Vladyko, A., Zakharov, M., Koucheryavy, A.: Model networks for internet of things and SDN. In: 18th International Conference on Advanced Communication Technology (ICACT), pp. 76–79 (2016)

    Google Scholar 

  2. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of things: a survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutor. 17(4), 2347–2376 (2015)

    Article  Google Scholar 

  3. Kirichek, R., Koucheryavy, A.: Internet of things laboratory test bed. In: Zeng, Q.-A. (ed.) Wireless Communications, Networking and Applications. LNEE, vol. 348, pp. 485–494. Springer, New Delhi (2016). doi:10.1007/978-81-322-2580-5_44

    Chapter  Google Scholar 

  4. Broschart, D., Zeile, P.: Architecture: augmented reality in architecture and urban planning. In: Peer Reviewed Proceedings of Digital Landscape Architecture 2015 at Anhalt University of Applied Sciences, pp. 111–118 (2015)

    Google Scholar 

  5. Billinghurst, M., Clark, A., Lee, G.: A survey of augmented reality. Found. Trends Hum.-Comput. Inter. 8(2–3), 73–272 (2015)

    Article  Google Scholar 

  6. Park, H.S., Kim, K.-H.: AR-based vehicular safety information system for forward collision warning. In: Shumaker, R., Lackey, S. (eds.) VAMR 2014. LNCS, vol. 8526, pp. 435–442. Springer, Cham (2014). doi:10.1007/978-3-319-07464-1_40

    Google Scholar 

  7. Koucheryavy, A., Makolkina, M., Paramonov, A.: Applications of augmented reality traffic and quality requirements study and modeling. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds.) DCCN 2016. CCIS, vol. 678, pp. 241–252. Springer, Cham (2016). doi:10.1007/978-3-319-51917-3_22

    Chapter  Google Scholar 

  8. BusinessWire: Global Augmented Reality & Virtual Reality in Healthcare Industry Worth USD 641 Million by 2018 - Analysis, Technologies & Forecasts 2013–2018 - Key Vendors: HologicInc, Artificial Life Inc, Aruba Networks - Research and Markets

    Google Scholar 

  9. Konstantinova, J., Jiang, A., Althoefer, K., Dasgupta, P., Nanayakkara, T.: Implementation of tactile sensing for palpation in robot-assisted minimally invasive surgery: a review. IEEE Sens. J. 14(8), 2490–2501 (2014). Bulling, A., Cakmakci, O., Kunze, K., Rehg, J.M.: Eyewear computing-augmented the humsn with head-mounted wearable assistants. Dagstuhl reports, vol. 6(1), SchlossDagstuhl-Leibniz-Zentrumfuerinformatik (2016)

    Article  Google Scholar 

  10. Hara, H., Kuwabara, H.: Innovation in On-site work using smart devices and augmented reality. Fujitsu Tech. J. 51(2), 12–19 (2015)

    Google Scholar 

  11. 5G and e-Health. White paper, 5GPPP, October 2015

    Google Scholar 

  12. Pyattaev, A., Johnsson, K., Surak, A., Florea, R., Andreev, S., Koucheryavy, Y.: Network-assisted D2D communications: implementing a technology prototype for cellular traffic offloading. In: Wireless Communications and Networking Conference (WCNC), pp. 3266–3271. IEEE (2014)

    Google Scholar 

  13. Vladyko, A., Muthanna, A., Kirichek, R.: Comprehensive SDN testing based on model network. In: Galinina, O., Balandin, S., Koucheryavy, Y. (eds.) NEW2AN/ruSMART -2016. LNCS, vol. 9870, pp. 539–549. Springer, Cham (2016). doi:10.1007/978-3-319-46301-8_45

    Chapter  Google Scholar 

  14. Zhang, M.: Real-time traffic flow prediction using augmented reality. University of Windsor Scholarship at UWindsor. Paper 5687 (2016)

    Google Scholar 

  15. Abdi, L., Meddeb, A., Abdallah, F.B.: Augmented reality based traffic sign recognition for improved driving safety. In: Kassab, M., Berbineau, M., Vinel, A., Jonsson, M., Garcia, F., Soler, J. (eds.) Nets4Cars/Nets4Trains/Nets4Aircraft 2015. LNCS, vol. 9066, pp. 94–102. Springer, Cham (2015). doi:10.1007/978-3-319-17765-6_9

    Google Scholar 

  16. Behzadan, A.H., Kamat, V.R.: Visualization of vehicular traffic in augmented reality for improved planning and analysis of road construction projects. In: Proceedings of 2009 NSF Engineering Research and Innovation Conference, Honolulu, Hawaii (2009)

    Google Scholar 

  17. Wang, G., Ng., T.S.E.: The impact of virtualization on network performance of amazon EC2 data center. In: Proceeding INFOCOM 2010 Proceedings of the 29th Conference on Information Communications, pp. 1163–1171 (2010)

    Google Scholar 

  18. Andreev, S., Galinina, O., Pyattaev, A., Johansson, K., Koucheryavy, Y.: Analyzing assisted offloading of cellular user sessions onto D2D links in unlicensed bands. IEEE J. Sel. Areas Commun. 33(1), 67–80 (2014)

    Article  Google Scholar 

  19. Abdi, L., Meddeb, A., Abdallah, F.B.: In-vehicle augmented reality traffic information system: a new type of communication between driver and vehicle. In: Proceedings of the International Conference on Advanced Wireless, Information, and Communication Technologies (AWICT) (2015)

    Google Scholar 

  20. Fu, W.T., Gasper, J., Kim, S.W.: Mixed and augmented reality (ISMAR). In: 2013 IEEE International Symposium, pp. 59–66. IEEE (2013)

    Google Scholar 

  21. Mogelmose, A., Trivedi, M.M., Moeslund, T.B.: Vision-based traffic sign detection and analysis for intelligent driver assistance systems: perspectives and survey. IEEE Trans. Intell. Transp. Syst. 13(4), 1484–1497 (2012)

    Article  Google Scholar 

  22. Razavi, R., Fleury, M., Ghanbari, M.: Low-delay video control in a personal area network for augmented reality. IET Image Proc. 2(3), 150–162 (2008)

    Article  Google Scholar 

  23. Iversen, V.: Teletraffic engineering and network planning, Department of Photonics Engineering, Technical University of Denmark. [http://www.fotonik.dtu.dk]

  24. Futahi, A.: Wireless sensor networks with temporary cluster head nodes. In: Futahi, A., Paramonov, A., Koucheryavy, A. (eds.) 18th International Conference on Advanced Communication Technology (ICACT), pp. 283–288 (2016)

    Google Scholar 

Download references

Acknowledgment

The publication was financially supported by the Ministry of Education and Science of the Russian Federation (the Agreement number 02.a03.21.0008), RFBR according to the research project No. 16-37-00209 mol_a “Development of the principles of integration the Real Sense technology and Internet of Things”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Makolkina .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Makolkina, M., Koucheryavy, A., Paramonov, A. (2017). The Models of Moving Users and IoT Devices Density Investigation for Augmented Reality Applications. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. ruSMART NsCC NEW2AN 2017 2017 2017. Lecture Notes in Computer Science(), vol 10531. Springer, Cham. https://doi.org/10.1007/978-3-319-67380-6_64

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67380-6_64

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67379-0

  • Online ISBN: 978-3-319-67380-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics