Skip to main content
SpringerLink
Log in

Manifold scalable video conveyance for m-wellbeing crisis relevance

  • Published:
Cluster Computing Aims and scope Submit manuscript

Abstract

M-wellbeing utilities are possible to be more and more significant in managing crisis relevance’s which allows backing in real-time through distant health specialists. During such circumstance, a manifold wellbeing-associated streams of video is transmitted from the emergency vehicle to distant clinic will enhance the effectiveness of tele-discussion utility, however, needs a wide bandwidth to support preferred peak signal-noise-ratio (PSNR), no more constantly assured by wireless communication. So as to convey a manifold stream of videos in a solitary bandwidth-constrained wireless medium, a framework proposed in this paper which allows categorizing the existing videos, choose dynamically and adjust accordingly, so that finest video streams are transmitted. The camera grading technique mutually functions along with inter-layer adjustment system intended for manifold scalable video to attain various targets as well as tradeoffs concerns to the amount and target PSNR of videos being conveyed. The goal is to adaptively alter the completely conveyed throughput to support the existing bandwidth, whilst offering high PSNR to investigative videos and low PSNR to less significant environment videos. Considering a sensible crisis situation, simulations performed in long term evolution advanced communication demonstrate that the proposed content and environment-sensitive result can choose the finest video source from a visual perspective and to attain ideal end-to-end PSNR both for investigative and environment videos.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Ahern, D.K., Kreslake, J.M., Phale, J.M.: What Is eHealth (6): perspectives on the evolution of eHealth research. J. Med. Internet Res. 8(1), e4 (2006)

    Article  Google Scholar 

  2. Perakis, K.: Third generation (3G) cellular networks. In: Telemedicine: Technological Overview, Applications, and Limitations. IGI Global, Hershey, PA, USA (2014)

  3. Paradiso, R., et al.: Remote health monitoring with wearable non-invasive mobile system: the healthwear project. In: Proceedings IEEE 30th Annual International Conference of the IEEE, pp. 1699–1702 . IEEE (Aug. 2008)

  4. Panayides, A., Eleftheriou, I., Pantziaris, M.: Open-source telemedicine platform for wireless medical video communication. Int. J. Telemed. Appl. 2013(457491), 12 (2013)

    Google Scholar 

  5. Martini, M.G., Istepanian, R.S.H., Mazzotti, M., Philip, N.Y.: Robust multilayer control for enhanced wireless telemedical video streaming. IEEE Trans. Mob. Comput. 9(1), 5–16 (2010)

    Article  Google Scholar 

  6. Tavli, B., Bicakci, K., Zilan, R., et al.: A survey of visual sensor networks. Multimed. Tools Appl. 60, 689 (2012)

    Article  Google Scholar 

  7. Ferrus, R., Sallent, O., Baldini, G., Goratti, L.: LTE: the technology driver for future public safety communications. IEEE Commun. Mag. 51(10), 154–161 (2013)

    Article  Google Scholar 

  8. Skorin-Kapov, L., Matijasevic, M.: Analysis of QoS requirements for E-health services and mapping to evolved packet system QoS classes. Int. J. Telemed. Appl. 2010(628086), 9 (2010)

    Google Scholar 

  9. Soro, S., Heinzelman, W.: A survey of visual sensor networks. Adv. Multimed. 2009(640386), 21 (2009)

    Google Scholar 

  10. Konda, K.R., Conci, N., De Natale, F.: Global coverage maximization in PTZ-camera networks based on visual quality assessment. IEEE Sens. J. 16(16), 6317–6332 (2016)

    Article  Google Scholar 

  11. Cho, Y., Lim, S.O., Yang, H.S.: Collaborative occupancy reasoning in visual sensor network for scalable smart video surveillance. IEEE Trans. Consumer Electron. 56(3), 1997–2003 (2010)

    Article  Google Scholar 

  12. Gallego, J.R., et al.: Performance analysis of multiplexed medical data transmission for mobile emergency care over the UMTS channel. IEEE Trans. Inf. Technol. Biomed. 9(1), 13–22 (2005)

    Article  Google Scholar 

  13. Alinejad, A., Philip, N.Y., Istepanian, R.S.: Cross-layer ultrasound video streaming over mobile WiMAX and HSUPA networks. IEEE Trans. Inf. Technol. Biomed. 16(1), 31–39 (2012)

    Article  Google Scholar 

  14. Martini, M.G., Istepanian, R.S.H., Mazzotti, M., Philip, N.: A crosslayer approach for wireless medical video streaming in robotic teleultrasonography. In: Proceedings of the International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3082–3085 (Aug. 2007)

  15. Ghanavati, S.A., Jemal, H.I., Davood, A., Abdulhameed, A.: Cloud-assisted IoT-based health status monitoring framework. Clust. Comput. 20(2), 1843–1853 (2017)

    Article  Google Scholar 

  16. Debono, C.J., Micallef, B.W., Philip, N.Y., AliNejad, A., Istepanian, R.S., Amso, N.N.: Cross Layer design for optimised region of interest of ultrasound video data over mobile WiMAX. IEEE Trans. Inf. Technol. Biomed. 16(6), 1007–1014 (2013)

    Article  Google Scholar 

  17. Hassan, M.M., Hossain, M.A., Abdullah-Al-Wadud, M., Al-Mudaihesh, T., Alyahya, S., Alghamdi, A.: A scalable and elastic cloud-assisted publish/subscribe model for IPTV video surveillance system. Clust. Comput. 18(4), 1539–1548 (2015)

    Article  Google Scholar 

  18. Rehman, I.U., Philip, N.Y.: M-QoE driven context, content and network aware medical video streaming based on fuzzy logic system over 4G and beyond small cells. In: Proceedings of IEEE EUROCON 2015-International Conference on Computer as a Tool, pp. 1–6 (Sep. 2015)

  19. Panayides, A., et al.: High-resolution, low-delay, and error-resilient medical ultrasound video communication using H.264/AVC over mobile WiMAX networks. IEEE J. Biomed. Health Inf. 17(3), 619–628 (2013)

  20. Cicalo, S., Mazzotti, M., Moretti, S., Tralli, V., Chiani, M.: Multiple video delivery in m-health emergency applications. IEEE Trans. Multimed. 18(10), 1988–2001 (2016)

    Article  Google Scholar 

  21. Iacobelli, L., et al.: An architecture for m-health services: The CONCERTO project solution. In: Proceedings of European Conference Networks and Communication, pp. 118–122 (Jun. 2015)

  22. Antoniou, Z., et al.: Adaptive emergency scenery video communications using HEVC for responsive decision support in disaster incidents. In: Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 173–176 (Aug. 2015)

  23. Schwarz, H., Marpe, D., Wiegand, T.: Overview of the scalable video coding extension of the H.264/AVC standard. IEEE Trans. Circ. Syst. Video Technol. 17(9), 1103–1120 (2007)

  24. Hu, H., et al.: Proxy-based multi-stream scalable video adaptation over wireless networks using subjective quality and rate models. IEEE Trans. Multimed. 15(7), 1638–1652 (2013)

    Article  Google Scholar 

  25. Cical‘o, S., Tralli, V.: Distortion-fair cross-layer resource allocation for scalable video transmission in OFDMA wireless networks. IEEE Trans. Multimed. 16(3), 848–863 (2014)

  26. Moretti, S., Cical‘o, S., Mazzotti, M., Tralli, V., Chiani, M.: Content/context-aware multiple camera selection and video adaptation for the support of m-health services. Procedia Comput. Sci, 40, 206–213 (2014)

  27. Shaeffer, D.K.: MEMS inertial sensors: a tutorial overview. IEEE Commun. Mag. 51(4), 100–109 (2013)

    Article  Google Scholar 

  28. Sobhani, B., Paolini, E., Giorgetti, A., Mazzotti, M., Chiani, M.: Target tracking for UWB multistatic radar sensor networks. IEEE J. Sel. Topics Signal Process. 8(1), 125–136 (2014)

    Article  Google Scholar 

  29. Dardari, D., Closas, P., Djuric, P.M.: Indoor tracking: theory, methods, and technologies. IEEE Trans. Veh. Technol. 64(4), 1263–1278 (2015)

    Article  Google Scholar 

  30. Glanzer, G.: Personal and first-responder positioning: State of the art and future trends. Proceedings Ubiquitous Positioning, Indoor Navigation, Location Based Service 2012, 1–7 (Oct. 2012)

  31. Policy and Charging Control Architecture, 3GPP TS 23.203, v10.7.0, 12

  32. Stuhlmuller, K., Farber, N., Link, M., Girod, B.: Analysis of video transmission over lossy channels. IEEE J. Sel. Areas Commun. 18(6), 1012–1032 (2000)

    Article  Google Scholar 

  33. Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Imag. Process. 13(4), 600–612 (2004)

    Article  Google Scholar 

  34. Cical‘o, S., Changuel, N., Tralli, V., Sayadi, B., Faucheux, F., Kerboeuf, S.: Improving QoE and fairness in HTTP adaptive streaming over LTE network. IEEE Trans. Circ. Syst. Video Technol . 26(12), 2284–2298 (2016)

  35. Martini, M.G., Hewage, C.T.: Flexible macroblock ordering for context-aware ultrasound video transmission over mobile WiMAX. Int. J. Telemed. Appl. 2010, 1–7 (2010)

    Google Scholar 

  36. Lin, K., Dumitrescu, S.: Cross-layer resource allocation for scalable video over OFDMA wireless networks: trade-off between quality fairness and efficiency. IEEE Trans. Mulmed. 99, 1 (2017)

    Google Scholar 

  37. Mazzotti, M., Moretti, S., Chiani, M.: Multiuser resource allocation with adaptive modulation and LDPC coding for heterogeneous traffic in OFDMA downlink. IEEE Trans. Commun. 60(10), 2915–2925 (2012)

    Article  Google Scholar 

  38. JSVM 9.19.11, Reference Software (Feb. 2011)

Download references

Author information

Authors and Affiliations

  1. Faculty of Information & Communication, Anna University, Chennai, India

    L. Balaji

  2. Department of ECE, Velammal Institute of Technology, Chennai, 601204, India

    L. Balaji

  3. RMD Engineering College, Chennai, 601206, India

    K. K. Thyagharajan

Authors
  1. L. Balaji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. K. Thyagharajan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to L. Balaji.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Balaji, L., Thyagharajan, K.K. Manifold scalable video conveyance for m-wellbeing crisis relevance. Cluster Comput 22 (Suppl 5), 10729–10741 (2019). https://doi.org/10.1007/s10586-017-1168-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10586-017-1168-x

Keywords

Search

Navigation