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Green media-aware medical IoT system

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Abstract

Rapid proliferation in state-of-the art technologies has revolutionized the medical market for providing urgent, effective and economical health facilities to aging society. In this context media (i.e., video) transmission is considered as a quite significant step during first hour of the emergency for presenting a big and better picture of the event. However, the energy hungry media transmission process and slow progress in battery technologies have become a major and serious problem for the evolution of video technology in medical internet of things (MIoT) or internet of medical things (IoMT). So, promoting Green (i.e., energy-efficient) transmission during voluminous and variable bit rate (VBR) video in MIoT is a challenging and crucial problem for researchers and engineers. Therefore, the need arose to conduct research on Green media transmission techniques to cater the need of upcoming wearable healthcare devices. Thus, this research contributes in two distinct ways; first, a novel and sustainable Green Media Transmission Algorithm (GMTA) is proposed, second, a mathematical model and architecture of Green MIoT are designed by considering a 8-min medical media stream named, ‘Navigation to the Uterine Horn, transection of the horn and re-anastomosis’ to minimize transmission energy consumption in media-aware MIoT, and to develop feasible media transmission schedule for sensitive and urgent health information from physian to patients and vice vers through extremely power hungry natured wearable devices. The experimental results demonstrate that proposed GMTA saves energy up to 41%, to serve the community.

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References

  1. Aborokbah MM et al (2017) Adaptive context aware decision computing paradigm for intensive health care delivery in smart cities—a case analysis. Sustain Cities Soc. https://doi.org/10.1016/j.scs.2017.09.004

  2. Decker R, Stummer C (2017) Marketing management for consumer products in the era of the internet of things. Adv IoT Scientific 7(2017):47–70

    Google Scholar 

  3. Dimitrov DV (2016) Medical internet of things and big data in healthcare. Health Inform Res 22(3):156–163

    Article  Google Scholar 

  4. Gonzalez E et al (2015) Survey of WBSNs for pre-hospital assistance: trends to maximize the networks lifetime and video transmission techniques. MDPI Sens 15(5):11993–12021

    Article  Google Scholar 

  5. Gope P, Hwang T (2016) BSN-Care: a secure IoT-based modern healthcare systems using BSN. IEEE Sens J 16(5):1368–1376

    Article  Google Scholar 

  6. Hamlyn Center Laparoscopic/endoscopic video datasets, http://hamlyn.doc.ic.ac.uk/vision/

  7. Hao Y, Limei P et al (2017) Energy harvesting based BANs for Smart health. MDPI Sensor 17(7):1–10

    Article  Google Scholar 

  8. Hassanalierag M, Page A et al (2015) Health monitoring and management using IoT Sesnong with cloud-based processing: opportunities and challenges. IEEE International Conference on Services Computing, New York City, pp 285–292

  9. Jusak J et al (2016) Internet of medical things for cardiac monitoring: paving the way to 5G mobile networks.IEEE International Conference Communication, Networks and Satellite (COMNETSAT), Surabaya, pp 75–79

  10. Kumar P et al (2017) A certificateless aggregate signature scheme for healthcare wireless sensor network. Sus Comput Inf Syst. https://doi.org/10.1016/j.suscom.2017.09.002

  11. Le NT et al (2016) Survy of promising technologies for 5G networks. Mob Inf Syst 2016(2016):1–26

    Google Scholar 

  12. Martinez B, Mont M (2015) The power of models: modeling power consumption for IoT devices. IEEE Sens J 15(10):5777–5789

    Article  Google Scholar 

  13. Mekomen T, Porambage P et al (2017) Energy consumption analysis of high quality multitier wireless multimedia sensor networks. IEEE Access 5(1):15848–15858

    Article  Google Scholar 

  14. Militano L et al (2015) Device to device communication for 5G internet of things. Eur Alliance Innov Endrosed Trans IoT 1(1):1–16

    Google Scholar 

  15. Mountney P, Stoyanov D, Yang G-Z (2010) Three-dimensional tissue deformation recovery and tracking: introducing techniques based on laparoscopic or endoscopic images. IEEE Signal Process Mag 27(4):14–24

    Article  Google Scholar 

  16. Paul A, Rho S (2016) Probablistic model for M2M in IoT networking and communication. Telecommun Syst 62(2016):59–66

    Article  Google Scholar 

  17. Qiu T et al (2017) A lifetime-enhanced data collecting scheme for internet of things. IEEE Commun Mag 55(11):132–137

    Article  Google Scholar 

  18. Sethi P, Sarangi SR (2017) Internet of things: architectures, protocols, and applications. J Electrica lComput Eng 2017:1–25

    Article  Google Scholar 

  19. Shaikh FK et al (2017) Enabling technologies for Green IoT. IEEE Sens J 11(2):983–994

    MathSciNet  Google Scholar 

  20. Shen X et al Internet of things for power transmission and distribution –intelligent monitoring and full lifecycle management, 2014 China International Conference on Electricity Distribution (CICED 2014) Shenzhen, 23–26 Sep. 2014

  21. Sodhro AH, Forino G (2017) Energy management during video transmission in WBSNs. 14th IEEE International Conference on Networking, Sensing and Control (ICNSC), Calabria, Southern Italy, May 16–18, 2017

  22. Sodhro AH, Li Y (2013) Medical quality-of-service optimization in wireless telemedicine system using optimal smoothing algorithm. E-Health Telecommun Syst Netw (ETSN) J 2(1):1–8

    Article  Google Scholar 

  23. Sodhro AH, Li Y (June 2013) Novel key storage and management solution for the security of wireless sensor networks. TELKOMNIKA Indonesian J Electrir Eng 11(6):3383–3390

    Google Scholar 

  24. Sodhro AH, Li Y (2014) Battery-friednly packet transmission strategies for wireless capsule endoscopy. IFMBE Int Conf Health Inf, Int Fed Med Biol Proc 42:236–239

    Google Scholar 

  25. Sodhro AH, Li Y (2017) Green and friendly video streaming in wireless body sensor networks. J Multimed Tools Appl 76(19):20001–20025

    Article  Google Scholar 

  26. Sodhro AH, Li Y, Shah MA (Jan. 2016) Energy-efficient Adaptive transmission power control in wireless body area networks. IET Commun 10(1):81–90

    Article  Google Scholar 

  27. Sodhro AH et al (2017) Role of 5G in medical health. IEEE International Conference on Innovations in Electrical Engineering and Computational Technologies(ICIEECT), Indus University, Karachi, Pakistan, April, 2017

  28. Tao F et al (2016) IoT in product lifecycle management. J Ind Inf Integration 1(2016):26–39

    Google Scholar 

  29. Wang Y et al (2016) Potential applications of IoT-based product lifecycle energy management. IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)

  30. Wind River System (2015) Managing the IoT lifecycle design through end-of-life, White Paper, pp 1–5

  31. Wu F et al A lightweight and robust two-factor authentication scheme for personalized healthcare systems using wireless medical sensor networks. Futur Gener Comput Syst. https://doi.org/10.1016/j.future.2017.08.042,2017

  32. Yoo M-J, Leung VCM, Shu L et al (2016) Closed-loop lifecycle management of service and product in the internet of things: semantic framework for knowledge integration. Sensors 16(7):1–26

    Article  Google Scholar 

  33. Zhu C et al (2015) Green internet of things for smart world. IEEE Access 3(1):2151–2162

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Sukkur IBA University, Sukkur, Sindh, Pakistan

    Ali Hassan Sodhro

  2. DISP LAB, University Lumiere Lyon 2, Lyon, France

    Ali Hassan Sodhro, Aicha Sekhari & Yacine Ouzrout

  3. School of Computing Science and Engineering, VIT University, Vellore, Tamil Nadu, 632014, India

    Arun Kumar Sangaiah

  4. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (SIAT-CAS), Shenzhen, 518055, China

    Sandeep Pirphulal

Authors
  1. Ali Hassan Sodhro
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  2. Arun Kumar Sangaiah
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  3. Sandeep Pirphulal
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  4. Aicha Sekhari
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  5. Yacine Ouzrout
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Corresponding authors

Correspondence to Ali Hassan Sodhro or Sandeep Pirphulal.

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Sodhro, A.H., Sangaiah, A.K., Pirphulal, S. et al. Green media-aware medical IoT system. Multimed Tools Appl 78, 3045–3064 (2019). https://doi.org/10.1007/s11042-018-5634-0

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  • DOI: https://doi.org/10.1007/s11042-018-5634-0

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