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Industry 4.0 Challenges in e-Healthcare Applications and Emerging Technologies

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Intelligent Interactive Multimedia Systems for e-Healthcare Applications

Abstract

Industry 4.0 becomes an essential part of tomorrow’s smart factories and smart hospitals, where software, technologies, and processes provide efficient and world class results with lesser time and cost. Healthcare modernization is being driven by various patterns including rising healthcare costs, a maturing populace, and the developing occurrence of ongoing conditions that will require long-haul care. In addition to the IoT, the application of predictive algorithms and artificial intelligence, capable of processing large amounts of data, plays a fundamental role in this context. This paper means to give a diagram of the cutting edge of late industry 4.0 applications in the field of medical services and to assess the function of empowering advances in the groundbreaking cycle of the present Emergency clinic 4.0. The implementation of I4.0 will certainly be a transitional process for the medical device industry because of the importance of retaining compliance and the need to prove quality systems. The aim of this paper is to highlight, for each application area of industry 4.0 technologies, the status of the research and future possible developments.

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References

  1. Oztemel, E., & Gursev, S., (2020, January). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(4). https://doi.org/10.1007/s10845-018-1433-8

  2. Kang, et al. (2020). Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 28, 17. https://doi.org/10.1186/s13049-020-0713-4

    Article  Google Scholar 

  3. Bendato, et al. (2015). New markets forecast and dynamic production redesign through stochastic simulation. International Journal of Simulation Modelling, 14(3), 485–498. https://doi.org/10.2507/ijsimm14(3)10.307

    Article  Google Scholar 

  4. Patrone, et al. (2017, March). Optimization of lean surgical route through POCT acquisition. International MultiConference of Engineers and Computer Scientists (Vol II). IMECS.

    Google Scholar 

  5. Cassettari, et al. (2013). A system dynamics study of an emergency department impact on the management of hospital’s surgery activities.https://doi.org/10.5220/0004617205970604

  6. Rajesh, E., et al. (2020). Different dimensions on healthcare using internet of things (IoT): Health monitoring. Journal of Critical Reviews, 7(9), 638–641. https://doi.org/10.31838/jcr.07.09.125

  7. Knowles, E., et al. (2018). Exploring variation in how ambulance services address non-conveyance: a qualitative interview study. BMJ Open, 8(11). https://doi.org/10.1136/bmjopen-2018-024228

  8. Aceto, G., Persico, V., & Pescapè, A. (2018, February 15). The role of information and communication technologies in healthcare: Taxonomies, perspectives, and challenges. Journal of Network and Computer Applications. https://doi.org/10.1016/j.jnca.2018.02.008

  9. Dash, S., et al. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6, Article number: 54.

    Google Scholar 

  10. Rejikumar, G., et al. (2019, July). Industry 4.0: key findings and analysis from the literature arena. Benchmarking an International Journal. https://doi.org/10.1108/BIJ-09-2018-0281

  11. Ashwin, M., et al. (2018, April). Heart life: A heart beat monitoring system using IoT. International Research Journal of Engineering and Technology (IRJET), 05(04), ISSN: 2395–0056.

    Google Scholar 

  12. Ocen, G. G., et al. (2020). Exponential disruptive technologies and the required skills of industry 4.0. Journal of Engineering, 2020, ID 4280156. https://doi.org/10.1155/2020/428015

  13. Lee Ventola, C. (2014, May). Mobile devices and apps for health care professionals: Uses and benefits. P & T: A Peer-reviewed Journal for Formulary Management, 39(5), 356–364.

    Google Scholar 

  14. Enrique, A., et al. (2010, October). Biometrics for Electronic Health Records. Journal of Medical Systems, 34(5):975–83.https://doi.org/10.1007/s10916-009-9313-6

  15. Jayabalan, M., & O’Daniel, T. (2019). A study on authentication factors in electronic health records. Journal of Applied Technology and Innovation (e-ISSN: 2600–7304), 3(1).

    Google Scholar 

  16. Nagy, J., et al. (2018). The role and impact of industry 4.0 and the internet of things on the business strategy of the value chain—The case of Hungary. Sustainability, 10, 3491. https://doi.org/10.3390/su10103491

  17. Sima, V., et al. (2020). Influences of the industry 4.0 revolution on the human capital development and consumer behavior: A systematic review. Sustainability, 12, 4035. https://doi.org/10.3390/su12104035

  18. https://towardsdatascience.com/the-power-of-artificial-intelligence-ai-virtual-and-augmented-reality-vr-and-ar-on-medical-4949c7a6fd72

  19. Li, J. -P. O., et al. Digital technology, tele-medicine and artificial artificial intelligence in ophthalmology: A global perspective. Elsevier Public Health Emergency Collection. https://doi.org/10.1016/j.preteyeres.2020.100900

  20. Nass, S. (2015, September). Improving diagnosis in health care. National Academies Press, ISBN: 978-0-309-37769-0. https://doi.org/10.17226/21794

  21. Hossain, M., et al. (2018, May). An internet of things-based health prescription assistant and its security system design. Future Generation Computer Systems, 82. https://doi.org/10.1016/j.future.2017.11.020

  22. Blowers, M., et al. (2016, October). The future internet of things and security of its control systems. https://www.researchgate.net/publication/308915644_The_Future_Internet_of_Things_and_Security_of_its_Control_Systems

  23. Ramya, G., Sai Lohitha, N. (2019, December). The role and advancements of IOT technology in smart farming for agribusiness. Journal of the Gujarat Research Society, 21(16), ISSN: 0374–8588.

    Google Scholar 

  24. Banerjee, S., & Badr, Y. (2018, January). Evaluating decision analytics from mobile big data using rough set based Ant Colony. https://doi.org/10.1007/978-3-319-67925-9_9

  25. Vaishnnave, M. P., Suganya Devi, K., & Srinivasan, P (2019). A survey on cloud computing and hybrid cloud. International Journal of Applied Engineering Research, 14(2), 429–434, ISSN 0973–4562.

    Google Scholar 

  26. Behmann, F., & Wu, K. Collaborative internet of things (C-IOT): For future smart connected life and business. Wiley Online Library. ISBN: 9781118913741. https://doi.org/10.1002/9781118913734

  27. Bruen, D., et al. (2017, August 12) Glucose sensing for diabetes monitoring: recent developments. Sensors (Basel).https://doi.org/10.3390/s17081866

  28. Thuemmler, C., & Bai, C. Health 4.0: How virtualization and big data are revolutionizing healthcare. https://link.springer.com/book/10.1007%2F978-3-319-47617-9

  29. Kashyap, R. (2019, January). Machine learning for internet of things. Next-generation wireless networks meet advanced machine learning applications (pp. 57–83). https://doi.org/10.4018/978-1-5225-7458-3.ch003

  30. Ginsburg, G. S., & Phillips, K. A. (2018, May). Precision medicine: From science to value. 37(5), 694–701. https://doi.org/10.1377/hlthaff.2017.1624

  31. Mizanoor Rahman, S. M. (2018). Cyber-physical-social system between a humanoid robot and a virtual human through a shared platform for adaptive agent ecology. IEEE/CAA Journal of Automatica Sinica, 5(1), 190–203.

    Google Scholar 

  32. Tyagi, A. K. (2016, March). Cyber physical systems (CPSs)—Opportunities and challenges for improving cyber security. International Journal of Computer Applications, 137(14):19–27, Published by Foundation of Computer Science (FCS), NY, USA.

    Google Scholar 

  33. Robidoux, R., et al. (2019). An analysis of pay-for-performance schemes and their potential impacts on health systems and outcomes for patients. 2019, Article ID 8943972. https://doi.org/10.1155/2019/8943972

  34. Tyagi, A. K., Nair, M. M., Niladhuri, S., & Abraham, A. (2020). Security, privacy research issues in various computing platforms: A survey and the road ahead. Journal of Information Assurance & Security, 15(1), p1–16, 16p.

    Google Scholar 

  35. Tyagi, A. K., & Goyal, D. (2020). A survey of privacy leakage and security vulnerabilities in the internet of things. 2020 5th International conference on communication and electronics systems (ICCES) (pp. 386–394), Coimbatore, India. https://doi.org/10.1109/ICCES48766.2020.9137886

  36. Shamila, M., Vinuthna, K., & Tyagi, A. (2019). A review on several critical issues and challenges in IoT based e-Healthcare system. 1036–1043. https://doi.org/10.1109/ICCS45141.2019.9065831.

  37. Pramod, A., Naicker, H. S., & Tyagi, A. K. (2020). Machine learning and deep learning: Open issues and future research directions for next Ten Years. In Computational analysis and understanding of deep learning for medical care: Principles, methods, and applications. Wiley Scrivener.

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, Tamilnadu, 600127, India

    Shruti Suhas Kute & Amit Kumar Tyagi

  2. Centre for Advanced Data Science, Vellore Institute of Technology, Chennai, Tamilnadu, 600127, India

    Amit Kumar Tyagi

  3. Department of Computer Science and Engineering, Jyothi Engineering College, Thrissur, Kerala, India

    S. U. Aswathy

Authors
  1. Shruti Suhas Kute
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  3. S. U. Aswathy
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Editor information

Editors and Affiliations

  1. Vellore Institute of Technology, Chennai, Tamil Nadu, India

    Amit Kumar Tyagi

  2. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  3. Department of Civil Engineering, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

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Kute, S.S., Tyagi, A.K., Aswathy, S.U. (2022). Industry 4.0 Challenges in e-Healthcare Applications and Emerging Technologies. In: Tyagi, A.K., Abraham, A., Kaklauskas, A. (eds) Intelligent Interactive Multimedia Systems for e-Healthcare Applications. Springer, Singapore. https://doi.org/10.1007/978-981-16-6542-4_14

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