Skip to main content
SpringerLink
Log in

Pillars for Big Data and Military Health Care: State of the Art

  • Conference paper
  • First Online:
Advances in Emerging Trends and Technologies (ICAETT 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1066))

  • 836 Accesses

Abstract

Big Data is a buzzword used to describe the processing of high volumes of data. Some types of health data are considered as Big Data due to the huge amount of data originated in this sector. Researchers have consolidated their efforts to present new tools and platforms for Big Data in health care, especially with the exponential growth observed on remote sensors. Although no specific studies have been presented at the military health context, the collected experience from several reviews proves the need for applying Big Data techniques to ensure efficient military operations. In this paper, we present the attained results from state of the art studies about Big Data and health case reviews published during the 2014 to 2018 timeframe. As a result, 17 relevant studies were found from several scientific digital libraries; the main proposed approaches and methodologies that are able to be included into the military health care domain were summarized into acquisition, storage, processing, management, security, and normative pillars. The results reveal the need for further studies regarding the military health care using Big Data approaches in order to improve the military life. It is important to mention that militaries are constantly exposed to health risks and this is the main reason for monitoring their health status.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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

References

  1. Waller, M.A., Fawcett, S.E.: Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. J. Bus. Logist. 34(2), 77–84 (2013)

    Article  Google Scholar 

  2. Fang, R., Pouyanfar, S., Yang, Y., Cheng, S.: Computational health informatics in the big data age a survey. ACM Comput. Surv. 49(1), 12.1–12.36 (2016)

    Article  Google Scholar 

  3. de la Torre Díez, I., Cosgaya, H.M., Garcia-Zapirain, B., López-Coronado, M.: Big data in health: a literature review from the year 2005. J. Med. Syst. 40(9), 209 (2016)

    Article  Google Scholar 

  4. Kitchenham, B.: Procedure for undertaking systematic reviews. Computer Science Department, Keele University and National ICT Australia Ltd., Australia (2004)

    Google Scholar 

  5. Islam, S.R., Kwak, D., Kabir, M.H., Hossain, M., Kwak, K.S.: The internet of things for health care: a comprehensive survey. IEEE Access 3, 678–708 (2015)

    Article  Google Scholar 

  6. Onyejekwe, E.R.: Big data in health informatics architecture. In: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 728–736 (2014)

    Google Scholar 

  7. Thara, D.K., Premasudha, B.G., Ravi, R.V., Suma, R.: Impact of big data in healthcare: a survey. In: 2nd International Conference on Contemporary Computing and Informatics, pp. 729–735 (2016)

    Google Scholar 

  8. Raghupathi, W., Raghupathi, V.: Big data analytics in healthcare: promise and potential. Health Inf. Sci. Syst. 2(1), 3 (2014)

    Article  Google Scholar 

  9. Andreu-Perez, J., Poon, C.C., Merrifield, R.D., Wong, S.T., Yang, G.Z.: Big data for health. IEEE J. Biomed. Health Inform. 19(4), 1193–1208 (2015)

    Article  Google Scholar 

  10. Wang, W., Krishnan, E.: Big data and clinicians: a review on the state of the science. JMIR Med. Inform. 2(1), 1–16 (2014)

    Article  Google Scholar 

  11. Hansen, M.M., Miron-Shatz, T., Lau, A.Y.S., Paton, C.: Big data in science and healthcare: a review of recent literature and perspectives. Yearb. Med. Inform. 9(1), 1–11 (2014)

    Google Scholar 

  12. Luo, J., Wu, M., Gopukumar, D., Zhao, Y.: Big data application in biomedical research and health care: a literature review. Biomed. Inform. Insights 8, 1–10 (2016)

    Google Scholar 

  13. Kruse, C.S., Goswamy, R., Raval, Y., Marawi, S.: Challenges and opportunities of big data in health care: a systematic review. JMIR Med. Inform. 4(4), 1–14 (2016)

    Article  Google Scholar 

  14. Mehta, N., Panditb, A.: Concurrence of big data analytics and healthcare: a systematic review. Int. J. Med. Inform. 114, 57–65 (2018)

    Article  Google Scholar 

  15. Palanisamy, V., Thirunavukarasu, R.: Implications of big data analytics in developing healthcare frameworks – a review. J. King Saud Univ.-Comput. Inf. Sci., 1–11 (2017)

    Google Scholar 

  16. Hamrioui, S., de la Torre Díez, I., Garcia-Zapirain, B., Saleem, K., Rodrigues, J.J.: A systematic review of security mechanisms for big data in health and new alternatives for hospitals. Wirel. Commun. Mob. Comput. 2017, 1–7 (2017)

    Article  Google Scholar 

  17. Alonso, S.G., de la Torre Díez, I., Rodrigues, J.J., Hamrioui, S., López-Coronado, M.: A systematic review of techniques and sources of big data in the healthcare sector. J. Med. Syst. 41(11), 183 (2017)

    Article  Google Scholar 

  18. Stylianou, A., Talias, M.A.: Big data in healthcare: a discussion on the big challenges. Health Technol. 7(1), 97–107 (2017)

    Article  Google Scholar 

  19. Cedillo, P., Sanchez, C., Campos, K., Bermeo, A.: A systematic literature review on devices and systems for ambient assisted living: solutions and trends from different user perspectives. In: International Conference on eDemocracy & eGovernment (2018)

    Google Scholar 

  20. Bird, S., Klein, E., Loper, E.: Natural Language Processing with Python. O’Reilly Media Inc, Sebastopol (2009)

    MATH  Google Scholar 

  21. Sarnovsky, M., Butka, P., Paulina, J.: Social-media data analysis using tessera framework in the hadoop cluster environment. In: 37th International Conference on Information Systems Architecture and Technology, vol. 2, pp. 239–251 (2017)

    Google Scholar 

  22. Iqbal, M.H., Soomro, T.R.: Big data analysis: apache storm perspective. Int. J. Comput. Trends Technol. 19, 9–14 (2015)

    Article  Google Scholar 

  23. Garg, N.: Apache Kafka. Packt Publishing Ltd., Birmingham (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, Alicante, Spain

    Diana Martinez-Mosquera & Sergio Luján-Mora

  2. Departamento de Ciencias de la Ingeniería, Universidad Israel, Quito, Ecuador

    Luis H. Montoya L.

  3. Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Rolando P. Reyes Ch. & Manolo Paredes Calderón

Authors
  1. Diana Martinez-Mosquera
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sergio Luján-Mora
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luis H. Montoya L.
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rolando P. Reyes Ch.
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Manolo Paredes Calderón
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Diana Martinez-Mosquera .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, Noord-Brabant, The Netherlands

    Miguel Botto-Tobar

  2. Universidad Técnica de Babahoyo, Babahoyo, Ecuador

    Joffre León-Acurio

  3. Universitat de Valencia, Valencia, Valencia, Spain

    Angela Díaz Cadena

  4. Centro de Investigación y Desarrollo Profesional, Babahoyo, Los Rios Province, Ecuador

    Práxedes Montiel Díaz

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Martinez-Mosquera, D., Luján-Mora, S., Montoya L., L.H., Reyes Ch., R.P., Paredes Calderón, M. (2020). Pillars for Big Data and Military Health Care: State of the Art. In: Botto-Tobar, M., León-Acurio, J., Díaz Cadena, A., Montiel Díaz, P. (eds) Advances in Emerging Trends and Technologies. ICAETT 2019. Advances in Intelligent Systems and Computing, vol 1066. Springer, Cham. https://doi.org/10.1007/978-3-030-32022-5_12

Download citation

Publish with us

Policies and ethics

Search

Navigation