Skip to main content

Indoor Positioning System Assisted Big Data Analytics in Smart Healthcare

  • Chapter
  • First Online:
Connected e-Health

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1021))

Abstract

Thousands of gigabytes of data mostly are now available on the internet, for all intents and purposes gathered from a variety of sources, deliberately or inadvertently. The science of converting all of this data into knowledge that can specifically improve everyone’s life pretty much simpler definitely is known as Big Data. Today, healthcare literally is one of the most important sectors. Our country’s healthcare resources basically are minimal, which particularly is fairly significant. As a result, making resources available to everyone in need becomes extremely difficult in a generally major way. Big Data Analytics can assist us in optimising the usage of these resources so that they particularly are available to anybody who requires them, which basically is quite significant. Keeping track of the resources that kind of are currently in use, those that literally are available, and those that may for all intents and purposes be reassigned is one strategy to optimise the available resources in a subtle way. These systems help us in determining the actually exact location of all resources definitely such that the ones nearest to the patient basically are allocated to him, making the treatment process faster. Indoor positioning systems definitely are like GPS systems but that work inside a building, in this case, hospital, which is fairly significant. This chapter discusses further about the contribution of big data analytics and indoor positioning systems in the evolution of smart healthcare.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover 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. Nambiar AR, Reddy N, Dutta D (2017) Connected health: opportunities and challenges. In: IEEE international conference on big data, IEEE, Boston, MA, pp 1658–1662

    Google Scholar 

  2. Mishra S, Mahanty C, Dash S, Mishra BK (2019) Implementation of BFS-NB hybrid model in intrusion detection system. In: Recent developments in machine learning and data analytics, Springer, Singapore, pp 167–175

    Google Scholar 

  3. Dwivedi S, Kasliwal P Soni S (2016) Comprehensive study of data analytics tools (RapidMiner, Weka, R tool, Knime). IEEE symposium on Colossal Data Analysis and Networking (CDAN), Indore

    Google Scholar 

  4. Zhuhadar LP, Thrasher E (2019) Data analytics and its advantages for addressing the complexity of healthcare: a simulated zika case study example. Appl Sci 9:2208

    Article  Google Scholar 

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

    Article  Google Scholar 

  6. Johri P, Singh T, Das S, Anand S (2017) Vitality of big data analytics in healthcare department. In: IEEE international conference on infocom technologies and unmanned systems (trends and future directions), Dubai

    Google Scholar 

  7. Wang H, Zhang Q, Ip M, Lau JTF (2018) Social media–based conversational agents for health management and interventions. Comput 51:26–33

    Article  Google Scholar 

  8. Agha L (2015) The effects of health information technology on the costs and quality of medical care. J Health Econ 34:19–30

    Article  Google Scholar 

  9. Burke J (2015) Is that data valid? Getting accurate financial data in healthcare. Health Catalyst

    Google Scholar 

  10. Diao J, Kohane IS, Manrai AK (2018) Biomedical informatics and machine learning for clinical genomics. Hum Mol Genet 27:R29–R34

    Article  Google Scholar 

  11. Uddin MS, Alam JB, Banu S (2017) Real time patient monitoring system based on internet of things. In: 4th IEEE international conference on advances in electrical engineering, Dhaka

    Google Scholar 

  12. Olaronke I, Oluwaseun O (2016) Big data in healthcare: prospects, challenges and resolutions. In: Future technologies conference, IEEE, San Francisco, CA, pp 1152–1157

    Google Scholar 

  13. Gawanmeh A (2016) Open issues in reliability, safety, and efficiency of connected health. In: First IEEE conference on connected health: applications, systems and engineering technologies, Washington, DC

    Google Scholar 

  14. Sonune S, Kalbande D, Yeole A, Oak S (2017) Issues in IoT healthcare platforms: a critical study and review. In: IEEE international conference on intelligent computing and control (I2C2), Coimbatore

    Google Scholar 

  15. Williams C, Mostashari F, Mertz K, Hogin E, Atwal P (2012) From the office of the national coordinator: the strategy for advancing the exchange of health information. Health Aff 31(3):527–536

    Article  Google Scholar 

  16. Mishra S, Sahoo S, Mishra BK (2019) Addressing security issues and standards in Internet of things. In: Emerging trends and applications in cognitive computing, IGI Global, pp 224–257

    Google Scholar 

  17. Thakkar H, Mishra S, Chakrabarty A (2012) A power efficient cluster-based data aggregation protocol for WSN (MHML). Int J Eng Innov Technol (IJEIT) 1(4):241–246

    Google Scholar 

  18. Rath M, Mishra S (2020) Security approaches in machine learning for satellite communication. In: Machine learning and data mining in aerospace technology, Springer, Cham, pp 189–204

    Google Scholar 

  19. Mishra S, Tripathy HK, Panda AR (2018) An improved and adaptive attribute selection technique to optimize dengue fever prediction. Int J Eng Technol 7:480–486

    Article  Google Scholar 

  20. Mishra S, Tadesse Y, Dash A, Jena L, Ranjan P (2021) Thyroid disorder analysis using random forest classifier. In: Intelligent and cloud computing, Springer, Singapore, pp 385–390

    Google Scholar 

  21. Rath M, Mishra S (2019) Advanced-level security in network and real-time applications using machine learning approaches. In: Machine learning and cognitive science applications in cyber security, IGI Global, pp 84–104

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sushruta Mishra .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Patnaik, M., Mishra, S. (2022). Indoor Positioning System Assisted Big Data Analytics in Smart Healthcare. In: Mishra, S., González-Briones, A., Bhoi, A.K., Mallick, P.K., Corchado, J.M. (eds) Connected e-Health. Studies in Computational Intelligence, vol 1021. Springer, Cham. https://doi.org/10.1007/978-3-030-97929-4_18

Download citation

Publish with us

Policies and ethics