Data Analysis and Interpretation in IoT-Based Systems for Critical Medical Services and Healthcare Applications

Abstract

The use of Internet of things in health care is a major breakthrough as it can help us save a lot of lives that can be prevented because of prolonged commute distance to the hospital. We have improvised on pre-existing models to create this model. We were successfully able to achieve results on a small scale by transmitting relays of data over a Wi-Fi network. Our model will help reduce the travel time, as well as send data to prior to the hospitals so they can take necessary precautions to attend to the patient. We have come up with a two-step process to achieve. (1) Create a green corridor for an ambulance. (2) Send the patient details (blood group, the reason for emergency, pulse rate, etc.) to the respective hospital.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

References

  1. 1.

    Wang, L., Yang, G.-Z., Huang, J., Zhang, J., Yu, L., Nie, Z., et al. (2010). A wireless biomedical signal interface system-on-chip for body sensor networks. IEEE Transactions on Biomedical Circuits and Systems, 4(2), 112–117.

    Article  Google Scholar 

  2. 2.

    Istepanaian, R. S. H., & Zhang, Y.-T. (2012). Guest editorial introduction to the special section: 4 G health—The long-term evolution of m-health. IEEE Transactions on Information Technology in Biomedicine, 16(1), 1–5.

    Article  Google Scholar 

  3. 3.

    Valls, M. G., & Val, P. B. (2013). Usage of DDS data-centric middleware for remote monitoring and control laboratories. IEEE Transactions on Industrial Informatics, 9(1), 567–574.

    Article  Google Scholar 

  4. 4.

    Shi, S., Xu, L., & Liu, B. (1999). Improving the accuracy of nonlinear combined forecasting using neural networks. Expert Systems with Applications, 16(1), 49–54.

    Article  Google Scholar 

  5. 5.

    Xu, L., He, W., & Li, S. (2014). Internet of Things in industries: A survey. IEEE Transactions on Industrial Informatics, 10, 2233–2243. https://doi.org/10.1109/tii.2014.2300753.

    Article  Google Scholar 

  6. 6.

    He, C., Fan, X., & Li, Y. (2013). Toward ubiquitous healthcare services with a novel efficient cloud platform. IEEE Transactions on Biomedical Engineering, 60(1), 230–234.

    Article  Google Scholar 

  7. 7.

    Wu, F., Wu, T., & Yuce, M. R. (2019). Design and implementation of a wearable sensor network system for IoT-connected safety and health applications. In 2019 IEEE 5th world forum on internet of things (WF-IoT). IEEE.

  8. 8.

    Pardeshi, V., et al. (2017). Health monitoring systems using IoT and Raspberry Pi—a review. In 2017 International conference on innovative mechanisms for industry applications (ICIMIA). IEEE.

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to S. Ananda Kumar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rustagi, A., Shukla, M., Samuel, F. et al. Data Analysis and Interpretation in IoT-Based Systems for Critical Medical Services and Healthcare Applications. Wireless Pers Commun (2021). https://doi.org/10.1007/s11277-020-08052-0

Download citation

Keywords

  • Healthcare
  • Ubiquitous data
  • Green-corridor
  • m-healthcare