Application of IoT in Predictive Health Analysis– A Review of Literature

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Geetha Poornima K
Krishna Prasad K

Abstract

Internet of Thing (IoT) has influenced several fields these days. Healthcare is one among them.
The field of health care has been changed forever with the help of smart devices, wearable along
with the overall level of inventions and connectivity in terms of the modern medical equipment.
IoT, Cloud computing and other emerging technologies use data from different devices distributed
across the network. Among those applications that are facilitated by the IoT, applications related
to health care are most significant ones. Predictive analysis is carried out on the real-time data of
patients to analyze their current situation for the purpose of effective and accurate clinical-decision
making. Generally, internet of thing has been extensively utilized for interconnecting the
advanced medical resource as well as for providing effective and smart health care services to the
people. In order to monitor the condition of the patient, advanced sensors can be embedded or
worn within the patient’s body. The data accumulated to such an extent that those data can beexamined, aggregated as well as mined to do the initial predictions of diseases. Moreover,physicians are assisted by the processing algorithm for the personalization of treatment and at the same time thereby making the field of heath care more economical. This literature review is carried out by using the secondary data obtained from peer-reviewed journals and other sources on the web. This review aims to explain the use of IoT for providing smart healthcare solutions. The limitation of this study is that the major focus is on application side there by excluding the hardware and theoretical aspects related to the subject

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How to Cite
Geetha Poornima K, & Krishna Prasad K. (2020). Application of IoT in Predictive Health Analysis– A Review of Literature. International Journal of Management, Technology and Social Sciences (IJMTS), 5(1), 185–214. https://doi.org/10.47992/IJMTS.2581.6012.0089
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