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Data management for resource optimization in medical IoT

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Abstract

Purpose

Medical IoT plays a substantial role in improving healthcare and patient monitoring. Enhancing the quality of healthcare system is a vibrant goal of society. IoT has been playing an important role in improving the quality of healthcare system. IoT technologies have been used over many years for observing patient’s health using different medical IoT devices in different scenarios and medical conditions like post COVID scenario. Medical IoT has wide range of applications in post COVID era like remote patient monitoring. Therefore, the role of IoT devices in different rising sectors is evident. These devices continuously generate huge amount of data counted among big data category. The data generation is so huge that special management is required to be analyzed and efficiently handle the patient care in real time environment taking into consideration the resource constrained nature of medical IoT devices. There are various challenges put forth by researchers in handling and managing medical IoT data due to resource constrained nature of IoT devices. This paper presents a survey of resource optimization in medical IoT. The main aim of this paper is to introduce novelty in medical IoT resource optimization through data management approach.

Methods

This study was performed by searching the related papers from 2014-2022 using different online databases like IEEE Xplore, Web of Science, Google Scholar and PubMed to examine relevant work on resource optimization in medical IoT.

Results

This paper presents a use case of Remote Patient Monitoring and proposes a model for optimizing medical IoT resources in medical IoT devices and the network through data management algorithms and protocols which are suited and specially designed for the purpose. This paper also presents a fair algorithm to pave a way for resource optimization.

Conclusion

In existing literature major work has been done on optimizing medical IoT resources via resource management approaches like task scheduling, resource allocation, virtualization etc., with a little focus on data. As data is central to all medical IoT applications, so proper data management can lead to better resource optimization in medical IoT. In this paper, the parameters and resource identification using mathematical formulation has been done to augment proposed model of resource optimization.

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  1. Department of Information Technology, NIT, Hazratbal, Srinagar, 190006, Jammu and Kashmir, India

    Iqra Jan & Shabir Sofi

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  1. Iqra Jan
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Jan, I., Sofi, S. Data management for resource optimization in medical IoT. Health Technol. 14, 51–68 (2024). https://doi.org/10.1007/s12553-023-00796-6

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