ICU Health Monitoring System in IoT with Machine Learning
DOI:
https://doi.org/10.37591/rrjoesa.v9i1.797Keywords:
Internet of Things, ICU, Wi-Fi connection, Patient Health Monitoring System, DC power. Supply.Abstract
The Internet of Things (IoT) allows humans to push to a higher level of automation by developing systems using various sensors, interconnected smart devices, and the Internet. In ICU, patient checking is basic and most vital activity as little deferral in choice related to patients’ treatment may cause lasting permanent disability or maybe death. Most ICU devices are equipped with various sensors to live health parameters but to watch it all the time remains a challenging job. We are proposing an IoT-based system which may help in fast communication and identify emergencies and initiate communication with healthcare staff and also helps to initiate proactive and quick treatment. This healthcare system reduces the possibility of human errors, delays in communication, and helps doctors to spare longer in decisions with accurate observations.Healthy people are important for any nation’s development.The use of the web in IoT-based BANs (body area networks) is increasing for continuous medical healthcare and monitoring so as to perform actions in real-time just in case of emergencies. However, within the case of monitoring the health of all citizens or people in a country, the many sensors attached to human bodies generate massive volumes of heterogeneous data, called Big Data. Processing Big Data and performing actions in real-time in situations that can be critical is a challenging task. Therefore, so as to deal with such issues, we propose a Real-time Medical Emergency Response System that involves IoT-based medical sensors deployed on the physical body.
Downloads
Published
Issue
Section
License
Declaration and Copyright Transfer Form
(to be completed by authors)
I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.
- I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
- I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
- I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
- I/We also agree to the authorship of the article in the following order:
Author’s name
1. ________________
2. ________________
3. ________________
4. ________________
| We Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal. |