Detecting SARs-COV'19 at early stages is essential for both providing suitable medical facility to the patients and also to safeguard the unaffected people. The dangerous part of COVID-19 infection occurs in patients with lower levels of immunity, say older people, patients with cardiovascular diseases, diabetes, chronic respiratory diseases, or cancer, in which case a serious illness develops and at last leads to the death of the patient. The chatper aims at monitoring the SpO2, heartbeat, and temperature of the COVID-19-infected patients in critical care units and takes immediate action by supplying oxygen or medicated aerosol to the needy patients. A supervised machine learning technique is used for effective prediction of the patient's condition based on the monitored parameters. Experimental results show that this model can predict the abnormal condition of the patient with an efficiency of 94% and revert back to normal conditions with an efficiency of 95%.
Top1. Introduction
The SARs-CoV-2 a new strain of corona virus that shook the world belongs to the group of viruses that are responsible for mild to serious respiratory illness in human. This SARs-CoV-2 virus was first identified in China’s Wuhan city in the middle of December 2019. Since then, every country in the world reported positive COVID cases. Globally, as of June 2022, there are around 532,887,351 confirmed cases of COVID-19, which includes 6,307,021 deaths, reported to WHO. As of now, a total of 11,854,673,610 vaccines have already been administered. Though the fatality rate is very low compared to the Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), COVID-19 is very contagious and has spread to every part of the globe. The first weapon taken by the world to take hold of the situation is early detection of the infection and isolating the infected to nullify further spread. Considering the pandemic of COVID-19, it is important to detect COVID-19 early, which could facilitate the slowdown of viral transmission and thus disease containment. With COVID-19 the common symptoms include fever, dry cough, and tiredness accompanied by loss of taste or smell, sore throat, heart disease and respiratory problems. In spite of all the medical advancements in the twentieth century, COVID’19 has traumatized the whole world like never before so that it can be called a disaster. The debate is still on as to how to name this pandemic and some common descriptions include “Sanitary Crisis”, “Health Emergency”, “Natural Disaster”, etc.
On the other hand, Science and Technological development leading the path towards Artificial Intelligence obviously playing a major role in every field in this 21st century. Though there are so many critics that it increases un-employment, when seen on the positive side, AI can be used effectively in scenarios that are harmful and dangerous for human interventions. A scenario aiding this argument is the COVID pandemic in which case complete isolation of the infected individual is highly recommended to avoid transmission of the virus. In such case where an individual is isolated, it is his right to get all medical aid for his well-being and that no one can stop. In spite of that, medical practitioners are highly vulnerable to the disease as they are always attending infected people. There are situations that we heard in televisions that Physicians attending COVID isolation ward are also quarantined to aid in containment of the disease. So, when it comes to a highly contagious disease like SARs-COV-19, there are two areas to be concentrated on, to handle the situation. They are i) Predicting the disease spread and contact tracing and ii) Effective healthcare monitoring and mitigation. Artificial Intelligence can be used for both the cases effectively and thus AI played a key role in handling the pandemic. This paper, proposes the most economical AI based patient monitoring system which can effectively monitor and mitigate the emergencies that arise with a COVID patient. With this small introduction let us have a look at the organization of the paper,
Section 1 is an Introduction to the current COVID scenario and the technologies that aid us in effective handling of the same. Section 2 briefs the different application of Artificial Intelligence in handling the COVID pandemic with limelight on i) Predicting, ii) Surveillance and iii) Minimizing human interventions to safeguard healthcare providers. It also elaborates the existing patient monitoring systems available for domestic personal care as well as a smart healthcare in a hospital setup throwing light on Internet of things and machine learning.
Section 3 explains the different blocks in the proposed system hardware along with their working.
Section 4 introduces the types of Machine Learning algorithms and their significances and depicts the ML algorithms used for the training and inference of a patient condition based on supervised learning algorithm whereas Section 5 discusses the effectiveness of the AI system in mitigating the risks based on the results obtained. The conclusion and future expansion of the work is discussed in Section 6 with the References cites being listed at the end.