Real-time artificial intelligence based health monitoring, diagnosing and environmental control system for COVID-19 patients

Math Biosci Eng. 2022 May 23;19(8):7586-7605. doi: 10.3934/mbe.2022357.

Abstract

By upgrading medical facilities with internet of things (IoT), early researchers have produced positive results. Isolated COVID-19 patients in remote areas, where patients are not able to approach a doctor for the detection of routine parameters, are now getting feasible. The doctors and families will be able to track the patient's health outside of the hospital utilizing sensors, cloud storage, data transmission, and IoT mobile applications. The main purpose of the proposed research-based project is to develop a remote health surveillance system utilizing local sensors. The proposed system also provides GSM messages, live location, and send email to the doctor during emergency conditions. Based on artificial intelligence (AI), a feedback action is taken in case of the absence of a doctor, where an automatic injection system injects the dose into the patient's body during an emergency. The significant parameters catering to our project are limited to ECG monitoring, SpO2 level detection, body temperature, and pulse rate measurement. Some parameters will be remotely shown to the doctor via the Blynk application in case of any abrupt change in the parameters. If the doctor is not available, the IoT system will send the location to the emergency team and relatives. In severe conditions, an AI-based system will analyze the parameters and injects the dose.

Keywords: Blynk IoT platform; SpO2; artificial intelligence; electrocardiogram (ECG); emergency condition; internet of things (IoT).

MeSH terms

  • Artificial Intelligence
  • COVID-19* / diagnosis
  • COVID-19* / epidemiology
  • Cloud Computing
  • Electrocardiography
  • Humans
  • Mobile Applications*