COVID-19 is a communicable disease caused by a new virus called “severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)”. The spread of the stated virus is a critical problem. Conducting tests is one of the World Health Organization (WHO)’s approaches to reduce its spread. Currently, the active COVID-19 infections are being identified using Polymerase Chain Reaction (PCR) test or Rapid test. These testing methods are costly, tedious, require professional expertise, and are not easily accessible in some countries. As the majority of infections become visible next to the symptom beginning, it is improbable to recognize the symptom’s transporter. This is a challenge for the nations engaged in combat to reduce the COVID- 19 spread across the world as an infected person can spread the virus during the testing process.

The current study aims at designing an IoT-based smart wearable device for early warning about COVID-19 cases. The smart wearable device can sense an individual’s body temperature, heart rate, oxygen saturation, cough rate and then monitor the user’s location with the help of DS18B20, Max30100, sound sensor, and NEO-6M-GPS sensors. The Arduino Nano based on ATmega328 was used as a processing unit. It is a high-performance and low power consumption microcontroller board. ESP8266 Wi-Fi Module is used to send sensed data to the ThingSpeak. This is an IoT platform that helps to store, visualize and analyze data from field sensors (things). A Wi-Fi Router is used as a gateway to help users interact with the system.

The system used decision tree rules namely R1 and R2 to analyze data then warn the guessed COVID-19 cases. When R1 is met, the system returns “Warning! Stay at home, Follow regulations, and Call a Doctor” otherwise it returns “You are Healthy” on the LCD of the smart wearable device. With the help of the Jupyter Notebook App, the decision tree model has been created, trained, and validated to help the concerned people such as medical staff to predict individuals with normal or abnormal status on the pandemic and view the correlation between the model inputs.

Keywords:Smart wearable device, real-time data monitoring, detection of COVID-19 cases, IoT data analysis, cloud platform.