Principal investigator Dr. Nizar Al Bassam and his team designed an Internet of Things (IoT) based wearable device prototype, which is capable of geographically tracking the health status of Possibly Infected Persons (PIPs) and monitor their movement during the quarantine period. The device is able to monitor the human vital signs directly related to the COVID-19 symptoms, such as skin temperature, heartbeat rate, oxygen saturation level in the blood, and even the detection of cough waves through a deep learning model and Edge Impulse platform.
According to Al Bassam, the information is used to detect and predict any infection possibility based on COVID-19 symptoms, and the device is provided with a GPS system to locate the patients and update the case managers about the geofencing status. Moreover, it is provided with the communication module which is connected to the cellular network or any data provided network. This feature ensures a direct connection to the cloud without passing through any external device such as a patient’s mobile.
All the collected sensing data is sent directly to the database in the front-end cloud-based system. The cloud web-based application is designed to display the related information, including all the patient’s vital signs, location, and even their health status with the possibility of infection based on detecting vital signs. Furthermore, it displays the total number of monitoring cases (possibly infected, not infected), confirmed cases and closed cases as this helps the authorities to have an overall view of the monitored cases and can immediately act based on the predicted cases.
Al Bassam elaborates that “this is done through PIP registration on the system as the device is connected to a mobile application, which is associated with each device capable of providing the summary of health status and providing a notification. The software is compatible with android mobile apps making it possible to alert the PIP’s friends or relatives in case abnormal physical symptoms are detected”.
In regards to the most important findings of the research, Dr. Nizar Al Bassam maintains that testing of all integrated systems shows that the wearable device can measure all human vital signs successfully. It can also able to detect the number of cough waves using the machine learning technique. He even states that the device was able to easily track the patient’s geographical information, providing a suitable alarm and indicating the quarantine’s violations. It can create an alert in case of quarantine violation of fewer than 100 meters and update the cloud databases regularly within two seconds. All information related to the patient and their health status history can be stored, managed, and monitored instantly.
Al Bassam further adds that the system was capable of generating a health record of each recorded patient as it displays the total number of monitored cases (possibly infected, not infected), confirmed cases, and closed cases. The website can smoothly and quickly monitor the cases and provide the medical authorities an overall view of the pandemic situation in a specific region, which can help them to be alert as well as monitor and control the spread of the COVID-19 virus.