Introduction: The coronavirus disease 2019 (COVID-19) pandemic affects every part of our lives. Delays in COVID-19 identification, diagnosis, and treatment will result in higher morbidity and mortality rates due to the recent lack of public knowledge. An integrated system of health services like telemedicine can be a tactical way to enhance COVID-19 results, diagnosis, and medication.
Method: G-COV is a tool to assess the severity of COVID-19 based on 800 chest X-rays from Dr. Zainoel Abidin General Hospital in Banda Aceh that had previously undergone the Visual Geometry G (VGG16) with CNN algorithm. Three sensors will be implanted on the patient to monitor vital signs and connect to the ESP 8266 to display sensor data in real-time. The ESP platform and Visual Studio Code are used to create the program system. An app called G-COV is integrated with other apps on mobile devices. Additionally, the application will show the COVID-19 diagnostic and therapy guide in real-time on Firebase. The prototype calibration was carried out on 20 COVID-19 patients.
Result: According to the experimental findings, the device has a 92.45% accuracy rate when measuring temperature, pulse, and oxygen saturation—the benchmarks for determining the severity of COVID-19. With 95% accurate diagnosis and severity of COVID-19 detection results, the calibration data demonstrate good tool performance.
Conclusion: Every Individual can use G COV to easily acquire treatment recommendations by detecting COVID-19. Before G COV is made available to the public, we will assess its usability during development.