Classification of Thorax X-ray Results on Corona Virus Infection Based on Internet of Things (IoT)

Abstract

The spread of the corona virus in Indonesia is still growing until now. One important thing to note is about the handling of patients exposed to the coronavirus. This study aims to be able to classify thorax x-ray images against corona virus infection based on the Internet of Things (IoT). IoT is a concept of internet connectivity that is connected continuously between remote devices. This study uses a supervised learning method, namely directed learning in which the expected results of the user have been trained in advance and the information is stored in the system (database). The training data used is a Thorax x-ray image that is processed based on image processing with segmentation and edge detection based on the Sobel operator with real time connected to the internet. The results showed that the 100 times experiment obtained the accuracy value of the normal Thorax X-ray image of 94% and the Thorax covid-19 X-ray image of 96%. Overall system test showed 95% on target and 5% error.