AI-based System for the Detection and Prevention of COVID-19

Abstract

The COVID-19 pandemic has had catastrophic consequences all over the world since the detection of the first case in December 2019. Currently, exponential growth is expected. In order to stop the spread of this pandemic, it is necessary to respect sanitary protocols such as the mandatory wearing of masks. In this research paper, we present an affordable artificial intelligence-based solution to increase the protection against COVID-19, covering several relevant aspects to facilitate the detection and prevention of this pandemic: noncontact temperature measurement, mask detection, automatic gel-dispensing, and automatic sterilization. Our main contribution is to provide high-quality, real-time learning and analysis. To achieve this goal, we used a deep convolutional neural network (CNN) based on MobileNetV2 architecture as the learning algorithm and Advanced Encryption Standard (AES) as an encryption protocol for sending secure data to notify hospital staff. The experimental results show the effectiveness of our model by providing 99.7% accuracy in detecting masks with a runtime of 1.54 s.

COVID-19 Detection on X-Ray Images using a Combining Mechanism of Pre-trained CNNs

“…In reality, the two subsets of AI are employed to health data analysis: the first subset is Machine Learning (ML) and the second is Deep Learning (DL) approaches, including radiography images or computed tomography scans, have been shown to be useful on detection of illness and monitoring [12]- [14], [15]- [17]. As a result, various types of human maladies, like as Parkinson's disease [18]- [21], brain tumor segmentation [22], [23], breast cancer [24], diabetes [25], medical image segmentation [26], and heart disease prediction [27]- [30], atherosclerosis diseases [31], could be identified using such techniques.…”