How Artificial Intelligence Helped the Humanity During the COVID-19 Pandemic: A Review

The unprecedented circumstances encountered during the COVID-19 pandemic in a variety of life aspects such as health, economy, and environment have urged the humanity to devise new solutions to control and mitigate the impact of the pandemic. Motivated by the high-accuracy decision-making capabilities of artificial intelligence, this article aims to highlight the effectiveness of artificial intelligence applications in the areas of virus detection, health monitoring, face mask detection, crowd sensing, and satellite-based environment monitoring. One of the most promising deep learning techniques presented in the literature is the convolutional neural network (CNN) that has shown remarkable classification accuracy. The reason for using artificial intelligence in this area is the inherent difficulty of these applications such as detecting COVID-19 infections using lung images due to its resemblance with other respiratory diseases. While the lack of sufficient training data is considered one of the main difficulties, it has been alleviated with the aid of specialized artificial intelligence techniques such as generative adversarial networks and transfer learning. Satellite-based imagery along with deep learning have shown an improvement in the air quality due to the imposed mobility restrictions during the pandemic. Apart from the technical challenges, some applications faced social and ethical challenges that are mainly related to the patient privacy. The latter factor have made dataset availability more limited, and restricted the implementation of some applications such as contact tracing. This work examines state-of-the-art studies and shows the effectiveness of artificial intelligence in solving the most challenging technical problems encountered during the pandemic.