What is Non-Pharmacological Disease Control

This article reveals how artificial intelligence and big data analytics help the non-pharmacological disease control measures. Several cutting-edge technologies are illustrated in terms of the system architecture, the data workflows, and the machine learning/deep learning models. This article will also investigate a comprehensive social control system that is designed for disease control measures by integrating the above mentioned technologies. For each component of the system, real-world applications will be represented in the form of examining the capability of the proposed models. The proposed system can detect whether people are keeping social distancing and wearing a facial mask in public spaces, along with measuring the mobility assessment, which can be applied to screen the stay-at-home orders using big data and visual mining. A fine-tuned CNN-based network will be applied for monitoring the social distancing, while the face mask detection module is trained by fine-tuning the MobileNet architecture.