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Big Data Helps for Non-Pharmacological Disease Control Measures of COVID-19
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Author(s): Peng Zhao (INTELLIGENTRABBIT LLC, USA), Yuan Ren (Shanghai Dianji University, China)and Xi Chen (Beijing University of Civil Engineering and Architecture, China)
Copyright: 2023
Pages: 13
Source title:
Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch009
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Abstract
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.
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