Human-Machine Interaction for Monitoring COVID-19 Internet Data in Russia and the World
15th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2022
; 930 LNEE:341-349, 2022.
Article
in English
| Scopus | ID: covidwho-1971538
ABSTRACT
We develop a human-machine interaction via dashboard for COVID-19 data visualization in the regions of Russia and the world. In particular, it includes an adaptive-compartmental multi-parametric model of the epidemic spread, which is a generalization of the classical SEIR models;and a module for visualizing and setting the parameters of this model according to epidemiological data, implemented in a dashboard. Data for testing have been collected since March 2020 on a daily basis from open Internet sources and placed on a “data farm” (an automated system for collecting, storing and pre-processing data from heterogeneous sources) hosted on a remote server. The combination of the proposed approach and its implementation in the form of a dashboard with the ability to conduct visual numerical experiments and compare them with real data allows most accurately tune the model parameters thus turning it into an intelligent system to support a decision-making. That is a small step towards Industry 5.0. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Big data algorithm; COVID-19 spread mathematical model; Dashboard; Data visualization; Human-machine interaction; Industry 5.0; Optimization of the decision-making process; Automation; Big data; Data handling; Decision making; Intelligent systems; Man machine systems; Visualization; Data algorithm; Decision-making process; Human machine interaction; Internet data; Optimisations; COVID-19
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
15th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2022
Year:
2022
Document Type:
Article
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