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Big Data assisted Strategy for Resuming of Work and Production during COVID-19
2021 International Conference on Information and Communication Technologies for Disaster Management, ICT-DM 2021 ; : 65-71, 2021.
Article in English | Scopus | ID: covidwho-1714061
ABSTRACT
In April 2020, with the development of the nationwide epidemic prevention and control work, the epidemic situation of New Coronavirus has entered a stable stage. However, the resumption of production and recovery is crucial to maintain the stable development of economy and society. Imminent. Therefore, how to co-ordinate the epidemic prevention and control and return to work has become another major challenge for governments at all levels. The joint prevention and control mechanism of the State Council issued a document requiring all localities to 'conduct accurate prevention and control in different regions and levels, and coordinate the prevention and control of epidemic situation and the restoration of economic and social order'. In this context, China Unicom gives full play to the unique advantages of multi-source, massive and integrated big data of operators, and helps enterprises to resume work and production from four aspects real-time insight of regional return to work rate, grid risk index assessment, risk analysis of regional population inflow, and risk analysis of employees' travel mode, so as to provide support for enterprise decision makers and formulate scientific policies and means, gradually realize the full return to work. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2021 International Conference on Information and Communication Technologies for Disaster Management, ICT-DM 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2021 International Conference on Information and Communication Technologies for Disaster Management, ICT-DM 2021 Year: 2021 Document Type: Article