Abstract
The air transport industry has marked unprecedented changes throughout the pandemic period of Covid-19 infection. Mostly in the number of flights canceled, liquidation of airlines and disconnection between points worldwide. The existing documentation relating to air traffic, in the specific period of this study, can be extracted, processed and visualized through tools widely used to support case study assumptions, especially in the context of Big Data. This document addresses to the use of a Big Data architecture to survey, analyze and explore different data sources and consequent loading, transformation and visual representation of the results obtained in order to verify the impact of the number of cases of infection by Covid-19 in air traffic. Based on the results obtained through the described methodology, it can be stated that the number of cases of infection by Covid-19 presents a significant impact on the number of flights that occurred ever since (around 50% less flights).
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Aknowledgements
This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R &D Units Project Scope: UIDB/00319/2020. The grant of Regina Sousa is supported by the project “Integrated and Innovative Solutions for the well-being of people in complex urban centers” within the Project Scope NORTE-01-0145-FEDER-000086.
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Sousa, R. et al. (2023). COVID-19 Cases and Their Impact on Global Air Traffic. In: Machado, J.M., Peixoto, H. (eds) AI-assisted Solutions for COVID-19 and Biomedical Applications in Smart Cities. AISCOVID 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 485. Springer, Cham. https://doi.org/10.1007/978-3-031-38204-8_2
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