Mobility and COVID-19 spread pattern recognition in Barcelona area through Machine Learning techniques
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/346127
Realitzat a/ambCooperative Automotive Research Network (CARNET)
Tipus de documentProjecte Final de Màster Oficial
Data2021-05-19
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The past year 2020 was marked by the COVID-19 pandemic which had a great impact on many aspects of society, being mobility one of the most affected. In this context, this master’s thesis was born with the aim of finding patterns of mobility and contagion of COVID-19 in the first crown of the metropolitan area of Barcelona. These patterns are useful to characterize the areas of the territory and to understand the temporal evolution of mobility and spread of COVID-19. The motivation for this master’s thesis arises from the opportunity presented by the institution of the Metropolitan Area of Barcelona to make use of cell phone big data provided by Orange to the Ministry of Transport, Mobility and Urban Agenda (MITMA). It is highly interesting to be able to carry out a study around these data complemented with other data sources, since they have not been exploited and the public administrationhas significant interest in them. To identify these patterns, a search of academic documentation has been carried out, and a Python software has been developed to process all the data, to compute correlations and to cluster the areas using machine learning techniques for further analysis. In this subsequent analysis, the correlations have been analysed and the causalities that justify them have been sought. Finally, the clusters have been used to find patterns visually by plotting the characteristics of the zones. It is interesting to mention that the developed software is used to process all the data from the MITMA database which is still being updated to the present date. The desired results have been obtained since the characterization of the mobility and contagions of COVID-19 by clusters of zones has been achieved. Interesting conclusions have been drawn, such as that women get more infected with COVID-19, areas with a higher percentage of population aged 0-15 years have a lower volume of mobility and COVID-19 cases, or that areas with more health, education and social services facilities have a higher volume of mobility and COVID-19 cases
MatèriesCOVID-19 Pandemic, 2020- -- Barcelona Metropolitan Area (Spain) -- Statistics, Urban transportation -- Barcelona Metropolitan Area (Spain) -- Statistics, Barcelona Metropolitan Area (Spain) -- Population -- Health aspects, Machine learning, Pandèmia de COVID-19, 2020- -- Barcelona (Catalunya : Àrea metropolitana) -- Estadístiques, Transport urbà -- Barcelona (Catalunya : Àrea metropolitana) -- Estadístiques, Barcelona (Catalunya : Àrea metropolitana) -- Població -- Aspectes sanitaris, Aprenentatge automàtic
TitulacióMÀSTER UNIVERSITARI EN ENGINYERIA INDUSTRIAL (Pla 2014)
Localització
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Fitxers | Descripció | Mida | Format | Visualitza |
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tfm-gerard-franco-panades.pdf | 3,464Mb | Visualitza/Obre |