Mejorando las ciudades a partir del análisis de datos de transporte

Author

Gesa Tàrrega, Carlos

Abstract

The objectives of the research work are the study and analysis of the Bicing network of the city of Barcelona, creating visualization to understand the usage behaviour of the bike sharing.
The analysis focuses on analysing a given data set and studying the possible implementations to extract useful data and conclusions that help us to take decisions.
To carry out this analysis, data has been obtained from the Open Data BCN system. Open data BCN or opening of public sector information, belongs to the Barcelona City Council and is a movement promoted by public administrations with the main objective of making the most of available public resources, exposing the information generated or kept by public organizations, allowing its access and reuse for the common good and for the benefit of interested persons and entities.
The data included in the analysis correspond to the use of Bicing bicycles during the month of June 2019, it shows the number of available bicycles according to the time of reading and the Id of the Bicing stations.
The study of the set will begin with the analysis of the raw data, the cleaning of it, and the possible conclusions depending on the results.
The results of the temporal and spatial patterns of the Bicing system have been obtained by analysing the visualizations and animations programmed in an R script. Different categories of stations have been identified depending on their behaviour and they have been represented in different maps to observe that they have a close geographical position to each other.
In conclusion, two sets of Bicing data have been analysed, one with information regarding the number of bicycles available at each station every 5 minutes and the other with the geographical location of the stations. Modifications have been made to the data for its correct use during the study. A series of visualizations and animations of the data have been developed. Finally, temporal and spatial patterns have been identified and categorized.

 

Director

Cuadros Margarit, Jordi
Serrano Molinero, Vanessa

Degree

IQS SE - Undergraduate Program in Industrial Engineering

Date

2021-06-17