Tesi etd-11152023-170457 |
Link copiato negli appunti
Tipo di tesi
Tesi di laurea magistrale
Autore
CORDEIRO OCAMPO, ANDRES ABEL
Indirizzo email
a.cordeiroocampo@studenti.unipi.it, cordeiroandres@gmail.com
URN
etd-11152023-170457
Titolo
Thunder Flow: A tool for Data-Driven Analysis of Electric Vehicle Battery Consumption
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Relatori
relatore Prof. Nanni, Mirco
Parole chiave
- big data gps
- electric mobility
- ev data driven analysis
- sustainable transportation
Data inizio appello
01/12/2023
Consultabilità
Tesi non consultabile
Riassunto
An innovative tool designed to estimate the energy consumption of battery electric vehicles (BEVs). This solution offers a comprehensive set of features to accurately process and analyze data related to EV energy usage. We conducted a thorough testing phase for our tool, comparing the results with the previous Java-based project, to ensure its functionality and scalability. After completing the standalone testing, we applied the tool to an extensive dataset containing geographic coordinates from central and northern Italy. Our focus was on conducting a detailed, data-driven analysis of the outcomes.
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