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Dynamic Insights: A Web-Based Analysis Platform for Italian Transport Trends

Masumeh Shahbazi

Dynamic Insights: A Web-Based Analysis Platform for Italian Transport Trends.

Rel. Cristina Pronello. Politecnico di Torino, Corso di laurea magistrale in Digital Skills For Sustainable Societal Transitions, 2024

Abstract:

The rapid growth of urban environments and the increasing complexity of transport systems require robust tools for analysing mobility trends to support strategic planning and effective decision-making. In response to these needs and based on the work carried out during the curricular internship at FS Research Centre of Ferrovie dello Stato Italiane, this research aims to develop a web-based platform integrated into the Strategic Information Management System (SIMS), to monitor Italian transport trends comprehensively. The research methodology is structured in several phases. Firstly, a benchmarking analysis of existing European mobility platforms was conducted to identify best practices and gaps. Secondly, key mobility datasets were identified, selected, and processed for integration into the platform. Finally, interactive dashboards were designed and implemented using Tableau software to provide visual insights into mobility trends. First results indicate that the platform effectively provides detailed and real-time insights, allowing for a better understanding of mobility trends. Furthermore, by enhancing the accessibility and usability of data, the platform supports decision-making and enables stakeholders to make more evidence-based decisions to implement timely and effective transport management strategies. This research demonstrates that integrating different data sources and creating an interactive dashboard helps to make the decision-making process faster and more accurate. However, the platform’s reliance on specific data sources and the complexities involved in data integration may constrain its broader applicability.

Relatori: Cristina Pronello
Anno accademico: 2024/25
Tipo di pubblicazione: Elettronica
Numero di pagine: 71
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Digital Skills For Sustainable Societal Transitions
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-91 - TECNICHE E METODI PER LA SOCIETÀ DELL'INFORMAZIONE
Aziende collaboratrici: Ferrovie dello Stato Italiane S.p.a.
URI: http://webthesis.biblio.polito.it/id/eprint/32464
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