Data scraping, storage and analysis of cruise data

Abstract

Τhis thesis deals with the conditions of cruises’ traffic around the world. It exploits data scraping, storage, and analysis techniques to provide a full overview on density, hotspots, and temporal trends of shipping in this region. AIS-related data and cruise metadata were scraped from several websites of maritime traffic and stored in a structured format for efficient retrieval/analysis with Elasticsearch and Tableau. These results highlight substantial traffic density in zones such as the Strait of Gibraltar and the Suez Canal, and primary harbors like Valencia and Barcelona. Temporal analysis accrues vessel movements to maximum values during daylight hours, while seasonal trends show more traffic in summer months. This information is very important in planning cruises’ operations, infrastructure design, and mitigation strategies for environmental impacts. The thesis also provides some insights into cruises’ traffic dynamics and integration of modern data analytics technologies in maritime research. More specifically, the thesis highlights that there could be practical applications aiming for the enhancement of resource allocation for port authorities, scheduling and route planning optimization for shipping companies, and targeted environmental monitoring. Further improvement of data collection methods, application of more efficient and advanced methods of analysis, and additional research of global events that influence sea traffic may become long-term goals for further studies. The work accomplished thus far provides a basis for continued research and development in cruises’ traffic analysis, where efforts aim to continue support of ever more efficient, sustainable, and resilient cruising operations.