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Maritime Tracking Data Analysis and Integration with AISdb

Authors :
Spadon, Gabriel
Kumar, Jay
Chen, Jinkun
Smith, Matthew
Hilliard, Casey
Vela, Sarah
Gehrmann, Romina
DiBacco, Claudio
Matwin, Stan
Pelot, Ronald
Publication Year :
2024

Abstract

Efficiently handling Automatic Identification System (AIS) data is vital for enhancing maritime safety and navigation, yet is hindered by the system's high volume and error-prone datasets. This paper introduces the Automatic Identification System Database (AISdb), a novel tool designed to address the challenges of processing and analyzing AIS data. AISdb is a comprehensive, open-source platform that enables the integration of AIS data with environmental datasets, thus enriching analyses of vessel movements and their environmental impacts. By facilitating AIS data collection, cleaning, and spatio-temporal querying, AISdb significantly advances AIS data research. Utilizing AIS data from various sources, AISdb demonstrates improved handling and analysis of vessel information, contributing to enhancing maritime safety, security, and environmental sustainability efforts.

Subjects

Subjects :
Computer Science - Databases

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2407.08082
Document Type :
Working Paper