# Maritime Tracking Data Analysis and Integration with AISdb

arXiv: https://arxiv.org/abs/2407.08082 · HTML: https://mlsanity.com/paper/2407.08082/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jul 2024.

## Built on by (most cited first, 3 of 3)

- [Physics-Informed Neural Networks for Vessel Trajectory Prediction: Learning Time-Discretized Kinematic Dynamics via Finite Differences](https://mlsanity.com/paper/2506.12029/) (2025)
- [Goal-Conditioned Reinforcement Learning for Data-Driven Maritime Navigation](https://mlsanity.com/paper/2509.01838/) (2025)
- [Multi-vessel Interaction-Aware Trajectory Prediction and Collision Risk Assessment](https://mlsanity.com/paper/2509.01836/) (2025)

## Abstract (arXiv)

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.