Reconstructing Damaged Data in AIS and Other Telecommunications Systems: A Survey

Authors

  • Marta Szarmach Gdynia Maritime University, Department of Marine Telecommunications, 81-87 Morska St., 81–225 Gdynia, Poland
  • Ireneusz Czarnowski Gdynia Maritime University, Department of Information Systems

DOI:

https://doi.org/10.26408/127.02

Keywords:

AIS data analysis, trajectory reconstruction, machine learning, telecommunication

Abstract

AIS (Automatic Identification System) is a telecommunication system created to enable ships to transmit information regarding their trajectories (such as their position, speed, course, etc.) to other ships and shore stations. With the use of AIS, collisions between ships can be avoided. Unfortunately, AIS suffers from some technical issues that lead to part of the transmitted data being damaged (incorrect or missing). This paper contains a review of machine learning based methods of reconstructing this damaged AIS data as well as examples of inspiration from other telecommunication systems for dealing with this kind of a problem. Finally, after analysing frameworks available in the relevant literature, a novel algorithm for AIS data reconstruction is briefly presented.

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Published

2023-09-30

How to Cite

Szarmach, M., & Czarnowski, I. (2023). Reconstructing Damaged Data in AIS and Other Telecommunications Systems: A Survey. Scientific Journal of Gdynia Maritime University, (127), 15–26. https://doi.org/10.26408/127.02

Issue

No. 127 (2023)

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