research-article

Classification of vessel activity in streaming data

Authors:

Ioannis Kontopoulos,

Konstantinos Chatzikokolakis,

Konstantinos Tserpes,

Dimitris ZissisAuthors Info & Claims

DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems

Pages 153 - 164

https://doi.org/10.1145/3401025.3401763

Published: 15 July 2020 Publication History

Abstract

In this paper we motivate the need for real-time vessel behaviour classification and describe in detail our event-based classification approach, as implemented in our real-world industry strong maritime event detection service at MarineTraffic.com. A novel approach is presented for the classification of vessel activity from real-time data streams. The proposed solution splits vessel trajectories into multiple overlapping segments and distinguishes the ones in which a vessel is engaged in trawling or longlining operation (e.g. fishing activity) from other segments that a vessel is simply underway from its departure towards its destination. We evaluate the effectiveness of our tool on real-world data, demonstrating that it can practically achieve high accuracy results. We present our results and findings intended for both researchers and practitioners in the field of intelligent ship tracking and surveillance.

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Cited By

Troupiotis-Kapeliaris AKastrisios CZissis D(2025)Vessel Trajectory Data Mining: A ReviewIEEE Access10.1109/ACCESS.2025.352595213(4827-4856)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3525952
d’Afflisio EMillefiori LBraca PGuerriero M(2024)MARITRAC: Maritime trajectory classification using object instance segmentation with model-based generated data augmentation2024 27th International Conference on Information Fusion (FUSION)10.23919/FUSION59988.2024.10706510(1-8)Online publication date: 8-Jul-2024
https://doi.org/10.23919/FUSION59988.2024.10706510
Kontopoulos IVarlamis IMakris ATserpes K(2024)A spatio-temporal matrix representation for trajectory classificationProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691209(481-484)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3678717.3691209
Show More Cited By

Index Terms

Classification of vessel activity in streaming data
1. Computer systems organization
  1. Real-time systems
    1. Real-time system architecture
2. Computing methodologies
  1. Distributed computing methodologies
    1. Distributed algorithms
  2. Machine learning
    1. Machine learning approaches

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Published In

cover image ACM Conferences

DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems

July 2020

244 pages

ISBN:9781450380287

DOI:10.1145/3401025

Conference Chair:
Julien Gascon-Samson
ÉTS
,
General Chairs:
Kaiwen Zhang
ÉTS Montréal
,
Khuzaima Daudjee
University of Waterloo
,
Bettina Kemme
McGill University

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 July 2020

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DEBS '20: The 14th ACM International Conference on Distributed and Event-based Systems

July 13 - 17, 2020

Quebec, Montreal, Canada

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DEBS '20 Paper Acceptance Rate 11 of 43 submissions, 26%;

Overall Acceptance Rate 145 of 583 submissions, 25%

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Cited By

Troupiotis-Kapeliaris AKastrisios CZissis D(2025)Vessel Trajectory Data Mining: A ReviewIEEE Access10.1109/ACCESS.2025.352595213(4827-4856)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3525952
d’Afflisio EMillefiori LBraca PGuerriero M(2024)MARITRAC: Maritime trajectory classification using object instance segmentation with model-based generated data augmentation2024 27th International Conference on Information Fusion (FUSION)10.23919/FUSION59988.2024.10706510(1-8)Online publication date: 8-Jul-2024
https://doi.org/10.23919/FUSION59988.2024.10706510
Kontopoulos IVarlamis IMakris ATserpes K(2024)A spatio-temporal matrix representation for trajectory classificationProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691209(481-484)Online publication date: 29-Oct-2024
https://dl.acm.org/doi/10.1145/3678717.3691209
Rong HTeixeira ASoares C(2024)A framework for ship abnormal behaviour detection and classification using AIS dataReliability Engineering & System Safety10.1016/j.ress.2024.110105(110105)Online publication date: Mar-2024
https://doi.org/10.1016/j.ress.2024.110105
Zaman BMarijan DKholodna T(2024)Online Ornstein–Uhlenbeck based anomaly detection and behavior classification using AIS data in maritimeOcean Engineering10.1016/j.oceaneng.2024.119057312(119057)Online publication date: Nov-2024
https://doi.org/10.1016/j.oceaneng.2024.119057
Luo DChen PYang JLi XZhao Y(2023)A New Classification Method for Ship Trajectories Based on AIS DataJournal of Marine Science and Engineering10.3390/jmse1109164611:9(1646)Online publication date: 23-Aug-2023
https://doi.org/10.3390/jmse11091646
Yin CChen SYin Z(2023)Clustering-based Active Learning Classification towards Data StreamACM Transactions on Intelligent Systems and Technology10.1145/357983014:2(1-18)Online publication date: 9-Jan-2023
https://dl.acm.org/doi/10.1145/3579830
Tavakoli YPeña-Castillo LSoares A(2022)A Study on the Geometric and Kinematic Descriptors of Trajectories in the Classification of Ship TypesSensors10.3390/s2215558822:15(5588)Online publication date: 26-Jul-2022
https://doi.org/10.3390/s22155588
Fikioris GPatroumpas KArtikis APitsikalis MPaliouras G(2022)Optimizing vessel trajectory compression for maritime situational awarenessGeoInformatica10.1007/s10707-022-00475-027:3(565-591)Online publication date: 29-Aug-2022
https://doi.org/10.1007/s10707-022-00475-0
ElZonkoly MMadbouly MGurguis S(2022)Real Time Adaptive GPS Trajectory CompressionProceedings of the 8th International Conference on Advanced Intelligent Systems and Informatics 202210.1007/978-3-031-20601-6_32(354-369)Online publication date: 18-Nov-2022
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