An investigation into computational methods for classifying fishing vessels to identify illegal, unreported and unregulated fishing activity

Grey, Benedict; Ouarbya, Lahcen and Blackwell, Tim. 2024. 'An investigation into computational methods for classifying fishing vessels to identify illegal, unreported and unregulated fishing activity'. In: 2023 8th International Conference on Computational Intelligence and Applications (ICCIA). Haikou, China 23-25 June 2023. [Conference or Workshop Item]

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Abstract or Description

Illegal, unreported and unregulated (IUU) fishing undermines collective efforts to create a global model for sustainable fishing. Countering IUU fishing is an urgent priority given world population growth and increasing dependence on oceansourced food. This paper examines deep learning methods for the classification of fishing vessels with the intent to determine illicit fishing operations. This is achieved through supervised learning with highly irregular time series data in the form of signals from the automatic identification system (AIS). To deal with the intermittent frequency of AIS signals, two separate approaches have been followed: feature engineering with zero padding and linear interpolation. Fundamentally, this work suggests there exists a distinct relationship between vessel movement patterns and method of fishing. Two neural network architectures: stacked bidirectional GRUs and 1D CNNs with residual connection blocks, are leveraged on each data pipeline to produce four sets of results. The GRU with feature engineering achieves 95% accuracy despite severe class imbalance in the large datasets. The system can classify a vessel’s fishing method over 24 hours in real-time to monitor behaviour in marine protected areas and detect gear discrepancies, safeguarding fish stocks in the process.

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Conference or Workshop Item (Paper)

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Deep learning, machine learning, data mining, supervised learning, automatic identification system, time series data, feature engineering, illegal fishing

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4 April 2023Accepted
15 January 2024Published

Event Location:

Haikou, China

Date range:

23-25 June 2023

Item ID:


Date Deposited:

25 Apr 2023 08:25

Last Modified:

01 Feb 2024 19:07


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