Edge computing based real-time Nephrops (Nephrops norvegicus) catch estimation in demersal trawls using object detection models

In demersal trawl fisheries, the unavailability of the catch information until the end of the catching process is a drawback, leading to seabed impacts, bycatches and reducing the economic performance of the fisheries. The emergence of in-trawl cameras to observe catches in real-time can provide suc...

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Bibliographic Details
Published in:Scientific reports 2024-04, Vol.14 (1), p.9481-9481, Article 9481
Main Authors: Avsar, Ercan, Feekings, Jordan P., Krag, Ludvig Ahm
Format: Article
Language:English
Subjects:
639/705/117
704/829/826
Algorithms
Animals
Bycatch
Commercial fishing
Deep learning
Economics
Edge computing
Fish
Fisheries
Fishes - physiology
Fishing
Humanities and Social Sciences
Image Processing, Computer-Assisted - methods
Models, Theoretical
multidisciplinary
Nephrops
Ocean floor
Processing speed
Science
Science (multidisciplinary)
Sustainability
Video Recording - methods
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Summary:In demersal trawl fisheries, the unavailability of the catch information until the end of the catching process is a drawback, leading to seabed impacts, bycatches and reducing the economic performance of the fisheries. The emergence of in-trawl cameras to observe catches in real-time can provide such information. This data needs to be processed in real-time to determine the catch compositions and rates, eventually improving sustainability and economic performance of the fisheries. In this study, a real-time underwater video processing system counting the Nephrops individuals entering the trawl has been developed using object detection and tracking methods on an edge device (NVIDIA Jetson AGX Orin). Seven state-of-the-art YOLO models were tested to discover the appropriate training settings and YOLO model. To achieve real-time processing and accurate counting simultaneously, four frame skipping ideas were evaluated. It has been shown that adaptive frame skipping approach, together with YOLOv8s model, can increase the processing speed up to 97.47 FPS while achieving correct count rate and F-score of 82.57% and 0.86, respectively. In conclusion, this system can improve the sustainability of the Nephrops directed trawl fishery by providing catch information in real-time.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-60255-8