Evaluating Deep Learning Assisted Automated Aquaculture Net Pens Inspection Using ROV

Waseem Akram, Muhayyuddin Ahmed, Lakmal Seneviratne, Irfan Hussain

2023

Abstract

In marine aquaculture, inspecting sea cages is an essential activity for managing both the facilities’ environmental impact and the quality of the fish development process. Fish escape from fish farms into the open sea due to net damage, which can result in significant financial losses and compromise the nearby marine ecosystem. The traditional inspection system in use relies on visual inspection by expert divers or Remotely Operated Vehicles (ROVs), which is not only laborious, time-consuming, and inaccurate but also largely dependent on the level of knowledge of the operator and has a poor degree of verifiability. This article presents a robotic-based automatic net defect detection system for aquaculture net pens oriented to on-ROV processing and real-time detection. The proposed system takes a video stream from an onboard camera of the ROV, employs a deep learning detector, and segments the defective part of the image from the background under different underwater conditions. The system was first tested using a set of collected images for comparison with the state-of-the-art approaches and then using the ROV inspection sequences to evaluate its effectiveness in real-world scenarios. Results show that our approach presents high levels of accuracy even for adverse scenarios and is adequate for real-time processing on embedded platforms.

Paper Citation

in Harvard Style

Akram W., Ahmed M., Seneviratne L. and Hussain I. (2023). Evaluating Deep Learning Assisted Automated Aquaculture Net Pens Inspection Using ROV. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5, SciTePress, pages 586-591. DOI: 10.5220/0012160900003543

in Bibtex Style

@conference{icinco23,
author={Waseem Akram and Muhayyuddin Ahmed and Lakmal Seneviratne and Irfan Hussain},
title={Evaluating Deep Learning Assisted Automated Aquaculture Net Pens Inspection Using ROV},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={586-591},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012160900003543},
isbn={978-989-758-670-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Evaluating Deep Learning Assisted Automated Aquaculture Net Pens Inspection Using ROV
SN - 978-989-758-670-5
AU - Akram W.
AU - Ahmed M.
AU - Seneviratne L.
AU - Hussain I.
PY - 2023
SP - 586
EP - 591
DO - 10.5220/0012160900003543
PB - SciTePress