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Research Article |

Real-Time Oil Spill Detection with YOLO Framework for Marine Ecosystem Surveillance

Author(s): Srinivas Talasila1*, Vijaya Kumar Gurrala2, Varshini M3, Siva Sai Balla4, Madhuri M5, Chinthakindi Kiran Kumar6

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 13, Issue 3

Publisher : FOREX Publication

Published : 30 August 2025

e-ISSN : 2347-470X

Page(s) : 463-470

DOI: https://doi.org/10.37391/IJEER.130310

Abstract

Early detection of oil spills is crucial and essential for marine environments to minimize environmental harm and enable quick responsive measures. Oil spills can cause significant ecological and financial losses, which emphasizes the need for an efficient monitoring system. This paper presents the use of YOLO deep learning algorithms to enhance the oil spill detection speed and accuracy. A robust and high-quality dataset is taken, consisting of images extracted from Roboflow. To maximize the data quality, preprocessing techniques such as label normalization, contrast enhancement and noise reduction were used. The proposed YOLO algorithms were trained using Adam and SGDM optimizers with an initial learning rate of 0.01, 0.001 and 0.0001. Among the adopted YOLO models, YOLOv9 yielded impressive results with an mAP@0.5 of 94.45%, precision of 95.6%, recall of 93.3% and F1 Score of 94.44%. The recommended system, which incorporates deep learning technologies into marine environment monitoring, greatly improves the marine surveillance systems for oil spill detection and emergency response capabilities by enabling real-time monitoring.

Keywords: Deep Learning, Image Processing, Oil Spill Detection, Marine Ecosystem, YOLO Algorithms.




Srinivas Talasila, Department of Electronics and Communication Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India; Email: srinivas_t@vnrvjiet.in

Vijaya Kumar Gurrala , Department of Electronics and Communication Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India; Email: vijayakumar_g@vnrvjiet.in

Varshini M, Department of Electronics and Communication Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India;Email: varshinics.m@gmail.com

Siva Sai Balla, Department of Electronics and Communication Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India; Email: saishiva216@gmail.com

Madhuri M, Department of Electronics and Communication Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India; Email: madhurigoudmusthyala@gmail.com

Chinthakindi Kiran Kumar, Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, Hyderabad, India; Email: ckkmtech11@gmail.com

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Srinivas Talasila, Vijaya Kumar Gurrala, Varshini M, Siva Sai Balla, Madhuri M, and Chinthakindi Kiran Kumar(2025), Real-Time Oil Spill Detection with YOLO Framework for Marine Ecosystem Surveillance. IJEER 13(3), 463-470. DOI: 10.37391/IJEER.130310.