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Oil Spilling Detection at Marine Environment using Automatic Identification System (AIS) and Satellite Datasets

Year: 2025

Type: article

Abstract: Oil spills in marine environments pose serious threats to ecosystems, public health, and maritime economies. This paper presents a dual-layered automated detection framework that integrates Automatic Identification System (AIS) data with satellite remote sensing to enable early detection and reporting of oil spills. The system uses Isolation Forest for unsupervised detection of vessel anomalies and a Support Vector Machine (SVM) model for classifying potential spills from satellite imagery. This combined approach enhances the speed and accuracy of detection while supporting real-time monitoring through a user-friendly web interface.

Source: International jounal of information technology and computer engineering.

DOI: 10.62647/ijitce2025v13i2spp233-238

Authors: Ali Abbas, Shaik Abdul Rehman, Abdul Wahed Ilyas, Dr. K. Upendra Babu

Language: English

Topic: Oil Spill Detection and Mitigation

Subfield: Pollution

Field: Environmental Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4411350203

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