Ecological Application of UAVs for Monitoring and Eliminating Oil Product Spills on the Sea Surface

Abstract

The objective of marine ecological safety necessitates the development of comprehensive, integrated strategies for oil spill management, encompassing advanced monitoring and effective remediation. This paper introduces and validates a novel integrated methodology and conceptual framework for autonomous marine environmental safety. The core of this framework lies in the merging of AI-assisted monitoring capabilities with a multi-agent Unmanned Aerial Vehicle (UAV) system for targeted dispersant delivery. UAV systems, within this methodology, function as a cost-effective and readily deployable operational platform. The study details the primary development stages of the methodology-driven system and presents empirical results from in-situ field trials. The framework leverages artificial intelligence (AI) tools developed and validated for slick monitoring, which execute primary segmentation for spill detection and subsequent secondary segmentation to categorize the slick into thickness uniformity maps. Datasets of actual marine oil slick imagery were compiled to facilitate robust deep learning of the underlying neural network architectures. The study explores scientific feasibility, specifically employing Laser-Induced Fluorescence (LIF) spectroscopy to classify oil product grades and assess the ecological impact of various remediation agents on local phytoplankton communities. This integrated method for spill response is underpinned by successful field validation results. The full methodology was tested during actual oil spill incidents in the waters of Peter the Great Bay from 2019 to 2024. The article presents experimental validation of a new concept and methodology of integrated environmental safety of marine areas by a multi-agent UAV system in the event of oil product spills.

Keywords

Oil product slick / UAV / Monitoring / Elimination / Dispersant / Segmentation / Neural net / Deep learning / AI / Laser induced fluorescence

Author Contributions

Conceptualization, O.A.B. and V.Y.; methodology, O.A.B. and D.P.; software, A.C. and D.P.; validation, D.K., I.B., D.B.; formal analysis, S.G. All authors have read and agreed to the published version of the manuscript.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Funding

This research was funded by the Russian Ministry of Transport (State Task No.110-00022-21-00).

Declaration of Competing Interest

The authors declare no conflict of interest.

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