Challenges and AI-driven solutions in maritime search and rescue planning: A comprehensive literature review

IF 3.5 2区社会学 Q2 ENVIRONMENTAL STUDIES

Marine Policy Pub Date : 2025-04-04 DOI:10.1016/j.marpol.2025.106692

Kemal Ihsan Kilic, Samir Maity, Inkyung Sung, Peter Nielsen

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引用次数: 0

Abstract

Maritime Search and Rescue (MSAR) operations face significant challenges due to high uncertainty, dynamic conditions, and resource constraints. Additionally, rigid organizational structures and hierarchical human-centered communication frameworks, fail to adapt to the challenging conditions of maritime environments. This paper provides a comprehensive review of the integration of Artificial Intelligence (AI) into MSAR operations, highlighting how AI can transform these systems through enhanced decision-making, real-time adaptability, decentralized autonomy, and resource optimization. Through analysis and synthesis, we identified and categorized key challenges in traditional SAR frameworks, such as inherent environmental and structural challenges. We discussed AI-driven solutions that offer efficient, autonomous, resilient, and decentralized coordination. Our thematic and statistical analysis of existing literature reveals significant research gaps, particularly regarding the holistic integration of AI across all SAR stages toward a decentralized fully autonomous paradigm shift. The paper also considers the technological challenges for the integration and adaptation of AI in SAR. By envisioning fully autonomous, AI-driven MSAR operations, this study sets the stage for future research and practical innovations, aiming to improve effectiveness and efficiency in maritime rescue efforts.

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海上搜救计划中的挑战和人工智能驱动的解决方案：综合文献综述

由于高度不确定性、动态条件和资源限制，海上搜救（MSAR）行动面临着重大挑战。此外，僵化的组织结构和分层的以人为中心的沟通框架无法适应海洋环境的挑战条件。本文全面回顾了人工智能（AI）与澳门特别行政区作战的整合，重点介绍了人工智能如何通过增强决策、实时适应性、分散自治和资源优化来改变这些系统。通过分析和综合，我们确定并分类了传统SAR框架中的关键挑战，如固有的环境和结构挑战。我们讨论了人工智能驱动的解决方案，这些解决方案提供了高效、自主、有弹性和分散的协调。我们对现有文献的专题和统计分析揭示了重大的研究差距，特别是关于人工智能在所有SAR阶段的整体整合，以实现分散的完全自主范式转变。本文还考虑了人工智能在搜救中的整合和适应所面临的技术挑战。通过设想完全自主的人工智能驱动的搜救行动，本研究为未来的研究和实践创新奠定了基础，旨在提高海上救援工作的有效性和效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Marine Policy Multiple-

CiteScore

7.60

自引率

13.20%

发文量

428

期刊介绍： Marine Policy is the leading journal of ocean policy studies. It offers researchers, analysts and policy makers a unique combination of analyses in the principal social science disciplines relevant to the formulation of marine policy. Major articles are contributed by specialists in marine affairs, including marine economists and marine resource managers, political scientists, marine scientists, international lawyers, geographers and anthropologists. Drawing on their expertise and research, the journal covers: international, regional and national marine policies; institutional arrangements for the management and regulation of marine activities, including fisheries and shipping; conflict resolution; marine pollution and environment; conservation and use of marine resources. Regular features of Marine Policy include research reports, conference reports and reports on current developments to keep readers up-to-date with the latest developments and research in ocean affairs.