Challenges and AI-driven solutions in maritime search and rescue planning
A comprehensive literature review
Bibliographic Data
| ID | 21521414 |
|---|---|
| Authors | Kemal Ihsan Kilic (0000-0002-6277-4867, Aalborg University, corresponding author), Samir Maity (0000-0002-7209-0784, Aalborg University), Inkyung Sung (0000-0002-7045-8143, Aalborg University), Peter Nielsen (0000-0002-7752-9514, Aalborg University) |
| Year | 2025 |
| Volume | 178 |
| Pages | 106692 |
| Publication date | 2025-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Marine Policy (JOURNAL) |
| Journal identifiers | ISSN: 0308-597X • E-ISSN: 1872-9460 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.marpol.2025.106692 |
| OpenAlex | W4409196495 |
| Language | EN |
| References cited | 65 |
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. • Comprehensive Literature Review of AI over MSAR. • Identification of Gaps and Key Challenges in MSAR. • Proposed AI-Driven Solutions Strategies for MSAR. • Trends and Future Directions through AI in MSAR
Business · Environmental planning · Geography · Operations research · Political science · Process management · Search and rescue · Computer Science · Engineering · Maritime Navigation and Safety · Optimization and Search Problems · Underwater Vehicles and Communication Systems · Artificial Intelligence
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Maritime search and rescue in canada and the use of emergency radio beacons
Consequence modelling for Arctic ship evacuations using expert knowledge
| Citation velocity | historical |
|---|---|
| Highly cited | No |