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Updated: Jul 13, 2026

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Artificial Intelligence in Wilderness Search and Rescue: A Narrative Review.

Kenneth V Iserson1

  • 1Department of Emergency Medicine, University of Arizona College of Medicine, Tucson, AZ.

Wilderness & Environmental Medicine
|July 9, 2026
PubMed
Summary
This summary is machine-generated.

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Artificial intelligence (AI) is enhancing wilderness Search and Rescue (SAR) operations, with AI-enabled drones proving effective in challenging conditions. Careful integration with human teams is crucial for AI to improve SAR outcomes.

Area of Science:

  • Wilderness Medicine
  • Computer Science
  • Emergency Medical Services

Background:

  • Wilderness Search and Rescue (SAR) operations face challenges including time constraints, difficult environments, and limited personnel.
  • Artificial intelligence (AI) is increasingly applied to SAR, drawing parallels with advancements in prehospital Emergency Medical Services (EMS).

Purpose of the Study:

  • To review current evidence on AI applications in wilderness SAR.
  • To identify AI's current operational status, demonstrated capabilities, and future potential in SAR.
  • To highlight lessons from EMS regarding human-AI interaction and workflow integration.

Main Methods:

  • A narrative review of literature from PubMed, IEEE Xplore, Scopus, and Google Scholar (2018-March 2026).
  • Search terms included "artificial intelligence," "machine learning," "search and rescue," "unmanned aerial vehicle," "wilderness medicine," and "prehospital care."
Keywords:
Search and Rescueartificial intelligencecomputer visiondeep reinforcement learningprehospital emergency careunmanned aerial vehicleswilderness medicine

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  • Inclusion of operational reports and trade publications for deployed SAR technologies.

    • Main Results:

    • AI-enabled unmanned aerial vehicles (UAVs) with thermal imaging and computer vision are deployed in SAR, successfully locating individuals in various conditions.
    • Deep reinforcement learning for autonomous search-path optimization shows over 160% improvement compared to traditional methods.
    • AI has been linked to successful SAR outcomes and documented live rescues.

    Conclusions:

    • AI, particularly UAVs, is actively contributing to successful wilderness SAR outcomes.
    • Lessons from EMS emphasize the importance of human-AI interaction and workflow integration for AI effectiveness.
    • Future priorities include outcome validation, drone coordination, AI-assisted medical protocols, and sustainable funding for SAR organizations.