Xia, PengRuan, JiParry, DavidAiello, StephenYu, JianBritnell, Sally2026-02-132026-02-132025-05-02Proceedings of the 22nd ISCRAM Conference: Managing and Responding to Coastal Disasters and Climate Change, held in Halifax, Nova Scotia, Canada: from May 18-21, 20251000-98251000-9825http://hdl.handle.net/10292/20638This study investigates the integration of Virtual Reality (VR) and Artificial Intelligence (AI) to enhance pre-hospital triage training for Mass Casualty Incidents (MCIs). Traditional training methods, such as field drills and full-scale simulations, are often costly and logistically challenging, while simpler methods like tabletop exercises remain limited in realism. To address these limitations, a VR learning tool was developed to simulate realistic emergency scenarios, providing emergency healthcare professionals with an immersive and cost-effective training environment to refine triage skills. The VR learning tool records both VR sensor data and speech data, and then utilizes statistical and AI methods (such as automatic speech recognition, and natural language processing) to process these data for evaluation. The survey results showed that participants with varying levels of experience found the VR training highly immersive and engaging. Additionally, AI-driven analysis of speech data from the training demonstrated improved consistency and correctness in participants’ communication over time. This research demonstrates VR’s potential as a valuable supplement to traditional training, identifying key areas for future developmentThe ISCRAM Proceedings are an open-access publication.0802 Computation Theory and Mathematics0803 Computer Software0805 Distributed ComputingSoftware Engineering46 Information and computing sciencesMass Casualty IncidentsVirtual RealityArtificial IntelligenceEducationTrainingConference ContributionOpenAccess