aceA Drone-Integrated Artificial Intelligence-Based System for Mass-Casualty Triage and Remote Monitoring
Objective Triage and data transfer are critical to the medical management of mass-casualty incidents (MCIs). However, the chaotic nature of such events makes it difficult to classify casualties according to structured triage protocols. Furthermore, even when triage is implemented effectively, communication disruptions between the incident scene and dispatch centers can hinder response operations. The aim of this study was to present a drone-integrated system that enables non-contact vital sign measurement, remot…
In a controlled indoor pilot, drone-captured images let AI algorithms measure victims' vital signs without contact, with relative accuracy of 86% to 99%, supporting remote triage and data transmission to dispatch.
The algorithms still need better robustness to motion, adaptability to changing environments, and consistent accuracy across individual differences, so field performance is unproven.
The accuracy results come from a pilot under controlled indoor conditions, and the authors say the algorithms need more robustness to motion, environmental change and individual differences.
Evidence
- Peer-reviewedPrehospital and Disaster Medicine2026-10-19
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Truvace Impact Record TRV-2026-2057, v1: “A Drone-Integrated Artificial Intelligence-Based System for Mass-Casualty Triage and Remote Monitoring.” Truvace, 2026-10-21. /record/TRV-2026-2057 (accessed at citation time). sha256 12304ce78c58fbdc…
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