Unmanned aerial vehicle based intelligent triage system in mass-casualty incidents using 5G and artificial intelligence

BACKGROUND:Rapid on-site triage is critical after mass-casualty incidents(MCIs)and other mass injury events.Unmanned aerial vehicles(UAVs)have been used in MCIs to search and rescue wounded individuals,but they mainly depend on the UAV operator’s experience.We used UAVs and artificial intelligence(AI)to provide a new technique for the triage of MCIs and more efficient solutions for emergency rescue.METHODS:This was a preliminary experimental study.We developed an intelligent triage system based on two AI algorithms,namely OpenPose and YOLO.Volunteers were recruited to simulate the MCI scene and triage,combined with UAV and Fifth Generation(5G)Mobile Communication Technology real-time transmission technique,to achieve triage in the simulated MCI scene.RESULTS:Seven postures were designed and recognized to achieve brief but meaningful triage in MCIs.Eight volunteers participated in the MCI simulation scenario.The results of simulation scenarios showed that the proposed method was feasible in tasks of triage for MCIs.CONCLUSION:The proposed technique may provide an alternative technique for the triage of MCIs and is an innovative method in emergency rescue.

Emergency Preparedness Nursing Education: Learner and Faculty Perspectives

Over the past decade, entry-to-practice emergency preparedness competencies have been identified as an essential component of nursing education. In this paper the author reports upon a small Canadian study which explores the perspective of undergraduate learners and faculty members who participated in and/or facilitated an Emergency Preparedness Simulation (EPS) module during a primary health care praxis course. The central purpose of this study was to explore the related experiences of learners and faculty who participated in or facilitated an Emergency Preparedness Simulation (EPS) module academic year and their perspectives on the effectiveness of the simulation in preparing learners to respond to emergencies in the future. The EPS module included a seminar followed by a mass-casualty simulation experience. The mass-casualty simulation experience included a “Teddy Bear” triage and an “Explosion” triage. The constructivist data analysis identified four related patterns for both the learner and faculty participants: Strengths (S), Objections (O), Suggestions (S), and Feelings (!) [SOS!]. Three themes were identified in each pattern: relevance, design, and engagement. In comparing the learner and faculty perspectives, there is a clear congruence between the strengths identified, the objections identified, and the power of feelings for both learners and faculty who participate in the emergency preparedness scenarios. Learners and faculty had different suggestions. Learners suggested more time on developing skills, particularly around first aid of individual clients, and recommended all students begin with the “Teddy Bear” triage. Faculty suggested a re-thinking of the “Explosion” triage simulation to emphasize community based emergency preparedness and responsiveness. Such re-focusing would support the integration of key primary health care principles and values including equity, social justice, and social determinants of health. Learners and faculty valued the EPS module and recommended it continue to be a learning component of the primary health care course.