摘要
针对院前急救资源配置低效问题,本研究通过车载传感器、智能标签实时采集车辆状态、物资消耗及操作数据形成全要素监测网络;融合人工智能算法与物联网技术建立基于国家标准的救护车智能选型模型、覆盖库存监控到应急调配的全流程物资管理机制,开发虚拟现实/增强现实模拟训练系统规范人员操作。研究从配置优化、流程规范、技能强化3维度提出疾病谱适配的物资精准储备策略,构建包含智能监测、预测性维护的车辆运维体系。研究通过人-车-物协同管理实现资源高效配置与风险前瞻干预,为院前急救数字化转型提供可复制的技术路径与实践参考。
Aiming at the problem of inefficient allocation of pre-hospital emergency resources,this study forms a full-element monitoring network by real-time collection of vehicle status,material consumption and operation data through on-board sensors and intelligent tags.Integrate artificial intelligence algorithms with Internet of Things(iot)technology to establish an intelligent ambulance selection model based on national standards,a full-process material management mechanism covering inventory monitoring to emergency allocation,and develop a virtual reality/augmented reality simulation training system to standardize personnel operations.The research proposes a precise material reserve strategy that suits the disease spectrum from three dimensions:configuration optimization,process standardization,and skill enhancement,and builds a vehicle operation and maintenance system that includes intelligent monitoring and predictive maintenance.The research aims to achieve efficient resource allocation and forward-looking risk intervention through the collaborative management of people,vehicles and objects,providing replicable technical paths and practical references for the digital transformation of pre-hospital emergency care.
作者
陶静
苏明敏
朱艳华
TAO Jing;SU Mingmin;ZHU Yanhua(Qidong City 120 Emergency Command Center,Qidong 226200,Jiangsu,China)
出处
《中国卫生产业》
2025年第17期128-131,共4页
China Health Industry
关键词
院前急救
救护车管理
急救物品
细节管理
Pre-hospital emergency treatment
Ambulance management
First aid supplies
Detail management
