GUIDE2FR:一个智能监控平台,具有消防员训练塔的数字孪生体,用于紧急情况

IF 7.6 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Marcos Delgado Álvaro , Robert Novak , Pedro Rafael Fernández Barbosa , Iván Chicano Capelo , Micael Gallego , M. Cristina Rodriguez-Sanchez
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引用次数: 0

摘要

本文介绍了为建筑物实施数字孪生,以提高第一反应小组(包括消防员、警察和紧急医疗服务)的应急响应能力。提出的平台改进了预防性疏散策略的规划,并支持紧急情况下的实时操作决策。它集成了专门为恶劣环境设计的无线监测信标、基于云的数据管理系统和监测环境空气质量参数的预测模型,这些参数在紧急情况下至关重要。该平台使用数字双胞胎来模拟建筑物的行为,结合多媒体内容和时间序列图表来增强态势感知和决策。实时建筑数据与智能建筑传感器生成的预测模型无缝集成,在基于web的监控界面上提供全面的可视化。这种方法为决策者提供了重要的见解,提高了救援行动和预防措施的安全性和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GUIDE2FR: A smart monitoring platform with a digital twin of a firefighter training tower for emergency scenarios

GUIDE2FR: A smart monitoring platform with a digital twin of a firefighter training tower for emergency scenarios
This paper describes the implementation of a digital twin for buildings to enhance the emergency response capabilities of first responder teams, including firefighters, police, and emergency medical services. The proposed platform improves the planning of preventive evacuation strategies and supports real-time operational decisions during emergencies. It integrates wireless monitoring beacons, specifically designed for hostile environments, a cloud-based data management system, and a predictive model to monitor environmental air quality parameters, which are critical during emergency scenarios. The platform uses a digital twin to simulate the building’s behavior, incorporating multimedia content and time series graphs to enhance situational awareness and decision-making. Real-time building data are seamlessly integrated with predictive models generated from smart building sensors, offering a comprehensive visualization on a web-based monitoring interface. This approach provides critical insights to decision-makers, improving the safety and efficiency of both rescue operations and preventive measures.
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来源期刊
Internet of Things
Internet of Things Multiple-
CiteScore
3.60
自引率
5.10%
发文量
115
审稿时长
37 days
期刊介绍: Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.
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