Division of Information Science and Technology, Wenhua University, Wuhan, Hubei, China.
School of Software, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Technol Health Care. 2022;30(S1):303-314. doi: 10.3233/THC-THC228029.
With the continuous expansion of urban scale and the increasing concentration of population, public health crisis has become an important part of urban residents' health management. The outbreak of the COVID-19 pandemic in Wuhan in 2020 has sounded the alarm.
With the government at all levels to carry out the construction of urban Internet of things and information internet, the Internet backbone network has been built, deployed a large number of sensors, and collected a large number of urban situation data.
In this paper, situational awareness technology is introduced into public health emergency services.
By constructing ontology, situational data and residents' health data are integrated. Through key technologies such as situational data collection, data fusion and data mining, real-time perception of environmental conditions of public health emergency scene is realized, and situational data fusion and situational information reasoning model are constructed.
The model is applied to the public health crisis emergency simulation system to verify the effectiveness of the model.
随着城市规模的不断扩大和人口的日益集中，公共卫生危机已成为城市居民健康管理的重要内容。2020 年武汉新冠肺炎疫情的爆发敲响了警钟。
随着各级政府开展城市物联网和信息互联网建设，骨干网已经建成，部署了大量传感器，并采集了大量城市情况数据。
本文将态势感知技术引入公共卫生应急服务中。
通过构建本体，整合态势数据和居民健康数据。通过态势数据采集、数据融合和数据挖掘等关键技术，实现对公共卫生应急场景环境条件的实时感知，构建态势数据融合和态势信息推理模型。
将模型应用于公共卫生危机应急模拟系统，验证模型的有效性。
