在5G网络中使用D2D跟踪Covid-19感染者及其邻近用户

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of Communications Software and Systems Pub Date : 2023-01-01 DOI:10.24138/jcomss-2022-0103
Maryam Qusai Abdulqadir, A. A. Al Janaby
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引用次数: 0

摘要

世界目睹了一场需要加以限制的大流行。COVID-19是一种通过感染者与他人密切接触而在人群中传播的疾病。为了减少病毒的传播,世界卫生组织(WHO)采取了预防措施,并提出了一些应遵循的规则,如保持社交距离和隔离感染者。我们提出了一个使用D2D和物联网技术的模型,用于跟踪COVID-19感染者及其邻近地区。如果一个人(移动设备)靠近被感染的人,他也会被感染,所以通过不断的移动,感染就会传播。因此,确定感染者及其接触者将限制疾病的传播。在每一种情况下,都有可能区分受感染的人数,知道他们是由谁感染的,以及感染的地点。仿真显示了移动设备在3米距离内接近感染者时的跟踪。因此,我们提出的D2D模型是有效的,特别是在发现COVID-19感染者,跟踪他们,确定最小距离并识别感染源的场景中。因此,该模型可以确定与感染者的3米距离,并向网络发送预防信息,从而限制新冠病毒的快速传播。
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Tracking Infected Covid-19 Persons and their Proximity Users Using D2D in 5G Networks
The world witnessed a pandemic that needs to be limited. COVID-19 is a disease that spreads among people when an infected person is in close contact with another. To decrease the virus spreading, World Health Organization (WHO) imposed precautionary measures and suggested some rules to be followed such as social distancing and quarantining the infected people. We propose a model, using D2D and IoT technology, for tracking infected persons with COVID-19 and its proximity. If a person (mobile device) gets close to an infected person, he will also get infected, so by continuous moving, the infection will be transmitted. Thus, identifying the infected persons and their contacts will limit the spread of the disease. In each scenario, it is possible to distinguish the number of infected people and know from whom they are infected, and the location of the infection. The simulation shows the tracking of a mobile device when proximate infected person at a distance of 3 meters. As a result, our proposed D2D model is effective, especially in the scenario which found the infected person with COVID-19, tracks them, determines minimum distances, and recognizes the source of the infection. Thus, the model can limit the rapid spread of COVID-19 as it determines the 3meters distance from infected person and send precaution messages to the network.
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来源期刊
Journal of Communications Software and Systems
Journal of Communications Software and Systems Engineering-Electrical and Electronic Engineering
CiteScore
2.00
自引率
14.30%
发文量
28
审稿时长
8 weeks
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