Explainable AI and Mass Surveillance System-Based Healthcare Framework to Combat COVID-I9 Like Pandemics
Explainable AI and Mass Surveillance System-Based Healthcare Framework to Combat COVID-I9 Like Pandemics
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DOI：
10.1109/mnet.011.2000458
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发表时间：
2020-07-01
期刊：
影响因子：
9.3
通讯作者：
Guizani, Nadra
中科院分区：
文献类型：
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作者：
Hossain, M. Shamim;Muhammad, Ghulam;Guizani, Nadra
专注于5G或超越5G的触觉边缘技术揭示了一种令人兴奋的方法，可以在国际上控制COVID-19等传染病。通过5G无线连接网络利用边缘计算，可以有效地控制COVID-19等流行病。分层边缘计算系统的实现提供了许多优点，例如低延迟、可扩展性以及对应用程序和训练模型数据的保护，使COVID-19能够由可靠的本地边缘服务器进行评估。此外，许多深度学习（DL）算法存在两个关键缺点：首先，训练需要由各个方面组成的大型COVID-19数据集，这将给地方议会带来挑战;其次，为了承认结果，深度学习的发现需要医疗保健部门以及其他贡献者在道德上接受和澄清。在这篇文章中，我们提出了一个B5 G框架，利用5G网络的低延迟，高带宽功能，通过胸部X光或CT扫描图像检测COVID-19，并开发一个大规模监控系统来监控社交距离，口罩佩戴和体温。在拟议的框架中研究了三个深度学习模型：ResNet 50、Deep tree和Inception v3。此外，区块链技术还用于确保医疗数据的安全性。
Tactile edge technology that focuses on 5G or beyond 5G reveals an exciting approach to control infectious diseases such as COVID-19 internationally. The control of epidemics such as COVID-19 can be managed effectively by exploiting edge computation through the 5G wireless connectivity network. The implementation of a hierarchical edge computing system provides many advantages, such as low latency, scalability, and the protection of application and training model data, enabling COVID-19 to be evaluated by a dependable local edge server. In addition, many deep learning (DL) algorithms suffer from two crucial disadvantages: first, training requires a large COVID-19 dataset consisting of various aspects, which will pose challenges for local councils; second, to acknowledge the outcome, the findings of deep learning require ethical acceptance and clarification by the health care sector, as well as other contributors. In this article, we propose a B5G framework that utilizes the 5G network's low-latency, high-bandwidth functionality to detect COVID-19 using chest X-ray or CT scan images, and to develop a mass surveillance system to monitor social distancing, mask wearing, and body temperature. Three DL models, ResNet50, Deep tree, and Inception v3, are investigated in the proposed framework. Furthermore, blockchain technology is also used to ensure the security of healthcare data.