【Author】
Muhammad, Ghulam; Alqahtani, Salman; Alelaiwi, Abdullah
【Abstract】The COVID-19 pandemic has had an unprecedented effect on the world. The pandemic has caused considerable death and suffering, triggered economic downturns, and led to significant job loss. Both during and after the pandemic, sophisticated and effective measures must be taken to diagnose COVID-19 patients and mitigate the effects of the virus. Emerging developments in the Internet of Things (IoT), 4G, 5G, and 6G wireless networks, artificial intelligence (AI), and blockchain technology can be harnessed to combat COVID-19. The implementation of IoT in hospitals enables highly integrated digital environments and real-time data collection, which can be utilized to identify clinical patterns, model risk interactions, and forecast effects via AI and deep learning systems. This article emphasizes the potential uses of IoT, AI, and 5G for combating pandemics similar to the COVID-19 pandemic. Then the authors propose a solution that uses federated learning and integrates these three technologies. Experiments were performed using cough sounds and chest X-ray images; the experiments yielded promising results.
【Keywords】COVID-19; Deep learning; Pandemics; 5G mobile communication; Wireless networks; Predictive models; Real-time systems
【标题】使用深度学习和 5G 通信对类似于 COVID-19 的疾病进行大流行管理
【摘要】COVID-19 大流行对世界产生了前所未有的影响。大流行已造成大量死亡和痛苦，引发经济衰退，并导致大量失业。在大流行期间和之后，必须采取复杂而有效的措施来诊断 COVID-19 患者并减轻病毒的影响。物联网 (IoT)、4G、5G 和 6G 无线网络、人工智能 (AI) 和区块链技术的新兴发展可用于对抗 COVID-19。医院物联网的实施实现了高度集成的数字环境和实时数据收集，可用于通过人工智能和深度学习系统识别临床模式、建模风险交互和预测效果。本文强调物联网、人工智能和 5G 在抗击类似于 COVID-19 大流行的流行病方面的潜在用途。然后作者提出了一个使用联邦学习并集成这三种技术的解决方案。使用咳嗽声和胸部 X 射线图像进行实验；实验产生了有希望的结果。
【关键词】新冠肺炎;深度学习；流行病； 5G移动通信；无线网络;预测模型；实时系统
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