As a worldwide pandemic, the coronavirus disease-19 (COVID-19) has caused serious restrictions in people's social life, along with the loss of lives, the collapse of economies and the disruption of humanitarian aids. Despite the advance of technological developments, we, as researchers, have witnessed that several issues need further investigation for a better response to a pandemic outbreak. With this motivation, researchers recently started developing ideas to stop or at least reduce the spread of the pandemic. While there have been some prior works on wireless networks for combating a pandemic scenario, vehicular networks and their potential bottlenecks have not yet been fully examined. This article provides an extensive discussion on vehicular networking for combating a pandemic. We provide the major applications of vehicular networking for combating COVID-19 in public transportation, in-vehicle diagnosis, border patrol and social distance monitoring. Next, we identify the unique characteristics of the collected data in terms of privacy, flexibility and coverage, then highlight corresponding future directions in privacy preservation, resource allocation, data caching and data routing. We believe that this work paves the way for the development of new products and algorithms that can facilitate the social life and help controlling the spread of the pandemic.
翻译:作为全球范围的流行病,Corona病毒19(COVID-19)对人们的社会生活造成严重限制,造成生命损失、经济崩溃和人道主义援助中断。尽管技术发展取得了进展,我们作为研究人员已经看到,有几个问题需要进一步调查,以更好地应对大流行病的爆发。借助这一动机,研究人员最近开始提出停止或至少减少该大流行病蔓延的想法。虽然以前曾就无线网络进行过一些工作,以防止大流行病的发生,但车辆网络及其潜在的瓶颈尚未得到充分研究。本文章就抗击大流行病的车辆联网问题进行了广泛的讨论。我们提供了在公共交通、车辆诊断、边境巡逻和社会距离监测方面打击COVID-19的车辆联网的主要应用。接下来,我们从隐私、灵活性和覆盖范围方面确定了所收集的数据的独特性,然后强调了隐私保护、资源分配、数据储存和数据流转方面相应的未来方向。我们认为,这项工作为开发新的产品和算法铺平了道路,这些产品和算法可以促进大流行病的传播。