论文标题
COVID-19跟踪中的联系人分类
Contact Classification in COVID-19 Tracing
论文作者
论文摘要
本文解决了使用Covid-19 Tracing应用程序可靠地识别关键联系的任务。可靠的分类对于确保高水平的保护至关重要，同时又可以防止许多人被应用程序送往隔离。跟踪应用程序基于当前智能手机的功能，可实现最广泛的可能可用性。智能手机的现有功能包括交换蓝牙低能（BLE）信号和音频信号，以及陀螺仪和磁传感器的使用。当今经常使用的蓝牙功率测量值可能会通过未来的音频范围和态度估计来补充。智能手机通常以不同的方式佩戴，通常是在口袋和袋子中，这使信号传播，因此分类是不可预测的。依靠用户的合作来戴上手机从脖子上挂着，这会大大改变这种情况。在这种情况下，通过BLE和音频测量可以实现的性能是可以预测的。我们的分析确定了至少在模型有效性范围内导致准确警告的参数。然后，应用程序可以大大减少疾病的传播，而不会导致许多人过度去隔离。本文是三篇论文中的第一篇，详细分析了情况。
The present paper addresses the task of reliably identifying critical contacts by using COVID-19 tracing apps. A reliable classification is crucial to ensure a high level of protection, and at the same time to prevent many people from being sent to quarantine by the app. Tracing apps are based on the capabilities of current smartphones to enable a broadest possible availability. Existing capabilities of smartphones include the exchange of Bluetooth Low Energy (BLE) signals and of audio signals, as well as the use of gyroscopes and magnetic sensors. The Bluetooth power measurements, which are often used today, may be complemented by audio ranging and attitude estimation in the future. Smartphones are worn in different ways, often in pockets and bags, which makes the propagation of signals and thus the classification rather unpredictable. Relying on the cooperation of users to wear their phones hanging from their neck would change the situation considerably. In this case the performance, achievable with BLE and audio measurements, becomes predictable. Our analysis identifies parameters that result in accurate warnings, at least within the scope of validity of the models. A significant reduction of the spreading of the disease can then be achieved by the apps, without causing many people to unduly go to quarantine. The present paper is the first of three papers which analyze the situation in some detail.
