RAPID: Acoustic Communications and Sensing for COVID-19 Data Collection

新型冠状病毒(新冠肺炎)的爆发已成为一场重大的国际危机，其影响已延伸到日常生活的方方面面。这导致了人类生命和国家经济福祉的毁灭性损失。随着美国各州开始重启经济，接触者追踪已成为一种宝贵的工具，使劳动力能够以安全和受控的方式返回。拟议的项目旨在通过利用移动设备的无处不在的优势，为有效的新冠肺炎跟踪和追踪建立一个保护隐私的众感系统。这项工作克服了视频监控系统等基于基础设施的技术的关键挑战，这些技术难以扩展和提供广泛的覆盖。该方法使用独特的基于不可听声学的通信系统来识别和监视用户与之交互的人。它只使用日常移动电话传感器(即内置扬声器和麦克风)的声学信号传输，以便于实施。在该项目期间进行的研究将克服能源管理和电源控制方面的关键挑战，以延长电池寿命，处理手机可能放在口袋或钱包中的遮挡环境，并检测用户之间的物理交互，从而为特定领域的研究领域本身做出基础性贡献。该系统将在社会接触的背景下利用人类互动的正常程序，并调整一种新的声音信号传播服务，该服务在特定的“地盘”内选择性地广播信息。这些遭遇的信息将自动或通过用户手动处理上载到中央服务器。中央服务器上的地图将相应更新。该解决方案将在以下方面保留一些理想的特性：(I)与蓝牙等竞争系统相比，移动电话上的声音信号的检测范围较小，但满足病毒检测的要求。事实上，这一功能实现的误报比基于蓝牙的方法要少得多。短距离还有助于保护隐私。(Ii)每个用户的唯一ID，如WiFi和蓝牙MAC地址，不会泄露给他们的同行。相反，只有随机生成的ID被披露。(Iii)用户可以选择向中央服务器报告哪些信息，例如，他们与GPS的接触、他们的医疗状况、年龄、真实身份等。他们也可以选择不报告某些地点的某些遭遇或遭遇。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The outbreak of the novel coronavirus (COVID-19) has unfolded as a major international crisis whose influence has extended to every aspect of daily life. This has led to a devastating loss of human life as well as the nation's economic well-being. As various US states begin to restart their economies, contact tracing has become an invaluable tool in allowing the workforce to return in a safe and controlled manner. The proposed project aims to build a privacy-preserving crowdsensing system for effective COVID-19 tracking and tracing by leveraging the ubiquity of mobile devices. This work overcomes key challenges of infrastructure-based techniques such as video monitoring systems, etc., that are difficult to scale and provide broad coverage. This approach uses a unique inaudible acoustic based communication system to identify and monitor persons with whom users have interacted with. It uses only acoustic signal transmission with every day mobile phone sensors (i.e., inbuilt speakers and microphones) to facilitate easy implementation. The research conducted during this project will overcome key challenges in energy management and power control to prolong battery life, dealing with an occluded environment where the phone may be in a pocket or a purse, and detecting physical interactions between users, thus making fundamental contributions to domain specific research areas themselves. The system will leverage the normal procedure of human interactions in the context of social encounters and adapt a novel acoustic signals dissemination service that selectively broadcasts information within particular "turfs". The encounters' information will be uploaded to a central server either automatically or with users' manual processing. The map at the central server will be updated accordingly. The solution will preserve a number of desirable qualities in the following dimensions: (i) The sensing range of acoustic signals on mobile phones is small compared with competing systems such as Bluetooth, but meets the requirements on virus detection. In fact, this feature enables far less false positives than Bluetooth based approaches. The short range also helps with privacy. (ii) Each user's unique ID such as WiFi and Bluetooth MAC addresses would not be disclosed to their peer encounters. Instead, only randomly generated IDs are disclosed. (iii) Users can choose what information to report to the central server, e.g., their encounters with/without GPS, their medical condition, age, real ID, etc. They could also choose not to report certain encounters or encounters at certain locations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.