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

RAPID：用于 COVID-19 数据收集的声学通信和传感

基本信息

批准号：
2028547
负责人：
Ness Shroff
金额：
$ 10万
依托单位：
Ohio State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-15 至 2022-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028547&HistoricalAwards=false
关键词：
RAPID Acoustic Communications Sensing COVID

项目摘要

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.

新型冠状病毒（COVID-19）的爆发已成为一场重大国际危机，其影响已延伸到日常生活的各个方面。这导致了人员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，接触者追踪已成为让劳动力以安全可控的方式返回的宝贵工具。拟议项目旨在利用无处不在的移动设备，构建一个保护隐私的众感知系统，以实现有效的 COVID-19 跟踪和追踪。这项工作克服了基于基础设施的技术（例如视频监控系统等）的关键挑战，这些技术难以扩展并提供广泛的覆盖范围。这种方法使用独特的基于听不见的声学的通信系统来识别和监控与用户交互的人员。它仅使用日常手机传感器（即内置扬声器和麦克风）进行声音信号传输，以方便实施。该项目期间进行的研究将克服能源管理和功率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封闭环境，以及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。该系统将利用社交场合中人类互动的正常程序，并采用新颖的声学信号传播服务，选择性地在特定“地盘”内广播信息。遭遇的信息将自动或通过用户手动处理上传到中央服务器。中央服务器上的地图将相应更新。该解决方案将在以下几个方面保留许多理想的品质：（i）与蓝牙等竞争系统相比，手机上的声学信号的感知范围较小，但满足病毒检测的要求。事实上，与基于蓝牙的方法相比，此功能的误报率要低得多。短距离也有助于保护隐私。 (ii) 每个用户的唯一 ID（例如 WiFi 和蓝牙 MAC 地址）不会向其同行泄露。相反，仅公开随机生成的 ID。 (iii) 用户可以选择向中央服务器报告哪些信息，例如他们有/没有GPS的遭遇、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遭遇或在某些地点的遭遇。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

On the Accuracy of Measured Proximity of Bluetooth-Based Contact Tracing Apps

基于蓝牙的接触者追踪应用程序测量接近度的准确性

DOI：
10.1007/978-3-030-63086-7_4
发表时间：
2020-01
期刊：
International Conference on Security and Privacy in Communication Systems (SecureComm
影响因子：
0
作者：
Zhao, Qingchuan;Wen, Haohuang;Lin, Zhiqiang;Xuan, Dong;Shroff, Ness B.
通讯作者：
Shroff, Ness B.

A Blueprint for Effective Pandemic Mitigation

有效缓解流行病的蓝图