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:
- 金额:$ 10万
- 依托单位:
- 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:
- 关键词:
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.
新颖的冠状病毒(Covid-19)的爆发是作为一次重大国际危机展开,其影响力扩大到日常生活的各个方面。这导致了毁灭性的人类生命以及国家的经济福祉。随着美国各州开始重新启动其经济体,接触追踪已成为允许劳动力以安全和控制的方式返回的宝贵工具。拟议的项目旨在通过利用移动设备的普遍性来建立一个有效的Covid-19跟踪和跟踪的众包系统。这项工作克服了基于基础架构的技术(例如视频监视系统等)的关键挑战,这些技术难以扩展并提供广泛的覆盖范围。这种方法使用一种独特的基于听觉的通信系统来识别和监视与用户与之互动的人。它仅使用每天的声学信号传输,每天的手机传感器(即内置的扬声器和麦克风)来促进易于实现。 该项目期间进行的研究将克服能源管理和电力控制方面的关键挑战,以延长电池寿命,以应对手机可能放在口袋或钱包中的封闭环境,并检测用户之间的身体互动,从而对特定的特定研究领域本身做出基本贡献。该系统将利用社会互动的背景下的人类互动的正常程序,并适应一种新颖的声学信号传播服务,该服务在特定的“草皮”中有选择地广播信息。相遇的信息将自动或使用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维度中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传感范围很小,但符合病毒检测的要求。实际上,与基于蓝牙的方法相比,此功能使误报要少得多。短范围也有助于隐私。 (ii)每个用户的唯一ID,例如WiFi和Bluetooth MAC地址,不会向其同行遇到。相反,仅披露随机生成的ID。 (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.
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
- DOI:10.1007/978-3-030-63086-7_4
- 发表时间:2020-01-01
- 期刊:
- 影响因子:0
- 作者:Qingchuan Zhao;Haohuang Wen;Shroff, Ness
- 通讯作者:Shroff, Ness
A Study of the Privacy of COVID-19 Contact Tracing Apps
- DOI:10.1007/978-3-030-63086-7_17
- 发表时间:2020-01-01
- 期刊:
- 影响因子:0
- 作者:Wen, Haohuang;Zhao, Qingchuan;Shroff, Ness
- 通讯作者:Shroff, Ness
A Blueprint for Effective Pandemic Mitigation
有效缓解流行病的蓝图
- DOI:
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Singh, Rahul;Ren, Wenbo;Liu, Fang;Xuan, Dong;Lin, Zhiqiang;Shroff, Ness B.
- 通讯作者:Shroff, Ness B.
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Ness Shroff其他文献
Ness Shroff的其他文献
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{{ truncateString('Ness Shroff', 18)}}的其他基金
Collaborative Research: NeTS: Medium: Black-box Optimization of White-box Networks: Online Learning for Autonomous Resource Management in NextG Wireless Networks
合作研究:NeTS:中:白盒网络的黑盒优化:下一代无线网络中自主资源管理的在线学习
- 批准号:
2312836 - 财政年份:2023
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE)
未来边缘网络和分布式智能人工智能研究所 (AI-EDGE)
- 批准号:
2112471 - 财政年份:2021
- 资助金额:
$ 10万 - 项目类别:
Cooperative Agreement
Collaborative Research: CNS Core: Medium: Analytics and Online Optimization at Scale for Cellular Networks
合作研究:CNS 核心:中:蜂窝网络大规模分析和在线优化
- 批准号:
2106933 - 财政年份:2021
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: Information Freshness in Scalable and Energy Constrained Machine to Machine Wireless Networks
合作研究:CNS 核心:中:可扩展且能量受限的机器对机器无线网络中的信息新鲜度
- 批准号:
2106932 - 财政年份:2021
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
Collaborative Research: CNS Core: Medium: Combating Latency and Disconnectivity in mmWave Networks: From Theory to Implementation
合作研究:CNS 核心:中:对抗毫米波网络中的延迟和断开连接:从理论到实施
- 批准号:
1955535 - 财政年份:2020
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
CNS Core: Small: New Caching Paradigms for Distributed and Dynamic Networks
CNS 核心:小型:分布式和动态网络的新缓存范例
- 批准号:
2007231 - 财政年份:2020
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
CNS Core: Medium: Collaborative: Exploring and Exploiting Learning for Efficient Network Control: Non-Stationarity, Inter-Dependence, and Domain-Knowledge
CNS 核心:中:协作:探索和利用学习实现高效网络控制:非平稳性、相互依赖和领域知识
- 批准号:
1901057 - 财政年份:2019
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
ICN-WEN: Collaborative Research: SPLICE: Secure Predictive Low-Latency Information Centric Edge for Next Generation Wireless Networks
ICN-WEN:协作研究:SPLICE:下一代无线网络的安全预测低延迟信息中心边缘
- 批准号:
1719371 - 财政年份:2017
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
CSR: NeTS: Small: Theoretical Foundations for Cache Networks: Performance Models, Algorithms, and Applications
CSR:NeTS:小型:缓存网络的理论基础:性能模型、算法和应用
- 批准号:
1717060 - 财政年份:2017
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
NeTS: Large: Collaborative Research: Practical Foundations for Networking with Many-Antenna Base Stations
NetS:大型:协作研究:多天线基站联网的实用基础
- 批准号:
1518829 - 财政年份:2015
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
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