CNS Core: Small: Towards Ubiquitous Sensing With Commodity Wi-Fi

CNS 核心：小型：利用商用 Wi-Fi 实现无处不在的传感

• 批准号: 1910519
• 负责人: Jie Yang
• 金额: $ 45.87万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910519&HistoricalAwards=false
• 关键词: CNS; Core; Small; Towards; Ubiquitous

The prevalence of Wi-Fi devices and ubiquitous coverage of Wi-Fi networks provide the opportunity to extend Wi-Fi's capabilities beyond communication, particularly in human sensing. As Wi-Fi signals travel through space, they modulate with the human body and undergo wave phenomena such as reflection and diffraction, which carry a rich set of information about the physical environment including human activities and gestures. This project aims to reuse commodity Wi-Fi devices to capture such wave phenomena to sense multiple persons simultaneously and to provide quantifiable gesture recognition. Exploiting commodity Wi-Fi devices for human sensing enables ubiquitous sensing for easy and large-scale deployments without requiring users to wear or install any specialized sensors. The outcome of this project can be directly adopted by industry and will have a societal impact by facilitating a variety of applications such as Human-Computer Interaction, smart home, mobile healthcare, and security surveillance. This project will lead to new technologies for human sensing and provide new insights on developing emerging mobile applications. The research activities will be integrated into Florida State University's Computer Science education program and will include curriculum development, female and minority students involvement, and K-12 education and industry outreach.This project focuses on building a commodity Wi-Fi based ubiquitous sensing system that can simultaneously sense multiple persons and provides quantifiable gesture recognition without requiring environment-dependent training. The proposed work enables multiple people tracking and activity recognition by extracting the signal reflections from each individual person based on fine-grained signal reflection paths. The periodical change of the reflection signal is further exploited to derive quantitative measures such as the movement distance and speed for quantifiable gesture recognition. Moreover, the motion-induced Doppler effects that reflect the signal dynamic due to human body movements are leveraged to perform environment-independent sensing. Next, it applies the proposed sensing technologies to develop human-computer-interface applications by considering issues such as environmental interferences. In addition, the project expands the Wi-Fi sensing capabilities from human sensing to sensing bio-information of fruit crops. It leverages the frequency diversity to capture the physiological changes of fruit due to ripening and develops mechanisms to extract multipath-independent features for ripeness detection. Finally, the system will be evaluated using real-scale test-beds. The techniques, algorithms, and software resulting from this research will deepen our understanding of mobile sensing and provide practical value by enabling emerging applications.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.

Wi-Fi设备的普及和Wi-Fi网络的无处不在的覆盖提供了将Wi-Fi的能力扩展到通信之外的机会，特别是在人类感知方面。当Wi-Fi信号在太空中传播时，它们会随着人体进行调制，并经历反射和衍射等波动现象，这些波动现象携带着有关物理环境的丰富信息，包括人类活动和手势。该项目旨在重复使用商用Wi-Fi设备来捕捉这种波现象，以同时感知多个人并提供可量化的手势识别。利用商用Wi-Fi设备进行人体感知，可以实现无处不在的感知，从而实现简单的大规模部署，而无需用户佩戴或安装任何专用传感器。该项目的成果可以直接被行业采用，并将通过促进人机交互、智能家居、移动的医疗保健和安全监控等各种应用产生社会影响。该项目将为人类感知带来新技术，并为开发新兴的移动的应用提供新的见解。该研究活动将被整合到佛罗里达州立大学的计算机科学教育计划中，并将包括课程开发，女性和少数民族学生的参与，以及K-12教育和行业推广。该项目的重点是建立一个基于商品Wi-Fi的无处不在的传感系统，该系统可以同时感知多个人，并提供可量化的手势识别，而不需要依赖于环境的培训。所提出的工作，使多人跟踪和活动识别提取的信号反射从每个人的基础上细粒度的信号反射路径。进一步利用反射信号的周期性变化来导出定量测量，诸如用于可量化手势识别的移动距离和速度。此外，运动引起的多普勒效应，反映了由于人体运动的信号动态被利用来执行与环境无关的感测。接下来，它应用所提出的传感技术开发人机界面应用程序，考虑环境干扰等问题。此外，该项目还将Wi-Fi传感能力从人类传感扩展到水果作物的生物信息传感。它利用频率的多样性，以捕捉由于成熟的水果的生理变化，并开发机制，以提取多路径独立的功能，成熟度检测。最后，该系统将使用实际规模的测试台进行评估。这项研究的技术、算法和软件将加深我们对移动的传感的理解，并通过支持新兴应用提供实用价值。该奖项反映了NSF的法定使命，并通过使用基金会的知识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

Person Re-identification in 3D Space: A WiFi Vision-based Approach

• 发表时间: 2023
• 作者: Ren;J. Yang

Liquid Level Sensing Using Commodity WiFi in a Smart Home Environment

• DOI: 10.1145/3380996
• 发表时间: 2020-03
• 期刊: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
• 作者: Yili Ren;Sheng Tan;Linghan Zhang;Zi Wang;Zhi Wang;J. Yang

Winect: 3D Human Pose Tracking for Free-form Activity Using Commodity WiFi

• DOI: 10.1145/3494973
• 发表时间: 2021
• 期刊: Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.
• 作者: Yili Ren;Z. Wang;Sheng Tan;Yingying Chen;Jie Yang

Tracking free-form activity using wifi signals

• DOI: 10.1145/3447993.3482857
• 发表时间: 2021-10
• 期刊: Proceedings of the 27th Annual International Conference on Mobile Computing and Networking
• 作者: Yili Ren;Zi Wang;Sheng Tan;Yingying Chen;Jie Yang

Commodity WiFi Sensing in Ten Years: Status, Challenges, and Opportunities

• DOI: 10.1109/jiot.2022.3164569
• 发表时间: 2022-09
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Sheng Tan;J. Yang