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

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的功能扩展到通信之外的机会，特别是在人类感知方面。当Wi-Fi信号在太空中传输时，它们会与人体一起进行调制，并经历反射和绕射等波动现象，这些现象携带着关于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品Wi-Fi设备来捕捉这种波动现象，同时感知多个人，并提供可量化的手势识别。利用商用Wi-Fi设备进行人类感知使无所不在的感知成为可能，无需用户佩戴或安装任何专门的传感器，即可轻松大规模部署。该项目的成果可以直接被行业采用，并将通过促进各种应用程序产生社会影响，如人机交互、智能家居、移动医疗保健和安全监控。该项目将引领人类感知的新技术，并为开发新兴的移动应用程序提供新的见解。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项目中，将包括课程开发、女性和少数族裔学生参与、K-12教育和行业外展。该项目专注于建立一个基于商品Wi-Fi的泛在感知系统，该系统可以同时感知多个人，并提供可量化的手势识别，而不需要依赖环境的培训。该工作通过基于细粒度信号反射路径提取每个人的信号反射来实现多人跟踪和活动识别。进一步利用反射信号的周期性变化来推导出用于可量化手势识别的移动距离和速度等量化度量。此外，利用运动诱导的多普勒效应来执行与环境无关的传感，该效应反映了由于人体运动而产生的信号动态。接下来，它通过考虑环境干扰等问题，将建议的传感技术应用于开发人机界面应用程序。此外，该项目还将Wi-Fi传感能力从人类传感扩展到果树生物信息传感。它利用频率多样性来捕捉果实在成熟过程中的生理变化，并开发了提取多路径无关特征的机制来检测成熟度。最后，使用真实规模的试验台对该系统进行了评估。这项研究产生的技术、算法和软件将加深我们对移动传感的理解，并通过支持新兴应用程序提供实用价值。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 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.