CAREER: Structures as Sensors: Elder Activity Level Monitoring through Structural Vibrations

职业：结构作为传感器：通过结构振动监测老年人的活动水平

• 批准号: 1653550
• 负责人: Hae Young Noh
• 金额: $ 50万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1653550&HistoricalAwards=false
• 关键词: CAREER; Structures; Sensors; Elder; Activity

The goal of this Faculty Early Career Development Program (CAREER) project is to enable "smart buildings" that can locate and identify specific individuals, and classify their activity, based only on the vibrations of the building structure caused by footsteps. Elder care facilities aim to maintain or improve the quality of life and independence of elders while reducing costs and capacity needs for care-professionals. One key to achieving this goal is to understand the activities of each occupant. Existing solutions to monitor occupants, such as vision, acoustic, motion, and force sensors and mobile devices, have strict installation requirements. These requirements lead to intrusive and dense deployment or require active user involvements. Instead, this project is built upon sensing the vibrations created by occupants' during their walking activity. Using building vibration to monitor occupants allows non-intrusive and scalable monitoring with inexpensive vibration sensors. More generally, this research will enable smart buildings to sense, track, and predict the status of occupants in a maintainable way using "structures as sensors" and thus enable future occupant-aware applications. Similarly, the technology can locate portions of a building with slippery or unsafe footing, or detect the presence of unauthorized people in restricted areas. By tracking first responders and locating imperiled civilians, such systems will also help dispatchers to mitigate emergencies. The project includes proof-of-concept deployments in three different elder care facilities. Targeted outreach activities will highlight the capabilities of this technology at an appropriate level of detail to appeal to female middle-school students.This project uses structures themselves as activity sensors, by passively sensing footstep-induced floor vibrations, and employing advanced sparse-signal approximation in a Bayesian framework, to extract individual activity information. The specific research thrusts are: (1) extracting individual persons' footstep-induced floor vibration signal from a noisy signal mixture due to multiple human sources, by exploiting hierarchical wavelet decompositions and applying structured sparsity regularization; (2) localizing individual footsteps by dynamically fusing information from multiple frequency components and leveraging human mobility and structural vibration patterns through Bayesian updating; and (3) improving model accuracy by iteratively fusing location information and signal separation. The key novelty in these thrusts lies in fusion of signal processing methods and physical constraints to address real world challenges.

该学院早期职业发展计划(Career)项目的目标是使能够定位和识别特定个人并对他们的活动进行分类的智能建筑，仅基于脚步引起的建筑结构的振动。老年护理设施旨在维持或改善老年人的生活质量和独立性，同时降低护理专业人员的成本和能力需求。实现这一目标的一个关键是了解每个居住者的活动。现有的监控乘员的解决方案，如视觉、声学、运动和力传感器以及移动设备，都有严格的安装要求。这些要求会导致侵入性和密集部署，或者需要活跃的用户参与。相反，这个项目是建立在感知乘客在步行活动中产生的振动的基础上的。使用建筑物振动监测居住者，可以使用廉价的振动传感器进行非侵入性和可扩展的监测。更广泛地说，这项研究将使智能建筑能够以一种可维护的方式感知、跟踪和预测居住者的状态，从而使未来的居住者感知应用成为可能。同样，这项技术可以定位建筑物基础湿滑或不安全的部分，或者检测到限制区域内未经授权的人的存在。通过跟踪急救人员和定位受威胁的平民，这类系统还将帮助调度员缓解紧急情况。该项目包括在三个不同的老年护理设施进行概念验证部署。有针对性的外展活动将以适当的细节水平突出这项技术的能力，以吸引女中学生。该项目使用结构本身作为活动传感器，通过被动感知足迹引起的地板振动，并在贝叶斯框架中使用先进的稀疏信号近似，以提取个人活动信息。具体的研究内容包括：(1)利用分层小波分解和结构化稀疏正则化方法，从多个人的噪声混合信号中提取人体脚步引起的地板振动信号；(2)通过动态融合多个频率分量的信息来定位个人脚步，并通过贝叶斯更新利用人的流动性和结构振动模式；(3)通过迭代融合位置信息和信号分离来提高模型精度。这些推力的关键新颖性在于融合了信号处理方法和物理约束，以应对现实世界的挑战。

项目成果

Smart Home Occupant Identification via Sensor Fusion Across On-Object Devices

• DOI: 10.1145/3218584
• 发表时间: 2018-12
• 期刊: ACM Transactions on Sensor Networks (TOSN)
• 作者: Jun Han;Shijia Pan;M. K. Sinha;H. Noh;Pei Zhang;P. Tague

A window-based sequence-to-one approach with dynamic voting for nurse care activity recognition using acceleration-based wearable sensor

一种基于窗口的序列对一方法，使用基于加速度的可穿戴传感器进行护士护理活动识别的动态投票

• DOI: 10.1145/3410530.3414336
• 发表时间: 2020
• 期刊: In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
• 作者: Dong, Yiwen;Liu, Jingxiao;Gao, Yitao;Sarkar, Sulagna;Hu, Zhizhang;Fagert, Jonathon;Pan, Shijia;Zhang, Pei;Noh, Hae Young;Mirshekari, Mostafa
• 通讯作者: Mirshekari, Mostafa

Occupant localization using footstep-induced structural vibration

• DOI: 10.1016/j.ymssp.2018.04.026
• 发表时间: 2018-11-01
• 期刊: MECHANICAL SYSTEMS AND SIGNAL PROCESSING
• 影响因子: 8.4
• 作者: Mirshekari, Mostafa;Pan, Shijia;Noh, Hae Young
• 通讯作者: Noh, Hae Young

Characterizing human activity induced impulse and slip-pulse excitations through structural vibration

• DOI: 10.1016/j.jsv.2017.10.034
• 发表时间: 2018-02
• 期刊: Journal of Sound and Vibration
• 影响因子: 4.7
• 作者: Shijia Pan;Mostafa Mirshekari;Jonathon Fagert;C. G. Ramirez;Albert Jin Chung;C. C. Hu-C.;John Paul Shen;Pei Zhang;H. Noh

Device-free Multiple People Localization through Floor Vibration

• DOI: 10.1145/3360773.3360887
• 发表时间: 2019-11
• 期刊: Proceedings of the 1st ACM International Workshop on Device-Free Human Sensing
• 作者: Laixi Shi;Mostafa Mirshekari;Jonathon Fagert;Yuejie Chi;H. Noh;Pei Zhang;Shijia Pan