CPS: TTP Option: Synergy: Collaborative Research: The Science of Activity-Predictive Cyber-Physical Systems (APCPS)

CPS：TTP 选项：协同：协作研究：活动预测网络物理系统 (APCPS) 的科学

• 批准号: 1543656
• 负责人: Diane Cook
• 金额: $ 110万
• 依托单位: Washington State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1543656&HistoricalAwards=false
• 关键词: CPS; TTP; Option; Synergy; Collaborative

This project aims to design algorithmic techniques to perform activity discovery, recognition, and prediction from sensor data. These techniques will form the foundation for the science of Activity- Prediction Cyber-Physical Systems, including potential improvement in the responsiveness and adaptiveness of the systems. The outcome of this work is also anticipated to have important implications in the specific application areas of health care and sustainability, two priority areas of societal importance. The first application will allow for health interventions to be provided that adapt to an individual's daily routine and operate in that person's everyday environment. The second application will offer concrete tools for building automation that improve sustainability without disrupting an individual's current or upcoming activities. The project investigators will leverage existing training programs to involve students from underrepresented groups in this research. Bi-annual tours and a museum exhibit will reach K-12 teachers, students and visitors, and ongoing commercialization efforts will ensure that the designed technologies are made available for the public to use.Deploying activity-predictive cyber-physical systems "in the wild" requires a number of robust computational components for activity learning, knowledge transfer, and human-in- the-loop computing that are introduced as part of this project. These components then create cyber physical systems that funnel information from a sensed environment (the physical setting as well as humans in the environment), to activity models in the cloud, to mobile device interfaces, to the smart grid, and then back to the environment. The proposed research centers on defining the science of activity-predictive cyber-physical systems, organized around the following thrusts: (1) the design of scalable and generalizable algorithms for activity discovery, recognition, and prediction; (2) the design of transfer learning methods to increase the the ability to generalize activity-predictive cyber-physical systems; (3) the design of human-in-the-loop computing methods to increase the sensitivity of activity-predictive cyber-physical systems; (4) the introduction of evaluation metrics for activity-predictive cyber-physical systems; and (5) transition of activity-predictive cyber-physical systems to practical applications including health monitoring/intervention and smart/sustainable cities.

该项目旨在设计算法技术，以从传感器数据中执行活动发现，识别和预测。这些技术将构成活动预测网络物理系统科学的基础，包括潜在的改善系统的响应能力和适应性。预计这项工作的结果还会在医疗保健和可持续性的特定应用领域（社会重要性的两个优先领域）具有重要意义。第一个申请将允许提供适应个人日常工作并在该人的日常环境中运作的健康干预措施。第二个应用程序将提供建立自动化的具体工具，可改善可持续性，而不会破坏个人的当前或即将进行的活动。项目调查人员将利用现有的培训计划，使来自代表性不足小组的学生参与这项研究。两年一次的游览和博物馆展览将吸引K-12的老师，学生和访客，并且正在进行的商业化工作将确保为公众提供设计的技术，以预测性预测性的网络物理系统“在野外”需要进行许多可靠的计算成分，以进行许多可靠的计算成分，以进行活动，知识传输，并介绍了该项目，以介绍了该项目，以介绍该项目。然后，这些组件创建了网络物理系统，这些系统将信息从感知的环境（物理环境以及环境中的人类），到云中的活动模型，移动设备接口，智能电网，然后返回环境。拟议的研究集中在定义活动预测性的网络物理系统科学的中心，该系统围绕以下推力组织：（1）设计，可伸缩且可推广的活动算法，以发现活动发现，识别和预测； （2）转移学习方法的设计，以提高推广活动预测性网络物理系统的能力； （3）设计人类计算方法的设计，以提高活动预测性网络物理系统的灵敏度； （4）引入活动预测性网络物理系统的评估指标； （5）将活动预测的网络物理系统转变为实际应用，包括健康监测/干预和智能/可持续城市。

项目成果

Fall detection in smart home sensors using UWB sensors and unsupervised change detection

使用 UWB 传感器和无监督变化检测的智能家居传感器中的跌倒检测

• 发表时间: 2018
• 期刊: Journal of Reliable Intelligent Environments
• 作者: Mokhtari, A;Aminikhanghahi, S;Zhang, Q;Cook, Diane J
• 通讯作者: Cook, Diane J

Design of a smart home-driven digital memory notebook to support self-management of activities for older adults

设计智能家居驱动的数字记忆笔记本，支持老年人的活动自我管理

• 发表时间: 2018
• 期刊: Gerontechnology
• 作者: Dahmen, J;Minor, B;Cook, D J;Schmitter-Edgecombe, M
• 通讯作者: Schmitter-Edgecombe, M

Using smart offices to predict occupational stress

• DOI: 10.1016/j.ergon.2018.04.005
• 发表时间: 2018-09-01
• 期刊: INTERNATIONAL JOURNAL OF INDUSTRIAL ERGONOMICS
• 影响因子: 3.1
• 作者: Alberd, Ane;Aztiria, Asier;Cook, Diane J.
• 通讯作者: Cook, Diane J.

Technology-Enabled Assessment of Functional Health

• DOI: 10.1109/rbme.2018.2851500
• 发表时间: 2019-01-01
• 期刊: IEEE REVIEWS IN BIOMEDICAL ENGINEERING
• 影响因子: 17.6
• 作者: Cook, Diane J.;Schmitter-Edgecombe, Maureen;Morant, Anne, V
• 通讯作者: Morant, Anne, V