CPS: Breakthrough: Wearables With Feedback Control

最近有越来越多的智能可穿戴设备，包括智能手表、手环、纽扣和吊坠。这些设备中的许多都是人在环网络物理系统（CPS）的一部分。随着这些能源和资源有限的设备在通信、控制和计算交叉领域的未来基本进展，许多CPS应用具有革命性的巨大潜力。可能的应用实例包括检测和控制洗手以防止感染或细菌的传播，监测和使用干预措施以保证工厂工人的安全，检测用于监测老年人的家庭活动，以及通过有控制的锻炼改善中风患者的康复。然而，到目前为止，可穿戴设备的大部分工作都集中在传感、收集和呈现数据上。为了在CPS中使用，有必要考虑增加使用新的传感模式，应用反馈来关闭控制回路，并关注环境和人类行为如何影响网络的基本问题。特别是，由于人类与可穿戴设备密切相关，因此有必要增加对人类行为如何影响和可能受到控制回路的影响以及系统如何保持安全的理解。这项工作开发了用于处理智能可穿戴数据的通用底层算法，而不是一次性解决方案，它通过解决人在环行为扩展了对可穿戴系统的理解和控制，并明确关注环境和人类行为对网络的影响。针对这些领域提出了新颖的想法，并为它们的整合提供了一个结构。例如，使用可穿戴设备支持更稳健、准确和高效的活动识别的算法方法基于五个基本概念：(i)方向不可知建模，（ii）方向感知建模，（iii）空间可达性，（iv）时空分割，(v)动态时空扭曲。为了处理人在环行为，将模型预测控制（MPC）扩展为基于语义的模型预测控制。这解决了不符合机电定律的控制问题，并采用了机器学习。许多CPS项目并没有明确地解决不确定的世界如何影响网络的发展，以实现稳健和安全的运行。一种新的*感知软件开发范式将物理-网络CPS问题作为中心原则，并作为所有建议工作的集成平台。感知范式关注的是如何使软件在满足安全性和适应性需求的同时，健壮地处理物理世界

Recently there is an increasing availability of smart wearables including smart watches, bands, buttons and pendants. Many of these devices are part of human-in-the-loop Cyber Physical Systems (CPS). With future fundamental advances in the intersection of communications, control, and computation for these energy and resource limited devices, there is a great potential to revolutionize many CPS applications. Examples of possible applications include detecting and controlling hand washing to prevent transmission of infections or bacteria, monitoring and using interventions to keep factory workers safe, detecting activities in the home for monitoring the elderly, and improving rehabilitation of stroke victims via controlled exercises. However, to date, much of the work on wearables concentrates on only sensing, collecting and presenting data. For use in CPS it is necessary to consider the increased use of new sensing modalities, to apply feedback to close the control loop, and to focus on the fundamental issues of how both the environment and human behavior affect the cyber. In particular, since humans are intimately involved with wearables it is necessary to increase understanding of how human behaviors affect and can be affected by the control loops and how the systems can maintain safety.This work develops generic underlying algorithms for processing smart wearable data rather than one-off solutions, it extends the understanding and control of wearable systems by addressing humans-in-the-loop behaviors, and it explicitly focuses on the impact of the environment and human behavior on the cyber. Novel ideas are proposed for each of these areas along with a structure for their integration. For example, the algorithmic approach to support more robust, accurate and efficient activity recognition using wearable devices is based on five fundamental concepts: (i) Direction Agnostic Modeling, (ii) Direction Aware Modeling, (iii) Spatial Reachability, (iv) Spatiotemporal Segmentation, and (v) Dynamic Space Time Warping. For dealing with humans-in the-loop behaviors, Model Predictive Control (MPC) is extended to semantic based MPC. This solves control problems that are not amenable to electromechanical laws and employs machine learning. Many CPS projects do not explicitly address how the uncertain world affects how the cyber must be developed in order to perform robustly and safely. A new *-aware software development paradigm focuses on physical-cyber CPS issues as central tenets and that serves as an integrating platform for all the proposed work. The *-aware paradigm focuses on how software must be made robust to handle the physical world, while meeting safety and adaptability requirements