CPS: Breakthrough: Wearables With Feedback Control

最近，包括智能手表、表带、按钮和吊坠的智能可穿戴设备越来越多。这些设备中的许多是人在回路网络物理系统（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根本性进步，有很大的潜力来彻底改变许多CPS应用。可能的应用示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持工厂工人的安全，检测家中的活动以监测老年人，以及通过受控运动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感知、收集和呈现数据上。在CPS中使用时，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控制回路以及系统如何保持安全性的理解。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，它通过解决人在回路中的行为来扩展对可穿戴系统的理解和控制，它明确地关注环境和人类行为对网络的影响。新颖的想法提出了这些领域的每一个沿着与结构，为他们的整合。例如，使用可穿戴设备来支持更鲁棒、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，以及（v）动态时空弯曲。为了处理人在回路中的行为，模型预测控制（MPC）扩展到基于语义的MPC。这解决了不服从机电定律的控制问题，并采用了机器学习。许多CPS项目没有明确解决不确定的世界如何影响网络必须如何开发，以便稳健和安全地执行。一个新的 * 感知软件开发范式专注于物理-网络CPS问题作为中心原则，并作为所有拟议工作的集成平台。*-aware范式关注的是，在满足安全性和适应性需求的同时，如何使软件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