In the United States, there is still a great disparity in medical care and most profoundly for emergency care, where limited facilities and remote location play a central role. Based on the Wessels Living History Farm report, the doctor to patient ratio in the United States is 30 to 10,000 in large metropolitan areas, only 5 to 10,000 in most rural areas; and the highest death rates are often found in the most rural counties. For emergency patient care, time to definitive treatment is critical. However, deciding the most effective care for an acute patient requires knowledge and experience. Though medical best practice guidelines exist and are in hospital handbooks, they are often lengthy and difficult to apply clinically. The challenges are exaggerated for doctors in rural areas and emergency medical technicians (EMT) during patient transport. This project's solution to transform emergency care at rural hospitals is to use innovative CPS technologies to help hospitals to improve their adherence to medical best practice. The key to assist medical staff with different levels of experience and skills to adhere to medical best practice is to transform required processes described in medical texts to an executable, adaptive, and distributed medical best practice guidance (EMBG) system. Compared to the computerized sepsis best practice protocol, the EMBG system faces a much bigger challenge as it has to adapt the best practice across rural hospitals, ambulances and center hospitals with different levels of staff expertise and equipment capabilities. Using a Global Positioning System analogy, a GPS leads drivers with different route familiarity to their destination through an optimal route based on the drivers' preferences, the EMBG system leads medical personnel to follow the best medical guideline path to provide emergency care and minimize the time to definitive treatment for acute patients. The project makes the following contributions: 1) The codification of complex medical knowledge is an important advancement in knowledge capture and representation; 2) Pathophysiological model driven communication in high speed ambulance advances life critical communication technology; and 3) Reduced complexity software architectures designed for formal verification bridges the gap between formal method research and system engineering.

Power systems have seen many changes over the last decade including the increased penetration of renewable generation, electric vehicles and new technologies for sensing, communication and control of a Smart Grid. The most significant impact of these changes are being felt at the consumer level. The ability for consumers and end devices to buy and sell energy and related services in a dynamic and interactive manner is expected to create a transactive energy market as highlighted in the Dec 2014 report of GridWise Alliance. Modeling and preparing the physical system to respond to the somewhat unpredictable behavior of active consumers over a cyber-infrastructure will be critical for maintaining grid reliability. Understanding the impact of such active consumers on the operational and business policies of the distribution utility requires advances in core system science that spans the areas of power engineering, economics, statistical signal processing, game theory, distributed control, multi-agent systems and cyber security. In conjunction with industrial partners, Westar Energy (the largest electric company in Kansas) and Kansas City Power and Light, the PIs plan to develop an architecture that requires little change to the existing investment in power distribution systems while allowing for the dynamic, adaptive control required to integrate active consumers with current and future combinations of high-variability distributed power sources, such as Photo-voltaic (PV) generators and storage batteries. In contrast to prior related efforts that primarily focus on demand response and distributed generation management with a single home/user centric approach, the proposed approach takes a holistic system perspective that includes cumulative modeling of multiple stochastic active consumers and the cyber infrastructure over which they may interact. Specific research thrusts include: (1) a general, extensible, and secure cyber architecture based on holonic multi-agent principles that provides a pathway to the emerging area of transactive energy market in power distribution systems, but also provides foundation for other engineered systems with active consumers; (2) new analytical insights into generalized stochastic modeling of consumer response to real]time price of electricity and the impact of such active consumers on grid reliability and security, and (3) novel methodology for comprehensive distributed control and management of power distribution systems with active consumers and high penetration of distributed renewable resources. Active consumers are an integral part of the Smart City vision where cyber systems are integrated into the transportation, energy, healthcare and biomedical, and critical infrastructure systems. Successful completion of this project will result in modeling, control, analysis and simulation architectures for all such active consumer driven CPS domains. The resulting gains in operating efficiency, economics, reliability and security will result in overall welfare for the society.

Computation is everywhere. Greeting cards have processors that play songs. Fireworks have processors for precisely timing their detonation. Computers are in engines, monitoring combustion and performance. They are in our homes, hospitals, offices, ovens, planes, trains, and automobiles. These computers, when networked, will form the Internet of Things (IoT). The resulting applications and services have the potential to be even more transformative than the World Wide Web. The security implications are enormous. Internet threats today steal credit cards. Internet threats tomorrow will disable home security systems, flood fields, and disrupt hospitals. The root problem is that these applications consist of software on tiny low-power devices and cloud servers, have difficult networking, and collect sensitive data that deserves strong cryptography, but usually written by developers who have expertise in none of these areas. The goal of the research is to make it possible for two developers to build a complete, secure, Internet of Things applications in three months. The research focuses on four important principles. The first is "distributed model view controller." A developer writes an application as a distributed pipeline of model-view-controller systems. A model specifies what data the application generates and stores, while a new abstraction called a transform specifies how data moves from one model to another. The second is "embedded-gateway-cloud." A common architecture dominates Internet of Things applications. Embedded devices communicate with a gateway over low-power wireless. The gateway processes data and communicates with cloud systems in the broader Internet. Focusing distributed model view controller on this dominant architecture constrains the problem sufficiently to make problems, such as system security, tractable. The third is "end-to-end security." Data emerges encrypted from embedded devices and can only be decrypted by end user applications. Servers can compute on encrypted data, and many parties can collaboratively compute results without learning the input. Analysis of the data processing pipeline allows the system and runtime to assert and verify security properties of the whole application. The final principle is "software-defined hardware." Because designing new embedded device hardware is time consuming, developers rely on general, overkill solutions and ignore the resulting security implications. The data processing pipeline can be compiled into a prototype hardware design and supporting software as well as test cases, diagnostics, and a debugging methodology for a developer to bring up the new device. These principles are grounded in Ravel, a software framework that the team collaborates on, jointly contributes to, and integrates into their courses and curricula on cyberphysical systems.

The wide-area measurement systems technology using Phasor Measurement Units (PMUs) has been regarded as the key to guaranteeing stability, reliability, state estimation, and control of next-generation power systems. However, with the exponentially increasing number of PMUs, and the resulting explosion in data volume, the design and deployment of an efficient wide-area communication and computing infrastructure is evolving as one of the greatest challenges to the power system and IT communities. The goal of this NSF CPS project is to address this challenge, and construct a massively deployable cyber-physical architecture for wide-area control that is fast, resilient and cost-optimal (FRESCO). The FRESCO grid will consist of a suite of optimal control algorithms for damping oscillations in power flows and voltages, implemented on top of a cost-effective and cyber-secure distributed computing infrastructure connected by high-speed wide-area networks that are dynamically programmable and reconfigurable. The value of constructing FRESCO is twofold (1) If a US-wide communication network capable of transporting gigabit volumes of PMU data for wide-area control indeed needs to be implemented over the next five years then power system operators must have a clear sense of how various forms of delays, packet losses, and security threats affect the stability of these control loops. (2) Moreover, such wide-area communication must be made economically feasible and sustainable via joint decision-making processes between participating utility companies, and testing how controls can play a potential role in facilitating such economics. Currently, there is very limited insight into how the PMU data transport protocols may lead to a variety of such delay patterns, or dictate the economic investments. FRESCO will answer all of these questions, starting from small prototypical grid models to those with tens of thousands of buses. Our eventual goal will be to make FRESCO fully open-source for Transition to Practice (TTP). We will work with two local software companies in Raleigh, namely Green Energy Corporation and Real-Time Innovations, Inc. to develop a scalable, secure middleware using Data-Distribution Service (DDS) technology. Thus, within the scope of the project, we also expect to enrich the state-of-the-art cloud computing and networking technologies with new control and management functions. From a technical perspective, FRESCO will answer three main research questions. First, can wide-area controllers be co-designed in sync with communication delays to make the closed-loop system resilient and delay-aware, rather than just delay-tolerant This is particularly important, as PMU data, in most practical scenarios, will have to be transported over a shared resource, sharing bandwidth with other ongoing applications, giving rise to not only transport delays, but also significant delays due to queuing and routing. Advanced ideas of arbitrated network control designs will be used to address this problem. The second question we address is for cost. Given that there are several participants in this wide-area control, how much is each participant willing to pay in sharing the network cost with others for the sake of supporting a system-wide control objective compared to its current practice of opting for selfish feedback control only Ideas from cooperative game theory will be used to investigate this problem. The final question addresses security how can one develop a scientific methodology to assess risks, and mitigate security attacks in wide-area control? Statistical and structural analysis of attack defense modes using Bayesian and Markov models, game theory, and discrete-event simulation will be used to address this issue. Experimental demos will be carried out using the DETER-WAMS network, showcasing the importance of cyber-innovation for the sustainability of energy infrastructures. Research results will be broadcast through journal publications, and jointly organized graduate courses between NCSU, MIT and USC.

Cyber-physical systems of the near future will collaborate with humans. Such cognitive systems will need to understand what the humans are doing. They will need to interpret human action in real-time and predict the humans' immediate intention in complex, noisy and cluttered environments. This proposal puts forward a new architecture for cognitive cyber-physical systems that can understand complex human activities, and focuses specifically on manipulation activities. The proposed architecture, motivated by biological perception and control, consists of three layers. At the bottom layer are vision processes that detect, recognize and track humans, their body parts, objects, tools, and object geometry. The middle layer contains symbolic models of the human activity, and it assembles through a grammatical description the recognized signal components of the previous layer into a representation of the ongoing activity. Finally, at the top layer is the cognitive control, which decides which parts of the scene will be processed next and which algorithms will be applied where. It modulates the vision processes by fetching additional knowledge when needed, and directs the attention by controlling the active vision system to direct its sensors to specific places. Thus, the bottom layer is the perception, the middle layer is the cognition, and the top layer is the control. All layers have access to a knowledge base, built in offline processes, which contains the semantics about the actions. The feasibility of the approach will be demonstrated through the development of a smart manufacturing system, called MONA LISA, which assists humans in assembly tasks. This system will monitor humans as they perform assembly task. It will recognize the assembly action and determine whether it is correct and will communicate to the human possible errors and suggest ways to proceed. The system will have advanced visual sensing and perception; action understanding grounded in robotics and human studies; semantic and procedural-like memory and reasoning, and a control module linking high-level reasoning and low-level perception for real time, reactive and proactive engagement with the human assembler. The proposed work will bring new tools and methodology to the areas of sensor networks and robotics and is applicable, besides smart manufacturing, to a large variety of sectors and applications. Being able to analyze human behavior using vision sensors will have impact on many sectors, ranging from healthcare and advanced driver assistance to human robot collaboration. The project will also catalyze K-12 outreach, new courseware (undergraduate and graduate), publication and open-source software.