The objective of this research is to develop algorithms and software for treatment planning in intensity modulated radiation therapy under assumption of tumor and healthy organs motion. The current approach to addressing tumor motion in radiation therapy is to treat it as a problem and not as a therapeutic opportunity. However, it is possible that during tumor and healthy organs motion the tumor is better exposed for treatment, allowing for the prescribed dose treatment of the tumor (target) while reducing the exposure of healthy organs to radiation. The approach is to treat tumor and healthy organs motion as an opportunity to improve the treatment outcome, rather than as an obstacle that needs to be overcome. Intellectual Merit: The leading intellectual merit of this proposal is to develop treatment planning and delivery algorithms for motion-optimized intensity modulated radiation therapy that exploit differential organ motion to provide a dose distribution that surpasses the static case. This work will show that the proposed motion-optimized IMRT treatment planning paradigm provides superior dose distributions when compared to current state-of-the art motion management protocols. Broader Impact: Successful completion of the project will mark a major step for clinical applications of intensity modulated radiation therapy and will help to improve the quality of life of many cancer patients. The results could be integrated within existing devices and could be used for training of students and practitioners. The visualization software for dose accumulation could be used to train medical students in radiation therapy treatment planning.

This Cyber-Physical Systems project designs and evaluates a foundational information substrate for efficient, agile, model-driven, human-centered building systems. The approach is to develop software-defined buildings, to shatter existing stovepipe architectures, dramatically reduce the effort to add new functions and applications without forklift upgrades, and expand communications and control capabilities beyond a single stand-alone building to enable groups of buildings to behave cooperatively and in cooperation with the energy grid. We investigate how such Software-Defined Buildings can be founded on a flexible, multi-service and open Building Integrated Operating System (BIOS) that allows applications to run reliably in safe, sandboxed environments. It supports sensor and actuator access, access management, metadata, archiving, and discovery, as well as multiple simultaneously executing programs. Building operators retain supervisory management, controlling application separation physically (access different controls), temporally (change controls at different times), informationally (what information leaves the building), and logically (what actions or sequences thereof are allowable). We construct, deploy, and demonstrate the capabilities of a prototype BIOS in the context of university, residential buildings and closely related industrial processes. Making buildings more efficient, while keeping occupants comfortable, productive, and healthy, is critical to our economy and health. Transforming buildings into agile, human centered cyber-physical systems eliminates waste, while allowing them to be a proactive resource on the electric grid with zero emission renewable supplies. And by providing greater value from the same physical plant, the SDB approach can move beyond cost-to-build and cost-to-operate metrics to broader return-on-investment for new extendable future-proof technologies.

This project aims to achieve key technology, infrastructure, and regulatory science advances for next generation medical systems based on the concept of medical application platforms (MAPs). A MAP is a safety/security-critical real-time computing platform for: (a) integrating heterogeneous devices and medical IT systems, (b) hosting application programs ("apps") that provide medical utility through the ability to both acquire information and update/control integrated devices, IT systems, and displays. The project will develop formal architectural and behavioral specification languages for defining MAPs, with a focus on techniques that enable compositional reasoning about MAP component interoperability and safety. These formal languages will include an extensible property language to enable the specification of real-time, quality-of-service, and attributes specific to medical contexts that can be leveraged by code generation, testing, and verification tools. The project will work closely with a synergistic team of clinicians, device industry partners, regulators, and medical device interoperability and safety standard organizations to develop an open source MAP innovation platform to enable key stakeholders within the nation's health care ecosphere to identify, prototype, and evaluate solutions to key technology and regulatory challenges that must be overcome to develop a commodity market of regulated MAP components. Because MAPs provide pre-built certified infrastructure and building blocks for rapidly developing multi-device medical applications, this research has the potential to usher in a new paradigm of medical system that significantly increases the pace of innovation, lowers development costs, enables new functionality by aggregating multiple devices into a system of systems, and achieves greater system safety.

This project's objective is to enable assertion-driven development and debugging of cyber-physical systems (CPS), in which required conditions are formalized as part of the design. In contrast with traditional uses of assertions in software engineering, CPS demand a tight coupling of the cyber with the physical, including in system validation. This project uses mathematical models of key physical attributes to guide creation of assertions, to identify inconsistent or infeasible assertions, and to localize potential causes for CPS failures. The goal is to produce methods and tools that use physical models to guide assertion-based verification of cyber-physical systems. An assertion language is being developed that is founded in mathematical logic while providing the familiarity of commonly used programming languages. This foundation enables new automated debugging techniques for CPS. By leveraging models that encode laws of physics and an automated decision procedure, the techniques being developed help identify causes of CPS failures by distinguishing inconsistent or infeasible physical states from valid ones. This model-based approach incorporates means to assess these physical states using both probabilistic and non-probabilistic measures. Two safety-critical applications guide the research and demonstrate the impact on the development of CPS: coordinated control of autonomous vehicles and monitoring and control of left-ventricular assist devices (LVADs). The focus on these safety-critical applications are motivational for recruiting and educating engineering students who have high expectations for how their lives should be enabled by computing advances. Further, this research advances methods needed to validate safe and effective CPS, promoting the public's confidence in their application to safety-critical systems.

Cyber physical systems (CPSs) are merging into major mobile systems of our society, such as public transportation, supply chains, and taxi networks. Past researchers have accumulated significant knowledge for designing cyber physical systems, such as for military surveillance, infrastructure protection, scientific exploration, and smart environments, but primarily in relatively stationary settings, i.e., where spatial and mobility diversity is limited. Differently, mobile CPSs interact with phenomena of interest at different locations and environments, and where the context information (e.g., network availability and connectivity) about these physical locations might not be available. This unique feature calls for new solutions to seamlessly integrate mobile computing with the physical world, including dynamic access to multiple wireless technologies. The required solutions are addressed by (i) creating a network control architecture based on novel predictive hierarchical control and that accounts for characteristics of wireless communication, (ii) developing formal network control models based on in-situ network system identification and cross-layer optimization, and (iii) designing and implementing a reference implementation on a small scale wireless and vehicular test-bed based on law enforcement vehicles. The results can improve all mobile transportation systems such as future taxi control and dispatch systems. In this application advantages are: (i) reducing time for drivers to find customers; (ii) reducing time for passengers to wait; (iii) avoiding and preventing traffic congestion; (iv) reducing gas consumption and operating cost; (v) improving driver and vehicle safety, and (vi) enforcing municipal regulation. Class modules developed on mobile computing and CPS will be used at the four participating Universities and then be made available via the Web.

This project designs algorithms for the integration of plug-in hybrid electric vehicles (PEVs) into the power grid. Specifically, the project will formulate and solve optimization problems critical to various entities in the PEV ecosystem -- PEV owners, commercial charging station owners, aggregators, and distribution companies -- at the distribution / retail level. Charging at both commercial charging stations and at residences will be considered, for both the case when PEVs only function as loads, and the case when they can also function as sources, equipped with vehicle-to-home (V2H) or vehicle-to-grid (V2G) energy reinjection capability. The focus of the project is on distributed decision making by various individual players to achieve analytical system-level performance guarantees. Electrification of the transportation market offers revenue growth for utility companies and automobile manufacturers, lower operational costs for consumers, and benefits to the environment. By addressing problems that will arise as PEVs impose extra load on the grid, and by solving challenges that currently impede the use of PEVs as distributed storage resources, this research will directly impact the society. The design principles gained will also be applicable to other cyber-physical infrastructural systems. A close collaboration with industrial partners will ground the research in real problems and ensure quick dissemination of results to the marketplace. A strong educational component will integrate the proposed research into the classroom to allow better training of both undergraduate and graduate students. The details of the project will be provided at http://ee.nd.edu/faculty/vgupta/research/funding/cps_pev.html

This project demonstrates the synergistic use of a cyber-physical infrastructure consisting of smart-phone devices; cloud computing, wireless communication, and intelligent transportation systems to manage vehicles in the complex urban network -- through the use of traffic controls, route advisories and road pricing -- to jointly optimize drivers' mobility and the sustainability goals of reducing energy usage and improving air quality. The system developed, MIDAS-CPS, proactively manages the interacting traffic demand and the available transportation supply. A key element of MIDAS-CPS is the data collection and display device PICT that collects each participating driver's vehicle position, forward images from the vehicle's dashboard, and communication time stamps, and then displays visualizations of predicted queues ahead, relevant road prices, and route advisories. Given the increasing congestion in most of the urban areas, and the rising costs of constructing traffic control facilities and implementing highway hardware, MIDAS-CPS could revolutionize the way traffic is managed on the urban network since all computing is done via clouds and the drivers instantly get in-vehicle advisories with graphical visualizations of predicted conditions. It is anticipated this would lead to improved road safety and lesser drive stress, besides the designed benefits on the environment, energy consumption, congestion mitigation, and driver mobility. This multidisciplinary project is at the cutting edge in several areas: real-time image processing, real-time traffic prediction and supply/demand management, and cloud computing. Its educational impacts include enhancements of curricula and laboratory experiences at participating universities, workforce development, and student diversity.

This project demonstrates the synergistic use of a cyber-physical infrastructure consisting of smart-phone devices; cloud computing, wireless communication, and intelligent transportation systems to manage vehicles in the complex urban network ? through the use of traffic controls, route advisories and road pricing ? to jointly optimize drivers? mobility and the sustainability goals of reducing energy usage and improving air quality. The system developed, MIDAS-CPS, proactively manages the interacting traffic demand and the available transportation supply. A key element of MIDAS-CPS is the data collection and display device PICT that collects each participating driver?s vehicle position, forward images from the vehicle?s dashboard, and communication time stamps, and then displays visualizations of predicted queues ahead, relevant road prices, and route advisories. Given the increasing congestion in most of the urban areas, and the rising costs of constructing traffic control facilities and implementing highway hardware, MIDAS-CPS could revolutionize the way traffic is managed on the urban network since all computing is done via clouds and the drivers instantly get in-vehicle advisories with graphical visualizations of predicted conditions. It is anticipated this would lead to improved road safety and lesser drive stress, besides the designed benefits on the environment, energy consumption, congestion mitigation, and driver mobility. This multidisciplinary project is at the cutting edge in several areas: real-time image processing, real-time traffic prediction and supply/demand management, and cloud computing. Its educational impacts include enhancements of curricula and laboratory experiences at participating universities, workforce development, and student diversity. Additional information on the project is available at http://midas-cps.mobicloud.asu.edu/.

This project aims to achieve key technology, infrastructure, and regulatory science advances for next generation medical systems based on the concept of medical application platforms (MAPs). A MAP is a safety/security-critical real-time computing platform for: (a) integrating heterogeneous devices and medical IT systems, (b) hosting application programs ("apps") that provide medical utility through the ability to both acquire information and update/control integrated devices, IT systems, and displays. The project will develop formal architectural and behavioral specification languages for defining MAPs, with a focus on techniques that enable compositional reasoning about MAP component interoperability and safety. These formal languages will include an extensible property language to enable the specification of real-time, quality-of-service, and attributes specific to medical contexts that can be leveraged by code generation, testing, and verification tools. The project will work closely with a synergistic team of clinicians, device industry partners, regulators, and medical device interoperability and safety standard organizations to develop an open source MAP innovation platform to enable key stakeholders within the nation's health care ecosphere to identify, prototype, and evaluate solutions to key technology and regulatory challenges that must be overcome to develop a commodity market of regulated MAP components. Because MAPs provide pre-built certified infrastructure and building blocks for rapidly developing multi-device medical applications, this research has the potential to usher in a new paradigm of medical system that significantly increases the pace of innovation, lowers development costs, enables new functionality by aggregating multiple devices into a system of systems, and achieves greater system safety.

Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid. The project integrates ideas from economics and behavioral science into frameworks grounded in control theory and power systems. Our central construct is that of a ?resource cluster,? a collection of distributed resources (ex: solar PV, storage, deferrable loads) that can be coordinated to efficiently and reliably offer services (ex: power delivery) in the face of uncertainty (ex: PV output, consumer behavior). Three topic areas form the core of the project: (a) the theoretical foundations for the ?cluster manager? concept and complementary tools to characterize the capabilities of a resource cluster; (b) centralized resource coordination strategies that span multiple time scales via innovations in stochastic optimal control theory; and (c) decentralized coordination strategies based on cluster manager incentives and built upon foundations of non-cooperative dynamic game theory. These innovations will improve the operation of infrastructure systems via a cyber-physical-social approach to the problem of resource allocation in complex infrastructures. By transforming the role of humans from passive resource recipients to active participants in the electric power system, the project will facilitate energy security for the nation, and climate change mitigation. The project will also engage K-12 students through lab-visits and lectures; address the undergraduate demand for power systems training through curricular innovations at the intersection of cyber-systems engineering and physical power systems; and equip graduate students with the multi-disciplinary training in power systems, communications, control, optimization and economics to become leaders in innovation.