The objective of this research is to establish a foundational framework for smart grids that enables significant penetration of renewable DERs and facilitates flexible deployments of plug-and-play applications, similar to the way users connect to the Internet. The approach is to view the overall grid management as an adaptive optimizer to iteratively solve a system-wide optimization problem, where networked sensing, control and verification carry out distributed computation tasks to achieve reliability at all levels, particularly component-level, system-level, and application level. Intellectual merit. Under the common theme of reliability guarantees, distributed monitoring and inference algorithms will be developed to perform fault diagnosis and operate resiliently against all hazards. To attain high reliability, a trustworthy middleware will be used to shield the grid system design from the complexities of the underlying software world while providing services to grid applications through message passing and transactions. Further, selective load/generation control using Automatic Generation Control, based on multi-scale state estimation for energy supply and demand, will be carried out to guarantee that the load and generation in the system remain balanced. Broader impact. The envisioned architecture of the smart grid is an outstanding example of the CPS technology. Built on this critical application study, this collaborative effort will pursue a CPS architecture that enables embedding intelligent computation, communication and control mechanisms into physical systems with active and reconfigurable components. Close collaborations between this team and major EMS and SCADA vendors will pave the path for technology transfer via proof-of-concept demonstrations.

Tens of thousands of the nation?s bridges are structurally deficient. This project proposes to design a self sustaining, wireless structural monitoring system. The novel low-power Flash FPGA-based hardware platform and the corresponding software architecture offer a radically new approach to CPS design. A soft multi-core platform where software modules that run in parallel will be guaranteed to have dedicated single-threaded soft processor cores enables flexible power management by running only the necessary cores at any given time at the slowest clock rate mandated by the observed/controlled physical phenomena. As bridges tend to vibrate due to wind and dynamic load conditions, we are developing a novel vibration-based energy harvesting device that is capable of automatically adjusting its resonant response in order to capture much more energy than the current techniques can. Moreover, the PIs are developing structural health assessment techniques involving quantitative analysis of signals to determine crack type, location and size. The technology will indicate structural problems before they become critical potentially saving human lives and averting late and extensive repairs. The impact of the vibration harvesting technique and the soft multi-core architecture will go beyond structural monitoring. A separate soft core dedicated to each software component that interacts with the physical world will make CPS more responsive while saving power at the same time. The education plan focuses on outreach toward underrepresented minorities by recruiting such undergraduates to participate in the research. To facilitate the dissemination of our results, all hardware designs and software developed under this project will be open source.

The objective of this research is to enable cyberphysical systems (CPS) to be context-aware of people in the environment and to use data from real-world probabilistic sensors. The approach is (1) to use radio tomography (RT) and RFID to provide awareness (location and potential identification) of every person in a building or area, and (2) to develop new middleware tools to enable context-aware computing systems to use probabilistic data, thus allowing new applications to exploit sometimes unreliable estimates of the environment.The intellectual merit of the proposal is in the development of new algorithms and models for building-scale RT with low radio densities and across multiple frequencies; the development of efficient multichannel access protocols for rapid and adaptive peer-to-peer measurements; the development of space-time and probabilistic data representations for use in stream-based context awareness systems and for merging ID and non-ID data; (4) and the development of a human context-aware software development toolkit that interfaces between probabilistic data and context-aware applications. The proposal impacts broadly the area of Cyber-physical systems that reason about human presence and rely on noisy and potentially ambiguous (practical) sensors. The research has additional dramatic impact in: (1) smart facilities which automatically enforce safety, privacy, and security procedures, increasing the ability to respond in emergency situations and prevent accidents and sabotage; (2) elder care, to monitor for physical or social decline so that effective intervention can be implemented, extending the period elders can live in their own home, without pervasive video surveillance.

The objective of this research is to establish a foundational framework for smart grids that enables significant penetration of renewable DERs and facilitates flexible deployments of plug-and-play applications, similar to the way users connect to the Internet. The approach is to view the overall grid management as an adaptive optimizer to iteratively solve a system-wide optimization problem, where networked sensing, control and verification carry out distributed computation tasks to achieve reliability at all levels, particularly component-level, system-level, and application level. Intellectual merit. Under the common theme of reliability guarantees, distributed monitoring and inference algorithms will be developed to perform fault diagnosis and operate resiliently against all hazards. To attain high reliability, a trustworthy middleware will be used to shield the grid system design from the complexities of the underlying software world while providing services to grid applications through message passing and transactions. Further, selective load/generation control using Automatic Generation Control, based on multi-scale state estimation for energy supply and demand, will be carried out to guarantee that the load and generation in the system remain balanced. Broader impact. The envisioned architecture of the smart grid is an outstanding example of the CPS technology. Built on this critical application study, this collaborative effort will pursue a CPS architecture that enables embedding intelligent computation, communication and control mechanisms into physical systems with active and reconfigurable components. Close collaborations between this team and major EMS and SCADA vendors will pave the path for technology transfer via proof-of-concept demonstrations.

The objective of this research is to enable cyberphysical systems (CPS) to be context-aware of people in the environment and to use data from real-world probabilistic sensors. The approach is (1) to use radio tomography (RT) and RFID to provide awareness (location and potential identification) of every person in a building or area, and (2) to develop new middleware tools to enable context-aware computing systems to use probabilistic data, thus allowing new applications to exploit sometimes unreliable estimates of the environment.The intellectual merit of the proposal is in the development of new algorithms and models for building-scale RT with low radio densities and across multiple frequencies; the development of efficient multichannel access protocols for rapid and adaptive peer-to-peer measurements; the development of space-time and probabilistic data representations for use in stream-based context awareness systems and for merging ID and non-ID data; (4) and the development of a human context-aware software development toolkit that interfaces between probabilistic data and context-aware applications. The proposal impacts broadly the area of Cyberphysical systems that reason about human presence and rely on noisy and potentially ambiguous (practical) sensors. The research has additional dramatic impact in: (1) smart facilities which automatically enforce safety, privacy, and security procedures, increasing the ability to respond in emergency situations and prevent accidents and sabotage; (2) elder care, to monitor for physical or social decline so that effective intervention can be implemented, extending the period elders can live in their own home, without pervasive video surveillance.

The objective of this research is to develop energy-efficient integrity establishment techniques for dynamic networks of cyber physical devices. In such dynamic networks, devices connect opportunistically and perform general-purpose computations on behalf of other devices. However, some devices may be malicious in intent and affect the integrity of computation. The approach is to develop new trust establishment mechanisms for dynamic networks. Existing trusted computing mechanisms are not directly applicable to cyber physical devices because they are resource-intensive and require devices to have special-purpose hardware. This project is addressing these problems along three research prongs. The first is a comprehensive study of the resource bottlenecks in current trust establishment protocols. Second, the insights from this study are being used to develop resource-aware attestation protocols for cyber physical devices that are equipped with trusted hardware. Third, the project is developing new trust establishment protocols for cyber physical devices that may lack trusted hardware. A key outcome of the project is an improved understanding of the tradeoffs needed to balance the concerns of security and resource-awareness in dynamic networks. Dynamic networks allow cyber physical devices to form a highly-distributed, cloud-like infrastructure for computations involving the physical world. The trust-establishment mechanisms developed in this project encourage devices to participate in dynamic networks, thereby unleashing the full potential of dynamic networks. This project includes development of dynamic networking applications, such as distributed gaming and social networking, in undergraduate curricula and course projects, thereby fostering the participation of this key demographic.

The objective of this research is to develop a theory of ActionWebs, that is, networked embedded sensor-rich systems, which are taskable for coordination of multiple decision-makers. The approach is to first identify models of ActionWebs using stochastic hybrid systems, an interlinking of continuous dynamical physical models with discrete state representations of interconnection and computation. Second, algorithms will be designed for tasking individual sensors, based on information objectives for the entire system. Third, algorithms for ActionWebs will be developed using multi-objective control methods for meeting safety and efficiency objectives. Two grand challenge applications for this research are in Intelligent Buildings for optimal heating, ventilation, air conditioning, and lighting based on occupant behavior and external environment; and Air Traffic Control for mobile vehicle platforms with sensor suites for environmental sensing to enable safe, convenient, and energy efficient routing. The intellectual merit of this research stems from a conceptual shift of ActionWebs away from passive information gathering to an action-orientation. This involves: modeling of ActionWebs using stochastic hybrid systems; taskable, multi-modal, and mobile sensor webs; and multi-scale action-perception hierarchies. The broader impact of the research is in two grand challenge national problems: energy efficient air transportation, and energy efficient, high productivity buildings, and will tackle social, privacy, economic, and usability issues. Integrated with the research is a program of coursework development in networked embedded systems, across stove pipes in EECS, Aero-Astro, Civil, and Mechanical Engineering departments. Outreach objectives include new course design at San Jose State University, and recruiting more women researchers.

The goal of the proposed research is to identify ways to inexpensively provide specific information about energy consumption in buildings and facilitate conservation. Signal processing, machine learning, and data fusion techniques will be developed to extract actionable information from whole-building power meters and other available sensors. The main objectives are: (a) to create a framework for obtaining disaggregated, appliance-specific feedback about electricity consumption in a building by extracting high-value information from low-cost data sources; and (b) to investigate and develop data mining and machine learning algorithms for making use of appliance-specific electricity data, in order to provide users with recommendations on how to optimize their energy consumption and understand the effects of their energy-related decisions. A series of residential buildings in Pittsburgh, PA will serve as a test-bed for evaluating and validating our proposed approach. Blueroof Technologies, a non-profit corporation located in McKeesport, PA that researches, develops and provides affordable senior-citizen housing with integrated sensor networks and building automation systems, will provide access to their Research Cottages for this project. Similarly, Robert Bosch LLC, a leading global provider of consumer goods and building technology, will provide additional technical research assistance and expertise. The main scientific merit of the project is the development of a framework for evaluating energy-use-disaggregation methods according to their value for promoting energy conservation. The resulting data sets will be large enough to produce significant conclusions about the feasibility and effectiveness of the technology, and allow for the development of new models about the trends and patterns of appliance usage in buildings. Broader impacts of this research include providing a foundation for future cyber-physical systems by inexpensively obtaining real-time appliance-level data. Such data can be used to help reduce the energy consumption of buildings by revealing the relationship between users' behavior and electricity consumption in buildings. The proposed industry-university collaborative research effort with Bosch will ensure that the technology and scientific contributions are steered toward innovative solutions that are practical for adoption in the market. Furthermore, the project will have significant diversity contributions by attracting minority students through collaboration with the University of Maryland Eastern Shore, a land-grant, historically black college with a diverse student body. Finally, a series of planned industry seminars, workshops and the publication of journal articles will allow further dissemination of the work.