The objective of this research project is to achieve fundamental advances in software technology that will enable building cyber-physical systems to allow citizens to see the environmental and health impacts of their daily activities through a citizen-driven body-worn mobile-phone-based commodity sensing platform. The approach is to create aspect-oriented extensions to a publish-subscribe architecture, called Open Rich Services (ORS), to provide a highly extensible and adaptive infrastructure. As one example, ORS will enable highly adaptive power management that not only adapts to current device conditions, but also the nature of the data, the data's application, and the presence and status of other sensors in the area. In this way, ORS will enable additional research advances in power management, algorithms, security and privacy during the project. A test-bed called CitiSense will be built, enabling in-the-world user and system studies for evaluating the approach and providing a glimpse of a future enhanced by cyber-physical systems. The research in this proposal will lead to fundamental advances in modularity techniques for composable adaptive systems, adaptive power management, cryptographic methods for open systems, interaction design for the mobile context, and statistical inference under multiple sources of noise. The scientific and engineering advances achieved through this proposal will advance our national capability to develop cyber-physical systems operating under decentralized control and severe resource constraints. The students trained under this project will become part of a new generation of researchers and practitioners prepared to advance the state of cyber-physical systems for the coming decades.

The objective of this research is to study active sensing and adaptive fusion using vision and acoustic sensors for continuous, reliable fall detection and assessment of fall risk in dynamic and unstructured home environments. The approach is to incorporate active vision with infrared light sources and camera controls, an acoustic array that identifies the sound characteristics and location, and sensor fusion based on the Choquet integral and hierarchical fuzzy logic systems that supports uncertain heterogeneous sensor data at varying time scales, qualitative data, and risk factors. The project will advance the state of the art in (1) active vision sensing for human activity recognition in dynamic and unpredictable environments, (2) acoustic sensing in unstructured environments, (3) adaptive sensor fusion and decision making using heterogeneous sensor data in dynamic and unpredictable environments, (4) automatic fall detection and fall risk assessment using non-wearable sensors, and (5) algorithms for cyber physical systems that address the interplay of anomaly detection (falls) and risk factors affecting the likelihood of an anomaly event. The project will impact the health care and quality of life for older adults. New approaches will assist health care providers to identify potential health problems early, offering a model for eldercare technology that keeps seniors independent while reducing health care costs. The project will train the next generation of researchers to handle real, cyber-physical systems. Students will be mentored, and research outcomes will be integrated into the classroom. Novel outreach activities are planned to reach the elderly community and the general public

The objective of this research is to develop methods and tools for a multimodal and multi-sensor assessment and rehabilitation game system called CPLAY for children with Cerebral Palsy (CP). CPLAY collects and processes multiple types of stimulation and performance data while a child is playing. Its core has a touch-screen programmable game that has various metrics to measure delay of response, score, stamina/duration, accuracy of motor/hand motion. Optional devices attached to extend CPLAY versions provide additional parallel measurements of level of concentration/participation/engagement that quantify rehabilitation activity. The approach is to model the process as a cyber-physical system (CPS) feedback loop whereby data collected from various physical 3D devices (including fNIR brain imaging) are processed into hierarchical events of low-to-high semantic meaning that impact/ adjust treatment decisions. Intellectual Merit: The project will produce groundbreaking algorithms for event identification with a multi-level data to knowledge feedback loop approach. New machine learning, computer vision, data mining, multimodal data fusion, device integration and event-driven algorithms will lead towards a new type of cyber- physical rehabilitation science for neurological disorders. It will deliver fundamental advancements to engineering by showing how to integrate physical devices with a computationally quantitative platform for motor and cognitive skills assessment. Broader Impacts: The project delivers a modular & expandable game system that has huge implications on the future of US healthcare and rehabilitation of chronic neurological disabilities. It brings hope to children with Cerebral Palsy via lower cost and remote rehabilitation alternatives. It brings new directions to human centered computing for intelligent decision-making that supplements evidence-based practices and addresses social and psychological isolation problems.

The objective of this research is to develop an atomic force microscope based cyber-physical system that can enable automated, robust and efficient assembly of nanoscale components such as nanoparticles, carbon nanotubes, nanowires and DNAs into nanodevices. The proposed approach is based on the premise that automated, robust and efficient nanoassembly can be achieved through tip based pushing in an atomic force microscope with intermittent local scanning of nanoscale components. In particular, in order to resolve temporally and spatially continuous movement of nanoscale components under tip pushing, we propose the combination of intermittent local scanning and interval non-uniform rational B-spline based isogeometric analysis in this research. Successful completion of this research would lead to foundational theories and algorithmic infrastructures for effective integration of physical operations (pushing and scanning) and computation (planning and simulation) for robust, efficient and automated nanoassembly. The resulting theories and algorithms will also be applicable to a broader set of cyber physical systems. If successful, this research will lead to leap progress in nanoscale assembly, from prototype demonstration to large-scale manufacturing. Through its integrated research, education and outreach activities, this project will provide advanced knowledge in cyber-physical systems and nanoassembly for students from high schools to graduate schools and will increase domestic students? interest in science and engineering and therefore strengthen our competitiveness in the global workforce.

The objective of this research is to develop new principles and techniques for adaptive operation in highly dynamic physical environments, using miniaturized, energy-constrained devices. The approach is to use holistic cross-layer solutions that simultaneously address all aspects of the system, from low-level hardware design to higher-level communication and data fusion algorithms to top-level applications. In particular, this work focuses on body area sensor networks as emerging cyber-physical systems. The intellectual merit includes producing new principles regarding how cyber systems must be designed in order to continually adapt and respond to rapidly changing physical environments, sensed data, and application contexts in an energy-efficient manner. New cross-layer technologies will be created that use a holistic bottom-up and top-down design -- from silicon to user and back again. A novel system-on-a-chip hardware platform will be designed and fabricated using three cutting-edge technologies to reduce the cost of communication and computation by several orders of magnitude. The broad impact of this project will enable the wide range of applications and societal benefits promised by body area networks, including improving the quality and reducing the costs of healthcare. The technology will have broad implications for any cyber physical system that uses energy constrained wireless devices. A new seminar series will bring together experts from many fields (including domain experts, such as physicians and healthcare professionals). The key aspects of this work that deal with healthcare have the potential to attract women and minorities to the computer field.

The objective of this research is to develop methods and tools for designing, implementing and verifying medical robotics. The approach is to capture the computational work-flow of systems with cyber, physical and biological components, to verify that work-flow and to synthesize systems from the work-flow model. The focusing application of this research is MRI-guided, high-frequency ultrasonic tumor ablation. MRI-guided ultrasonic tumor ablation poses challenges beyond the scope of current verification techniques. Medicine is filled with highly non-linear biological systems, which puts them at the frontier of mathematically rigorous correctness checking and verification. For instance, in this research, guaranteeing the safety of a cancer patient undergoing treatment will require verifying against Pennes bioheat equation, a non-linear differential equation with dozens of environmental factors. This research tackles such complexity using tiers of abstractions to efficiently, precisely and safely approximate the behavior of each component of a system. To ensure a faithful implementation of controllers, this research will investigate synthesizing the control code directly from the verified model in a correct by construction manner. The project will help develop the most appropriate family of formal methods for handling the safety and correctness challenges in the area of medical robotics. It directly addresses the CPS agenda of methods and tools by proposing formal techniques that bridge the gap between the cyber and physical elements. It will train manpower in cross-disciplinary areas through new seminars, workshops and courses. And, last but not least, the project will make a direct humanitarian impact on the well-being of society.

The objective of this research is to develop a prototype programmable microfluidic laboratory-on-chip that concurrently executes assays (chemical algorithms) in an on-line fashion. A chemist specifies an assay (chemical algorithm) using a text-based language. Assays arrive at the device in real-time and an operating system/virtual machine running on an attached microcontroller interprets them. The approach is to develop a software simulation infrastructure for the laboratory-on-chip and to build the operating system/virtual machine on top of it. The intellectual merit of this activity is due to the fact that no type of runtime support system has yet been proposed for microfluidic devices. The key challenges to be solved in this project include: deadlock-free deterministic and adaptive routing algorithms; real-time constraints for routing droplets in the system; routing wash droplets for decontamination; scheduling assay operations on the devices; congestion estimation; and fault diagnosis and recovery. In terms of broader impact, advances in laboratory-on-chip technology will improve public health worldwide and lead to significant advances in clinical diagnostics and medicine. Laboratory-on-chips are commercially available from established companies such as Agilent Technologies as well as startup companies such as Advanced Liquid Logic, Silicon Biosystems, and Ayanda Biosystems; thus, the economic impact of this research is tremendous. The University of California, Riverside is a Minority-Serving Institution. The PI is committed to the introduction of laboratory-on-chip technology in both undergraduate and graduate education and will make every possible effort to recruit underrepresented minorities (including women) at the graduate and undergraduate level to work on the project.

Complex surgical procedures in hospitals are increasingly aided by robotic surgery systems, often at the request of patients. These systems allow greatly increased precision, reach and flexibility to the surgeon. However, their powerful capabilities entail substantial system complexity in both hardware and software. The high probability of serious injuries should a malfunction occur calls for rigorous assessment and monitoring of the reliability and safety of these cyber-physical systems. In this research project, a framework for assessing and monitoring the reliability and safety of robotic surgery systems during development, field testing, and general deployment is being developed. The proposed framework complements existing techniques used in earlier phases of validation by taking into account how surgeons actually use a robotic surgery system, how it is affected by operating conditions, and how its observable behavior is related to its hardware and software dynamics. Before deployment, this framework uses accurate simulations to assess pre-clinical reliability. After deployment, the framework uses data collection through online monitoring of the system as it is being used in the field, followed by analysis to obtain assessments of operational reliability and safety. The collected data is also used to improve the simulations for future testing. The framework also aims to support post-market surveillance of these systems by providing a workable basis for reassessing reliability and safety properties after system maintenance. The developed tools and methods will also have applications in the validation of safety and reliability of other medical devices with embedded software and other cyber-physical systems in general.