To reduce reliance on other countries for minerals (e.g., coal, rare-earth metals), the USA has seen an invigoration of mining activity in recent years. Unfortunately, miners often have to work in dangerous environments where there is risk of mine explosions, fires, poisonous gases, and flooding in tunnels. Mine accidents have killed over 500 US and 40,000 mine workers worldwide in the past decade. Most of these accidents occurred in structurally diverse underground mines with extensive labyrinths of interconnected tunnels, where the environment continually changes as mining progresses and machinery is repositioned, complicating search and rescue efforts. In recognition of the severity of the problem, the Mine Improvement and New Emergency Response Act passed in 2006 mandated mines to monitor levels of methane, carbon monoxide, smoke, and oxygen to warn miners of possible danger due to air poisoning, fire, or explosions. The Act also mandated plans to rapidly and safely respond in post-accident scenarios, involving two-way, wired or semi-wired tracking and communication systems that could save lives during entrapment and water inundation emergencies. But the high cost of deploying such a safety infrastructure encourages companies today to meet only the bare minimum required safeguards. This project will involve transformative, foundational, and synergistic research that is necessary to overcome monitoring, communication, and tracking challenges in the underground mining context, to realize a cost-effective safety infrastructure that can be deployed in any type of underground mine. Such a framework will not only minimize the risks facing hundreds of thousands of miners in the USA today, but the foundational research outcomes will also be applicable to a wide range of applications in the realms of Smart and Connected Communities (S&CC) and Internet of Things (IoT), wherever the emphasis is on creating smart workplaces, sustainably operating in harsh environments, and improving human safety. The principal objective of this proposal is to devise, design, prototype, and test a fundamentally novel wireless cyber-physical framework of low-cost, energy-efficient, and reliable sensor nodes and commodity smartphones for monitoring, tracking, and communication, to improve miner safety in underground mines. This synergy project contributes to the science and engineering principles needed to realize Cyber-Physical Systems and seeks to grow at the intersection of three research thrusts: quality-aware voice and data streaming, mobile computing assisted location tracking, and computational electromagnetics driven wireless signal characterization. These three thrusts (1) introduce novel mechanisms to enable the co-existence of high quality voice streams with environmental sensor data streams in low-power wireless mesh networks of sensor nodes operating in noisy underground environments; (2) develop schemes for energy-efficient scheduling of location queries and error-tolerant indoor localization to locate individual miners and groups of miners underground; and (3) characterize wireless signal behavior with electromagnetic modeling in highly complex and uncertain environments, based on measurements from a real underground mine, to guide optimal placement of wireless nodes in mining tunnels. Not only is the convergence of these thrusts novel as a whole, but also the techniques and insights developed for each thrust are transformative and go beyond conventional approaches. Collaboration with a mining company for technology transfer will enable rapid real-world deployment of the proposed research. The broader impacts of the research will tightly integrate research results into all levels of teaching, including graduate, undergraduate, and K-12 education; broaden the participation of women and minority students in Cyber-Physical research; and integrate research into the syllabi of existing and new courses.

The central-heating paradigm has always functioned in tandem with clothing, which for the most part conserves body heat through insulation. This project tips the balance toward on-body solutions, using active on-body heating in conjunction with insulation and passive thermal protection to heat the individual human body rather than the entire environment. The motivating hypothesis is that if heat can be delivered effectively to the individual?s body, then the need to heat large (and often empty) spaces will be significantly reduced. However, if on-body heating technologies are ever to become widely accepted, they must be comfortable and wearable in everyday environments, while also keeping the body as comfortable as central heating currently does. This is a challenge because the body?s perception of thermal comfort is strongly influenced by the temperature of the face and hands, areas where wearable technologies can be obstructive or socially awkward to wear in everyday situations. This project will develop comfortable, socially subtle wearable technologies that both preserve body heat and deliver additional heat to these key body areas, and evaluate their ability to maintain thermal comfort and reduce the comfortable ambient temperature in heated spaces. If successful, such technologies have the potential to offer both large-scale energy savings, but also allow for individualized thermal comfort, with each occupant selecting their optimal temperature. Because of the interdisciplinary nature of the problem, this project will contribute to the education of students from several contributing disciplines, and will introduce project and research opportunities to students in undergraduate and graduate coursework. The research proposed here focuses on the development and thermal chamber evaluation of comfortable, socially appropriate methods of delivering heating to these sensitive areas. Second, the effect of these technologies on acceptable ambient temperatures (and the resulting energy savings) are evaluated in a field trial. Finally, the boundaries of the concept are extended in early-stage exploration of persuasive interfaces through on-body temperature modulation. The intellectual merit of the proposal lies in its contributions to developing effective sensor/actuator technologies for modulating individual micro-climate in conjunction with IoT and ambient devices, and establishing the boundaries of the relative influence of micro-climate on human comfort (with corresponding effects on energy consumption). The broader impacts of the proposed research most directly include the potential for a large savings in the energy costs spent on heating in cold climates. The education plan integrated into this research will contribute to interdisciplinarity and diversity in engineering.

Data-driven cyber-physical systems are ubiquitous in many sectors including manufacturing, automotive, transportation, utilities and health care. This project develops the theory, methods and tools necessary to answer the central question "how can we, in a data-rich world, design and operate cyber-physical systems differently?" The resulting data-driven techniques will transform the design and operation process into one in which data and models - and human designers and operators - continuously and fluently interact. This integrated view promises capabilities beyond its parts. Explicitly integrating data will lead to more efficient decision-making and help reduce the gap from model-based design to system deployment. Furthermore, it will blend design- and run-time tasks, and help develop cyber-physical systems not only for their initial deployment but also for their lifetime. While proposed theory, methods and tools will cut across the spectrum of cyber-physical systems, the project focuses on their implications in the emerging application of additive manufacturing. Even though a substantial amount of engineering time is spent, additive manufacturing processes often fail to produce acceptable geometric, material or electro-mechanical properties. Currently, there is no mechanism for predicting and correcting these systematic, repetitive errors nor to adapt the design process to encompass the peculiarities of this manufacturing style. A data-driven cyber-physical systems perspective has the potential to overcome these challenges in additive manufacturing. The project's education plan focuses on the already much needed transformation of the undergraduate and graduate curricula to train engineers and computer scientists who will create the next-generation of cyber-physical with a data-driven mindset. The team will reach out to K-12 students and educators through a range of activities, and to undergraduate students from underrepresented groups through year-long research projects. All educational material generated by the project will be shared publicly.

Factories, chemical plants, automobiles, and aircraft have come to be described today as cyber-physical systems of systems--distinct systems connected to form a larger and more complex system. For many such systems, correct operation is critical to safety, making their security of paramount importance. Unfortunately, because of their heterogeneous nature and special purpose, it is very difficult to determine whether a malicious attacker can make them behave in a manner that causes harm. This type of security analysis is an essential step in building and certifying secure systems. Unfortunately, today's state of the art security analysis tools are tailored to the analysis of server, desktop, and mobile software. We currently lack the tools for analyzing the security of cyber physical systems of systems. The proposed work will develop new techniques for testing and analyzing security properties of such systems. These techniques will be used to build a new generation of tools that can handle the complexity of modern cyber-physical systems and thus make these critical systems more secure.The technical approach taken by the investigators is to applying proven dynamic analysis techniques, including dynamic information flow tracking and symbolic execution, to this problem. Existing tools, while powerful, are monolithic, designed to apply a single technique to a single system. Scaling them to multiple heterogeneous systems is the main contribution of the proposed work. To do so, the investigators will develop a common platform for cross-system dynamic analysis supporting arbitrary combinations of component execution modes (physical, simulated, and emulated), requiring new coordination mechanisms. Second, building on the platform above, they will implement cross-system dynamic information flow tracking, allowing dynamic information flow tracking across simulated, emulated, and potentially physical components. Third, they will extend existing symbolic/concrete execution techniques to execution across multiple heterogeneous systems. Fourth, they will introduce new ways of handling special-purpose hardware, a problem faced by dynamic analysis tools in general.

Scaling the Internet of Things (IoT) to billions and possibly trillions of "things" requires transformative advances in the science, technology, and engineering of cyber-physical systems (CPS), with none more pressing or challenging than the power problem. Consider that if every device in a 1 trillion IoT network had a battery that lasted for a full five years, over 500 million batteries would need to be changed every day. Clearly, a battery-powered IoT is not feasible at this scale due to both human resource logistics and environmental concerns. There is a need for a batteryless approach that dependably meets functionality requirements using energy harvested from the physical world. This project brings together experts in materials, devices, circuits, and systems to pursue a holistic approach to self-powered wireless devices deployed in real-world environments and IoT systems and applications. In addition, educational and outreach activities will help develop the workforce for this relatively new field with the holistic, materials-to-systems perspective that will be necessary to lead innovation in this space. A critical challenge that this project addresses is that both optimal device operation and energy harvester efficiency are heavily dependent on physical world dynamics, and thus, self-powered devices that are statically configured or that just respond to instantaneous conditions are unlikely to provide the dependability required for many IoT systems and applications. To address this fundamental and critically enabling challenge, data collections will be performed to study the physical world dynamics that impact device operation and harvester efficiency, such as ambient conditions, electromagnetic interference, and human behavior. This scientific study will lead to the development of dynamic models that will, in turn, be used to develop algorithms to dynamically configure devices and harvesters based not only on past and current conditions but also on predictions of future conditions. These algorithms will then be used to dynamically configure technological innovations in ultra-low power device operation and ultra-high efficiency energy harvesting to engineer and operate dependable self-powered things for the IoT.

Poor air quality has been linked to not just adverse health effects such as increased incidence of cardiac arrhythmia, lung cancer, heart disease, and mortality, but also to the vitality of a region?s economy. These issues are particularly important in cities such as Salt Lake City (SLC), where topography, climate, and urban expansion combine to create some of the worst air quality episodes in the country. Cities like SLC currently rely on small numbers of expensive sensors placed across a large geographic area to measure air quality, making local, neighborhood-level measurements impossible to determine. Meanwhile, new commodity technologies are leading to fine-grained, community-based strategies for measuring and communicating air quality. Leveraging both of these approaches, this project will develop and deploy a dense, distributed, and dynamic air quality cyber-physical framework -- focusing on fine particulate matter and using SLC as an urban testbed -- to produce neighborhood-level estimates of air quality. The framework includes a network of low-cost sensors, hosted and maintained through a citizen science effort and maker-kit approach. This research will result in novel developments in three areas: (i) sensor development that focuses on dramatically reducing cost and a movement toward cheap, wearable, passive sensors; (ii) computational modeling that combines heterogeneous sensor measurements with information about weather, topography, and land use patterns; and (iii) visualization interface design that communicates air quality estimates over space and time, coupled with related uncertainty measurements. Each of these areas requires a multidisciplinary approach that integrates existing and novel insights about sensor networks, computational modeling, and sense-making of data, as well as leveraging an engaged and connected community of residents through citizen science.

Loss of walking function and leg sensation are devastating consequences of spinal cord injury (SCI). These deficits have a profoundly negative impact on independence and quality of life of those affected. Moreover, wheelchair reliance after SCI increases the risk of medical complications. The healthcare costs associated with SCI are ~$50 billion/year, presenting a significant public health concern. Currently, there are no biomedical solutions capable of restoring walking and leg sensation after SCI. Clinically practical and socially acceptable solutions to these important problems are desperately needed. Employing a cyber-physical system (CPS) to bypass the damaged spinal cord may be a novel way to restore walking and leg sensation to those with leg paralysis due to SCI. The proposed multi-disciplinary effort will inspire students from traditionally underprivileged and underrepresented groups to pursue college education in STEM fields by demonstrating how engineering and science can make a difference in the well-being of those with disabilities. In addition, it will engage individuals with disabilities, their family members, friends, and caregivers, in educational opportunities in order to increase their scientific and technical literacy. The outreach to these communities will be accomplished by leveraging diverse ethnic makeup of Orange and Los Angeles Counties, geographic proximity of the three study sites, which makes outreach activities amenable to integration, and the high societal significance and visibility of the project. Impairment or complete loss of gait function and lower extremity sensation are common after spinal cord injury (SCI). A new cyberphysical system, CPS, can be realized as a permanently implantable bi-directional (BD) brain-computer interface (BCI), which translates walking intentions from brain signals into commands for a leg prosthesis, and converts prosthesis sensor signals into electrical stimulation of the brain for artificial leg sensation. This closed-loop operation would come close to restoring able-body-like walking and leg sensation after SCI. Before such an implantable CPS is deployed in humans, its feasibility and safety must be established. The main objective of this Frontier project is to design, develop, and test a wearable analogue of a fully implantable electrocorticogram (ECoG)-based BD-BCI for walking and leg sensation. The BD-BCI CPS will be designed as an ultra-low power modular system with revolutionary techniques for interference mitigation to enable simultaneous electrical stimulation and recording. The first module will consist of a custom brain signal acquisition system that exploits ECoG signal attributes to significantly reduce power consumption. The second module will consist of a low-power processing unit, brain stimulator, and wireless communication transceiver. This module will internally execute optimized BCI algorithms and wirelessly transmit commands to a robotic gait exoskeleton for walking. Comprehensive benchtop and bedside tests will be conducted to assess proper system function. Finally, subjects with paraplegia due to SCI will be recruited to undergo a 30-day ECoG implantation to test the BD-BCI's ability to restore brain-controlled walking and leg sensation. The goals of transition to practice (TTP) are to: (1) develop a fully implantable version of the BD-BCI, (2) perform a series of industrial-standard medical device benchtop tests, and (3) test the implants safety.

This work examines how to get safety and security in Internet of Things (IoT) systems where multiple devices (things), each designed in isolation from others, are brought together to form a networked system, controlled via one or more software applications ("apps"). "Things" in an IoT environment can include simple devices such as switches, lightbulbs, smart locks, thermostats, and safety alarms as well as complex systems such as appliances, smartphones, and cars. Software IoT "apps" can monitor and control multiple devices in homes, cars, cities, and businesses, providing significant benefits such as energy efficiency, security, safety, and user convenience. Unfortunately, programmable IoT systems also introduce new risks, including enabling remote control by hackers of devices in smart homes, cars, and cities, via buggy IoT apps. Testing IoT apps to remove bugs is currently challenging due to a variety of physical devices with which such apps may interact, including devices that were not even available during app development. The proposed work will help develop techniques for testing IoT apps efficiently and for enforcing safety and security constraints on their run-time behavior. More specifically, the proposed work is centered around three technical thrusts: 1) creating virtual device models to help efficiently test IoT apps systematically without knowing the precise details of physical devices that the apps will control in advance; 2) automating test development for an IoT app to check safety and security specifications against a flexible set of devices; and 3) providing support for enforcement of specifications at run-time for security and safety assertions. The work includes extensive experimentation and evaluation using diverse devices and will represent a significant advance in hardening this important spaces

Loss of walking function and leg sensation are devastating consequences of spinal cord injury (SCI). These deficits have a profoundly negative impact on independence and quality of life of those affected. Moreover, wheelchair reliance after SCI increases the risk of medical complications. The healthcare costs associated with SCI are ~$50 billion/year, presenting a significant public health concern. Currently, there are no biomedical solutions capable of restoring walking and leg sensation after SCI. Clinically practical and socially acceptable solutions to these important problems are desperately needed. Employing a cyber-physical system (CPS) to bypass the damaged spinal cord may be a novel way to restore walking and leg sensation to those with leg paralysis due to SCI. The proposed multi-disciplinary effort will inspire students from traditionally underprivileged and underrepresented groups to pursue college education in STEM fields by demonstrating how engineering and science can make a difference in the well-being of those with disabilities. In addition, it will engage individuals with disabilities, their family members, friends, and caregivers, in educational opportunities in order to increase their scientific and technical literacy. The outreach to these communities will be accomplished by leveraging diverse ethnic makeup of Orange and Los Angeles Counties, geographic proximity of the three study sites, which makes outreach activities amenable to integration, and the high societal significance and visibility of the project. Impairment or complete loss of gait function and lower extremity sensation are common after spinal cord injury (SCI). A new cyberphysical system, CPS, can be realized as a permanently implantable bi-directional (BD) brain-computer interface (BCI), which translates walking intentions from brain signals into commands for a leg prosthesis, and converts prosthesis sensor signals into electrical stimulation of the brain for artificial leg sensation. This closed-loop operation would come close to restoring able-body-like walking and leg sensation after SCI. Before such an implantable CPS is deployed in humans, its feasibility and safety must be established. The main objective of this Frontier project is to design, develop, and test a wearable analogue of a fully implantable electrocorticogram (ECoG)-based BD-BCI for walking and leg sensation. The BD-BCI CPS will be designed as an ultra-low power modular system with revolutionary techniques for interference mitigation to enable simultaneous electrical stimulation and recording. The first module will consist of a custom brain signal acquisition system that exploits ECoG signal attributes to significantly reduce power consumption. The second module will consist of a low-power processing unit, brain stimulator, and wireless communication transceiver. This module will internally execute optimized BCI algorithms and wirelessly transmit commands to a robotic gait exoskeleton for walking. Comprehensive benchtop and bedside tests will be conducted to assess proper system function. Finally, subjects with paraplegia due to SCI will be recruited to undergo a 30-day ECoG implantation to test the BD-BCI's ability to restore brain-controlled walking and leg sensation. The goals of transition to practice (TTP) are to: (1) develop a fully implantable version of the BD-BCI, (2) perform a series of industrial-standard medical device benchtop tests, and (3) test the implants safety.

The goal of this project is to develop an automated assistive device capable of restoring walking and standing functions in persons with motor impairments. Although research on assistive devices, such as active and passive orthoses and exoskeletons, has been ongoing for several decades, the improvements in mobility have been modest due to a number of limitations. One major challenge has been the limited ability to sense and interpret the state of the human, including volitional motor intent and fatigue. The proposed device will consist of powered electric motors, as well as the power generated by the person's own muscles. This work proposes to develop novel sensors to monitor muscle function, and, muscle fatigue is identified, the system will switch to the electric motors until the muscles recover. Through research on methods of seamless automated control of a hybrid assistive device while minimizing muscle fatigue, this study addresses significant limitations of prior work. The proposed project has the long-term potential to significantly improve walking and quality of life of individuals with spinal cord injuries and stroke. The proposed work will also contribute to new science of cyber-physical systems by integrating wearable image-based biosensing with physical exoskeleton systems through computational algorithms. This project will provide immersive interdisciplinary training for graduate and undergraduate students to integrate computational methods with imaging, robotics, human functional activity and artificial devices for solving challenging public health problems. A strong emphasis will be placed on involving undergraduate students in research as part of structured programs at our institutions. Additionally, students with disabilities will be involved in this research activities by leveraging an ongoing NSF-funded project. This project includes the development of wearable ultrasound imaging sensors and real-time image analysis algorithms that can provide direct measurement of the function and status of the underlying muscles. This will allow development of dynamic control allocation algorithms that utilize this information to distribute control between actuation and stimulation. This approach for closed-loop control based on muscle-specific feedback represents a paradigm shift from conventional lower extremity exoskeletons that rely only on joint kinematics for feedback. As a testbed for this new approach, the team will utilize a hybrid exoskeleton that combines active joint actuators with functional electrical stimulation of a person's own muscles. Repetitive electrical stimulation leads to the rapid onset of muscle fatigue that limits the utility of these hybrid systems and potentially increases risk of injury. The goals of the project are: develop novel ultrasound sensing technology and image analysis algorithms for real-time sensing of muscle function and fatigue; investigate closed-loop control allocation algorithms utilizing measured muscle contraction rates to minimize fatigue; integrate sensing and control methods into a closed loop hybrid exoskeleton system and evaluate on patients with spinal cord injury. The proposed approach will lead to innovative CPS science by (1) integrating a human-in-the-loop physical exoskeleton system with novel image-based real-time robust sensing of complex time-varying physical phenomena, such as dynamic neuromuscular activity and fatigue, and (2) developing novel computational models to interpret such phenomena and effectively adapt control strategies. This research will enable practical wearable image-based biosensing, with broader applications in healthcare. This framework can be widely applicable in a number of medical CPS problems that involve a human in the loop, including upper and lower extremity prostheses and exoskeletons, rehabilitation and surgical robots. The new control allocation algorithms relying on sensor measurements could have broader applicability in fault-tolerant and redundant actuator systems, and reliable fault-tolerant control of unmanned aerial vehicles.