Patients with chronic illness require frequent and avoidable hospital visits. This project aims to develop a new class of battery-less, low-cost, disposable, wireless electronic patch sensors to monitor a variety of physiological signals and a custom smartphone app to monitor their health status and to elect to share their anonymized events-of-interest with their community towards a smart and connected community (S&CC). To achieve these aims, the interdisciplinary research team is collaborating with the non-profit McKendree District of the United Methodist Church located in the greater Memphis community to complete this work. This will empower users, permit the community stakeholders to assess population health status, reduce the need for frequent hospital visits, and help identify potential individual and community actions to achieve improvement in health status. The project also involves the training of undergraduate and graduate students in interdisciplinary research activities on emerging technologies, and is expected to impact public and private sector efforts to improve healthcare. A smart and connected community (S&CC) will utilize distributed sensors and embedded computing to seamlessly generate meaningful interpretations that would be of greater benefit to individuals, the community, and society, in general, through improved health and safety, efficient public infrastructure, and better access to needed services. Although rapidly emerging mobile health technology is already tapping into widely used smartphone infrastructure, data collection using smartphone mobile devices is currently limited by few integrated sensors (e.g., Inertial measurement unit (IMU), camera, optical sensors, temperature sensor, and GPS). There are tremendous opportunities to advance the smart and connected communities by incorporating capabilities from external battery-less sensors into this framework to enable data collection and analysis for broader personal and community gain. Towards this goal, this research will (1) deliver a platform of fully-passive wireless electronic patch sensors for physiological data collection and to incorporate multimodal sensor data, (2) develop an open-source framework for meaningful and reliable Events-of-Interest (EoI) detection using a custom smartphone app for self-monitoring and communal sharing, and (3) deploy the sensors in a "Living Lab" for a pilot study to collect and classify these data in real-time to generate EoIs for various health conditions, such as arrhythmia, asthma, and sleep disorder.

This Smart and Connected Communities research project focuses on developing an innovative solution for enabling emergency communications during disaster recovery. An aerial base station can substitute for a damaged cell tower and provide cellular connectivity among the first responders and citizens who were impacted by a natural or manmade disaster until the damaged cell tower is restored. The project will lead to fundamental understanding of the science and engineering aspects of the design and deployment of aerial base stations. It will result in a proof-of-concept for a deployable communication system. Aerial base stations have the advantage of higher altitude compared to regular cell towers. They provide better coverage and connectivity to the users. They can be deployed more quickly after a disaster when compared to Cells on Wheels which are traditionally deployed by cellular providers during disaster recovery. This project addresses the capability to quick deploy a communication system, which is a technology gap in today's emergency communication systems. The proposed research investigates efficient strategies for providing cellular coverage in areas where the coverage is not available or lost due to loss of cell towers. It brings the network closer to the disaster victims and relays the voice calls and data between the first responders and victims. The immediate need for quickly deployable communication systems during disaster recovery times makes this project a high-risk and high-reward project. Graduate and undergraduate students, who are participating in this research project will gain hands-on experience in developing innovative solutions for communities effected by disasters. This smart and connected community project engages local communities including the Fire Department and the Civil Air Patrol in the City of Denton, Texas, as well as private organizations in Telecommunications and Aviation industry. The project will be demonstrated in two phases during the Global City Team Challenge Exhibitions (2016 and 2017) organized jointly by the U.S. Ignite and the National Institute of Standards and Technology.

Complex, networked, distributed cyber-physical systems (CPSs) are emerging in many safety-critical application domains such as aerospace and automotive. Design of such systems heavily relies on insights and experiences of engineers as principled design methodologies that can cope with the complexity of these systems are lacking. As a result, extensive testing and fine-tuning is required to ensure that the final product satisfies the design objectives. As a principled alternative, this project proposes to use modularity for managing complexity during both the design- and the life-cycles of cyber-physical systems. The objective is to develop the scientific foundation and associated algorithmic tools for the design of modular cyber-physical control systems. If successful, in the long-run this research will lead to a "plug and play" integration framework for CPSs supported by automated design tools, where one can replace a subsystem with another one or perform upgrades to subsystems while maintaining operational correctness guarantees. Results from this research will be relevant to many application domains, including next generation air vehicles, automotive systems and robotics. Its potential transformative impact will be on the way CPSs in these domains are designed and operated. Translation to the economy will proceed by actively seeking and engaging industrial partners. This research effort will be complemented by an education plan where interdisciplinary research and thinking in the area of CPS will be fostered among undergraduate and graduate students to prepare the next generation of CPS researchers and practitioners. To be specific, the project will develop theoretical foundations and associated algorithmic tools for distributed synthesis of provably correct control protocols that give rise to compositional design principles for cyber-physical control systems. In particular, algorithms for decompositions of system requirements at the discrete/logic level and of the system states at the continuous/system level will be developed. The main idea is a novel separation between external and internal factors affecting each subsystem that allows internal interactions required for the successful operation of a subsystem to be computed explicitly. These internal interactions, namely interface rules, are captured in terms of assumption and guarantee pairs that are used for solving local synthesis problems to obtain local controllers in a distributed manner, while maintaining global correctness guarantees when these controllers are deployed simultaneously. The modularity-performance trade-off space will be explored by introducing proper partial orders on these interface rules and by tuning the complexity of the interface rules according to these order relations. Tools from control theory (decentralized and robust control, model reduction, discrete event systems) and formal methods (temporal logics, compositional verification, distributed reactive synthesis) will be brought to bear to address these problems.

This project seeks to develop logical foundations for cyber-physical systems (CPS), i.e., systems that combine cyber aspects such as communication and computer control with physical aspects such as movement in space. CPS applications abound. Ensuring their correct functioning, however, is a serious challenge. Scientists and engineers need analytic tools to understand and predict the behavior of their systems. This is the key to designing smart and reliable control. By providing such analytic foundations, this project addresses an intellectual grand challenge that has substantial scientific, economical, societal, and educational impact arising from the benefits of improved CPS analysis and design. In order to tame their complexity, this project studies CPS as multi-dynamical systems, i.e., in terms of the elementary dynamical aspects of their parts. Multi-billion dollar industries spend 50% of the development cost on control software design and testing. This cannot be sustained any longer. The foundations of computer science have revolutionized our society. We need even stronger foundations when software interacts with the physical world. Multi-dynamical systems concepts provide a unifying principle for education and enable students to focus on one dynamical aspect at a time without missing the big picture. They overcome the divide between computer science and engineering that keeps causing irreconcilable differences among design teams. This project develops cross-departmental graduate/undergraduate courses on Mathematical Foundations of CPS as prime examples of STEM integration. Long-term goals include a K-12 outreach that inspires young people to pursue science careers through an early exposure to both mathematical beauty and exciting societal challenges. CPS foundations excel in demonstrating the paramount importance of discrete and continuous mathematics, not as separate disciplines, but well-integrated.

Cyber-physical systems (CPSs) have become pervasive in the modern society, enabling transformative applications in the transportation, healthcare and energy sectors. However, the reliable development of CPSs remains an outstanding challenge. At the design level, hybrid systems theory provides a rich set of techniques and tools for ensuring correctness of high level functional properties such as safety and liveness. Current analysis techniques at the implementation level focus primarily on detecting low level runtime errors such as buffer overflows and divide by zero. A holistic approach to verifying functional specifications will considerably enhance the reliability scenario of CPSs development. This project investigates a robust verification methodology that guarantees functional correctness of the implementation by a "deeper" analysis on the design. More precisely, robust verification not only ensures that a design satisfies a given specification, but that small perturbations in the design still satisfy the specification. The perturbations on the design account for the deviations in the implementation with respect to the actual system. The proposed research investigates new foundations, abstractions and verification algorithms for robust analysis, in light of novel quantitative and/or topological aspects of robustness. In addition, prototype tools are developed to enable practical application and evaluation. The successful completion of the research will advance the knowledge in the fields of formal methods and hybrid control systems by leveraging ideas from control theory, dynamical systems theory, optimization theory and satisfiability modulo theory. New cross-disciplinary courses at the undergraduate and graduate levels in hybrid control system design and analysis will be developed and taught. Activities for pre-college students involving programming with physical systems will be conducted towards increasing their interest in STEM related careers. Undergraduates, especially those from minority and underrepresented groups, will be recruited and mentored through involvement in research and outreach activities. The success of this research will force a quantum jump in the existing verification methodologies for CPSs, in particular, in the domains of automotive and aerospace systems, by bridging the gap in the analyses at the design and implementation phases.

Crime is a major problem in many urban communities. This project focuses on developing a framework for increased security and crime prevention in crime-prone environments by identifying and integrating hitherto disaggregated heterogeneous data and analyzing the causal and spatio-temporal interconnections between constituent parts of a connected community including environmental aspects (i.e., traffic, lighting, poverty levels, business proximity such as banks/ATMs), crime history, and social events. While existing crime prediction and prevention methods focus on the location of the crimes to detect ``hot-zones'', this project takes a fundamentally different, data-driven approach towards integrated multi-scale data analytics for identifying the characteristics and features of crime-prone environments. This high-risk high-payoff project research is based on real-time crime data and interactions with crime prevention and safety agencies. By revealing the connections between crime and environmental, social, and economic factors, this research aims to demonstrate the critical need of an integrated systems approach to crime prevention, instead of focusing on post-crisis management. This interdisciplinary endeavor of developing computational methods for crime prevention across public urban landscapes requires the combination of data mining and statistical methods in space and time to extract useful features and discover models from passive data sets. The proposed project will develop 1) new tools for the fundamental understanding of criminal behavior by analyzing the time varying and location-specific systems and patterns observed as a result of complex processes between interacting cyber-physical entities, and 2) scalable data-driven Nowcasting algorithms for crime prediction that will adapt with the constantly evolving state of criminal activity by continuously learning from a rich set of spatial and demographic features, including traffic, spatial attributes, socio-economic characteristics of neighborhoods, and current time, as well as context. To enable continuous forecasting over streaming data, while maintaining high prediction accuracy and low time complexity, the project will develop and train crime prediction artificial neural networks (CANN) for prediction across space and time. The output of the proposed data-driven models will feed a novel multi-objective optimization formulation that will be used for the integrated optimization of personnel positioning, patrol scheduling and safest route calculation. The resulting decision support environment, will be transferred to the USC Department of Public Safety (DPS), the Los Angeles Police Department (LAPD), and South Park Business Improvement District (SPBID) for integration with their systems to enable decision makers to choose the best course of action at any given time. This project will lead to the development of technology for crime prevention that will be directly applicable to smart and connected communities across the US, with the potential to bring together white and blue-collar residents from mixed urban communities- college campus residents, off-campus neighborhood residents and businesses with their employees, transiting commuters and law enforcement under the theme of making the communities quantifiably more secure. The project will leverage the USC Living Laboratory, a unique ?city within a city? campus and its adjacent neighborhoods as a real-world use case of a connected community of interrelated infrastructures.

Distributed Data Analytics for Real-Time Monitoring and Detection of Flash Floods in Smart City Nirmalya Roy, University of Maryland Baltimore County Storms and floods cause 70% of the world's natural disasters. These natural disasters affect on average up to 200 million people in a year, with economic losses between US$50 billion to US$100 billion annually. Monitoring these flash flood prone areas proactively in populated areas and providing just-in-time notification to the city officials can help in effectively prioritizing, controlling, and mitigating such disastrous events. Solving flash floods problems helps improve the flow of traffic, reduce traffic congestion, environmental hazards, and formation of stagnant water, and prevent damages of any surrounding properties, premises, and loss of lives. This project is building a portable wireless sensor network-based hardware system to monitor the rising level of water, designing distributed predictive data analytics algorithms with human in the loop, and providing smartphone based real time notifications to city officials. The project proposes to integrate human observations from micro-blogging feeds to forecast the manifestation of the flood events by considering real-time contextual information of the target event. The project will be deployed in several flash flood prone areas in Ellicott City and Baltimore City in partnership with the Howard County and Baltimore County local government officials. The research will pursue the junction of wireless sensor networks based data analytics and real-time social network data such as tweets. First, the project aims to build predictive data analytics techniques to forecast the severity of flash floods. Second, the project investigates the appropriateness, and representation of micro-blogging services, and feeds from social network sites associated with real-time flash flood events. Third, the project augments the multi-modal sensor-based data analytics model with human generated facts and observations from micro-blogging services. We engineer its deployment for detecting and assessing the emergent flood situation in real environments. The PI team is collaborating with city partners to measure and compare the key performance improvements over existing municipal systems or protocols in practice and the viability of the proposed system for practical city usage and demonstration as part of the Global City Team Challenge program.

This NSF Cyber-Physical Systems (CPS) Frontier project "Verified Human Interfaces, Control, and Learning for Semi-Autonomous Systems (VeHICaL)" is developing the foundations of verified co-design of interfaces and control for human cyber-physical systems (h-CPS) --- cyber-physical systems that operate in concert with human operators. VeHICaL aims to bring a formal approach to designing both interfaces and control for h-CPS, with provable guarantees. The VeHICaL project is grounded in a novel problem formulation that elucidates the unique requirements on h-CPS including not only traditional correctness properties on autonomous controllers but also quantitative requirements on the logic governing switching or sharing of control between human operator and autonomous controller, the user interface, privacy properties, etc. The project is making contributions along four thrusts: (1) formalisms for modeling h-CPS; (2) computational techniques for learning, verification, and control of h-CPS; (3) design and validation of sensor and human-machine interfaces, and (4) empirical evaluation in the domain of semi-autonomous vehicles. The VeHICaL approach is bringing a conceptual shift of focus away from separately addressing the design of control systems and human-machine interaction and towards the joint co-design of human interfaces and control using common modeling formalisms and requirements on the entire system. This co-design approach is making novel intellectual contributions to the areas of formal methods, control theory, sensing and perception, cognitive science, and human-machine interfaces. Cyber-physical systems deployed in societal-scale applications almost always interact with humans. The foundational work being pursued in the VeHICaL project is being validated in two application domains: semi-autonomous ground vehicles that interact with human drivers, and semi-autonomous aerial vehicles (drones) that interact with human operators. A principled approach to h-CPS design --- one that obtains provable guarantees on system behavior with humans in the loop --- can have an enormous positive impact on the emerging national ``smart'' infrastructure. In addition, this project is pursuing a substantial educational and outreach program including: (i) integrating research into undergraduate and graduate coursework, especially capstone projects; (ii) extensive online course content leveraging existing work by the PIs; (iii) a strong undergraduate research program, and (iv) outreach and summer programs for school children with a focus on reaching under-represented groups.

Recently there is an increasing availability of smart wearables including smart watches, bands, buttons and pendants. Many of these devices are part of human-in-the-loop Cyber Physical Systems (CPS). With future fundamental advances in the intersection of communications, control, and computation for these energy and resource limited devices, there is a great potential to revolutionize many CPS applications. Examples of possible applications include detecting and controlling hand washing to prevent transmission of infections or bacteria, monitoring and using interventions to keep factory workers safe, detecting activities in the home for monitoring the elderly, and improving rehabilitation of stroke victims via controlled exercises. However, to date, much of the work on wearables concentrates on only sensing, collecting and presenting data. For use in CPS it is necessary to consider the increased use of new sensing modalities, to apply feedback to close the control loop, and to focus on the fundamental issues of how both the environment and human behavior affect the cyber. In particular, since humans are intimately involved with wearables it is necessary to increase understanding of how human behaviors affect and can be affected by the control loops and how the systems can maintain safety. This work develops generic underlying algorithms for processing smart wearable data rather than one-off solutions, it extends the understanding and control of wearable systems by addressing humans-in-the-loop behaviors, and it explicitly focuses on the impact of the environment and human behavior on the cyber. Novel ideas are proposed for each of these areas along with a structure for their integration. For example, the algorithmic approach to support more robust, accurate and efficient activity recognition using wearable devices is based on five fundamental concepts: (i) Direction Agnostic Modeling, (ii) Direction Aware Modeling, (iii) Spatial Reachability, (iv) Spatiotemporal Segmentation, and (v) Dynamic Space Time Warping. For dealing with humans-in the-loop behaviors, Model Predictive Control (MPC) is extended to semantic based MPC. This solves control problems that are not amenable to electromechanical laws and employs machine learning. Many CPS projects do not explicitly address how the uncertain world affects how the cyber must be developed in order to perform robustly and safely. A new *-aware software development paradigm focuses on physical-cyber CPS issues as central tenets and that serves as an integrating platform for all the proposed work. The *-aware paradigm focuses on how software must be made robust to handle the physical world, while meeting safety and adaptability requirements

This project aims to enable cyber-physical systems that can be worn on the body in order to one day allow their users to touch, feel, and manipulate computationally simulated three-dimensional objects or digital data in physically realistic ways, using the whole hand. It will do this by precisely measuring touch and movement-induced displacements of the skin in the hand, and by reproducing these signals interactively, via new technologies to be developed in the project. The resulting systems will offer the potential to impact a wide range of human activities that depend on touch and interaction with the hands. The project seeks to enable new applications for wearable cyber physical interfaces that may have broad applications in health care, manufacturing, consumer electronics, and entertainment. Although human interactive technologies have advanced greatly, current systems employ only a fraction of the sensorimotor capabilities of their users, greatly limiting applications and usability. The development of whole-hand haptic interfaces that allow their wearers to feel and manipulate digital content has been a longstanding goal of engineering research, but has remained far from reality. The reason can be traced to the difficulty of reproducing or even characterizing the complex, action-dependent stimuli that give rise to touch sensations during everyday activities. This project will pioneer new methods for imaging complex haptic stimuli, consisting of movement dependent skin strain and contact-induced surface waves propagating in skin, and for modeling the dependence of these signals on hand kinematics during grasping. It will use the resulting fundamental advances to catalyze the development of novel wearable CPS, in the form of whole-hand haptic interfaces. The latter will employ surface wave and skin strain feedback to supply haptic feedback to the hand during interaction with real and computational objects, enabling a range of new applications in VR. The project will be executed through research in three main research areas. In the first, it will utilize novel contact and non-contact techniques based on data acquired through on-body sensor arrays to measure whole-hand mechanical stimuli and grasping kinematics at high spatial and temporal resolution. In a second research area, it will undertake data-driven systems modeling and analysis of statistical contingencies between the kinematic and cutaneous sensed during everyday activities. In a third research area, it will engineer and perceptually evaluate novel cyber physical systems consisting of haptic interfaces for whole hand interaction. In order to further advance the applications of these systems in medicine, through a collaboration with the Drexel College of Medicine, the project will develop new methods for assessing clinical skills of palpation during medical examination, with the aim of improving the efficacy of what is often the first, most common, and best opportunity for diagnosis, using physician's own sense of touch.