2018

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Visible to the public Events of Interest Capture Using Novel Body-worn Fully-passive Wireless Sensors for S&CC

Abstract: 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.

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Visible to the public Enabling Smart Underground Mining with an Integrated Context-Aware Wireless Cyber-Physical Framework

o 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.

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Visible to the public Enabling Real-time Dynamic Control and Adaptation of Networked Robots in Resource-constrained and Uncertain Environments

Overview: Near-real-time water-quality monitoring in rivers, lakes, and water reservoirs of different physical variables is critical to prevent contaminated water from reaching the civilian population and to deploy timely solutions, e.g., to withdraw water from a treatment plant in the case of an emergency (caused by an accident or a terrorist attack) or at least to issue early warnings so to save damage to human and aquatic life. To make optimal decisions and "close the loop" promptly, it is necessary to collect, aggregate, and process real-time water data.

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Visible to the public Enabling Multimodal Sensing, Real-time Onboard Detection and Adaptive Control for Fully Autonomous Unmanned Aerial Systems

The goal of this proposed research project is to achieve true onboard autonomy in real time for small UAVs in the absence of remote control and external navigation aids. Three major areas have been explored. In the area of UAV flight control, an automatic trajectory generation framework is developed. It consists of waypoint planning at upper level and LQR based trajectory generation in the lower level. The Deep reinforcement learning based framework reduces the control trust by more than 15% with much less computing complexity compared to state-of-the-art approaches.

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Visible to the public Enabling “White-Box” Autonomy in Medical Cyber-Physical Systems

In pursuit of the long-term goal of enabling interpretable "white-box" autonomy in healthcare, the goal of this project is to investigate physiological modeling, coordinated and resilient multivariable closed-loop control, and regulatory science methodologies for white-box autonomy, as well as to illustrate its application to an important critical care scenario of circulatory resuscitation. The idea of introducing autonomy to the healthcare domain is not new. However, prior autonomy capabilities have not been suitably mature for real-world critical care, due to the limitations a

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Visible to the public Emerging Markets and Myopic Decision-Making in Multi-Modal Transportation Systems- Models and Validation

This project aims to create high-fidelity models, validated with real-world data, of mixed-mode travel decisions and emerging mobility markets. A growing subset of travelers make decisions informed by apps that optimize (mixed-mode) routes based on user-defined preferences. Locally optimized solutions tend to cause inefficiencies that are exacerbated by risk-sensitivity (arising from en-dogenous and exogenous uncertainties) in travelers.

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Visible to the public Elevating the Edge to be a Peer of the Cloud

Abstract: The surge of cyber-physical systems around us has led to the emergence of novel use-cases like smart surveillance and smart cars. These use-cases either involve high amounts of machine-to-machine communication or are highly interactive, making low-latency response to events critically important. Traditional cloud computing paradigm is unsuitable for such applications due to high network latency to datacenters, leading to the emergence of the edge computing paradigm.

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Visible to the public Efficient Traffic Management- A Formal Methods Approach

This project is developing tools for traffic management and control using formal methods. By applying techniques such as model-checking and correct-by-construction synthesis, we ensure that traffic flow satisfies high-level objectives expressed using temporal logics that guarantee desirable behavior such as avoiding congestion, maintaining high throughput, ensuring fairness of ramp metering strategies, and reacting to incidents or unexpected conditions.

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Visible to the public Dynamic Methods of Traffic Control that Impact Quality of Life in Smart Cities

Traffic control management strategies have been largely focused on improving vehicular traffic flows on highways and freeways but arterials have not been used properly and pedestrians are mostly ignored. New urban arterial designs encourage modal shifts which gives further impetus to devise novel traffic control strategies to more quickly respond to changing conditions and salient events, while balancing safety and efficiency for all users.