Coordinating individual systems to function dynamically and simultaneously in all situations.
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Effective response and adaptation to the physical world, and rigorous management of such behaviors, are mandatory features of cyber-physical systems (CPS). However, achieving such capabilities across diverse application requirements surpasses the current state of the art in system platforms and tools. Existing systems do not support the expression, integration, and enforcement of such properties that span cyber and physical domains.
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The aims of this project are to contribute the fundamental physical and algorithmic building blocks of a novel cyber--physical two--way communication platform designed to enable accurate training and monitoring of canines. The project efforts lie at the intersection of computer science, electrical engineering, and veterinary behavior.
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Researchers from the University of Illinois at Urbana-Champaign in collaboration with physicians and nurses from Intensive Care Unit, Carle Foundation Hospital are developing a new initiative on engineering next generation of medical systems. This project is part of the initiative and focuses on exploring the efficient and safe operation of integrated Emergency Cyber Physical Human (ECPH) systems in emergency scenarios from the Intensive Care Unit (ICU) environment. The key requirements are:
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The goals of this project include the development of real-time control for human-machine co-control of highly dynamic and potentially dangerous systems. The work focuses on formalizing the automated assessment of trust, primarily focusing on the degree to which a computer should trust a human operator. We are focusing on two experimental tasks: a) a crane operation task, where control in automation settings requires a highly skilled operator, and b) rehabilitation and training tasks.
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This project focuses on the formal design of semi-autonomous automotive Cyber Physical Systems (CPS). Rather than disconnecting the driver from the vehicle, the goal is to obtain a vehicle where the degree of autonomy is continuously changed in real-time as a function of certified uncertainty ranges in driver behavior and environment reconstruction.
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The aim of this project is to lay down the foundations of a novel approach to real-time control of networked cyber-physical systems (CPS) that leverages their cooperative nature. Most networked controllers are not implementable over embedded digital computer systems because they rely on continuous time or synchronous executions that are costly to enforce.
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Optimization algorithms used in a real-time and safety-critical context offer the potential for considerably advancing robotic and autonomous systems by improving their ability to execute complex missions. However, this promise cannot happen without proper attention to the considerably stronger operational constraints that real time, safety-critical applications must meet, unlike their non-real-time, desktop counterparts.
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Traditionally, buildings have been viewed as mere energy consumers; however, with the new power grid infrastructure and distributed energy resources, buildings can not only consume energy, but they can also output energy. As a result, this project removes traditional boundaries between buildings in the same cluster or between the cluster and power grids, transforming individual smart buildings into NetZero building clusters enabled by cyber-support tools.
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This project has introduced a programming language, compiler, and runtime environment that enables software to control a "cyber-physical" microfluidic device in which integrated sensors and video monitoring equipment form a closed feedback loop (a). The technical contributions of the project include the design and implementation of the language, and a detailed description of the algorithms built into the compiler to enable fast decision-making in real-time in response to sensory feedback (b).
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Intensity modulated radiation therapy (IMRT) requires tight coordination between computational systems and the physical devices that deliver the prescribed treatment plan, making it a perfect example of cyber-physical system. The current approach to addressing tumor motion in radiation therapy is to treat it as a problem and not as a therapeutic opportunity. Existing treatment planning methods attempt to create dose distributions that are at best dosimetrically equivalent to the static case.
