CPSPI MTG 2014 Posters, Videos and Abstracts
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The SDB project seeks to design, engineer, and evaluate the foundational information substrate for cyberphysical systems in a concrete, canonical form - creation of efficient, agile, model- driven, human-centered building systems. Modern commercial buildings provide increasingly integrated Building Management Systems, but are typically closed or based on proprietary interfaces, are difficult to extend, and it is expensive to add new capabilities.
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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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Our proposed research is motivated by two fundamental challenges that are traditionally studied in separate disciplines. The first key challenge is that in existing digital cameras, the functionalities of a camera are constrained by its size due to the optics and quantum nature of light. It remains a challenge to design a camera architecture that has both - a small form factor and has versatile functionalities, e.g.
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The project focuses on swarming cyber-physical systems (swarming CPS) consisting of a collection of mobile networked agents, each of which has sensing, computing, communication, and locomotion capabilities, and that have a wide range of civilian and military applications. Different from conventional static CPS, swarming CPS rely on mobile computing entities, e.g., robots, which collaboratively interact with phenomena of interest at different physical locations.
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The National Science Foundation established the Cyber-Physical Systems (CPS) program with the vision of developing a scientific and engineering foundation for routinely building cyber-enabled engineered systems in which cyber capability is deeply embedded at all scales, yet which remain safe, secure, and dependable -- "systems you can bet your life on." The CPS challenge spans essentially every engineering domain.
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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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The artificial pancreas (AP) is a set of increasingly sophisticated devices and algorithms that will automate the delivery of insulin to patients with type--1 diabetes. While the AP concept promises to alleviate the burden posed by the self-- management of blood glucose levels, it also poses significant risks arising from a combination of external disturbances such as patient meals, physical activity, sensor errors, network delays and physiological variations.
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We have been developing a novel virtually transparent epidermal imagery (VTEI) system for laparo-endoscopic single-site (LESS) surgery. The system uses a network of multiple, micro wireless cameras and multiview mosaicing technique to obtain a panoramic view of the surgery area. This view provides visual feedback to surgeons with large viewing angles and areas of interest so that the surgeons can improve the safety of surgical procedures by being better aware of where the surgical instruments are relative to tissue and organs.
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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.
