National CPS PI Meeting 2015
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Abstract:
Data-driven intelligence is an essential foundation for physical systems in transportation safety and efficiency, area surveillance and security, as well as environmental sustainability. While sophisticated data analysis and synthesis can be well supported in large data centers, future intelligent systems require on-the-scene processing with faster responses and less dependence on the unreliable (often wireless) data communications in the field.
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The goal of this project is to demonstrate that new cyber physical architectures will enable closed-loop sensor networks to be shared among multiple applications. This aids in dynamically allocating sensing and computing resources necessary to analyze sensor data and perform sensor actuation. Existing closed-loop sensor networks are based on dedicated, ``stove-pipe'' architectures, that prevent the sharing of these networks.
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One of the challenges for the future cyber-physical systems is the exploration of large design spaces. Genetic algorithms (GAs), which embody a simplified computational model of the mutation and election mechanisms of natural evolution, are known to be effective for design optimization. However, the traditional formulations are limited to choosing values for a predetermined set of parameters within a given fixed architecture.
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This project will design next-generation defense mechanisms to protect critical infrastructures, such as power grids, large industrial plants, and water distribution systems. These critical infrastructures are complex primarily due to the integration of cyber and physical components, the presence of high-order behaviors and functions, and an intricate and large interconnection pattern.
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This project addresses highly dynamic Cyber-Physical Systems (CPSs) understood as systems where a computing delay of a few milliseconds or an incorrectly computed response to a disturbance can lead to catastrophic consequences. Such is the case of advanced safety systems on passenger cars, unmanned air vehicles performing critical maneuvers such as landing, or disaster and rescue response bipedal robots rushing through the rubble to collect information or save human lives.
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Transit hub is a city scale smart phone application that provides real-time, contextual transit travel planning services. It uses a centralized decision support system for integrating the different sensor data streams including the automated vehicle locator, the usage data gathered from the application, and other related data streams that are publically available.
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Project Description
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Rapid industrialization and increased pollution impose severe threats to the availability and quality of water resources worldwide. Currently, many wastewater treatment plants are discharging treated wastewater containing significant amounts of nutrients, such as nitrogen, ammonium, and phosphate ions, directly into the water system, posing significant threats to the environment. Finding a solution for effective treatment and safe discharge of wastewater has become an urgent and challenging task.
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Despite the contributions of automation to vehicular (aircraft, automobile, etc.) safety and efficiency, the problems associated with technology-centered rather than human-centered automation are well known: decreased operator situation awareness, deterioration of manual control skills, difficulties operators experience when trying to jump into the loop when needed, and so forth.