Center for Compressive Sensing Center for Compressive Sensing

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Welcome to the Center for Compressive Sensing

New theory and techniques for processing information received from wireless sensor networks are being investigated for the ultimate purpose of monitoring the nation's infrastructure, including bridges, buildings and related construction. Named, "Sensing Sensors: Compressed Sampling with Co-design of Hardware and Algorithms across Multiple Layers in Wireless Sensor Networks," this new five year, $3M multi-disciplinary research program funded by the National Science Foundation includes a diverse team of faculty in the areas of circuits (Prof. Michael Flynn, Principle Investigator, and Prof.David Wentzloff), systems (Profs. Mingyan Liu and Wayne Stark), mathematics (Prof. Anna Gilbert) and civil and environmental engineering (Prof. Jerry Lynch).

 


The research program is aimed towards development of a revolutionary wireless sensor node, optimized for infrastructure monitoring, and characterized by ultra-low power consumption. Energy efficiency and battery lifetime will be improved through the use of compressed sampling in sensing, physical communication and network communication, and through the co-design of hardware and algorithms. Compressive sampling is an emerging theory which permits radically new sensing devices that simultaneously acquire and compress certain signals using very efficient randomized sensing protocols.

In addition to power consumption, the program will address installation complexity and installation costs, which are significant bottlenecks to the widespread deployment of wireless monitoring of our nation's infrastructure.

 
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University of Michigan College of Engineering Electrical Engineering and Computer Science