Events Calendar

Astani CEE Seminar

Speaker: Dr. Jerome P. Lynch, Anne Voshel and Gerald Nudo CEE Faculty Scholar Associate Professor, Department of Civil and Environmental Engineering and Department of Computer Science, University of Michigan

Talk Title: Compressive Sensing in Asynchronous Wireless Sensor Networks for High-Performance Infrastructure Monitoring

Abstract: Low-cost wireless sensors have been designed for dense instrumentation in civil infrastructure systems to monitor structural responses and estimate structural conditions (i.e., automated structural health monitoring). Ongoing field deployments in operational infrastructure systems have confirmed that wireless sensors can serve as accurate and reliable alternatives to traditional tethered sensors. However, these same deployments have brought to the fore a number of technical challenges that must be adequately addressed before widespread adoption can occur. First, viable long-term energy solutions for wireless sensors remain elusive. Second, wireless communications come with limited communication bandwidths that limit the amount of data that can be communicated by the network in real-time. In this presentation, compressive sensing is explored to resolve some of the aforementioned hurdles of wireless sensor networks including energy consumption and limited communication bandwidths. Compressive sensing exploits signal sparsity in a specific domain to perform accurate signal reconstruction using a smaller set of data than that required by the traditional Nyquist-Shannon criterion. Compressive sensing presents a significant advantage to sensor networks when considering the amount of work saved in the acquisition, storage, and transmission of sensor data. In a wireless sensor network where a premium is placed on energy and transmission bandwidth, the energy efficiency of the compressive sensing framework proves to be an even more valuable asset. In this presentation, two compressive sensing strategies are proposed: compressive sensing of randomly sampled time-history data using the compressive sampling matching pursuits algorithm (CoSaMP) and compressive sensing based on bio-inspired time-frequency decomposition. In both approaches, traditional synchronous sample-transmit data acquisition strategies are abandoned for asynchronous ones. The methods proposed are applied to real structural monitoring data collected from wireless sensor networks installed in full-scale structures.



Biography: Dr. Jerome Lynch is an Associate Professor of Civil and Environmental Engineering at the University of Michigan; he is also holds a courtesy faculty appointment with the Department of Electrical Engineering and Computer Science. Dr. Lynch completed his graduate studies at Stanford University where he received his PhD in Civil and Environmental Engineering in 2002, MS in Civil and Environmental Engineering in 1998, and MS in Electrical Engineering in 2003. Prior to attending Stanford, Dr. Lynch received his BE in Civil and Environmental Engineering from the Cooper Union in New York City. His current research interests are in the areas of wireless cyber-physical systems, cyberinfrastructure tools for management of massive structural monitoring datasets, and nanoengineered thin film sensors for damage detection. Dr. Lynch has been awarded the 2005 ONR Young Investigator Award, 2009 NSF CAREER Award, 2009 Presidential Early Career Award for Scientists and Engineers (PECASE) and 2012 EMI Leonardo da Vinci Award.

Host: Dr. Erik Johnson

Location: Kaprielian Hall (KAP) - 209 Conference Room

Audiences: Everyone Is Invited

Contact: Evangeline Reyes