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5200 N Lake Rd, Merced, CA 95343https://eecs.ucmerced.edu/
The world is undergoing the largest wave of urban growth in history. Monitoring various infrastructures in an urban system is an important step toward making our city more intelligent and responsive. For example, it is essential to prevent severe damage to infrastructures that may lead to significant human and economic losses. Monitoring the state of aging infrastructure helps detect structural damages in early stages. People have deployed many dedicated sensors (e.g., cameras, motion sensors, etc.) for infrastructure monitoring. However, using a dense set of dedicated sensors is inefficient and costly for large-scale infrastructure monitoring as it requires on-site installation and maintenance of sensors and equipment. To this end, my research introduces the use of interactive ambient vibrations to monitor civil infrastructures in a scalable way. Here the interactive ambient vibrations are measured from non-dedicated sensing platforms (e.g., pre-existing vehicles and telecommunication fiber cables) that interact with civil infrastructures..
Jingxiao Liu is a Ph.D. candidate in the Department of Civil & Environmental Engineering at Stanford University. He received his M.S. in Civil Engineering from Carnegie Mellon University in 2017. His research focuses on structural health monitoring, smart infrastructure systems, and smart city applications using signal processing, data mining, physics-guided machine learning, mobile sensing, and fiber-optic sensing techniques.
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