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Data Analytics/Machine Learning

New Paper on Near Real-Time Heatmap Visualization of Roadway Activity Using Distributed Acoustic Sensing

New Paper on Near Real-Time Heatmap Visualization of Roadway Activity Using Distributed Acoustic Sensing

A new paper titled “Near real-time heatmap visualization of roadway activity using distributed acoustic sensing” has been published in Transportation Research Interdisciplinary Perspectives. The paper is authored by Jaewon Saw, Victor Yartsev, Chuao Dong, Peter G. Hubbard, and Kenichi Soga. The stud…

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Pajaro Hydro-Twin Project

Pajaro Hydro-Twin Project

Creating a collaborative and evolving digital twin for diverse flood management applications in face of climate change The Pajaro Hydro-Twin Project is a collaboration between the UC Berkeley Center for Smart Infrastructure and the Vienna Research Center for Visual Computing (VRVis GmbH) in Austria.…

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Smart City Technology Adoption

Smart City Technology Adoption

This project examines technology adoption by the cities, counties, and other local government agencies that manage infrastructure.  Which types of institutions are more likely to adopt new technologies and why?  Which technologies are more likely to be adopted? How do those managing infras…

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EBMUD – Water Network Resiliency Evaluation

EBMUD – Water Network Resiliency Evaluation

CSI has collaborated with the EBMUD to deploy AI/ML techniques to improve water distribution network resiliency. This is a rapidly developing sector of CSI+EBMUD collaboration! 1) Investigating the Effects of Operational and Environmental Factors on Water Distribution Pipeline Failures using Surviva…

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Sixense / Enzan / Kajima – AI/ML for TBM Tunneling

Sixense / Enzan / Kajima – AI/ML for TBM Tunneling

CSI has collaborated with notable entities in the Tunneling & Underground Construction industry: Sizense, Enzan Koubou, and Kajima to implement AI/ML techniques to improve TBM tunneling. 1) Supervised geologic interpretation based on TBM data This research aims to develop a supervised system for…

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