CIAM-UTC-REG22
Research Team
PI: Tong Qiu, Penn State
Co-PI: Chaopeng Shen, Penn State
Co-PI: Allan M Zarembski, University of Delaware
Project Description
The objective of this study is to develop an artificial intelligence (AI) model for advance landslide warning along railroad tracks in Pennsylvania and Delaware. The objective will be achieved through a collaborative research between researchers from the Department of Civil and Environmental Engineering at The Pennsylvania State University and the Railroad Engineering and Safety Program at University of Delaware. The Penn State team was recently awarded a Google AI Impact Challenge grant (July 2019 – June 2022) from Google.org. The main goal of the Google AI grant is to improve the predictive capability of rainfall-induced landslide hazards. Under the Google AI grant, the Penn State team will: (1) develop and deploy deep learning tools to identify landslide events and compile a landslide database; and (2) create predictive deep learning models to improve the prediction accuracy of where and when landslides occur and the potential impacted areas, based on the compiled database and other data sources, accounting for weather forecasts, topography, landcover, and soil moisture. The proposed UTC project is a natural extension of the Google AI grant. The Penn State team is waiting for Google’s official 3 approval of using a portion of the Google AI grant as matching to support the proposed study (the initial feedback from Google.org on the matching was positive).