Vidya Samadi

Clemson University | Assistant Professor

Subject Areas: Hydroinformatics

 Recent Activity

ABSTRACT:

Flood Analytics Information System (FAIS) is a data analytics application funded by the National Science Foundation to integrate crowd intelligence, machine learning, and natural language processing of tweets for flood situational awareness. This national scale prototype combines flood peak rates and river level information with geotagged tweets to identify a dynamic set of at-risk locations to flooding. FAIS can help users to (i) collect georeferenced tweets, traffic and the USGS webcam images in real time to identify at-risk locations, (ii) detect label and score the objects in time-lapse flooded and non-flooded images, and (iii) perform flood frequency analysis (FFA) using various probability distributions with the associated uncertainty estimation to assist engineers in designing safe structures. FAIS is successfully tested in real-time during several hurricane driven flooding events across the south and southeast US where the storms made extensive disruption to critical infrastructure and communities. FAIS is freely accessible to everyone, but primarily designed for real-time and operational use. FAIS video tutorial and educational material are freely available to researchers, students, and professionals via Hydrosystem and Hydroinformatics Research (HHR) group at Clemson University.

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Resources
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Collection 0
Composite Resource 0
Generic 0
Geographic Feature 0
Geographic Raster 0
HIS Referenced Time Series 0
Model Instance 0
Model Program 0
MODFLOW Model Instance Resource 0
Multidimensional (NetCDF) 0
Script Resource 0
SWAT Model Instance 0
Time Series 0
Web App 0
Web App Resource Web App Resource
Flood Analytics Information System (FAIS)
Created: Jan. 16, 2021, 4:14 a.m.
Authors: Samadi, Vidya ยท Jose Vidal

ABSTRACT:

Flood Analytics Information System (FAIS) is a data analytics application funded by the National Science Foundation to integrate crowd intelligence, machine learning, and natural language processing of tweets for flood situational awareness. This national scale prototype combines flood peak rates and river level information with geotagged tweets to identify a dynamic set of at-risk locations to flooding. FAIS can help users to (i) collect georeferenced tweets, traffic and the USGS webcam images in real time to identify at-risk locations, (ii) detect label and score the objects in time-lapse flooded and non-flooded images, and (iii) perform flood frequency analysis (FFA) using various probability distributions with the associated uncertainty estimation to assist engineers in designing safe structures. FAIS is successfully tested in real-time during several hurricane driven flooding events across the south and southeast US where the storms made extensive disruption to critical infrastructure and communities. FAIS is freely accessible to everyone, but primarily designed for real-time and operational use. FAIS video tutorial and educational material are freely available to researchers, students, and professionals via Hydrosystem and Hydroinformatics Research (HHR) group at Clemson University.

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