A Flash Flood Categorization System using Scene-Text Recognition

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smartcomp18_bipen.pdf (2.13 MB)

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http://mpsc.umbc.edu/wp-content/uploads/2018/05/smartcomp18_bipen.pdf

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http://hdl.handle.net/11603/11039

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UMBC Information Systems Department
UMBC Faculty Collection

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2018

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conference papers and proceedings preprints
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This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please contact the author.

Subjects

Cyber-Physical System
Smart Environments
Computer Vision
Scene-Text Recognition
Object detection

Abstract

Detecting flash floods in real-time and taking rapid actions are of utmost importance to save human lives, loss of infrastructures, and personal properties in a smart city. In this paper, we develop a low-cost low-power cyber-physical System prototype using a Raspberry Pi camera to detect the rising water level. We deployed the system in the real word and collected data in different environmental conditions (early morning in the presence of fog, sunny afternoon, late afternoon with sunsetting). We employ image processing and text recognition techniques to detect the rising water level and articulate several challenges in deploying such a system in the real environment. We envision this prototype design will pave the way for mass deployment of the flash flood detection system with minimal human intervention.