DATA-DRIVEN STREET FLOOD WARNING SYSTEM

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United States of America Patent

APP PUB NO 20240135797A1
SERIAL NO

18485217

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Abstract

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A data-driven street flood warning system that employs distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) and machine learning (ML) technologies and techniques to provide a prediction of street flood status along a telecommunications fiber optic cable route using the DFOS/DAS data and ML models. Operationally, a DFOS/DAS interrogator collects and transmits vibrational data resulting from rain events while an online web server provides a user interface for end-users. Two machine learning models are built respectively for rain intensity prediction and flood level prediction. The machine learning models serve as predictive models for rain intensity and flood levels based on data provided to them, which includes rain intensity, rain duration, and historical data on flood levels.

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NEC LABORATORIES AMERICA INC4 INDEPENDENCE WAY SUITE 200 PRINCETON NJ 08540

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  • 2023 Application Filing Year
  • G08B Class
  • 1602 Applications Filed
  • 627 Patents Issued To-Date
  • 39.14 % Issued To-Date
Click to zoom InYear of Issuance% of Matters IssuedCumulative IssuancesYearly Issuances2023202420250255075100

Inventor(s)

Inventor Name Address # of filed Patents Total Citations
DING, Yangmin East Brunswick, US 33 10
OZHARAR, Sarper Pennington, US 40 20
TIAN, Yue Princeton, US 73 180
WANG, Ting West Windsor, US 763 6307

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Citation count rangeNumber of patents cited in rangeNumber of patents cited in various citation count ranges339118901 - 10020040060080010001200140016001800200022002400260028003000320034003600

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