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Dataset . 2020
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ZENODO
Dataset . 2020
License: CC BY
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NYU FloodSense street sign mounted distance sensor

Authors: Sai Venkat Challagonda, Praneeth; Mydlarz, Charlie; Henaff, Elizabeth; Silverman, Andrea; Brain, Tega; Khan, Junaid;

NYU FloodSense street sign mounted distance sensor

Abstract

Ultrasonic distance data in mm from a sensor mounted on a street sign post at the corner of 5th Street and Hoyt, Brooklyn, NY (40.676640, -73.994595). The sensor is designed to detect flood water that fills the street and blocks vehicle and pedestrian traffic, as well as depositing micro-organisms on the street. The sensor transmits its data via LoRaWAN and is equipped with a solar panel for continuous operation. Data is collected at ~5min intervals. Time fields are in local time (New York). Two types of erroneous data has been observed: Large spikes in distance that always manifest at 5000mm - can be excluded There are ~1% rises in distance measures on days with sun which suggests that the distance sensor is affected by direct sunlight This data is prelimary and is for prototyping purposes. Not to be used as a reliable data source as it is. This dataset will be updated when more data is collected. Please see our github org for sensor information and build instructions: github.com/floodsense

https://github.com/floodsense

Related Organizations
Keywords

flood, water depth, distance, urban, street level

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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