Detecting Heavy Rain Disaster from Social and Physical Sensor

Tomoya Iwakura, Seiji Okajima, Nobuyuki Igata, Kunihiro Takeda, Yuzuru Yamakage, Naoshi Morita


Abstract
We present our system that assists to detect heavy rain disaster, which is being used in real world in Japan. Our system selects tweets about heavy rain disaster with a document classifier. Then, the locations mentioned in the selected tweets are estimated by a location estimator. Finally, combined the selected tweets with amount of rainfall given by physical sensors and a statistical analysis, our system provides users with visualized results for detecting heavy rain disaster.
Anthology ID:
C18-2014
Volume:
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
63–67
Language:
URL:
https://www.aclweb.org/anthology/C18-2014
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/C18-2014.pdf