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Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring
Joint Authors
Xu, Zhaozhuo
Pu, Fangling
Fang, Xin
Fu, Jing
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-11-23
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Wireless sensor networks are proved to be effective in long-time localized torrential rain monitoring.
However, the existing widely used architecture of wireless sensor networks for rain monitoring relies on network transportation and back-end calculation, which causes delay in response to heavy rain in localized areas.
Our work improves the architecture by applying logistic regression and support vector machine classification to an intelligent wireless sensor node which is created by Raspberry Pi.
The sensor nodes in front-end not only obtain data from sensors, but also can analyze the probabilities of upcoming heavy rain independently and give early warnings to local clients in time.
When the sensor nodes send the probability to back-end server, the burdens of network transport are released.
We demonstrate by simulation results that our sensor system architecture has potentiality to increase the local response to heavy rain.
The monitoring capacity is also raised.
American Psychological Association (APA)
Xu, Zhaozhuo& Pu, Fangling& Fang, Xin& Fu, Jing. 2016. Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring. Journal of Sensors،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1110456
Modern Language Association (MLA)
Xu, Zhaozhuo…[et al.]. Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring. Journal of Sensors No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1110456
American Medical Association (AMA)
Xu, Zhaozhuo& Pu, Fangling& Fang, Xin& Fu, Jing. Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring. Journal of Sensors. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1110456
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1110456