A debris flow monitoring system by means of fiber optic interferometers

2007 ◽  
Author(s):  
Yung-Li Lin ◽  
Ken-Huang Lin ◽  
Wuu-Wen Lin ◽  
Mao-Hsiung Chen
Keyword(s):  
Debris Flow ◽  
Monitoring System ◽  
Fiber Optic ◽  
Flow Monitoring

scholarly journals An Efficient In-Situ Debris Flow Monitoring System over a Wireless Accelerometer Network

2019 ◽  
Vol 11 (13) ◽  
pp. 1512 ◽  
Author(s):  
Jiaxing Ye ◽  
Yuichi Kurashima ◽  
Takeshi Kobayashi ◽  
Hiroshi Tsuda ◽  
Teruyoshi Takahara ◽  
...  
Keyword(s):  
Machine Learning ◽  
Debris Flow ◽  
Monitoring System ◽  
In Situ Monitoring ◽  
Machine Learning Techniques ◽  
Mountainous Area ◽  
Accelerometer Sensor ◽  
Flow Monitoring ◽  
Wireless Accelerometer

Debris flow disasters pose a serious threat to public safety in many areas all over the world, and it may cause severe consequences, including losses, injuries, and fatalities. With the emergence of deep learning and increased computation powers, nowadays, machine learning methods are being broadly acknowledged as a feasible solution to tackle the massive data generated from geo-informatics and sensing platforms to distill adequate information in the context of disaster monitoring. Aiming at detection of debris flow occurrences in a mountainous area of Sakurajima, Japan, this study demonstrates an efficient in-situ monitoring system which employs state-of-the-art machine learning techniques to exploit continuous monitoring data collected by a wireless accelerometer sensor network. Concretely, a two-stage data analysis process had been adopted, which consists of anomaly detection and debris flow event identification. The system had been validated with real data and generated favorable detection precision. Compared to other debris flow monitoring system, the proposed solution renders a batch of substantive merits, such as low-cost, high accuracy, and fewer maintenance efforts. Moreover, the presented data investigation scheme can be readily extended to deal with multi-modal data for more accurate debris monitoring, and we expect to expend addition sensory measurements shortly.

A SOA based debris flow monitoring system

2009 ◽  
Author(s):  
Lan-Kun Chung ◽  
Yao-Min Fang ◽  
Yin-Huei Chang ◽  
Tien-Yin Chou ◽  
B.J. Lee ◽  
...  
Keyword(s):  
Debris Flow ◽  
Monitoring System ◽  
Flow Monitoring

Development of a remotely controlled debris flow monitoring system in the Dolomites (Acquabona, Italy)

2003 ◽  
Vol 17 (9) ◽  
pp. 1771-1784 ◽  
Author(s):  
Pia R. Tecca ◽  
Antonio Galgaro ◽  
Rinaldo Genevois ◽  
Andrea M. Deganutti
Keyword(s):  
Debris Flow ◽  
Monitoring System ◽  
Flow Monitoring

Debris flow monitoring system and observed event in Taiwan: A case study at Aiyuzi River

2007 ◽  
Vol 12 (4) ◽  
pp. 610-618 ◽  
Author(s):  
Taichung Hsiao ◽  
Bingjean Lee ◽  
Tienyin Chou ◽  
Huipain Lien ◽  
Yinghuei Chang
Keyword(s):  
Debris Flow ◽  
Monitoring System ◽  
Flow Monitoring

Nursing Movement Monitoring System Utilizing Hetero-core Fiber Optic Sensors Embedded in Medical Thin Films

2018 ◽  
Vol 138 (12) ◽  
pp. 525-532
Author(s):  
Masahiko Ito ◽  
Yuya Koyama ◽  
Michiko Nishiyama ◽  
Emi Yanagisawa ◽  
Mariko Hayashi ◽  
...  
Keyword(s):  
Thin Films ◽  
Monitoring System ◽  
Fiber Optic ◽  
Fiber Optic Sensors ◽  
Core Fiber ◽  
Movement Monitoring

Design of an IoT-based water flow monitoring system

2020 ◽  
Author(s):  
Zill Ullah Khan ◽  
M Umair Anwar ◽  
Sabah Pirani ◽  
Faisal Lalani ◽  
Babatunde Adegoke ◽  
...  
Keyword(s):  
Monitoring System ◽  
Water Flow ◽  
Flow Monitoring

scholarly journals Development and Preliminary Tests of a Low-Power Automatic Monitoring System for Flexible Debris Flow Barriers

2021 ◽  
Vol 55 ◽  
pp. 1783-1790
Author(s):  
Roberto Savi ◽  
Alessandro Valletta ◽  
Andrea Carri ◽  
Edoardo Cavalca ◽  
Andrea Segalini
Keyword(s):  
Debris Flow ◽  
Low Power ◽  
Monitoring System ◽  
Automatic Monitoring ◽  
Automatic Monitoring System
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