DocumentCode
691833
Title
Intelligent Early-Warning System for Landslides Based on the ZigBee Network
Author
Jian Xu ; Yuanhong Wang ; Yu Zhang ; Shushan Yang
Author_Institution
Sch. of Inf. Eng., Hubei Univ. for Nat., Enshi, China
fYear
2013
fDate
21-22 Dec. 2013
Firstpage
187
Lastpage
191
Abstract
For mountain landslide, This paper proposes an intelligent early-warning system for landslides based on ZigBee network. It adopts Cortex-M3 architecture of the chip as the embedded core control processor to improve system integration, data processing capabilities, the ZigBee uses CC2530 as the hardware foundation to construct ZIGBEE wireless sensor network, and then uses GPRS as the technological manner to remotely convey data transmission and early warning information. The results show that the system is completely functional. And it has versatility and good scalability, can overcome the traditional monitoring method of single function which efficiency is low and cost is high, it can effectively achieve the landslide monitoring and prevention of the adverse geological conditions under the mountains.
Keywords
Zigbee; alarm systems; computerised monitoring; data communication; embedded systems; geomorphology; geophysical techniques; geophysics computing; microcontrollers; wireless sensor networks; CC2530; Cortex-M3 architecture; GPRS; ZIGBEE wireless sensor network; data processing capabilities; data transmission; early warning information; embedded core control processor; geological conditions; integration; intelligent early-warning system; landslide monitoring method; mountain landslide; mountains; scalability; single function efficiency; Ground penetrating radar; Logic gates; Monitoring; Terrain factors; Wireless communication; Wireless sensor networks; Zigbee; Displacements; Early Warning; Inclination; Landslide; Water level; Wireless Sensor Networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Dependable, Autonomic and Secure Computing (DASC), 2013 IEEE 11th International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-3380-8
Type
conf
DOI
10.1109/DASC.2013.60
Filename
6844360
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