Slope disaster monitoring and early warning system based on 3D-MEMS and NB-IoT

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI:10.1109/IAEAC47372.2019.8997685

M. Xie, Zheng He, Lei Liang, Zhixiang Wu, G. Sun

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引用次数: 5

Abstract

Slope disasters are extremely destructive and pose a serious threat to human life and property safety. The conventional communication method (2G/3G/4G) of slope disaster monitoring has large power consumption and high cost. In addition, the warning indexes for slope instability are single and inaccurate. In order to solve the above problems, this paper develops an automatic monitoring and early warning system based on 3D-MEMS acceleration sensing and NB-IoT transmission technology. It includes intelligent sensor acquisition subsystem, data transmission subsystem, photovoltaic self- powered subsystem, data reception and analysis subsystem. Moreover, the successful on-site application of the Hong'en Temple Tunnel entrance slope in Chongqing, China, shows that the system can stably collect and transmit multi-source monitoring data, and the data change trend is consistent with the slope actual state. This system provides multi-source early warning indexes acquisition method and new data transmission scheme for slope disasters.

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基于3D-MEMS和NB-IoT的边坡灾害监测预警系统

边坡灾害具有极大的破坏性，对人类生命财产安全构成严重威胁。传统的边坡灾害监测通信方式(2G/3G/4G)功耗大，成本高。此外，边坡失稳预警指标单一且不准确。为了解决上述问题，本文开发了一种基于3D-MEMS加速度传感和NB-IoT传输技术的自动监控预警系统。它包括智能传感器采集子系统、数据传输子系统、光伏自供电子系统、数据接收与分析子系统。此外，重庆洪恩寺隧道入口边坡的成功现场应用表明，该系统能够稳定地采集和传输多源监测数据，且数据变化趋势与边坡实际状态一致。该系统为边坡灾害提供了多源预警指标获取方法和新的数据传输方案。

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2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

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