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基于物联网的岩土工程监测系统集成自动数据采集和处理程序的优势。

Advantages of IoT-Based Geotechnical Monitoring Systems Integrating Automatic Procedures for Data Acquisition and Elaboration.

机构信息

ASE-Advanced Slope Engineering S.R.L., Via Robert Koch 53/a, Fraz. Pilastrello, 43123 Parma, Italy.

Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze 181/a, 43124 Parma, Italy.

出版信息

Sensors (Basel). 2021 Mar 23;21(6):2249. doi: 10.3390/s21062249.

DOI:10.3390/s21062249
PMID:33807083
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8005060/
Abstract

Monitoring instrumentation plays a major role in the study of natural phenomena and analysis for risk prevention purposes, especially when facing the management of critical events. Within the geotechnical field, data collection has traditionally been performed with a manual approach characterized by time-expensive on-site investigations and monitoring devices activated by an operator. Due to these reasons, innovative instruments have been developed in recent years in order to provide a complete and more efficient system thanks to technological improvements. This paper aims to illustrate the advantages deriving from the application of a monitoring approach, named Internet of natural hazards, relying on the Internet of things principles applied to monitoring technologies. One of the main features of the system is the ability of automatic tools to acquire and elaborate data independently, which has led to the development of dedicated software and web-based visualization platforms for faster, more efficient and accessible data management. Additionally, automatic procedures play a key role in the implementation of early warning systems with a near-real-time approach, providing a valuable tool to the decision-makers and authorities responsible for emergency management. Moreover, the possibility of recording a large number of different parameters and physical quantities with high sampling frequency allows to perform meaningful statistical analyses and identify cause-effect relationships. A series of examples deriving from different case studies are reported in this paper in order to present the practical implications of the IoNH approach application to geotechnical monitoring.

摘要

监测仪器在自然现象研究和风险预防分析中起着重要作用,特别是在面对关键事件管理时。在岩土工程领域,数据采集传统上采用手动方法进行,这种方法需要在现场进行耗时的调查和由操作员激活的监测设备。由于这些原因,近年来开发了创新的仪器,以便通过技术改进提供更完整和更有效的系统。本文旨在说明基于物联网原则应用于监测技术的一种名为自然灾害物联网的监测方法的应用优势。该系统的主要特点之一是自动工具能够独立获取和处理数据的能力,这导致了专用软件和基于网络的可视化平台的开发,以实现更快、更高效和更易于访问的数据管理。此外,自动程序在实施具有近实时方法的预警系统方面起着关键作用,为负责应急管理的决策者和当局提供了有价值的工具。此外,以高采样频率记录大量不同参数和物理量的可能性允许进行有意义的统计分析并确定因果关系。本文报告了一系列源自不同案例研究的示例,以展示自然灾害物联网方法在岩土工程监测中的实际应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/e6c8731375f0/sensors-21-02249-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/3b0041830aa4/sensors-21-02249-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/68905937448b/sensors-21-02249-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/67f022dfebe1/sensors-21-02249-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/862b6a0cac23/sensors-21-02249-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/0ea410b6c199/sensors-21-02249-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/5651282c9a05/sensors-21-02249-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/120b66d610f4/sensors-21-02249-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/c27e9dd7ee5e/sensors-21-02249-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/e6c8731375f0/sensors-21-02249-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/3b0041830aa4/sensors-21-02249-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/68905937448b/sensors-21-02249-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/67f022dfebe1/sensors-21-02249-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/862b6a0cac23/sensors-21-02249-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/0ea410b6c199/sensors-21-02249-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/5651282c9a05/sensors-21-02249-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/120b66d610f4/sensors-21-02249-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/c27e9dd7ee5e/sensors-21-02249-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/159e/8005060/e6c8731375f0/sensors-21-02249-g009.jpg

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本文引用的文献

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Monitoring and early warning method for a rockfall along railways based on vibration signal characteristics.基于振动信号特征的铁路落石监测预警方法。
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3
ADVICE: a new approach for near-real-time monitoring of surface displacements in landslide hazard scenarios.
建议:一种用于滑坡灾害情景中地表位移近实时监测的新方法。
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