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Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System

The rapid development of highway engineering has made slope stability an important issue in infrastructure construction. To meet the needs of green vegetation growth, ecological recovery, landscape beautification and the economy, long-term monitoring research on high-slope micrometeorology has impor...

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Autores principales: Liu, Dunwen, Chen, Haofei, Tang, Yu, Liu, Chao, Cao, Min, Gong, Chun, Jiang, Shulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838333/
https://www.ncbi.nlm.nih.gov/pubmed/35161957
http://dx.doi.org/10.3390/s22031214
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author Liu, Dunwen
Chen, Haofei
Tang, Yu
Liu, Chao
Cao, Min
Gong, Chun
Jiang, Shulin
author_facet Liu, Dunwen
Chen, Haofei
Tang, Yu
Liu, Chao
Cao, Min
Gong, Chun
Jiang, Shulin
author_sort Liu, Dunwen
collection PubMed
description The rapid development of highway engineering has made slope stability an important issue in infrastructure construction. To meet the needs of green vegetation growth, ecological recovery, landscape beautification and the economy, long-term monitoring research on high-slope micrometeorology has important practical significance. Because of that, we designed and created a new slope micrometeorological monitoring and predicting system (SMMPS). We innovatively upgraded the cloud platform system, by adding an ARIMA prediction system and data-fitting system. From regularly sensor-monitored slope micrometeorological factors (soil temperature and humidity, slope temperature and humidity, and slope rainfall), a data-fitting system was used to fit atmospheric data with slope micrometeorological data, the trend of which ARIMA predicted. The slope was protected in time to prevent severe weather damage to the slope vegetation on a large scale. The SMMPS, which upgrades its cloud platform, significantly reduces the cost of long-term monitoring, protects slope stability, and improves the safety of rail and road projects.
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spelling pubmed-88383332022-02-13 Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System Liu, Dunwen Chen, Haofei Tang, Yu Liu, Chao Cao, Min Gong, Chun Jiang, Shulin Sensors (Basel) Article The rapid development of highway engineering has made slope stability an important issue in infrastructure construction. To meet the needs of green vegetation growth, ecological recovery, landscape beautification and the economy, long-term monitoring research on high-slope micrometeorology has important practical significance. Because of that, we designed and created a new slope micrometeorological monitoring and predicting system (SMMPS). We innovatively upgraded the cloud platform system, by adding an ARIMA prediction system and data-fitting system. From regularly sensor-monitored slope micrometeorological factors (soil temperature and humidity, slope temperature and humidity, and slope rainfall), a data-fitting system was used to fit atmospheric data with slope micrometeorological data, the trend of which ARIMA predicted. The slope was protected in time to prevent severe weather damage to the slope vegetation on a large scale. The SMMPS, which upgrades its cloud platform, significantly reduces the cost of long-term monitoring, protects slope stability, and improves the safety of rail and road projects. MDPI 2022-02-05 /pmc/articles/PMC8838333/ /pubmed/35161957 http://dx.doi.org/10.3390/s22031214 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Dunwen
Chen, Haofei
Tang, Yu
Liu, Chao
Cao, Min
Gong, Chun
Jiang, Shulin
Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System
title Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System
title_full Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System
title_fullStr Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System
title_full_unstemmed Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System
title_short Slope Micrometeorological Analysis and Prediction Based on an ARIMA Model and Data-Fitting System
title_sort slope micrometeorological analysis and prediction based on an arima model and data-fitting system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838333/
https://www.ncbi.nlm.nih.gov/pubmed/35161957
http://dx.doi.org/10.3390/s22031214
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