INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The high rate of rainfall is the main trigger factor in many cases of landslides. However each type of soils has unique characteristics and behaviour concerning the rainfall infilteration. Therefore, early warning system of landslide will be more accurate by monitoring the changes of ground water conditions. The monitoring of ground water changes is designed by using soil moisture sensor. To determine the soil characteristic and behaviour with respect to water content that induce landslides, an experiment involving small-scale landslide model is conducted. The increase of soil water content will lead to the rise of the pore pressure and soil weight which could cause soil vulnerability to the movement. The soil movement sensor utilizes a sliding potentiometer that converts distances into stresses and a humidity sensor. The results obtained through the simulation that the system is able to measure the movement of soil, soil moisture, and provide early warning through sirens.
Keywords:
Soil Moisture Sensor, Gyroscope, Experimental Model
Cite Article:
"Landslide Early Warning System By Analyzing Soil Moisture And Land Movement", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.k48-k54, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305A05.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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