PDF(Pubmed)
Abstract：
A landslide involves the downward movement of a mass of rock, debris, earth, or soil. Landslides happen when gravitational forces and other types of shear stresses on a slope surpass the shear strength of the materials. Additionally, landslides can be triggered by processes that weaken the shear strength of the slope\'s material. Shear strength primarily depends on two factors such as frictional strength, which is the resistance to movement between the interacting particles of the slope material, and cohesive strength, which is the bonding between those particles. A landslide is a terrible natural disaster that causes much damage to both human life and the economy. It often occurs in steep mountainous areas or hilly regions, ranging in scale from medium to large. It progresses slowly (20-50 mm/year), but when it occurs, it can move at a speed of 3 m/s. Therefore, early detection or prevention of this disaster is an essential and significant task. This paper developed a method to collect and analyze data, with the purpose of determining the possibility of landslide occurrences to reduce its potential losses.•The proposed method is convenient for users to grasp information of landslide phenomenon.•A machine learning model is applied to forecast landslide phenomenon.•Internet of things (IoT) system is utilized to manage and send a warning text to individual email address and mobile devices.
摘要：
滑坡涉及大量岩石的向下运动，碎片,地球,或土壤。当斜坡上的重力和其他类型的剪切应力超过材料的剪切强度时，就会发生滑坡。此外,滑坡可以由削弱边坡材料抗剪强度的过程引发。剪切强度主要取决于两个因素，如摩擦强度，这是斜坡材料的相互作用粒子之间运动的阻力，和凝聚力，这是这些颗粒之间的结合。滑坡是一种可怕的自然灾害，对人类生活和经济都造成了巨大的损害。它通常发生在陡峭的山区或丘陵地区，规模从中型到大型。它进展缓慢（20-50毫米/年），但是当它发生时，它可以以3m/s的速度移动。因此,及早发现或预防这场灾难是一项重要而重要的任务。本文提出了一种收集和分析数据的方法，目的是确定滑坡发生的可能性，以减少其潜在损失。•该方法便于用户掌握滑坡现象信息。•应用机器学习模型预测滑坡现象。•物联网(IoT)系统用于管理并向个体电子邮件地址和移动设备发送警告文本。
