Image Recognition Based Precursor Detection System for Landslide Prevention

In recent years, landslides caused by excessive reclamation and natural disasters have caused many lives and economic losses. Therefore, in addition to the most fundamental method of preventing ground landslides, being able to detect signs of landslides to a certain extent is also a way to prevent loss of life and finances. Currently, satellite imagery and aerial photography are the main methods for landslide detection. However, it is sometimes impossible to confirm the ground through this method due to trees and other obstructions. Therefore, some areas are calling on local residents to record the location and size of cracks and report them to local authorities if they think there are signs of landslides. In this paper, the purpose is to develop a landslide detection system. This system combines image processing and artificial intelligence, and is paired with a multi-functional head-mounted AR display to assist professional civil engineers in identifying possible stratigraphic landslide signs. The AR display marks directions to a set destination and records signs of landslides read in real time from the camera as it moves.