Research on Landslide Early Warning and Multi-Source Data Fusion Technology Based on DS Evidence Theory

Landslides pose significant threats to human lives and properties, rendering landslide monitoring and early warning a critical aspect of disaster prevention and control. This study designs and implements an embedded-system-based landslide monitoring system that assesses potential landslide risks by real-time monitoring of key environmental parameters, such as displacement, rainfall, and soil moisture. The system employs LoRa wireless communication technology, with an ESP8266 NodeMCU serving as the gateway node. Sensor data is received via the LoRa module and transmitted to a cloud platform for analysis and processing through the WiFi enabled by the ESP8266. To meet the demand for multi-source data fusion, the study integrates Dempster-Shafer (DS) evidence theory, facilitating the effective integration of various sensor data for landslide risk assessment.