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SPEPC TECHNOLOGY
Solution
Collapse-Related Geological Hazard Monitoring and Early Warning Solution
Background Introduction
Rockfalls are a common type of geological hazard, typically triggered by the sudden collapse, sliding, or subsidence of mountain masses, rocks, or soil under the influence of gravity, and are characterized by their abrupt onset and significant destructive power.
Collapse-related disasters often result in casualties, transportation disruptions, damage to infrastructure, and property losses, and they occur frequently along highways and railways as well as in areas where houses are built on cut slopes, particularly in the mountainous and hilly regions of China.
Conventional manual inspection methods struggle to provide continuous monitoring of subtle deformations, crack propagation, and tilt changes in hazardous rock masses, failing to detect precursory signs of collapse and resulting in delayed early‑warning responses.
Accordingly, the development of an automated monitoring and early-warning system for collapse hazards—capable of real-time surveillance of critical parameters such as fractures, dip angles, accelerations, and stresses in rock and soil masses—has become an essential technological approach for safeguarding human life and property and for mitigating sudden disasters by enabling full‑cycle perception of slope stability and trend analysis, coupled with intelligent early warning.
Solution Overview
This scheme is a set based on Internet of Things, MEMS sensing, and AI-powered intelligent analytics technologies An automated monitoring and early-warning system for collapse-related geological hazards.
The system’s core employs integrated tilt‑and‑collapse monitors, integrated crack monitors, GNSS receivers, and other front‑end sensors to continuously and in real time collect data on surface tilt changes, crack opening and closing, vibration acceleration, and displacement of the collapse mass.
Data is transmitted to a cloud-based monitoring and early-warning platform via wireless communication technologies such as 4G, LoRa, and NB‑IoT. The platform incorporates AI algorithms and multi‑level warning models to perform fused analysis of multidimensional monitoring data, assess trend patterns, and predict potential disasters.
When monitoring data exceed preset thresholds—such as sudden changes in tilt angles or accelerated crack propagation—the system automatically issues early warning notifications through multiple channels, including platform pop-up alerts, SMS messages, and audio‑visual alarms, while simultaneously activating on-site alarm devices, thereby enabling the prevention and mitigation of collapse hazards. “Monitoring–Analysis–Early Warning–Response” Closed-loop management provides a scientific basis for decision-making by departments responsible for natural resources, transportation, and other sectors.
FEATURES OF THE SOLUTION
Multi-parameter integrated monitoring
High precision and fast response
Crack Dynamic Tracking
Wireless Networking and Low Power Consumption
Multi-level Intelligent Early Warning
Remote Operations and Management
Typical Configuration for Application Scenarios
The geological hazard monitoring and early warning platform comprises modules for station management, real-time monitoring, image-based surveillance, early warning management, information management, operation and maintenance inspections, statistical analysis, hazard‑spot management, and system administration.
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Contact Information
6th Floor, Building 10, Entrepreneurship Industrial Park, Chaoyang Township, Qixing District, Guilin City, Guangxi Zhuang Autonomous Region
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