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Geological Disaster Monitoring, Early Warning, and Rescue Command Platform

 

Solution Background

Geological disasters (such as landslides, debris flows, collapses, ground subsidence, etc.) are highly sudden and destructive, posing a serious threat to people's lives, property, and infrastructure safety. To enhance geological disaster risk prevention and control capabilities, it is necessary to build an "air-space-ground" integrated monitoring network, integrate multi-source data with intelligent algorithms, and achieve early warning, accurate assessment, rapid response, and scientific rescue for disasters.

Solution Introduction

Utilizing various professional equipment such as displacement sensors, rain gauges, and video surveillance, and based on remote sensing (RS) technology, Geographic Information Systems (GIS), and geological disaster monitoring technology, this solution monitors geological deformation bodies like landslides, debris flows, collapses, and ground subsidence. By analyzing and processing information on deformation factors, related factors, and triggering factors, it assesses the stability and changing trends of the deformation bodies, thereby preventing geological disasters and reducing loss of life and property.

  • System Objectives

Real-time Monitoring: Conduct 24/7 all-domain dynamic monitoring of geological disaster-prone areas.

Intelligent Early Warning: Based on multi-dimensional data fusion, achieve disaster probability prediction and graded early warning.

Collaborative Command: Integrate emergency resources, optimize rescue paths and personnel evacuation plans.

Post-disaster Assessment: Quantify disaster impact, support post-disaster reconstruction and risk zonation updates.

  • System Architecture

Adopting a "Perceive-Analyze-Decide-Act" closed-loop architecture, it is divided into the following levels:

Level Function
Perception Layer Satellites, UAVs, GNSS surface displacement monitoring stations, crack gauges, inclinometers, rain gauges, groundwater level sensors, microseismic monitoring equipment, etc.
Network Layer 5G/Beidou short message/Microwave communication/Fiber optic transmission, supporting low-power wide-area networks to ensure communication in remote areas.
Platform Layer Cloud Computing Center (Data Lake, AI Analysis Engine, GIS Engine), Edge Computing Nodes (Real-time data processing).
Application Layer Monitoring and early warning, emergency command, risk assessment, public services, and other modules.

Core Function Modules

  • Multi-source Monitoring and Intelligent Early Warning

Dynamic Monitoring of Hazard Points:

Surface Deformation Monitoring: Using InSAR (Interferometric Radar) and GNSS to obtain millimeter-level surface displacement data.

Underground Parameter Monitoring: Analyzing geotechnical body stability through soil moisture content, pore water pressure, and groundwater level sensors.

Meteorological and Hydrological Linkage: Combining real-time rainfall and river water level data to predict debris flow trigger conditions (e.g., hourly rainfall >50mm triggers a red alert).

AI Risk Prediction Model:

Based on algorithms like Random Forest and LSTM, integrating geological structures, historical disaster data, and real-time monitoring data to output disaster probability heatmaps (e.g., landslide probability >80% triggers a Level 1 alert).

  • Emergency Command and Resource Dispatch

3D Situation Deduction:

Based on DEM (Digital Elevation Model) and BIM (Building Information Model), simulate landslide body movement trajectories, impact areas, and damage to critical facilities (e.g., roads, residential areas).

Intelligent Rescue Planning:

Combine real-time traffic and terrain data to generate optimal evacuation paths and rescue material drop points;

Support rapid UAV surveying of disaster areas, using AI image recognition to locate trapped personnel.

Multi-department Collaboration: Linkage with meteorological, transportation, and medical departments, ensuring traceability of instructions and resource allocation through blockchain technology.

  • Risk Assessment and Post-disaster Reconstruction

Disaster Chain Analysis: Assess the risk of secondary disasters (e.g., landslides blocking rivers causing floods).

Rapid Loss Assessment: Using UAV oblique photography and remote sensing imagery to automatically calculate the area of collapsed houses and damaged roads.

Risk Zonation Update: Update the hazard point database based on post-disaster geological data, and delineate high-risk control zones.

  • Public Services and Training

Graded Early Warning Push: Disseminate evacuation guidelines to the public via SMS, radio, APP, and audio-visual systems (e.g., "Heavy rain red alert, please evacuate to A3 shelter").

Emergency Drills: Simulate collapse and debris flow scenarios, training grassroots cadres and the public in emergency avoidance skills.

 

Key Technologies

  • Multi-modal Data Fusion:

Integrate InSAR, LiDAR, and UAV aerial photography data to build a centimeter-level accurate digital twin of geological disasters.

  • AI Prediction Engine:

Utilize Graph Neural Networks (GNN) to analyze geological body interactions and predict disaster chain evolution trends.

  • Edge Intelligent Computing:

Deploy lightweight AI models at monitoring stations to achieve local real-time alarms for excessive rainfall or sudden displacement.

  • Resilient Communication Network:

Microwave communication + Mesh ad-hoc networking, ensuring uninterrupted communication in extreme weather.

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