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Land Transport

Forest Fire Monitoring, Early Warning and Rescue Command Platform

 

Solution Background

With the impact of global climate change and human activities, the frequency and destructiveness of forest fires are increasing year by year. To enhance forest fire prevention and control capabilities, achieve rapid response, and scientific rescue, there is a need to build a comprehensive platform integrating real-time monitoring, intelligent early warning, resource scheduling, and command decision-making.

Solution Introduction

Solution Overview

  • Early Warning: Achieve real-time fire monitoring and early warning through multi-source data fusion circuitry
  • Precise Positioning: Rapidly locate fire points and predict spread trends
  • Efficient Command: Integrate rescue resources, optimize rescue paths and task assignments
  • Post-Disaster Assessment: Quantify disaster loss data to provide a basis for ecological restoration

System Architecture

  • The platform adopts a "Cloud-Edge-End" collaborative architecture, divided into the following modules:
Layer Function
Perception Layer Satellites, drones, ground cameras, weather stations, infrared sensors, and other equipment collect data in real time
Network Layer 5G/satellite communication/microwave communication, IoT data transmission
Platform Layer Cloud Computing Center (data storage, AI analysis, model training)
Application Layer Visual monitoring, command and dispatch, post-disaster assessment, public services, and other modules

IV. Core Function Modules

Real-time Monitoring and Early Warning

Multi-source Data Fusion: Integrates satellite remote sensing, drone aerial photography, ground cameras, meteorological data (temperature and humidity, wind speed and direction), etc

AI Fire Recognition: Image analysis algorithms based on deep learning automatically identify smoke and fire points (accuracy ">=" 95%)

Dynamic Early Warning Map: Combines with GIS system to generate real-time fire risk level distribution maps, supporting heatmaps and spread simulation

 

Rescue Command and Dispatch

 

Resource Management: Real-time monitoring of the location and status of fire brigades, material warehouses, and rescue vehicles

Path Planning: Generates optimal rescue paths based on terrain, fire conditions, and traffic conditions, supporting 3D terrain simulation

Task Assignment: Pushes task instructions to frontline personnel via mobile terminals (APP/smart devices)

 

Post-Disaster Assessment and Recovery

 

Loss Statistics: Analyzes burned area and vegetation damage degree using remote sensing images

Ecological Restoration: Generates vegetation restoration plans based on soil and climate data

 

Decision Support

 

AI Prediction Model: Predicts fire spread direction and speed (e.g., using FARSITE model)

Emergency Plan Library: Stores historical cases and best practices, supporting intelligent recommendation of rescue strategies

 

Public Services and Training

 

Information Release: Pushes fire risk warnings and evacuation guidelines via SMS and APP

Emergency Drills: Simulates fire scenarios to train rescue personnel in collaborative combat capabilities

Key Technologies

AI and Big Data Analytics

Fire Point Recognition Models (YOLO, ResNet, etc.)

Time Series Data Analysis (LSTM) to predict fire trends

3D Visualization

Building 3D geographical environments based on Unity/Unreal Engine, overlaying real-time fire data

Edge Computing

Deploying lightweight AI models on drones or edge nodes to reduce data transmission latency

Application Cases

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Solution Introduction

Application Cases

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