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Forest Fire Scene Situation Awareness and Command and Rescue Assisted Decision-making Platform

This platform integrates multiple data sources such as satellite remote sensing, UAV inspection, ground sensor networks, and video surveillance to achieve real-time monitoring and rapid response to forest fire sites. Combining big data analysis, cloud computing, and artificial intelligence technologies, the platform can automatically identify fire risk areas, predict fire spread trends, assess the scope of disaster impact, and provide scientific rescue plans and decision-making basis for command personnel.

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Forest Fire Scene Situation Awareness and Command and Rescue Assisted Decision-making Platform

Forest Fire Scene Situation Awareness and Command and Rescue Assisted Decision-making Platform

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Platform Overview

This platform integrates various data sources such as satellite remote sensing, UAV inspection, ground sensor networks, and video surveillance to achieve real-time monitoring and rapid response to forest fire sites. Combining big data analysis, cloud computing, and artificial intelligence technologies, the platform can automatically identify high-risk fire areas, predict fire spread trends, assess the scope of disaster impact, and provide scientific rescue plans and decision-making basis for command personnel.

 

 

Core Functions

1. On-site Situational Awareness

Centered on "data-driven decision-making, AI-powered command," it builds an intelligent command hub covering all scenarios and processes of disaster prevention and control.

Create an integrated "perception-decision-command" intelligent decision-making hub, achieving "one map for overall view, one map for command."

Establish a "four-situation" (weather, fire, disaster, hazard) monitoring system to achieve real-time perception of disaster sites and precise prediction of hazards, solving the problem of fragmented multi-source data.

Intelligently analyze rescue capabilities based on the level of disaster occurrence and on-site sensory data, combined with rescue equipment and material allocation.

Integrate multi-dimensional data such as alarm information, resource distribution, and population heatmaps, access on-site video, display real-time disaster site conditions, and combine with real-time deduction and simulation of fire spread models to provide auxiliary judgment for on-site disaster command.

 

2. Smoke and Fire Detection

A smoke and fire feature library is formed by training on a large amount of actual fire data using machine learning, utilizing features such as smoke and fire morphology, contour, spectrum, and their relationship with the background.

By real-time access to front-end forest area high-definition video images, video data streams are analyzed. In a forest background, effective image features of smoke and fire targets are extracted for comparison and identification against the smoke and fire feature knowledge base.

 

3. Precise Fire Point Localization

Achieve fire point localization by obtaining data such as horizontal angle, pitch angle, coordinates, and tower height from front-end cameras, combined with high-precision terrain DEM data.

Fire point localization adopts an automated process design. Once the fire detection system identifies a fire, it simultaneously marks the fire point location on the map. The fire point localization accuracy is high, with an error within 10M.

 

4. Fire Spread Deduction

Dynamically deduce the trend, speed, and intensity of fire spread based on information such as the current fire point location, terrain, wind direction, temperature, humidity, ground temperature, and vegetation, providing a scientific basis for firefighting command.

 

 

5. Command and Dispatch

A full-domain resource coordination hub that intelligently recommends emergency response plans based on underlying data, supports intelligent matching of "resources-tasks-scenarios," and improves response speed. It addresses bottlenecks such as traditional dispatch relying on manual experience, low cross-departmental collaboration efficiency, and unbalanced allocation of emergency resources.

Dynamic resource dispatch engine, real-time tracking of team, vehicle, and material status, real-time linkage response.

Real-time acquisition of video surveillance footage, collaborative map marking, and identification of key command areas.

Intelligent path planning, optimizing rescue routes combining GIS and traffic conditions.

Multi-department collaborative command, cross-level instruction distribution, dynamic adjustment of task priorities.

 

 

6. Mobile Terminal

By equipping smart terminal devices with the forest ranger mobile patrol system, grid-based patrols are conducted in forest areas to promptly report and handle various anomalies and hidden dangers. It enables attendance management, daily patrol management, and trajectory playback for forest rangers.

Key functions include patrol route planning, forest ranger trajectory playback, attendance management, inspection reporting, fire incident handling, real-time video upload, and real-time voice calls.

 

 

Platform - Product Value

 

Visual Data Display:

It adopts advanced data visualization technology to present data in an intuitive and easy-to-understand manner. Through model algorithms and other intuitive simulations, it demonstrates disaster site conditions, helping decision-makers quickly make accurate decisions.

 

Intelligent Data Analysis:

Possesses strong data analysis capabilities, automatically identifies key information to recommend solutions, provides intelligent data support for decision-makers, and improves the efficiency and response speed of command and rescue.

 

Closed-loop Management Process:

The system implements a closed-loop management process from event occurrence to completion of handling, ensuring that every rescue operation receives timely and effective tracking and feedback. Through standardized management, it enhances the regularity and efficiency of rescue operations.

 

 

Platform - Product Value

Visual Data Display : It adopts advanced data visualization technology to present data in an intuitive and easy-to-understand manner. Through model algorithms and other intuitive simulations, it demonstrates disaster site conditions, helping decision-makers quickly make accurate decisions.

Intelligent Data Analysis : Possesses strong data analysis capabilities, automatically identifies key information to recommend solutions, provides intelligent data support for decision-makers, and improves the efficiency and response speed of command and rescue.

Closed-loop Management Process : The system implements a closed-loop management process from event occurrence to completion of handling, ensuring that every rescue operation receives timely and effective tracking and feedback. Through standardized management, it enhances the regularity and efficiency of rescue operations.

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Based on Industrial Internet + AI, the intelligent operation and maintenance management platform ensures the safe, stable, and efficient operation of major equipment, extends its service life, and reduces operation and maintenance costs through real-time monitoring, fault prediction, health assessment, and decision optimization.

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2021-09-15 00:00


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Platform Functions

Platform Overview

This platform integrates various data sources such as satellite remote sensing, UAV inspection, ground sensor networks, and video surveillance to achieve real-time monitoring and rapid response to forest fire sites. Combining big data analysis, cloud computing, and artificial intelligence technologies, the platform can automatically identify high-risk fire areas, predict fire spread trends, assess the scope of disaster impact, and provide scientific rescue plans and decision-making basis for command personnel.

 

 

Core Functions

1. On-site Situational Awareness

Centered on "data-driven decision-making, AI-powered command," it builds an intelligent command hub covering all scenarios and processes of disaster prevention and control.

Create an integrated "perception-decision-command" intelligent decision-making hub, achieving "one map for overall view, one map for command."

Establish a "four-situation" (weather, fire, disaster, hazard) monitoring system to achieve real-time perception of disaster sites and precise prediction of hazards, solving the problem of fragmented multi-source data.

Intelligently analyze rescue capabilities based on the level of disaster occurrence and on-site sensory data, combined with rescue equipment and material allocation.

Integrate multi-dimensional data such as alarm information, resource distribution, and population heatmaps, access on-site video, display real-time disaster site conditions, and combine with real-time deduction and simulation of fire spread models to provide auxiliary judgment for on-site disaster command.

 

2. Smoke and Fire Detection

A smoke and fire feature library is formed by training on a large amount of actual fire data using machine learning, utilizing features such as smoke and fire morphology, contour, spectrum, and their relationship with the background.

By real-time access to front-end forest area high-definition video images, video data streams are analyzed. In a forest background, effective image features of smoke and fire targets are extracted for comparison and identification against the smoke and fire feature knowledge base.

 

3. Precise Fire Point Localization

Achieve fire point localization by obtaining data such as horizontal angle, pitch angle, coordinates, and tower height from front-end cameras, combined with high-precision terrain DEM data.

Fire point localization adopts an automated process design. Once the fire detection system identifies a fire, it simultaneously marks the fire point location on the map. The fire point localization accuracy is high, with an error within 10M.

 

4. Fire Spread Deduction

Dynamically deduce the trend, speed, and intensity of fire spread based on information such as the current fire point location, terrain, wind direction, temperature, humidity, ground temperature, and vegetation, providing a scientific basis for firefighting command.

 

 

5. Command and Dispatch

A full-domain resource coordination hub that intelligently recommends emergency response plans based on underlying data, supports intelligent matching of "resources-tasks-scenarios," and improves response speed. It addresses bottlenecks such as traditional dispatch relying on manual experience, low cross-departmental collaboration efficiency, and unbalanced allocation of emergency resources.

Dynamic resource dispatch engine, real-time tracking of team, vehicle, and material status, real-time linkage response.

Real-time acquisition of video surveillance footage, collaborative map marking, and identification of key command areas.

Intelligent path planning, optimizing rescue routes combining GIS and traffic conditions.

Multi-department collaborative command, cross-level instruction distribution, dynamic adjustment of task priorities.

 

 

6. Mobile Terminal

By equipping smart terminal devices with the forest ranger mobile patrol system, grid-based patrols are conducted in forest areas to promptly report and handle various anomalies and hidden dangers. It enables attendance management, daily patrol management, and trajectory playback for forest rangers.

Key functions include patrol route planning, forest ranger trajectory playback, attendance management, inspection reporting, fire incident handling, real-time video upload, and real-time voice calls.

 

 

Platform - Product Value

 

Visual Data Display:

It adopts advanced data visualization technology to present data in an intuitive and easy-to-understand manner. Through model algorithms and other intuitive simulations, it demonstrates disaster site conditions, helping decision-makers quickly make accurate decisions.

 

Intelligent Data Analysis:

Possesses strong data analysis capabilities, automatically identifies key information to recommend solutions, provides intelligent data support for decision-makers, and improves the efficiency and response speed of command and rescue.

 

Closed-loop Management Process:

The system implements a closed-loop management process from event occurrence to completion of handling, ensuring that every rescue operation receives timely and effective tracking and feedback. Through standardized management, it enhances the regularity and efficiency of rescue operations.

 

 

Platform - Product Value

Visual Data Display : It adopts advanced data visualization technology to present data in an intuitive and easy-to-understand manner. Through model algorithms and other intuitive simulations, it demonstrates disaster site conditions, helping decision-makers quickly make accurate decisions.

Intelligent Data Analysis : Possesses strong data analysis capabilities, automatically identifies key information to recommend solutions, provides intelligent data support for decision-makers, and improves the efficiency and response speed of command and rescue.

Closed-loop Management Process : The system implements a closed-loop management process from event occurrence to completion of handling, ensuring that every rescue operation receives timely and effective tracking and feedback. Through standardized management, it enhances the regularity and efficiency of rescue operations.