Aircraft sudden fire accident emergency resource real-time scheduling system and method

Abstract

The invention relates to the technical field of civil aviation emergency management, and provides an aircraft sudden fire accident emergency resource real-time scheduling system and method, and the system comprises a screen display system, an electronic sand table system, a remote control system and an intelligent software system. The screen display system is used for displaying aircraft attitudes, a GIS geographic information system and aircraft real-time safety condition data in an airport and an adjacent area of the airport, and providing comprehensive visual display; the electronic sand table system is used for displaying the ground real-time environment of an airport and an adjacent area thereof and displaying an aircraft sudden fire accident scene; the remote control system is used for dispatching personnel of each rescue department to command and coordinate the rescue personnel of the department in the event scene in real time; the intelligent software system integrates various functional modules and databases, supports information sharing, optimal rescue path calculation, real-time navigation and communication interconnection among departments, and provides support for rescue decision making. According to the invention, real-time scheduling of emergency resources can be well carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of civil aviation emergency management, and specifically, to a real-time scheduling system and method for emergency resources in the event of an aircraft sudden fire incident. Background Art

[0002] In air transportation, aircraft sudden fire incidents pose a serious threat to the lives and property safety of passengers. Currently, there are many problems in the emergency resource scheduling for such fire incidents. Traditional scheduling methods rely on manual experience and simple rules, and cannot quickly and accurately respond to complex and changeable fire scenarios. There are no scientific prediction and analysis means when determining the types and quantities of rescue resources, which easily leads to insufficient or excessive resource allocation. When planning the rescue path, the dynamic changes at the fire scene cannot be considered in real time, making it difficult to guarantee the timeliness and safety of rescue operations. Moreover, the communication and coordination efficiency among various rescue departments is low, and the information transmission is not timely and accurate, seriously affecting the overall effect of emergency rescue. At the same time, there are problems such as unsmooth information transmission, difficult command, and inaccurate resource scheduling in the traditional rescue command system for aircraft sudden fire incidents. For example, when on-site rescue personnel transmit information to the command center, due to poor communication or unclear conveyance, the command center cannot understand the situation in time and delays the decision-making time. The command center lacks real-time data support and intelligent decision-making tools in the face of aircraft mechanical failure accidents and is difficult to make quick and effective decisions. When a large number of medical rescue personnel and equipment are needed in emergencies, due to scattered resource information and low scheduling efficiency, some medical resources cannot arrive in time, affecting the treatment of the wounded. These problems highlight the challenges faced by traditional systems in dealing with emergencies. With the rapid development of the air transportation industry and the continuous increase in the number of flights, higher requirements are put forward for the emergency handling ability of aircraft sudden fire incidents. There is an urgent need for an efficient and intelligent real-time scheduling method for emergency resources and a new type of intelligent and digital rescue command system to improve the rescue efficiency and quality. Summary of the Invention

[0003] The content of the present invention is to provide a real-time scheduling system and method for emergency resources in the event of an aircraft sudden fire incident, which can solve the problems such as information transmission delay, difficult command decision-making, and inaccurate resource scheduling existing in the traditional system.

[0004] According to a real-time scheduling system for emergency resources in the event of an aircraft sudden fire incident of the present invention, it includes a screen display system, an electronic sand table system, a remote control system, and an intelligent software system;

[0005] The screen display system is used to display the attitude of aircraft, GIS geographical information system, and real-time safety situation data of aircraft within the airport and its adjacent areas, and provide a comprehensive visual display;

[0006] The electronic sand table system is used to display the real-time ground environment of the airport and its adjacent areas, and display the scene of the aircraft sudden fire incident;

[0007] A remote control system is used for each rescue department to dispatch personnel to conduct real-time command and coordination of the rescue personnel of this department at the incident site, including information transmission, resource allocation, and personnel arrangement, to ensure the smooth progress of the collaborative rescue work among departments;

[0008] An intelligent software system integrates various functional modules and databases, supports information sharing, optimal rescue path calculation and real-time navigation, and communication interconnection among departments, and provides support for rescue decision-making.

[0009] Preferably, the screen display system includes a seamless splicing screen, a zooming module, a distance adjustment module, and a roaming and moving module;

[0010] The seamless splicing screen includes multiple liquid crystal screens. The multiple liquid crystal screens are spliced to form a display screen. The screen size is not less than 3 meters × 2 meters, and it is used to provide a display space;

[0011] The zooming module is used for zooming in and out operations so that personnel can view the situation in more detail;

[0012] The distance adjustment module is used to pull the view far or near to understand the relationship and distance between various parts of the airport;

[0013] The roaming and moving module is used to achieve roaming and moving at any position to observe the airport layout and building conditions from different angles.

[0014] Preferably, the electronic sand table system includes a projection module, a multi-functional operation module, a real-time interaction module, and a drawing module;

[0015] The projection module is used to display the airport GIS map and three-dimensional model information. The electronic sand table system includes multiple projectors, and the information is projected onto the electronic sand table through a fusion processor and a computer host;

[0016] The multi-functional operation module is used to achieve functions such as zooming in and out, displacement, and marking of the sand table view;

[0017] The real-time interaction module is used to update the map information and model data in real time, so that the personnel in the emergency command center can timely understand the airport situation and make immediate decisions and adjustments;

[0018] The drawing module is used to draw marks and path lines on the electronic sand table to assist the command personnel in emergency rescue and tactical deployment.

[0019] Preferably, the remote control system includes a multi-host configuration module, a function configuration and designation module, and a permission management module;

[0020] A multi-host configuration module is used to form a local area network system with a sound system and a switch to achieve information interconnection and data transmission, including several control console host groups;

[0021] A function configuration and designation module is used for a main control computer to configure functions for all computers of control seats, designate different function attributes, grouping, and permission management of control seats to meet the needs and permission restrictions of different users;

[0022] A permission management module is used to support the permission management function, set different permission levels according to user identities and needs, and ensure information security and operation specifications.

[0023] Preferably, the intelligent software system includes sensor data integration, an artificial intelligence module, a resource allocation and path optimization module implanted with a particle swarm algorithm, an intelligent communication protocol, and data processing equipment;

[0024] Sensor data integration is used to integrate data from various sensors such as smoke detectors, temperature sensors, and gas sensors deployed inside the airport to collect fire-related data. The implementation process includes data cleaning through the use of low-pass filters, mean, and standard deviation calculations to remove noise and irrelevant information, using box plot analysis and isolation forest algorithms for outlier detection to identify and process outliers in the data to prevent misleading subsequent analysis, and also using Fourier transform and principal component analysis for feature extraction to facilitate subsequent analysis and decision-making;

[0025] The artificial intelligence module is used for a personnel trajectory recognition system to assist the command center in monitoring and dispatching rescue operations; the implementation method is to use a convolutional neural network for image recognition to achieve early detection of fires; use optical flow method and deep learning models to carry out personnel trajectory recognition, so as to provide the command center with real-time position information of rescue personnel and trapped personnel;

[0026] The resource allocation and path optimization module implanted with a particle swarm algorithm is used to optimize the allocation of rescue resources including fire trucks, ambulances, and rescue personnel, and at the same time plan the best travel routes for rescue vehicles and personnel; in terms of implementation, use the particle swarm algorithm, combine historical fire data with environmental factors to predict the development trend of fires, and achieve the optimal allocation of rescue resources by simulating the search behavior of the particle swarm; and use the particle swarm algorithm to plan paths for rescue vehicles and personnel, which can be dynamically adjusted to avoid fire areas and congested sections;

[0027] The intelligent communication protocol is used to realize communication between rescue teams by developing and utilizing natural language processing technology; in terms of implementation, use natural language processing technology to improve the accuracy and efficiency of communication; at the same time, build a multi-agent system for the actions of different rescue departments, achieve cross-departmental coordinated operations through collaborative learning, and the multi-agent system can adjust communication strategies in real time;

[0028] A data processing device for processing large amounts of data; in the implementation approach, by using high-performance databases, MySQL and MongoDB, to store sensor data, image data, and communication data; using a distributed computing framework, Apache Spark to process large amounts of data; applying a stream processing algorithm, Apache Kafka to analyze real-time data streams, capable of quickly identifying fire emergencies and triggering an emergency response mechanism.

[0029] This embodiment provides a method for real-time scheduling of emergency resources for aircraft sudden fire events, which adopts the above-mentioned system for real-time scheduling of emergency resources for aircraft sudden fire events, and includes the following steps:

[0030] Step 1: Construct a basic information acquisition and display system;

[0031] Step 2: Implement intelligent analysis and decision support;

[0032] Step 3: Ensure the execution and coordination of rescue operations.

[0033] Preferably, in Step 1, specifically:

[0034] Step 1.1: Multi-source data collection and preprocessing: Integrate smoke detectors, temperature sensors, and gas sensors in the airport through an intelligent software system to collect fire-related data in real time; use low-pass filters, mean and standard deviation calculations to clean the data, remove noise and irrelevant information; use box plot analysis and isolation forest algorithms to detect and process outliers; use Fourier transform and principal component analysis for feature extraction to provide a data basis for subsequent decision-making;

[0035] Step 1.2: Build a visualization information display platform: On the one hand, the real-time video monitoring equipment in the airport area transmits the fire scene video data to the screen display system in the emergency command center; the system uses a seamless splicing screen, with a resolution of not less than 1920×1080 and a screen size of not less than 3 meters×2 meters, capable of stably displaying the aircraft attitude, GIS information, and real-time safety status of the aircraft in the airport and adjacent areas, while displaying action instructions and resource allocation, and having functions such as zooming in and out, adjusting the distance, and roaming, facilitating emergency response personnel to comprehensively observe and analyze; on the other hand, the electronic sand table system projects the airport GIS map and three-dimensional model information onto the electronic sand table through multiple projectors under the coordination of a fusion processor and a computer host; the electronic sand table has multifunctional operations, interactivity, real-time interaction, and drawing functions, intuitively displaying the real-time ground environment and fire event scene in the airport and adjacent areas.

[0036] Preferably, in Step 2, specifically:

[0037] Step 2.1, Fire Situation Prediction: The resource allocation and path optimization module implanted with the particle swarm algorithm in the intelligent software system integrates historical fire data and environmental factors to predict the development trend of the fire, providing a basis for subsequent rescue resource allocation and operation planning;

[0038] Step 2.2, Resource Optimization and Path Planning: The particle swarm algorithm is used to reasonably allocate fire trucks, ambulances, and rescue personnel. At the same time, the best travel routes are planned for rescue vehicles and personnel, and can be dynamically adjusted according to the real-time situation to avoid fire areas and congested sections to ensure the implementation of rescue operations;

[0039] Step 2.3, Auxiliary Decision-making: The person in charge of each rescue department in the emergency command center works with the control seats of the remote control system; the remote control system consists of several control seat hosts, a speaker system, and a switch to form a local area network to achieve information interconnection; the main control computer configures the functions and manages the permissions of each control seat computer; based on the information displayed by the screen display system and the electronic sand table system and the analysis results of the intelligent software system, the person in charge of each department formulates on-site fire rescue plans.

[0040] Preferably, in Step 3, specifically:

[0041] Step 3.1, Rescue Operation Initiation and Execution: The personnel of each rescue department act quickly according to the instructions of the command center, and the fire trucks and ambulances drive towards the fire scene according to the paths planned by the intelligent software system;

[0042] Personnel Dynamic Monitoring and Scheduling: The intelligent software system uses artificial intelligence technology to perform early fire detection through image recognition by a convolutional neural network, and uses the optical flow method and deep learning model to carry out personnel trajectory recognition to provide the command center with real-time position information of rescue personnel and trapped personnel;

[0043] Step 3.2, Communication and Collaboration Guarantee: The rescue teams communicate through the intelligent communication protocol of the intelligent software system; the protocol uses natural language processing technology to build a multi-agent system to simulate the actions of different rescue departments, and realizes cross-departmental collaborative operations through collaborative learning and adjusts the communication strategy in real time;

[0044] Step 3.3, Real-time Monitoring and Dynamic Adjustment: The screen display system updates the progress of the rescue operation in real time, including the positions of rescue personnel, the driving status of rescue vehicles, and the changes in the fire situation at the fire scene; the commanders can timely grasp the rescue dynamics based on this and make flexible decision adjustments to ensure the smooth progress of the rescue operation and ultimately achieve the response to aircraft sudden fire incidents.

[0045] The beneficial effects of the present invention are as follows:

[0046] The core components of the present invention include screen display, electronic sand table, remote control, and intelligent software. By applying 3D GIS and artificial intelligence technologies, it realizes real-time data collection, intelligent decision-making support, and optimization of resource scheduling, providing comprehensive, intuitive, and efficient command and emergency rescue support, with the goal of improving rescue efficiency and quality and ensuring aviation safety and the safety of passengers' lives and property. Through the close cooperation and coordinated work among various rescue departments, the effectiveness of emergency rescue for aircraft sudden fire incidents is effectively improved.

[0047] Compared with the existing patent technologies, the present invention has significant advantages in aspects such as advanced technology application, real-time performance, and coordination. The present invention adopts various technical means, including 3D GIS, artificial intelligence, etc., to achieve all-round command and emergency support, ensuring that commanders can obtain the latest information, make quick decision-making and processing, and improve rescue efficiency and quality, thus effectively ensuring aviation safety and the safety of passengers' lives and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of a method for real-time scheduling of emergency resources for aircraft sudden fire incidents in the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0049] To further understand the content of the present invention, the present invention will be described in detail in combination with the drawings and embodiments. It should be understood that the embodiments are only for explaining the present invention and not for limiting it.

[0050] Embodiment

[0051] This embodiment provides a system for real-time scheduling of emergency resources for aircraft sudden fire incidents, which includes a screen display system, an electronic sand table system, a remote control system, and an intelligent software system. These components jointly promote the effective implementation of emergency handling of aircraft sudden fire incidents.

[0052] The screen display system is used to display the attitude of aircraft, GIS geographical information system, and real-time safety situation data of aircraft within the airport and its adjacent areas, providing a comprehensive visual display to facilitate emergency response decision-makers to observe and analyze the overall situation.

[0053] The electronic sand table system is used to display the real-time ground environment of the airport and its adjacent areas, and show the scene of aircraft sudden fire incidents, including fires, rescue processes, etc., enabling command and coordination personnel to more intuitively understand the incident situation, improving the coordination efficiency among various rescue departments, and also effectively enhancing the overall emergency response level.

[0054] The remote control system is used for dispatchers of each rescue department to conduct real-time command and coordination of the rescue personnel of their own department at the incident site, including information transmission, resource allocation, and personnel arrangement, ensuring the smooth progress of coordinated rescue work among various departments.

[0055] An intelligent software system integrates various functional modules and databases, supports information sharing among departments, calculates the optimal rescue path and provides real-time navigation and communication interconnection, and provides support for rescue decision-making.

[0056] The screen display system includes a high-definition seamless splicing screen, a zoom-in / zoom-out module, a far / near adjustment module, and a roaming and moving module.

[0057] The seamless splicing screen includes multiple liquid crystal screens. The multiple liquid crystal screens are spliced to form a display screen with a screen size of not less than 3 meters × 2 meters, which is used to provide an intuitive display space.

[0058] The zoom-in / zoom-out module is used for zooming in and out operations, enabling personnel to view the situation in more detail.

[0059] The far / near adjustment module is used to pull the view far or near to understand the relationship and distance between various parts of the airport.

[0060] The roaming and moving module is used to achieve roaming and moving at any position to observe the airport layout and building conditions from different angles.

[0061] The electronic sand table system includes a projection module, a multi-functional operation module, a real-time interaction module, and a drawing module.

[0062] The projection module is used to display the airport GIS map and three-dimensional model information. The electronic sand table system includes 2 projectors, and projects the information onto the electronic sand table through a fusion processor and a computer host.

[0063] The multi-functional operation module is used to achieve functions such as zooming in and out, displacement, and marking of the sand table view.

[0064] The real-time interaction module is used to update map information and model data in real time, enabling personnel in the emergency command center to understand the airport situation in a timely manner and make immediate decisions and adjustments.

[0065] The drawing module is used to draw marks and path lines on the electronic sand table to assist the command personnel in emergency rescue and tactical deployment.

[0066] The remote control system includes a multi-host configuration module, a function configuration and assignment module, and a permission management module.

[0067] The multi-host configuration module is used to form a local area network system with the speaker system and the switch to achieve information interconnection and data transmission, including 10 control console host groups.

[0068] The function configuration and assignment module is used for the main control computer to configure the functions of all control console computers, assign different function attributes, grouping, and permission management of the control consoles to meet the needs and permission restrictions of different users.

[0069] The permission management module is used to support the permission management function, set different permission levels according to the user identity and requirements, and ensure information security and operation specifications.

[0070] The intelligent software system includes sensor data integration, an artificial intelligence module, a resource allocation and path optimization module implanted with a particle swarm algorithm, an intelligent communication protocol, and data processing equipment.

[0071] Sensor data integration is used to integrate data from various sensors deployed inside the airport, such as smoke detectors, temperature sensors, and gas sensors, to collect fire-related data. The implementation process includes data cleaning to remove noise and irrelevant information to improve data quality by using filtering techniques (low-pass filters) and statistical methods (mean and standard deviation calculations), outlier detection to identify and process outliers in the data to prevent misleading subsequent analysis by using statistical methods (box plot analysis) and machine learning methods (isolation forest algorithm), and feature extraction for subsequent analysis and decision-making by using signal processing techniques (Fourier transform) and machine learning methods (principal component analysis).

[0072] The artificial intelligence module is used in the personnel trajectory recognition system to assist the command center in monitoring and dispatching rescue operations. Its implementation method is to use a convolutional neural network for image recognition to achieve early detection of fires, and use computer vision algorithms (optical flow method) and deep learning models to carry out personnel trajectory recognition, so as to provide the command center with real-time position information of rescue personnel and trapped people.

[0073] The resource allocation and path optimization module implanted with a particle swarm algorithm is used to optimize the allocation of rescue resources including fire trucks, ambulances, and rescue personnel, and at the same time plan the best travel routes for rescue vehicles and personnel. In terms of implementation, this module uses the particle swarm algorithm, combines historical fire data and environmental factors to predict the fire development trend, and achieves the optimal allocation of rescue resources by simulating the search behavior of the particle swarm. And it uses the particle swarm algorithm to plan routes for rescue vehicles and personnel, which can be dynamically adjusted to avoid fire areas and congested sections, thus ensuring the timeliness and safety of rescue operations.

[0074] The intelligent communication protocol is used to realize the communication between rescue teams by developing and utilizing natural language processing technology, thereby reducing misunderstandings and communication costs. In terms of implementation, this protocol uses natural language processing technology, such as using the BERT model for speech recognition and text generation, to improve the accuracy and efficiency of communication. At the same time, a multi-agent system is constructed for the actions of different rescue departments, and cross-departmental collaborative operations are achieved through collaborative learning. And this multi-agent system can adjust the communication strategy in real time to effectively ensure the timeliness and accuracy of information transmission.

[0075] A data processing device is used to process a large amount of data to ensure the stability of system operation. In terms of implementation, a high-performance database, MySQL or MongoDB, is used to store sensor data, image data, and communication data. The distributed computing framework, Apache Spark, is utilized to process a large amount of data. The stream processing algorithm, Apache Kafka, is applied to analyze real-time data streams, enabling quick identification of fire emergencies and triggering an emergency response mechanism.

[0076] This embodiment assists the commanders in comprehensively understanding the situation and guiding rescue operations by clearly displaying real-time emergency scenarios, operation instructions, and resource allocation, thereby improving the rescue efficiency. This embodiment can present real-time scenarios of aircraft emergencies, show the task distribution and resource locations, provide visual support for the commanders to formulate the best rescue plan, and promote rapid response and effective execution.

[0077] As Figure 1 shown, this embodiment provides a method for real-time scheduling of emergency resources for aircraft sudden fire incidents. It adopts the above-mentioned real-time scheduling system for emergency resources of aircraft sudden fire incidents and includes the following steps:

[0078] Step 1: Construct a basic information acquisition and display system;

[0079] Step 2: Implement intelligent analysis and decision support;

[0080] Step 3: Ensure the execution and coordination of rescue operations.

[0081] In Step 1, specifically:

[0082] Step 1.1: Multi-source data collection and preprocessing: Integrate smoke detectors, temperature sensors, and gas sensors in the airport through an intelligent software system to collect fire-related data in real time. Use filtering techniques (low-pass filters) and statistical means (mean and standard deviation calculations) to clean the data, removing noise and irrelevant information. Apply statistical methods (box plot analysis) and machine learning algorithms (isolation forest algorithm) to detect and process outliers. Use signal processing techniques (Fourier transform) and machine learning methods (principal component analysis) for feature extraction to provide a high-quality data basis for subsequent decision-making.

[0083] Step 1.2. Construction of Visual Information Display Platform: On the one hand, the real-time video monitoring devices in the airport area transmit the video data of the fire scene to the screen display system in the emergency command center. The system uses a seamless splicing screen with a resolution of not less than 1920×1080 and a screen size of not less than 3m×2m, which can stably display the aircraft attitude, GIS information, and real-time safety status of the aircraft in the airport and adjacent areas. At the same time, it displays the operation instructions and resource allocation situation, and has functions such as zooming in and out, adjusting the distance, and roaming, which is convenient for emergency response personnel to comprehensively observe and analyze. On the other hand, through 2 projectors, the electronic sand table system projects the airport GIS map and 3D model information onto the electronic sand table under the coordination of the fusion processor and the computer host. The electronic sand table has multi-functional operations (zooming in and out, displacement, marking, etc.), interactivity (supporting interactive methods such as touch screens), real-time interaction, and drawing functions, intuitively displaying the real-time ground environment and fire incident scenes in the airport and adjacent areas, and improving the coordination efficiency and emergency response level of the rescue department.

[0084] In Step 2, specifically:

[0085] Step 2.1. Fire Situation Prediction: The resource allocation and path optimization module implanted with the particle swarm algorithm in the intelligent software system integrates historical fire data and environmental factors to predict the development trend of the fire, providing a basis for subsequent rescue resource allocation and action planning.

[0086] Step 2.2. Resource Optimization and Path Planning: The particle swarm algorithm is used to reasonably allocate fire trucks, ambulances, and rescue personnel. At the same time, the best travel paths are planned for rescue vehicles and personnel, and can be dynamically adjusted according to the real-time situation to avoid fire areas and congested roads, ensuring the implementation of rescue operations.

[0087] Step 2.3. Auxiliary Decision-making: The person in charge of each rescue department in the emergency command center works with the control seats of the remote control system. The remote control system consists of 10 control seat hosts, a speaker system, and a switch to form a local area network for information interconnection. The main control computer configures the functions and manages the permissions of each control seat computer. Based on the information displayed by the screen display system, the electronic sand table system, and the analysis results of the intelligent software system, the person in charge of each department formulates the on-site fire rescue plan.

[0088] In Step 3, specifically:

[0089] Step 3.1. Start and Execution of Rescue Operations: The personnel of each rescue department act quickly according to the instructions of the command center. The fire trucks and ambulances drive towards the fire scene along the paths planned by the intelligent software system.

[0090] Personnel Dynamic Monitoring and Scheduling: The intelligent software system uses artificial intelligence technology to achieve early fire detection through image recognition by convolutional neural networks, and uses computer vision algorithms (optical flow method) and deep learning models to carry out personnel trajectory recognition, providing real-time location information of rescue personnel and trapped people for the command center, and assisting the command center in precise monitoring and scheduling.

[0091] Step 3.2, Communication and Collaboration Guarantee: The rescue teams communicate efficiently through the intelligent communication protocol of the intelligent software system. This protocol uses natural language processing technology, such as using the BERT model for speech recognition and text generation, to improve communication accuracy and efficiency; constructs a multi-agent system to simulate the actions of different rescue departments, realizes cross-departmental collaborative operations through collaborative learning, and adjusts the communication strategy in real time to ensure timely and accurate information transmission.

[0092] Step 3.3, Real-time Monitoring and Dynamic Adjustment: The screen display system updates the progress of the rescue operation in real time, including information such as the location of rescue personnel, the driving status of rescue vehicles, and the change of the fire situation at the fire scene. The commanders can thus timely grasp the rescue dynamics and make flexible decision adjustments to ensure the smooth progress of the rescue operation, ultimately achieving an efficient response to aircraft sudden fire incidents and ensuring aviation safety and the life and property safety of passengers.

[0093] This embodiment further includes:

[0094] Step 4, Emergency End and Follow-up Processing;

[0095] When the fire is successfully extinguished and all trapped people are safely rescued, the rescue operation ends. The emergency command center conducts a review and summary of the entire rescue process through the screen display system and the electronic sand table system.

[0096] The intelligent software system sorts out and stores various types of data generated during this rescue process, such as sensor data, image data, communication data, etc., and uses high-performance databases (MySQL, MongoDB) for storage, providing data support for subsequent data analysis and experience summary.

[0097] Inspect and maintain the screen display system, the electronic sand table system, the remote control system and the intelligent software system to ensure that each system can operate normally in the next emergency event. At the same time, optimize and improve the system according to the problems and deficiencies found during this rescue process, and continuously improve the performance and response ability of the emergency resource real-time scheduling system.

[0098] Before this embodiment runs, system startup and initialization are carried out, specifically:

[0099] A. At the airport emergency command center, the staff turn on the screen display system, the electronic sand table system, the remote control system and the intelligent software system.

[0100] B. The screen display system conducts self-check to ensure the normal operation of the high-definition seamless splicing screen. All functions such as zooming in and out, distance adjustment, and roaming can be used normally. The resolution reaches no less than 1920×1080, the screen size is no less than 3m×2m, and it can stably and reliably display various information.

[0101] C. Through 2 projectors, the electronic sand table system, with the cooperation of the fusion processor and the computer host, accurately projects the airport GIS map and three-dimensional model information onto the electronic sand table to ensure the normal realization of multifunctional operations (zooming in and out, displacement, marking, etc.), interactivity (touch screen operation), real-time interaction, and drawing functions.

[0102] D. The 10 control console hosts of the remote control system form a local area network system with the audio system and the switch to achieve information interconnection and data transmission. The integrated control system is ready, and leaders of each department can perform subsequent operations through this system.

[0103] E. The intelligent software system starts to integrate data from various sensors deployed inside the airport, such as smoke detectors, temperature sensors, and gas sensors. At the same time, it completes data cleaning, outlier detection, and feature extraction work to ensure data quality. Functional modules such as image recognition and personnel trajectory recognition in the artificial intelligence technology module also enter the standby state.

[0104] This embodiment comprehensively applies real-time video monitoring data transmission, intelligent software system navigation, and multi-department collaborative working mechanisms to achieve the intuitive display and real-time transmission of information, significantly improve decision-making efficiency and collaborative working ability, and thus effectively ensure aviation safety and the life and property safety of passengers.

[0105] The above has schematically described the present invention and its implementation manners. This description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. Therefore, if those of ordinary skill in the art are inspired by it and design similar structural manners and embodiments without creative work without departing from the purpose of the present invention, they shall fall within the protection scope of the present invention.

Claims

1. An emergency resource real-time scheduling system for aircraft sudden fire incidents, characterized in that: It includes a screen display system, an electronic sand table system, a remote control system and an intelligent software system; The screen display system is used to display the postures of aircraft, GIS geographical information system, and real-time safety situation data of aircraft within the airport and its adjacent areas, providing a comprehensive visual display; The electronic sand table system is used to display the real-time ground environment of the airport and its adjacent areas, and demonstrate the scenarios of aircraft sudden fire incidents; The remote control system is used for the dispatchers of each rescue department to conduct real-time command and coordination of the rescue personnel of their own department at the incident site, including information transmission, resource allocation, and personnel arrangement, ensuring the smooth progress of the collaborative rescue work among departments; The intelligent software system integrates various functional modules and databases, supports information sharing, optimal rescue path calculation and real-time navigation, and communication interconnection among departments, providing support for rescue decision-making.

2. The real-time scheduling system for emergency resources in the event of an aircraft sudden fire, as claimed in claim 1, is characterized in that: The screen display system includes a seamless splicing screen, a zoom-in / zoom-out module, a far / near adjustment module, and a roaming and moving module; The seamless splicing screen includes multiple liquid crystal screens. The multiple liquid crystal screens are spliced to form a display screen with a screen size of not less than 3 meters × 2 meters, which is used to provide a display space; The zoom-in / zoom-out module is used for zoom-in and zoom-out operations, enabling personnel to view the situation in more detail; The far / near adjustment module is used to pull the view far or near, so as to understand the relationship and distance between different parts of the airport; The roaming and moving module is used to achieve roaming and moving at any position, observing the airport layout and building conditions from different angles.

3. The real-time scheduling system for emergency resources of aircraft sudden fire incidents according to claim 2, characterized in that: The electronic sand table system includes a projection module, a multi-functional operation module, a real-time interaction module, and a drawing module; The projection module is used to display the airport GIS map and three-dimensional model information. The electronic sand table system includes multiple projectors, which project the information onto the electronic sand table through a fusion processor and a computer host; The multi-functional operation module is used to achieve functions such as zooming in and out, displacement, and marking of the sand table view; The real-time interaction module is used to update the map information and model data in real time, enabling the personnel in the emergency command center to understand the airport situation in a timely manner, make immediate decisions and adjustments; The drawing module is used to draw marks and path lines on the electronic sand table, assisting the commanders in conducting emergency rescue and tactical deployment.

4. The real-time scheduling system for emergency resources in the event of an aircraft sudden fire, as claimed in claim 3, wherein: The remote control system includes a multi-host configuration module, a function configuration and assignment module, and a permission management module; The multi-host configuration module is used to form a local area network system with the audio system and the switch, realizing information interconnection and data transmission, including several control console host groups; The function configuration and assignment module is used for the main control computer to configure the functions of all control console computers, specify the function attributes, grouping, and permission management of different control console seats to meet the needs and permission restrictions of different users; The permission management module is used to support the permission management function, set different permission levels according to the user identity and needs, and ensure information security and operation specifications.

5. The real-time scheduling system for emergency resources in the event of an aircraft sudden fire, as claimed in claim 4, wherein: The intelligent software system includes sensor data integration, an artificial intelligence module, a resource allocation and path optimization module implanted with a particle swarm algorithm, an intelligent communication protocol, and data processing equipment; Sensor data integration is used to integrate data from various sensors such as smoke detectors, temperature sensors, and gas sensors deployed within the airport to collect fire-related data. The implementation process includes data cleaning through low-pass filters, mean, and standard deviation calculations to remove noise and irrelevant information, outlier detection using box plot analysis and isolation forest algorithms to identify and handle outliers in the data to prevent misleading subsequent analysis, and feature extraction using Fourier transform and principal component analysis for subsequent analysis and decision-making; The artificial intelligence module is used in the personnel trajectory recognition system to assist the command center in monitoring and dispatching rescue operations; The implementation method is to use convolutional neural networks for image recognition to achieve early detection of fires; use optical flow methods and deep learning models to carry out personnel trajectory recognition, so as to provide the command center with real-time location information of rescue personnel and trapped people; The resource allocation and path optimization module implanted with the particle swarm algorithm is used to optimize the allocation of rescue resources including fire trucks, ambulances, and rescue personnel, and at the same time plan the best travel routes for rescue vehicles and personnel; In terms of implementation, the particle swarm algorithm is used to predict the fire development trend by combining historical fire data and environmental factors, and the optimization allocation of rescue resources is achieved by simulating the search behavior of the particle swarm; And the particle swarm algorithm is used to plan paths for rescue vehicles and personnel, which can be dynamically adjusted to avoid fire areas and congested sections; The intelligent communication protocol is used to achieve communication between rescue teams by developing and utilizing natural language processing technology; In terms of implementation, natural language processing technology is used to improve the accuracy and efficiency of communication; at the same time, a multi-agent system is constructed for the actions of different rescue departments, and cross-departmental collaborative operations are achieved through collaborative learning, and the multi-agent system can adjust communication strategies in real time; The data processing device is used to process a large amount of data; In terms of implementation, high-performance databases, MySQL and MongoDB are used to store sensor data, image data, and communication data; the distributed computing framework, Apache Spark is used to process a large amount of data; the stream processing algorithm, Apache Kafka is used to analyze real-time data streams, which can quickly identify fire emergencies and trigger the emergency response mechanism.

6. Emergency resource real-time scheduling method for aircraft sudden fire incidents, characterized in that: It adopts the aircraft sudden fire event emergency resource real-time scheduling system as described in any one of claims 1-5, and includes the following steps: Step 1: Build a basic information acquisition and display system; Step 2: Achieve intelligent analysis and decision support; Step 3; Ensure the execution and coordination of rescue operations.

7. The method for real-time scheduling of emergency resources for aircraft sudden fire incidents according to claim 6, characterized in that: In Step 1, specifically: Step 1.1: Multi-source data collection and preprocessing: Integrate smoke detectors, temperature sensors, and gas sensors in the airport through an intelligent software system to collect fire-related data in real time; Use low-pass filters, mean, and standard deviation calculations to clean the data, remove noise and irrelevant information; Use box plot analysis and isolation forest algorithms to detect and process outliers; Perform feature extraction using Fourier transform and principal component analysis to provide a data basis for subsequent decision-making; Step 1.

2. Visualization Information Display Platform Construction: On the one hand, the real-time video monitoring devices in the airport area transmit the fire scene video data to the screen display system in the emergency command center. The system uses a seamless splicing screen with a resolution of not less than 1920×1080 and a screen size of not less than 3m×2m, which can stably display the aircraft postures, GIS information, and real-time safety conditions of aircraft in the airport and adjacent areas, while displaying the operation instructions and resource allocation, and has functions of zooming in and out, adjusting the distance, and roaming, facilitating the comprehensive observation and analysis by emergency response personnel. On the other hand, the electronic sand table system projects the airport GIS map and 3D model information onto the electronic sand table through multiple projectors under the coordination of the fusion processor and the computer host. The electronic sand table has functions of multi-functional operation, interactivity, real-time interaction, and drawing, intuitively displaying the real-time ground environment and fire incident scenes in the airport and adjacent areas.

8. The method for real-time scheduling of emergency resources for aircraft sudden fire incidents according to claim 7, characterized in that: In Step 2, specifically: Step 2.

1. Fire Situation Prediction: The resource allocation and path optimization module implanted with the particle swarm algorithm in the intelligent software system integrates historical fire data and environmental factors to predict the fire development trend, providing a basis for subsequent rescue resource allocation and operation planning. Step 2.

2. Resource Optimization and Path Planning: The particle swarm optimization (PSO) algorithm is used to reasonably allocate fire trucks, ambulances, and rescue personnel, and at the same time plan the best travel routes for rescue vehicles and personnel, and can dynamically adjust according to the real-time situation, avoiding fire areas and congested sections to ensure the implementation of rescue operations. Step 2.

3. Auxiliary Decision-making: The persons in charge of each rescue department in the emergency command center carry out their work through the control seats of the remote control system. The remote control system consists of several control seat hosts, a speaker system, and a switch to form a local area network to realize information interconnection. The main control computer configures the functions and manages the permissions of each control seat computer. The persons in charge of each department formulate on-site fire fighting and rescue plans based on the information displayed by the screen display system and the electronic sand table system and the analysis results of the intelligent software system.

9. The method for real-time scheduling of emergency resources for aircraft sudden fire incidents according to claim 8, wherein: In Step 3, specifically: Step 3.

1. Rescue Operation Initiation and Execution: The personnel of each rescue department act quickly according to the instructions of the command center, and the fire trucks and ambulances drive towards the fire scene along the paths planned by the intelligent software system. Personnel Dynamic Monitoring and Scheduling: The intelligent software system uses artificial intelligence technology to achieve early fire detection through image recognition by the convolutional neural network, and carry out personnel trajectory recognition using the optical flow method and the deep learning model, providing the real-time position information of rescue personnel and trapped persons for the command center. Step 3.

2. Communication and Collaboration Guarantee: The rescue teams communicate through the intelligent communication protocol of the intelligent software system. The protocol uses natural language processing technology to construct a multi-agent system to simulate the actions of different rescue departments, and realizes cross-departmental collaborative operations through collaborative learning and adjusts the communication strategy in real time. Step 3.3, Real-time Monitoring and Dynamic Adjustment: The screen display system updates the progress of the rescue operation in real time, including the positions of rescue personnel, the driving status of rescue vehicles, and the changes in the fire situation at the fire scene; the commanders can accordingly timely grasp the rescue dynamics and make flexible decision adjustments to ensure the smooth progress of the rescue operation and ultimately achieve the response to aircraft sudden fire incidents.

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