Selection control system for treatment equipment for mass casualty aeromedical evacuation

Abstract

The present application belongs to the technical field of wounded information simulation, and particularly relates to a selection control system for treatment equipment of batch wounded air evacuation, which simulates the generation of air evacuation task scene by collecting geographic, wounded distribution, medical resource and meteorological information, constructs air evacuation path library, and matches medical materials and path according to wounded information and environment; utilizes wounded condition classification evaluation and deep reasoning model to generate individualized treatment technical scheme, intelligently selects medical equipment and control process, and optimizes air evacuation and treatment efficiency through simulation evaluation module to ensure real-time optimal state; users can also interactively select task scene, scheme and parameter setting through user interface module to realize efficient and accurate intelligent selection and control of batch wounded air evacuation and treatment equipment, and improve emergency medical rescue efficiency and quality.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of wounded information simulation, and particularly relates to a selection control system of treatment equipment for batch wounded air transportation. BACKGROUND

[0002] In the treatment of batch wounded, efficient air transportation is the key to guarantee the treatment quality and improve the survival rate. The traditional transportation decision mainly depends on the experience and intuition of the command personnel, lacking scientific prediction and evaluation means. This experience-oriented decision-making method has many shortcomings and deficiencies: first, the decision-making process lacks systematicness and scientificity, and it is difficult to fully consider various complex factors, such as the severity of the wounded, the distribution of medical resources, the traffic conditions and weather conditions of the transportation path, etc. Secondly, the traditional method cannot be dynamically adjusted and optimized, and once a sudden situation occurs, it is difficult to quickly respond effectively. The traditional decision-making method lacks pre-evaluation and post-feedback of the transportation effect, and it is difficult to form a closed-loop optimization mechanism, resulting in low accuracy and reliability of the decision-making. The main task of air transportation is to transport, and it is difficult to quickly and accurately transport batch personnel to the rear and use limited space to configure medical equipment to prevent the wounded from getting worse, which is a difficulty to be solved in the process of air transportation.

[0003] The patent application with publication number CN113871030A discloses an information system and working method for wounded air transportation, which is provided with a portable data terminal, a wounded information acquisition system, a storage module, a display interaction module, a wounded information identification module and a medical record rapid construction module. After collecting the data of life sign monitoring, on-the-way medical treatment and on-the-way medical nursing of the wounded, electronic injury ticket information is generated, and the uploaded medical record information corresponds to the injury ticket information and the wounded information. The wounded identity information is judged by the wounded information identification module, and the corresponding electronic injury ticket information is extracted from the storage module and sent to the display interaction module for display.

[0004] The above prior art has the following problems: existing air transportation is mainly focused on "rescue", ignoring the main rapid transportation process, lacking strategies for rapid transportation of large quantities of wounded, and in addition, the air transportation space is limited, how to use the limited space to configure the most effective medical equipment for temporary medical assistance to the wounded is also one of the problems to be solved in air transportation. Therefore, the present application provides a selection control system of treatment equipment for batch wounded air transportation. SUMMARY

[0005] In view of the deficiencies of the prior art, the application provides a selection control system of treatment equipment for batch wounded and sick person air evacuation, which simulates generation of an air evacuation task scene by collecting geographic, wounded and sick person distribution, medical resource and meteorological information, constructs an air evacuation path library, and matches medical supplies and paths according to wounded and sick person information and environment; utilizes wounded condition classification evaluation and deep reasoning model to generate an individualized treatment technical scheme, intelligently selects medical equipment and control process, and optimizes air evacuation and treatment efficiency through a simulation evaluation module to ensure real-time optimal state; the user can also interactively select a task scene, scheme and parameter setting through a user interface module to realize efficient and accurate intelligent selection and control of batch wounded and sick person air evacuation and treatment equipment, and improve emergency medical rescue efficiency and quality.

[0006] To achieve the above object, the application provides the following technical scheme: a selection control system of treatment equipment for batch wounded and sick person air evacuation, comprising a data management module, a scene modeling module, an evacuation decision module and a treatment decision module;

[0007] According to various treatment scene information stored by the data management module and air evacuation treatment simulation information under the corresponding scene, the scene modeling module generates different types of air evacuation task scene spaces and corresponding batch wounded and sick person distribution information, medical supply distribution information, rescue environment and meteorological state and corresponding air evacuation path library under each space;

[0008] The evacuation decision module comprises a medical supply configuration unit and a collaborative path configuration unit; according to the distribution information of batch wounded and sick persons and the medical supply distribution information under the corresponding scene, the medical supply configuration unit is used for scheduling and configuring medical equipment and personnel supplies for the rescue helicopter, and according to the rescue environment and meteorological state and the corresponding air evacuation path library, the collaborative path configuration unit is used for air evacuation path configuration for the rescue helicopter;

[0009] The treatment decision module comprises a wounded condition classification evaluation unit, a treatment technology selection unit and a medical equipment selection unit; according to the wounded type information of batch wounded and sick persons under the corresponding scene, the wounded condition classification evaluation unit is used to obtain the wounded condition evaluation score and disease development trend of each corresponding wounded type of corresponding wounded person after classification, and the deep reasoning model configured by the treatment technology selection unit and the distributed storage unit in the data management module is used to generate a treatment technical scheme of corresponding wounded person according to the wounded condition evaluation score and disease development trend of corresponding wounded type of wounded person, and the medical equipment selection unit is used to match and select corresponding treatment medical equipment according to the corresponding treatment technical scheme and the medical equipment of the helicopter configuration, and generate medical equipment control instructions, and the disease development trend is used to adjust the treatment technical scheme and medical equipment control instruction parameters in real time.

[0010] Specifically, the selection control system further comprises a simulation evaluation module; the evacuation decision module further comprises an evacuation decision adjustment unit; and the treatment decision module further comprises a treatment decision adjustment unit.

[0011] The simulation evaluation module evaluates the efficiency of medical material allocation and path allocation in the evacuation decision module and the generation of a treatment technical solution and treatment medical equipment in the treatment decision module, selects the efficiency of treatment control, performs multi-dimensional simulation evaluation, obtains the path and medical allocation efficiency in the air evacuation decision in the evacuation decision module, and the injury classification evaluation and selection efficiency of treatment medical equipment in the treatment technical decision in the treatment decision module, and feeds back the path and medical allocation efficiency in the air evacuation decision to the evacuation decision adjustment unit, and feeds back the injury classification evaluation and selection efficiency of treatment medical equipment in the treatment technical decision to the treatment decision adjustment unit, to respectively adjust the air evacuation decision and the treatment technical decision in real time.

[0012] Specifically, the air evacuation and treatment simulation information corresponding to the scene includes geographic information, wounded personnel distribution information, personnel and material information, medical equipment information, air evacuation path information, and weather information.

[0013] The scene modeling module comprises a scene modeling unit and a scene path library unit; the workflow of the scene path library unit comprises:

[0014] A1, generating and constructing a current type air evacuation task scene space through the scene modeling unit, and configuring corresponding geographic location information, wounded personnel distribution state, adjustable personnel and material state, medical equipment information, and dynamic weather state in the current type air evacuation task scene space through the air evacuation and treatment simulation information;

[0015] A2, according to the geographic location information configured after the air evacuation task scene space, obtaining the map layer space of the target region corresponding to the current air evacuation task scene space through a map layer algorithm;

[0016] A3, according to the map layer space of the target region and the wounded personnel distribution state, obtaining the latitude and longitude position information of each wounded personnel in the map layer space, inputting the latitude and longitude position information of the wounded personnel into a clustering algorithm, obtaining the wounded personnel clustering distribution sub-region and the number of wounded personnel in each sub-region, and labeling each sub-region.

[0017] Specifically, the workflow of the scene path library unit further comprises:

[0018] A4, based on the wounded personnel clustering distribution sub-region label and the number of wounded personnel in each sub-region, the maximum number of rescued wounded personnel in a single rescue of a rescue helicopter, and the dynamic weather state corresponding to the map layer space, constructing an input chromosome of a genetic algorithm P iand P, where X i and Y i respectively represent the take-off and landing target area position corresponding to the i-th rescue helicopter, p jk respectively represent the longitude and latitude position corresponding to the k-th wounded person in the j-th wounded person clustering distribution sub-area, N1 represents the total number of wounded persons corresponding to the current map layer space, N2 represents the total number of callable helicopters corresponding to the current map layer space, N j respectively represent the number of wounded persons corresponding to the j-th wounded person clustering distribution sub-area, f j respectively represent the number of required rescue helicopters corresponding to the j-th wounded person clustering distribution sub-area, and respectively represent the wind force level, wind direction and visibility corresponding to the current map layer space, f i respectively represent the safety score of the path corresponding to the rescue task performed by the i-th helicopter under the current meteorological condition of the current map layer space, P i respectively represent the feasible path generation parameter space corresponding to the i-th helicopter; P represents the cooperative parameter space of the feasible paths corresponding to all helicopters;

[0019] A5, based on the input chromosome of the genetic algorithm, the fitness function F of the feasible path of a single helicopter is constructed i and the helicopter cooperative path fitness function F, specifically: F i ≥ F0, where l i respectively represent the length of the feasible path corresponding to the i-th helicopter, T i respectively represent the total flight time of the feasible path corresponding to the i-th helicopter, w1, w2 and w3 represent the weighting coefficients in the fitness function in turn, and F0 represents the fitness threshold value of the feasible path corresponding to the i-th helicopter.

[0020] Specifically, the workflow of the scene path library unit further includes:

[0021] A6, set the maximum number of iterations g max and the change rate stop threshold θ u , iterate the genetic algorithm, and calculate the change rate of the Pareto front The specific formula is wherein, U t-i respectively represent the Pareto front solution set of the t-i-th generation obtained in the iteration process of the genetic algorithm, x ∈ U t-i respectively represent x as one of the solutions in the Pareto front solution set of the t-i-th generation obtained, y represents one of the solutions in the Pareto front solution set of the t-th generation obtained, and || ||2 represents the 2-norm symbol;

[0022] A7, based on the maximum number of iterations and the change rate stop threshold set in A6, the A4-A6 process is iteratively calculated, when When the iteration stops, the optimal generation parameter space of the feasible path corresponding to the ith helicopter and the optimal coordination parameter space of all feasible paths corresponding to N2 helicopters are output;

[0023] A8, input the obtained optimal generation parameter space of the feasible path corresponding to the ith helicopter and the optimal coordination parameter space of all feasible paths corresponding to N2 helicopters into the Dijkstra algorithm to obtain the coordinated feasible path corresponding to all helicopters under the current meteorological state;

[0024] A9, construct the air evacuation path library corresponding to the current type of air evacuation task scene space by using the coordinated feasible path corresponding to all helicopters, and update the air evacuation path library in real time by using the dynamic meteorological state at each moment.

[0025] Specifically, the generation step of the treatment technical scheme corresponding to the wounded and sick personnel includes:

[0026] B1, obtain the basic information, physiological parameters and wound description text information of each simulated wounded and sick personnel from the map layer space configured in A2 and preprocess, and input the preprocessed data into the dynamic electronic medical record with an embedded text automatic updating model to obtain a personal dynamic electronic medical record table and a dynamic physiological parameter table;

[0027] B2, input the personal dynamic electronic medical record table into the wound classification model for real-time wound classification;

[0028] B3, input the obtained wound type and corresponding dynamic physiological parameter table into the configured trauma scoring subsystem and Glasgow coma scoring subsystem to obtain the trauma assessment score and coma assessment score corresponding to the wounded and sick personnel and the comprehensive wound severity assessment score corresponding to the wounded and sick personnel.

[0029] Specifically, the generation step of the treatment technical scheme corresponding to the wounded and sick personnel further includes:

[0030] B4, input the trauma assessment score, coma assessment score and comprehensive wound severity assessment score corresponding to the wounded and sick personnel and the real-time obtained dynamic physiological parameter table into the pre-constructed wound change prediction model to obtain the severity change trend of the type of wound corresponding to each wounded and sick personnel;

[0031] B5, input the personal dynamic electronic medical record table, dynamic physiological parameter table, trauma assessment score, coma assessment score and comprehensive wound severity assessment score corresponding to the wounded and sick personnel into the configured matching generation model to match the treatment technical specification corresponding to the wounded and sick personnel from the distributed node reasoning database embedded in the data management module, and generate a treatment technical implementation process structure table corresponding to the wounded and sick personnel;

[0032] Specifically, the generating step of the treatment technical solution corresponding to the wounded and sick person further comprises:

[0033] B6, input the generated treatment technical implementation process structure table and the injury severity trend corresponding to the wounded and sick person into the deep reasoning model configured by the distributed node reasoning database, perform physical verification on the generated treatment technical implementation process structure table, and evaluate the professionalism and standardization of the treatment technical implementation process structure table by using the expert verification sub-model matched in the deep reasoning model, to obtain a corresponding professional evaluation score;

[0034] B7, set a professional evaluation score threshold, when the professional evaluation score is greater than the professional evaluation score threshold, output the corresponding treatment technical implementation process structure table, and output the prepared treatment technical specification process structure table corresponding to the injury severity trend.

[0035] Specifically, the step of generating the medical equipment control instruction comprises:

[0036] C1, according to the obtained treatment technical implementation process structure table, the matching medical equipment table corresponding to the current injury type of the wounded and sick person is obtained from the medical equipment information saved in the distributed node reasoning database and the medical equipment configured in the current rescue helicopter by a matching algorithm, and a matching medical equipment use process is generated;

[0037] C2, according to the prepared treatment technical specification process structure table, the matching medical equipment table is updated by a matching algorithm, and an updated matching medical equipment table is obtained;

[0038] C3, according to the treatment technical process information in the treatment technical implementation process structure table, the physiological parameter information of the corresponding wounded and sick person, and the matching medical equipment use process, the process control instruction of the corresponding medical equipment in the matching medical equipment table is generated by a control algorithm, and the corresponding equipment is controlled to perform emergency rescue on the wounded and sick person;

[0039] C4, using the prepared treatment technical specification process structure table, a prepared equipment control instruction is generated by a control algorithm, and when the corresponding wounded and sick person changes, the prepared equipment in the updated matching medical equipment table is controlled by the prepared equipment control instruction to perform real-time treatment on the changed condition of the corresponding wounded and sick person.

[0040] Compared with the prior art, the beneficial effects of the present application are:

[0041] The present application aims at the deficiencies of the prior art, collects various rescue scene information and air transport evacuation rescue simulation information under the corresponding scene through the data management module, and classifies and stores the data at different nodes to ensure the comprehensiveness and accuracy of the data; the scene modeling module generates different types of air transport evacuation task scene spaces and the distribution information of batches of wounded and sick under each space, the distribution information of medical supplies, the rescue environment and meteorological state, and the corresponding air transport evacuation path library, to provide a scientific basis for decision-making; the medical supply configuration unit and the collaborative path configuration unit in the evacuation decision module, according to the distribution of wounded and sick and the distribution of medical supplies, efficiently schedule and configure the rescue helicopters, and select the optimal path according to the rescue environment and meteorological state, to ensure fast and safe air transport evacuation. The injury classification assessment unit, the rescue technology selection unit and the medical equipment selection unit in the rescue decision module, through the assessment of the injury of the wounded and sick and the prediction of the disease development trend, generate individualized rescue technology solutions, and select the most suitable medical equipment for temporary medical assistance, through real-time adjustment of the rescue scheme and control instruction parameters, to ensure the accuracy and effectiveness of the rescue; the system not only solves the problems of fast transportation and limited space medical equipment configuration in the prior art, but also improves the overall efficiency and rescue quality of air transport evacuation. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 Figure 1 is a module diagram of the selection control system of the rescue equipment for batch wounded and sick air transport evacuation according to Embodiment 1 of the present application.

[0043] Figure 2 Figure 2 is a work flow architecture diagram of the selection control system of the rescue equipment for batch wounded and sick air transport evacuation according to Embodiment 2 of the present application. DETAILED DESCRIPTION

[0044] Embodiment 1

[0045] Please refer to Figure 1 An embodiment provided by the present application is a selection control system of rescue equipment for batch wounded and sick air transport evacuation, which comprises a data management module, a scene modeling module, an evacuation decision module, a rescue decision module, a simulation evaluation module and a user interface module.

[0046] The data management module is used for collecting, storing and managing various rescue scene data and rescue process data; the data management module comprises a data collection unit and a distributed storage unit.

[0047] The data collection unit is used for collecting and preprocessing geographic information, wounded and sick distribution information, medical resource information and meteorological information under various rescue scenes; the medical resource information comprises medical equipment configuration information, rescue specification library configuration information and adjustable medical personnel configuration information.

[0048] Further, if the embodiment is based on air transportation of batch casualties in naval battle, the treatment specification library configuration information includes treatment methods and treatment technical specification process information for various types of injuries of batch casualties in naval battle;

[0049] Further, for the treatment technical specification process information, since the embodiment is based on air transportation of batch casualties in naval battle, the most important treatment technology in the air transportation process of naval battle is the tracheal management and hemostasis technology treatment specification;

[0050] The distributed storage unit classifies the data preprocessed by the data collection unit through a classification algorithm, and stores the classified data in the distributed node reasoning database;

[0051] Further, the distributed node reasoning database in the embodiment is constructed by a knowledge graph algorithm and a graph database; the distributed node reasoning database is configured with a deep reasoning model, and the distributed node reasoning database is composed of multiple storage nodes, including a first scene storage node, which is mounted with a scene modeling information storage node, a medical equipment information storage node, a treatment method and treatment specification storage node, an adjustable medical personnel and material information storage node, and a real scene geographic information and weather information storage node; further, the deep reasoning model in the embodiment is constructed by a Chinese pre-trained Bert reasoning model;

[0052] The scene modeling module is used to simulate different air transportation task scene data and construct different scene simulation spaces;

[0053] The scene modeling module includes a scene modeling unit, a casualty distribution unit, a medical material simulation unit, an environmental meteorological simulation unit, and a scene path library unit;

[0054] The scene modeling unit is used to generate and construct different types of air transportation task scene spaces through a scene generation algorithm according to the information saved by the distributed storage unit; in the embodiment, different types of air transportation task scene spaces include ship battle, beach landing, island contention, sea rescue, adverse weather conditions (such as storm and strong wind), and night combat, etc.

[0055] The casualty distribution unit is used to simulate the distribution position information and the corresponding injury type information of batch casualties according to different air transportation task scene space information;

[0056] Further, in the embodiment, the air transportation of batch casualties in naval battle is simulated, and the corresponding various distribution positions and corresponding injury types of naval battle casualties in the naval battle process are simulated, such as gunshot wound, explosion injury, drowning, burn injury, fracture, internal hemorrhage, craniocerebral injury, infection, and hypothermia, etc.

[0057] An environmental meteorological simulation unit is configured to simulate different rescue environments and meteorological conditions corresponding to air evacuation according to geographical information and meteorological information data corresponding to historical scenarios stored in the distributed storage unit.

[0058] A medical material simulation unit is configured to simulate distribution state information of medical materials corresponding to different air evacuation task scenarios; the medical materials include the number of rescue personnel, the number of rescue aircraft, and other battlefield rescue material data.

[0059] Further, in this embodiment, the key technology of special environment batch wounded air evacuation equipment is taken as an example to simulate battlefield medical materials and equipment in sea warfare;

[0060] In this embodiment, according to the tasks and modified configurations of the general medical aircraft, general medical materials and special medical material modules are designed and developed, including common modules, first-aid modules, epidemic prevention modules, burn modules, plateau modules, and sea warfare injury modules, etc. Appearance indicators, internal design indicators, and medical material quantity standards are required for each module. The modules have primary first-aid and advanced first-aid capabilities specified in the new version of the war injury treatment rules, and special modules have special functions according to different tasks and environmental characteristics.

[0061] First, the module indicators and design schemes are proposed according to the combat requirements and task requirements. After multiple rounds of expert demonstrations, sample pieces (mobile, integrated drag-and-pull integrated box, and back-and-pull dual-purpose bag) are produced. Through continuous optimization and modification through army trial and on-board exercise, the final design is finalized. Through the above-mentioned general medical aircraft configuration of drugs and corresponding medical equipment modules, professional simulation of medical materials and medical equipment is carried out.

[0062] Further, in this embodiment, the key technology specifications of the air evacuation medical treatment technology of the general medical aircraft include:

[0063] (1) According to the characteristics of the injury and injury type of the wounded in the plateau and sea special environment, and the secondary injury caused by the aviation environment in air evacuation medical evacuation, a special environment air evacuation medical treatment scheme and a wounded disposal scheme during air transfer are proposed to form a draft of the key treatment technology specifications for special environment (plateau and far sea) air evacuation of the wounded.

[0064] (2) Through intelligence analysis, demand research, and research, technical requirements for special equipment for air evacuation of batch wounded in plateau and far sea are proposed. According to the air evacuation medical treatment task and modified configuration based on the general medical rescue aircraft, an integrated technical scheme of special medical material modules for air evacuation medical treatment is proposed, including on-board treatment basic modules, first-aid modules, auxiliary diagnosis modules, epidemic prevention modules, and special modules such as burn modules, and a development scheme of an air portable auxiliary diagnosis platform and a ground transfer portable integrated rapid medical diagnosis platform is proposed.

[0065] (3) Develop a “mass air evacuation and evacuation simulation decision support system”. The system has prediction, decision-making and evaluation functions. It supports modeling the evacuation mission scenario and supports the formation of evacuation decisions based on the evacuation mission scenario, including how to dispatch medical rescue aircraft, medical personnel, medicines and equipment and other medical resources, as well as planning the evacuation route. It uses simulation technology to simulate the implementation of evacuation decisions, provides data support for evaluating the implementation effect of decisions, and provides auxiliary decision support for the mass air evacuation and evacuation of wounded and sick personnel. It is available for use by airborne medical authorities, war zone medical authorities and related hospitals.

[0066] The scenario path library unit is used to generate and construct air transport path libraries for different scenarios based on different air transport and delivery scenario tasks and corresponding geographical and meteorological information through path generation algorithms.

[0067] Furthermore, in this embodiment, the simulated information for air transport evacuation and treatment in the corresponding scenario includes geographical information, distribution information of the wounded and sick, personnel and material information, medical equipment information, air transport evacuation route information, and meteorological information;

[0068] The scene modeling module includes a scene modeling unit and a scene path library unit; the workflow of the scene path library unit includes:

[0069] A1. Generate and construct the current type of air evacuation mission scenario space through the scenario modeling unit, and configure the corresponding geographical location information, patient distribution status, available personnel and material status, medical equipment information and dynamic weather status of the current type of air evacuation mission scenario space through air evacuation and medical treatment simulation information.

[0070] A2. Based on the geographical location information configured in the air transport and delivery mission scenario space, obtain the map layer space of the target area corresponding to the current air transport and delivery mission scenario space through map layer algorithms.

[0071] A3. Based on the map layer space of the target area and the distribution of the wounded and sick, obtain the latitude and longitude location information of each wounded and sick person in the map layer space, input the latitude and longitude location information of the wounded and sick persons into the clustering algorithm, obtain the cluster distribution sub-regions of the wounded and sick persons and the number of wounded and sick persons in each sub-region, and label each sub-region.

[0072] A4. Construct the input chromosome for the genetic algorithm based on the sub-region labels of the patient cluster distribution, the number of patients in each sub-region, the maximum number of patients that a rescue helicopter can rescue in a single trip, and the dynamic weather conditions corresponding to the map layer space. P i and P, where X i and Y i p represents the takeoff and landing target area locations corresponding to the i-th rescue helicopter, respectively. jkN represents the latitude and longitude of the k-th wounded soldier in the j-th cluster distribution sub-region, N1 represents the total number of wounded soldiers in the current map layer space, N2 represents the total number of available helicopters in the current map layer space, and N... j f represents the number of wounded soldiers corresponding to the j-th cluster distribution sub-region of wounded soldiers. j This represents the number of rescue helicopters required for the j-th cluster of wounded and sick personnel. and f represents the wind force level, wind direction, and visibility corresponding to the current map layer, respectively. i P represents the safety score of the path taken by the i-th helicopter in the current map layer space under the current weather conditions for carrying out a rescue mission. i Let represent the parameter space for generating feasible paths for the i-th helicopter; P represents the collaborative parameter space for feasible paths for all helicopters.

[0073] A5. Constructing a single helicopter feasible path fitness function F based on the input chromosomes of a genetic algorithm. i The fitness function F for the cooperative path with the helicopter is as follows: F i ≥F0, where, l i T represents the length of the feasible path corresponding to the i-th helicopter. i Let w1, w2, and w3 represent the total flight time of the feasible path corresponding to the i-th helicopter, w1, w2, and w3 represent the weighting coefficients in the fitness function, and F0 represent the fitness threshold of the feasible path corresponding to the i-th helicopter.

[0074] A6. Set the maximum number of iterations g max and the rate of change stopping threshold θ u The genetic algorithm is iterated, and the Pareto front rate of change is calculated. The specific formula is as follows: Among them, U t-i Let x∈U be the Pareto front solution set obtained in the ti-th generation during the iteration of the genetic algorithm. t-i Let x represent a solution in the Pareto front solution set obtained in the ti-th generation, and y represent a solution in the Pareto front solution set obtained in the t-th generation, where || ||2 represents the 2-norm symbol;

[0075] A7. Based on the maximum number of iterations and the rate of change stopping threshold set in A6, iteratively calculate the process from A4 to A6. When the iteration stops, the output is the optimal generation parameter space of the feasible path corresponding to the i-th helicopter and the optimal cooperative parameter space of all feasible paths corresponding to N2 helicopters.

[0076] A8. Input the optimal generation parameter space of the feasible path corresponding to the i-th helicopter and the optimal cooperative parameter space of all feasible paths corresponding to N2 helicopters into the Dijkstra algorithm to obtain the cooperative feasible paths corresponding to all helicopters under the current weather conditions.

[0077] A9. Construct an air transport route library corresponding to the current type of air transport evacuation mission scenario space using all the collaborative feasible routes corresponding to the helicopters, and update the air transport route library in real time using the dynamic weather status at each moment.

[0078] The evacuation decision module is used to generate the optimal evacuation decision plan based on the simulated task scenario, including medical resource scheduling and evacuation route planning.

[0079] The follow-up decision module includes a medical supplies configuration unit, a collaborative path configuration unit, and a follow-up decision adjustment unit;

[0080] The medical supplies configuration unit is used to schedule and configure medical equipment and personnel supplies based on the batch of wounded and sick personnel information and corresponding injury and illness types simulated by the wounded and sick personnel distribution unit in the corresponding air transport evacuation scenario. The configuration of medical supplies includes the quantity of rescue medical equipment, the number of rescue aircraft, and other battlefield rescue supplies data. Other battlefield rescue supplies data include medicines, gauze, bandages, etc.

[0081] Furthermore, this embodiment takes the key technologies of special equipment for the air transport and evacuation of large numbers of wounded and sick personnel in special environments as an example to demonstrate the configuration of medical equipment and supplies for rescue helicopters;

[0082] In this embodiment, based on the missions and modified configurations of general-purpose medical aircraft, general-purpose and special-purpose medical material modules are designed and developed, including conventional modules, first aid modules, epidemic prevention modules, burn modules, high-altitude modules, and naval combat injury modules. Each module needs to propose appearance indicators, internal design indicators, and medical material quality standards.

[0083] It possesses the basic and advanced first aid capabilities stipulated in the new version of the combat casualty treatment rules, and special modules highlight dedicated functions according to different mission and environmental characteristics. First, the indicators and design schemes of each module were proposed based on operational needs and mission requirements. After multiple rounds of expert demonstrations, prototypes (mobile, integrated towing box, and dual-purpose backpack / towing bag) were produced. Through troop trials and airborne exercises, it was continuously optimized, modified, and improved before being finalized.

[0084] The collaborative path configuration unit simulates and constructs specific air evacuation patient distribution information, geographical location information, and meteorological information based on the scenario modeling module. It matches the corresponding air evacuation path from the air evacuation path library through matching and path adjustment algorithms, adjusts the matched path, and configures the matched path information into different transport aircraft. It then coordinates and controls the rescue aircraft to quickly reach different patient distribution locations and quickly transport the patients back to the rear.

[0085] Furthermore, the path adjustment algorithm in this embodiment utilizes the specific input parameters of the genetic algorithm for the A4-A7 process to achieve the effect of adjusting the specific airlift route;

[0086] This process, through a scenario modeling module and a evacuation decision-making module, enables the system to simulate different air evacuation mission scenarios, construct simulation spaces for different scenarios, and generate optimal evacuation decision-making schemes. This process includes multiple stages such as scenario modeling, casualty distribution, medical supply simulation, environmental and meteorological simulation, and route database construction. Each stage employs advanced algorithms and technologies to ensure the scientific nature and accuracy of evacuation decisions. For example, the scenario modeling unit generates different types of air evacuation mission scenario spaces through scenario generation algorithms, such as naval combat, beach landing, and island conquest, providing basic data for subsequent casualty distribution and medical supply allocation. The casualty distribution unit simulates the distribution location and injury type of batches of casualties according to different mission scenarios, ensuring the rational allocation of medical resources.

[0087] The medical supplies allocation unit, based on simulated mass casualty information and corresponding injury / illness types, allocates and deploys medical equipment and personnel supplies. Specifically, for missions and modified configurations of general-purpose medical aircraft, it has designed and developed general-purpose and specialized medical supplies modules, including conventional, emergency, epidemic prevention, burn, high-altitude, and naval combat injury modules. These modules possess the primary and advanced emergency medical capabilities stipulated in the new version of the combat casualty treatment rules, and highlight specialized functions based on different mission and environmental characteristics. Through multiple rounds of expert review and troop trials, the system has been continuously optimized and improved before finalization. This refined medical supplies allocation not only improves treatment efficiency but also ensures the rational use of medical resources and avoids waste.

[0088] The collaborative path configuration unit, based on the simulated distribution, geographic location, and meteorological information of the airlifted casualties, matches corresponding airlift paths from the airlift path library using matching and path adjustment algorithms, and adjusts the matched paths accordingly. The scenario path library unit generates and constructs airlift path libraries for different scenarios using genetic and Dijkstra's algorithms. The genetic algorithm optimizes path length, flight time, and safety by constructing fitness functions for individual helicopter feasible paths and collaborative helicopter paths. Dijkstra's algorithm generates collaborative feasible paths for all helicopters under the current dynamic weather conditions. This efficient path planning not only shortens rescue time but also improves path safety, ensuring that the casualties can receive timely and safe treatment.

[0089] The follow-up decision adjustment unit is used to adjust the medical supplies configuration and the generated collaborative transportation path information in the current follow-up decision based on real-time information from the simulated scene.

[0090] The treatment decision module is used to generate corresponding treatment plans based on the status information of simulated wounded and sick personnel. The treatment decision module includes an injury classification and assessment unit, a treatment technology selection unit, a medical equipment selection unit, and a treatment decision adjustment unit.

[0091] The injury classification and assessment unit is used to classify the injuries and illnesses of a batch of wounded and sick personnel based on the simulated batch injury and illness type information through a classification and assessment algorithm. It also assesses the current status information of each corresponding wounded and sick personnel after classification, obtains the injury assessment score for each type of injury and sick personnel, and obtains the corresponding injury and illness development trend of each wounded and sick personnel through an expert prediction model based on the current status information of the wounded and sick personnel.

[0092] The treatment technology selection unit is used to generate treatment technology solutions for each patient based on the type of injury, injury assessment score, and disease progression trend of each patient obtained from the injury classification and assessment unit, through a generation algorithm and a distributed node reasoning database.

[0093] Furthermore, the treatment solutions generated in this embodiment are all based on existing medical treatment guidelines and text information. This generation involves professional integration of existing treatment guidelines and techniques, without creating anything out of thin air. Moreover, the generated solutions are all generated by models trained by experts, and are based on existing medical treatment guidelines. There are no ethical or professional issues. This embodiment does not generate information that is not in the medical treatment guidelines. All generation is based on the medical treatment guidelines and text information, integrating the treatment process text of the treatment technical guidelines corresponding to the injury and symptoms.

[0094] Furthermore, the steps for generating the corresponding treatment plan for the wounded and sick in this embodiment include:

[0095] B1. Obtain basic information, physiological parameters and injury description text information of each simulated patient from the map layer space configured in A2 and preprocess it. At the same time, input the preprocessed data into the dynamic electronic medical record with built-in automatic text update model to obtain the individual dynamic electronic medical record table and dynamic physiological parameter table.

[0096] B2. Input the individual dynamic electronic medical record into the injury and illness classification model with built-in expert experience information for real-time injury and illness classification; further, in this embodiment, the expert experience information is the historical medical rescue and diagnosis information of professionals in various specialties of naval combat rescue.

[0097] B3. Input the obtained injury type and corresponding dynamic physiological parameter table into the trauma scoring subsystem and Glasgow coma scoring subsystem to obtain the corresponding injury assessment score, coma assessment score and comprehensive injury severity assessment score of the corresponding patient.

[0098] B4. Input the corresponding trauma assessment score, coma assessment score, and comprehensive injury severity assessment score of the corresponding wounded patient, as well as the real-time dynamic physiological parameter table, into the injury and illness change prediction model pre-built using Bilstm and expert experience method to obtain the change trend of the severity of each type of injury and illness for each wounded patient.

[0099] B5. Input the individual dynamic electronic medical record, dynamic physiological parameter table, trauma assessment score, coma assessment score, and corresponding comprehensive injury severity assessment score of the injured patient into the configured matching generation model. Match the corresponding treatment technical specifications for the injured patient from the distributed node inference database built into the data management module, and generate the corresponding treatment technical implementation process structure table for the injured patient.

[0100] B6. The generated treatment technology implementation process structure table and the trend of injury severity change of the corresponding wounded and sick are input into the deep inference model configured in the distributed node inference database. The generated treatment technology implementation process structure table is physically verified, and the professionalism and standardization of the treatment technology implementation process structure table are evaluated by the expert verification sub-model matched in the deep inference model to obtain the corresponding professional evaluation score.

[0101] B7. Set a professional assessment score threshold. When the professional assessment score is greater than the professional assessment score threshold, output the corresponding treatment technology implementation process structure table, and at the same time output the preparatory treatment technology specification process structure table corresponding to the trend of change in the severity of injury and illness.

[0102] Through its treatment decision-making module, the system can automatically generate personalized treatment plans based on the current status of simulated patients. This process includes multiple stages such as injury classification and assessment, treatment technology selection, medical equipment selection, and treatment technology decision adjustment. Each stage employs advanced algorithms and technologies to ensure the scientific rigor and accuracy of the treatment plan. For example, the injury classification and assessment unit uses a classification algorithm to categorize the injuries of a batch of patients and combines it with an expert prediction model to obtain the disease progression trend of the patients, providing accurate basic data for subsequent treatment technology selection. The treatment technology selection unit uses a disease change prediction model built using Bilstm and expert experience to generate personalized treatment plans for each patient, ensuring the targetedness and effectiveness of the treatment plan.

[0103] The medical equipment selection unit is used to select the corresponding medical equipment for the treatment plan based on the obtained treatment plan and the medical supplies configured by the medical supplies configuration unit. Based on the treatment process and the development trend of the patient's condition in the treatment plan, the unit generates control instructions through the control algorithm to control and adjust the parameters of the corresponding treatment plan and medical equipment treatment plan to carry out treatment for the corresponding symptoms and illnesses.

[0104] Furthermore, in this embodiment, the step of generating medical device control instructions includes:

[0105] C1. Based on the obtained rescue technology implementation process structure table, the medical equipment information stored in the distributed node reasoning database and the medical equipment currently configured on the rescue helicopter are matched and obtained from the matching medical equipment table for the current injury and illness type of the corresponding patient, and the corresponding matching medical equipment usage process is generated.

[0106] C2. Based on the pre-treatment technical specification process structure table, the matching medical equipment table is updated by matching algorithm to supplement and update the matching medical equipment table according to the changes in the injury, and the updated matching medical equipment table is obtained.

[0107] C3. Based on the rescue technology process information in the rescue technology implementation process structure table, the corresponding patient physiological parameter information, and the matching medical equipment usage process, generate process control instructions for the corresponding medical equipment in the matching medical equipment table through the control algorithm, and control the corresponding equipment to carry out emergency rescue for the patient.

[0108] C4. Utilize the pre-treatment technical specification process structure table, and generate pre-treatment equipment control instructions through a control algorithm. When the corresponding wounded or sick person changes, control the pre-treatment equipment in the updated matching medical equipment table through the pre-treatment equipment control instructions to provide real-time treatment for the changed condition of the corresponding wounded or sick person.

[0109] The medical equipment selection unit retrieves matching medical equipment from the distributed node inference database using a matching algorithm and generates corresponding control commands, ensuring the efficient use of medical resources. Especially during air evacuation, where helicopters have limited medical equipment, precise matching and control can maximize the use of existing medical equipment and avoid resource waste. In addition, the system adjusts treatment plans and medical equipment usage parameters in real time according to the development trend of the patients' conditions, ensuring that each patient receives the most timely and effective treatment even with limited resources.

[0110] The treatment plans generated by this system are based on existing medical guidelines and treatment text information, integrating the entire process to ensure that all generated plans comply with medical standards and are free from ethical and professional issues. By inputting the generated treatment implementation process structure table and the trend of injury severity into a deep reasoning model for verification, the system can evaluate the professionalism and standardization of the treatment plans, obtaining a professional assessment score. Only when the professional assessment score exceeds a set threshold will the system output the final treatment plan, ensuring the scientific rigor and reliability of the treatment process. This transparent decision-making process not only increases medical staff's trust in the system but also facilitates subsequent auditing and optimization.

[0111] The treatment decision adjustment unit is used to adjust the generated treatment technology plan and selected medical equipment based on the real-time injury status information of the wounded and sick and the predicted trend of injury changes, so that each wounded and sick can receive the most timely and correct treatment.

[0112] The simulation evaluation module is used to evaluate the efficiency of route and medical configuration in air evacuation decision-making and the efficiency of injury classification and selection of treatment equipment in rescue technology decision-making. It performs real-time multi-dimensional simulation evaluation through a configured multi-dimensional simulation evaluation algorithm and feeds the evaluation results back to the rescue decision adjustment unit and the evacuation decision adjustment unit.

[0113] The user interface module is used to simulate mission scenarios, air evacuation plans, and medical treatment plans, allowing for interactive selection and parameter settings. It also incorporates AR navigation technology to assist medical personnel in quickly locating wounded and sick personnel on the battlefield.

[0114] Example 2

[0115] Please see Figure 2 Another embodiment of the present invention provides a workflow for a selection and control system for medical equipment used in the mass airlift of wounded and sick personnel, specifically as follows:

[0116] First, the data collection unit collects various rescue scenario information, as well as corresponding geographic information, patient distribution information, medical resource information, medical equipment information, air transport evacuation route information, and meteorological information under the scenario, and performs preprocessing. The preprocessed data is then classified and stored in a distributed storage unit.

[0117] Second, through the scenario modeling unit, based on the historical scenario information stored in the distributed storage unit, different types of air evacuation mission scenario spaces are simulated and generated. Based on the scenario space information of different air evacuation missions, the distribution location information of batches of wounded and sick personnel, the corresponding injury and illness information, and the corresponding medical supply distribution status information of different air evacuation scenarios are simulated through the patient distribution unit and the medical supply simulation unit. At the same time, through the environmental and meteorological simulation unit, the rescue environment and meteorological conditions corresponding to different air evacuation scenarios are simulated through the geographical location information and meteorological information in the scenario space information of the air evacuation missions.

[0118] Third, based on different air evacuation scenarios and corresponding geographical, meteorological, and patient distribution information, the scenario path library unit generates and constructs air evacuation path libraries for different scenarios.

[0119] Fourth, based on the batch of casualties and their corresponding injury types in the corresponding scenarios, the medical supplies configuration unit schedules and configures medical equipment and personnel supplies for multiple helicopters participating in the rescue. At the same time, based on the location distribution information, geographical location information, and meteorological information of the casualties being airlifted, the collaborative path configuration unit matches the corresponding path information from the airlift path database and configures the matched path information into different transport aircraft, so as to coordinate and control the rescue aircraft to quickly reach the different locations of the casualties for airlift rescue.

[0120] Fifth, based on the simulated batch of casualties' injury and illness information in the corresponding air transport evacuation scenario, the injury classification and assessment unit evaluates the current status of each corresponding casualty after classification, obtaining an assessment score for each casualty's corresponding injury type. Simultaneously, based on the casualty's current status information, an expert prediction model is used to obtain the corresponding casualty's condition development trend. The injury assessment score and condition development trend for each casualty are then input into the treatment technology selection unit. Based on the deep reasoning model of treatment methods, treatment specifications, and configurations stored in the distributed storage unit, a treatment technology plan for the corresponding casualty is generated. According to the medical equipment configured on the helicopter corresponding to the treatment technology plan, the medical equipment selection unit matches and selects the appropriate medical equipment from the configured medical supplies. Based on the treatment process and the casualty's condition development trend in the treatment technology plan, a control algorithm generates control commands to control and adjust the corresponding treatment technology plan and medical equipment control command parameters in real time, providing targeted treatment.

[0121] Sixth, the simulation evaluation module is used to simulate and evaluate the configuration of medical supplies corresponding to air transport and the generated path library, as well as the air transport efficiency and treatment efficiency corresponding to the treatment plan generated during the treatment process and the selected medical equipment. The evaluation results are fed back to the air transport decision adjustment unit and the treatment decision adjustment unit to optimize and update the air transport decision process and the treatment technology decision process, so that the efficiency of air transport and treatment can be kept at the optimal state in real time.

[0122] Seventh, the user interface module allows for interactive selection and parameter settings of simulated mission scenarios, air evacuation plans, and medical treatment plans in the first to sixth processes. AR navigation technology assists medical personnel in quickly locating battlefield casualties, thereby improving rescue efficiency.

[0123] This system, through multi-step integrated processing, significantly improves the efficiency and quality of airlifting and evacuating large numbers of wounded and sick personnel from naval battles. First, the data collection and distributed storage units ensure comprehensive, accurate collection and efficient storage of various types of information, providing a solid data foundation for subsequent decision-making. Second, the scenario modeling and environmental / meteorological simulation units generate different types of airlift evacuation mission scenarios using historical data and real-time information, simulating the distribution of wounded and sick personnel and the status of medical supplies, thus improving the scientific rigor and rationality of decision-making. Finally, the optimal path library generated by the scenario path library unit, combined with the medical supply configuration unit and the collaborative path configuration unit, realizes medical... Efficient resource allocation and rapid response ensure that rescue aircraft can quickly reach the wounded and sick; the injury classification and assessment unit and the treatment technology selection unit improve the accuracy and effectiveness of treatment by accurately assessing and predicting the injury of each wounded and sick person and generating personalized treatment plans; the simulation evaluation module evaluates and optimizes the entire process in real time to ensure that airlift and treatment efficiency remains at its optimal level; the user interface module provides flexible interactive options and parameter settings, enhancing the system's usability and adaptability; through these comprehensive measures, the system not only significantly improves the efficiency of airlift evacuation and treatment but also significantly enhances the scientific nature of decision-making.

[0124] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments under the guidance of the present invention without departing from the spirit and scope of the claims. All of these variations are within the protection scope of the present invention.

[0125] If the technical solution disclosed herein involves personal information, the product using this technical solution has clearly informed the user of the personal information processing rules and obtained the user's voluntary consent before processing the personal information. If the technical solution disclosed herein involves sensitive personal information, the product using this technical solution has obtained the user's separate consent before processing the sensitive personal information, and also meets the requirement of "express consent". For example, at personal information collection devices such as cameras, clear and prominent signs are set up to inform users that they have entered the scope of personal information collection and that personal information will be collected. If an individual voluntarily enters the collection scope, it is deemed that they have agreed to the collection of their personal information; or on the personal information processing device, with clear signs / information informing users of the personal information processing rules, authorization is obtained from the individual through pop-up information or by asking the individual to upload their personal information; wherein, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the types of personal information processed.

Claims

1. A selection and control system for medical equipment used in the air evacuation of large numbers of wounded and sick personnel, characterized in that, include: Data management module, scenario modeling module, evacuation decision module, and treatment decision module; Based on the various rescue scenario information and corresponding air evacuation rescue simulation information stored in the data management module, the scenario modeling module generates different types of air evacuation mission scenario spaces and the distribution information of batches of wounded and sick personnel, medical supplies distribution information, rescue environment and weather conditions, and corresponding air evacuation route databases for each space. The simulated information for air evacuation and medical treatment in the corresponding scenario includes geographical information, distribution information of the wounded and sick, personnel and material information, medical equipment information, air evacuation route information, and meteorological information; The scene modeling module includes a scene modeling unit and a scene path library unit; The workflow of the scene path library unit includes: A1. Generate and construct the current type of air evacuation mission scenario space through the scenario modeling unit, and configure the corresponding geographical location information, patient distribution status, available personnel and material status, medical equipment information and dynamic weather status of the current type of air evacuation mission scenario space through air evacuation and medical treatment simulation information. A2. Based on the geographical location information configured in the air transport and delivery mission scenario space, obtain the map layer space of the target area corresponding to the current air transport and delivery mission scenario space through map layer algorithms. A3. Based on the map layer space and the distribution of wounded and sick in the target area, obtain the latitude and longitude location information of each wounded and sick in the map layer space, input the latitude and longitude location information of the wounded and sick into the clustering algorithm, obtain the cluster distribution sub-regions of wounded and sick and the number of wounded and sick in each sub-region, and label each sub-region. A4. Construct the input chromosome for the genetic algorithm based on the sub-region labels of the cluster distribution of wounded and sick personnel, the number of wounded and sick personnel in each sub-region, the maximum number of wounded and sick personnel that a rescue helicopter can rescue in a single trip, and the dynamic meteorological status corresponding to the map layer space. A5. Constructing a fitness function for a single helicopter feasible path based on the input chromosomes of a genetic algorithm. The fitness function F for the cooperative path with the helicopter; A6. Set the maximum number of iterations and rate of change stop threshold The genetic algorithm is iterated, and the Pareto front rate of change is calculated. ; A7. Based on the maximum number of iterations and the rate of change stopping threshold set in A6, iteratively calculate the process from A4 to A6. When the iteration stops, the optimal generated parameter space for the feasible path corresponding to the i-th helicopter is output. The optimal cooperative parameter space for each helicopter corresponds to all feasible paths; A8. The optimal generation parameter space for the feasible path corresponding to the i-th helicopter is obtained and... The optimal cooperative parameter space corresponding to all feasible paths for each helicopter is input into the Dijkstra algorithm to obtain the cooperative feasible paths for all helicopters under the current weather conditions. A9. Construct an air transport route library corresponding to the current type of air transport evacuation mission scenario space using all the collaborative feasible routes corresponding to the helicopters, and update the air transport evacuation route library in real time using the dynamic weather status at each moment. The evacuation decision module includes a medical supplies configuration unit and a collaborative path configuration unit. Based on the distribution information of a batch of wounded and sick persons and the distribution information of medical supplies in the corresponding scenario, the medical supplies configuration unit schedules and configures medical equipment and personnel supplies for the rescue helicopter. At the same time, based on the rescue environment and weather conditions and the corresponding air evacuation path database, the collaborative path configuration unit configures the air evacuation path for the rescue helicopter. The treatment decision-making module includes an injury classification and assessment unit, a treatment technology selection unit, and a medical equipment selection unit. Based on the injury and illness type information of a batch of injured and sick persons in a corresponding scenario, the injury classification and assessment unit obtains the injury assessment score and disease development trend of each corresponding injured and sick person after classification. Then, through the deep inference model configured in the treatment technology selection unit and the distributed storage unit in the data management module, a treatment technology plan is generated for each injured and sick person based on the injury assessment score and disease development trend. At the same time, based on the corresponding treatment technology plan and the medical equipment configured on the helicopter, the medical equipment selection unit matches and selects the corresponding medical equipment and generates medical equipment control instructions. The parameters of the treatment technology plan and medical equipment control instructions are adjusted in real time according to the disease development trend.

2. The selection and control system for medical equipment used in the mass air transport of wounded and sick personnel as described in claim 1, characterized in that, The selection control system further includes a simulation evaluation module; the follow-up decision module further includes a follow-up decision adjustment unit; the treatment decision module further includes a treatment decision adjustment unit. The simulation evaluation module performs multi-dimensional simulation evaluations on the efficiency of medical supply configuration and route configuration in the evacuation decision module and the efficiency of selection and control of treatment technology solutions and medical equipment in the treatment decision module. This yields the efficiency of route and medical configuration in air evacuation decision within the evacuation decision module, as well as the efficiency of injury classification assessment and selection of medical equipment in treatment technology decision within the treatment decision module. The efficiency of route and medical configuration in air evacuation decision is fed back to the evacuation decision adjustment unit, and the efficiency of injury classification assessment and selection of medical equipment in treatment technology decision is fed back to the treatment decision adjustment unit, allowing for real-time adjustments to both air evacuation decision and treatment technology decision.

3. The selection and control system for medical equipment used in the mass air transport of wounded and sick personnel as described in claim 2, characterized in that, The input chromosome for the genetic algorithm is: , and ,in, and These represent the takeoff and landing target area locations corresponding to the i-th rescue helicopter, respectively. This represents the latitude and longitude position of the k-th wounded soldier in the sub-region of the j-th wounded soldier's cluster distribution. This indicates the total number of wounded and sick soldiers corresponding to the current map layer space. This indicates the total number of helicopters available for use in the current map layer space. This represents the number of wounded soldiers corresponding to the j-th cluster distribution sub-region. This represents the number of rescue helicopters required for the j-th cluster of wounded and sick personnel. , and These represent the wind speed, wind direction, and visibility corresponding to the current map layer, respectively. This represents the safety score of the path taken by the i-th helicopter during a rescue mission under the current weather conditions in the current map layer space. Let represent the parameter space for generating feasible paths for the i-th helicopter; P represents the collaborative parameter space for feasible paths for all helicopters. The fitness function of the single helicopter feasible path The fitness function F for the cooperative path with the helicopter is as follows: , , ,in, This represents the length of the feasible path corresponding to the i-th helicopter. This represents the total flight time of the feasible path corresponding to the i-th helicopter. , and These represent the weighting coefficients in the fitness function, in that order. This represents the fitness threshold for the feasible path corresponding to the i-th helicopter.

4. The selection and control system for medical equipment used in the mass air transport of wounded and sick personnel as described in claim 3, characterized in that, The Pareto frontier rate of change The specific formula is Among them, This represents the first number obtained during the iteration of the genetic algorithm. Pareto front solution set of the generation. Indicates that x is the number of times the digit is obtained. A solution in the Pareto front solution set of the generation, y represents the obtained first solution. A solution in the Pareto front solution set of the generation. Represents the 2-norm symbol.

5. The selection and control system for medical equipment used in the mass air transport of wounded and sick personnel as described in claim 4, characterized in that, The steps for generating the corresponding treatment plan for the wounded and sick include: B1. Obtain basic information, physiological parameters and injury description text information of each simulated patient from the map layer space configured in A2 and preprocess it. At the same time, input the preprocessed data into the dynamic electronic medical record with built-in automatic text update model to obtain the individual dynamic electronic medical record table and dynamic physiological parameter table. B2. Input the individual dynamic electronic medical record into the injury and illness classification model for real-time injury and illness classification; B3. Input the obtained injury type and corresponding dynamic physiological parameter table into the trauma scoring subsystem and Glasgow coma scoring subsystem to obtain the corresponding injury assessment score, coma assessment score and comprehensive injury severity assessment score of the corresponding patient.

6. The selection and control system for medical equipment used in the mass air transport of wounded and sick personnel as described in claim 5, characterized in that, The steps for generating the corresponding treatment plan for the wounded and sick also include: B4. Input the trauma assessment score, coma assessment score, and comprehensive injury severity assessment score of the corresponding wounded patient, along with the real-time dynamic physiological parameter table, into the pre-constructed injury change prediction model to obtain the change trend of the severity of each type of injury for each wounded patient. B5. Input the individual dynamic electronic medical record, dynamic physiological parameter table, trauma assessment score, coma assessment score, and corresponding comprehensive injury severity assessment score of the injured patient into the configured matching generation model. Match the corresponding patient treatment technical specifications from the distributed node inference database built into the data management module, and generate the corresponding patient treatment technical implementation process structure table.

7. The selection and control system for medical equipment used in the mass air transport of wounded and sick personnel as described in claim 6, characterized in that, The step of generating medical device control commands includes: C1. Based on the obtained rescue technology implementation process structure table, the medical equipment information stored in the distributed node reasoning database and the medical equipment currently configured on the rescue helicopter are matched and obtained from the matching medical equipment table for the current injury and illness type of the corresponding patient, and the corresponding matching medical equipment usage process is generated. C2. Based on the pre-treatment technical specification process structure table, the matching medical equipment table is updated by matching algorithm to supplement and update the matching medical equipment table according to the changes in the injury, and the updated matching medical equipment table is obtained. C3. Based on the rescue technology process information in the rescue technology implementation process structure table, the corresponding patient physiological parameter information, and the matching medical equipment usage process, generate process control instructions for the corresponding medical equipment in the matching medical equipment table through the control algorithm, and control the corresponding equipment to carry out emergency rescue for the patient. C4. Utilize the pre-treatment technical specification process structure table, and generate pre-treatment equipment control instructions through a control algorithm. When the corresponding wounded or sick person changes, control the pre-treatment equipment in the updated matching medical equipment table through the pre-treatment equipment control instructions to provide real-time treatment for the changed condition of the corresponding wounded or sick person.

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