Selection control system of treatment equipment for batch air transportation and post-delivery of sick and wounded

Abstract

The invention belongs to the technical field of wounded information simulation, and particularly relates to a selection control system for treatment equipment for batch air transportation and post-delivery of the wounded, which simulates and generates an air transportation and post-delivery task scene and constructs an air transportation and post-delivery path library by collecting geography, wounded distribution, medical resources and weather information. Medical supplies and paths are matched according to the sick and wounded information and the environment; a personalized treatment technical scheme is generated by utilizing a injury condition classification evaluation and deep reasoning model, medical equipment and a control flow are intelligently selected, air transportation and treatment efficiency is optimized through a simulation evaluation module, and a real-time optimal state is ensured; and the user can also interactively select a task scene, a scheme and parameter setting through the user interface module, so that efficient and accurate intelligent selection and control of batch sick and wounded air transportation and treatment equipment are realized, and the emergency medical rescue efficiency and quality are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of wounded person information simulation, and in particular relates to a selection control system for medical treatment equipment used for air transport of batches of wounded and sick persons. Background Art

[0002] In the treatment of a large number of wounded and sick, efficient air transport is the key to ensuring the quality of treatment and improving the survival rate. Traditional evacuation decisions mainly rely on the experience and intuition of commanders, and lack scientific prediction and evaluation methods. This experience-driven decision-making method has many shortcomings and deficiencies: First, the decision-making process lacks systematicity and scientificity, and it is difficult to fully consider various complex factors, such as the severity of the wounded and sick, the distribution of medical resources, the traffic conditions and weather conditions of the evacuation route, etc. Secondly, traditional methods cannot be dynamically adjusted and optimized. Once an emergency occurs, it is difficult to quickly make effective response measures. Traditional decision-making methods lack prior evaluation and post-event feedback on the evacuation effect, and it is difficult to form a closed-loop optimization mechanism, resulting in low accuracy and reliability of decision-making. In addition, the main task of air transport is to send a large number of people to the rear quickly and accurately, and to use medical equipment configured in a limited space so that the wounded and sick will not deteriorate. These are the difficulties to be solved in the current air transport process.

[0003] For example, a patent application with publication number CN113871030A discloses an information system and working method for air transport of the wounded, which is provided with a portable data terminal, a wounded information collection system, a storage module, a display interaction module, a wounded information identification module and a medical record rapid construction module. After collecting data on the wounded's vital signs monitoring, medical treatment on the way, and medical care on the way, electronic injury ticket information is generated, and the uploaded medical record information corresponds to the injury ticket information and the wounded information at the same time; and 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 existing technologies have the following problems: the existing air transport is mostly based on "rescue", ignoring the most important rapid transportation process, and lacking a strategy for rapid transportation of large quantities of wounded and sick. In addition, air transport space is limited. How to use the limited space to configure the most effective medical equipment to provide temporary medical assistance to the wounded and sick is also one of the problems to be solved in air transport. For this reason, the present invention provides a selection control system for medical treatment equipment for air transport of batches of wounded and sick. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention proposes a selection and control system for medical treatment equipment for air transport of batches of wounded and sick patients. The system collects geographical information, distribution of wounded and sick patients, medical resources and meteorological information, simulates and generates air transport mission scenarios, builds an air transport path library, and matches medical supplies and paths according to the wounded and sick information and the environment; utilizes injury classification assessment and deep reasoning models to generate personalized treatment technology solutions, and intelligently selects medical equipment and control processes, and optimizes air transport and treatment efficiency through simulation evaluation modules to ensure real-time optimal status; users can also interactively select mission scenarios, solutions and parameter settings through the user interface module, to achieve efficient and accurate air transport of batches of wounded and sick patients and intelligent selection and control of medical treatment equipment, thereby improving the efficiency and quality of emergency medical rescue.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a selection control system for medical treatment equipment for air transport of batches of injured and sick patients, comprising: a data management module, a scenario modeling module, an evacuation decision module and a treatment decision module;

[0007] According to the various rescue scene information stored in the data management module and the air transport rescue simulation information under the corresponding scenes, the scene modeling module generates different types of air transport mission scene spaces and the corresponding distribution information of batches of injured and sick people, medical supplies distribution information, rescue environment and meteorological conditions and the corresponding air transport path library under each space;

[0008] The evacuation decision module includes a medical material configuration unit and a collaborative path configuration unit. According to the distribution information of the batch of injured and sick people and the distribution information of medical materials in the corresponding scenario, the medical material configuration unit dispatches and configures the medical equipment and personnel materials of the rescue helicopter. At the same time, according to the rescue environment and meteorological conditions and the corresponding air transport evacuation path library, the collaborative path configuration unit configures the air transport evacuation path of the rescue helicopter.

[0009] The rescue decision-making module includes an injury classification and assessment unit, a rescue technology selection unit and a medical equipment selection unit; according to the injury type information of the batch of injured and sick patients in the corresponding scenario, the injury classification and assessment unit is used to obtain the injury assessment score and disease development trend of each corresponding injured and sick patient after classification, and through the deep reasoning model configured in the rescue technology selection unit and the distributed storage unit in the data management module, according to the injury assessment score and disease development trend of the corresponding injury and disease type of the injured and sick, a rescue technology plan for the corresponding injured and sick patient is generated, and at the same time, according to the corresponding rescue technology plan and the medical equipment configured on the helicopter, the medical equipment selection unit is used to match and select the corresponding rescue medical equipment and generate medical equipment control instructions, and at the same time, the rescue technology plan and medical equipment control instruction parameters are adjusted in real time according to the disease development trend.

[0010] Specifically, the selection control system further includes a simulation evaluation module; the transport decision module further includes a transport decision adjustment unit; the treatment decision module further includes a treatment decision adjustment unit;

[0011] Through the simulation evaluation module, a multi-dimensional simulation evaluation is conducted on the medical material configuration and path configuration efficiency in the transport decision module, the generation of the treatment technology plan and the treatment medical equipment, and the efficiency of selecting and controlling the treatment in the treatment decision module. The path and medical configuration efficiency in the air transport transport decision in the transport decision module, as well as the injury classification evaluation and the treatment efficiency of the medical equipment selection in the treatment technology decision in the treatment decision module are obtained. The path and medical configuration efficiency in the air transport transport decision is fed back to the transport decision adjustment unit, and the injury classification evaluation and the treatment efficiency of the medical equipment selection in the treatment technology decision are fed back to the treatment decision adjustment unit, so as to make real-time adjustments to the air transport transport decision and the treatment technology decision respectively.

[0012] Specifically, the air transport and rescue simulation information in the corresponding scenario includes geographic information, distribution information of the wounded and sick, personnel and material information, medical equipment information, air transport and rescue path information and meteorological information;

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

[0014] A1. Generate and construct the current type of air transport mission scene space through the scene modeling unit, and configure the corresponding geographical location information, the distribution status of the wounded and sick, the status of the deployable personnel and materials, the medical equipment information and the dynamic meteorological status of the current type of air transport mission scene space through the air transport rescue simulation information;

[0015] A2. According to the geographical location information of the air transport mission scene space after configuration, the map layer space corresponding to the target area of ​​the current air transport mission scene space is obtained through the map layer algorithm;

[0016] A3. According to the map layer space of the target area and the distribution status of the wounded and sick, the longitude and latitude position information corresponding to each wounded and sick is obtained in the map layer space, and the longitude and latitude position information of the wounded and sick is input into the clustering algorithm to obtain the cluster distribution sub-areas of the wounded and sick and the number of the wounded and sick in each sub-area, and each sub-area is labeled.

[0017] Specifically, the workflow of the scene path library unit also includes:

[0018] A4. Construct the input chromosome of the genetic algorithm based on the sub-region labels of the cluster distribution of the wounded and the number of wounded and sick in each sub-region, the maximum number of wounded and sick that can be rescued by the rescue helicopter at a time, and the dynamic meteorological state corresponding to the map layer space. P iand P, where X i and Y i represents the take-off and landing target area positions corresponding to the i-th rescue helicopter, p jk represents the latitude and longitude position of the kth patient in the jth patient cluster distribution sub-area, N1 represents the total number of patients in the current map layer space, N2 represents the total number of helicopters that can be called in the current map layer space, and N j represents the number of injured and sick patients corresponding to the jth cluster distribution sub-region, f j represents the number of rescue helicopters required for the jth cluster distribution sub-region of the injured and sick, and It represents the wind force level, wind direction and visibility corresponding to the current map layer space, f i represents the safety score of the path corresponding to the rescue mission performed by the i-th helicopter under the current meteorological conditions in the current map layer space, P i represents the feasible path generation parameter space corresponding to the i-th helicopter; P represents the feasible path coordination parameter space corresponding to all helicopters;

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

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

[0021] A6. Set the maximum number of iterations g max and the rate of change stop threshold θ u , iterate the genetic algorithm and calculate the Pareto front change rate The specific formula is Among them, U t-i represents the Pareto frontier solution set of the tith generation obtained during the iteration of the genetic algorithm, x∈U t-i indicates that x is a solution in the Pareto front solution set of the ti-th generation, y is a solution in the Pareto front solution set of the t-th generation, and || ||2 represents the 2-norm symbol;

[0022] A7, iterate the A4-A6 process based on the maximum number of iterations and the change rate stop threshold set in A6. When , the iteration stops, and the output search obtains the optimal generation parameter space of the feasible path corresponding to the i-th helicopter and the optimal coordination parameter space of all feasible paths corresponding to N2 helicopters;

[0023] A8. Input the optimal generation parameter space of the feasible path corresponding to the i-th helicopter and the optimal coordination parameter space of all feasible paths corresponding to the N2 helicopters into the Dijkstra algorithm to obtain the coordinated feasible paths corresponding to all helicopters under the current meteorological conditions;

[0024] A9. Use the collaborative feasible paths corresponding to all helicopters to build an air transport path library corresponding to the current type of air transport mission scenario space, and use the dynamic meteorological conditions at each moment to update the air transport path library in real time.

[0025] Specifically, the steps for generating a treatment technical plan for the injured and sick include:

[0026] B1, obtain the basic information, physiological parameters and injury description text information of each simulated patient from the map layer space configured in A2 and pre-process it, and input the pre-processed data into the dynamic electronic medical record with a built-in text automatic update model to obtain the personal dynamic electronic medical record table and dynamic physiological parameter table;

[0027] B2. Input personal dynamic electronic medical records into the injury and illness classification model to perform real-time injury and illness classification;

[0028] B3. The obtained injury type and the corresponding dynamic physiological parameter table are simultaneously input into the configuration trauma scoring subsystem and Glasgow coma scoring subsystem to obtain the trauma assessment score and coma assessment score of the corresponding injured person and the comprehensive injury severity assessment score of the corresponding injured person.

[0029] Specifically, the steps for generating a treatment technical plan for the injured and sick also include:

[0030] B4. Inputting the trauma assessment score, coma assessment score, and comprehensive injury severity assessment score of the corresponding injured and sick person and the real-time acquired dynamic physiological parameter table into a pre-built injury change prediction model to obtain the change trend of the severity of the corresponding type of injury of each injured and sick person;

[0031] B5. Input the personal dynamic electronic medical record, dynamic physiological parameter table, trauma assessment score, coma assessment score and the comprehensive injury severity assessment score of the corresponding injured and sick into the configured matching generation model, match the corresponding injured and sick treatment technical specifications from the distributed node reasoning database built into the data management module, and generate the corresponding treatment technology implementation process structure table for the injured and sick;

[0032] Specifically, the steps for generating a treatment technical plan for the injured and sick also include:

[0033] B6. Input the generated treatment technology implementation process structure table and the injury severity change trend of the corresponding injured and sick patients into the deep reasoning model configured in the distributed node reasoning database, conduct physical verification on the matched treatment technology implementation process structure table, and use the matched expert verification sub-model in the deep reasoning model to evaluate the professionalism and standardization of the treatment technology implementation process structure table to obtain the corresponding professional evaluation score;

[0034] B7. Set a professional assessment score threshold. When the professional assessment score is greater than the professional assessment score threshold, output the corresponding rescue technology implementation process structure table, and at the same time output the preparatory rescue technology specification process structure table corresponding to the change trend of the severity of the injury.

[0035] Specifically, the steps of generating a medical device control instruction include:

[0036] C1. Based on the obtained rescue technology implementation process structure table, the medical equipment information saved in the distributed node inference database and the medical equipment currently configured by the rescue helicopter are matched and obtained from the matching medical equipment table corresponding to the current injury type of the injured and sick, and the corresponding matching medical equipment usage process is generated;

[0037] C2. According to the preliminary rescue technical specification process structure table, the matching medical equipment table is supplemented and updated with the injury change through the matching algorithm to obtain the supplemented and updated matching medical equipment table;

[0038] C3. Based on the rescue technology process information in the rescue technology implementation process structure table, the corresponding physiological parameter information of the injured and sick, and the matching medical equipment usage process, the control algorithm is used to generate the process control instructions of the corresponding medical equipment in the matching medical equipment table, and the corresponding equipment is controlled to perform emergency rescue on the injured and sick;

[0039] C4. Use the technical specification process structure table of preparatory rescue to generate preparatory equipment control instructions through the control algorithm. When the corresponding injured and sick patients change, the preparatory equipment in the supplemented and updated matching medical equipment table is controlled through the preparatory equipment control instructions to provide real-time rescue for the changed conditions of the corresponding injured and sick patients.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] In view of the deficiencies in the prior art, the present invention collects various types of rescue scene information and air transport rescue simulation information in corresponding scenes through a data management module, and classifies and stores them in nodes to ensure the comprehensiveness and accuracy of the data; the scene modeling module generates different types of air transport mission scene spaces and batch sick and wounded distribution information, medical supplies distribution information, rescue environment and meteorological conditions and corresponding air transport path library in each space to provide a scientific basis for decision-making; the medical supplies configuration unit and the collaborative path configuration unit in the transport decision module efficiently dispatch and configure the rescue helicopter according to the distribution of sick and wounded and the distribution of medical supplies, and selects the optimal path according to the rescue environment and meteorological conditions to ensure fast and safe air transport. The injury classification and assessment unit, treatment technology selection unit and medical equipment selection unit in the treatment decision-making module generate personalized treatment technology plans by assessing the injuries of the wounded and predicting the development trend of the disease, and select the most appropriate medical equipment for temporary medical assistance. The accuracy and effectiveness of treatment are ensured by real-time adjustment of treatment plans and control command parameters. The system not only solves the problems of rapid transportation and configuration of medical equipment in limited space in existing technologies, but also improves the overall efficiency and quality of air transport. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a module diagram of a selection control system for medical treatment equipment for air transport of batches of injured and sick persons according to Embodiment 1 of the present invention;

[0043] Figure 2 This is a workflow architecture diagram of a control system for selecting medical equipment for air transport of batches of wounded and sick patients according to Example 2 of the present invention. DETAILED DESCRIPTION

[0044] Example 1

[0045] See also Figure 1 , an embodiment provided by the present invention: a selection control system for medical treatment equipment for air transport of batches of injured and sick patients, comprising: a data management module, a scenario modeling module, an evacuation decision module, a treatment decision module, a simulation evaluation module and a user interface module;

[0046] The data management module is used for the collection, storage and management of various rescue scene data and rescue process data; the data management module includes a data collection unit and a distributed storage unit;

[0047] Data collection unit, used for the collection and preprocessing of geographic information, distribution information of the wounded and sick, medical resource information and meteorological information in various rescue scenarios; medical resource information includes medical equipment configuration information, rescue standard library configuration information and deployable medical personnel configuration information;

[0048] Furthermore, if the present embodiment is based on the air transport of a large number of wounded and sick soldiers in naval battles, the configuration information of the treatment specification library includes the treatment methods and treatment technical specification process information of various types of injuries and diseases of a large number of wounded and sick soldiers in naval battles;

[0049] Furthermore, with respect to the treatment technical specification process information, since this embodiment is based on the air transport of a large number of wounded and sick soldiers in naval battles, the most important treatment technology in the air transport process of naval battles is the tracheal management and hemostasis technical treatment specifications;

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

[0051] Furthermore, in this embodiment, the distributed node reasoning database 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 multi-level storage nodes, including a first-level scene storage node, and the first-level scene storage node is mounted with a scene modeling information storage node, a medical equipment information storage node, a treatment method and treatment specification storage node, an deployable medical personnel and material information storage node, and a real-scene geographic information and weather information storage node; further, the deep reasoning model in this embodiment is constructed by a Chinese pre-trained Bert reasoning model;

[0052] The scenario modeling module is used to simulate different air transport mission scenario data and build different scenario simulation spaces;

[0053] The scenario modeling module includes scenario modeling unit, sick and wounded distribution unit, medical supplies simulation unit, environmental meteorological simulation unit and scenario path library unit;

[0054] A scenario modeling unit is used to generate and construct different types of air transport mission scenario spaces through a scenario generation algorithm according to the information stored in the distributed storage unit; in this embodiment, naval battles are used as the background, and different types of air transport mission scenario spaces include battlefield rescue scenario spaces such as ship battles, beach landings, island battles, maritime rescue, severe weather conditions (such as storms and strong winds), and night operations;

[0055] The sick and wounded distribution unit is used to simulate the distribution location information and corresponding injury type information of batches of sick and wounded according to the spatial information of different air transport mission scenarios;

[0056] Furthermore, in this embodiment, the air transport of batches of wounded and sick soldiers in naval battles is used as the background to simulate the various distribution positions and corresponding types of injuries and diseases of the wounded in naval battles during naval battles, such as gunshot wounds, explosion injuries, drowning, burns, fractures, internal bleeding, craniocerebral injuries, infections and hypothermia;

[0057] An environmental meteorological simulation unit, used to simulate different rescue environments and meteorological conditions corresponding to air transport according to the geographic information and meteorological information data corresponding to the historical scenes stored in the distributed storage unit;

[0058] The medical supplies simulation unit is used to simulate the distribution status information of medical supplies in different air transport mission scenarios; medical supplies include the number of rescue personnel, the number of rescue aircraft, and other battlefield rescue supplies data;

[0059] Furthermore, in this embodiment, the key technology of special equipment for air transport of wounded and sick patients in a special environment is used as an example to simulate medical supplies and equipment in a naval battlefield;

[0060] In this embodiment, according to the tasks and modification configurations performed by the general-purpose medical aircraft, general-purpose medicinal materials and special medicinal materials modules are designed and developed, including conventional modules, first aid modules, epidemic prevention modules, burn modules, plateau modules, naval battle injury modules, etc. Each module needs to propose appearance indicators, internal design indicators, medicinal materials quantity standards, etc.; it has the primary first aid and advanced first aid capabilities specified in the new version of the combat injury treatment rules, and according to different tasks and environmental characteristics, special modules highlight special functions;

[0061] First, the indicators and design schemes of each module are proposed according to the operational needs and mission requirements. After multiple rounds of expert demonstration, samples (mobile, integrated towing box, back-to-towing dual-purpose bag) are produced. Through troop trials and on-board exercises, continuous optimization, modification and improvement are carried out, and the final design is finalized. Through the medicine and corresponding medical equipment modules configured on the above-mentioned general-purpose medical aircraft, professional simulation of medical substances and medical equipment is carried out.

[0062] Furthermore, the key technical specifications for air transport medical evacuation and treatment technology for general-purpose medical aircraft in this embodiment include:

[0063] (1) Based on the injuries and characteristics of the injured and sick in special environments such as plateaus and offshore, as well as the secondary injuries caused to the injured by the aviation environment during air medical evacuation, research and propose onboard treatment plans for air medical evacuation in special environments and treatment plans for injuries and illnesses during air transport transit, and formulate a draft of key technical specifications for the treatment of the injured and sick in special environments (plateaus and offshore);

[0064] (2) Through intelligence analysis, demand surveys, and research, technical requirements for special equipment for air transport of wounded and sick patients in large quantities in plateaus and offshore areas are proposed; for air transport medical evacuation missions and modification configurations based on general-purpose medical rescue aircraft, a technical solution for the integration of special medicinal material modules for air transport medical evacuation is proposed, including basic onboard treatment modules, first aid modules, auxiliary diagnosis modules, epidemic prevention modules, and special modules such as burns, and a development plan for an air portable auxiliary diagnosis platform and a ground transfer portable integrated rapid medical diagnosis platform is proposed;

[0065] (3) Develop a "simulation decision support system for air transport of bulk wounded and sick patients". The system has prediction, decision-making and evaluation functions, supports modeling of evacuation mission scenarios, supports the formation of evacuation decisions based on evacuation mission scenarios, including how to dispatch medical rescue aircraft, medical personnel, medicines and other health resources and plan evacuation routes. It uses simulation technology to deduce the implementation of evacuation decisions, provides data support for the evaluation of decision implementation effects, and provides auxiliary decision support for air transport of bulk wounded and sick patients for use by air logistics health agencies, theater health agencies and related hospitals.

[0066] The scenario path library unit is used to generate and construct the air transport path library under different scenarios through the path generation algorithm according to different air transport scenario tasks and corresponding geographical and meteorological information;

[0067] Furthermore, in the present embodiment, the air transport and rescue simulation information in the corresponding scenario includes geographical information, distribution information of the wounded and sick, personnel and material information, medical equipment information, air transport and rescue path 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 transport mission scene space through the scene modeling unit, and configure the corresponding geographical location information, the distribution status of the wounded and sick, the status of the deployable personnel and materials, the medical equipment information and the dynamic meteorological status of the current type of air transport mission scene space through the air transport rescue simulation information;

[0070] A2. According to the geographical location information of the air transport mission scene space after configuration, the map layer space corresponding to the target area of ​​the current air transport mission scene space is obtained through the map layer algorithm;

[0071] A3. According to the map layer space of the target area and the distribution status of the wounded and sick, the longitude and latitude position information corresponding to each wounded and sick is obtained in the map layer space, and the longitude and latitude position information of the wounded and sick is input into the clustering algorithm to obtain the cluster distribution sub-areas of the wounded and sick and the number of the wounded and sick in each sub-area, and each sub-area is labeled.

[0072] A4. Construct the input chromosome of the genetic algorithm based on the sub-region labels of the cluster distribution of the wounded and the number of wounded and sick in each sub-region, the maximum number of wounded and sick that can be rescued by the rescue helicopter at a time, and the dynamic meteorological state corresponding to the map layer space. P i and P, where X i and Y i represents the take-off and landing target area positions corresponding to the i-th rescue helicopter, p jkrepresents the latitude and longitude position of the kth patient in the jth patient cluster distribution sub-area, N1 represents the total number of patients in the current map layer space, N2 represents the total number of helicopters that can be called in the current map layer space, and N j represents the number of injured and sick patients corresponding to the jth cluster distribution sub-region, f j represents the number of rescue helicopters required for the jth cluster distribution sub-region of the injured and sick, and It represents the wind force level, wind direction and visibility corresponding to the current map layer space, f i represents the safety score of the path corresponding to the rescue mission performed by the i-th helicopter under the current meteorological conditions in the current map layer space, P i represents the feasible path generation parameter space corresponding to the i-th helicopter; P represents the feasible path coordination parameter space corresponding to all helicopters;

[0073] A5. Construct a single helicopter feasible path fitness function F based on the input chromosome of the genetic algorithm i And the helicopter cooperative path fitness function F, specifically: F i ≥F0, where l i represents the feasible path length corresponding to the i-th helicopter, T i represents the total flight time of the feasible path corresponding to the i-th helicopter, w1, w2 and w3 represent the weighted coefficients in the fitness function respectively, and F0 represents 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 stop threshold θ u , iterate the genetic algorithm and calculate the Pareto front change rate The specific formula is Among them, U t-i represents the Pareto frontier solution set of the tith generation obtained during the iteration of the genetic algorithm, x∈U t-i indicates that x is a solution in the Pareto front solution set of the ti-th generation, y is a solution in the Pareto front solution set of the t-th generation, and || ||2 represents the 2-norm symbol;

[0075] A7, iterate the A4-A6 process based on the maximum number of iterations and the change rate stop threshold set in A6. When , the iteration stops, and the output search obtains the optimal generation parameter space of the feasible path corresponding to the i-th helicopter and the optimal coordination 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 coordination parameter space of all feasible paths corresponding to the N2 helicopters into the Dijkstra algorithm to obtain the coordinated feasible paths corresponding to all helicopters under the current meteorological conditions;

[0077] A9. Use the collaborative feasible paths corresponding to all helicopters to build an air transport path library corresponding to the current type of air transport mission scenario space, and use the dynamic meteorological conditions at each moment to update the air transport path library in real time.

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

[0079] The evacuation decision module includes a medical material configuration unit, a collaborative path configuration unit, and an evacuation decision adjustment unit;

[0080] The medical material allocation unit is used to dispatch and allocate medical equipment and personnel materials according to the batch of injured and sick information and the corresponding injury type information simulated by the injured and sick distribution unit in the corresponding air transport evacuation scenario; the configuration of medical materials includes the number of rescue medical equipment, the number of rescue aircraft and other battlefield rescue material data; other battlefield rescue material data includes medicines, gauze bandages, etc.;

[0081] Furthermore, in this embodiment, the key technology of special equipment for air transport of batches of injured and sick people in special environments is used as an example to demonstrate the configuration of medical equipment and supplies for rescue helicopters;

[0082] In this embodiment, according to the tasks and modification configurations performed by the general-purpose medical aircraft, general-purpose medicinal materials and special-purpose medicinal materials modules are designed and developed, including conventional modules, first-aid modules, epidemic prevention modules, burn modules, plateau modules, naval battle injury modules, etc. Each module needs to propose appearance indicators, internal design indicators, medicinal materials quality standards, etc.

[0083] It has the primary and advanced first aid capabilities stipulated in the new version of the combat injury treatment rules, and special modules highlight special functions according to different tasks and environmental characteristics. First, the indicators and design plans of each module are proposed according to combat needs and task requirements. After multiple rounds of expert demonstration, samples (mobile, integrated towing box, back-to-back dual-purpose bag) are produced, and they are continuously optimized, modified and improved through troop trials and on-board exercises, and finally finalized.

[0084] The collaborative path configuration unit simulates and constructs specific air transport and evacuation wounded and sick distribution information, geographic location information and weather information according to the scenario modeling module, matches the corresponding air transport and evacuation paths from the air transport and evacuation path library through the matching algorithm and path adjustment algorithm, adjusts the matched paths, and configures the matched path information to different transport aircraft, collaboratively controls the rescue aircraft to quickly reach different distribution locations of the wounded, and quickly sends the wounded back to the rear;

[0085] Furthermore, the path adjustment algorithm in this embodiment achieves the effect of adjusting the specific post-air transport transport path by adjusting the specific input parameters of the A4-A7 process genetic algorithm;

[0086] Through the scenario modeling module and the evacuation decision module, the system can simulate different air transport evacuation mission scenarios, construct simulation spaces for different scenarios, and generate the optimal evacuation decision plan; this process includes scenario modeling, distribution of the wounded and sick, medical supplies simulation, environmental meteorological simulation, and path library construction. Each link uses advanced algorithms and technologies to ensure the scientificity and accuracy of the evacuation decision; for example, the scenario modeling unit generates different types of air transport evacuation mission scenario spaces through scenario generation algorithms, such as ship battles, beach landings, island battles, etc., which provides basic data for subsequent distribution of the wounded and sick and allocation of medical supplies; the wounded and sick distribution unit simulates the distribution locations and injury types of batches of wounded and sick according to different mission scenarios, ensuring the rational allocation of medical resources.

[0087] The medical material allocation unit dispatches and allocates medical equipment and personnel materials according to the simulated batch of wounded and sick information and the corresponding injury and disease type information; in particular, for the tasks and modification configurations performed by general-purpose medical aircraft, general-purpose and special-purpose medicinal material modules are designed and developed, including conventional modules, first-aid modules, epidemic prevention modules, burn modules, plateau modules, and naval battle injury modules; these modules have the primary and advanced first-aid capabilities specified in the new version of the combat injury treatment rules, and highlight special functions according to different tasks and environmental characteristics; through multiple rounds of expert demonstrations and troop trials, they are continuously optimized and improved and finally finalized. This refined allocation of medical materials not only improves the efficiency of treatment, but also ensures the rational use of medical resources and avoids waste of resources.

[0088] The collaborative path configuration unit matches the corresponding air transport path from the air transport path library through the matching algorithm and path adjustment algorithm according to the specific air transport and sick distribution information, geographic location information and meteorological information constructed by simulation, and adjusts the matched path; the scenario path library unit generates and constructs the air transport path library under different scenarios through the genetic algorithm and the Dijkstra algorithm; the genetic algorithm optimizes the length, flight time and safety of the path by constructing the fitness function of a single helicopter feasible path and the helicopter collaborative path fitness function; the Dijkstra algorithm is used to generate the collaborative feasible paths of all helicopters under the dynamic meteorological conditions at the current moment; this efficient path planning not only shortens the rescue time, but also improves the safety of the path, ensuring that the wounded and sick can be treated in a timely and safe manner;

[0089] A delivery decision adjustment unit is used to adjust the medical material configuration and the generated collaborative transportation path information in the currently generated delivery decision according to the real-time information of the simulated site;

[0090] The rescue decision module is used to generate corresponding treatment plans according to the corresponding status information of the simulated injured and sick persons; the rescue decision module includes an injury classification assessment unit, a rescue technology selection unit, a medical equipment selection unit and a rescue decision adjustment unit;

[0091] The injury classification and assessment unit is used to classify the injury types of the batch of injured and sick patients according to the simulated injury type information of the batch of injured and sick patients through the classification and assessment algorithm, and to evaluate the current status information of each corresponding injured and sick patient after classification, so as to obtain the injury assessment score of the corresponding type of each injured and sick patient, and at the same time, according to the current status information of the injured and sick patients, obtain the development trend of the corresponding condition of the injured and sick patients through the expert prediction model;

[0092] The treatment technology selection unit is used to generate a treatment technology plan for each injured person by inferring the injury type, injury assessment score and condition development trend of each injured person obtained by the injury classification and assessment unit, through the generation algorithm and the distributed node reasoning database;

[0093] Furthermore, the technical rescue solutions generated in this embodiment are all generated on the basis of existing medical standard treatment text information. The generation here is a professional process integration of existing rescue standard technologies, and will not be generated out of nothing. Moreover, the generated solutions are all generated by models trained by expert experience, and are all based on existing medical treatment standards. There are no ethical and professional issues. In this embodiment, no information that is not in the medical treatment standards is generated. All generation is based on medical treatment standard text information, and the treatment process text is integrated with the treatment technical specifications corresponding to the injuries and symptoms.

[0094] Furthermore, in this embodiment, the steps of generating a treatment technical solution for the injured or sick include:

[0095] B1, obtain the basic information, physiological parameters and injury description text information of each simulated patient from the map layer space configured in A2 and pre-process it, and input the pre-processed data into the dynamic electronic medical record with a built-in text automatic update model to obtain the personal dynamic electronic medical record table and dynamic physiological parameter table;

[0096] B2. Inputting the personal dynamic electronic medical record into the injury classification model with built-in expert experience information to perform real-time injury classification; further, in this embodiment, the expert experience information is the historical medical rescue diagnosis information of various specialists in naval combat rescue;

[0097] B3. The obtained injury type and the corresponding dynamic physiological parameter table are simultaneously input into the configuration trauma scoring subsystem and Glasgow coma scoring subsystem to obtain the trauma assessment score and coma assessment score of the corresponding injured person and the comprehensive injury severity assessment score of the corresponding injured person.

[0098] B4. Input the corresponding injury assessment score, coma assessment score, and comprehensive injury severity assessment score of the injured and sick patients and the real-time dynamic physiological parameter table into the injury change prediction model pre-built by Bilstm and expert experience method to obtain the change trend of the severity of the corresponding type of injury of each injured and sick patient;

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

[0100] B6. Input the generated treatment technology implementation process structure table and the injury severity change trend of the corresponding injured and sick patients into the deep reasoning model configured in the distributed node reasoning database, conduct physical verification on the matched treatment technology implementation process structure table, and use the matched expert verification sub-model in the deep reasoning model to evaluate the professionalism and standardization of the treatment technology implementation process structure table 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 rescue technology implementation process structure table, and at the same time output the preparatory rescue technology specification process structure table corresponding to the change trend of the severity of the injury.

[0102] Through the treatment decision module, the system can automatically generate personalized treatment technology solutions based on the current status information of the simulated injured and sick. This process includes multiple links such as injury classification assessment, treatment technology selection, medical equipment selection and treatment technology decision adjustment. Each link uses advanced algorithms and technologies to ensure the scientificity and accuracy of the treatment plan. For example, the injury classification assessment unit classifies the types of injuries and illnesses of a batch of injured and sick people through a classification assessment algorithm, and combines the expert prediction model to obtain the development trend of the injured and sick people's condition, which provides accurate basic data for subsequent treatment technology selection. The treatment technology selection unit uses the injury change prediction model constructed by Bilstm and expert experience method to generate personalized treatment technology solutions for each injured and sick person, ensuring the pertinence and effectiveness of the treatment plan.

[0103] The medical equipment selection unit is used to select the medical equipment corresponding to the rescue technical solution through the medical supplies configured by the medical supplies configuration unit according to the obtained rescue technical solution, and generate control instructions through the control algorithm according to the rescue process solution and the development trend of the patient's condition in the rescue technical solution, control and adjust the corresponding rescue technical solution and medical equipment rescue technical solution parameters, and perform corresponding symptom injury and disease treatment;

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

[0105] C1. Based on the obtained rescue technology implementation process structure table, the medical equipment information saved in the distributed node inference database and the medical equipment currently configured by the rescue helicopter are matched and obtained from the matching medical equipment table corresponding to the current injury type of the injured and sick, and the corresponding matching medical equipment usage process is generated;

[0106] C2. According to the preliminary rescue technical specification process structure table, the matching medical equipment table is supplemented and updated with the injury change through the matching algorithm to obtain the supplemented and updated matching medical equipment table;

[0107] C3. Based on the rescue technology process information in the rescue technology implementation process structure table, the corresponding physiological parameter information of the injured and sick, and the matching medical equipment usage process, the control algorithm is used to generate the process control instructions of the corresponding medical equipment in the matching medical equipment table, and the corresponding equipment is controlled to perform emergency rescue on the injured and sick;

[0108] C4. Use the technical specification process structure table of preparatory rescue to generate preparatory equipment control instructions through the control algorithm. When the corresponding injured and sick patients change, the preparatory equipment in the supplemented and updated matching medical equipment table is controlled through the preparatory equipment control instructions to provide real-time rescue for the changed conditions of the corresponding injured and sick patients.

[0109] The medical equipment selection unit obtains matching medical equipment from the distributed node reasoning database through a matching algorithm and generates corresponding control instructions, ensuring efficient use of medical resources. Especially during air transport, the helicopter is equipped with limited medical equipment. Through precise matching and control, the role of existing medical equipment can be maximized to avoid waste of resources. In addition, the system also adjusts the treatment technology plan and the use parameters of medical equipment in real time according to the development trend of the patient's condition, ensuring that every patient can receive the most timely and effective treatment under limited resources.

[0110] The treatment technology plan generated by the system is a process integration based on the existing medical standard treatment text information, ensuring that all generated plans comply with medical standards and there are no ethical and professional issues. By inputting the generated treatment technology implementation process structure table and the trend of changes in injury severity into the deep reasoning model for verification, the system can evaluate the professionalism and standardization of the treatment technology plan and obtain a professional evaluation score. When the professional evaluation score exceeds the set threshold, the system will output the final treatment technology plan, ensuring the scientificity and reliability of the treatment process. This transparent decision-making process not only increases the medical staff's trust in the system, but also facilitates subsequent audits and optimization.

[0111] The treatment decision adjustment unit is used to adjust the generated treatment technical plan and selected medical equipment according to the real-time injury status information of the injured and sick and the predicted injury change trend, so that every injured and sick can receive the most timely and correct treatment;

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

[0113] The user interface module is used to simulate the interactive selection and parameter setting of mission scenarios, air transport plans and medical treatment technology plans, and set up AR navigation technology to assist medical treatment personnel in quickly finding battlefield casualties.

[0114] Example 2

[0115] See also Figure 2 Another embodiment provided by the present invention is a workflow of a selection control system for medical treatment equipment for air transport of batches of wounded and sick persons, specifically:

[0116] First, the data collection unit collects and pre-processes various rescue scene information and the corresponding geographic information, distribution information of the injured and sick, medical resources information, medical equipment information, air transport path information and meteorological information, and the pre-processed data is classified and stored in nodes through the distributed storage unit;

[0117] Second, through the scenario modeling unit, according to the different historical scenario information stored in the distributed storage unit, different types of air transport mission scenario spaces are simulated and generated, and according to the different air transport mission scenario spatial information, the distribution location information of the batch of wounded and sick corresponding to different air transport scenarios and the corresponding injury and disease type information and the corresponding medical supplies distribution status information are simulated through the wounded and sick distribution unit and the medical supplies simulation unit. At the same time, through the environmental meteorological simulation unit, the geographical location information and meteorological information in the air transport mission scenario spatial information are used to simulate the rescue environment and meteorological status corresponding to different air transport scenarios;

[0118] Third, based on different air transport scenarios and tasks and the corresponding geographical, meteorological and casualty distribution information, the air transport path library under different scenarios is generated and constructed through the scenario path library unit;

[0119] Fourth, according to the batch information of the injured and sick in the corresponding scenario and the corresponding injury type information, the medical material configuration unit dispatches and configures the medical equipment and personnel materials of multiple helicopters participating in the rescue. At the same time, according to the location distribution information, geographical location information and meteorological information of the injured and sick in the air transport, the collaborative path configuration unit matches the corresponding path information from the air transport path library, and configures the matched path information to different transport aircraft, and collaboratively controls the rescue aircraft to quickly reach the different distribution locations of the injured for air transport rescue;

[0120] Fifth, according to the injury type information of the batch of injured and sick patients simulated in the corresponding air transport evacuation scenario, the current status information of each corresponding injured and sick patient after classification is evaluated through the injury classification and evaluation unit to obtain the corresponding type of injury evaluation score of each injured and sick patient. At the same time, according to the current status information of the injured and sick patient, the corresponding type of injury evaluation score and the development trend of the injured and sick patient's condition are obtained through the expert prediction model; and the corresponding type of injury evaluation score of each injured and sick patient and the development trend of the injured and sick patient's condition are input into the treatment technology selection unit, and the treatment method and the deep reasoning model of the treatment specification and configuration stored in the distributed storage unit are used to generate the corresponding treatment technology plan for the injured and sick patient; according to the corresponding treatment technology plan for the injured and sick patient, the medical equipment configured for the helicopter is matched and selected from the configured medical supplies through the medical equipment selection unit, and according to the treatment process plan in the treatment technology plan and the development trend of the injured and sick patient's condition, the control algorithm is used to generate control instructions, and the corresponding treatment technology plan and medical equipment control instruction parameters are controlled and adjusted in real time to perform symptomatic treatment of injuries and diseases;

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

[0122] Seventh, the user interface module is used to interactively select and set parameters for the simulated mission scenarios, air transport plans and rescue technology plans in the first to sixth processes, and AR navigation technology is used to assist medical rescue personnel in quickly finding the wounded and sick on the battlefield and improve rescue efficiency.

[0123] Through multi-step comprehensive processing, the system has significantly improved the efficiency and quality of air transport of large numbers of wounded and sick in naval battles. First, the data collection unit and distributed storage unit ensure the comprehensive, accurate collection and efficient storage of various types of information, providing a solid data foundation for subsequent decision-making. Secondly, the scenario modeling unit and environmental meteorological simulation unit generate different types of air transport mission scenarios through historical data and real-time information, simulate the distribution of wounded and sick and the status of medical supplies, and improve the scientificity and rationality of decision-making. The optimal path library generated by the scenario path library unit, combined with the medical supplies configuration unit and the collaborative path configuration unit, realizes medical Efficient scheduling and rapid response of resources ensure that rescue aircraft can quickly reach the location of the injured and sick; the injury classification assessment unit and the treatment technology selection unit improve the accuracy and effectiveness of treatment by accurately assessing and predicting the injuries of each injured and sick person and generating personalized treatment plans; the simulation evaluation module conducts real-time evaluation and optimization of the entire process to ensure that the efficiency of air transportation and treatment always remains at the optimal state; the user interface module provides flexible interactive selection and parameter settings, enhancing the ease of use and adaptability of the system; through these comprehensive measures, the system not only greatly improves the efficiency of air transport and treatment, but also significantly enhances the scientific nature of decision-making.

[0124] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in the field may also change, modify, replace and modify the above-mentioned embodiments without departing from the scope of protection of the purpose of the present invention and the claims, and all of these are within the protection of the present invention.

[0125] If the disclosed technical solution involves personal information, the product using the disclosed technical solution has clearly informed the personal information processing rules and obtained the individual's voluntary consent before processing the personal information. If the disclosed technical solution involves sensitive personal information, the product using the disclosed technical solution has obtained the individual's separate consent before processing the sensitive personal information, and at the same time meets the "explicit consent" requirement. For example, on personal information collection devices such as cameras, clear and prominent signs are set to inform that the personal information collection scope has been entered and personal information will be collected. If the individual voluntarily enters the collection scope, it is deemed that he or she agrees to the collection of his or her personal information; or on the device that processes personal information, when the personal information processing rules are notified by obvious signs / information, the individual's authorization is obtained through pop-up information or by asking the individual to upload his or her personal information; among them, 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 type of personal information processed.

Claims

1. A selection control system for medical equipment used for air transport of batches of wounded and sick, characterized in that: include: Data management module, scenario modeling module, evacuation decision module and treatment decision module; According to the various types of rescue scene information stored in the data management module and the air transport rescue simulation information under the corresponding scenes, the scene modeling module generates different types of air transport mission scene spaces and the corresponding distribution information of batches of injured and sick people, medical supplies distribution information, rescue environment and meteorological conditions and corresponding air transport path library under each space; The evacuation decision module includes a medical material configuration unit and a collaborative path configuration unit; according to the distribution information of the batch of injured and sick people and the distribution information of medical materials in the corresponding scenario, the medical material configuration unit is used to dispatch and configure the medical equipment and personnel materials of the rescue helicopter, and at the same time, according to the rescue environment and meteorological conditions and the corresponding air transport evacuation path library, the collaborative path configuration unit is used to configure the air transport evacuation path of the rescue helicopter; The rescue decision module includes an injury classification and assessment unit, a rescue technology selection unit and a medical equipment selection unit; according to the injury type information of the batch of injured and sick patients in the corresponding scenario, the injury classification and assessment unit is used to obtain the injury assessment score and disease development trend of each corresponding injured and sick patient after classification, and the rescue technology selection unit and the deep reasoning model configured in the distributed storage unit in the data management module are used to generate a rescue technology plan for the corresponding injured and sick patient according to the injury assessment score and disease development trend of the corresponding injury and disease type of the injured and sick patient. At the same time, according to the corresponding rescue technology plan and the medical equipment configured on the helicopter, the medical equipment selection unit is used to match and select the corresponding rescue medical equipment and generate medical equipment control instructions, and at the same time, the rescue technology plan and the medical equipment control instruction parameters are adjusted in real time according to the disease development trend.

2. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 1, characterized in that: The selection control system further includes a simulation evaluation module; the transport decision module further includes a transport decision adjustment unit; the treatment decision module further includes a treatment decision adjustment unit; The simulation evaluation module is used to perform multi-dimensional simulation evaluation on the medical material configuration and path configuration efficiency in the send-back decision module, the treatment technology solution and the medical equipment in the treatment decision module, and the efficiency of selecting and controlling treatment, so as to obtain the path and medical configuration efficiency in the air transport send-back decision in the send-back decision module, as well as the injury classification evaluation and medical equipment selection and treatment efficiency in the treatment technology decision in the treatment decision module. The path and medical configuration efficiency in the air transport send-back decision is fed back to the send-back decision adjustment unit, and the injury classification evaluation and medical equipment selection and treatment efficiency in the treatment technology decision are fed back to the treatment decision adjustment unit, so as to make real-time adjustments to the air transport send-back decision and the treatment technology decision, respectively.

3. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 2, characterized in that: The air transport and rescue simulation information in the corresponding scenario includes geographical information, distribution information of the wounded and sick, personnel and material information, medical equipment information, air transport and rescue path 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 transport mission scene space through the scene modeling unit, and configure the corresponding geographical location information, the distribution status of the wounded and sick, the status of the deployable personnel and materials, the medical equipment information and the dynamic meteorological status of the current type of air transport mission scene space through the air transport rescue simulation information; A2. According to the geographical location information of the air transport mission scene space after configuration, the map layer space corresponding to the target area of ​​the current air transport mission scene space is obtained through the map layer algorithm; A3. According to the map layer space of the target area and the distribution status of the wounded and sick, the longitude and latitude position information corresponding to each wounded and sick is obtained in the map layer space, and the longitude and latitude position information of the wounded and sick is input into the clustering algorithm to obtain the cluster distribution sub-areas of the wounded and sick and the number of the wounded and sick in each sub-area, and each sub-area is labeled.

4. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 3, characterized in that: The workflow of the scene path library unit also includes: A4. Construct the input chromosome of the genetic algorithm based on the sub-region labels of the cluster distribution of the wounded and the number of wounded and sick in each sub-region, the maximum number of wounded and sick that can be rescued by the rescue helicopter at a time, and the dynamic meteorological state corresponding to the map layer space. P i and P, where X i and Y i represents the take-off and landing target area positions corresponding to the i-th rescue helicopter, p jk represents the latitude and longitude position of the kth patient in the jth patient cluster distribution sub-area, N1 represents the total number of patients in the current map layer space, N2 represents the total number of helicopters that can be called in the current map layer space, and N j represents the number of injured and sick patients corresponding to the jth cluster distribution sub-region, f j represents the number of rescue helicopters required for the jth cluster distribution sub-region of the injured and sick, and It represents the wind force level, wind direction and visibility corresponding to the current map layer space, f i represents the safety score of the path corresponding to the rescue mission performed by the i-th helicopter under the current meteorological conditions in the current map layer space, P i represents the feasible path generation parameter space corresponding to the i-th helicopter; P represents the feasible path coordination parameter space corresponding to all helicopters; A5. Construct a single helicopter feasible path fitness function F based on the input chromosome of the genetic algorithm i And the helicopter cooperative path fitness function F, specifically: F i ≥F0, where l i represents the feasible path length corresponding to the i-th helicopter, T i represents the total flight time of the feasible path corresponding to the i-th helicopter, w1, w2 and w3 represent the weighted coefficients in the fitness function respectively, and F0 represents the fitness threshold of the feasible path corresponding to the i-th helicopter.

5. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 4, characterized in that: The workflow of the scene path library unit also includes: A6. Set the maximum number of iterations g max and the rate of change stop threshold θ u , iterate the genetic algorithm and calculate the Pareto front change rate The specific formula is Among them, U t-i represents the Pareto frontier solution set of the tith generation obtained during the iteration of the genetic algorithm, x∈U t-i indicates that x is a solution in the Pareto front solution set of the ti-th generation, y is a solution in the Pareto front solution set of the t-th generation, and || ||2 represents the 2-norm symbol; A7, iterate the A4-A6 process based on the maximum number of iterations and the change rate stop threshold set in A6. When , the iteration stops, and the output search obtains the optimal generation parameter space of the feasible path corresponding to the i-th helicopter and the optimal coordination parameter space of all feasible paths corresponding to N2 helicopters; A8. Input the optimal generation parameter space of the feasible path corresponding to the i-th helicopter and the optimal coordination parameter space of all feasible paths corresponding to the N2 helicopters into the Dijkstra algorithm to obtain the coordinated feasible paths corresponding to all helicopters under the current meteorological conditions; A9. Use the collaborative feasible paths corresponding to all helicopters to build an air transport path library corresponding to the current type of air transport mission scenario space, and use the dynamic meteorological conditions at each moment to update the air transport path library in real time.

6. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 5, characterized in that: The steps of generating the corresponding treatment technical plan for the injured and sick include: B1, obtain the basic information, physiological parameters and injury description text information of each simulated patient from the map layer space configured in A2 and pre-process it, and input the pre-processed data into the dynamic electronic medical record with a built-in text automatic update model to obtain the personal dynamic electronic medical record table and dynamic physiological parameter table; B2. Input personal dynamic electronic medical records into the injury and illness classification model to perform real-time injury and illness classification; B3. The obtained injury type and the corresponding dynamic physiological parameter table are simultaneously input into the configuration trauma scoring subsystem and Glasgow coma scoring subsystem to obtain the trauma assessment score and coma assessment score of the corresponding injured person and the comprehensive injury severity assessment score of the corresponding injured person.

7. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 6, characterized in that: The step of generating the corresponding treatment technical plan for the injured and sick also includes: B4. Inputting the trauma assessment score, coma assessment score, and comprehensive injury severity assessment score of the corresponding injured and sick person and the real-time acquired dynamic physiological parameter table into a pre-built injury change prediction model to obtain the change trend of the severity of the corresponding type of injury of each injured and sick person; B5. Input the personal dynamic electronic medical record, dynamic physiological parameter table, trauma assessment score, coma assessment score and the comprehensive injury severity assessment score of the corresponding injured and sick persons into the configured matching generation model, match the corresponding injured and sick persons' treatment technical specifications from the distributed node reasoning database built into the data management module, and generate the corresponding injured and sick persons' treatment technology implementation process structure table.

8. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 7, characterized in that: The step of generating the corresponding treatment technical plan for the injured and sick also includes: B6. Input the generated treatment technology implementation process structure table and the injury severity change trend of the corresponding injured and sick patients into the deep reasoning model configured in the distributed node reasoning database, conduct physical verification on the matched treatment technology implementation process structure table, and use the matched expert verification sub-model in the deep reasoning model to evaluate the professionalism and standardization of the treatment technology implementation process structure table to obtain the corresponding professional evaluation score; B7. Set a professional assessment score threshold. When the professional assessment score is greater than the professional assessment score threshold, output the corresponding rescue technology implementation process structure table, and at the same time output the preparatory rescue technology specification process structure table corresponding to the change trend of the severity of the injury.

9. The selection control system for medical treatment equipment for air transport of batches of wounded and sick persons as claimed in claim 8, characterized in that: The step of generating a medical device control instruction comprises: C1. Based on the obtained rescue technology implementation process structure table, the medical equipment information saved in the distributed node inference database and the medical equipment currently configured by the rescue helicopter are matched and obtained from the matching medical equipment table corresponding to the current injury type of the injured and sick, and the corresponding matching medical equipment usage process is generated; C2. According to the preliminary rescue technical specification process structure table, the matching medical equipment table is supplemented and updated with the injury change through the matching algorithm to obtain the supplemented and updated matching medical equipment table; C3. Based on the rescue technology process information in the rescue technology implementation process structure table, the corresponding physiological parameter information of the injured and sick, and the matching medical equipment usage process, the control algorithm generates the process control instructions of the corresponding medical equipment in the matching medical equipment table, and controls the corresponding equipment to perform emergency rescue on the injured and sick; C4. Use the technical specification process structure table of preparatory rescue to generate preparatory equipment control instructions through the control algorithm. When the corresponding injured and sick patients change, the preparatory equipment in the supplemented and updated matching medical equipment table is controlled through the preparatory equipment control instructions to provide real-time rescue for the changed conditions of the corresponding injured and sick patients.

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