Intelligent medical emergency command and dispatch method and system

Abstract

The application provides an intelligent medical emergency command and dispatch method and system, relates to the technical field of medical emergency command and dispatch, and constructs emergency resources, demand sites, distribution centers and vehicle sets, takes the emergency resources as source nodes, takes the demand sites as target nodes, takes the distribution centers as common nodes, generates a primary node group, forms a final permanent marked node group through a search algorithm, calculates the dispatch value of each permanent marked node in the permanent marked node group, sorts the permanent marked node group, generates a new marked node group, selects the number of associated paths and the radius of the support range of the permanent marked nodes in the new marked node group, calculates the total time and the total cost of task completion of the new marked node group, and screens the optimal dispatch node and path according to the total time and the total cost of task completion. Real-time monitoring, command and dispatch of rescue are realized, and scientific decision support is provided for emergency command and dispatch of emergencies.

Description

Technical Field

[0001] This invention relates to the field of medical emergency command and dispatch technology, specifically to intelligent medical emergency command and dispatch methods and systems. Background Technology

[0002] Traditional medical emergency dispatch systems primarily consist of computer network platforms, wired voice communication systems, dispatch and information management systems, electronic map systems, and vehicle-mounted satellite positioning systems. They are systems responsible for handling "120" emergency calls, dispatching ambulances, providing emergency communication services, and coordinating medical rescue efforts during major disasters. However, these traditional systems are primarily focused on dispatching and cannot effectively address the resource shortages and lack of efficient command inherent in the existing pre-hospital emergency care system. In recent years, the rapid development of technologies such as the Internet of Things and cloud computing has provided technical support for the intelligent upgrading of traditional medical emergency dispatch systems. These systems should be transformed from "dispatch systems" into "dispatch and command systems," or simply medical emergency command systems.

[0003] The medical emergency command system is a modern, comprehensive pre-hospital medical rescue system integrating telephone voice communication, emergency command and dispatch, vehicle-mounted video terminals, video surveillance and acquisition, vehicle navigation and medical assistance, vehicle positioning, remote emergency consultation, public service platform, and remote vital sign monitoring. This intelligent medical emergency command system not only optimizes the functions of traditional medical emergency dispatch systems, making pre-hospital treatment faster and more efficient, but also adds functions such as remote consultation guidance and real-time video transmission, extending in-hospital emergency care to the pre-hospital level, achieving seamless pre-hospital and in-hospital integration, greatly shortening treatment time and improving treatment efficiency.

[0004] At present, the pre-hospital emergency care system in China is facing the following problems: (1) Traffic congestion prevents ambulances from delivering patients to medical aid points within the golden rescue time; (2) There is no effective information collection and communication platform, making it difficult to transmit information about critically ill patients in real time. The connection between ambulances and emergency departments is not in place, and patients only begin diagnosis and rescue preparations after arriving at the medical aid point, which greatly increases the rescue time; (3) There is no remote expert support system, so medical resources cannot be used efficiently and effectively; (4) At present, emergency centers and medical units in China have not yet established a pre-hospital diagnosis and treatment system, and pre-hospital care cannot truly achieve "capacity-based treatment". If the medical aid point where patients arrive is not capable of providing treatment, they need to be transferred to another hospital or even to another city to receive effective treatment. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention proposes an intelligent medical emergency command and dispatch method, comprising the following steps:

[0006] S1. Construct emergency resources, demand locations, and distribution centers. Use emergency resources as source nodes, demand locations as target nodes, and distribution centers as ordinary nodes to generate an initial node group. After a search algorithm, form the final permanently marked node group.

[0007] S2. Calculate the scheduling value for each permanent marker node, sort them, and generate a group of marker nodes;

[0008] S3. Select the number of associated paths and the supported range radius of the permanently marked nodes in the marked node group;

[0009] S4. Calculate the total task completion time and total task completion cost of the marked node group, and select the optimal scheduling node and path according to the total task completion time and total task completion cost.

[0010] Further, step S2 includes:

[0011] S21. Obtain the minimum length t from each permanently marked node to the target node. i ;

[0012] S22. Obtain the ratio of the number of permanently marked nodes to the number of all ordinary nodes, and obtain the estimated speed V between any two permanently marked nodes based on the ratio and the average speed of all permanently marked nodes.

[0013] S23. Based on the estimated speed V and minimum duration t i Calculate the scheduling value F for each permanently marked node;

[0014] S24. Sort the nodes according to the scheduling value F of each permanent marker node to generate a group of marker nodes.

[0015] Furthermore, in step S3, the support range radius R of the i-th permanently marked node i and the number of supported paths S i The following formulas are shown respectively:

[0016]

[0017]

[0018] In the formula, F min and F max F represents the minimum and maximum scheduling values ​​in the group of marked nodes, respectively. i Let γ be the scheduling value of the i-th permanently marked node, ρ be the target path length, ρ be the number of target support paths, δ be a minimal constant, and N be the total number of permanently marked nodes.

[0019] Further, in step S4, M represents the number of supporting tasks, N represents the total number of permanently marked nodes, and tc ij r represents the execution time of the j-th support task on the i-th permanent marker node. i Let T represent the unit cost of the i-th permanently marked node, and the total task completion time T be:

[0020]

[0021]

[0022] In the formula, l(j) represents the time required for the j-th task, and v i Let be the processing speed of the i-th permanently marked node;

[0023] The total cost C for completing the task is:

[0024]

[0025]

[0026] In the formula, c(i) is the cost of the i-th permanent marker node.

[0027] Furthermore, in step S22, the ratio p of the total number of permanently marked nodes N to the total number of ordinary nodes A is:

[0028] p = N / A;

[0029] Calculate the estimated velocity V between any two permanently marked nodes:

[0030]

[0031] Where Vmax is the maximum speed between any two permanently marked nodes, Vave is the average speed between all ordinary nodes, and Vave is the average speed between any two permanently marked nodes.

[0032] Further, in step S23, the scheduling value F of the i-th permanently marked node is calculated based on the estimated speed V and the minimum duration ti:

[0033]

[0034] This invention also proposes an intelligent medical emergency command and dispatch system for realizing an intelligent medical emergency command and dispatch method, including: an initial node group construction unit, a permanently marked node group construction unit, a sorting unit, and an optimal scheduling node and path generation unit;

[0035] The initial node group construction unit constructs emergency resources, demand locations, and distribution centers, using emergency resources as source nodes, demand locations as target nodes, and distribution centers as ordinary nodes to generate the initial node group.

[0036] The permanent marker node group construction unit searches for ordinary nodes in the initial node group using a search algorithm to form the final permanent marker node group.

[0037] The sorting unit calculates the scheduling value of each permanent marker node, sorts them, and generates a group of marker nodes.

[0038] The optimal scheduling node and path generation unit selects the number of associated paths and the support range radius of the permanently marked nodes in the marked node group, calculates the total task completion time and total task completion cost of the marked node group, and filters the optimal scheduling nodes and paths according to the total task completion time and total task completion cost.

[0039] Compared with the prior art, the present invention has the following beneficial technical effects:

[0040] This invention relates to an intelligent medical emergency command and dispatch system. Targeting medical emergencies, the system utilizes data processing technology to accurately construct a dataset of emergency resources, demand locations, and distribution centers. Then, it applies analysis and calculations from various units within the system to find the optimal dispatch nodes and paths. Using network analysis and path analysis functions, it provides vehicle and material resource allocation and emergency rescue path analysis. Users in need can submit support task requests to the data center, which then rationally schedules these tasks to virtual machines for real-time monitoring, command, and dispatch, providing scientific decision support for emergency command and dispatch in sudden incidents. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the intelligent medical emergency command and dispatch method of the present invention.

[0043] Figure 2 This is a schematic diagram of the intelligent medical emergency command and dispatch system of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0045] In the accompanying drawings of specific embodiments of the present invention, in order to better and more clearly describe the working principle of each component in the system and show the connection relationship of each part in the device, only the relative positional relationship between each component is clearly distinguished. It does not constitute a limitation on the signal transmission direction, connection sequence, or size, dimension, and shape of each part within the component or structure.

[0046] The intelligent medical emergency command and dispatch system utilizes task scheduling algorithms to allocate support tasks to virtual machines. When a user submits a support task request to the data center, the system rationally schedules the support task to virtual machines for processing. Figure 1 As shown, the intelligent medical emergency command and dispatch method includes the following steps:

[0047] S1. Construct emergency resources, demand locations, and distribution centers. Use emergency resources as source nodes, demand locations as target nodes, and distribution centers as ordinary nodes to generate an initial node group. After a search algorithm, form the final permanently marked node group.

[0048] First, all ordinary nodes except the source and target nodes are initialized as unmarked nodes. Multiple ordinary nodes connected to the source node are marked as first temporary marked nodes, and the ordinary node with the shortest path length to the source node is marked as a permanent marked node, thus forming a shortest path from the source node. The search continues. During the search, multiple ordinary nodes connected to ordinary nodes in the shortest path, and within a specified search range, are marked as second temporary marked nodes. In each iteration, the ordinary node with the shortest path length to the source node is searched from the temporary marked nodes and designated as a permanent marked node. In each iteration, if a path connecting to the target node is found, a shortest path is obtained, and the shortest path counter is incremented by 1. The algorithm terminates when the shortest path counter reaches a threshold. If all ordinary nodes within the specified range become permanent marked nodes, and the shortest path counter has not reached the threshold, the search range is increased, and the search continues until the upper limit of the search range is reached or all required shortest paths are found, at which point the algorithm terminates.

[0049] S2. Calculate the scheduling value for each permanently marked node, sort them, and generate a group of marked nodes. This includes the following steps:

[0050] S21. Obtain the minimum length t from each permanently marked node to the target node. i .

[0051] For a target node, it will receive data packets from many permanent marker nodes, but the time taken for different permanent marker nodes to reach the target node is different. At this time, it is necessary to obtain the minimum time from the permanent marker node to the target node.

[0052] S22. Obtain the ratio of the number of permanently marked nodes to the number of all ordinary nodes, and obtain the estimated speed V between any two permanently marked nodes based on the ratio and the average speed of all permanently marked nodes.

[0053] First, the ratio p of the total number of permanently marked nodes N to the total number of ordinary nodes A is:

[0054] p = N / A;

[0055] Calculate the estimated velocity V between any two permanently marked nodes:

[0056]

[0057] Among them, V max V represents the maximum speed between any two permanently marked nodes. ave V is the average velocity among all ordinary nodes. ave Let be the average velocity between any two permanently marked nodes.

[0058] S23. Based on the estimated speed V and minimum duration t i Calculate the scheduling value F for each permanently marked node.

[0059]

[0060] S24. Sort the nodes according to the scheduling value F of each permanent marker node to generate a group of marker nodes.

[0061] S3. Select the number of associated paths and the supported range radius of the permanently marked nodes in the marked node group.

[0062] The radius of the supported range R of the i-th permanently marked node i and the number of supported paths S i The following formulas are shown respectively:

[0063]

[0064]

[0065] In the formula, F min and Fmax F represents the minimum and maximum scheduling values ​​in the group of marked nodes, respectively. i Let be the scheduling value for the i-th permanent marker node, Y be the target path length used to adjust the radius of the support range, ρ be the number of target support paths used to control the number of support paths generated by the permanent marker node, δ be a minimum constant, and N be the total number of permanent marker nodes.

[0066] S4. Calculate the total task completion time and total task completion cost of the marked node group, and select the optimal scheduling node and path according to the total task completion time and total task completion cost.

[0067] In the process of scheduling support tasks, a task scheduling algorithm is used to reasonably allocate M support tasks in need to N permanent marker nodes for scheduling, where M>N, thereby achieving the goals of short time, low cost, and load balancing.

[0068] Let M represent the number of supporting tasks, N represent the total number of permanently marked nodes, and tc ij This represents the execution time of the j-th support task on the i-th permanent marker node, used to calculate the time required for tasks to complete on each permanent marker node. i Let $i$ represent the unit cost of the $i$-th permanently marked node, where $i \in [1, N]$ and $j \in [1, M]$.

[0069] Task completion time is one of the important factors in measuring the effectiveness of task scheduling. The total task completion time T is shown in the following formula:

[0070]

[0071]

[0072] In the formula, l(j) represents the time required for the j-th support task, and v i Let be the processing speed of the i-th permanently marked node.

[0073] The total cost C for completing the task is shown in the following formula:

[0074]

[0075]

[0076] In the formula, c(i) is the cost of the i-th permanent marker node.

[0077] Finally, the optimal permanently marked node is selected as the scheduling node and path based on the total task completion time and total task completion cost.

[0078] This invention also proposes an intelligent medical emergency command and dispatch system for implementing the above-mentioned intelligent medical emergency command and dispatch method, comprising: an initial node group construction unit, a permanently marked node group construction unit, a sorting unit, and an optimal scheduling node and path generation unit.

[0079] The initial node cluster construction unit constructs emergency resources, demand locations, and distribution centers, using emergency resources as source nodes, demand locations as target nodes, and distribution centers as ordinary nodes to generate the initial node cluster.

[0080] The permanent marker node group construction unit searches for ordinary nodes in the initial node group using a search algorithm to form the final permanent marker node group.

[0081] The sorting unit calculates the scheduling value of each permanent marker node, sorts them, and generates a group of marker nodes.

[0082] The optimal scheduling node and path generation unit selects the number of associated paths and the support range radius of the permanently marked nodes in the marked node group, calculates the total task completion time and total task completion cost of the marked node group, and filters the optimal scheduling nodes and paths according to the total task completion time and total task completion cost.

[0083] This invention relates to an intelligent medical emergency command and dispatch system. Targeting medical emergencies, the system utilizes data processing technology to accurately construct a database of emergency resources, demand locations, distribution centers, and vehicles. The system then analyzes and calculates data from various units within the system to find the optimal dispatch nodes and routes. It employs network analysis and path analysis functions to provide vehicle and material resource allocation and emergency rescue route analysis. Users in need can submit support task requests to the data center, which then rationally schedules these tasks to virtual machines. This enables real-time monitoring, command, and dispatch of rescue efforts, providing scientific decision support for emergency command and dispatch in the event of an emergency.

[0084] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0085] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An intelligent medical emergency command and dispatch method, characterized in that, Includes the following steps: S1. Construct a set of emergency resources, demand locations, and distribution centers. Use emergency resources as source nodes, demand locations as target nodes, and distribution centers as ordinary nodes to generate an initial node group. After a search algorithm, form the final permanently marked node group. First, initialize all ordinary nodes except the source node and the target node as unmarked nodes. Then, mark multiple ordinary nodes connected to the source node as the first temporary marked node, and select the ordinary node with the shortest path length to the source node as the permanent marked node. Continue searching for multiple ordinary nodes connected to ordinary nodes in the shortest path, and if these multiple ordinary nodes are within the specified search range, then these multiple ordinary nodes are marked as second temporary marker nodes. In each loop, the ordinary node with the shortest path length from the source node is searched from the temporary marker nodes and designated as a permanent marker node. In each loop, if a path connecting to the target node is found, a shortest path is obtained, and the shortest path counter is incremented by 1 until the shortest path counter reaches the threshold to end the algorithm. If all ordinary nodes within the specified range become permanently marked nodes and the shortest path counter has not reached the threshold, then increase the search range until the upper limit of the search range is reached or all the required shortest paths are found to end the algorithm. S2. Calculate the scheduling value for each permanently marked node, sort them, and generate a group of marked nodes, including: S21. Obtain the minimum length t from each permanently marked node to the target node. i ; S22. Obtain the ratio of the number of permanently marked nodes to the number of all ordinary nodes, and obtain the estimated speed V between any two permanently marked nodes based on the ratio and the average speed of all permanently marked nodes. S23. Based on the estimated speed V and minimum duration t i Calculate the scheduling value F for each permanently marked node; S24. Sort the nodes according to the scheduling value F of each permanent marker node to generate a group of marker nodes; S3. Select the number of supported paths and the radius of the supported range for the permanent marker nodes in the marker node group; the radius of the supported range R for the i-th permanent marker node. i and the number of supported paths S i The following formulas are shown respectively: ； ； In the formula, F min and F max F represents the minimum and maximum scheduling values ​​in the group of marked nodes, respectively. i Let be the scheduling value for the i-th permanently marked node. The target path length. To the target number of supported paths, is a very small constant, and N is the total number of permanently marked nodes; S4. Calculate the total task completion time and total task completion cost of the marked node group, and select the optimal scheduling node and path according to the total task completion time and total task completion cost; Let M represent the number of supporting tasks, N represent the total number of permanently marked nodes, and tc ij r represents the execution time of the j-th support task on the i-th permanent marker node. i Let T represent the unit cost of the i-th permanently marked node, and the total task completion time T be: ； ； In the formula, v represents the time required for the j-th support mission. i Let be the processing speed of the i-th permanently marked node; The total cost C for completing the task is: ； ； In the formula, c(i) is the cost of the i-th permanent marker node.

2. An intelligent medical emergency command and dispatch system, used to implement the intelligent medical emergency command and dispatch method as described in claim 1, characterized in that, include: Initial node group construction unit, permanently marked node group construction unit, sorting unit, optimal scheduling node and path generation unit; The initial node group construction unit constructs a set of emergency resources, demand locations, and distribution centers, using emergency resources as source nodes, demand locations as target nodes, and distribution centers as ordinary nodes to generate the initial node group. The permanent marker node group construction unit searches for ordinary nodes in the initial node group using a search algorithm to form the final permanent marker node group. The sorting unit calculates the scheduling value of each permanent marker node, sorts them, and generates a group of marker nodes. The optimal scheduling node and path generation unit selects the number of supported paths and the radius of the supported range of the permanently marked nodes in the marked node group, calculates the total task completion time and total task completion cost of the marked node group, and filters the optimal scheduling nodes and paths according to the total task completion time and total task completion cost.

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