Task scheduling method and device, computer equipment and storage medium

Abstract

The invention discloses a task scheduling method and device, computer equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring rescue request information of all accident points; determining all schedulable rescue teams, and obtaining position information of each schedulable rescue team; calculating a rescue distance between each accident point and each dispatchable rescue team based on the rescue position information of each accident point and the position information of each dispatchable rescue team; constructing a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team; constructing an emergency level array and a resource demand array; and according to the rescue distance array, the emergency level array and the resource demand array, performing task scheduling on each schedulable rescue team by using a pre-configured greedy scheduling strategy. The invention further relates to the technical field of block chains, and the rescue request information is stored on a block chain network. The rescue efficiency and coverage can be comprehensively improved.

Description

Technical Field

[0001] The present application belongs to the field of artificial intelligence technology, and specifically relates to a task scheduling method, device, computer equipment and storage medium. Background Art

[0002] The rescue dispatch system of an insurance company is a comprehensive management platform based on modern information technology. It integrates GPS / LBS positioning technology, big data analysis, cloud computing and other technical means to achieve real-time monitoring, dispatching and management of vehicles, personnel and rescue resources. The system can not only help insurance companies respond quickly to accidents, but also provide efficient rescue services, thereby improving customer satisfaction and the company's operational efficiency.

[0003] At present, the dispatching scheme adopted by the rescue dispatching system is usually based on the closest distance between the accident site and the current location of the rescue team for intelligent allocation. This dispatching scheme can solve the problem of rapid response to daily small accidents. However, when a large-scale sudden safety incident occurs, such as a natural disaster or a major traffic accident, due to the large number of accident points and the wide range, the scheme may cause the rescue in other areas to lag due to the concentration of resources in a certain area, which makes it difficult to fully and efficiently respond to complex rescue needs. For example, in a large-scale earthquake disaster, many places are affected at the same time, roads are interrupted, and communications are blocked. At this time, although the traditional dispatching scheme based on the closest distance can quickly respond to individual serious disaster areas, it may not be able to take into account other remote areas that are also in urgent need of assistance in a timely manner, resulting in uneven distribution of rescue resources and affecting the overall rescue efficiency. Summary of the invention

[0004] The purpose of the embodiments of the present application is to propose a task scheduling method, apparatus, computer equipment and storage medium to solve the technical problem that it is difficult to comprehensively and efficiently respond to complex rescue needs in existing scheduling schemes due to centralized resource allocation.

[0005] In order to solve the above technical problems, the present application embodiment provides a task scheduling method, which adopts the following technical solution:

[0006] A task scheduling method, comprising:

[0007] Receive task dispatch instructions and obtain rescue request information of all accident points, where the rescue request information includes rescue location information, urgency level, and resource demand information of each accident point;

[0008] Determine all dispatchable rescue teams and obtain the location information of each dispatchable rescue team;

[0009] Based on the rescue location information of each accident point and the location information of each dispatchable rescue team, the rescue distance between each accident point and each dispatchable rescue team is calculated;

[0010] Construct a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team;

[0011] The emergency level and resource requirement information are quantified respectively, and an emergency level array and a resource requirement array are constructed;

[0012] According to the rescue distance array, emergency level array and resource requirement array, each dispatchable rescue team is scheduled using a pre-configured greedy scheduling strategy.

[0013] Furthermore, the steps of scheduling tasks for each dispatchable rescue team using a pre-configured greedy scheduling strategy according to the rescue distance array, the emergency level array, and the resource requirement array specifically include:

[0014] Calculate the rescue distance priority score according to the rescue distance array;

[0015] Calculate the emergency level priority score according to the emergency level array;

[0016] Calculate resource requirement priority scores based on the resource requirement array;

[0017] The rescue distance priority score, the emergency level priority score and the resource demand priority score are compared to determine the optimal greedy scheduling strategy, where the greedy scheduling strategy includes the rescue distance priority strategy, the emergency level priority strategy and the resource demand priority strategy.

[0018] Use the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team.

[0019] Furthermore, the step of calculating the rescue distance priority score according to the rescue distance array specifically includes:

[0020] Design a distance priority score calculation function, wherein the distance priority score calculation function calculates the priority score based on the inverse of the distance;

[0021] Use the distance priority score calculation function to calculate the priority score of the rescue distance array to obtain the rescue distance priority score;

[0022] Design an emergency level priority score calculation function, wherein the emergency level priority score calculation function is based on the emergency level value as the priority score;

[0023] Use the emergency level priority score calculation function to calculate the priority score of the emergency level array to obtain the emergency level priority score;

[0024] A resource requirement priority score calculation function is designed, wherein the resource requirement priority score calculation function calculates the priority score based on the required resource quantity.

[0025] Use the resource requirement priority score calculation function to calculate the priority score of the resource requirement array to obtain the resource requirement priority score.

[0026] Furthermore, the distance priority score calculation function expression is:

[0027]

[0028] In the formula, P is the rescue distance priority score, L is the rescue distance, and ε is a constant;

[0029] The resource requirement priority score calculation function expression is:

[0030]

[0031] Where Q is the resource requirement priority score, M is the number of required resources, and β is a constant.

[0032] Furthermore, the steps of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically include:

[0033] When the optimal greedy scheduling strategy is the emergency level priority strategy, the emergency level priority strategy is executed, the first rescue task is determined based on the emergency level array, and the first target rescue task is obtained;

[0034] Determining resource requirement information of the first target rescue mission based on the resource requirement array;

[0035] Determine, according to the resource demand information of the first target rescue mission, a dispatchable rescue team that can provide the required resources for the first target rescue mission, and obtain a first rescue team set;

[0036] The rescue distances of each dispatchable rescue team in the first rescue team set to the first target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the first target rescue team.

[0037] Furthermore, the steps of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically include:

[0038] When the optimal greedy scheduling strategy is the resource demand priority strategy, the resource demand priority strategy is executed, the first rescue task is determined based on the resource demand array, and the second target rescue task is obtained;

[0039] Determining resource requirement information of a second target rescue mission based on the resource requirement array;

[0040] Determine, according to the resource requirement information of the second target rescue mission, a dispatchable rescue team that can provide the required resources for the second target rescue mission, and obtain a second rescue team set;

[0041] The rescue distances of each dispatchable rescue team in the second rescue team set to the second target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the second target rescue team.

[0042] Furthermore, the steps of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically include:

[0043] When the optimal greedy scheduling strategy is the rescue distance priority strategy, the rescue distance priority strategy is executed, and the first rescue task is determined based on the rescue distance priority strategy to obtain the third target rescue task;

[0044] Determining resource requirement information of a third target rescue mission based on the resource requirement array;

[0045] Determine, according to the resource demand information of the third target rescue mission, a dispatchable rescue team that can provide the required resources for the third target rescue mission, and obtain a third rescue team set;

[0046] The rescue distances of each dispatchable rescue team in the third rescue team set to the third target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the third target rescue team.

[0047] In order to solve the above technical problems, the embodiment of the present application further provides a task scheduling device, which adopts the following technical solution:

[0048] A task scheduling device, comprising:

[0049] A rescue information acquisition module is used to receive task dispatch instructions and obtain rescue request information of all accident points, wherein the rescue request information includes rescue location information, emergency level, and resource demand information of each accident point;

[0050] A location information determination module is used to determine all dispatchable rescue teams and obtain the location information of each dispatchable rescue team;

[0051] A rescue distance calculation module is used to calculate the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team;

[0052] A first array building module is used to build a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team;

[0053] The second array construction module is used to quantify the emergency level and resource demand information respectively, and construct an emergency level array and a resource demand array;

[0054] The rescue task scheduling module is used to schedule tasks for each dispatchable rescue team based on the rescue distance array, emergency level array and resource requirement array, using a pre-configured greedy scheduling strategy.

[0055] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0056] A computer device comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of any one of the above-mentioned task scheduling methods when executing the computer-readable instructions.

[0057] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0058] A computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of any one of the task scheduling methods described above.

[0059] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0060] The present application discloses a task scheduling method, device, computer equipment and storage medium, which belongs to the field of artificial intelligence technology. The present application obtains the rescue request information of all accident points; determines all dispatchable rescue teams, and obtains the location information of each dispatchable rescue team; calculates the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team; constructs a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team; constructs an emergency level array and a resource demand array; and performs task scheduling for each dispatchable rescue team based on the rescue distance array, the emergency level array and the resource demand array, and uses a pre-configured greedy scheduling strategy. The present application realizes the flexible allocation and optimal configuration of rescue resources through multi-dimensional evaluation of rescue information and combines the greedy scheduling strategy, which can ensure that in complex rescue scenarios, the rescue team can respond quickly and the resources are reasonably dispersed, thereby comprehensively improving the rescue efficiency and coverage, effectively alleviating the limitations brought about by the centralized allocation of resources, and better meeting the diverse emergency rescue needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0062] Figure 1 An exemplary system architecture diagram is shown in which the present application can be applied;

[0063] Figure 2 A flowchart of an embodiment of a task scheduling method according to the present application is shown;

[0064] Figure 3 A schematic diagram of the structure of an embodiment of a task scheduling device according to the present application is shown;

[0065] Figure 4 A schematic structural diagram of an embodiment of a computer device according to the present application is shown. DETAILED DESCRIPTION

[0066] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0067] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0068] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0069] like Figure 1As shown, the system architecture 100 may include a terminal device 101, a network 102 and a server 103. The terminal device 101 may be a laptop 1011, a tablet computer 1012 or a mobile phone 1013. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables.

[0070] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0071] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop computer 1011, the tablet computer 1012 or the mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer and a desktop computer, etc.

[0072] The server 103 may be a server that provides various services, such as a background server that provides support for a web page displayed on the terminal device 101 .

[0073] It should be noted that the task scheduling method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the task scheduling device is generally set in the server / terminal device.

[0074] It should be understood that Figure 1 The numbers of terminal devices, networks and servers in the embodiment are merely illustrative. The above system may have any number of terminal devices, networks and servers according to implementation requirements.

[0075] Continue to refer Figure 2 , shows a flow chart of an embodiment of a method for task scheduling according to the present application. The task scheduling method comprises the following steps:

[0076] S201, receiving a task dispatching instruction, and obtaining rescue request information of all accident points, wherein the rescue request information includes rescue location information, emergency level, and resource demand information of each accident point.

[0077] Specifically, by receiving the task mobilization instructions in a timely manner, the system can immediately enter the emergency state and quickly respond to various emergency rescue needs. After receiving the instructions, the system comprehensively collects the rescue request information of each accident point, which includes three core elements: rescue location information, urgency level and resource demand information. The accuracy of the rescue location information is directly related to whether the rescue team can arrive at the scene quickly; the classification of urgency levels helps the system prioritize the most urgent rescue requests; and the clarity of resource demand information ensures that the rescue team can carry the correct equipment and supplies to the scene, thereby improving rescue efficiency.

[0078] S202, determine all dispatchable rescue teams, and obtain location information of each dispatchable rescue team.

[0079] Specifically, the system can maximize the use of existing resources by identifying all dispatchable rescue teams. The system then obtains the location information of each dispatchable rescue team and can use positioning technology (such as GPS) to ensure the accuracy of the location information. Identifying the dispatchable rescue teams and obtaining their location information is the basis for subsequent rescue team allocation, rescue route planning, etc. Based on this location information, the system can formulate a reasonable dispatch plan to ensure that the rescue team can reach the accident site quickly and accurately.

[0080] S203, based on the rescue location information of each accident point and the location information of each dispatchable rescue team, calculate the rescue distance between each accident point and each dispatchable rescue team.

[0081] Specifically, the system determines the rescue location information of each accident point and the location information of each dispatchable rescue team, and by calculating the distance between the two, the system can make decisions based on the actual spatial distribution. By understanding the shortest (or optimal) path from each rescue team to each accident point, the system can more quickly determine which teams can arrive at the scene the fastest, so that these teams can be dispatched first, which helps to shorten response time and improve rescue efficiency.

[0082] S204, constructing a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team.

[0083] Specifically, the rescue distance array is a two-dimensional array used to store and represent the rescue distances between multiple accident points and multiple dispatchable rescue teams, where rows represent accident points, columns represent dispatchable rescue teams, and each element in the array corresponds to a specific rescue distance. Before constructing the rescue distance array, it is necessary to calculate the rescue distances between each accident point and each dispatchable rescue team. The process of constructing the rescue distance array involves a lot of calculations. Parallel computing technology can be used to process multiple computing tasks simultaneously, or a cache mechanism can be used to reduce repeated calculations.

[0084] By constructing a rescue distance array to effectively represent and store the rescue distance information between each accident point and each dispatchable rescue team, it provides important data support for subsequent dispatch decisions and helps to optimize the efficiency of rescue operations.

[0085] S205, quantifying the emergency level and resource requirement information respectively, and constructing an emergency level array and a resource requirement array.

[0086] Specifically, quantitative processing is the process of converting fuzzy, subjective or qualitative information into specific, comparable and calculable values ​​or levels. Constructing emergency level arrays and resource demand arrays helps to structure and standardize data, facilitating rapid query, sorting and comparison operations. Through quantitative processing, it can ensure that the urgency and resource requirements of different accidents or events can be compared and sorted in a unified, objective and measurable way.

[0087] The quantification of the emergency level is usually based on a series of predefined evaluation criteria or indicators, such as casualties, property damage, and the scope of the accident. These criteria or indicators are assigned different weights and scored or rated according to the actual situation. Ultimately, the emergency level of each accident or incident is obtained through comprehensive calculation.

[0088] The quantification of resource requirement information involves a detailed assessment and calculation of the various resources (such as human, material, financial, etc.) required for the rescue operation, including determining the number, type, professional skills of the required rescue teams, as well as the required equipment, supplies and funds.

[0089] The system quantifies the urgency level and resource demand information and constructs the corresponding array structure to achieve data structuring and standardization, thereby improving the accuracy and efficiency of scheduling decisions.

[0090] S206, according to the rescue distance array, the emergency level array and the resource requirement array, and using a pre-configured greedy scheduling strategy, each dispatchable rescue team is task scheduled.

[0091] The greedy scheduling strategy is configured based on the principle of greedy algorithm. Greedy algorithm (Greedy Algorithm), also known as greedy algorithm, is an algorithm that takes the best or optimal (i.e. most favorable) choice in each step, hoping to lead to the best or optimal result in the world. The basic idea of ​​greedy algorithm is to start from a certain initial solution of the problem and gradually approach the given goal to obtain a better solution as quickly as possible. When a certain step is reached and it can no longer move forward, the algorithm stops.

[0092] Specifically, the system makes full use of three key data sources: rescue distance array, emergency level array and resource demand array. By integrating the data of these three arrays, the dispatch system can comprehensively evaluate the actual situation of each accident point, including its urgency, distance and required resources, so as to make more accurate and reasonable dispatch decisions.

[0093] For example, in a scheduling scenario, first, the scheduling system will sort the accident points according to the emergency level array, giving priority to the accident points with higher urgency. Then, for each accident point, the scheduling system will screen out all the dispatchable rescue teams that can reach the accident point according to the rescue distance array. Next, the scheduling system will evaluate and compare the selected rescue teams based on the resource demand array and the actual capabilities of the rescue teams (such as the number of personnel, types of equipment, etc.). Finally, the scheduling system will select the optimal rescue team for task allocation based on the greedy scheduling strategy, and update the relevant arrays to reflect the latest scheduling situation.

[0094] The greedy scheduling strategy is simple to implement, fast in calculation, and can make effective scheduling decisions in a short time. In addition, the scheme makes full use of information from multiple data sources to improve the accuracy and rationality of scheduling decisions.

[0095] In the above embodiments, the present application realizes flexible allocation and optimal configuration of rescue resources through multi-dimensional evaluation of rescue information and combines it with a greedy scheduling strategy, which can ensure that in complex rescue scenarios, rescue teams can respond quickly and resources are reasonably dispersed, thereby comprehensively improving rescue efficiency and coverage, effectively alleviating the limitations brought about by centralized resource allocation, and better meeting diverse emergency rescue needs.

[0096] Furthermore, the steps of scheduling tasks for each dispatchable rescue team using a pre-configured greedy scheduling strategy according to the rescue distance array, the emergency level array, and the resource requirement array specifically include:

[0097] Calculate the rescue distance priority score according to the rescue distance array;

[0098] Calculate the emergency level priority score according to the emergency level array;

[0099] Calculate resource requirement priority scores based on the resource requirement array;

[0100] The rescue distance priority score, the emergency level priority score and the resource demand priority score are compared to determine the optimal greedy scheduling strategy, where the greedy scheduling strategy includes the rescue distance priority strategy, the emergency level priority strategy and the resource demand priority strategy.

[0101] Use the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team.

[0102] In this embodiment, the rescue distance from each accident point to each dispatchable rescue team can be calculated through the rescue distance array. Based on these rescue distances, the priority score of the rescue distance can be further calculated. Generally speaking, the closer the distance, the higher the score, indicating that the rescue team should be given priority.

[0103] The emergency level array provides the emergency level information of each accident point. Based on this emergency level information, it can be converted into an emergency level priority score. The higher the emergency level, the higher the score, which means that the accident point should be handled with priority.

[0104] The resource requirement array lists in detail the resource types and quantities required for each incident point. Based on these resource requirements, the ability of each dispatchable rescue team to meet these requirements can be evaluated, and the priority score of the resource requirements can be calculated accordingly. The higher the resource matching degree, the higher the score, indicating that the rescue team is more suitable for performing the task.

[0105] Based on the rescue distance array, emergency level array and resource demand array, three greedy scheduling strategies are determined, namely the rescue distance priority strategy, the emergency level priority strategy and the resource demand priority strategy. Then, the priority score is calculated according to the preset priority score calculation function to determine the optimal greedy scheduling strategy. After determining the optimal greedy scheduling strategy, the tasks of each dispatchable rescue team are scheduled according to the strategy.

[0106] In the above embodiment, by quantifying the three key factors of rescue distance, emergency level and resource demand, and combining with the greedy scheduling strategy, a systematic and effective method is provided for the task scheduling of the rescue team.

[0107] Furthermore, the step of calculating the rescue distance priority score according to the rescue distance array specifically includes:

[0108] Design a distance priority score calculation function, wherein the distance priority score calculation function calculates the priority score based on the inverse of the distance;

[0109] Use the distance priority score calculation function to calculate the priority score of the rescue distance array to obtain the rescue distance priority score.

[0110] In this embodiment, it can be set that the shorter the distance, the higher the priority should be, which can be achieved in many ways, such as using the reciprocal of the distance (or some transformation of the reciprocal to avoid division by zero) as the priority score.

[0111] Further, in a specific embodiment of the present application, the distance priority score calculation function expression is:

[0112]

[0113] In the formula, P is the rescue distance priority score, L is the rescue distance, and ε is a constant. ε is a small positive number (such as 0.001) to avoid the division by zero error when the distance is 0. The purpose of this formula is to map the distance into a positive range, and the shorter the distance, the higher the score.

[0114] Furthermore, an emergency level priority score calculation function is designed, wherein the emergency level priority score calculation function is based on the emergency level value as the priority score;

[0115] The emergency level priority score calculation function is used to calculate the priority score of the emergency level array to obtain the emergency level priority score.

[0116] In this embodiment, the method for calculating the emergency level priority score by the emergency level array generally depends on how the emergency level is defined and quantified, for example, the emergency level is directly mapped to a priority score, such as assuming that the emergency level itself is the priority score, or it can be converted into a priority score through a simple linear transformation, where the higher the emergency level, the higher the priority score.

[0117] Furthermore, a resource requirement priority score calculation function is designed, wherein the resource requirement priority score calculation function calculates the priority score based on the required resource quantity.

[0118] Use the resource requirement priority score calculation function to calculate the priority score of the resource requirement array to obtain the resource requirement priority score.

[0119] In this embodiment, the demand for various resources at each rescue point is counted, and a resource demand array is constructed. This array is a two-dimensional array, in which rows represent different rescue points, columns represent different types of resources, and each element represents the demand for a resource at a rescue point. The lower the ratio of the demand to the available amount, the higher the priority should be. A function that calculates the priority score based on the number of required resources can be designed to calculate the resource demand priority score.

[0120] Furthermore, in a specific embodiment of the present application, the resource requirement priority score calculation function expression is:

[0121]

[0122] In the formula, Q is the resource demand priority score, M is the number of required resources, and β is a constant. β is a very small positive number (such as 0.001) to avoid the division by zero error when the distance is 0. The purpose of this formula is to map the resource demand to a positive range, and the lower the resource demand, the higher the score.

[0123] Furthermore, the steps of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically include:

[0124] When the optimal greedy scheduling strategy is the emergency level priority strategy, the emergency level priority strategy is executed, the first rescue task is determined based on the emergency level array, and the first target rescue task is obtained;

[0125] Determining resource requirement information of the first target rescue mission based on the resource requirement array;

[0126] Determine, according to the resource demand information of the first target rescue mission, a dispatchable rescue team that can provide the required resources for the first target rescue mission, and obtain a first rescue team set;

[0127] The rescue distances of each dispatchable rescue team in the first rescue team set to the first target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the first target rescue team.

[0128] In this embodiment, first, the task that needs to be rescued first, that is, the task with the highest emergency level, is determined based on the emergency level array, and is regarded as the first target rescue task. Next, based on the resource requirement array, the specific information such as the type and quantity of resources required for the first target rescue task is analyzed in detail to ensure that the selected rescue team can meet the task requirements. Then, based on the resource requirement information of the first target rescue task, all dispatchable rescue teams that can provide the required resources are screened to form a first rescue team set. Finally, based on the rescue distance array, the rescue distance from each dispatchable rescue team in the first rescue team set to the first target rescue task is calculated. Then, the rescue team with the shortest rescue distance is selected as the first target rescue team to perform the rescue task.

[0129] In the above embodiment, under the emergency level priority strategy, a clear and systematic process is provided for the task scheduling of the rescue team, and the effectiveness and efficiency of the rescue operation are ensured through measures such as rapid response, resource matching and efficiency optimization.

[0130] Furthermore, the steps of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically include:

[0131] When the optimal greedy scheduling strategy is the resource demand priority strategy, the resource demand priority strategy is executed, the first rescue task is determined based on the resource demand array, and the second target rescue task is obtained;

[0132] Determining resource requirement information of a second target rescue mission based on the resource requirement array;

[0133] Determine, according to the resource requirement information of the second target rescue mission, a dispatchable rescue team that can provide the required resources for the second target rescue mission, and obtain a second rescue team set;

[0134] The rescue distances of each dispatchable rescue team in the second rescue team set to the second target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the second target rescue team.

[0135] In this embodiment, first, according to the resource requirement array, the resource requirements of each task to be rescued are evaluated, and the task that needs to be rescued first, that is, the task with the most urgent or critical resource requirements, is determined, and it is regarded as the second target rescue task. Then, the resource requirement information of the second target rescue task is deeply analyzed, including the required resource type, quantity, special requirements, etc. According to the resource requirement information of the second target rescue task, all dispatchable rescue teams that can provide the required resources are screened to form a second rescue team set. Finally, based on the rescue distance array, the rescue distance from each dispatchable rescue team in the second rescue team set to the second target rescue task is calculated. Then, the rescue team with the shortest rescue distance is selected as the second target rescue team to perform the rescue task.

[0136] In the above embodiment, under the resource demand priority strategy, a clear and systematic process is provided for the task scheduling of the rescue team, and the effectiveness and efficiency of the rescue operation are ensured through measures such as resource orientation, precise matching and efficiency optimization.

[0137] Furthermore, the steps of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically include:

[0138] When the optimal greedy scheduling strategy is the rescue distance priority strategy, the rescue distance priority strategy is executed, and the first rescue task is determined based on the rescue distance priority strategy to obtain the third target rescue task;

[0139] Determining resource requirement information of a third target rescue mission based on the resource requirement array;

[0140] Determine, according to the resource demand information of the third target rescue mission, a dispatchable rescue team that can provide the required resources for the third target rescue mission, and obtain a third rescue team set;

[0141] The rescue distances of each dispatchable rescue team in the third rescue team set to the third target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the third target rescue team.

[0142] In this embodiment, first, the relative distance between each task to be rescued and the dispatchable rescue team is evaluated based on the rescue distance array, and the task with the closest distance is selected as the task that needs to be rescued first, that is, the third target rescue task. After determining the third target rescue task, based on the resource requirement array, the specific information such as the type and quantity of resources required for the task is analyzed in detail. According to the resource requirement information of the third target rescue task, all dispatchable rescue teams that can provide the required resources are screened out to form a third rescue team set. Based on the rescue distance array again, the actual rescue distance from each dispatchable rescue team in the third rescue team set to the third target rescue task is determined. Finally, the rescue team with the shortest rescue distance is selected as the third target rescue team to perform the rescue task.

[0143] In the above embodiment, under the rescue distance priority strategy, a clear and systematic process is provided for the task scheduling of the rescue team. Through efficiency priority, resource matching and double screening, the effectiveness and efficiency of the rescue operation are ensured.

[0144] The above three priority scheduling strategies (including emergency level priority, resource demand priority, and rescue distance priority) are used to schedule the tasks of the rescue team, each of which has significant technical effects. The emergency level priority strategy ensures that the most urgent tasks can be responded to quickly, effectively reducing the losses caused by delays. The resource demand priority strategy is scheduled according to the resource urgency of the task, ensuring that key resources can be allocated to the most needed tasks first, improving resource utilization efficiency. The rescue distance priority strategy directly targets the rescue efficiency. By selecting the team closest to the accident site, the response time is shortened and the overall rescue speed is improved.

[0145] These three dispatching strategies optimize the effectiveness and efficiency of rescue operations. In practical applications, these strategies can be flexibly selected or combined according to specific circumstances and needs to achieve the best rescue effect. By comprehensively considering the degree of urgency, resource requirements and rescue efficiency, rescue teams can be dispatched more scientifically and reasonably, providing strong guarantees for the success of rescue operations.

[0146] In the above embodiment, the present application discloses a task scheduling method, which belongs to the field of artificial intelligence technology. The present application obtains the rescue request information of all accident points; determines all dispatchable rescue teams, and obtains the location information of each dispatchable rescue team; calculates the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team; constructs a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team; constructs an emergency level array and a resource demand array; and performs task scheduling for each dispatchable rescue team based on the rescue distance array, the emergency level array and the resource demand array, and uses a pre-configured greedy scheduling strategy. The present application realizes the flexible allocation and optimal configuration of rescue resources through multi-dimensional evaluation of rescue information and combined with a greedy scheduling strategy, which can ensure that in complex rescue scenarios, the rescue team can respond quickly and resources are reasonably dispersed, thereby comprehensively improving the rescue efficiency and coverage, effectively alleviating the limitations brought about by centralized resource allocation, and better meeting diverse emergency rescue needs.

[0147] In this embodiment, the task scheduling method is executed on the electronic device (eg Figure 1 The server shown in the figure can receive instructions or obtain data through a wired connection or a wireless connection. It should be noted that the above wireless connection method may include but is not limited to 3G / 4G connection, Wi-Fi connection, Bluetooth connection, Wi MAX connection, Zigbee connection, UWB (Ultra Wi-Fi Band) connection, and other wireless connection methods currently known or to be developed in the future.

[0148] It should be emphasized that in order to further ensure the privacy and security of the above rescue request information, the above rescue request information can also be stored in a blockchain node.

[0149] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0150] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0151] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0152] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0153] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0154] Further references Figure 3 , as a response to the above Figure 2 The present application provides an embodiment of a task scheduling device, and the embodiment of the device is similar to Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0155] like Figure 3 As shown, the task scheduling device 300 described in this embodiment includes:

[0156] The rescue information acquisition module 301 is used to receive the task dispatch instruction and obtain the rescue request information of all accident points, wherein the rescue request information includes the rescue location information, emergency level, and resource demand information of each accident point;

[0157] A location information determination module 302 is used to determine all dispatchable rescue teams and obtain location information of each dispatchable rescue team;

[0158] A rescue distance calculation module 303 is used to calculate the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team;

[0159] A first array building module 304 is used to build a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team;

[0160] The second array construction module 305 is used to quantify the emergency level and resource requirement information and construct an emergency level array and a resource requirement array;

[0161] The rescue task scheduling module 306 is used to schedule tasks for each dispatchable rescue team according to the rescue distance array, the emergency level array and the resource requirement array, using a pre-configured greedy scheduling strategy.

[0162] Furthermore, the rescue mission scheduling module 306 is specifically used for:

[0163] Calculate the rescue distance priority score according to the rescue distance array; calculate the emergency level priority score according to the emergency level array;

[0164] Calculate the resource demand priority score according to the resource demand array; compare the rescue distance priority score, emergency level priority score and resource demand priority score to determine the optimal greedy scheduling strategy, where the greedy scheduling strategy includes the rescue distance priority strategy, emergency level priority strategy and resource demand priority strategy. Use the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team.

[0165] Furthermore, the rescue mission scheduling module 306 is further used to:

[0166] Design a distance priority score calculation function, wherein the distance priority score calculation function calculates the priority score based on the inverse of the distance; use the distance priority score calculation function to calculate the priority score of the rescue distance array to obtain the rescue distance priority score;

[0167] Design an emergency level priority score calculation function, wherein the emergency level priority score calculation function is based on the emergency level value as the priority score; use the emergency level priority score calculation function to calculate the priority score of the emergency level array to obtain the emergency level priority score;

[0168] Design a resource requirement priority score calculation function, wherein the resource requirement priority score calculation function calculates the priority score based on the required resource quantity. Use the resource requirement priority score calculation function to calculate the priority score of the resource requirement array to obtain the resource requirement priority score.

[0169] Furthermore, the distance priority score calculation function expression is:

[0170]

[0171] In the formula, P is the rescue distance priority score, L is the rescue distance, and ε is a constant;

[0172] The resource requirement priority score calculation function expression is:

[0173]

[0174] Where Q is the resource requirement priority score, M is the number of required resources, and β is a constant.

[0175] Furthermore, the rescue mission scheduling module 306 is also used to:

[0176] When the optimal greedy scheduling strategy is the emergency level priority strategy, the emergency level priority strategy is executed, and the first rescue mission is determined based on the emergency level array to obtain the first target rescue mission; the resource requirement information of the first target rescue mission is determined based on the resource requirement array; according to the resource requirement information of the first target rescue mission, the dispatchable rescue team that can provide the required resources for the first target rescue mission is determined to obtain the first rescue team set; based on the rescue distance array, the rescue distance from each dispatchable rescue team in the first rescue team set to the first target rescue mission is determined, and the rescue team corresponding to the shortest rescue distance is determined as the first target rescue team.

[0177] Furthermore, the rescue mission scheduling module 306 is also used to:

[0178] When the optimal greedy scheduling strategy is the resource demand priority strategy, the resource demand priority strategy is executed, and the first rescue mission is determined based on the resource demand array to obtain the second target rescue mission; the resource demand information of the second target rescue mission is determined based on the resource demand array; according to the resource demand information of the second target rescue mission, the dispatchable rescue team that can provide the required resources for the second target rescue mission is determined to obtain the second rescue team set; based on the rescue distance array, the rescue distance from each dispatchable rescue team in the second rescue team set to the second target rescue mission is determined, and the rescue team corresponding to the shortest rescue distance is determined as the second target rescue team.

[0179] Furthermore, the rescue mission scheduling module 306 is also used to:

[0180] When the optimal greedy scheduling strategy is the rescue distance priority strategy, the rescue distance priority strategy is executed, and the first rescue task is determined based on the rescue distance priority strategy to obtain the third target rescue task; the resource requirement information of the third target rescue task is determined based on the resource requirement array; according to the resource requirement information of the third target rescue task, the dispatchable rescue team that can provide the required resources for the third target rescue task is determined to obtain the third rescue team set; based on the rescue distance array, the rescue distance from each dispatchable rescue team in the third rescue team set to the third target rescue task is determined, and the rescue team corresponding to the shortest rescue distance is determined as the third target rescue team.

[0181] In the above embodiment, the present application discloses a task scheduling device, which belongs to the field of artificial intelligence technology. The present application obtains the rescue request information of all accident points; determines all dispatchable rescue teams, and obtains the location information of each dispatchable rescue team; calculates the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team; constructs a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team; constructs an emergency level array and a resource demand array; and performs task scheduling for each dispatchable rescue team based on the rescue distance array, the emergency level array and the resource demand array, and uses a pre-configured greedy scheduling strategy. The present application realizes the flexible allocation and optimal configuration of rescue resources through multi-dimensional evaluation of rescue information and combined with a greedy scheduling strategy, which can ensure that in complex rescue scenarios, the rescue team can respond quickly and resources are reasonably dispersed, thereby comprehensively improving the rescue efficiency and coverage, effectively alleviating the limitations brought about by centralized resource allocation, and better meeting diverse emergency rescue needs.

[0182] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0183] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected and communicated through a system bus. It should be noted that the figure only shows a computer device 4 having a memory 41, a processor 42, and a network interface 43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital processor (DSP), an embedded device, etc.

[0184] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0185] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart memory card (Smart Med ia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the task scheduling method, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0186] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run computer-readable instructions or process data stored in the memory 41, such as computer-readable instructions for running the task scheduling method.

[0187] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0188] In the above embodiment, the present application discloses a computer device, which belongs to the field of artificial intelligence technology. The present application obtains the rescue request information of all accident points; determines all dispatchable rescue teams, and obtains the location information of each dispatchable rescue team; calculates the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team; constructs a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team; constructs an emergency level array and a resource demand array; and performs task scheduling for each dispatchable rescue team based on the rescue distance array, the emergency level array and the resource demand array, and uses a pre-configured greedy scheduling strategy. The present application realizes the flexible allocation and optimal configuration of rescue resources through multi-dimensional evaluation of rescue information and combined with a greedy scheduling strategy, which can ensure that in complex rescue scenarios, the rescue team can respond quickly and resources are reasonably dispersed, thereby comprehensively improving the rescue efficiency and coverage, effectively alleviating the limitations brought about by centralized resource allocation, and better meeting diverse emergency rescue needs.

[0189] The present application also provides another implementation, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the task scheduling method as described above.

[0190] In the above embodiment, the present application discloses a computer-readable storage medium, which belongs to the field of artificial intelligence technology. The present application obtains the rescue request information of all accident points; determines all dispatchable rescue teams, and obtains the location information of each dispatchable rescue team; calculates the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team; constructs a rescue distance array based on the rescue distance between each accident point and each dispatchable rescue team; constructs an emergency level array and a resource demand array; and performs task scheduling for each dispatchable rescue team according to the rescue distance array, the emergency level array and the resource demand array, and uses a pre-configured greedy scheduling strategy. The present application realizes the flexible allocation and optimal configuration of rescue resources through multi-dimensional evaluation of rescue information and combined with a greedy scheduling strategy, which can ensure that in complex rescue scenarios, the rescue team can respond quickly and resources are reasonably dispersed, thereby comprehensively improving the rescue efficiency and coverage, effectively alleviating the limitations brought about by centralized resource allocation, and better meeting diverse emergency rescue needs.

[0191] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0192] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0193] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A task scheduling method, characterized in that: include: Receive task dispatch instructions and obtain rescue request information of all accident points, wherein the rescue request information includes rescue location information, emergency level, and resource demand information of each accident point; Determine all dispatchable rescue teams and obtain the location information of each dispatchable rescue team; Calculating the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team; Constructing a rescue distance array based on the rescue distances between each accident point and each dispatchable rescue team; Quantifying the emergency level and the resource requirement information respectively, and constructing an emergency level array and a resource requirement array; According to the rescue distance array, the emergency level array and the resource requirement array, a pre-configured greedy scheduling strategy is used to perform task scheduling for each dispatchable rescue team.

2. The task scheduling method according to claim 1, characterized in that: The step of scheduling tasks for each dispatchable rescue team according to the rescue distance array, the emergency level array and the resource requirement array and using a pre-configured greedy scheduling strategy specifically includes: Calculate a rescue distance priority score according to the rescue distance array; Calculate the emergency level priority score according to the emergency level array; Calculating a resource requirement priority score according to the resource requirement array; Compare the rescue distance priority score, the emergency level priority score and the resource demand priority score to determine an optimal greedy scheduling strategy, wherein the greedy scheduling strategy includes a rescue distance priority strategy, an emergency level priority strategy and a resource demand priority strategy; The optimal greedy scheduling strategy is used to schedule tasks for each dispatchable rescue team.

3. The task scheduling method according to claim 2, characterized in that: The step of calculating the rescue distance priority score according to the rescue distance array specifically includes: Designing a distance priority score calculation function, wherein the distance priority score calculation function calculates the priority score based on the inverse of the distance; Use the distance priority score calculation function to calculate the priority score of the rescue distance array to obtain the rescue distance priority score; Designing an emergency level priority score calculation function, wherein the emergency level priority score calculation function is based on the emergency level value as the priority score; Calculate the priority score of the emergency level array using the emergency level priority score calculation function to obtain an emergency level priority score; Designing a resource requirement priority score calculation function, wherein the resource requirement priority score calculation function calculates the priority score based on the number of required resources; The resource requirement priority score calculation function is used to calculate the priority score of the resource requirement array to obtain the resource requirement priority score.

4. The task scheduling method according to claim 3, characterized in that: The distance priority score calculation function expression is: In the formula, P is the rescue distance priority score, L is the rescue distance, and ε is a constant; The resource requirement priority score calculation function expression is: Where Q is the resource requirement priority score, M is the number of required resources, and β is a constant.

5. The task scheduling method according to claim 2, characterized in that: The step of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically includes: When the optimal greedy scheduling strategy is an emergency level priority strategy, the emergency level priority strategy is executed, and the first rescue task is determined based on the emergency level array to obtain the first target rescue task; Determining resource requirement information of the first target rescue mission based on the resource requirement array; Determine, according to the resource requirement information of the first target rescue task, a dispatchable rescue team that can provide the required resources for the first target rescue task, and obtain a first rescue team set; The rescue distances from each dispatchable rescue team in the first rescue team set to the first target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the first target rescue team.

6. The task scheduling method according to claim 2, characterized in that: The step of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically includes: When the optimal greedy scheduling strategy is a resource demand priority strategy, the resource demand priority strategy is executed, the first rescue task is determined based on the resource demand array, and the second target rescue task is obtained; Determining resource requirement information of the second target rescue mission based on the resource requirement array; Determine, according to the resource requirement information of the second target rescue mission, a dispatchable rescue team that can provide the required resources for the second target rescue mission, and obtain a second rescue team set; The rescue distances from each dispatchable rescue team in the second rescue team set to the second target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the second target rescue team.

7. The task scheduling method according to claim 2, characterized in that: The step of using the optimal greedy scheduling strategy to schedule tasks for each dispatchable rescue team specifically includes: When the optimal greedy scheduling strategy is a rescue distance priority strategy, the rescue distance priority strategy is executed, and the first rescue task is determined based on the rescue distance priority strategy to obtain a third target rescue task; Determining resource requirement information of the third target rescue mission based on the resource requirement array; Determine, according to the resource requirement information of the third target rescue mission, a dispatchable rescue team that can provide the required resources for the third target rescue mission, and obtain a third rescue team set; The rescue distances from each dispatchable rescue team in the third rescue team set to the third target rescue mission are determined based on the rescue distance array, and the rescue team corresponding to the shortest rescue distance is determined as the third target rescue team.

8. A task scheduling device, characterized in that: include: A rescue information acquisition module is used to receive task dispatch instructions and acquire rescue request information of all accident points, wherein the rescue request information includes rescue location information, emergency level, and resource demand information of each accident point; A location information determination module is used to determine all dispatchable rescue teams and obtain the location information of each dispatchable rescue team; A rescue distance calculation module, used to calculate the rescue distance between each accident point and each dispatchable rescue team based on the rescue location information of each accident point and the location information of each dispatchable rescue team; A first array building module, used to build a rescue distance array based on the rescue distances between each accident point and each dispatchable rescue team; A second array construction module, used to quantify the emergency level and the resource requirement information, and construct an emergency level array and a resource requirement array; The rescue task scheduling module is used to schedule tasks for each of the dispatchable rescue teams according to the rescue distance array, the emergency level array and the resource demand array, using a pre-configured greedy scheduling strategy.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the task scheduling method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the task scheduling method according to any one of claims 1 to 7 are implemented.

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