Task merging and distributing method and device, equipment and medium

Abstract

The invention relates to the technical field of data processing, can be applied to business scenes of medical health, financial science and technology and the like, and discloses a task merging and distributing method which comprises the following steps: creating and storing task information, acquiring a corresponding active task set, matching an object identifier, extracting a terminal equipment identifier, and extracting and sending the task information, and updating the task state after receiving the task confirmation information, screening and combining the tasks when the task confirmation information is not confirmed, generating a composite task unit, and issuing the composite task unit to a task execution end according to a preset strategy. According to the method, the tasks are screened and matched on the basis of the geographic region identifiers and the object identifiers, so that repeated pushing of the tasks in the same region and the same object is effectively reduced, and the task allocation accuracy is improved; in combination with the task state information and the terminal equipment identifier, the task receiving process is optimized, and the task execution efficiency is improved; through a task merging mechanism, the task execution cost is reduced, and in combination with a preset release strategy, task scheduling is more balanced, and the intelligent level of overall task management is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a method, apparatus, device, and storage medium for task merging and allocation. Background Art

[0002] In the financial field, especially in the financial leasing business, on-site inspection of equipment is an important link to ensure the actual arrival of leased assets and reduce business risks. Currently, leasing companies usually rely on on-site inspection methods to verify leased assets, mainly executed by crowdsourcing personnel. However, in the actual operation process, there are many problems with the existing task allocation methods. For example, multiple inspection tasks within the same geographical area are often randomly assigned to different crowdsourcing personnel, resulting in multiple crowdsourcing personnel performing tasks for the same customer in a short period of time, increasing task redundancy and operating costs. In addition, due to the lack of a reasonable scheduling mechanism in the task push method, some inspection tasks may not be claimed, while other tasks may be overly concentrated in the hands of specific personnel, affecting the balance of task execution and inspection quality.

[0003] In the field of healthcare, hospitals and medical institutions also face similar problems in the management of equipment inspections, remote medical examinations, and patient follow-up tasks. Regular maintenance and inspection of medical equipment usually require on-site inspection, and medical institutions will entrust third-party technical personnel to conduct equipment inspections. However, the existing task management methods often rely on fixed time schedules or manual assignments, lacking intelligent matching of task areas, equipment status, and personnel availability, resulting in different tasks in the same area being claimed by different executors, increasing the possibility of repeated scheduling. In addition, in the allocation of patient follow-up tasks, some patients may receive follow-up requests from different medical teams in a short period of time, while patients in some areas may not receive timely follow-up services, affecting the rational utilization of medical resources.

[0004] In the prior art, crowdsourcing task allocation mainly adopts a method based on personnel ability evaluation, that is, by evaluating factors such as the ability score and matching degree of crowdsourcing personnel to determine the task allocation method. However, this method mainly focuses on the ability of task executors and fails to effectively solve the problem of how to reasonably merge and push multiple tasks in the same geographical area or for the same object. For example, equipment inspection tasks in a certain area may be pushed to multiple crowdsourcing personnel simultaneously, resulting in repeated task execution, or the tasks may not be concentrated in the hands of suitable executors, affecting the execution efficiency. In addition, the time constraints, spatial distribution of tasks, and logical relationships between tasks are not effectively considered in the task allocation process, resulting in uneven allocation of task resources and affecting the overall efficiency of task scheduling. Summary of the Invention

[0005] The main object of the present invention is to provide a task merging and allocation method, device, equipment and storage medium, aiming to solve the technical problems that the existing task allocation method lacks comprehensive consideration of the matching relationship between geographical regions and objects, resulting in repeated task pushing, increased execution costs and unbalanced resource scheduling, and affecting the overall task execution efficiency.

[0006] To achieve the above object, the present invention provides a task merging and allocation method, including:

[0007] Create current task information including geographical region identification and object identification, and store the current task information in the task set to be allocated;

[0008] Obtain an active task set corresponding to the geographical region identification of the current task, where the active task set includes active task information in an execution state;

[0009] When there is active task information in the active task set that matches the object identification of the current task, extract the terminal device identifier from the matching active task information;

[0010] Extract the current task information from the task set to be allocated and send it to the terminal device corresponding to the terminal device identifier;

[0011] If the task reception confirmation information returned by the terminal device is received, add the current task information to the associated task list of the matching active task information;

[0012] If the task reception confirmation information returned by the terminal device is not received, screen out the task information to be merged that matches the geographical region identification and object identification of the current task information from the task set to be allocated;

[0013] Merge the current task information with the task information to be merged to generate a composite task unit;

[0014] Publish the composite task unit to the task execution terminal according to a preset publishing policy.

[0015] Furthermore, to achieve the above object, the present invention provides a task merging and allocation device, including:

[0016] A task creation module, configured to create current task information including geographical region identification and object identification, and store the current task information in the task set to be allocated;

[0017] An active task management module, configured to obtain an active task set corresponding to the geographical region identification of the current task, where the active task set includes active task information in an execution state;

[0018] A matching processing module, configured to extract a terminal device identifier from the matched active task information when there is active task information matching the current task object identifier in the active task set;

[0019] A task distribution module, configured to extract the current task information from the to-be-assigned task set and send it to the terminal device corresponding to the terminal device identifier;

[0020] A task confirmation module, configured to add the current task information to the associated task list of the matched active task information if a task reception confirmation message returned by the terminal device is received;

[0021] A task screening module, configured to screen out to-be-merged task information matching the geographical area identifier and object identifier of the current task information from the to-be-assigned task set if a task reception confirmation message returned by the terminal device is not received;

[0022] A task merging module, configured to merge the current task information and the to-be-merged task information to generate a composite task unit;

[0023] A task publishing module, configured to publish the composite task unit to a task execution terminal according to a preset publishing policy.

[0024] Further, to achieve the above object, the present invention further provides a computer device, where the computer device includes a memory, a processor, and a task merging and distribution program stored on the memory and executable on the processor. When the task merging and distribution program is executed by the processor, the steps of the task merging and distribution method as described above are implemented.

[0025] Further, to achieve the above object, the present invention further provides a computer-readable storage medium, where a task merging and distribution program is stored on the storage medium. When the task merging and distribution program is executed by a processor, the steps of the task merging and distribution method as described above are implemented.

[0026] Beneficial Effects: The present invention relates to the technical field of data processing and can be applied to business scenarios such as medical health and fintech. It discloses a task merging and allocation method, including: creating current task information containing geographical area identifiers and object identifiers and storing it in the task set to be allocated; obtaining the active task set corresponding to the current task geographical area identifier; matching object identifiers in the active task set and extracting terminal device identifiers; extracting the current task information from the task set to be allocated and sending it to the terminal device; receiving task receipt confirmation information and adding the current task information to the associated task list of the matching active task information; when the task receipt confirmation information is not received, screening for matching task information from the task set to be allocated; merging the current task information and the task information to be merged to generate a composite task unit; and publishing the composite task unit to the task execution end according to a preset publishing strategy. By screening and matching tasks based on geographical area identifiers and object identifiers, the present invention effectively reduces the repeated push of tasks for the same area and the same object, improves the accuracy of task allocation; combines task status information and terminal device identifiers to optimize the task receiving process and improve task execution efficiency; reduces task execution costs through a task merging mechanism, and combines a preset publishing strategy to make task scheduling more balanced and improve the overall intelligent level of task management. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The following will further illustrate the present invention in conjunction with the drawings. In the drawings:

[0028] Figure 1 It is a schematic diagram of an application environment of the task merging and allocation method in an embodiment of the present invention;

[0029] Figure 2 It is a schematic flowchart of an embodiment of the task merging and allocation method of the present invention;

[0030] Figure 3 It is a schematic diagram of the functional modules of a preferred embodiment of the task merging and allocation device of the present invention;

[0031] Figure 4 It is a schematic diagram of the structure of a computer device in an embodiment of the present invention;

[0032] Figure 5 It is another schematic diagram of the structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0034] The task merging and allocation method provided by the embodiments of the present invention can be applied in, for example Figure 1In the application environment, the client communicates with the server through the network. The server can create current task information including a geographical area identifier and an object identifier through the client, and store it in the task set to be assigned; obtain an active task set corresponding to the geographical area identifier of the current task; match the object identifier in the active task set, and extract the terminal device identifier; extract the current task information from the task set to be assigned and send it to the terminal device; receive the task reception confirmation information, and add the current task information to the associated task list of the matched active task information; when the task reception confirmation information is not received, screen the matching task information from the task set to be assigned; merge the current task information with the task information to be merged to generate a composite task unit; and publish the composite task unit to the task execution end according to a preset publishing policy. The present invention effectively reduces the repeated push of tasks in the same area and for the same object by screening and matching tasks based on the geographical area identifier and the object identifier, improving the accuracy of task allocation; combines the task status information and the terminal device identifier to optimize the task reception process and improve the task execution efficiency; reduces the task execution cost through the task merging mechanism, and combines the preset publishing policy to make the task scheduling more balanced and improve the overall intelligent level of task management. Among them, the client can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of multiple servers. The present invention will be described in detail below through specific embodiments.

[0035] Please refer to Figure 2 , Figure 2 which is a schematic flowchart of an embodiment of the task merging and allocation method provided by the present invention. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described herein may be executed in a different order.

[0036] As Figure 2 shown, the task merging and allocation method proposed by the present invention includes the following steps:

[0037] S10, create current task information including a geographical area identifier and an object identifier, and store the current task information in the task set to be assigned;

[0038] In this embodiment, the process of creating task information needs to obtain the basic attributes of the task and perform standardization processing on the task data to facilitate subsequent matching and scheduling. The geographical area identifier and the object identifier are the core data of the task information, which are used to identify the execution scope and associated object of the task respectively.

[0039] The determination of geographical area identification involves multiple data processing steps. First, the task information may contain an address in natural language form, such as "No. 6A, Jianguomenwai Avenue, Chaoyang District, Beijing". This address needs to be parsed and converted into structured geographical coordinates. Geocoding technology can be used to map the natural language address to longitude and latitude coordinates, and at the same time, by querying the administrative division database, the administrative region code to which the task belongs can be determined, such as 110105 (Chaoyang District, Beijing). In some embodiments, the geographical area identification can also be optimized by combining historical task data. For example, tasks with multiple adjacent addresses can be merged into the same geographical area to reduce task dispersion and increase the possibility of task merging.

[0040] The object identification is used to identify the associated target of the task, such as an enterprise, an individual, or a device. For the financial business scenario, the leasing company needs to verify the identity of the lessee to whom the equipment belongs to prevent duplicate task allocation or false delivery of the equipment. Therefore, the corresponding enterprise code or the unique identification code of the equipment can be retrieved from the object database to ensure the uniqueness of the task object. In the healthcare scenario, the task object may be a medical device or a patient, and the system needs to extract the corresponding identification information from the equipment management system or the patient electronic medical record system to ensure the accurate matching of the task.

[0041] After the task information is created, it needs to be stored in the set of tasks to be assigned for subsequent scheduling. During the storage process, a structured data storage method can be adopted. For example, the task data can be stored in JSON format or a relational database to facilitate quick retrieval and query. In some cases, a task status marking mechanism can also be adopted to set an initial status for the task, such as "to be assigned", "high priority", etc., to enhance the flexibility of task scheduling.

[0042] The way of task creation can be adjusted according to different technical environments and application requirements. In the cloud architecture, a distributed storage system can be used to store the task data in the task management database, and at the same time, the task queue management system can be used to classify and store the tasks, such as partitioning according to geographical area, object category, etc., to optimize the task query efficiency. In the edge computing architecture, the task information can be first stored in the local cache and then synchronized to the central server when the task is scheduled, reducing the data transmission delay and improving the real-time performance of task allocation.

[0043] In some implementation manners, machine learning algorithms can be combined to automatically classify the task data. For example, based on the historical execution situation of the task, the execution priority of the task can be predicted, and a task priority label can be attached when the task is stored. This way can optimize task scheduling and improve the overall execution efficiency of the task.

[0044] The storage format of task data can also be adjusted according to actual requirements. For high-concurrency task scenarios, NoSQL databases such as MongoDB or Cassandra can be used to provide high-throughput task storage and query capabilities. For task management systems that require strong transactionality, relational databases such as MySQL or PostgreSQL can be adopted to ensure the consistency of task data.

[0045] In the medical and health scenario, additional consideration may be needed for the data compliance of tasks when creating tasks. For example, for medical device inspection tasks, information such as device models and maintenance records may need to be attached to ensure the integrity of inspection tasks. In the financial scenario, task information may involve sensitive data. Therefore, when storing tasks, encryption technology can be combined to encrypt the task data to ensure the security of task data.

[0046] Example illustration: In the medical and health field, a hospital needs to conduct regular inspections of equipment. When creating a task, the system extracts the unique identification code of the equipment from the equipment management system and obtains the geographical area code of the equipment through the hospital's geographical information system. When storing task information, the system attaches information such as inspection time windows and equipment types to each task for subsequent assignment to suitable technicians. In the scenario of high-priority inspection tasks, the system can mark the task as "urgent" and trigger task scheduling immediately after the task is stored to improve the task response speed.

[0047] In the financial field, a leasing company needs to conduct an inspection on the arrival of equipment. When creating a task, the system extracts lessee information from the lease contract system and obtains the expected arrival location of the equipment from the logistics system. When storing the task, the system automatically assigns a priority to the task based on the equipment type and the lessee's credit rating, and encrypts the task data to prevent data leakage. When scheduling tasks, the system performs intelligent matching based on task priorities and geographical regions to improve the inspection efficiency.

[0048] Through the creation and storage of task information, with standardized geographical area identification and object identification, the standardization of task data is improved, making task scheduling more accurate. The task storage adopts a structured method, improving the efficiency of task query and matching. By introducing a task status management mechanism, task scheduling becomes more flexible and supports different task priority management. For high-concurrency or distributed task systems, the task processing capacity of the system is improved by optimizing the storage format and database selection. In addition, in task scenarios involving sensitive information, data security is enhanced through encrypted storage methods.

[0049] S20, obtain an active task set corresponding to the geographical area identifier of the current task, where the active task set contains active task information in an execution state;

[0050] In this embodiment, the process of obtaining the set of active tasks corresponding to the geographical area identifier of the current task involves multiple links such as task screening, spatial matching, and status detection, so as to ensure that the current task can be associated with the existing executed tasks, improve the rationality of task scheduling, and reduce duplicate task allocation.

[0051] First, it is necessary to determine the geographical area identifier of the current task. The geographical area identifier is used to define the spatial scope of the task and can be represented in ways such as administrative division codes, geographical coordinate ranges, and electronic fences. For example, in urban-level task management, the geographical area identifier can use administrative division codes (such as "110105" representing Chaoyang District, Beijing), and in more refined spatial management, the specific execution scope of the task can be determined using longitude and latitude coordinate ranges. In addition, to improve the accuracy of task matching, based on the geographical area identifier, the detailed location information of the task can be combined, such as the specific building or industrial park code, to further refine the geographical attribution of the task.

[0052] When obtaining the set of active tasks, it is necessary to retrieve all currently executing tasks from the execution task database or the task management system. Task status management can be implemented based on status codes. For example: Pending; InProgress; Completed; Failed; Expired.

[0053] Only tasks marked as "InProgress" belong to the set of active tasks. The task status can be stored in the task management database, and the data structure of each task includes information such as task ID, task status, geographical area identifier, and execution terminal identifier. In some embodiments, a task timeout mechanism can be set to recycle tasks that have not updated their status for a long time to prevent expired tasks from affecting the accuracy of the set of active tasks.

[0054] In the process of obtaining the set of active tasks, it is also necessary to combine spatial matching technology to ensure that the geographical area identifier of the task is consistent with the execution scope of the active task. Spatial indexes (such as R-tree, Quad-tree) can be used to accelerate geographical area matching and improve query efficiency. For the case where the task execution terminal is in a mobile scenario, such as mobile medical device inspection or on-site patrol tasks, the system can dynamically update the geographical area identifier of the task based on real-time location information to ensure the accuracy of matching tasks.

[0055] After obtaining the set of active tasks, the tasks can also be classified and aggregated, for example, grouped according to task type, priority, or task object, in order to optimize task scheduling. For example, in equipment inspection tasks, tasks of the same equipment model can be grouped together and preferentially pushed to the execution terminals familiar with the equipment.

[0056] The way to obtain the set of active tasks can be adjusted according to different technical architectures. For example, in a distributed task management system, distributed query technology can be adopted to retrieve active tasks in parallel among multiple task storage nodes to improve query efficiency. Under the cloud computing architecture, a cloud database or a caching system (such as Redis) can be used to store the active task list, and indexing can be used to accelerate the query to reduce the latency of task filtering.

[0057] In some implementation methods, a real-time task tracking system can be combined to dynamically update the task execution status. For example, in a crowdsourcing task management system, each execution terminal can regularly upload task status data, and the system can judge whether the task is still in the execution state based on the time of the most recent status update. For tasks with dynamic updates, a data synchronization policy can be set, such as incremental update or full synchronization, to ensure the real-time nature of task data.

[0058] For certain specific industries, such as financial equipment inspection, the task execution logs can be combined to analyze the task completion situation of the execution terminals to optimize the task filtering method. For example, if a certain execution terminal has recently completed tasks for the same object, the task status can be preferentially obtained from this terminal to reduce unnecessary data queries.

[0059] In the medical and health scenario, the maintenance tasks of hospital equipment are usually responsible for by multiple execution teams. When obtaining active tasks, they can be classified and filtered according to departments, equipment types, and urgency levels. For example, for the maintenance tasks of CT machines or MRI equipment, they can be filtered according to the departments to which the equipment belongs to ensure that the tasks are assigned to the appropriate execution teams.

[0060] In the transportation and logistics scenario, when obtaining active tasks, a GPS real-time positioning system can be combined to filter the nearest execution terminals. For example, for a certain cargo inspection task that needs to be carried out in a certain highway service area, the system can obtain all the active tasks in this service area to ensure that the tasks are pushed to the nearest executors to improve the efficiency of task execution.

[0061] The process of obtaining the set of active tasks improves the accuracy of task filtering, reduces the execution of duplicate tasks, and reduces the resource consumption of task scheduling through task status management, spatial matching, and task classification optimization. Combining real-time task tracking and distributed query optimization makes the acquisition of task data more efficient and improves the response speed of task allocation. In scenarios such as medical, financial, and logistics, optimizing the active task filtering mechanism can reduce task conflicts, improve task execution efficiency, and enhance the intelligent level of task management.

[0062] S30. When there is active task information in the active task set that matches the current task object identifier, extract the terminal device identifier from the matching active task information;

[0063] In this embodiment, during the task allocation process, it is necessary to ensure that the current task has the same object identifier as the tasks in the active task set, so as to facilitate the reasonable scheduling of task execution, reduce duplicate task allocation, and improve task execution efficiency. The object identifier is usually the associated target of the task, such as an enterprise, a device, an individual, an account, etc., and its function is to limit the task within a specific object range. For example, in the financial business, the object identifier may be the unique number of the leased device, and in the field of medical and health, the object identifier may be the patient ID or the medical device ID.

[0064] After determining the active task set, object matching needs to be performed. The matching method can be exact matching or fuzzy matching:

[0065] Exact matching: The object identifier of the current task must be exactly the same as the object identifier of a certain task in the active task set, such as the unique ID matching in the database.

[0066] Fuzzy matching: When the task involves multiple related objects, matching can be performed based on business rules, such as matching the same organization name, the same address, or the same customer group.

[0067] After successful matching, it is necessary to extract the terminal device identifier from the matching active task information. The terminal device identifier is used to indicate which execution terminal is executing the task, and it can usually be: the unique device identifier (such as the MAC address, IMEI number); the user ID of the execution terminal (such as the crowdsourcing personnel number, enterprise account ID); the registration ID of the task execution system (such as the registration identifier of the IoT device).

[0068] In some cases, multiple terminal devices may jointly execute the tasks of the same object. At this time, the most suitable terminal device can be determined through a priority policy:

[0069] Priority based on the most recent update time: Select the terminal device that has updated the task status most recently to ensure the timeliness of the data;

[0070] Priority based on historical task execution records: Give priority to selecting the terminal device that has previously executed the same type of task to improve execution coherence;

[0071] Priority based on device capabilities: If the task has special requirements for device computing capabilities, network conditions, etc., the terminal device that meets the conditions can be selected preferentially.

[0072] After extracting the terminal device identifier, the current task can be directly associated with the terminal device to ensure more accurate task allocation.

[0073] In different technical environments, the methods for extracting terminal device identifiers can vary. In a cloud computing architecture, active task information can be stored in a distributed database or a caching system (such as Redis). The system can quickly match object identifiers through index queries and obtain the corresponding terminal device identifiers. For example, in a task management database, each active task may have the following structure:

[0074] Task ID: T12345;

[0075] Object identifier: device_0001;

[0076] Execution status: In execution;

[0077] Terminal device identifier: D56789.

[0078] When a new task arrives, the system can query the database. If it finds a task with the same object identifier, it can extract its terminal device identifier.

[0079] In an edge computing architecture, active task data can be stored in local gateway devices, and task matching can be performed at the edge to reduce the computing burden on the cloud. For example, in an intelligent inspection system, each inspection robot can store information about the tasks it has executed. When a new inspection task is issued, the system can directly retrieve the task status from nearby robots and extract the corresponding terminal device identifiers.

[0080] In the field of healthcare, a hospital's equipment maintenance management system can store inspection tasks for each device. When a new equipment inspection task is created, the system can query the engineer terminals that are currently performing the same equipment maintenance tasks and extract their device identifiers, and push the tasks to the same execution terminals to reduce changes in task executors and improve the coherence of maintenance work.

[0081] In the financial field, lease equipment survey tasks usually involve multiple inspection links, such as equipment delivery surveys and equipment operation status monitoring. The system can query the list of tasks being executed for the current leased equipment, determine whether there are already tasks in progress, and extract the execution terminal identifiers to ensure that new tasks are preferentially pushed to the currently executing terminals, reduce duplicate surveys, and improve task efficiency.

[0082] By matching object identifiers to extract terminal device identifiers, tasks can be reasonably assigned to terminal devices that already have tasks in progress, reducing duplicate task assignments and improving the coherence and accuracy of task execution. Optimizing the selection of terminal devices in combination with task execution records, device capabilities, and real-time status can improve task execution efficiency, reduce resource waste, and ensure the timeliness of tasks.

[0083] S40. Extract the current task information from the set of tasks to be assigned and send it to the terminal device corresponding to the terminal device identifier.

[0084] In this embodiment, during the task assignment process, it is necessary to extract the current task information from the set of tasks to be assigned and send it to the matching terminal device to ensure that the task can be accurately assigned to the appropriate execution terminal. This process involves multiple technical aspects such as task extraction, data encoding, and transmission strategies to ensure the integrity of the task, the efficient transmission of data, and the adaptability of the execution terminal.

[0085] First of all, task extraction is a key link to ensure the correct scheduling of task information. The set of tasks to be assigned is usually stored in a task management database or a task queue system. Each task contains information such as task ID, geographical area identifier, object identifier, task status, and task execution requirements. The task extraction method can be based on index query or task scheduling algorithm:

[0086] Index query method: Based on the task ID or object identifier, quickly search for the tasks to be assigned in the task database.

[0087] Task scheduling algorithm: If the task queue is large, a task priority scheduling algorithm can be used to select the most suitable task for extraction according to parameters such as the urgency of the task and the historical completion rate.

[0088] After task extraction, it is necessary to encode the task data to optimize the data transmission efficiency. Since the computing capabilities and network conditions of terminal devices are different, different task data encoding strategies can be adopted for different devices:

[0089] Standard JSON or XML format: Suitable for high-performance execution terminals, directly transmit the complete task data structure.

[0090] Compressed encoding (such as Protocol Buffers, MessagePack): Suitable for low-bandwidth network environments, reduce the size of data packets, and improve the task transmission rate.

[0091] Incremental data synchronization: If the task information is large, only the changed data, such as task update fields, can be transmitted to reduce the transmission overhead.

[0092] After the task data is prepared, it is necessary to detect the network status of the terminal device to select a suitable task transmission method. For example, the following two methods can be adopted:

[0093] Real-time streaming transmission: If the network signal strength of the terminal device is higher than the preset threshold, directly push the task through protocols such as TCP / WebSocket to ensure that the task data can reach the terminal with low latency.

[0094] Chunked asynchronous transmission: If the network signal of the terminal device is weak or unstable, a chunked transmission strategy is adopted. For example, based on protocols such as MQTT and HTTP long connection, the task data is split into multiple small chunks for resume - interrupted transfer, ensuring that the task data will not be lost due to network interruption.

[0095] After the task data is sent, the terminal device needs to return a task - received confirmation message to ensure the successful allocation of the task. If the terminal does not confirm the task reception within the specified time, the task retry mechanism can be triggered or other terminals can be re - selected for task allocation.

[0096] By extracting tasks from the task set to be allocated and sending them to the terminal device, the task allocation is made more accurate, reducing the redundant transmission of task data and improving the real - time performance of task scheduling. Combining technical means such as data compression, chunked transmission, and network adaptation can improve the transmission efficiency of tasks and ensure that task data can still be reliably delivered in a complex network environment. Through the task - received confirmation mechanism, the system can ensure the successful distribution of tasks, improve the stability of task execution, and effectively enhance the intelligent level of task allocation in task management scenarios in industries such as healthcare and finance.

[0097] S50, if the task - received confirmation message returned by the terminal device is received, add the current task information to the associated task list of the matched active task information;

[0098] In this embodiment, when the terminal device successfully receives the task information, it needs to return a task - received confirmation message to the task management system to ensure the successful allocation of the task and trigger subsequent task status updates and scheduling optimizations. The task - received confirmation message usually contains content such as task identification, terminal device identification, reception timestamp, network status, and the current load condition of the device. These data can be used to further optimize task management, improve the reliability of the system, and the coherence of task execution.

[0099] After receiving the task acceptance confirmation information returned by the terminal device, the task management system needs to associate the current task information with the matched active task information and add the task to the associated task list of the active task information. The associated task list is used to maintain the task dependency relationship and status management during the task execution process. For example, when there are multiple tasks running simultaneously in the same area or on the same object, the system can ensure that these tasks are not executed repeatedly through the associated task list, avoiding resource waste; in some task scenarios, tasks may need to be executed according to the dependency relationship. For example, in the equipment inspection task, the basic inspection task may need to be completed first, and then the function test task can be carried out. The task association mechanism can ensure that tasks are executed in a reasonable order; task association can also be used to record the execution history. For example, when the execution of a task fails or needs to be reassigned, the system can find the historical execution situation of related tasks from the associated task list, avoiding reassigning them to the same execution terminal and improving the task scheduling efficiency.

[0100] When the task management system adds the task information to the associated task list of the active task information, it usually performs the following key operations:

[0101] Task status update: The system needs to modify the status of the current task from "to be assigned" to "in execution" and record the latest assignment time of the task. For a distributed task management system, a transaction processing mechanism can be adopted to ensure the atomicity of task status update and avoid inconsistent status caused by network exceptions.

[0102] Data storage and synchronization: Task data is usually stored in a database or a cache system to support high-concurrency task queries. In high-frequency task assignment scenarios, high-performance cache systems such as Redis can be used to reduce the database query pressure and improve the reading speed of task data. At the same time, the task management system can synchronize the task status to the persistent storage regularly to ensure the integrity of task data.

[0103] Task dependency relationship management: There may be execution dependency relationships between tasks. For example, some tasks must complete the prerequisite tasks before they can continue to execute. When the system adds a task to the associated task list of the active task information, it can check the task dependency relationship to ensure that tasks are executed in the correct order. The dependency relationship can be managed in the form of a DAG (Directed Acyclic Graph) to ensure the rationality of task execution.

[0104] Task log recording: The task management system needs to record the changes in task status, including information such as task assignment time, task reception time, and the load situation of the execution terminal. These log data can be used in scenarios such as task optimization, fault diagnosis, and execution efficiency analysis to improve the stability and intelligent scheduling ability of the system.

[0105] After the task is added to the associated task list of the active task information, the task management system can also dynamically adjust the task allocation strategy according to factors such as the historical task records of the execution terminal and the current task load of the execution. For example, if the current task load of a certain execution terminal is too high, the system can delay or re-allocate new tasks to ensure the balance of task execution.

[0106] In addition, the task management system can also combine artificial intelligence and machine learning models to perform pattern analysis on task reception situations. For example: predicting the task reception rate and optimizing the task push strategy according to historical task data; analyzing the task completion efficiency of different terminal devices and dynamically adjusting the task scheduling rules; combining the Geographic Information System (GIS) to analyze the spatial distribution of tasks, optimizing the task allocation scope, and improving the task coverage rate of the execution terminal.

[0107] By adding task information to the associated task list of the active task information, the task execution process can be made traceable, ensuring the consistency of task data between the execution end and the management end. Combining technical means such as task status management, task storage optimization, and intelligent scheduling, the accuracy of task allocation is improved, resource waste is reduced, and the task execution efficiency is optimized. Through task log recording and real-time monitoring mechanisms, the visualization management ability of tasks is enhanced, and combined with load balancing and intelligent matching algorithms, the fairness and intelligent level of task scheduling are improved.

[0108] S60, if the task reception confirmation information returned by the terminal device is not received, filter out the pending merge task information that matches the geographical area identifier and object identifier of the current task information from the set of tasks to be allocated;

[0109] In this embodiment, when the task management system does not receive the task reception confirmation information returned by the terminal device within the specified time, the system needs to re-evaluate the task allocation situation to ensure that the task will not be lost or not executed for a long time due to terminal device anomalies or communication failures. At this time, the system will filter out the pending merge task information that matches the geographical area identifier and object identifier of the current task information from the set of tasks to be allocated, in order to optimize the task allocation and improve the task execution efficiency.

[0110] To ensure the stable execution of tasks, the system will set a timeout for task reception confirmation, such as 5 seconds, 10 seconds, or a longer time limit. If the terminal device does not return the task reception confirmation information within the timeout period, the system will consider the task allocation to have failed and enter the task merging and re-allocation process. Task confirmation timeouts may be caused by the following reasons:

[0111] Unstable network: The terminal device is in a weak signal or disconnected state, resulting in the failure to transmit the task reception confirmation information in a timely manner.

[0112] Terminal device failure: The device runs out of power, has hardware damage, or the application crashes, resulting in the task being unable to be received normally.

[0113] Task processing conflict: The current task queue of the terminal device is full and cannot receive new tasks.

[0114] Executor rejects the task: In some cases, the executor may not accept the task due to reasons such as task difficulty and time conflict, but does not actively return a rejection message.

[0115] To improve the coherence and efficiency of task execution, after the task assignment fails, the system needs to screen eligible task information from the set of tasks to be assigned for merging and then re-pushing. When screening tasks, it is necessary to match the geographical area identifier and the object identifier to ensure that the new tasks can be reasonably assigned.

[0116] Geographical area identifier matching means that the tasks need to be within the same geographical area range. For example: when the administrative division code (such as 110105 in Chaoyang District, Beijing) is the same, the tasks can be merged; when the geographical coordinate range (such as the area enclosed by the GPS coordinates) overlaps, the tasks can be merged; when the electronic fence (such as the business scope of a hospital, factory, or financial institution) is the same, the tasks can be merged.

[0117] Geofencing is a location-based virtual boundary technology that allows the system to perform specific operations on devices, users, or tasks within a specified physical range. Geofencing usually relies on technologies such as GPS, Wi-Fi, Bluetooth, and cellular networks for positioning, and combines with a Geographic Information System (GIS) or a geographical coordinate database to create a dynamic or static geographical area for monitoring the entry and exit status, location changes, and task triggering of objects.

[0118] In a task assignment system, geofencing can be used to define the applicable scope of tasks, ensuring that tasks are only assigned to execution terminals located in a specific area and preventing problems such as incorrect task assignment or location mismatch. For example: in equipment inspection tasks, geofencing can ensure that tasks are only assigned to inspectors located in a certain factory, computer room, or office building, preventing inspectors from accepting tasks when they are not at the location of the equipment; in financial risk control, banks can set up geofencing for the verification tasks of equipment financial leasing to ensure that the surveyors complete the tasks near the actual location of the leased equipment and prevent the submission of false survey reports remotely; in healthcare, a remote healthcare system can create a geofencing for a certain ward or home care area to ensure that nurses or doctors must be in the patient's area to complete the care records.

[0119] Geofencing can be classified into the following types according to the application scenario and technical requirements:

[0120] (1) Static Geofence

[0121] The static geofence is created based on preset geographical coordinates and is applicable to task management in fixed locations such as hospitals, factories, office areas, airports, etc. The task management system can set the boundary of a hospital (such as Peking Union Medical College Hospital). When a medical task needs to be executed, the system will detect whether the doctor's or nurse's device is within the fence to ensure that the task can only be executed within the hospital. Logistics companies can set the fence for a warehouse. When goods arrive at or leave the designated warehouse, the system automatically records and triggers subsequent tasks such as inspection and warehousing operations.

[0122] (2) Dynamic Geofence

[0123] The dynamic geofence is a fence adjusted based on real-time location information and is applicable to task management that requires flexible adjustment, such as mobile device survey, patrol tasks, shared bicycle management, etc. In equipment rental survey, the system can create a dynamic fence based on the real-time GPS location of the equipment to ensure that the surveyor must be close to the equipment location to execute the task and prevent remote submission of false reports. In the financial risk control scenario, banks can set location restrictions for loan applicants when submitting documents to ensure that applicants complete identity verification within the bank business hall and cannot submit false materials at other locations.

[0124] (3) Multi-Level Geofence

[0125] The multi-level geofence is applicable to scenarios where task execution requires step-by-step verification, such as high-security areas, medical and health tasks, etc. At airports or customs, the geofence can be set to multiple levels: the first level (public area), the second level (security check area), the third level (boarding gate area) to ensure that tasks are executed in the appropriate area and prevent unauthorized task access. In the financial industry, banks can set different levels of geofences for loan approval. For example, the preliminary review task can be completed in the business hall, while high-risk approvals must be executed in the designated area of the headquarters to ensure data security and risk control.

[0126] The implementation of an electronic fence relies on multiple positioning technologies and is applicable to task management in different scenarios. Among them, GPS electronic fences are suitable for large-scale outdoor tasks such as inspections, cargo transportation, and financial surveys. The task management system can create a virtual boundary of a specific range based on geographical coordinates and compare the GPS positioning data of the terminal device to determine whether the task is executed within the specified area. For example, in the equipment rental survey task, the surveyor needs to complete the task within 500 meters of the equipment location; otherwise, the system will not update the task status. In addition, in freight monitoring, the electronic fence can ensure that the driver travels along the specified route and avoids detours or illegal parking.

[0127] In an indoor environment, Wi-Fi and Bluetooth electronic fences are more applicable. The Wi-Fi electronic fence confirms whether the terminal device is in the specified area through the MAC address or signal strength (RSSI) of the wireless access point (AP), such as in scenarios like hospital wards, shopping malls, and bank branches. For example, a hospital can restrict nurses' devices to connect to the hospital Wi-Fi to perform nursing tasks to prevent the submission of false records remotely. The Bluetooth electronic fence is suitable for more precise short-distance management, such as in medical operating rooms or financial vault management. The system can deploy BLE beacons in a specific area, and only devices that detect a legal Bluetooth signal can perform corresponding operations, such as doctors signing electronic medical records or bank security personnel querying vault data.

[0128] For larger-scale task management, cellular network electronic fences rely on base station positioning to monitor task execution. This method is suitable for tasks such as national-wide inspections and insurance on-site surveys, ensuring that the executors complete operations within the specified area. For example, an insurance company can require that the surveyor's device must be within the base station coverage area of the accident scene to submit a survey report, preventing the remote submission of false survey information. At the same time, financial institutions can use base station positioning to restrict borrowers to complete loan approval operations only within bank business halls, thereby reducing the risk of cross-regional fraud.

[0129] Object identifier matching means that tasks involve the same task object. For example: in the equipment inspection task, multiple inspection tasks of the same equipment can be merged; in the medical detection task, multiple health data collection tasks of the same patient can be merged; in the financial field, loan approval and credit check tasks of the same customer can be merged.

[0130] When screening task information to be merged, strategies such as index query or task priority matching can be adopted to improve query efficiency. For example:

[0131] Index query: The system can use database indexes (such as B+ trees, hash indexes) to quickly find tasks that match geographical area identifiers and object identifiers, improving the matching speed.

[0132] Task priority matching: If multiple tasks to be merged meet the criteria, the most suitable task for merging can be preferentially selected based on factors such as the urgency of the task, historical completion rate, importance score, etc.

[0133] By screening the task information to be merged after the task reception fails, the system can avoid task loss caused by factors such as equipment failures and network problems, and at the same time improve the task execution efficiency. The task merging mechanism enables multiple related tasks to be pushed to the execution terminal at one time, reducing the repeated distribution of tasks and improving resource utilization. Combining technical means such as geographical area matching, object matching, and priority scheduling, the task scheduling becomes more intelligent. In the fields of medical health, financial management, equipment inspection, etc., it can effectively improve the task execution success rate and enhance the stability and flexibility of the task management system.

[0134] S70, merge the current task information with the task information to be merged to generate a composite task unit;

[0135] In this embodiment, in the task management system, in order to improve the task execution efficiency and reduce the resource consumption of repeated dispatching, tasks need to be merged to form a composite task unit. When the task management system detects that a certain task fails to be successfully received or confirmed by the terminal device, it will screen out the tasks that match the current task information from the set of tasks to be assigned, ensuring that these tasks have a high degree of consistency in geographical area and object identification. Geographical area identification matching is the core condition for task merging. For example, in the equipment inspection task, the equipment maintenance tasks within the same industrial park can be merged, while the tasks in different regions cannot be merged. Similarly, object identification matching ensures that the merged tasks belong to the same customer or device. For example, in the financial survey task, it is necessary to confirm that multiple audit tasks at the same bank branch belong to the same customer before they can be merged and executed.

[0136] During the task merging process, the system will calculate the overlap degree of the task time window and screen out tasks with similar times for merging. For example, in the medical health task management, if the blood pressure monitoring and blood glucose detection of a patient are arranged in similar time periods, they can be merged into a composite task unit, reducing the patient's waiting time and improving the task execution efficiency. Task type similarity is also a key factor in task merging. The system will preferentially merge tasks of the same type, such as credit audit tasks at multiple bank branches or equipment repair tasks at different locations, to reduce the task switching cost of the execution terminal. In addition, task priority also needs to be considered during task merging to ensure that high-priority tasks are not delayed by low-priority tasks due to merging.

[0137] After task merging, the system creates composite task units and sets the time window for task execution. To optimize the task execution path, the system can adopt an intelligent task grouping strategy, such as clustering tasks based on task category, time distribution, or geographical location, to make the execution of task units more efficient. At the same time, the task system will detect the spatial rationality of tasks to ensure that the execution terminals of task units will not lead to a decline in execution efficiency due to an overly large task scope. For example, in the task of inspecting leased equipment in the financial field, after task merging, the geographical distribution of the equipment needs to be considered to ensure that the executors can complete all tasks within a reasonable time without affecting work efficiency due to an overly large regional span.

[0138] After the creation of task units is completed, the system stores them in the task queue and marks them as in a pending execution state. The dispatching priority of task units depends on the status of the terminal device. If the original execution terminal of the task is still available, it will be preferentially pushed to the original terminal device. If the original terminal device is unavailable due to network failure, device problems, or other reasons, the system will reselect the optimal execution terminal for dispatching to ensure the smooth execution of tasks. In the medical and health scenario, if a nurse's terminal device fails to receive ward care tasks, the system will automatically assign the tasks to other nurses to ensure that the care tasks will not be delayed due to device problems. In the financial scenario, if a bank credit review task cannot be dispatched to the original reviewer due to network problems, the task system will reselect an available reviewer to execute the task to ensure the continuity of the business process.

[0139] By merging and matching tasks to form composite task units, the task management system can optimize the task allocation process, improve task execution efficiency, and reduce resource waste caused by repeated dispatching. This mechanism has wide application value in multiple fields such as medical and health, financial inspection, and equipment patrol, improving the intelligence level of task execution, optimizing the task allocation of executors at the same time, and enhancing the overall efficiency of task management.

[0140] By merging task information, composite task units are generated, making task scheduling more efficient, reducing the increased execution costs caused by fragmented task allocation, and improving the utilization rate of task execution terminals. Task merging optimizes the execution path, enabling the execution terminal to complete multiple related tasks in a shorter time, reducing unnecessary repeated dispatch, and improving execution efficiency. In the field of medical and health, merging multiple health monitoring tasks of patients can reduce waste of medical resources and improve the continuity and accuracy of nursing work; in the field of financial survey, merging multiple review tasks of the same customer can reduce the repetitive work of surveyors, improve review efficiency, and ensure the coherence of business processes. In the scenario of equipment inspection, merging equipment inspection tasks in the same area can optimize the inspection route, reduce the movement cost of the execution terminal, and improve inspection efficiency. The task management system achieves precise merging through geographical matching, time analysis, and task type screening, improving the overall efficiency of task execution, while ensuring the flexibility of task allocation, making task scheduling more intelligent and efficient.

[0141] S80, publish the composite task unit to the task execution terminal according to a preset publishing strategy.

[0142] In this embodiment, after the task information is merged, it is necessary to push the composite task unit to a suitable execution terminal according to a preset publishing strategy to ensure the efficient execution of tasks. When the task management system publishes tasks, it needs to comprehensively consider factors such as the execution time window of the task, the status of the task execution terminal, historical task execution data, and geographical area distribution, etc., to optimize task scheduling, improve execution efficiency, and reduce resource waste caused by repeated task dispatch.

[0143] The strategy of task publishing depends on parameters such as the task load of the task execution terminal, device capabilities, network environment, etc., to ensure that tasks can be reasonably allocated to the most suitable execution terminal. For example, in the medical and health scenario, the scheduling, workload, and available time of different nurses need to be taken into account in task allocation to avoid task overload or resource idleness. In the financial risk control survey task, the system needs to consider the experience, workload of the surveyor, and the urgency of the survey task to reasonably schedule tasks and improve the efficiency of financial risk control.

[0144] In the specific task release process, the system will first calculate the number of subtasks of the task unit and the unified execution time window, and analyze the geographical area identifier of the task to ensure that the task is only pushed to the execution terminals covering this geographical range. When the number of subtasks of the task unit exceeds the set release scale threshold, the system will extract the historical task execution records of this area and analyze the suitable release time point based on the past execution data. For example, in the bank credit review task, the system can refer to the historical data to determine that the efficient execution period of the review task is from 9:00 to 11:00 on weekdays, and thus give priority to pushing the task within this time period to improve the task processing efficiency. In the equipment inspection task, if the historical data shows that the inspection work in a specific equipment area is usually completed in the morning, the system can give priority to arranging the inspection task to be pushed in the morning time period to ensure a reasonable work time arrangement for the execution terminals.

[0145] Before the task is finally pushed, the system will set an accurate release time point for the composite task unit according to the historical task execution data and task priority, and add the task to the task release queue to trigger the task push at the appropriate time. If the current time reaches the set release time point, the system will push the task to all online execution terminals within the coverage of the geographical area identifier of this task unit and ensure that the task can enter the execution state as soon as possible. To further optimize task dispatching, the system can adopt a dynamic task push strategy, and flexibly adjust the task release method according to the real-time status of the task execution terminals (such as device online status, network connection quality, current task load, etc.) to ensure the success rate of task push.

[0146] Example illustration: In fields such as medical health, financial survey, and equipment inspection, the intelligent allocation and efficient execution of tasks are crucial for optimizing work processes, reducing operating costs, and increasing the task completion rate. In the existing technology, task allocation usually adopts a method based on personnel ability scores, which is difficult to intelligently merge and accurately push tasks for the same geographical area and object, resulting in problems such as low task execution efficiency, waste of execution terminal resources, and increased duplicate dispatching.

[0147] In the medical and health scenario, hospitals need to arrange a large number of nursing tasks every day, including monitoring patients' vital signs, providing daily care, and following up on patients' conditions. The task management system first creates nursing task information. The system generates a geographical area identifier based on the ward number where the patient is located and uses the patient's medical record number as the object identifier to ensure that tasks can be accurately assigned to the corresponding ward area and patient. After the task information is created, the system stores it in the set of tasks to be assigned for subsequent task allocation. After the task storage is completed, the system obtains the set of active nursing tasks in the current ward and checks whether there are already ongoing nursing tasks in the ward. For example, if there is already a nurse A performing a nursing task in a certain ward, the system summarizes all the tasks in the execution status of this ward to avoid duplicate task allocation. If there is a task in the active task set that matches the current nursing task, such as nursing tasks for multiple patients in the same ward area, the system extracts the device identifier of nurse A and attempts to directly assign the new task to the device of this nurse. Subsequently, the system extracts the nursing task information from the set of tasks to be assigned and sends it to the mobile terminal of nurse A. After receiving the task push, the device of nurse A can choose to accept or reject the task. If nurse A accepts the task and sends a task acceptance confirmation message, the system adds this nursing task to the task execution list of nurse A to ensure that all tasks can be carried out according to the established nursing plan. If nurse A fails to receive the task due to being busy or other reasons, the system will screen for other nursing tasks in the set of tasks to be assigned that match the current task, such as nursing tasks for other patients during the same time period, to combine them into a composite task unit. The system combines the current nursing task with the other nursing tasks screened out to generate a composite task unit, ensuring that the nurse can complete multiple nursing tasks at one time, reducing repeated walking in the ward area, and improving nursing efficiency. After the tasks are combined, the system publishes the composite task unit according to the preset nursing work arrangement strategy to ensure that the nurse receives the merged task push at the appropriate time in the work schedule, thereby optimizing the scheduling of nursing resources and improving the continuity and accuracy of nursing work.

[0148] In the financial survey scenario, during the loan review and leased equipment management processes, banks need to conduct on-site surveys to ensure the actual existence of assets and reduce business risks. The task management system creates survey task information, generates a geographical area identifier based on the bank branch address, and uses the enterprise number of the loan applicant as the object identifier to ensure that the task can be correctly matched to the relevant enterprise or leased equipment. After the task information is created, the system stores it in the set of tasks to be assigned and waits for the task to be executed. After the task is stored, the system obtains the set of active survey tasks of the current bank branch and checks whether there is an ongoing survey task at this bank branch. For example, if surveyor B is already performing a loan assessment task at this branch, the system aggregates all the tasks with an execution status at this branch to avoid scattered task execution. If there is a task in the active task set that matches the current survey task, such as enterprise credit assessment and equipment lease verification belonging to the same customer, the system extracts the equipment identifier of surveyor B and attempts to directly push the new task to surveyor B's device. Subsequently, the system extracts this survey task from the set of tasks to be assigned and sends it to surveyor B's mobile terminal, waiting for surveyor B to confirm receipt. If surveyor B receives the task and confirms the task receipt, the system adds this task to surveyor B's task execution list to ensure that all relevant survey tasks are completed at this branch at one time. If surveyor B fails to receive the task due to work arrangements or time conflicts, the system filters out other survey tasks that match the current task from the set of tasks to be assigned, such as other business surveys of the same customer, to optimize the execution order of the survey work. The system merges the current task with the filtered relevant survey tasks to generate a composite task unit and adjusts the task execution time to ensure that the surveyor can efficiently complete multiple tasks and reduce unnecessary repeated visits. After the tasks are merged, the system publishes the composite task unit according to the banking business approval process to ensure that the surveyor receives the merged task within the optimal time window and dynamically adjusts the execution order of the survey tasks according to the task priority to improve the accuracy and timeliness of the survey work.

[0149] In the scenario of equipment patrol inspection, in environments such as factories, logistics warehouses, and intelligent transportation equipment, equipment patrol inspection tasks need to be carried out regularly to ensure the normal operation of equipment. The task management system creates equipment patrol inspection task information, generates a geographical area identifier based on the factory area or warehouse area location where the equipment is located, and uses the unique number of the equipment as the object identifier to ensure that the task can be correctly matched to the patrol inspection target. After the task is created, the system stores it in the set of tasks to be assigned, waiting for the patrol inspection personnel to execute. After the task is stored, the system obtains the set of active patrol inspection tasks in the current area and checks whether there is an ongoing patrol inspection task in this area. For example, if a patrol inspector C is already carrying out equipment patrol inspection tasks in this area, the system will summarize all the tasks in the execution status in this area to reduce the situation of repeated patrol inspections. If there is a task in the active task set that matches the current patrol inspection task, such as the maintenance tasks of multiple devices belonging to the same area, the system will extract the device identifier of patrol inspector C and try to directly push the new task to the device of patrol inspector C. Subsequently, the system extracts this patrol inspection task from the set of tasks to be assigned and sends it to the mobile terminal of patrol inspector C, waiting for the patrol inspector to receive the task. If patrol inspector C accepts the task and confirms the receipt, the system will add this patrol inspection task to the task execution list of patrol inspector C to ensure that all equipment patrol inspection tasks can be completed as planned. If patrol inspector C fails to receive the task due to equipment repair time delay or work arrangement, the system will screen the patrol inspection tasks that match the current task from the set of tasks to be assigned, such as the maintenance tasks of other devices in the same area, to optimize the patrol inspection path. The system merges the current task with the screened patrol inspection tasks to generate a composite task unit and adjusts the patrol inspection priority to ensure that the patrol inspector can efficiently complete multiple patrol inspection tasks. After the tasks are merged, the system releases the composite task unit according to the factory equipment maintenance plan to ensure that the patrol inspector receives the task push within the specified maintenance time window, improve the efficiency of equipment patrol inspection, and reduce the risk of equipment failures.

[0150] Through a preset release strategy based on the analysis of task execution time, execution terminal status, and historical data, the task push is made more accurate, the rationality of task allocation is improved, and the problem of uneven load on the execution terminals caused by random task distribution is reduced. The task management system can optimize the task release time point so that the task can be pushed in a suitable time period, improving the success rate of task execution. In fields such as medical health, financial survey, and equipment patrol inspection, this task release mechanism can ensure the efficient scheduling of tasks, improve the execution efficiency, and reduce the waste of execution resources caused by improper task allocation.

[0151] The present invention relates to the technical field of data processing and can be applied to business scenarios such as medical health and fintech. It discloses a task merging and allocation method, including: creating current task information containing geographical area identifiers and object identifiers, and storing it in the task set to be allocated; obtaining the active task set corresponding to the current task geographical area identifier; matching the object identifier in the active task set and extracting the terminal device identifier; extracting the current task information from the task set to be allocated and sending it to the terminal device; receiving the task reception confirmation information and adding the current task information to the associated task list of the matching active task information; when the task reception confirmation information is not received, screening the matching task information from the task set to be allocated; merging the current task information with the task information to be merged to generate a composite task unit; and publishing the composite task unit to the task execution end according to a preset publishing strategy. By screening and matching tasks based on geographical area identifiers and object identifiers, the present invention effectively reduces the repeated push of tasks in the same area and for the same object, improves the accuracy of task allocation; combines task status information and terminal device identifiers to optimize the task reception process and enhance the task execution efficiency; reduces the task execution cost through the task merging mechanism, and combines the preset publishing strategy to make the task scheduling more balanced and improve the overall intelligent level of task management.

[0152] In one embodiment, the above S10 includes:

[0153] S101, receiving the natural language address description and object identifier in the task creation request;

[0154] S102, converting the natural language address description into latitude and longitude coordinate data, querying the administrative division database according to the latitude and longitude coordinate data, and obtaining the corresponding standard geographical area identifier;

[0155] S103, verifying the effective status of the object identifier in the object information library to generate a validity verification result;

[0156] S104, when the validity verification result is valid, generating a task form template containing the standard geographical area identifier and the valid object identifier;

[0157] S105, filling the task type identifier and the scheduling verification time window field value in the task form template;

[0158] S106, binding the filled task form template with the task creation timestamp to generate structured current task information;

[0159] S107, writing the structured current task information into the unallocated task partition of the task set to be allocated according to a preset storage format.

[0160] In this embodiment, task creation is a core part of the task allocation process, ensuring that task information is complete, structured, and can be correctly identified and scheduled. First, the system receives a task creation request, which contains a natural language address description and an object identifier. The natural language address description may include street names, building names, or other geographical information, such as "No. 88 Jianguo Road, Chaoyang District, Beijing", and the object identifier is used to uniquely identify the task target, such as a patient number, enterprise number, or device number.

[0161] The task system needs to convert the natural language address into latitude and longitude coordinate data. This process relies on geocoding technologies, such as Google Maps API, Baidu Maps API, etc., to ensure that the address can be standardized and subsequent matching can be performed. The converted latitude and longitude coordinates are used to query the administrative division database to obtain the corresponding standard geographical area identifier. The standard geographical area identifier usually adopts national or industry standards, such as GB / T 2260 (Administrative Division Code), to ensure the consistency and identifiability of geographical information for task allocation.

[0162] The validity verification of the object identifier is an important step to ensure that the task does not point to an invalid target. The system needs to query the status of the object identifier in the object information library, determine whether it exists and is valid, and generate a validity verification result. For example, in a medical scenario, the patient's inpatient number needs to match the hospital information library; in a financial survey scenario, the enterprise number needs to match the industrial and commercial data; in an equipment inspection scenario, the equipment number needs to match the asset management system. If the object identifier is valid, the system will generate a task form template based on this information. The template contains information such as the standardized geographical area identifier and the object identifier.

[0163] The task form template needs to supplement necessary scheduling information, including the task type identifier and the value of the scheduling verification time window field. The task type identifier is used to distinguish task categories, such as "nursing task", "credit survey task", "inspection task", etc., and the value of the scheduling verification time window field is used to determine the earliest and latest execution times of the task to ensure that the task is executed within an appropriate time range. Subsequently, the system binds the filled task form template with the task creation timestamp to ensure that the task information contains a time attribute and supports the time management of task execution.

[0164] Finally, the system writes the structured task information into the unallocated task partition of the task set to be allocated according to a preset storage format, such as JSON, XML, or database storage format, to ensure that tasks can be quickly read and allocated during subsequent task scheduling.

[0165] In the medical and health scenario, when the hospital information system generates patient care tasks, doctors or nurses can input the ward area, bed number, or patient name through a mobile terminal. The system automatically parses the ward area address, such as "Bed No. 1, Surgical Ward, Peking Union Medical College Hospital, Beijing", and converts it into standardized longitude and latitude coordinates to ensure that the task can be accurately matched to the ward area. Subsequently, the system queries the patient's hospitalization number in the hospital information system (HIS) to confirm that the patient is in the hospital and still requires care tasks. When the confirmation information is valid, the system generates a care task template, attaches the task type "Patient Care", and a scheduling time window, such as 08:00 - 10:00. Finally, the system writes the structured care task into the unassigned task pool, waiting to be assigned to the nurse terminal later.

[0166] In the financial survey field, banks need to conduct on-site verification of the asset status of loan applicants. The credit manager inputs the registered address of the loan enterprise, such as "No. 958, Lujiazui Ring Road, Pudong New Area, Shanghai", in the survey management system. The system parses the address and queries the enterprise's industrial and commercial data to confirm that the enterprise still exists and its business status is normal. The system generates a credit survey task template, with the task type marked as "Credit Survey", and sets a survey time window according to bank regulations, such as 09:00 - 17:00. Subsequently, the task data is deposited into the unassigned task pool, waiting for the surveyor to receive the task.

[0167] In the equipment inspection scenario, the factory inspection system receives a request to create an inspection task, including the equipment number "EQP_45678" and the location of the equipment "Factory Building No. 1, Hangzhou High-Tech Development Zone". The system parses the address and converts it into longitude and latitude coordinates. At the same time, it queries the equipment number in the asset management database to confirm that the equipment status is "Running, requires inspection". The system generates an inspection task template, with the task type marked as "Equipment Inspection", and sets an inspection time window, such as 12:00 - 14:00. Finally, the task information is deposited into the unassigned task pool to ensure that the inspector receives the inspection task at the appropriate time.

[0168] This embodiment ensures that tasks can be accurately created and stored in the task pool through task information standardization, object identifier verification, and geographical area matching, avoiding task failures caused by address parsing errors, invalid object identifiers, etc. during the task creation process. At the same time, the addition of task types and time windows makes task management more intelligent, capable of adapting to different application scenarios, and improving the accuracy and controllability of task execution.

[0169] In one embodiment, the above S20 includes:

[0170] S201, obtaining a set of administrative region boundary coordinates corresponding to the current task geographical area identifier;

[0171] S202. Extract task information with all task status codes being the execution status from the execution task list;

[0172] S203. Traverse the task information with the execution status, and extract the location coordinates of the execution terminal device stored in each task information;

[0173] S204. Perform a spatial inclusion relationship analysis on each location coordinate of the execution terminal device and the set of administrative region boundary coordinates;

[0174] S205. When the location coordinate of the execution terminal device is within the electronic fence formed by the set of administrative region boundary coordinates, mark the corresponding task information as a region - associated task;

[0175] S206. Extract the task identifiers and the corresponding execution terminal device identifiers of all region - associated tasks;

[0176] S207. Bind the task identifier of each region - associated task with the execution terminal device identifier to generate an active task information unit;

[0177] S208. Classify and aggregate all active task information units according to the current task geographical region identifier to obtain the active task set.

[0178] In this embodiment, during the task assignment process, it is necessary to ensure that newly created tasks can be reasonably associated with the tasks currently being executed to avoid duplicate assignment or task conflicts. For this purpose, the system first obtains the set of administrative region boundary coordinates corresponding to the current task geographical region identifier. This process relies on the Geographic Information System (GIS), and by querying the preset administrative division database, the boundary coordinate data of the region is obtained. For example, in the field of medical and health, this data can correspond to the physical boundary of the hospital ward area; in the field of financial survey, it corresponds to the geographical scope of bank branches or enterprises; in the equipment inspection scenario, it corresponds to the inspection area of factories or warehouses.

[0179] The system needs to extract task information with all task status codes being the execution status from the execution task list to filter out the tasks currently being executed. The execution task list usually stores the status information of tasks, including status codes such as "to be executed", "executing", and "completed". Only tasks in the "executing" status will be included in the active task set. For example, in the medical scenario, the system needs to check whether there is currently a nursing task being executed in this ward area; in the financial survey scenario, it is necessary to confirm whether there is currently a survey task being carried out for this enterprise or bank branch; in the equipment inspection task, it is necessary to check whether there are other inspection tasks being executed in the current workshop or equipment.

[0180] Subsequently, the system traverses the task information in the execution state and extracts the location coordinates of the execution terminal device stored in each task information. The execution terminal device usually includes a mobile device, an intelligent sensor or a remote workstation, such as the mobile terminal of a nurse, the intelligent device of an inspector, the handheld terminal of a patrolman or an unmanned patrol robot, etc. The system extracts the real-time location coordinates of the device based on the device's GPS, Wi-Fi, Bluetooth or cellular signal for subsequent comparison.

[0181] Next, the system performs a spatial inclusion relationship analysis between the location coordinates of each execution terminal device and the set of administrative region boundary coordinates to determine whether the execution terminal is within the target area. The spatial inclusion relationship analysis is usually based on GIS spatial query algorithms, such as the Point-in-Polygon (PIP) calculation, to determine whether the device coordinates fall within the area range. For example, in the financial inspection scenario, if the inspector's device is within the administrative boundary of the target enterprise, then the task can be regarded as a matching task; in the medical scenario, if the nurse's device coordinates fall within the fence range of the ward area, then the task can be regarded as an effective task.

[0182] If the device location coordinates are within the electronic fence range formed by the set of administrative region boundary coordinates, the system will mark the corresponding task information as a region-associated task. The role of the electronic fence technology in task management is to ensure that tasks are executed within the correct geographical range. For example, in the financial inspection task, the electronic fence can be used to prevent the inspector from completing the task at an inappropriate location; in the equipment patrol task, the electronic fence can ensure that the patrolman must arrive near the equipment in person before he can execute the patrol task.

[0183] The system then extracts the task identifiers of all region-associated tasks and the corresponding execution terminal device identifiers for subsequent task management. The task identifier uniquely identifies each task, while the execution terminal device identifier is used to identify which device executes the task. For example, in the medical scenario, the mobile device of Nurse A may be bound to multiple nursing tasks at the same time, and in the financial inspection task, the terminal device of Inspector B may be bound to multiple credit assessment tasks at the same time.

[0184] Finally, the system binds the task identifier of each region-associated task to the execution terminal device identifier to generate an active task information unit, and classifies and aggregates all active task information units according to the current task geographical area identifier to obtain an active task set. This process ensures that new tasks can form a reasonable association with the tasks being executed to optimize the task execution efficiency and reduce resource waste.

[0185] In this embodiment, through spatial matching, electronic fence judgment, and task binding, it is ensured that tasks can be intelligently allocated to the terminal devices that are executing tasks in the target area, avoiding duplicate task dispatching and improving task execution efficiency. At the same time, the application of the electronic fence technology ensures that tasks must be executed within the correct physical area, preventing the occurrence of remotely submitting tasks or incorrectly executing tasks, and improving the accuracy of task scheduling.

[0186] In one embodiment, the above S40 includes:

[0187] S401, obtaining the device performance parameters corresponding to the terminal device identifier;

[0188] S402, generating a task information compression format according to the device performance parameters, and encoding the current task information according to the compression format;

[0189] S403, detecting the current network signal strength of the terminal device corresponding to the terminal device identifier;

[0190] S404, when the current network signal strength of the terminal device is equal to or higher than the preset strength threshold, sending the encoded current task information to the terminal device through the real-time streaming protocol;

[0191] S405, when the current network signal strength of the terminal device is lower than the preset strength threshold, sending the encoded current task information to the terminal device through the chunked asynchronous transfer protocol.

[0192] In this embodiment, the allocation of task information needs to consider the performance of the terminal device, the network environment, and the data transmission method to ensure that the task information can be transmitted efficiently and accurately and correctly received and processed by the terminal.

[0193] First, the system obtains the device performance parameters corresponding to the terminal device identifier, including the computing power, storage space, supported decoding formats, etc. of the device. For example, in the field of medical and health, the mobile devices of hospital nursing staff may be high-performance medical-grade terminals that support directly parsing complete task data, while in the field of financial survey, surveyors may use resource-constrained mobile devices that need to optimize the storage and parsing methods of task data. In the field of equipment inspection, inspection robots or intelligent monitoring devices may have different storage capabilities and computing capabilities, and the system needs to determine the transmission and processing methods of task information based on these characteristics.

[0194] Based on the device performance parameters, the system generates a compressed format of the task information and encodes the current task information. If the terminal device has strong computing power, efficient compression formats (such as JSON, XML) can be used; if the device has limited storage space or low processing capacity, binary compression formats (such as Protocol Buffers or MessagePack) can be adopted to reduce the data transmission volume. In addition, for cases where the task information is large, such as containing data like images and videos, the system can transmit only the key fields of the task and allow the terminal device to request the complete task details as needed. For example, in a medical scenario, the system can first transmit the basic information of the patient care task, such as the bed number and care type, and the detailed care instructions can be supplemented and transmitted when requested by the terminal device.

[0195] After the task information is encoded, the system detects the current network signal strength of the terminal device corresponding to the terminal device identifier. This process can be achieved by querying the cellular network (4G / 5G), Wi-Fi signal strength (RSSI), or Bluetooth connection quality (such as BLE signal strength). For example, in the financial survey field, the surveyor may be in a remote area with weak network signals, and in the medical inspection field, the terminal device may be in an area with poor hospital network coverage. Therefore, the system needs to determine the task transmission method according to the network conditions.

[0196] When it is detected that the current network signal strength of the terminal device is equal to or higher than the preset strength threshold, the system sends the encoded task information to the terminal device through a real-time streaming protocol (such as WebSocket, MQTT, HTTP / 2). This method is suitable for a good network environment and can ensure that the task information is transmitted quickly and securely. For example, in a hospital ward environment, the nurse terminal is usually connected to a stable Wi-Fi, and the system can directly push the complete care task data; in a bank survey task, the surveyor may be located in the urban business district, and the system can directly transmit the complete survey task data through a high-speed network.

[0197] When the current network signal strength of the terminal device is lower than the preset strength threshold, the system sends the encoded task information to the terminal device through a block asynchronous transmission protocol (such as UDP, fragmented HTTP, resume point transfer protocol). This method is suitable for unstable or weak network environments. For example, in a device inspection task, if the inspector is located in the underground workshop of a factory, the system can use the resume point transfer method to divide the task information into multiple small blocks for asynchronous transmission to ensure that the task data can ultimately be completely transmitted to the terminal device. In addition, in a financial survey task, if the surveyor is located in a mountainous or remote area with poor signal, the system can first send the task summary information and supplement the complete task data after the signal is restored.

[0198] In this embodiment, through device - adaptive task encoding, network signal strength detection, and dynamic task transmission strategies, it is ensured that tasks can be efficiently transmitted under different terminal devices and network environments, improving the success rate of task pushing. The use of the real - time streaming protocol guarantees that tasks can be quickly transmitted to terminal devices, while the chunked asynchronous transmission protocol ensures the reliability of task data in weak network environments, thereby optimizing the stability and availability of task allocation.

[0199] In one embodiment, the above - mentioned S70 includes:

[0200] S701, obtaining the scheduling verification time - window field of the current task information, where the scheduling verification time - window field includes a start timestamp and an end timestamp;

[0201] S702, extracting the scheduling verification time - window fields of all task information from the to - be - merged task information;

[0202] S703, determining the time overlap interval of all scheduling verification time - window fields, where the time overlap interval is the period between the maximum value of the start timestamps and the minimum value of the end timestamps of each scheduling verification time - window field;

[0203] S704, when the duration of the time overlap interval is greater than or equal to a preset effective - duration threshold, generating a composite task unit including the current task information and the to - be - merged task information;

[0204] S705, setting a unified execution time window for the composite task unit, where the start time of the unified execution time window is the earliest time point of the time overlap interval, and the end time is the latest time point of the time overlap interval.

[0205] In this embodiment, task merging is an important link in task - allocation optimization, ensuring that multiple tasks have a reasonable execution window in terms of time to improve task - execution efficiency and reduce the cost of repeated scheduling. First, the system obtains the scheduling verification time - window field of the current task information, which includes the start timestamp and end timestamp of the task and is used to define the executable time range of the task. For example, in a medical - care scenario, a patient - care task may need to be executed between 08:00 - 10:00; in a financial - survey scenario, an enterprise due - diligence investigation may need to be completed between 09:00 - 17:00; and in an equipment - inspection task, an inspector may need to perform inspections between 14:00 - 16:00.

[0206] The system then extracts the scheduling verification time window fields of all tasks from the tasks to be merged to ensure that the time ranges of the tasks can match the current task. The time window information of the tasks is stored in the task database, usually set by the task creator or automatically generated based on business rules. For example, in medical tasks, the time window of a nursing task may be set by a doctor, while in financial tasks, the time window of an inspection task may be determined by the enterprise's opening hours. In equipment inspection tasks, the inspection time window may be adjusted according to the equipment usage status.

[0207] Next, the system determines the time overlap interval of all scheduling verification time window fields. By calculating the maximum value of the start timestamps and the minimum value of the end timestamps of each task, it determines the time period during which the tasks can be executed together. Only when the execution times of the tasks have an overlapping area can the tasks be merged. For example, in a financial inspection task, if the credit review task window of a certain enterprise is from 09:00 to 15:00, and the risk assessment task window is from 10:00 to 16:00, then the overlapping interval of the two tasks is from 10:00 to 15:00. In equipment inspection tasks, if the sensor maintenance task window of the same equipment is from 13:00 to 15:00, and the equipment status inspection task window is from 14:00 to 16:00, then its overlapping interval is from 14:00 to 15:00.

[0208] When the duration of the time overlap interval is greater than or equal to the preset effective duration threshold, the system generates a composite task unit that includes the current task information and the tasks to be merged. This effective duration threshold is usually determined by business requirements. For example, medical nursing tasks may require at least 30 minutes of time overlap, financial inspection tasks may require at least 1 hour of overlap time, and equipment inspection tasks may require at least 15 minutes of overlap time. If the overlap time is less than this threshold, the system will not merge the tasks to ensure that tasks do not cause execution conflicts or resource waste due to too short a shared window.

[0209] Finally, the system sets a unified execution time window for the composite task unit. The start time of this time window is the earliest time point of the time overlap interval, and the end time is the latest time point of the time overlap interval. For example, in a financial inspection task, if the overlapping interval of the risk assessment task and the credit review task is from 10:00 to 15:00, then the execution time window of the composite task unit will be set to 10:00 - 15:00. In medical tasks, if the time overlap interval of two patient care tasks is from 08:30 to 10:00, then the execution time window of the composite task unit is set to 08:30 - 10:00. This can ensure that multiple tasks are executed efficiently within the same time window, reduce duplicate task assignments, and improve task execution efficiency.

[0210] In this embodiment, through the calculation of the scheduling verification time window, the task merging strategy, and the optimization of the execution time window, it is ensured that multiple tasks can be merged within a reasonable time range, improving the task execution efficiency and reducing the cost of repeated scheduling. The calculation of the time overlap interval enables tasks to be intelligently matched based on the time window, the generation of composite task units makes task scheduling more accurate, and the setting of a unified execution time window avoids task execution conflicts, making task management more intelligent and efficient.

[0211] In one embodiment, the above S80 includes:

[0212] S801, obtaining the number of subtasks of the composite task unit and the start time of the unified execution time window, and obtaining the geographical area identifier common to all subtasks within the composite task unit;

[0213] S802, when the number of subtasks exceeds the preset release scale threshold, extracting the historical task execution period record set corresponding to the common geographical area identifier;

[0214] S803, determining the release time point according to the historical task execution period record set, binding the composite task unit to the release time point, and then adding it to the task release queue;

[0215] S804, when the current time reaches the release time point, pushing the composite task unit to all online task execution terminals within the coverage range of the common geographical area identifier.

[0216] In this embodiment, the final link of task allocation is to release the composite task unit to the task execution terminal according to the preset release strategy. This link ensures that tasks can be pushed to the appropriate execution terminals at the appropriate time, maximizing the task execution efficiency and reducing resource waste.

[0217] First, the system obtains the number of subtasks of the composite task unit, the start time of the unified execution time window, and the geographical area identifier common to all subtasks. The number of subtasks is used to judge the task scale to ensure that the task will not affect the execution efficiency due to being too large. The start time of the unified execution time window is used to determine the earliest executable time of the task, while the geographical area identifier is used to determine the physical scope applicable to the task. For example, in medical care tasks, there may be multiple nursing tasks in a certain ward that need to be merged for execution, and the geographical area identifier can be the ward number; in financial survey tasks, the identifier may be the administrative division where the target enterprise is located; in equipment inspection tasks, the identifier may be the code of a certain workshop or production area.

[0218] When the number of subtasks exceeds the preset release scale threshold, the system extracts the record set of historical task execution time periods corresponding to the geographical area identifier. The preset release scale threshold is a key parameter for task scheduling, ensuring that tasks do not affect the execution efficiency due to excessive scale. For example, in medical care tasks, the number of combined care tasks in a single instance may be limited to no more than 5; in financial survey tasks, the number of tasks that a single surveyor can execute in a single instance may be limited to no more than 3; in equipment inspection tasks, the number of inspection tasks in the same time period may be limited to no more than 10. The record set of historical task execution time periods includes the execution time distribution of previous tasks in this area, such as when tasks are most intensive in a specific area and the active time periods of execution terminals, etc.

[0219] The system determines the release time point based on the record set of historical task execution time periods, binds the composite task unit to the release time point, and then adds it to the task release queue. The setting of the release time point needs to comprehensively consider historical data to ensure that tasks are pushed at the best time. For example, in medical tasks, care tasks are usually executed the most during the morning shift (07:00 - 09:00) and the evening shift (19:00 - 21:00), so the system will select these time periods as the preferred task release time points; in financial survey tasks, the peak of surveyors' tasks may be from 10:00 to 12:00 in the morning and from 14:00 to 16:00 in the afternoon, so the system will try to release tasks before these times; in equipment inspection tasks, inspectors may prefer to conduct inspections during non-production peak periods (such as 22:00 - 06:00 at night), so the system can arrange task pushes in the evening.

[0220] When the current time reaches the release time point, the system pushes the composite task unit to all online task execution terminals within the coverage of the geographical area identifier. This means that the system does not push tasks immediately but waits for the best release time to improve the acceptance rate and execution efficiency of tasks. For example, in medical tasks, the system does not push tasks during the care handover period (such as 07:30, 19:30), but pushes them after the shift is stable; in financial survey tasks, the system ensures that tasks are pushed before the surveyors enter the target area; in equipment inspection tasks, the system pushes tasks before the normal working hours of inspectors so that inspectors can complete tasks within the specified time.

[0221] In addition, the release time point may need to meet the following constraints:

[0222] The release time point is earlier than the start time of the unified execution time window, and the advance amount is not less than the preset buffer duration. This constraint ensures that the execution terminal has sufficient time to prepare after the task is pushed. For example, in a medical task, the caregiver may need to receive the task 30 minutes in advance to make nursing preparations; in a financial survey task, the surveyor may need at least 60 minutes of preparation time; in an equipment inspection task, the inspector may need to check the equipment status and plan the inspection path 15 minutes in advance.

[0223] The release time point is within the standard working period range of the execution terminal associated with the geographical area identifier, ensuring that the execution terminal is active when the task is pushed. For example, in a medical care task, the task will not be released in the early morning or late at night; in a financial survey task, the task will not be pushed during non-working hours; in an equipment inspection task, the task will not be pushed during the factory shutdown and maintenance time.

[0224] In this embodiment, through task scale control, historical task analysis, release time point optimization, and buffer duration control, it is ensured that the task push conforms to the best reception time of the execution terminal, improving the task execution efficiency. The task push strategy is dynamically adjusted based on historical data, avoiding the situation where the execution terminal cannot respond in time due to the task being released too early or too late, and at the same time ensuring a reasonable task distribution, reducing task backlog or resource waste, and making task scheduling more intelligent and efficient.

[0225] In one embodiment, after the above S80, it further includes:

[0226] S901, modifying the task status field value of each task information in the associated task list to the associated execution status code;

[0227] S902, obtaining the geographical area identifier and the corresponding terminal device location coordinates of the task information that has been allocated in the composite task unit;

[0228] S903, determining the spatial overlap degree between the geographical area coverage range corresponding to the geographical area identifier of the task information that has been allocated and the corresponding terminal device location coordinates;

[0229] S904, when the spatial overlap degree reaches the preset matching threshold, modifying the task status field value of the corresponding task information to the independent execution status code;

[0230] S905, generating a storage partition identifier according to the geographical area identifier of the currently processed task information, where the currently processed task information includes the task information whose task status field value in the associated task list has been modified and the task information whose task status field value in the composite task unit has been modified;

[0231] S906, classify and store the current processing task information into the corresponding logical partition of the active task set according to the storage partition identifier.

[0232] In this embodiment, after task allocation, the system needs to manage the execution status of tasks, ensure that tasks can be accurately classified, and stored in the appropriate task dataset to optimize task scheduling and execution management. After the task is pushed to the terminal device, the system first modifies the task status field value of each task information in the associated task list to update it to the associated execution status code. This status code is used to identify the subordinate execution relationship between the task and the active task information, ensuring that the system can identify which tasks are dependent on the previous task status. For example, in a medical care task, if a nurse's care task depends on a previous ward inspection task, this task will be marked as an associated execution status; in a financial survey task, if an enterprise credit review task depends on the completion of a financial assessment task, the task status needs to be marked as an associated execution status; in an equipment inspection task, if a sensor inspection task of a certain equipment depends on an equipment calibration task, its status also needs to be updated to an associated execution status.

[0233] The system then obtains the geographical area identifier of the task information that has been completed and allocated in the composite task unit and the corresponding terminal device location coordinates. The core of this process is to ensure that the physical location of the task executor matches the execution scope required by the task. For example, in a medical task, the system needs to confirm whether the nurse is within the ward range; in a financial task, the system needs to confirm whether the surveyor has arrived at the target enterprise site; in an equipment inspection task, the system needs to confirm whether the inspector's equipment is within the factory production area.

[0234] To ensure that the actual execution location of the task meets the expectations, the system determines the geographical area coverage range corresponding to the geographical area identifier of the task information that has been completed and allocated, and performs a spatial overlap analysis with the actual location coordinates of the terminal device. The system uses methods such as electronic fences, GPS, Wi-Fi signals, and cellular base stations to calculate whether the terminal device is in the specified area. For example, in a medical care task, the nurse's terminal device must be within the Wi-Fi coverage range of the target ward; in a financial survey task, the surveyor's device must be connected to the enterprise internal network or the GPS coordinates must fall within the enterprise park; in an equipment inspection task, the inspector's device must enter the specific factory area electronic fence to ensure that the task execution location meets the requirements.

[0235] When the spatial overlap degree reaches the preset matching threshold, the system modifies the task status field value of the corresponding task information to the independent execution status code. This independent execution status code indicates that the task can be executed independently of the active task information and no longer depends on other tasks. For example, in a medical care task, when a nurse enters the ward area and scans the patient's wristband, the system can confirm that the task enters the independent execution status; in a financial survey task, when a surveyor enters the gate of the target enterprise and completes the identity verification, the system can confirm the independent execution of the task; in an equipment inspection task, when an inspector enters the equipment monitoring range and connects to a specific sensor, the system can confirm the independent execution of the task.

[0236] After the task status is updated, the system generates a storage partition identifier based on the geographical area identifier of the currently processed task information. This storage partition identifier contains the coding information of the area where the task is located, ensuring that task data can be divided by region during storage. For example, in a medical task, the storage partition can be generated based on the ward number, such as "ICU_A01"; in a financial task, the storage partition can be generated based on the industry classification and geographical location of the enterprise, such as "FIN_110105"; in an equipment inspection task, the storage partition can be generated based on the plant number and equipment type, such as "PLANT_C05_SENSOR".

[0237] Finally, based on the storage partition identifier, the system classifies and stores the currently processed task information in the corresponding logical partition of the active task set, ensuring that task data is logically separated from other task data during storage. For example, in a medical task, nursing tasks in different wards will be stored in their respective nursing management databases; in a financial survey task, enterprise survey tasks in different industries will be stored in their respective credit assessment databases; in an equipment inspection task, different types of equipment inspection tasks will be stored in the corresponding equipment monitoring databases for subsequent query and analysis.

[0238] Logical partitions play a key role in task data storage and management. It refers to the division of data in a database or storage system according to specific logical criteria, thereby improving data retrieval efficiency, optimizing storage management, and supporting data processing in a distributed computing environment. Logical partitions are mainly used for classified storage according to the geographical area identifier of tasks, ensuring that task data in the same geographical area and of the same type can be classified into the same storage unit, facilitating subsequent retrieval, task correlation analysis, and data management.

[0239] The division of logical partitions is usually based on predefined partition strategies. The following are several common logical partition methods:

[0240] Logical partitioning based on geographical area is applicable to scenarios where tasks need to be managed by region. For example:

[0241] Medical care tasks: The ward numbers in the hospital (such as "ICU_A01", "WARD_B03") can be used as logical partition identifiers, and the care tasks of each ward are stored in the corresponding logical partition to ensure that the ward care management system can quickly retrieve all pending tasks in this ward.

[0242] Financial survey tasks: The survey tasks can be divided according to the administrative regions of the target enterprises. For example, "Chaoyang District, Beijing (FIN_110105)". In this way, when querying the survey tasks in a specific region, the system can directly access the corresponding logical partition without traversing the entire database, improving the query efficiency.

[0243] Equipment inspection tasks: The numbers of factories or production areas (such as "PLANT_C05") can be used as logical partitions, and the equipment inspection tasks of each area are stored in the corresponding partition. The inspection system can quickly screen the equipment status data that needs to be processed.

[0244] The logical partition based on the task type is applicable to the situation where different types of tasks need to be stored and managed independently. For example:

[0245] In the medical scenario, care tasks, surgical preparation tasks, equipment disinfection tasks, etc. can be stored in different logical partitions respectively to ensure that different tasks are not confused.

[0246] In the financial scenario, loan approval tasks, enterprise due diligence tasks, credit assessment tasks, etc. can be divided and stored respectively to improve the accuracy of task classification management.

[0247] In the equipment inspection scenario, different types of equipment (such as sensor monitoring, mechanical component inspection, energy consumption monitoring) can correspond to different logical partitions to ensure more orderly management of equipment data.

[0248] The logical partition based on time is applicable to the situation where task data needs to be managed according to time batches. For example:

[0249] In medical care tasks, the daily care task data can be logically partitioned by date (such as "Nursing_20240220") to facilitate time series analysis by the system.

[0250] In financial survey tasks, the system can organize the survey task data by quarter (such as "FIN_Q1_2024") to facilitate the statistics of the task completion situation in each quarter.

[0251] In equipment inspection tasks, the inspection tasks can be stored by week (such as "Inspect_Week_08_2024") to ensure that the inspection system can quickly find historical inspection records.

[0252] In this embodiment, through technical means such as task status encoding, spatial matching verification, and storage partition management, it is ensured that the status management after task allocation is more accurate, the matching degree between the task execution location and the target area is higher, and at the same time, data storage is more structured. The hierarchical management of task status makes task scheduling more flexible. The spatial matching degree analysis ensures that the task executor is in the correct geographical location. The introduction of storage partition identifiers optimizes task data management, making task execution more intelligent, efficient, and accurate.

[0253] In one embodiment, a task merging and allocation device is provided, and this task merging and allocation device corresponds one-to-one with the task merging and allocation method in the above embodiment. Refer to Figure 3 , Figure 3 which is a schematic diagram of the functional modules of a preferred embodiment of the task merging and allocation device of the present invention. Task creation module 10, active task management module 20, matching processing module 30, task distribution module 40, task confirmation module 50, task screening module 60, task merging module 70, and task publishing module 80. The detailed description of each functional module is as follows:

[0254] The task creation module 10 is used to create current task information including geographical area identification and object identification, and store the current task information in the task set to be allocated;

[0255] The active task management module 20 is used to obtain an active task set corresponding to the geographical area identification of the current task, and the active task set includes active task information in an execution state;

[0256] The matching processing module 30 is used to extract the terminal device identifier from the matching active task information when there is active task information in the active task set that matches the object identification of the current task;

[0257] The task distribution module 40 is used to extract the current task information from the task set to be allocated and send it to the terminal device corresponding to the terminal device identifier;

[0258] The task confirmation module 50 is used to add the current task information to the associated task list of the matching active task information if the task reception confirmation information returned by the terminal device is received;

[0259] The task screening module 60 is used to screen out the task information to be merged that matches the geographical area identification and object identification of the current task information from the task set to be allocated if the task reception confirmation information returned by the terminal device is not received;

[0260] The task merging module 70 is used to merge the current task information with the task information to be merged to generate a composite task unit;

[0261] A task publishing module 80, configured to publish the composite task unit to a task execution terminal according to a preset publishing policy.

[0262] In one embodiment, the task creation module 10 is specifically configured to:

[0263] Receive the natural language address description and the object identifier in the task creation request;

[0264] Convert the natural language address description into latitude and longitude coordinate data, and query an administrative division database according to the latitude and longitude coordinate data to obtain a corresponding standard geographical area identifier;

[0265] Verify the valid status of the object identifier in the object information library to generate a validity verification result;

[0266] When the validity verification result is valid, generate a task form template including the standard geographical area identifier and the valid object identifier;

[0267] Fill in the task type identifier and the scheduling verification time window field value in the task form template;

[0268] Bind the filled task form template with the task creation timestamp to generate structured current task information;

[0269] Write the structured current task information into the unassigned task partition of the to-be-assigned task set according to a preset storage format.

[0270] In one embodiment, the active task management module 20 is specifically configured to:

[0271] Obtain a set of administrative region boundary coordinates corresponding to the current task geographical area identifier;

[0272] Extract all task information with a task status code of the execution status from the execution task list;

[0273] Traverse the task information in the execution status, and extract the execution terminal device location coordinates stored in each task information;

[0274] Perform a spatial inclusion relationship analysis on each execution terminal device location coordinate and the set of administrative region boundary coordinates;

[0275] When the execution terminal device location coordinate is within the electronic fence range formed by the set of administrative region boundary coordinates, mark the corresponding task information as a region-associated task;

[0276] Extract the task identifiers and the corresponding execution terminal device identifiers of all region-associated tasks;

[0277] Bind the task identifier of each area - related task to the execution terminal device identifier to generate an active task information unit;

[0278] Classify and aggregate all active task information units according to the current task geographical area identifier to obtain the active task set.

[0279] In one embodiment, the task distribution module 40 is specifically configured to:

[0280] Obtain the device performance parameters corresponding to the terminal device identifier;

[0281] Generate a task information compression format according to the device performance parameters, and encode the current task information according to the compression format;

[0282] Detect the current network signal strength of the terminal device corresponding to the terminal device identifier;

[0283] When the current network signal strength of the terminal device is equal to or higher than the preset strength threshold, send the encoded current task information to the terminal device through the real - time streaming protocol;

[0284] When the current network signal strength of the terminal device is lower than the preset strength threshold, send the encoded current task information to the terminal device through the chunked asynchronous transfer protocol.

[0285] In one embodiment, the task merging module 70 is specifically configured to:

[0286] Obtain the scheduling verification time window field of the current task information, where the scheduling verification time window field includes a start timestamp and an end timestamp;

[0287] Extract the scheduling verification time window fields of all task information from the task information to be merged;

[0288] Determine the time overlap interval of all scheduling verification time window fields, where the time overlap interval is the period between the maximum value of the start timestamps of each scheduling verification time window field and the minimum value of the end timestamps;

[0289] When the duration of the time overlap interval is greater than or equal to the preset effective duration threshold, generate a composite task unit including the current task information and the task information to be merged;

[0290] Set a unified execution time window for the composite task unit, where the start time of the unified execution time window is the earliest time point of the time overlap interval, and the end time is the latest time point of the time overlap interval.

[0291] In one embodiment, the task publishing module 80 is specifically configured to:

[0292] Obtain the number of subtasks of the composite task unit and the start time of the unified execution time window, and obtain the geographical area identifier common to all subtasks within the composite task unit;

[0293] When the number of subtasks exceeds the preset release scale threshold, extract the historical task execution period record set corresponding to the common geographical area identifier;

[0294] Determine the release time point according to the historical task execution period record set, bind the composite task unit to the release time point, and then add it to the task release queue;

[0295] When the current time reaches the release time point, push the composite task unit to all online task execution terminals within the coverage range of the common geographical area identifier.

[0296] In one embodiment, the task release module 80 is specifically configured to:

[0297] Modify the task status field value of each task information in the associated task list to the associated execution status code;

[0298] Obtain the geographical area identifier of the task information that has been allocated in the composite task unit and the corresponding terminal device location coordinates;

[0299] Determine the spatial overlap degree between the geographical area coverage range corresponding to the geographical area identifier of the task information that has been allocated and the corresponding terminal device location coordinates;

[0300] When the spatial overlap degree reaches the preset matching threshold, modify the task status field value of the corresponding task information to the independent execution status code;

[0301] Generate a storage partition identifier according to the geographical area identifier of the currently processed task information, where the currently processed task information includes the task information whose task status field value in the associated task list has been modified and the task information whose task status field value in the composite task unit has been modified;

[0302] Classify and store the currently processed task information into the corresponding logical partition of the active task set according to the storage partition identifier.

[0303] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 4As shown in the figure. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client through a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the server side of a task merging and allocation method.

[0304] In one embodiment, a computer device is provided. The computer device can be a client, and its internal structure diagram can be as Figure 5 shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the client side of a task merging and allocation method

[0305] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0306] Create current task information including a geographical area identifier and an object identifier, and store the current task information in a task set to be allocated;

[0307] Obtain an active task set corresponding to the geographical area identifier of the current task. The active task set includes active task information in an execution state;

[0308] When there is active task information in the active task set that matches the object identifier of the current task, extract the terminal device identifier from the matching active task information;

[0309] Extract the current task information from the task set to be allocated and send it to the terminal device corresponding to the terminal device identifier;

[0310] If a task reception confirmation message returned by the terminal device is received, add the current task information to the associated task list of the matching active task information;

[0311] If the task reception confirmation information returned by the terminal device is not received, filter out the pending merge task information that matches the geographical area identifier and object identifier of the current task information from the set of tasks to be assigned;

[0312] Merge the current task information with the pending merge task information to generate a composite task unit;

[0313] Publish the composite task unit to the task execution terminal according to a preset publishing policy.

[0314] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0315] Create current task information including a geographical area identifier and an object identifier, and store the current task information in the set of tasks to be assigned;

[0316] Obtain an active task set corresponding to the current task geographical area identifier, where the active task set includes active task information in an execution state;

[0317] When there is active task information in the active task set that matches the current task object identifier, extract the terminal device identifier from the matching active task information;

[0318] Extract the current task information from the set of tasks to be assigned and send it to the terminal device corresponding to the terminal device identifier;

[0319] If the task reception confirmation information returned by the terminal device is received, add the current task information to the associated task list of the matching active task information;

[0320] If the task reception confirmation information returned by the terminal device is not received, filter out the pending merge task information that matches the geographical area identifier and object identifier of the current task information from the set of tasks to be assigned;

[0321] Merge the current task information with the pending merge task information to generate a composite task unit;

[0322] Publish the composite task unit to the task execution terminal according to a preset publishing policy.

[0323] It should be noted that for the functions or steps that can be realized by the above computer-readable storage medium or computer device, reference can be made to the relevant descriptions on the server side and the user side in the foregoing method embodiments. To avoid repetition, they will not be described in detail here.

[0324] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0325] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0326] It should be noted that if there are software tools or components of other companies in the embodiments of the present application, they are only used for example introduction and do not represent actual use. The above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A task merging and allocating method, characterized in that: The following steps are involved: Creating current task information including a geographic area identifier and an object identifier, and storing the current task information in a set of tasks to be assigned; Acquire an active task set corresponding to the current task geographic area identifier, wherein the active task set includes information of active tasks in execution state; When active task information matching the current task object identifier exists in the active task set, extracting a terminal device identifier from the matching active task information; Extracting the current task information from the set of tasks to be assigned and sending the current task information to the terminal device corresponding to the terminal device identifier; If task reception confirmation information returned by the terminal device is received, the current task information is added to the associated task list of the matched active task information; If the task reception confirmation information returned by the terminal device is not received, filtering out the task information to be merged that matches the geographic area identifier and the object identifier of the current task information from the set of tasks to be assigned; Merging the current task information with the task information to be merged to generate a composite task unit; The composite task unit is published to the task execution terminal according to a preset publishing strategy.

2. The task merging and allocating method according to claim 1, characterized in that: Creating current task information including a geographic area identifier and an object identifier, and storing the current task information in a set of tasks to be assigned, including: Receive the natural language address description and object identifier in the task creation request; Convert the natural language address description into longitude and latitude coordinate data, and query the administrative division database according to the longitude and latitude coordinate data to obtain the corresponding standard geographic area identifier; Verifying the validity status of the object identifier in the object information library and generating a validity verification result; When the validity verification result is valid, generating a task form template including the standard geographic area identifier and the valid object identifier; Filling the task type identifier and the scheduling verification time window field value in the task form template; Bind the filled task form template to the task creation timestamp to generate structured current task information; The structured current task information is written into the unassigned task partition of the to-be-assigned task set according to a preset storage format.

3. The task merging and allocating method according to claim 1, characterized in that: Obtain an active task set corresponding to the current task geographic area identifier, wherein the active task set contains information about active tasks in execution, including: Get the administrative area boundary coordinate set corresponding to the current task geographic area identifier; Extract all task information with the task status code of execution from the execution task list; Traversing the task information of the execution status, and extracting the execution terminal device location coordinates stored in each task information; Performing spatial inclusion relationship analysis between the location coordinates of each execution terminal device and the set of administrative area boundary coordinates; When the location coordinates of the execution terminal device are within the electronic fence formed by the set of administrative area boundary coordinates, marking the corresponding task information as an area-related task; Extract the task identifiers of all region-related tasks and the corresponding execution terminal device identifiers; Bind the task identifier of each area-associated task with the execution terminal device identifier to generate an active task information unit; All active task information units are classified and aggregated according to the current task geographic area identifier to obtain the active task set.

4. The task merging and allocating method according to claim 1, characterized in that: Extracting the current task information from the set of tasks to be assigned and sending the current task information to the terminal device corresponding to the terminal device identifier includes: Obtaining device performance parameters corresponding to the terminal device identifier; Generate a compressed format of task information according to the device performance parameters, and encode the current task information according to the compressed format; Detecting the current network signal strength of the terminal device corresponding to the terminal device identifier; When the current network signal strength of the terminal device is equal to or higher than a preset strength threshold, the encoded current task information is sent to the terminal device via a real-time streaming protocol; When the current network signal strength of the terminal device is lower than a preset strength threshold, the encoded current task information is sent to the terminal device via a block asynchronous transmission protocol.

5. The task merging and allocating method according to claim 1, characterized in that: The current task information is combined with the task information to be combined to generate a composite task unit, including: Obtain a scheduling verification time window field of the current task information, wherein the scheduling verification time window field includes a start timestamp and an end timestamp; Extracting the scheduling verification time window field of all task information from the task information to be merged; Determine a time overlap interval of all scheduling verification time window fields, where the time overlap interval is a period between a maximum value of a start timestamp and a minimum value of an end timestamp of each scheduling verification time window field; When the duration of the time overlap interval is greater than or equal to a preset effective duration threshold, generating a composite task unit including the current task information and the task information to be merged; A unified execution time window is set for the composite task unit, wherein the start time of the unified execution time window is the earliest time point of the time overlap interval, and the end time is the latest time point of the time overlap interval.

6. The task merging and allocating method according to claim 1, characterized in that: Publishing the composite task unit to the task execution terminal according to a preset publishing strategy includes: Obtaining the number of subtasks of the composite task unit and the start time of a unified execution time window, and obtaining a common geographic area identifier for all subtasks in the composite task unit; When the number of subtasks exceeds a preset release scale threshold, extracting a historical task execution period record set corresponding to the common geographic area identifier; Determine a release time point according to the historical task execution period record set, bind the composite task unit to the release time point and add it to the task release queue; When the current time reaches the publishing time point, the composite task unit is pushed to all online task execution terminals within the coverage of the common geographic area identifier.

7. The task merging and allocating method according to claim 1, characterized in that: After publishing the composite task unit to the task execution terminal according to the preset publishing strategy, the method further includes: Modify the task status field value of each task information in the associated task list to the associated execution status code; Obtaining the geographical area identification and the corresponding terminal device location coordinates of the task information that has been assigned in the composite task unit; Determine the spatial overlap between the geographical area coverage corresponding to the geographical area identifier of the assigned task information and the corresponding terminal device location coordinates; When the spatial overlap reaches a preset matching threshold, the task status field value of the corresponding task information is modified to an independent execution status code; Generate a storage partition identifier according to the geographic area identifier of the currently processed task information, wherein the currently processed task information includes the task information whose task status field value in the associated task list has been modified and the task information whose task status field value in the composite task unit has been modified; The currently processed task information is classified and stored into corresponding logical partitions of the active task set according to the storage partition identifier.

8. A task merging and allocating device, characterized in that: The task merging and allocating device comprises: A task creation module, used to create current task information including a geographic area identifier and an object identifier, and store the current task information in a set of tasks to be assigned; An active task management module, used to obtain an active task set corresponding to the current task geographic area identifier, wherein the active task set includes information of active tasks in execution state; A matching processing module, configured to extract a terminal device identifier from the matched active task information when there is active task information matching the current task object identifier in the active task set; A task distribution module, used for extracting the current task information from the set of tasks to be assigned and sending the current task information to the terminal device corresponding to the terminal device identifier; A task confirmation module, configured to add the current task information to a list of associated tasks of the matched active task information if task reception confirmation information returned by the terminal device is received; A task screening module, configured to screen out the task information to be merged that matches the geographic area identifier and the object identifier of the current task information from the set of tasks to be assigned if the task reception confirmation information returned by the terminal device is not received; A task merging module, used for merging the current task information with the task information to be merged to generate a composite task unit; The task publishing module is used to publish the composite task unit to the task execution terminal according to a preset publishing strategy.

9. A computer device, characterized in that: The computer device includes a memory, a processor, and a task merging and allocating program stored in the memory and executable on the processor. When the task merging and allocating program is executed by the processor, the steps of the task merging and allocating method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The storage medium stores a task merging and allocating program, which, when executed by a processor, implements the steps of the task merging and allocating method according to any one of claims 1 to 7.

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