Natural resource field proof task generation method and device

Abstract

The invention discloses a natural resource on-site proof task generation method and device, and relates to the technical field of task generation, and the natural resource on-site proof task generation method is applied to a proof scene visualization building platform. A preset proof database and a preset template warehouse are stored on the proof scene visualization building platform. The method comprises the following steps: responding to a building request of a user for a natural resource field proof task; analyzing the building request, and determining to-be-generated proof task information; querying corresponding proof data from a preset proof database according to the to-be-generated proof task information; selecting a target task template from a preset template warehouse according to the proof data; and performing proof task configuration on the proof data on the target task template to generate a natural resource field proof task. Through the automatic process, the generation efficiency of the natural resource on-site proof task is improved, and the complexity and error rate of manual operation are reduced.

Description

Technical Field

[0001] The present application relates to the field of task generation technology, and in particular to a method and device for generating natural resource on-site evidence tasks. Background Art

[0002] In existing natural resource management, field evidence collection tasks often require extensive manual configuration and setup, which is not only time-consuming and labor-intensive but also prone to errors. Traditional methods often rely on manual operations by managers, from selecting evidence data, configuring task templates, to generating the final evidence collection task. This process is cumbersome and inefficient. Furthermore, due to the involvement of manual operations, different managers may have different understandings and implementations, making it difficult to ensure the quality and consistency of evidence collection tasks. Summary of the Invention

[0003] The main purpose of this application is to provide a method and device for generating natural resource field evidence tasks, aiming to solve the current technical problem of low efficiency and accuracy in generating natural resource field evidence tasks.

[0004] To achieve the above-mentioned purpose, the present application proposes a method for generating a natural resource field evidence task, which is applied to a visualization platform for building evidence scenarios, wherein a preset evidence database and a preset template warehouse are stored on the visualization platform for building evidence scenarios; The method for generating a natural resource on-site evidence task includes: Responding to user requests for establishing natural resource field evidence tasks; Parsing the construction request to determine the evidence task information to be generated; According to the information of the evidence task to be generated, corresponding evidence data is searched from a preset evidence database; Selecting a target task template from a preset template warehouse based on the evidence data; The evidence data is configured as an evidence task on the target task template to generate a natural resource field evidence task. The evidence task configuration includes one or more of the following: task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

[0005] In addition, to achieve the above-mentioned purpose, the present application also proposes a natural resource field evidence task generation device, the natural resource field evidence task generation device comprising: A response module, used to respond to a user's request to build a natural resource field evidence task; A parsing module, configured to parse the building request and determine information of the evidence task to be generated; A query module, configured to query corresponding evidence data from a preset evidence database according to the evidence task information to be generated; A selection module, configured to select a target task template from a preset template repository based on the evidence data; A configuration module is used to configure the evidence data on the target task template to generate a natural resource field evidence task. The evidence task configuration includes one or more of the following: task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

[0006] In addition, to achieve the above-mentioned purpose, the present application also proposes a natural resource field evidence task generation device, which includes: a memory, a processor, and a computer program stored on the memory and runnable on the processor, and the computer program is configured to implement the steps of the natural resource field evidence task generation method as described above.

[0007] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and when the computer program is executed by the processor, the steps of the natural resource field evidence task generation method as described above are implemented.

[0008] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the natural resource field evidence task generation method as described above.

[0009] One or more technical solutions proposed in this application automate the entire process from user request to task generation, reducing manual operation and intervention, and significantly improving the efficiency and accuracy of task generation. Users only need to provide a setup request, and the system automatically parses, queries, selects, and configures relevant data and templates, greatly simplifying the complex process of task setup. By extracting corresponding data from a preset evidence database and configuring tasks based on preset templates, the generated evidence tasks can be ensured to meet standardized requirements, improving the accuracy and consistency of tasks and avoiding errors or omissions introduced by manual operation. Flexible configuration of multiple aspects of tasks is supported, including basic task information, workflows, survey fields, forms, and personnel management. This allows different task requirements to be adapted through configuration adjustments, meeting diverse evidence scenarios and ensuring the platform's applicability and versatility. The platform's visual setup allows users to intuitively build and manage evidence tasks, improving the user experience. Through a graphical interface, users can more easily design and adjust tasks to suit different usage needs and scenarios. Automated processes and template selection reduce reliance on manual labor, avoid bias caused by human factors, and improve the reliability and stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0011] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0012] Figure 1 A flowchart illustrating the first embodiment of the method for generating a natural resource field evidence task for this application is provided; Figure 2 A schematic diagram of the overall architecture for agile construction of a natural resource field evidence scenario provided in an embodiment of the method for generating a natural resource field evidence task of this application; Figure 3 A flowchart illustrating a second embodiment of the method for generating a natural resource field evidence task for this application is provided; Figure 4 A flowchart illustrating the third embodiment of the method for generating a natural resource field evidence task in this application; Figure 5 A schematic diagram of the definition of the conceptual model provided for an embodiment of the method for generating a natural resource field evidence task of this application; Figure 6A schematic diagram of a visualization scenario provided for an embodiment of a method for generating a natural resource field evidence task in this application; Figure 7 A flowchart illustrating a fourth embodiment of the method for generating a natural resource field evidence task in this application is provided; Figure 8 A schematic diagram of automatic expansion of investigation and evidence tasks provided in accordance with an embodiment of a method for generating on-site evidence tasks for natural resources of this application; Figure 9 A brief flowchart of an embodiment of a method for generating a natural resource field evidence task in this application is provided; Figure 10 This is a schematic diagram of the module structure of the natural resource field evidence task generation device according to an embodiment of the present application; Figure 11 This is a schematic diagram of the device structure of the hardware operating environment involved in the method for generating a natural resource field evidence task in an embodiment of the present application.

[0013] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0014] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0015] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0016] The main solution of the embodiment of the present application is: the natural resource field evidence task generation method is applied to the evidence scene visualization construction platform, and the evidence scene visualization construction platform stores a preset evidence database and a preset template warehouse; the natural resource field evidence task generation method includes: responding to the user's construction request for the natural resource field evidence task; parsing the construction request to determine the evidence task information to be generated; querying the corresponding evidence data from the preset evidence database according to the evidence task information to be generated; selecting the target task template from the preset template warehouse according to the evidence data; configuring the evidence task on the target task template to generate a natural resource field evidence task, and the evidence task configuration includes one or more of the task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration and task dictionary management configuration.

[0017] Since existing field evidence collection tasks usually require a lot of manual configuration and settings, the entire process is cumbersome and inefficient.

[0018] This application provides a solution and proposes an agile construction model for evidence scenarios that combines standardization and customization. For general investigation and evidence tasks, you can directly select the built-in evidence task template to create the evidence task. When the general evidence template cannot meet the evidence task, the "zero-code" evidence scenario construction engine can be used to customize the evidence task, forming a set of universal front-end and back-end configuration architectures and visual configuration processes for business personnel to customize field tasks on demand. The evidence scenario construction technology that combines standardization and customization can easily cope with frequent adjustments to the types and structures of evidence tasks. For diverse needs, there is no need for code development. Customized task generation can be achieved only through modeling and configuration. This process does not require professional configuration of products or on-site implementation personnel, which improves the timeliness of task configuration.

[0019] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device capable of implementing the above functions, a visual construction platform for evidence presentation scenarios, etc. The following uses the visual construction platform for evidence presentation scenarios as an example to illustrate this embodiment and the following embodiments.

[0020] Based on this, the embodiment of the present application provides a method for generating a natural resource field evidence task, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the method for generating a natural resource field evidence task in this application.

[0021] The visual construction platform for evidence-giving scenarios stores a preset evidence-giving database and a preset template warehouse.

[0022] It should be noted that the visual construction platform for evidence scenarios in this embodiment is equipped with a construction engine in advance, which has good environmental adaptability and does not require development. It can be implemented by technical personnel on the client side configuration, and can support a variety of investigation tasks or verification task monitoring needs. Including customization of investigation information, field attributes, association logic, default values, and field values. Autonomous configuration of field content, filter content, search content, and page forms displayed on the web and mobile terminals. Custom configuration of business review links, processes, and responses, as well as flexible configuration of business user objects. The evidence scenario construction engine provides a large number of pre-built modules, templates, and databases of evidence data. Users can directly use these modules, templates, and evidence data to quickly build evidence tasks. These modules and templates usually cover common evidence business logic and functions, such as task information, map structure, investigation content, operators, review processes, etc. The following are several key features of pre-built modules and templates: Functional module: Each module is an independent functional unit, and users can freely combine and configure these modules according to their needs.

[0023] Template library: The platform usually provides a rich library of survey task templates, and users can quickly combine appropriate survey task templates based on their business needs.

[0024] Customizability: Although the modules and templates are pre-built, users can still customize and adjust them based on the general modules according to their needs.

[0025] In this embodiment, the method for generating a natural resource on-site evidence task includes steps S10 to S50: Step S10: responding to the user's request to establish a natural resource field evidence task.

[0026] It should be noted that when a user has a request to generate a natural resource on-site evidence task, he or she can first operate the visual construction platform for the evidence scene. The visual construction platform for the evidence scene can be deployed on the web page. The user generates a request to build the natural resource on-site evidence task by accessing the visual construction platform for the evidence scene on the web page.

[0027] In the work of natural resource monitoring and supervision, there are many monitoring objects, heavy monitoring tasks, and tight time requirements. The field evidence of natural resources involves forest, grassland and wetland surveys, routine monitoring, supervision and law enforcement, water resources surveys, land change surveys, cultivated land protection, land use supervision, cultivated land satellite image supervision, afforestation, use control, satellite image law enforcement and many other types. At the same time, there are also various temporary field tasks or emergency verification needs. In response to the above needs, the overall architecture of the natural resource field evidence scenario is agilely constructed, such as Figure 2 As shown, Figure 2To agilely build an overall architecture diagram for the natural resource field evidence scenario, developers in the development center can set up standardized templates in advance, including model definitions and operation links. They can first clarify the field tasks, and then define the tasks (i.e., what tasks are to be done?), upload field maps, set field survey requirements, assign field tasks, and set field results review. They can also define the map structure (which maps to adjust), field fields (what information to collect?), operators (who will conduct the field work?), and review processes (how to review the results?); the configuration center is set up by operation and maintenance personnel for customized configuration, including configuration tools and configuration content. This includes configuration of task information, patch structure, survey content, operator, and review process. Task information includes task name, scope, and responsible department. Patch structure includes patch number, patch location, and spatial position. Survey content includes which information to fill in, whether it is required, and how many photos to collect. Operator configuration includes who will perform the work, which patches are responsible, and who is the administrator. Review process configuration includes the review departments involved, the review process, and review opinion options. Tasks are executed by field personnel and include multi-scenario applications, including daily changes, routine monitoring, post-supply supervision, land consolidation, and emergency field tasks. Multi-scenario applications can be built using the Evidence Scenario Agile Build Engine.

[0028] Step S20: parse the construction request to determine the evidence task information to be generated.

[0029] It's important to note that the request can be parsed to determine the specific requirements of the natural resource field evidence task the user wishes to generate. This parsing process may involve detailed analysis of the text description, graphical interface operations, or other forms of information in the request to extract key information, such as task type, investigation content, target area, and timeline. This information will serve as the basis for querying evidence data and selecting target task templates in subsequent steps.

[0030] In a specific implementation, the information of the task to be proved may include the name of the task to be generated, the task area, the task type, the priority of the task type to be generated, and other information.

[0031] In a feasible implementation, step S20 may include steps A11 to A15: Step A11: extract keywords from the construction request to obtain the name of the evidence task to be generated and the task area.

[0032] In practice, the build request can be parsed to extract keywords from the content. For example, keyword extraction algorithms (such as TF-IDF and TextRank) can be used to identify keywords related to the task type. For example, "investigation," "report," and "monitoring" can help identify whether the task type is "investigation task" or "monitoring task."

[0033] It is understandable that by extracting keywords from the build request, the name of the evidence task to be generated and the specific area can be obtained.

[0034] Step A12: Encode the construction request to obtain a text vector representation.

[0035] It should be noted that the build request can be encoded using the BERT (Bidirectional Encoder Representations from Transformers, pre-trained language) model to obtain a text vector representation.

[0036] Step A13: Input the text vector representation into the classifier to predict the task type and obtain the type of evidence task to be generated.

[0037] In a specific implementation, the text vector can be input into a classifier (such as SVM (Support Vector Machine) or Softmax classifier) ​​to predict the task type, thereby obtaining the type of evidence task to be generated.

[0038] Step A14: Use rule matching and priority reasoning to parse the construction request to obtain the priority of the evidence task type to be generated.

[0039] In practice, rule matching can be performed based on a pre-defined rule base that defines different types of tasks and their corresponding priorities. Priority reasoning can involve analyzing specific information in the request (such as urgency and task size) to determine the relative importance of the tasks. For example, if a request contains the keywords "urgent" or "as soon as possible," the priority is assigned to "high."

[0040] Step A15: The name of the task to be generated, the task area, the type of the task to be generated and the priority of the task to be generated are used as the information of the task to be generated.

[0041] For specific implementers, all the key information extracted and predicted previously can be integrated together to form a complete set of information on the evidence task to be generated, providing necessary input for subsequent steps.

[0042] Step S30: querying corresponding evidence data from a preset evidence database according to the evidence task information to be generated.

[0043] It should be noted that the pre-set evidence database contains a large amount of evidence data, which may involve different types of natural resources, different geographical locations, different time periods, and various related attribute information. After determining the information for the pending evidence task, the system will use this information to conduct a precise query within the pre-set evidence database to find the dataset that best matches the pending evidence task. This process may involve complex database query techniques and algorithms to ensure the accuracy and efficiency of the query results.

[0044] Step S40: selecting a target task template from a preset template repository according to the evidence data.

[0045] It's important to note that the preset template repository stores various types of evidence-generating task templates, pre-designed based on common evidence-generating task requirements and business logic. When selecting a target task template, the system comprehensively considers the type and structure of the evidence data, as well as the specific requirements of the task being generated. Using an intelligent matching algorithm, the system quickly selects the template from the preset template repository that best matches the task at hand. This process not only improves the efficiency of task generation but also ensures that the generated evidence-generating tasks comply with business regulations and standards.

[0046] Data templates are the foundation of investigation and evidence collection tasks. Forming a structured, readable, and logically coherent data template system enhances understanding of investigation and evidence collection tasks. Strictly adhering to the principles of scientificity, practicality, stability, scalability, compatibility, and pertinence, we rationally develop task templates, map structure templates, field field templates, operator templates, and review process templates, building a bridge for data continuity and communication and ensuring consistency in data acquisition, processing, management, and application.

[0047] Step S50: The evidence data is configured as an evidence task on the target task template to generate a natural resource field evidence task. The evidence task configuration includes one or more of the following: task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

[0048] During implementation, the configuration of a proof task may involve multiple aspects to ensure that the generated proof task not only meets business requirements but also has the ability to be executed efficiently. The following is a detailed description of each part of the proof task configuration: Configuring basic task information: This includes setting basic information such as the task name, number, creation time, and expected completion time. This information helps task managers quickly understand the task overview and facilitates task tracking and management. Configuring the evidence task workflow: The workflow defines the various stages from task creation to completion, as well as the required operations and responsible individuals for each stage. By configuring the workflow, you can ensure that the task execution process adheres to established business logic and process specifications, improving task execution efficiency and accuracy. Configuring survey fields: Survey fields are key elements for collecting data. When configuring survey fields, you need to determine the type of information to be collected, the field name, the field type, and whether or not a field is required based on business requirements. Proper field configuration ensures that the collected data is comprehensive, accurate, and meets business requirements. Configuring page forms: Page forms are the interface through which users interact with the system. When configuring page forms, consider user habits and operational processes to ensure that the form design is intuitive, concise, and easy to use. Furthermore, ensure that the fields in the form are consistent with the survey field configuration to ensure accurate data collection and storage. Configuring personnel for evidence task: Personnel configuration defines the personnel involved in the task and their roles and responsibilities. When assigning personnel, it's important to rationally allocate resources based on the scale and complexity of the task, as well as their professional capabilities and experience. By clarifying personnel responsibilities and division of labor, you can ensure smooth and efficient task execution. Evidence Task Management Configuration: Management configuration involves monitoring and managing the task execution process. This includes setting task reminders, progress tracking, and data reporting methods. Effective management configuration provides real-time visibility into task execution status and issues, enabling timely adjustments and optimizations to ensure smooth task completion. Task Dictionary Management Configuration: The task dictionary is a collection of various terms, codes, and standards related to the task. When configuring the task dictionary, ensure its accuracy and completeness to provide accurate reference and guidance during task execution. By comprehensively applying the above configuration items, you can generate natural resource field evidence tasks that meet business needs and are highly efficient. These tasks will help improve the efficiency and quality of natural resource monitoring and supervision, providing strong support for the rational development and utilization of natural resources.

[0049] In specific implementation, for common investigation and evidence-gathering tasks, built-in evidence-gathering task templates can be directly selected to create evidence-gathering tasks. When common evidence-gathering templates cannot meet the requirements of the evidence-gathering task, the "zero-code" evidence-gathering scenario construction engine can be used to customize the evidence-gathering task, forming a universal front-end and back-end configuration architecture and a visual configuration process for business personnel to customize field tasks on demand. The evidence-gathering scenario construction technology that combines standardization and customization can easily cope with the frequent adjustments to the types and structures of evidence-gathering tasks. For diverse needs, no code development is required; customized tasks can be generated through modeling and configuration alone. This process does not require specialized configuration of products or on-site implementation personnel, which improves the timeliness of task configuration.

[0050] After designing templates, setting up scenarios, and creating evidence-gathering tasks, the field evidence-gathering task setup is essentially complete. The evidence-gathering platform automatically generates evidence-gathering tasks on the webpage and creates a quick entry point for business applications, allowing users to easily access the corresponding business modules and conduct investigation, monitoring, evidence-gathering, and verification. The mobile terminal, serving as a unified terminal application portal, leverages technologies such as Internet Plus, mobile GIS, and drone connectivity, providing common foundational modules and monitoring and supervision modules to enable on-site evidence collection, video interconnection, and location-based search.

[0051] In a feasible implementation, when the amount of evidence-gathering tasks at the same time point is too large, intelligent resource scheduling is required. Therefore, the method for generating natural resource field evidence-gathering tasks further includes steps A21 to A24: Step A21: During the configuration of the evidence task, obtain the current status of the resource; In specific implementation, the current status of resources may include the real-time location, available time, professional skills, etc. of field personnel. This information is uploaded to the system in real time through mobile or web terminals to ensure the accuracy and timeliness of resource scheduling.

[0052] Step A22: Obtain resource load according to the current state of the resource; Resource load is determined by a comprehensive assessment of the scale, urgency, and resource requirements of all current evidence-generating tasks. When resource load exceeds a preset threshold, the system triggers an intelligent resource scheduling mechanism to ensure that all tasks can be completed efficiently and orderly.

[0053] Step A23: When the resource load is greater than a preset load threshold, the patch type, terrain complexity, and evidence requirements of each evidence task are analyzed, and an expansion node is determined; In specific implementations, the preset load threshold represents the critical value at which resource load becomes excessively high and can be set as needed. When the resource load exceeds the preset load threshold, resource scheduling is required. Therefore, the map type, terrain complexity, and evidence requirements of each evidence-gathering task can be analyzed in order to more accurately assess the specific resource requirements of each task. For example, some map patches may be located in remote areas and require personnel with special skills to conduct field investigations; while certain areas with complex terrain may require additional equipment or time to complete the evidence. Through detailed analysis, the system can more accurately determine which tasks require priority resource scheduling and which tasks can be appropriately delayed.

[0054] Identifying expansion nodes is a key step in intelligent resource scheduling. These can include additional compute nodes, storage nodes, or bandwidth resources. These expansion nodes can include adding field personnel, deploying specialized equipment, or extending work hours. Based on analyzed resource requirements and current resource status, the system intelligently selects the optimal expansion node solution to ensure rational resource allocation and efficient utilization. This process not only improves resource scheduling flexibility but also ensures high-quality completion of evidence collection tasks.

[0055] The task resource requirement coefficient is calculated as f(pattern type, terrain complexity, and evidence requirement). The patch complexity coefficient assigns a complexity coefficient to each patch type, with more complex patches requiring more resources. The patch complexity coefficient is calculated as: base complexity × geographic factor coefficient. Similarly, terrain complexity can be quantified using a coefficient, with complex terrain having a larger coefficient and simple terrain having a smaller coefficient. The terrain complexity coefficient is calculated as: terrain type coefficient × regional scale coefficient.

[0056] Step A24: performing resource scheduling for the evidence task configuration according to the patch type, the terrain complexity, the evidence requirement, and the extension node.

[0057] Finally, resource scheduling is performed based on the patch type, terrain complexity, evidence requirements, and expansion nodes. This process involves complex algorithms and models to ensure accurate and efficient scheduling. Through intelligent resource scheduling, the system can maximize the efficiency and quality of evidence tasks within limited resources, providing strong support for the rational development and utilization of natural resources.

[0058] By dynamically matching task requirements with resource status, efficient coordination of manpower, equipment, and data is achieved. A spatial clustering algorithm is used for the distribution rules of field evidence patches. Adjacent patches are logically aggregated based on coordinates to reduce field travel distances. When the volume of evidence collection tasks at a given time is too large, the system can elastically scale up and down, expanding nodes in seconds. Optimal resource matching analyzes task attributes (patch type, terrain complexity, evidence requirements) and resource status (personnel location, equipment load, skill tags) in real time, optimizing matching strategies through algorithms to reduce operational response latency. For the parallel distribution of large-scale field evidence patches across the province on a single day, the engine utilizes a parallel processing mechanism, splitting patch sets and performing multi-threaded synchronous processing. Dynamic batch processing distributes 50-100 patches per batch to avoid overloading a single node, and automatically increases or decreases processing nodes based on queue accumulation.

[0059] This embodiment provides a method for generating on-site evidence collection tasks for natural resources. It automates the entire process from user request to task generation, reducing manual operation and intervention, and significantly improving the efficiency and accuracy of task generation. Users simply provide a setup request, and the system automatically parses, queries, selects, and configures relevant data and templates, greatly simplifying the complex task creation process. By extracting corresponding data from a pre-set evidence collection database and configuring the task based on pre-set templates, the generated evidence collection tasks can be ensured to meet standardized requirements, improving task accuracy and consistency and avoiding errors or omissions introduced by manual operation. Flexible configuration of multiple aspects of the task is supported, including basic task information, workflows, survey fields, forms, and personnel management. This allows different task requirements to be adapted through configuration adjustments, meeting diverse evidence collection scenarios and ensuring the platform's applicability and versatility. The platform's visual setup allows users to intuitively build and manage evidence collection tasks, enhancing the user experience. Through a graphical interface, users can more easily design and adjust tasks to suit different usage needs and scenarios. Automated processes and template selection reduce reliance on manual labor, avoid bias caused by human factors, and improve system reliability and stability.

[0060] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 3 , step S50 includes steps S501 to S503: Step S501: Obtain basic information of the evidence task based on the evidence data, wherein the basic information of the evidence task includes the name of the evidence task, the area of ​​the evidence task, the description of the evidence task, the business to which the evidence task belongs, and the project management information of the evidence task.

[0061] It should be noted that when configuring the basic information of a proof task, you can first obtain this information from the proof data, thereby providing the ability to configure basic task information for business systems and application development. You can set the task name, task area, description, business to which it belongs, and whether it is managed as a project.

[0062] The name of the evidence task is the title or name of the task, which is usually used to describe the purpose and content of the task concisely and clearly. The task area is the administrative division involved in the field evidence collection. It supports the definition of task areas as provinces, cities, and counties. One or more districts, counties, and towns can be selected as task areas. The description of the evidence task is a detailed description of the task, including the background, purpose, and specific requirements of the task. The business to which the evidence task belongs includes which business the task is related to, such as "resource management" and "environmental monitoring". The project management information of the evidence task is project management information about the task, which may include the project's time schedule, person in charge, budget, and other content.

[0063] The calculation of the evidence task area may need to be derived based on administrative divisions or geographic information. Assuming that the target area can be defined by latitude and longitude ranges:

[0064] Among them, lat1 and lat2 are the ranges of latitude, long1 and long2 are the ranges of longitude, and dA is a small area element.

[0065] Step S502: query the corresponding component on the target task template to set the evidence task name, the evidence task area, the evidence task description, and the business to which the evidence task belongs.

[0066] In practice, visual construction is the core of the agile construction engine for evidence-gathering scenarios. It encapsulates complex business logic into graphical components and modules, allowing users to drag and drop these components to build field evidence-gathering tasks. Within this visual construction environment, users can design the interface layout of evidence-gathering tasks by dragging and dropping interface elements, and configure the appearance and behavior of investigative information by configuring properties. The platform also provides a rich set of logical components, such as button click events, data query, data processing, and results submission. Users simply associate these logical components with interface elements to implement complex interactive functions.

[0067] Therefore, after determining the evidence task name, evidence task area, evidence task description, and the business to which the evidence task belongs, the corresponding components can be queried and displayed, allowing the user to set the content of the basic information of the evidence task by dragging and connecting these components.

[0068] Step S503: query the corresponding component on the target task template to set the unit of the evidence object for project-based management of the evidence task, complete the configuration of the basic information of the evidence task, and generate a natural resource field evidence task. The unit of the evidence object includes map spots and projects.

[0069] It can be understood that project-based management mainly provides map-based evidence and project-based evidence-giving capabilities for different evidence objects, such as map-based evidence and project-based evidence. Examples of map-based evidence include routine monitoring and daily change investigations, while examples of project-based evidence include land consolidation and balance projects. When project-based management is used, the first thing is the project, and then the specific map-based evidence within the project.

[0070] Therefore, the target task template can be used to query the unit component of the evidence object and set the unit of the evidence object. In the target task template, two main units of evidence object are set: Parcel: In a geographic information system (GIS), a parcel generally represents the basic unit of geographic area, usually a polygon demarcating a certain area. Project: A project unit generally corresponds to a larger task unit and may involve multiple parcel areas. By combining the basic information obtained in step S501 and the template settings in step S502, combined with the requirements of project-based management, a complete natural resource field evidence task is ultimately generated.

[0071] After configuration is complete, you can perform a consistency check to ensure that each field is correctly filled in. For example, check whether the task area matches the task name or task description to ensure information consistency.

[0072] Verification formula = ∑(task description consistency, region and name consistency, business matching) It should be noted that if the result is not 0, adjustments need to be made or a configuration error should be reported.

[0073] This embodiment obtains basic information of the evidence task based on the evidence data, and the basic information of the evidence task includes the name of the evidence task, the area of ​​the evidence task, the description of the evidence task, the business to which the evidence task belongs, and the project management information of the evidence task; queries the corresponding components on the target task template to set the name of the evidence task, the area of ​​the evidence task, the description of the evidence task, and the business to which the evidence task belongs; queries the corresponding components on the target task template to set the unit of the evidence object of the project management of the evidence task, completes the configuration of the basic information of the evidence task, and generates a natural resource field evidence task, and the unit of the evidence object includes map spots and projects.

[0074] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as those in the above embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 4 , step S50 includes steps S504 to S506: Step S504: obtaining the current workflow of the evidence presentation service according to the evidence presentation data.

[0075] In practice, the current workflow for evidence collection may involve multiple stages and participants, such as field investigation, data entry, preliminary review, re-review, and final review. Each stage has specific responsibilities and requirements to ensure the accuracy and compliance of evidence collection tasks. Based on the evidence collection data, the system can automatically identify and extract key information about the current workflow, such as the number of stages, participants in each stage, and the time required. This information provides the basis for subsequent workflow configuration.

[0076] Step S505: querying the corresponding component configuration minimum review unit on the target task template based on the current workflow.

[0077] On the target task template, the system will query and display the corresponding components based on the current workflow. These components represent the various steps and participants in the workflow, and users can drag and drop and connect these components to build the workflow.

[0078] The minimum audit unit is a key step in the workflow. It is responsible for conducting self-inspection, rectification, and review of the evidence provided after the task is completed. Based on the current workflow, the system can determine the level and responsibilities of the minimum audit unit and query and display the corresponding components in the target task template.

[0079] Step S506: Query the corresponding components on the target task template to configure the self-inspection and rectification rules, review rules, audit process rules and return process of the minimum audit unit after the work is completed, complete the evidence task workflow configuration, and generate a natural resource field evidence task.

[0080] After setting up the minimum audit unit, the system also requires configuring self-inspection and rectification rules, review rules, audit process rules, and a rejection process. These rules ensure a smooth and compliant workflow and prevent errors and omissions. Users can set these rules by dragging and dropping and configuring properties on the target task template.

[0081] For example, self-inspection and rectification rules may require investigators to conduct self-inspections and rectifications before submitting evidence to ensure the accuracy and completeness of the data. Review rules may require auditors to review the evidence provided by investigators to ensure data compliance and consistency. Review process rules may define the responsibilities and approval processes for auditors at different levels. The return process defines how to return evidence to investigators for reinvestigation and rectification when it does not meet the requirements. Through detailed workflow configuration, the system can generate a complete natural resource field evidence task and ensure its accuracy and compliance. This greatly improves the efficiency and quality of evidence task execution, providing strong support for the rational development and utilization of natural resources.

[0082] Business process configuration capabilities are provided for different workflows of evidence-gathering businesses. Based on your own needs and business circumstances, you can independently configure the minimum review unit, whether it is the county, township, or village level. Whether the county level is required to conduct self-inspection and rectification after field work is completed, whether there is a review process for users at all levels after the review, how the review process is defined, whether it is reviewed by the provincial, municipal, and county levels, or whether the county level directly submits the review to the municipal level, whether the township level participates in the review process, whether the review is rejected, and other issues can be quickly realized through configuration.

[0083] In a feasible implementation, the generation of the evidence task also includes the configuration of the survey field. Therefore, step S50 may also include: obtaining different information collection requirements based on the evidence data; querying the corresponding components on the target task template based on different information collection requirements to configure the filling rules of the survey field, the logical relationship of the survey field, the reference attribute field and the field selection items, completing the survey field configuration of the evidence task, and generating the natural resource field evidence task.

[0084] It's important to note that survey fields are a crucial component of evidence collection tasks, collecting the various information needed for field investigations. In practice, different evidence collection tasks may require different information, such as land type, vegetation cover, and building conditions. Therefore, when generating evidence collection tasks, these requirements must be determined based on the evidence data.

[0085] After determining the information collection requirements, the system will query the target task template for the corresponding components. These components represent different survey fields. Users can set the field filling rules, logical relationships, reference attribute fields, and field selection options by dragging and configuring properties. Filling rules define the input format and restrictions of fields, such as numbers, text, dates, etc. Logical relationships are used to set associations and constraints between fields to ensure data accuracy and consistency. Reference attribute fields provide a reference range or default value for field values, which helps reduce input errors. Field selection options list the possible values ​​of the field, making it easier for users to quickly select.

[0086] Through meticulous investigation field configuration, the system generates a practical and easy-to-use evidence collection task. This significantly improves the efficiency and accuracy of data collection, providing strong support for subsequent data analysis and utilization. Furthermore, users can flexibly configure and adjust investigation fields based on their own needs and business circumstances to accommodate diverse evidence collection scenarios and requirements.

[0087] To meet the diverse needs of field evidence collection, on-demand field field configuration is provided. This includes determining whether fields being investigated are required, whether field entry thresholds are required (e.g., a threshold greater than or equal to 0), whether fields are logically related (e.g., after field A is filled, field B must be filled in or left blank), whether fields have data dictionaries for easy selection during fieldwork, whether fields are rarefied and mapped, and which attribute fields field personnel can reference. Based on survey field configuration, you can quickly collect first-hand, accurate, and reliable field information for decision-making.

[0088] In a feasible implementation, the generation of the evidence task also includes the configuration of the page form, so step S50 also includes: obtaining business information based on the evidence data; querying the corresponding component on the target task template according to the information type of the business information to classify and display the layout of the business information, completing the evidence task page form configuration, and generating the natural resource field evidence task.

[0089] Page form configuration organizes and lays out business information. Users can categorize information by type and present it in separate interfaces. Page forms are a key interface for user interaction during evidence presentation tasks, displaying various task information and operational options. In practice, different evidence presentation tasks may involve different types of business information, such as land area, vegetation type, and building number. Therefore, when generating evidence presentation tasks, it is necessary to determine these information types based on the evidence data. After determining the information type, the system searches the target task template for the corresponding components and categorizes and configures the page form layout based on the characteristics of these information types. These components represent different elements on the page form, such as text boxes, drop-down lists, and checkboxes. Users can configure the layout, display mode, and interactive behavior of these elements by dragging and dropping them and configuring their properties. Layout settings define the overall structure of the page form and the arrangement of its elements, ensuring clear presentation and easy operation. Display mode sets the display format and style of elements, such as font, color, and size. Interaction behavior defines how users interact with the page form, such as clicking, typing, and selecting.

[0090] Through meticulous page form configuration, the system generates a practical and easy-to-use evidence presentation task that meets actual needs. This significantly improves user interaction efficiency and experience, providing strong support for subsequent data entry and review. Furthermore, users can flexibly configure and adjust page forms based on their own needs and business circumstances to accommodate different evidence presentation scenarios and requirements. Flexible form configuration is provided to meet the page form display requirements of different evidence presentation tasks. Configuration can quickly determine whether form fields are required, how to define the field display format, whether multiple fields are associated with each other, whether form fields have order requirements, whether to display them in pages, and more. Based on page form configuration, an evidence presentation task interface that meets business needs can be quickly built, facilitating subsequent field investigations and internal audits. Verification and audit information can be arranged in a flexible format across both the web and mobile interfaces. This feature allows users to flexibly and independently layout business information, making business application and management smoother, faster, and more efficient, saving time and effort while avoiding the additional development required under traditional models.

[0091] In a feasible implementation, the generation of evidence tasks also includes the configuration of field personnel. By providing field personnel configuration capabilities for field tasks, for example, which levels of users are required to participate in a certain business, which department is required to participate, which technical support unit is required to participate, how user permissions are divided, whether a user can be responsible for multiple businesses, and whether a working group needs to be created, the personnel structure restrictions are broken. Through user system configuration, data security can be guaranteed to prevent other users from viewing business results, and business results can be classified to avoid users having an overly complex system user experience.

[0092] It also provides evidence management for various configuration tasks, including uploading field maps, viewing map lists / details / maps, and viewing, reviewing, and downloading field evidence results. Users can add verification tasks and select the area, granularity (minimum verification unit), and data distribution mode. This feature allows users to independently create, maintain, and delete tasks. It also supports grouped management of multiple tasks, meeting the needs of running a large number of tasks in parallel. This feature enables verification work to be highly autonomous, flexible, convenient, and operational.

[0093] The configuration of the task dictionary supports dictionary search query, dictionary addition, editing, deletion and other functions. Dictionaries can be added according to business needs, and the dictionary display value, storage value and serial number can be set. After the dictionary is configured in the Jiangxi Cloud mobile and web fields, the corresponding dictionary display value can be displayed.

[0094] like Figure 5 As shown, Figure 5 This is a conceptual model definition diagram. This embodiment can also design a monitoring and supervision task conceptual model in advance. The design of the investigation, monitoring and supervision task conceptual model refers to abstracting and generalizing the investigation and monitoring objects based on the clear investigation and evidence collection task requirements. It mainly includes clarifying the entity objects, object expression methods and object association relationships. The basic information definition, structure definition, review process definition, and personnel definition organization and relationship are realized through the entity object model. Figure 6 As shown, Figure 6 Build a scene diagram for visualization, including business model components, filter item components, button area components, table column components and other areas. When configuring tasks, you can configure them according to the components for rendering and display.

[0095] This embodiment obtains the current workflow for the evidence presentation task based on the evidence presentation data; based on the current workflow, queries the target task template for the corresponding component to configure the minimum audit unit; and queries the target task template for the corresponding component to configure the self-inspection and rectification rules, review rules, audit process rules, and return process for the minimum audit unit after the work is completed, thereby completing the configuration of the evidence presentation task workflow and generating a natural resource field evidence presentation task. Through meticulous evidence presentation task configuration, the system can generate an evidence presentation task that meets actual needs and is easy to operate. This significantly improves the efficiency and accuracy of data collection, providing strong support for subsequent data analysis and utilization. Users can flexibly configure and adjust evidence presentation tasks based on their own needs and business circumstances to adapt to different evidence presentation scenarios and requirements. By providing flexible page form configuration capabilities, a practical and easy-to-use evidence presentation task interface can be generated. This significantly improves the efficiency and user experience of user interaction, providing strong support for subsequent data entry and review. Furthermore, users can flexibly configure and adjust page forms based on their own needs and business circumstances to meet different evidence presentation requirements.

[0096] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction and will not be described in detail later. Figure 7 , after step S50, further comprising steps S51-S52: Step S51: After the natural resource on-site evidence task is generated, a business application interface is created.

[0097] It should be noted that the verification rules of the "Technical Specifications for Land Change Survey" can be built into the engine, and the compliance and accuracy of the evidence data can be ensured through the real-time rule interface and combined with intelligent quality inspection.

[0098] The business application interface is used to interact with users. When submitting field investigation and evidence results, it automatically intercepts illegal submissions (such as missing positioning watermarks, digital certificates, etc.). The verification rules mainly include: basic compliance verification rules, business logic verification rules, intelligent quality inspection enhancement rules, closed-loop disposal rules, etc.

[0099] Step S52: Send the natural resource on-site evidence task to the user, so that the user enters the business application interface to monitor and verify the natural resource on-site evidence task.

[0100] In specific implementation, the natural resource field evidence task can be sent to the user's mobile terminal, so that the user can enter the business application interface to check and verify the generated evidence task. The communication between the engine's web terminal and the mobile terminal mainly adopts the HTTP protocol. The HTTP protocol is characterized by simple and flexible design and supports the transmission of data in multiple formats.

[0101] The core features of HTTP are as follows: 1. Stateless protocol: By default, previous requests or session information is not recorded (state management can be achieved later through technologies such as cookies and sessions). 2. Based on the request-response model, the client sends a request (Request) and the server returns a response (Response). 3. Supports multiple methods: such as GET (get resources), POST (submit data), PUT (update resources), DELETE (delete resources), etc. 4. Strong scalability: Additional information is passed through request headers / response headers (Headers), supporting functions such as caching, compression, and authentication. How HTTP works: 1. Establish a connection. The client connects to the server through TCP / IP (default port 80) (HTTP / 1.1 defaults to a persistent connection, and HTTP / 2 supports multiplexing). 2. Send a request. The request message includes: (1) Request line: method (such as GET), URL (such as / index.html), protocol version (such as HTTP / 1.1). (2) Request header: meta information such as Host, User-Agent, Accept. (3) Request body (optional): such as form data submitted by POST. 3. The server processes and returns a response. The response message includes: (1) Status line: status code (such as 200 OK), protocol version. (2) Response header: Content-Type, Content-Length, etc. (3) Response body: actual data (such as HTML, JSON). (4) Close the connection. (Disconnect the TCP connection if it is not a persistent connection).

[0102] In a feasible implementation, the evidence task can also be updated. Therefore, after step S50, it also includes: obtaining updated evidence specifications, updated quality control requirements and preset task instructions based on the natural resource field evidence task; sending the updated evidence specifications, the updated quality control requirements and the preset task instructions to the corresponding user through the mobile terminal, so that the user can adjust the natural resource field evidence task based on the updated evidence specifications, the updated quality control requirements and the preset task instructions.

[0103] It should be noted that preset task instructions are task-specific and can be set based on specific tasks. The latest evidence standards, quality control requirements, or specific task instructions can be dynamically distributed to mobile operators, enabling real-time updates and execution control of evidence rules. This mechanism primarily relies on the cloud-based rule configuration and distribution of the construction engine, and the real-time reception and execution of rules on the mobile terminal. Real-time rule injection, without affecting the survey progress or the evidence already provided, has become a core means of ensuring the "accuracy, efficiency, and compliance" of land surveys.

[0104] In specific implementation, the investigation tasks can be automatically expanded according to different departments and different businesses, such as Figure 8 As shown, Figure 8 The diagram automatically expands for investigation and evidence collection tasks. A custom configuration engine is used to configure the audit flow, business flow, survey field configuration, and user system configuration. Audit flow configuration includes: whether the county level conducts self-inspection? Is there a review after the audit? Review at the county, city, and provincial levels? Does the township level participate in the review? Will the review be rejected if it fails? Business flow configuration includes: whether photographs are required? Whether the ledger needs to be exported? Is field work required for each image patch? Whether the task is issued in a distribution or collection mode? Survey field configuration includes: whether fields are required? Do fields have entry thresholds? Do fields have logical relationships? Does the field have a data dictionary? Are fields thinned and mapped? User system configuration includes: which levels of users are involved? How are user permissions divided? Can a user be responsible for multiple tasks? Is it necessary to create a working group? This provides business support for routine monitoring, farmland protection, satellite image enforcement, change investigations, and post-supply supervision.

[0105] This embodiment creates a business application interface after the natural resource field evidence task is generated; the natural resource field evidence task is sent to the user, so that the user enters the business application interface to monitor and verify the natural resource field evidence task. The creation of the business application interface enables users to interact with the system conveniently, especially when submitting field survey evidence results, the system can automatically intercept illegal submissions to ensure the compliance and accuracy of the evidence data. This function greatly improves the quality and credibility of the data, and lays a solid foundation for subsequent data analysis and utilization. It is completed through the coordination of cloud-based rule configuration and issuance, and real-time reception and execution on the mobile terminal, which enables the real-time update and execution of evidence rules. This mechanism ensures the "precision, efficiency, and compliance" of land surveys and improves the quality and efficiency of survey work.

[0106] For example, in order to help understand the implementation process of the method for generating a natural resource field evidence task obtained by combining this embodiment with the above embodiment 1, please refer to Figure 9 , Figure 9 A brief flow chart of a method for generating a natural resource field evidence task is provided. Specifically: first, define the basic information of the evidence task, including: the business to which it belongs, the task area, and the task name; then define the field process, including: the review process, the review opinion type, and the return flow; then define the field field, including: the field field name, the field field type, and the drop-down selection items; thereby configure the field form, including: field configuration, drop-down configuration, search configuration, and display configuration; and define field personnel, such as field worker 1, field worker 2, and field worker 3; and perform field task management, including: map uploading, task assignment, result viewing, and result review; thereby generating a field evidence task and conducting field evidence.

[0107] It should be noted that the above examples are only used to understand this application and do not constitute a limitation on the method for generating natural resource field evidence tasks in this application. More simple transformations based on this technical concept are all within the scope of protection of this application.

[0108] This application also provides a natural resource field evidence task generation device, please refer to Figure 10 The natural resource on-site evidence task generation device includes: The response module 10 is used to respond to the user's request to build a natural resource field evidence task; The parsing module 20 is used to parse the construction request and determine the evidence task information to be generated; A query module 30 is configured to query corresponding evidence data from a preset evidence database according to the evidence task information to be generated; A selection module 40 is configured to select a target task template from a preset template repository based on the evidence data; Configuration module 50 is used to configure the evidence data on the target task template to generate a natural resource field evidence task. The evidence task configuration includes one or more of the following: task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

[0109] The natural resource field evidence task generation device provided in this application utilizes the natural resource field evidence task generation method described in the aforementioned embodiment, and can address the current technical issues of low efficiency and accuracy in natural resource field evidence task generation. Compared to the prior art, the natural resource field evidence task generation device provided in this application has the same beneficial effects as the natural resource field evidence task generation method described in the aforementioned embodiment, and the other technical features of the natural resource field evidence task generation device are the same as those disclosed in the aforementioned embodiment method, and are not further described here.

[0110] The present application provides a natural resource field evidence task generation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the natural resource field evidence task generation method in the above-mentioned embodiment one.

[0111] Reference below Figure 11, which shows a schematic diagram of the structure of a natural resource field evidence task generation device suitable for implementing embodiments of the present application. The natural resource field evidence task generation device in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 11 The natural resource field evidence task generation device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0112] like Figure 11 As shown, the natural resource field evidence task generation device may include a processing device 1001 (e.g., a central processing unit, graphics processing unit, etc.), which can perform various appropriate actions and processes based on programs stored in ROM (Read Only Memory) 1002 or programs loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the natural resource field evidence task generation device. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to the I / O interface 1006: input devices 1007, such as a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008, such as an LCD (Liquid Crystal Display), speaker, vibrator, etc.; storage devices 1003, such as a magnetic tape, hard disk, etc.; and communication devices 1009. Communication devices 1009 may allow the natural resource field evidence task generation device to communicate with other devices wirelessly or by wire to exchange data. While the figure shows a natural resource field evidence task generation device with various systems, it should be understood that implementation or presence of all the illustrated systems is not required. More or fewer systems may alternatively be implemented or present.

[0113] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0114] The natural resource field evidence task generation device provided in this application utilizes the natural resource field evidence task generation method described in the aforementioned embodiment, and can address the current technical issues of low efficiency and accuracy in natural resource field evidence task generation. Compared to the prior art, the beneficial effects of the natural resource field evidence task generation device provided in this application are the same as those of the natural resource field evidence task generation method described in the aforementioned embodiment. The other technical features of this natural resource field evidence task generation device are the same as those disclosed in the aforementioned embodiment and are not further elaborated here.

[0115] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0116] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0117] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, and the computer-readable program instructions are used to execute the natural resource field evidence task generation method in the above-mentioned embodiment.

[0118] The computer-readable storage medium provided herein may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory or Flash memory), optical fiber, CD-ROM (CD-Read Only Memory), optical storage device, magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including, but not limited to, wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0119] The above-mentioned computer-readable storage medium may be included in the natural resource field evidence task generation device; or it may exist independently without being assembled into the natural resource field evidence task generation device.

[0120] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the natural resource field evidence task generation device, the natural resource field evidence task generation device is enabled to: respond to the user's request to build a natural resource field evidence task; parse the building request to determine the evidence task information to be generated; query the corresponding evidence data from the preset evidence database according to the evidence task information to be generated; select the target task template from the preset template warehouse according to the evidence data; configure the evidence task on the target task template with the evidence data to generate a natural resource field evidence task, and the evidence task configuration includes one or more of the following: task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration and task dictionary management configuration.

[0121] The computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a LAN (Local Area Network) or a WAN (Wide Area Network), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0122] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0123] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0124] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned method for generating on-site evidence collection tasks for natural resources. This computer-readable storage medium can address the current technical issues of low efficiency and accuracy in generating on-site evidence collection tasks for natural resources. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the method for generating on-site evidence collection tasks for natural resources provided in the aforementioned embodiments, and are not further elaborated here.

[0125] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned natural resource field evidence task generation method.

[0126] The computer program product provided in this application can address the current technical issues of low efficiency and accuracy in generating natural resource field evidence tasks. Compared to the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the natural resource field evidence task generation method provided in the aforementioned embodiment, and are not further elaborated here.

[0127] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for generating a natural resource field evidence task, characterized in that: The method for generating on-site evidence tasks for natural resources is applied to a visualization platform for building evidence scenarios, wherein a preset evidence database and a preset template warehouse are stored on the visualization platform for building evidence scenarios; The method for generating a natural resource on-site evidence task includes: Responding to user requests for establishing natural resource field evidence tasks; Parsing the construction request to determine the evidence task information to be generated; According to the information of the evidence task to be generated, corresponding evidence data is searched from a preset evidence database; Selecting a target task template from a preset template warehouse based on the evidence data; The evidence data is configured as an evidence task on the target task template to generate a natural resource field evidence task. The evidence task configuration includes one or more of the following: task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

2. The method according to claim 1, wherein The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: Obtain basic information of the evidence task based on the evidence data, wherein the basic information includes the name of the evidence task, the area of ​​the evidence task, the description of the evidence task, the business to which the evidence task belongs, and the project management information of the evidence task; Query the corresponding component on the target task template to set the evidence task name, the evidence task area, the evidence task description, and the business to which the evidence task belongs; Query the corresponding components on the target task template to set the units of the evidence objects for project-based management of the evidence tasks, complete the configuration of the basic information of the evidence tasks, and generate the natural resource field evidence tasks. The units of the evidence objects include map spots and projects.

3. The method according to claim 1, wherein The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: Obtaining the current workflow of the evidence presentation business based on the evidence presentation data; Querying the corresponding component configuration minimum review unit on the target task template based on the current workflow; Query the corresponding components on the target task template to configure the self-inspection and rectification rules, review rules, audit process rules and return process of the minimum audit unit after the work is completed, complete the evidence task workflow configuration, and generate the natural resource field evidence task.

4. The method according to claim 1, wherein The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: Obtaining different information collection requirements based on the evidence data; Based on different information collection requirements, the corresponding components are queried on the target task template to configure the filling rules of the survey fields, the logical relationship of the survey fields, the reference attribute fields and the field selection items, complete the survey field configuration of the evidence task, and generate the natural resource field evidence task.

5. The method according to claim 1, wherein The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: Obtaining business information based on the evidence data; According to the information type of the business information, the corresponding component is queried on the target task template to classify the business information and set the layout for display, complete the form configuration of the evidence task page, and generate the natural resource field evidence task.

6. The method according to claim 1, wherein The step of parsing the construction request and determining the evidence task information to be generated includes: Extract keywords from the construction request to obtain the name of the evidence task to be generated and the task area; Encoding the construction request to obtain a text vector representation; Input the text vector representation into the classifier to predict the task type and obtain the type of evidence task to be generated; Parsing the construction request using rule matching and priority reasoning to obtain the priority of the evidence task type to be generated; The name of the task to be generated, the task area, the type of the task to be generated and the priority of the task to be generated are used as the information of the task to be generated.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: During the configuration of the evidence task, obtain the current status of the resource; Obtaining resource load according to the current state of the resource; When the resource load is greater than a preset load threshold, analyzing the patch type, terrain complexity, and evidence requirements of each evidence task, and determining an expansion node; Resources are scheduled for the evidence task configuration according to the patch type, the terrain complexity, the evidence requirement, and the extension node.

8. The method according to any one of claims 1 to 6, characterized in that The method further comprises: After the natural resources field evidence task is generated, a business application interface is created; The natural resource on-site evidence task is sent to the user, so that the user enters the business application interface to monitor and verify the natural resource on-site evidence task.

9. The method according to any one of claims 1 to 6, characterized in that The method further comprises: Based on the natural resource field evidence collection tasks, updated evidence collection standards, updated quality control requirements and preset task instructions were obtained; The updated evidence specifications, the updated quality control requirements and the preset task instructions are sent to the corresponding user through the mobile terminal, so that the user can adjust the natural resource field evidence task based on the updated evidence specifications, the updated quality control requirements and the preset task instructions.

10. A natural resource field evidence task generation device, characterized in that: The device comprises: A response module, used to respond to a user's request to build a natural resource field evidence task; A parsing module, configured to parse the building request and determine information of the evidence task to be generated; A query module, configured to query corresponding evidence data from a preset evidence database according to the evidence task information to be generated; A selection module, configured to select a target task template from a preset template repository based on the evidence data; A configuration module is used to configure the evidence data on the target task template to generate a natural resource field evidence task. The evidence task configuration includes one or more of the following: task basic information configuration, evidence task workflow configuration, survey field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

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