Natural resource field evidence task generation method and device

Abstract

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

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of task generation, in particular to a natural resource field evidence task generation method and device. BACKGROUND

[0002] In the existing natural resource management, field evidence tasks usually need to be manually configured and set, which not only consumes time and effort, but also is prone to errors. The traditional way often relies on manual operation of managers, from selecting evidence data, configuring task templates to generating the final evidence task, the whole process is cumbersome and inefficient. In addition, due to the intervention of manual operation, there may be differences in understanding and execution between different managers, making it difficult to guarantee the quality and consistency of the evidence task. SUMMARY

[0003] The main purpose of the present application is to provide a natural resource field evidence task generation method and device, aiming at solving the technical problems of low efficiency and accuracy of current natural resource field evidence task generation.

[0004] To achieve the above-mentioned purpose, the present application provides a natural resource field evidence task generation method, which is applied to an evidence scene visual construction platform, and a preset evidence database and a preset template warehouse are stored on the evidence scene visual construction platform;

[0005] The natural resource field evidence task generation method comprises:

[0006] In response to a user's request for building a natural resource field evidence task;

[0007] The build request is parsed to determine the to-be-generated evidence task information;

[0008] According to the to-be-generated evidence task information, corresponding evidence data is queried from the preset evidence database;

[0009] According to the evidence data, a target task template is selected from the preset template warehouse;

[0010] The evidence data is configured on the target task template to generate a natural resource field evidence task, and the evidence task configuration includes one or more of task basic information configuration, evidence task workflow configuration, investigation field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration and task dictionary management configuration.

[0011] In addition, to achieve the above-mentioned purpose, the present application also provides a natural resource field evidence task generation device, which comprises:

[0012] A response module is configured to respond to a user request for building a natural resource field evidence task;

[0013] An analysis module is configured to analyze the request and determine evidence task information to be generated;

[0014] A query module is configured to query corresponding evidence data from a preset evidence database according to the evidence task information to be generated;

[0015] A selection module is configured to select a target task template from a preset template warehouse according to the evidence data;

[0016] A configuration module is configured to configure the evidence data on the target task template to generate a natural resource field evidence task, and the evidence task configuration includes one or more of task basic information configuration, evidence task workflow configuration, investigation field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

[0017] In addition, to achieve the above object, the present application also provides a natural resource field evidence task generation device, which comprises a memory, a processor and a computer program stored on the memory and executable 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.

[0018] In addition, to achieve the above object, the present application also provides a storage medium, which is a computer readable storage medium, and a computer program is stored on the storage medium, and the computer program is executed by a processor to implement the steps of the natural resource field evidence task generation method as described above.

[0019] In addition, to achieve the above object, the present application also provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the natural resource field evidence task generation method as described above.

[0020] One or more technical solutions proposed in the present application automate the entire process from user request to task generation, reduce manual operation and intervention, and greatly improve the efficiency and accuracy of task generation. The user only needs to provide a building request, and the system can automatically analyze, query, select and configure related data and templates, greatly simplifying the complex process of task building. By extracting corresponding data from the preset evidence database and combining the preset templates for task configuration, it can ensure that the generated evidence task meets the standardization requirements, improve the accuracy and consistency of the task, and avoid errors or omissions introduced by manual operation; support flexible configuration of multiple aspects of the task, including basic information of the task, workflow, investigation field, form, personnel management, etc. In this way, different task requirements can be adapted by adjusting the configuration to meet various evidence scenarios and ensure the applicability and versatility of the platform. The visual building of the platform enables users to intuitively construct and manage evidence tasks, improving user experience. Through the graphical interface, users can more conveniently design and adjust tasks to adapt to different usage requirements and scenarios. Through the automated process and template selection, the dependence on manual operation is reduced, avoiding the deviation caused by human factors and improving the reliability and stability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without creative labor.

[0023] Figure 1 The flowchart provided for the natural resource field evidence task generation method embodiment one of the present application;

[0024] Figure 2 The natural resource field evidence scene agile construction overall architecture schematic diagram provided for the natural resource field evidence task generation method one embodiment of the present application;

[0025] Figure 3 The flowchart provided for the natural resource field evidence task generation method embodiment two of the present application;

[0026] Figure 4 The flowchart provided for the natural resource field evidence task generation method embodiment three of the present application;

[0027] Figure 5Definition diagram of conceptual model provided for an embodiment of the natural resource field evidence generation method of the present application;

[0028] Figure 6 Visualized building scene diagram provided for an embodiment of the natural resource field evidence generation method of the present application;

[0029] Figure 7 Flow diagram provided for the fourth embodiment of the natural resource field evidence generation method of the present application;

[0030] Figure 8 Investigation evidence task automatic expansion diagram provided for an embodiment of the natural resource field evidence generation method of the present application;

[0031] Figure 9 Brief flow diagram provided for an embodiment of the natural resource field evidence generation method of the present application;

[0032] Figure 10 Module structure diagram of the natural resource field evidence generation device of the embodiment of the present application;

[0033] Figure 11 Device structure diagram of the hardware running environment involved in the natural resource field evidence generation method of the embodiment of the present application.

[0034] The purpose implementation, functional features and advantages of the present application will be further explained in combination with the embodiments and with reference to the drawings. DETAILED DESCRIPTION

[0035] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application, and are not used to limit the present application.

[0036] In order to better understand the technical solutions of the present application, the following will be described in detail in combination with the drawings of the specification and specific embodiments.

[0037] The main solution of the embodiment of the application is that the natural resource field evidence collection task generation method is applied to an evidence collection scene visualized building platform, the evidence collection scene visualized building platform stores a preset evidence collection database and a preset template warehouse; the natural resource field evidence collection task generation method comprises the following steps: responding to a building request of a user for a natural resource field evidence collection task; analyzing the building request to determine to-be-generated evidence collection task information; querying corresponding evidence collection data from the preset evidence collection database according to the to-be-generated evidence collection task information; selecting a target task template from the preset template warehouse according to the evidence collection data; and performing evidence collection task configuration on the target task template by using the evidence collection data to generate a natural resource field evidence collection task, wherein the evidence collection task configuration comprises one or more of task basic information configuration, evidence collection task workflow configuration, investigation field configuration, page form configuration, evidence collection task personnel configuration, evidence collection task management configuration, and task dictionary management configuration.

[0038] The prior art field evidence collection task usually needs to be manually configured and set, and the whole process is tedious and inefficient.

[0039] The application provides a solution, and proposes an evidence collection scene agile building mode combining standardization and customization. For a general investigation evidence collection task, an embedded evidence collection task template can be directly selected to realize evidence collection task creation. When a general evidence collection template cannot meet the evidence collection task, a "zero code" evidence collection scene construction engine can be used to realize evidence collection task customization, and a set of universal front-end and back-end configuration architecture and visualized configuration process are formed to allow business personnel to customize field tasks on demand. The evidence collection scene building technology combining standardization and customization can easily cope with frequent adjustment of evidence collection task types and structures, and for diversified needs, code development is not needed, and only modeling and configuration are needed to realize customized task generation. This process does not need product or field implementation personnel to perform professional configuration, and improves task configuration timeliness.

[0040] It should be noted that the execution subject of the embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone and the like, or an electronic device capable of realizing the above functions, an evidence collection scene visualized building platform and the like. The embodiment and the following embodiments will be described below by taking the evidence collection scene visualized building platform as an example.

[0041] Based on this, the embodiment of the application provides a natural resource field evidence collection task generation method, which is described below with reference to Figure 1 , Figure 1 FIG. 1 is a flowchart of a natural resource field evidence collection task generation method according to a first embodiment of the application.

[0042] The evidence scene visualization building platform stores a preset evidence database and a preset template warehouse.

[0043] It should be noted that the evidence scene visualization building platform in the embodiment is provided in advance with a building engine, has good environmental adaptability, does not need to be developed, can be realized by a technical personnel configuring on a client side, and can support a plurality of investigation task or verification task monitoring requirements. The investigation information includes self-definition, field attribute, association logic, default value, and field value. The web page end and the mobile end show the self-configuration of field content, filtering content, search content, and page form. The self-configuration of business audit link, process, and return, and the flexible configuration of a business user object are included. The evidence scene building engine provides a large number of pre-built modules, templates, and evidence data databases, and a user can directly use the modules, templates, and evidence data to quickly build an evidence task. These modules and templates usually cover common evidence business logic and functions, such as task information, plot structure, investigation content, work personnel, and audit process. The following are several key features of the pre-built modules and templates:

[0044] Functional module: each module is an independent functional unit, and a user can freely combine and configure these modules according to a requirement.

[0045] Template library: the platform usually provides a rich investigation task template library, and a user can select a suitable investigation task template according to a business requirement to quickly combine.

[0046] Customization: although the modules and templates are pre-built, a user can still customize and adjust the general modules according to a requirement.

[0047] In the embodiment, the natural resource field evidence task generation method includes steps S10-S50.

[0048] Step S10: in response to a user's building request for a natural resource field evidence task.

[0049] It should be noted that when the user has a generation request for the natural resource field evidence task, the evidence scene visualization building platform can be operated first. The evidence scene visualization building platform can be deployed on a web page end. The user accesses the evidence scene visualization building platform on the web page end, and thus the building request for the natural resource field evidence task is generated.

[0050] In the natural resource monitoring and supervision work, there are many characteristics such as many monitoring objects, heavy monitoring tasks and tight time requirements. The natural resource field evidence involves many types such as forest and grass wet investigation, routine monitoring, supervision and law enforcement, water resource investigation, land change investigation, farmland protection, land use supervision, farmland satellite supervision, afforestation, use control, satellite law enforcement, and various temporary field tasks or emergency verification requirements. To meet the above requirements, the natural resource field evidence scene agile construction overall architecture is as shown in Figure 2 Figure 2 The development center developer can set up a standardized template in advance, including model definition and job link. The task definition (i.e. what task?) can be determined first, and the field plot upload, field investigation requirement setting, field task allocation and field result audit setting can be performed. The plot structure definition (which plots are adjusted), field definition (which information is collected?), job personnel definition (who performs the field work?), and audit process definition (how to perform the result audit?) are defined. The configuration center is set by the operation and maintenance personnel, and the customized configuration is performed, including configuration tools and configuration content. The configuration content includes task information configuration, plot structure configuration, investigation content configuration, job personnel configuration, and audit process configuration. The task information configuration includes task name, job scope, and department in charge. The plot structure configuration includes plot number, plot location, and spatial position. The investigation content configuration includes which information to fill in, whether it is required, and how many photos to take. The job personnel configuration includes who goes to work, which plots are responsible for, and who is the administrator. The audit process configuration includes the audit department involved, the audit process, and the audit opinion options. The task center is executed by the field personnel, including multi-scene application, such as daily change, routine monitoring, post-supply supervision, land remediation, and emergency field tasks. The evidence scene agile construction engine can build multi-scene applications.

[0051] Step S20: Analyzing the construction request to determine the evidence task information to be generated.

[0052] It should be noted that the construction request can be analyzed to determine the specific requirements of the natural resource field evidence task that the user wants to generate. The analysis process may involve detailed analysis of the textual description, graphical interface operation or other forms of information in the request to extract key information such as task type, investigation content, target area, time requirement, etc. These information will be used as the basis for querying evidence data and selecting target task templates in subsequent steps.

[0053] In specific implementation, the evidence task information to be generated can include evidence task name to be generated, task area, task type, evidence task type priority to be generated, and the like.

[0054] ​In an implementable embodiment, step S20 can include steps A11-A15:

[0055] Step A11: keyword extraction is performed on the build request to obtain a to-be-generated evidence task name and a task area.

[0056] In a specific implementation, the build request can be parsed to perform keyword extraction on the content in the build request, for example, by using a keyword extraction algorithm (such as TF-IDF, TextRank, etc.) to identify keywords in the request that are related to the task type. For example, “investigate”, “report”, and “monitor” can help identify that the type of task is an “investigation task” or a “monitoring task”.

[0057] It can be understood that, by performing keyword extraction on the build request, the name of the to-be-generated evidence task and the specific area can be obtained.

[0058] Step A12: encoding is performed on the build request to obtain a text vector representation.

[0059] It should be noted that the build request can be encoded by using a BERT (Bidirectional Encoder Representations from Transformers) model to obtain a text vector representation.

[0060] Step A13: inputting the text vector representation into a classifier to perform task type prediction to obtain a to-be-generated evidence task type.

[0061] In a specific implementation, the text vector can be input into a classifier (such as an SVM (Support Vector Machine) or a Softmax classifier) to perform task type prediction to obtain the to-be-generated evidence task type.

[0062] Step A14: using rule matching and priority reasoning to parse the build request to obtain a to-be-generated evidence task type priority.

[0063] In a specific implementation, rule matching can be based on a pre-set rule library, which defines different types of tasks and their corresponding priorities. Priority reasoning can involve analyzing specific information (such as urgency, task size, etc.) in the request to determine the relative importance of the task. If the request contains the keywords “urgent” or “as soon as possible”, the priority is “high”.

[0064] Step A15: taking the to-be-generated evidence task name, the task area, the to-be-generated evidence task type, and the to-be-generated evidence task priority as to-be-generated evidence task information.

[0065] In a specific implementation, all the key information extracted and predicted can be integrated together to form a complete to-be-generated evidence task information, providing necessary input for subsequent steps.

[0066] Step S30: Querying corresponding evidence data from a preset evidence database according to the to-be-generated evidence task information.

[0067] It should be noted that the preset evidence database stores 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 to-be-generated evidence task information, the system will perform accurate querying in the preset evidence database according to these information to find the most matched data set for the to-be-generated evidence task. This process may involve complex database querying techniques and algorithms to ensure the accuracy and efficiency of the query results.

[0068] Step S40: Selecting a target task template from a preset template warehouse according to the evidence data.

[0069] It should be noted that the preset template warehouse stores various types of evidence task templates, which are designed in advance according to common evidence task requirements and business logic. When selecting the target task template, the system will comprehensively consider the type, structure of the evidence data and the specific requirements of the to-be-generated evidence task. Through intelligent matching algorithms, the system can quickly filter out the most suitable template for the current task from the preset template warehouse. This process not only improves the efficiency of task generation, but also ensures that the generated evidence task meets the business specifications and standards.

[0070] Data templates are the basis for investigation and evidence tasks. Forming a data template system that is organized, readable, and logically clear improves the understanding of investigation and evidence tasks. Strictly follow the principles of scientificity, practicality, stability, scalability, compatibility, and pertinence to reasonably compile task templates, plot structure templates, field templates, personnel templates, audit process templates, and build bridges for data continuity and communication, ensuring consistency in data acquisition, processing, management, and application.

[0071] Step S50: Configuring the evidence task on the target task template with the evidence data to generate a natural resource field evidence task, wherein the evidence task configuration includes one or more of task basic information configuration, evidence task workflow configuration, investigation field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

[0072] In specific implementation, the evidence task configuration may involve multiple aspects to ensure that the generated evidence task meets both business needs and efficient execution. The following is a detailed description of each part of the evidence task configuration:

[0073] Task basic information configuration: including setting the name, number, creation time, and expected completion time of the task. These information helps task managers quickly understand the task overview, facilitating task tracking and management. Evidence task workflow configuration: workflow defines each stage of the task from creation to completion, as well as the operations and responsibilities required in each stage. By configuring the workflow, it can ensure that the execution process of the task meets the established business logic and process specifications, improving the efficiency and accuracy of task execution. Survey field configuration: survey field is the key element of data collection. When configuring the survey field, you need to determine the information type, field name, field type, and whether it is required according to business needs. Through reasonable field configuration, it can ensure that the collected data is comprehensive, accurate and meets business requirements. Page form configuration: page form is the interface for users to interact with the system. When configuring the page form, you need to consider the user's usage habits and operation process to ensure that the form design is intuitive, simple and easy to operate. At the same time, it is necessary to ensure that the fields in the form are consistent with the survey field configuration to ensure correct data collection and storage. Evidence task personnel configuration: personnel configuration determines the personnel involved in the task and their roles and responsibilities. When configuring personnel, you need to allocate personnel according to the size and complexity of the task, as well as their professional ability and experience. By clearly defining personnel responsibilities and division of labor, it can ensure the smooth execution and efficient completion of the task. Evidence task management configuration: management configuration involves monitoring and managing the execution process of the task. This includes setting the task reminder method, progress tracking method, data reporting method, etc. Through effective management configuration, it can real-time understand the execution status and problems of the task, and timely adjust and optimize to ensure the smooth completion of the task. Task dictionary management configuration: task dictionary is a collection of various terms, codes and standards involved in the task. When configuring the task dictionary, you need to ensure the accuracy and completeness of the dictionary content 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 have efficient execution capabilities. These tasks will help improve the efficiency and quality of natural resource monitoring and supervision, and provide strong support for the rational development and utilization of natural resources.

[0074] In a specific implementation, for a general investigation evidence collection task, a built-in evidence collection task template can be directly selected to realize evidence collection task creation. When the general evidence collection template cannot meet the evidence collection task, a "zero code" evidence collection scene construction engine can be used to realize customized evidence collection task, forming a set of universal front-end and back-end configuration architecture and visual configuration process for business personnel to customize field tasks on demand. The evidence collection scene construction technology combining standardization and customization can easily cope with frequent adjustments of evidence collection task types and structures. For diversified needs, no code development is required, and only modeling and configuration can realize customized task generation. This process does not require professional configuration of product or field implementation personnel, improving the timeliness of task configuration.

[0075] After template design, scene construction, and evidence collection task creation, the field evidence collection task construction is basically completed. At the same time, the evidence collection platform automatically generates evidence collection tasks on the web page and creates a business application shortcut entry to facilitate users to enter the corresponding business module and carry out investigation and monitoring evidence verification business. The mobile terminal serves as a unified terminal application portal based on Internet+, mobile GIS, and unmanned aerial vehicle interconnection technologies to provide general basic modules and monitoring and supervision modules to realize field evidence collection, video interconnection, and positioning search.

[0076] In a feasible implementation, when the amount of evidence collection tasks at the same time point is too large, intelligent resource scheduling is required. Therefore, the natural resource field evidence collection task generation method further includes steps A21-A24:

[0077] Step A21: In the evidence collection task configuration process, the current state of the resource is obtained.

[0078] In a specific implementation, the current state of the resource can include the real-time location, available time, and professional skills of the field personnel. These information is uploaded to the system in real time through the mobile terminal or web page to ensure the accuracy and timeliness of resource scheduling.

[0079] Step A22: Obtain resource load according to the current state of the resource.

[0080] The resource load is obtained by comprehensively evaluating the size, urgency, and required resources of all current evidence collection tasks. When the resource load exceeds the preset load threshold, the system triggers an intelligent resource scheduling mechanism to ensure that all tasks can be efficiently and orderly completed.

[0081] Step A23: When the resource load is greater than the preset load threshold, analyze the polygon type, terrain complexity, and evidence collection requirements of each evidence collection task, and determine the expansion node.

[0082] In specific implementation, the preset load threshold represents a critical value of resource load, which can be set according to demand. When the resource load is greater than the preset load threshold, resource scheduling is needed. Therefore, the types of the evidence tasks, the terrain complexity, and the evidence requirements can be analyzed to more accurately assess the specific resource needs of each task. For example, some plots may be located in remote areas and require personnel with special skills for field investigation; some 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.

[0083] Determining the expansion node is a key step in intelligent resource scheduling. The expansion node can be an additional computing node, storage node, or bandwidth resource. The expansion node can include increasing field personnel, deploying professional equipment, extending working hours, etc. The system intelligently selects the optimal expansion node scheme based on the analyzed resource needs and current resource status to ensure reasonable allocation and efficient use of resources. This process not only improves the flexibility of resource scheduling, but also ensures that evidence tasks can be completed with high quality.

[0084] wherein the task resource demand coefficient = f (plot type, terrain complexity, evidence requirement), the plot complexity coefficient can be assigned to each plot type, and more complex plots require more resources. Plot complexity coefficient = basic complexity × geographic factor coefficient Plot complexity coefficient = basic complexity × geographic factor coefficient. Similarly, terrain complexity can be quantified by a coefficient, with a larger complex terrain coefficient and a smaller simple terrain coefficient. Terrain complexity coefficient = terrain type coefficient × area size coefficient Terrain complexity coefficient = terrain type coefficient × area size coefficient.

[0085] Step A24: Resource scheduling for the evidence task configuration according to the plot type, the terrain complexity, the evidence requirement, and the expansion node.

[0086] Finally, resource scheduling is performed for the evidence task configuration according to the plot type, the terrain complexity, the evidence requirement, and the expansion node. This process involves complex algorithms and models to ensure the accuracy and efficiency of scheduling. Through intelligent resource scheduling, the system can maximize the efficiency and quality of evidence task execution under limited resources, providing strong support for the rational development and utilization of natural resources.

[0087] By dynamically matching task requirements and resource states, efficient coordination of manpower, equipment, and data is achieved. For the task assignment rule of field evidence plot, a spatial clustering algorithm is used to logically aggregate adjacent plots based on coordinates, reducing the mobile distance of field work. When the amount of evidence task is too large at the same time point, the system can be flexibly scaled up or down, with second-level node expansion. Optimal resource matching: real-time analysis of task attributes (plot type, terrain complexity, evidence requirements) and resource states (personnel location, equipment load, skill label), optimization of matching strategy through algorithm, and reduction of operation response delay. For large-scale field evidence plot parallel distribution in a single day, the engine uses a parallel processing mechanism to split the plot set and process multiple threads synchronously; dynamic batch processing, with 50-100 plots per batch to avoid single-node overload and automatically increase or decrease processing nodes based on queue accumulation.

[0088] The embodiment provides a natural resource field evidence task generation method, which automates the entire process from user request to task generation, reduces manual operation and intervention, and greatly improves the efficiency and accuracy of task generation. Users only need to provide a build request, and the system can automatically analyze, query, select and configure related data and templates, greatly simplifying the complex process of task building. By extracting corresponding data from the preset evidence database and combining the preset templates for task configuration, it can ensure that the generated evidence task meets the standardization requirements, improve the accuracy and consistency of the task, and avoid errors or omissions caused by manual operation; support flexible configuration of multiple aspects of the task, including basic information, workflow, investigation fields, forms, personnel management, etc. In this way, different task requirements can be adapted by adjusting the configuration to meet various evidence scenarios and ensure the applicability and versatility of the platform. The visual build of the platform enables users to intuitively construct and manage evidence tasks, improving user experience. Through the graphical interface, users can more conveniently design and adjust tasks to adapt to different usage requirements and scenarios. Through automated processes and template selection, the dependence on human labor is reduced, avoiding human factors that cause bias and improving the reliability and stability of the system.

[0089] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as the above-mentioned first embodiment can be referred to the above introduction, and the following will not be repeated. On this basis, please refer to Figure 3 , step S50 includes steps S501-S503:

[0090] Step S501: obtaining evidence task basic information from the evidence data, the evidence task basic information including evidence task name, evidence task area, evidence task description, evidence task belonging business, and evidence task project management information.

[0091] It should be noted that when configuring the basic information of the evidence task, the basic information of the evidence task can be obtained through the evidence data, thereby providing the task basic information configuration capability for the business system and application construction. The task name, task area, description, belonging business, and whether project management are set.

[0092] The evidence task name is the title or name of the task, which is usually used to briefly and clearly describe the purpose and content of the task. The task area is the administrative division involved in the field evidence collection, supporting the definition of the task area in units of province, city, and county. One or more counties / townships can be selected as the task area. The evidence task description is a detailed description of the task, including the background, purpose, and specific requirements of the task. The evidence task belonging business includes the business related to the task, such as "resource management" and "environmental monitoring". The evidence task project management information is the project management information about the task, which may include the time schedule, responsible person, and budget of the project.

[0093] The calculation of the evidence task area may need to be derived based on the administrative division or geographic information. It is assumed that the target area can be defined by latitude and longitude range:

[0094]

[0095] where lat1 and lat2 are the latitude range, long1 and long2 are the longitude range, and dA is a small area element.

[0096] Step S502: querying the corresponding components on the target task template to set the evidence task name, evidence task area, evidence task description, and evidence task belonging business.

[0097] In specific implementation, visual building is the core of the evidence scene agile building engine. It encapsulates complex business logic into graphical components and modules, allowing users to construct field evidence tasks by dragging and connecting these components. In the visual building environment, users can design the interface layout of the evidence task by dragging interface elements, and set the appearance and behavior of the survey information by configuring properties. At the same time, the platform provides a variety of logic components, such as button click events, data queries, data processing, and result submission. Users only need to associate these logic components with interface elements to achieve complex interactive functions.

[0098] Therefore, after determining the evidence task name, evidence task area, evidence task description, and evidence task belonging business, the corresponding components can be queried and displayed, so that users can set the content in the evidence task basic information by dragging and connecting these components.

[0099] Step S503: Query the corresponding component on the target task template to set the unit of the evidence object for the evidence task item management, complete the configuration of the evidence task basic information, and generate a natural resource field evidence task. The unit of the evidence object includes a parcel and a project.

[0100] It can be understood that project management mainly provides parcel evidence and project evidence capabilities for different evidence objects in units of parcels and projects. Parcels are units such as routine monitoring and daily change investigation, and projects are units such as land consolidation and balance compensation projects. When project management is used, the project is first, and then the specific parcel in the project.

[0101] Therefore, the unit of the evidence object can be queried on the target task template to set the unit of the evidence object. In the target task template, two main units of the evidence object are set, a parcel (Parcel) : In a geographic information system (GIS), a parcel usually represents a basic unit of a geographic area, usually a polygon that delimits a certain area. A project (Project) : A project unit usually corresponds to a larger task unit, which may involve multiple parcel areas. Through the basic information obtained in step S501 and the template setting of step S502, combined with the requirements of project management, a complete natural resource field evidence task is finally generated.

[0102] After the configuration is completed, consistency checking can be performed to ensure that each field is correctly filled. For example, check whether the task area matches the task name or task description to ensure the consistency of the information.

[0103] Verification formula = ∑(task description consistency, area and name consistency, business matching degree)

[0104] It should be noted that if the result is not 0, the configuration error needs to be adjusted or reminded.

[0105] The embodiment obtains evidence task basic information according to the evidence data, and the evidence task basic information includes an evidence task name, an evidence task area, an evidence task description, an evidence task belonging business, and evidence task project management information. The corresponding component on the target task template is queried to set the evidence task name, the evidence task area, the evidence task description, and the evidence task belonging business. The corresponding component on the target task template is queried to set the unit of the evidence object for the evidence task item management, complete the configuration of the evidence task basic information, and generate a natural resource field evidence task. The unit of the evidence object includes a parcel and a project.

[0106] Based on the first embodiment of the present application, in the third embodiment of the present application, the same or similar contents as the above embodiment one can be referred to the above introduction, and the subsequent will not be described. On this basis, please refer to Figure 4 , step S50 includes steps S504-S506:

[0107] Step S504: obtaining the current workflow of the evidence service according to the evidence data.

[0108] In specific implementation, the current workflow of the evidence service may involve multiple links and participants, such as field investigation, data entry, preliminary review, review, final review, etc. Each link has its specific responsibilities and requirements to ensure the accuracy and compliance of the evidence task. According to the evidence data, the system can automatically identify and extract the key information of the current workflow, such as the number of process links, participants of each link, required time, etc. These information provides the basis for the subsequent workflow configuration.

[0109] Step S505: querying the corresponding component configuration minimum audit unit on the target task template based on the current workflow.

[0110] On the target task template, the system will query and display the corresponding components according to the current workflow. These components represent the various links and participants in the workflow, and users can construct the workflow by dragging and connecting these components.

[0111] The minimum audit unit is a key link in the workflow, which is responsible for self-checking and rectification of the evidence results after the task is completed. According to the current workflow, the system can determine the level and responsibility of the minimum audit unit, and query and display the corresponding components on the target task template.

[0112] Step S506: querying the corresponding component on the target task template to configure the self-checking and rectification rules, review rules, audit process rules and return process of the minimum audit unit after the work is completed, completing the evidence task workflow configuration, and generating natural resource field evidence task.

[0113] After completing the setting of the minimum audit unit, the system also needs to configure the self-checking and rectification rules, review rules, audit process rules and return process. These rules ensure the smoothness and compliance of the workflow, and prevent errors and omissions. Users can set these rules on the target task template by dragging and configuring properties.

[0114] For example, the self-checking and rectification rule may require the investigator to conduct self-checking and rectification before submitting the evidence results, to ensure the accuracy and integrity of the data. The review rule may require the reviewer to review the evidence results of the investigator, to ensure the compliance and consistency of the data. The review process rule may define the responsibilities and approval process of different levels of reviewers. The return process defines how to return to the investigator for re-investigation and rectification when the evidence results do not meet the requirements. Through detailed workflow configuration, the system can generate a complete natural resource field evidence task and ensure the accuracy and compliance of the task. This greatly improves the efficiency and quality of the execution of the evidence task, and provides strong support for the rational development and utilization of natural resources.

[0115] For different evidence business workflows, business process configuration capabilities are provided. The minimum audit unit can be configured independently according to the needs and business conditions. Whether the county level, township level, or village level, whether the county level needs to be self-checked and rectified after the field work is completed, whether there is a review process after the review by the user at each level, how the review process is defined, whether the province, city, and county levels audit or the county level directly submits to the city level for audit, whether the township level participates in the audit process, whether the audit is not passed, and a series of questions such as whether to return, etc. can be quickly implemented through configuration.

[0116] In a feasible implementation, the generation of the evidence task also includes the configuration of the investigation field. Therefore, step S50 can further include: obtaining different collection information requirements according to the evidence data; based on the different collection information requirements, querying the corresponding component on the target task template to configure the filling rules of the investigation field, the logical relationship of the investigation field, the reference attribute field, and the field selection item, complete the investigation field configuration of the evidence task, and generate the natural resource field evidence task.

[0117] It should be noted that the investigation field is an important part of the evidence task, which is used to collect various information required by the field investigation. In actual operation, different evidence businesses may have different collection information requirements, such as land type, vegetation coverage, building condition, etc. Therefore, when generating the evidence task, the needs of these requirements need to be determined according to the evidence data.

[0118] After determining the collection information needs, the system will query the corresponding components in the target task template. These components represent different survey fields, and users can set the field filling rules, logical relationships, reference attribute fields, and field selection items by dragging and configuring properties. The filling rules define the input format and limit conditions of the field, such as numbers, text, dates, etc. The logical relationship is used to set the association and constraint between fields, ensuring the accuracy and consistency of data. The reference attribute field provides a reference range or default value for the field value, which helps to reduce input errors. The field selection item lists the possible values of the field, making it easy for users to quickly select.

[0119] Through detailed survey field configuration, the system can generate a proof task that meets the actual needs and is easy to operate. This greatly improves the efficiency and accuracy of data collection, providing strong support for subsequent data analysis and utilization. At the same time, users can also flexibly configure and adjust the survey fields according to their own needs and business conditions to adapt to different proof scenarios and needs.

[0120] According to the different needs of different field collection information, the on-demand field configuration function is provided. Whether the field of field investigation and verification has a mandatory limit, whether the field has a filling threshold, such as must be greater than or equal to 0, whether the field has a logical relationship, after filling field A, field B must be filled or must be empty, whether the field has a data dictionary, so that the field can be selected during field work, whether the field is sparse and mapped, and which attribute fields can the field worker refer to. According to the survey field configuration, first-hand real and accurate on-site information is quickly collected for decision-making.

[0121] In a feasible implementation, the generation of the proof task also includes the configuration of the page form, so step S50 further includes: obtaining business information according to the proof data; querying corresponding components on the target task template according to the information type of the business information to classify and display the layout of the business information, complete the configuration of the proof task page form, and generate a natural resource field proof task.

[0122] The page form configuration is to organize and layout the business information. Users can classify and display the information on the interface according to the information type. The page form is an important interface for user interaction in the evidence task, which displays various information and operation options of the task. In actual operation, different evidence businesses may involve different types of business information, such as land area, vegetation type, building number, etc. Therefore, when generating the evidence task, the information type needs to be determined according to the evidence data. After determining the information type, the system queries the corresponding components in the target task template, and classifies and displays the layout settings of the page form according to the characteristics of these information types. These components represent different elements on the page form, such as text boxes, drop-down lists, check boxes, etc. Users can set the layout, display mode, and interaction behavior of these elements by dragging and configuring properties. Layout settings define the overall structure of the page form and the arrangement of each element, ensuring clear display and easy operation of information. Display mode is used to set the display format and style of elements, such as font, color, size, etc. Interaction behavior defines the user interaction with the page form, such as clicking, inputting, selecting, etc.

[0123] Through detailed page form configuration, the system can generate an evidence task that meets actual needs and is easy to operate. This greatly improves the efficiency and experience of user interaction, providing strong support for subsequent data entry and review. At the same time, users can flexibly configure and adjust the page form according to their own needs and business situations to adapt to different evidence scenarios and needs. Flexible form configuration capabilities are provided for the page form display needs of different evidence businesses. Whether fields in the form have mandatory items, how to define the display format of fields, whether there is a layout association between multiple fields, whether there is a sequence requirement for form fields, whether to display in pages, and a series of questions can be quickly implemented through configuration. According to the page form configuration, the evidence task interface that meets the business needs can be quickly built, providing convenience for subsequent field investigation and internal review. It supports content layout of verification information, review information, etc. on web and mobile interfaces. Through this function, users can flexibly and independently layout business information, making business application and management more smooth, fast, time-saving and labor-saving, avoiding the additional development in traditional mode.

[0124] In a feasible implementation, the generation of the evidence task also includes the configuration of field personnel. By providing field personnel configuration capabilities for field tasks, such as which level of users need to participate in a certain business, which department needs to participate, which technical support unit needs to participate, how to divide user rights, whether a user can be responsible for multiple businesses, whether to create a work group, breaking the limitations of personnel structure, configuring through the user system can not only ensure data security and prevent other users from viewing business results, but also categorize and avoid users experiencing a too cluttered system.

[0125] It also provides various configuration tasks for evidence collection task management, including uploading field map features, viewing map feature lists / details / maps, viewing, reviewing, and downloading field evidence collection results. Users can add verification tasks by selecting the region, granularity (smallest verification unit), and data distribution mode. This function allows users to independently create, maintain, and delete tasks, and also supports grouped management of multiple tasks to meet the needs of a large number of concurrent tasks. This feature gives verification work excellent autonomy, flexibility, convenience, and operability.

[0126] The task dictionary configuration supports dictionary search, dictionary addition, editing, and deletion functions. Dictionaries can be added according to business needs, and the dictionary display value, stored value, and sequence number can be set. After configuring the dictionary for a field on the Jiangxi Cloud mobile and web platforms, the corresponding dictionary display value can be displayed.

[0127] like Figure 5 As shown, Figure 5 This embodiment, serving as a conceptual model definition diagram, also allows for the advance design of a conceptual model for monitoring and regulatory tasks. The design of this conceptual model involves abstracting and generalizing the monitoring and investigation objects based on a clear understanding of the investigation and evidence-gathering task requirements. This primarily includes clarifying the entity objects, object representation methods, and object relationships. The entity object model is used to define the organization and relationships of basic information, structure, review processes, and personnel. For example... Figure 6 As shown, Figure 6 To visualize the scene, a schematic diagram is built, including business model components, filter item components, button area components, table column components, and other areas. When configuring tasks, the components can be configured to render and display the results.

[0128] The embodiment obtains the current workflow of the evidence service according to the evidence data; queries the corresponding component configuration minimum audit unit on the target task template based on the current workflow; queries the self-checking and rectification rules, review rules, audit process rules and return process of the corresponding component configuration minimum audit unit on the target task template, completes the evidence task workflow configuration, and generates the natural resource field evidence task. Through detailed evidence task configuration, the system can generate an evidence task that meets the actual needs and is easy to operate. This greatly improves the efficiency and accuracy of data collection and provides strong support for subsequent data analysis and utilization. Users can flexibly configure and adjust the evidence task according to their own needs and business conditions to adapt to different evidence scenarios and needs. By providing flexible page form configuration capabilities, an evidence task interface that meets the actual needs and is easy to operate can be generated. This greatly improves the efficiency and experience of user interaction, and provides strong support for subsequent data entry and review. At the same time, users can also flexibly configure and adjust the page form according to their own needs and business conditions to meet different evidence business display needs.

[0129] Based on the first embodiment of the present application, in the fourth embodiment of the present application, the same or similar contents as the above embodiment one can refer to the above introduction, and the following will not be repeated. On this basis, please refer to Figure 7 After step S50, steps S51-S52 are further included.

[0130] Step S51: After the natural resource field evidence task is generated, a business application interface is created.

[0131] It should be noted that the built-in “Land Change Survey Technical Specification” verification rules in the engine can be combined with intelligent quality inspection through real-time rule interface to ensure the compliance and accuracy of the evidence data.

[0132] The business application interface is used for interaction with the user. When the field investigation evidence result is submitted, it automatically intercepts illegal submission (such as missing positioning watermark, digital certificate, etc.). The verification rules mainly include: basic compliance verification rules, business logic verification rules, intelligent quality inspection enhancement rules, closed-loop disposal rules, etc.

[0133] Step S52: 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.

[0134] In a specific implementation, the natural resource field evidence collection task can be sent to the mobile terminal of the user, so that the user enters the business application interface to detect and verify the generated evidence collection task. The communication between the web page end of the engine and the mobile terminal mainly adopts the HTTP protocol. The HTTP protocol is simple and flexible in design and supports the transmission of various formats of data.

[0135] The core features of HTTP are as follows: 1. Stateless protocol: by default, no previous request or session information is recorded (state management can be realized through Cookie, Session, etc. in the future). 2. Based on the request-response model, the client sends a request (Request), and the server returns a response (Response). 3. Support multiple methods: such as GET (get resources), POST (submit data), PUT (update resources), DELETE (delete resources), etc. 4. Strong scalability: additional information is transmitted through request / response headers (Headers), supporting caching, compression, identity verification, and other functions. The working principle of HTTP is as follows: 1. Establish a connection, and the client connects with the server through TCP / IP (default port 80) (HTTP / 1.1 default persistent connection, HTTP / 2 supports multiplexing). 2. Send a request, and the request message includes: (1) Request line: method (such as GET), URL (such as / index.html), and protocol version (such as HTTP / 1.1). (2) Request header: Host, User-Agent, Accept, and other meta information. (3) Request body (optional): such as the 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), and 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 when the connection is not persistent).

[0136] In a feasible implementation, the evidence collection task can also be updated, so after step S50, it further includes: obtaining updated evidence collection specifications, updated quality control requirements, and preset task instructions based on the natural resource field evidence collection task; and issuing the updated evidence collection specifications, the updated quality control requirements, and the preset task instructions to the corresponding user through the mobile terminal, so that the user adjusts the natural resource field evidence collection task based on the updated evidence collection specifications, the updated quality control requirements, and the preset task instructions.

[0137] It should be noted that the preset task instruction is a specific task instruction, which can be set according to the specific task, and the latest evidence specification, quality control requirements or specific task instruction can be dynamically issued to the mobile terminal operator to realize the instant update and execution control of the evidence rule. This mechanism mainly relies on the cooperation of cloud rule configuration and issuance of the built engine, real-time receiving and execution of the mobile terminal to complete, and real-time rule injection has become the core means to ensure the "precision, efficiency and compliance" of land survey in the case of not affecting the survey progress and the evidence of the achievement.

[0138] In specific implementation, the survey task can be automatically expanded according to different offices and different businesses, such as Figure 8 , Figure 8 To automatically expand the survey evidence task, the audit flow configuration, business flow configuration, survey field configuration and user system configuration are configured by self-defined configuration engine. The audit flow configuration includes whether the county conducts self-examination? Whether there is a review after the audit? County, city and province level audit? Whether the township participates in the audit? Whether the audit is not passed? The business flow configuration includes whether it is necessary to take photos? Whether it is necessary to export the account book? Whether it is necessary to take pictures outside? Whether the task is issued in distribution mode or in taking mode? The survey field configuration includes whether the field has a mandatory limit? Whether the field has a filling threshold? Whether the field has a logical relationship? Whether the field has a data dictionary? Whether the field is sparse and mapped? The user system configuration includes which level user participates? How to divide the user rights? Whether a user can be responsible for multiple businesses? Whether it is necessary to create a work group? So as to provide business support for regular monitoring, farmland protection, map enforcement, change survey and post-supervision.

[0139] After the natural resource field evidence task is generated, a business application interface is created, and the natural resource field evidence task is sent to the user to make the user enter the business application interface to monitor and verify the natural resource field evidence task. The creation of the business application interface enables the user to conveniently interact with the system, especially when the field survey evidence is submitted, the system can automatically intercept the illegal submission to ensure the compliance and accuracy of the evidence data. This function greatly improves the quality and reliability of the data, and lays a solid foundation for subsequent data analysis and utilization. Through the cooperation of cloud rule configuration and issuance, real-time receiving and execution of the mobile terminal, the instant update and execution of the evidence rule are realized. This mechanism ensures the "precision, efficiency and compliance" of land survey, and improves the quality and efficiency of the survey work.

[0140] Exemplarily, in order to help understand the implementation process of the natural resource field evidence task generation method obtained after the above embodiment one, please refer to Figure 9 , Figure 9A brief flowchart of a natural resource field evidence collection task generation method is provided, specifically: starting to define basic information of the collection task, including: the business to which it belongs, the task area, and the task name, then defining the field work process, including: the review process, the review opinion type, and the return flow, then defining the field work field, including: the field name, the field type, and the drop-down selection item, thereby configuring the field work form, including: the field configuration, the drop-down configuration, the search configuration, and the display configuration, and defining the field workers, such as field worker 1, field worker 2, and field worker 3, and performing field task management, including: plot uploading, task allocation, result viewing, and result auditing, thereby generating the field evidence collection task and performing field evidence collection.

[0141] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the natural resource field evidence collection task generation method of the present application. Based on this technical concept, more forms of simple changes are within the protection scope of the present application.

[0142] The present application also provides a natural resource field evidence collection task generation device, please refer to Figure 10 , the natural resource field evidence collection task generation device comprises:

[0143] The response module 10 is configured to respond to a user's request for building a natural resource field evidence collection task;

[0144] The analysis module 20 is configured to analyze the building request and determine the to-be-generated evidence collection task information;

[0145] The query module 30 is configured to query corresponding evidence data from a preset evidence database according to the to-be-generated evidence collection task information;

[0146] The selection module 40 is configured to select a target task template from a preset template warehouse according to the evidence data;

[0147] The configuration module 50 is configured to perform evidence collection task configuration on the target task template with the evidence data, generate a natural resource field evidence collection task, and the evidence collection task configuration includes one or more of task basic information configuration, evidence collection task workflow configuration, investigation field configuration, page form configuration, evidence collection task personnel configuration, evidence collection task management configuration, and task dictionary management configuration.

[0148] The natural resource field evidence task generation device provided in the application can solve the technical problem of low efficiency and accuracy of natural resource field evidence task generation. Compared with the prior art, the natural resource field evidence task generation device provided in the application has the same beneficial effects as the natural resource field evidence task generation method provided in the above embodiment, and other technical features in the natural resource field evidence task generation device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0149] The application provides a natural resource field evidence task generation device, which comprises at least one processor and a memory in communication connection with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the natural resource field evidence task generation method in the above embodiment one.

[0150] Reference will be made to the accompanying drawings Figure 11 which shows a structural diagram of a natural resource field evidence task generation device suitable for implementing the embodiments of the application. The natural resource field evidence task generation device in the embodiments of the application can include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal Digital Assistant), PADs (Portable Application Description), PMPs (Portable Media Player), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. Figure 11 The natural resource field evidence task generation device shown is only an example and should not impose any limitation on the functions and use range of the embodiments of the application.

[0151] As Figure 11As shown, the natural resource field evidence task generation device can include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to programs stored in a ROM (Read Only Memory) 1002 or programs loaded from a storage device 1003 into a RAM (Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the natural resource field evidence task generation device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, an LCD (Liquid Crystal Display), a speaker, a vibrator, etc.; the storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the natural resource field evidence task generation device to communicate with other devices wirelessly or by wire to exchange data. Although the natural resource field evidence task generation device with various systems is shown in the figure, it should be understood that all the systems shown are not required to be implemented or possessed. More or fewer systems can be alternatively implemented or possessed.

[0152] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. 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 containing program codes for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are performed.

[0153] The natural resource field evidence task generation device provided by the present application adopts the natural resource field evidence task generation method in the above-mentioned embodiments, and can solve the technical problem of low efficiency and accuracy of natural resource field evidence task generation. Compared with the prior art, the natural resource field evidence task generation device provided by the present application has the same beneficial effects as the natural resource field evidence task generation method provided by the above-mentioned embodiments, and other technical features in the natural resource field evidence task generation device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0154] It should be understood that various parts of the present disclosure can be implemented in 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.

[0155] The above merely provides the specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present disclosure, which should be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

[0156] The present disclosure provides a computer readable storage medium having stored thereon computer readable program instructions (i.e. computer programs) for performing the natural resource field evidence task generation method in the above embodiments.

[0157] The computer readable storage medium provided by the present disclosure may, for example, be a U disk, but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, system or device, or any combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to: an electrical connection having one or more conductive wires, a portable computer diskette, a hard disk, a RAM (Random Access Memory, Random Access Memory), a ROM (Read Only Memory, Read Only Memory), an EPROM (Erasable Programmable Read Only Memory, Erasable Programmable Read Only Memory or flash memory), an optical fiber, a CD-ROM (CD-Read Only Memory, Compact Disc Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present embodiment, the computer readable storage medium can be any tangible medium containing or storing 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 can be transmitted in any suitable medium, including but not limited to: electrical wires, optical cables, RF (Radio Frequency, Radio Frequency), etc., or any suitable combination of the above.

[0158] The above computer readable storage medium can be contained in the natural resource field evidence task generation device; or can exist separately without being assembled into the natural resource field evidence task generation device.

[0159] The computer readable storage medium described above carries one or more programs, when the one or more programs are executed by the natural resource field evidence task generation device, the natural resource field evidence task generation device is caused to: in response to a user's request for building a natural resource field evidence task; parse the building request, determine the to-be-generated evidence task information; query the corresponding evidence data from the preset evidence database according to the to-be-generated evidence task information; select a target task template from the preset template warehouse according to the evidence data; perform evidence task configuration on the target task template with the evidence data, and generate a natural resource field evidence task, wherein the evidence task configuration includes one or more of task basic information configuration, evidence task workflow configuration, investigation field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration.

[0160] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0161] The flow and block diagrams in the drawings show architectural, functional, and operational representations of possible implementations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flow and block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may be executed in the reverse order, depending on the functionality involved. It will also be noted that each block of the block diagrams and / or flowchart illustrations, and combinations thereof, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or combinations of hardware and computer instructions.

[0162] The modules described in the embodiments of the present application can be implemented in the form of software or in the form of hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0163] The readable storage medium provided by the present application is a computer readable storage medium, which stores computer readable program instructions (i.e., a computer program) for executing the natural resource field evidence task generation method described above, and can solve the technical problem of low efficiency and accuracy of the natural resource field evidence task generation. Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the natural resource field evidence task generation method provided by the above embodiments, and will not be described here.

[0164] The present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the natural resource field evidence task generation method as described above.

[0165] The computer program product provided by the present application can solve the technical problem of low efficiency and accuracy of the natural resource field evidence task generation. Compared with the prior art, the computer program product provided by the present application has the same beneficial effects as the natural resource field evidence task generation method provided by the above embodiments, and will not be described here.

[0166] The above only describes some embodiments of the present application, and does not limit the patent scope of the present application. Any equivalent structural transformation, direct / indirect application in other related technical fields based on the technical concept of the present application, and the contents of the present application specification and drawings are included in the patent protection scope of the present application.

Claims

1. A method for generating on-site evidence collection tasks for natural resources, characterized in that, The method for generating on-site evidence collection tasks for natural resources is applied to an evidence collection scenario visualization platform, which stores a preset evidence collection database and a preset template repository. The method for generating the on-site evidence collection task for natural resources includes: In response to user requests for the establishment of on-site evidence collection tasks for natural resources; The process of parsing the setup request to determine the information of the evidence task to be generated includes: extracting keywords from the setup request to obtain the name and region of the evidence task to be generated; encoding the setup request to obtain a text vector representation; inputting the text vector representation into a classifier for task type prediction to obtain the type of the evidence task to be generated; parsing the setup request using rule matching and priority reasoning to obtain the priority of the evidence task type to be generated; and using the name, region, type, and priority of the evidence task to be generated as the information of the evidence task to be generated. Based on the information of the evidence task to be generated, query the corresponding evidence data from the preset evidence database; Select a target task template from the preset template repository based on the evidence data; The evidence data is configured 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, investigation field configuration, page form configuration, evidence task personnel configuration, evidence task management configuration, and task dictionary management configuration. The task dictionary configuration supports dictionary search query, dictionary addition, editing, and deletion functions. Dictionaries can be added according to business needs, and dictionary display values, storage values, and serial numbers can be set. The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: Business information is obtained based on the evidence data; Based on the information type of the business information, query the corresponding component on the target task template to classify and display the business information, complete the form configuration of the evidence task page, and generate the natural resource field evidence task.

2. The method as described in claim 1, characterized in that, The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: Based on the evidence data, the basic information of the evidence task is obtained, which 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 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; The corresponding component is queried on the target task template to set the unit of the evidence object for the project-based management of the evidence task, complete the configuration of the basic information of the evidence task, and generate the natural resource field evidence task. The unit of the evidence object includes map patches and projects.

3. The method as described in claim 1, characterized in that, The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: The current workflow of the evidence submission process is obtained based on the evidence data. Based on the current workflow, query the corresponding component configuration minimum review unit on the target task template; Query the corresponding component configuration on the target task template to configure the self-inspection and rectification rules, review rules, review process rules and return process of the minimum review unit after the work is completed, complete the configuration of the evidence collection task workflow, and generate the natural resource field evidence collection task.

4. The method as described in claim 1, characterized in that, The step of configuring the evidence data on the target task template to generate a natural resource field evidence task includes: Different information collection requirements are derived based on the evidence data provided. Based on different information collection needs, query the corresponding components 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 options, complete the configuration of the survey fields for the evidence collection task, and generate the natural resource field evidence collection task.

5. The method according to any one of claims 1 to 4, characterized in that, The method further includes: During the configuration of the evidence submission task, the current status of the resources is obtained; The resource load is obtained based on the current state of the resources. When the resource load exceeds a preset load threshold, the map patch type, terrain complexity, and evidence requirements of each evidence collection task are analyzed, and expansion nodes are determined. Resource scheduling is performed on the evidence-gathering task configuration based on the type of map feature, the terrain complexity, the evidence requirements, and the extended nodes.

6. The method according to any one of claims 1 to 4, characterized in that, The method further includes: After the on-site evidence collection task for natural resources is generated, a business application interface is created; The task of providing on-site evidence of natural resources is sent to the user so that the user can access the business application interface to monitor and verify the task.

7. The method according to any one of claims 1 to 4, characterized in that, The method further includes: Based on the aforementioned on-site evidence collection task for natural resources, updated evidence collection standards, updated quality control requirements, and preset task instructions are obtained; The updated evidence submission guidelines, the updated quality control requirements, and the preset task instructions are sent to the corresponding users via mobile terminals, so that the users can adjust the on-site evidence submission task for natural resources based on the updated evidence submission guidelines, the updated quality control requirements, and the preset task instructions.

8. A device for generating on-site evidence collection tasks for natural resources, characterized in that, The natural resource field evidence generation device performs the natural resource field evidence generation method according to any one of claims 1 to 7, the device comprising: The response module is used to respond to user requests for setting up on-site evidence collection tasks for natural resources; The parsing module is used to parse the setup request and determine the evidence task information to be generated; The query module is used to query the corresponding evidence data from the preset evidence database based on the evidence task information to be generated; The selection module is used to select a target task template from a preset template repository based on the evidence data. The 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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