GIS data processing method and device based on artificial intelligence

Abstract

The invention discloses a GIS data processing method and device based on artificial intelligence, and the method comprises the steps: integrating a map rendering engine in a database development management tool, and constructing a communication interface between the management tool and a language large model; receiving a natural language, and transmitting the natural language to the language large model through a communication interface; converting a natural language into an SQL statement through a language large model, and returning the SQL statement to the management tool through a communication interface; and finally, sending an SQL statement to the target database through a database development tool to obtain a GIS data processing result, and performing map visualization display on the GIS data processing result through a map rendering engine. By accessing the artificial intelligence large model interface and integrating the GIS processing module, the system has natural language processing and GIS data visual display capabilities, and the database development and management efficiency is remarkably improved.

Description

Technical Field

[0001] This application relates to the cross - integration field of computer software and GIS, and particularly to a GIS data processing method and device based on artificial intelligence. Background Art

[0002] In today's digital age, Geographic Information System (GIS) data plays a key role in many fields, such as urban planning, traffic management, environmental monitoring, logistics distribution, etc. With the increasing dependence of various industries on geospatial information, the scale of GIS data is constantly expanding, and these data cover a variety of formats and types, including vector data, raster data, etc.

[0003] Currently, large - scale GIS data usually needs to be stored in different types of databases and undergoes complex spatial analysis and queries. However, current GIS data processing relies on manually writing SQL or using dedicated GIS software tools, which are not easy for non - GIS professionals to get started quickly, and the operations are complex and time - consuming, resulting in slow GIS data processing efficiency; moreover, different types of databases have different levels of support and implementation methods for GIS data, lacking a unified data management tool, leading to poor data interoperability. Summary of the Invention

[0004] Embodiments of this application provide a GIS data processing method and device based on artificial intelligence, which are used to solve the problems of slow GIS data processing efficiency and poor data interoperability between different databases.

[0005] Embodiments of this application adopt the following technical solutions:

[0006] On the one hand, embodiments of this application provide a GIS data processing method based on artificial intelligence, mainly including: integrating a map rendering engine in a database development management tool and constructing a communication interface between the management tool and a language large - model; then receiving natural language for processing GIS data through the management tool and transmitting the natural language to the language large - model through the communication interface; then converting the natural language into an SQL statement by the language large - model, returning the SQL statement to the management tool through the communication interface; finally, sending the SQL statement to the target database through the database development tool to obtain the GIS data processing result, and visualizing the GIS data processing result on a map through the map rendering engine.

[0007] In one example, before receiving the natural language for processing GIS data through the database development management tool, the method further includes: receiving the data table conditions for GIS data processing, determining the target data table according to the data table conditions; generating the condition limiting content of the target data table, and displaying the condition limiting content to the client; transmitting the natural language to the language large model through the communication interface, specifically including: when receiving the limiting information of the data table conditions, transmitting the limiting information and the natural language to the language large model.

[0008] In one example, generating the condition limiting content of the target data table specifically includes: parsing the spatial attributes and non-spatial attributes in the target data table conditions; extracting the coordinate system information associated with the spatial attributes and the dimension labels associated with the non-spatial attributes according to the metadata of the target data table; combining the coordinate system information and the dimension labels to generate the condition limiting content with spatial constraints.

[0009] In one example, before constructing the communication interface between the database development management tool and the language large model, the method further includes: collecting GIS operation samples of different databases, and establishing a mapping relationship between natural language and multi-version SQL through the GIS operation samples; the mapping relationship includes a spatial mapping relationship and a non-spatial mapping relationship.

[0010] In one example, after constructing the communication interface between the database development management tool and the language large model, the method further includes: determining the multiple databases connected by the database management tool; connecting the large language model to the multiple databases through ODBC to obtain the metadata of the multiple databases; according to the metadata of the multiple databases, obtaining the syntax rules of the multiple databases through the restricted decoding technology.

[0011] In one example, visually displaying the GIS data processing result through the map rendering engine specifically includes: when receiving the visual display request, determining the visual parameters of the processed GIS data; performing spatial calculation processing on the GIS data processing result according to the visual parameters through the database development management tool; visually displaying the GIS data processing result through the map rendering engine according to the spatial calculation processing.

[0012] In one example, the method further includes: confirming to the client whether the visual display result meets the natural language requirements; when it is met, permanently saving the visual display result to the target database.

[0013] In one example, the method further includes: sending the SQL statement to the client for verification; when the SQL statement does not meet the natural language, generating a correction suggestion for the SQL statement; regenerating a new SQL statement according to the correction suggestion, and sending the new SQL statement to the client for verification.

[0014] In one example, an SQL statement is sent to a target database for execution, and the returned result data is received through a management tool, specifically including: monitoring the database resource occupancy when the SQL statement is executed; when the running memory occupancy exceeds a preset threshold, triggering a streaming processing mode to perform chunk calculation on the GIS data to be processed.

[0015] On the other hand, an embodiment of the present application provides a GIS data processing device based on artificial intelligence, including: at least one processor; and a memory communicatively connected to 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 a method for processing GIS data based on artificial intelligence according to any one of the above.

[0016] The above at least one technical solution adopted in the embodiment of the present application can achieve the following beneficial effects:

[0017] By accessing the artificial intelligence large model interface, the system has natural language processing capabilities. This intelligent interaction method breaks through the limitations of traditional database operations on professional SQL writing skills and significantly improves the efficiency of database development and management. At the same time, the GIS data extension function is integrated, combined with the intelligent processing mechanism, to realize the automatic analysis of spatial data in different databases. The system visualizes the analysis results on a map, presenting spatial data and its attribute information in an intuitive graphical way, effectively solving the problems of interoperability of database tools in GIS data processing functions and cumbersome spatial operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the present application, some embodiments of the present application will be described in detail below with reference to the drawings, in which:

[0019] Figure 1 is a schematic flowchart of a method for processing GIS data based on artificial intelligence provided by an embodiment of the present application;

[0020] Figure 2 is a step flowchart of a method for processing GIS data based on artificial intelligence provided by an embodiment of the present application;

[0021] Figure 3 is a schematic structural diagram of a GIS data processing device based on artificial intelligence provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope of protection of this application.

[0023] The following will refer to the drawings to elaborate on some embodiments of this application in detail.

[0024] Figure 1 It is a schematic flowchart of a GIS data processing method based on artificial intelligence provided by an embodiment of this application. This method can be applied to different business fields. Some input parameters or intermediate results in this process allow manual intervention and adjustment to help improve accuracy.

[0025] The implementation of the analysis method involved in the embodiments of this application can be a terminal device or a server, and this application does not impose special restrictions on this. For the convenience of understanding and description, the following embodiments will be described in detail by taking the control system as an example.

[0026] It should be noted that the database development and management tool is a management platform that supports multiple databases (such as Oracle Spatial, PostGIS, SQL Server), and has functions such as database connection management, SQL query, and data processing. The tool integrates GIS data extension functions and is specifically used for storing, querying, analyzing, and visualizing geographic information data.

[0027] Based on this, the specific process of the present invention is as follows:

[0028] S101: Integrate a map rendering engine in the database development and management tool, and construct a communication interface between the database development and management tool and the language large model.

[0029] It should be noted that in some embodiments of this application, before constructing the communication interface between the database development and management tool and the language large model, it is necessary to first train the language large model, establish a spatial and non-spatial semantic mapping library, collect GIS operation samples of different databases, input the operation samples into the language large model, and establish a mapping relationship between natural language and SQL according to the database type of the operation samples and the semantic mapping library; the mapping relationship therein includes a spatial mapping relationship and a non-spatial mapping relationship.

[0030] Furthermore, after establishing the mapping relationship, input natural language for processing GIS data into the language large model, verify the obtained SQL statements, and check the training results. If all the SQL statements pass the verification, it means that the training of the large language model is completed.

[0031] It should also be noted that in some embodiments of the present application, after constructing the communication interface between the database development management tool and the large language model, it is necessary to determine the multiple databases connected by the database management tool; then connect the large language model to the multiple databases through ODBC to obtain the metadata of the multiple databases; according to the metadata of the multiple databases, through the constrained decoding technology, the syntax rules of the multiple databases are obtained. So as to generate SQL statements that match the database type when generating SQL statements.

[0032] Among them, ODBC is an open database connectivity standard that allows programs in any language to access different databases through a unified interface. It provides a database access method independent of programming languages, supports non-relational data sources, and adapts to multiple databases through the "ODBC Driver Manager". Constrained Decoding is a method used in natural language processing (NLP) to dynamically impose constraints during text generation, aiming to ensure that the generated content meets specific rules.

[0033] S102: Receive the natural language for processing GIS data through the database development management tool, and transmit the natural language to the large language model through the communication interface.

[0034] It should be noted that in some embodiments of the present application, when inputting natural language into the database development management tool, in addition to directly sending natural language, the user can also select the conditions for data processing. First, the user inputs their own condition selection, and the management tool receives the data table conditions for GIS data processing. According to the data table conditions, the target data table is determined; the target data table is the data table containing the condition selection. Further, the user can further filter the data in the condition setting area to generate the condition limiting content of the target data table, and display the condition limiting content to the client; the condition limiting content includes spatial limitation and non-spatial limitation.

[0035] It should be noted that to generate the condition limiting content of the target data table, first, the spatial attributes and non-spatial attributes in the target data table conditions need to be parsed; according to the metadata of the target data table, the coordinate system information associated with the spatial attributes and the dimension labels associated with the non-spatial attributes are extracted; then the coordinate system information and the dimension labels are combined to generate the condition limiting content with spatial constraints. And when receiving the limiting information of the data table conditions, the limiting information and the natural language are transmitted to the large language model.

[0036] S103: Convert the natural language into an SQL statement through the language large model, and return the SQL statement to the database development and management tool through the communication interface; the SQL statement includes the target database.

[0037] It should be noted that in some embodiments of the present application, after the user inputs natural language, the trained language large model will convert the natural language into a corresponding SQL statement. For example: "I want to create a stadium at the location of 116.395174, 39.996935 in Beijing, with a 10m buffer zone for the surrounding green belt." Based on the extracted key information, the language large model automatically generates a standard SQL statement, which includes the geometric location data of the stadium and the creation logic of the 10-meter buffer zone. Another example: "I want the intersection result and attribute table of the data in Table A and Table B." The core task of this requirement is to perform a spatial intersection operation on the two tables and extract the data in the intersection part. The system parses the natural language input by the user by accessing the language large model and extracts the following key information: Data sources: Table A and Table B. Operation type: Spatial intersection analysis (Intersection).

[0038] Furthermore, after generating the SQL statement, the system will send the SQL statement to the client for verification; if the SQL statement does not meet the natural language, the system generates a correction suggestion for the SQL statement; and regenerates a new SQL statement according to the correction suggestion, and then sends the new SQL statement to the client for verification again.

[0039] S104: Send the SQL statement to the target database through the database development tool to obtain the GIS data processing result, and perform map visualization display on the GIS data processing result through the map rendering engine.

[0040] It should be noted that in some embodiments of the present application, after the user verification is passed, the management tool sends an SQL query request to the target database, the database engine executes the SQL statement, and monitors the database resource occupancy during the execution of the SQL statement; when the running memory occupancy exceeds the preset threshold, the streaming processing mode is triggered to perform chunk calculation on the GIS data to be processed. Then the data processing result is returned to the management tool. In the management tool, the user can select the visualization option, and determine the visualization parameters of the processed GIS data when receiving the visualization display request; and perform spatial calculation processing on the GIS data processing result according to the visualization parameters through the database development and management tool; then perform map visualization display on the GIS data processing result through the map rendering engine according to the spatial calculation processing.

[0041] Further, after the visual display, the client is used to confirm whether the visual display result meets the natural language requirements. After the user confirms that the data meets the requirements, the user can choose to permanently save the data to the database.

[0042] It should be noted that although the embodiments of the present application are described with reference to Figure 1 to introduce and illustrate steps S101 to S105 in sequence, this does not mean that steps S101 to S105 must be executed in a strict order. The reason why the embodiments of the present application introduce and illustrate steps S101 to S105 in the order shown in Figure 1 is to facilitate those skilled in the art to understand the technical solutions of the embodiments of the present application. In other words, in the embodiments of the present application, the order between steps S101 to S105 can be appropriately adjusted according to actual needs.

[0043] Through Figure 1 the method, an artificial intelligence large model interface is accessed, and the system has natural language processing capabilities. This intelligent interaction method breaks through the limitations of traditional database operations on professional SQL writing skills and significantly improves the efficiency of database development and management. At the same time, the GIS data extension function is integrated, combined with the intelligent processing mechanism, to realize the automatic analysis of spatial data in different databases. The system visualizes the analysis results on a map and presents the spatial data and its attribute information in an intuitive graphical way, effectively solving the problems of interoperability in GIS data processing functions of database tools and cumbersome spatial operations.

[0044] Figure 2 It is a step flow chart of a GIS data processing method based on artificial intelligence provided by an embodiment of the present application.

[0045] In Figure 2 , the processing steps are to first open the database development and management tool, then the user selects conditions, enters text according to the selected conditions, that is, natural language, and automatically generates an SQL statement according to the input natural language. Data analysis, data generation, and data visualization are performed through the SQL language, and then the processed data that meets the standards is permanently stored in the database.

[0046] Figure 3 It is a structural schematic diagram of a GIS data processing device based on artificial intelligence provided by an embodiment of the present application, including:

[0047] At least one processor; and,

[0048] A memory communicatively connected to at least one processor; wherein,

[0049] The memory stores instructions executable by at least one processor, and the instructions are executed by at least one processor to enable the at least one processor to execute an artificial intelligence-based GIS data processing method according to any one of the above.

[0050] A non-volatile computer storage medium for artificial intelligence-based GIS data processing provided by some embodiments of the present application stores computer-executable instructions, and the computer-executable instructions can execute an artificial intelligence-based GIS data processing method according to any one of the above.

[0051] The various embodiments in the present application are all described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiments.

[0052] The devices and media provided by the embodiments of the present application correspond one by one to the methods. Therefore, the devices and media also have beneficial technical effects similar to those of their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be elaborated here.

[0053] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0054] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0055] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction means that implements the function specified in one or more of the acts and / or blocks Figure 1 of one or more acts and / or blocks Figure 1 specified in the flowchart.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the function specified in one or more of the acts and / or blocks Figure 1 of one or more acts and / or blocks Figure 1 specified in the flowchart.

[0057] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0058] The memory may include non-permanent memory in the computer-readable medium, random access memory (RAM), and non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

[0059] Computer-readable media includes both permanent and non-permanent, removable and non-removable media implemented by any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0060] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0061] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modifications, equivalent replacements, improvements, etc. made within the technical principles of the present application shall fall within the protection scope of the present application.

Claims

1. A GIS data processing method based on artificial intelligence, characterized in that: The method comprises: Integrate a map rendering engine into a database development and management tool, and construct a communication interface between the database development and management tool and a large language model; Receiving natural language for processing GIS data through the database development management tool, and transmitting the natural language to the language macro model through the communication interface; Converting the natural language into SQL statements through the language macro model, and returning the SQL statements to the database development management tool through the communication interface; the SQL statements include a target database; The SQL statement is sent to the target database through the database development tool to obtain the GIS data processing result, and the GIS data processing result is displayed on a map through the map rendering engine.

2. The method according to claim 1, characterized in that Before receiving the natural language for processing GIS data through the database development management tool, the method further includes: receiving data table conditions for GIS data processing, and determining a target data table according to the data table conditions; Generating conditional content of the target data table, and displaying the conditional content to the client; The natural language is transmitted to the language model through the communication interface, specifically comprising: When the limiting information of the data table condition is received, the limiting information and the natural language are transmitted to the language macro model.

3. The method according to claim 2, characterized in that The conditional limitation content of generating the target data table specifically includes: Parsing spatial attributes and non-spatial attributes in the target data table condition; Extracting coordinate system information associated with the spatial attribute and dimension labels associated with the non-spatial attribute according to metadata of the target data table; The coordinate system information is combined with the dimension label to generate conditional content with spatial constraints.

4. The method according to claim 1, characterized in that: Before constructing the communication interface between the database development management tool and the language large model, the method further includes: GIS operation samples of different databases are collected, and a mapping relationship between natural language and multi-version SQL is established through the GIS operation samples; the mapping relationship includes a spatial mapping relationship and a non-spatial mapping relationship.

5. The method according to claim 1, characterized in that After constructing the communication interface between the database development management tool and the language large model, the method further includes: determining a plurality of databases to which the database management tool is connected; Connecting the large language model to the multiple databases through ODBC to obtain metadata of the multiple databases; According to the metadata of the multiple databases, the grammatical rules of the multiple databases are obtained through restricted decoding technology.

6. The method according to claim 1, characterized in that The map rendering engine is used to visualize the GIS data processing results on a map, specifically including: Upon receiving a visualization display request, determining visualization parameters of the processed GIS data; Performing spatial calculation processing on the GIS data processing results according to the visualization parameters through the database development management tool; According to the spatial calculation processing, the GIS data processing results are visualized on a map through the map rendering engine.

7. The method according to claim 1, characterized in that After the map rendering engine is used to visualize the GIS data processing result, the method further includes: Confirm with the client whether the visualization result meets the natural language requirement; When the conditions are met, the visual display result is permanently saved in the target database.

8. The method according to claim 1, characterized in that Before returning the SQL statement to the database development management tool through the communication interface, the method further includes: Send the SQL statement to the client for verification; When the SQL statement does not satisfy the natural language, generating a correction suggestion for the SQL statement; A new SQL statement is regenerated according to the correction suggestion, and the new SQL statement is sent to the client for verification.

9. The method according to claim 1, characterized in that: The step of sending the SQL statement to the target database through the database development tool to obtain the GIS data processing result specifically includes: Monitor database resource usage when the SQL statement is executed; When the running memory usage exceeds the preset threshold, the streaming processing mode is triggered to perform block calculations on the GIS data to be processed.

10. A GIS data processing device based on artificial intelligence, characterized in that: include: at least one processor; as well as, a memory communicatively connected to 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 so that the at least one processor can execute the artificial intelligence-based GIS data processing method described in any one of claims 1 to 9.

Images