Data processing method, system and device for indoor electronic map and medium

Abstract

The invention discloses a data processing method, system and device for an indoor electronic map, and a storage medium. The method comprises the following steps: acquiring original data converted from the indoor map and an original attribute set; generating first coordinate data after coordinate conversion according to the original data; generating new attribute data corresponding to the coordinate data according to the first coordinate data; adding the new attribute data to the original attribute set to obtain a first attribute set; screening the first attribute set to obtain a target attribute set; and inputting the first coordinate data and the target attribute set into a JSON template to obtain target data. The method can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data processing method, system, device and storage medium for indoor electronic maps. Background Art

[0002] Currently, there are many types of indoor map data. In related technologies, specific processing methods are usually required for different data types. This processing method is not only complicated, but also lacks automation and relies heavily on the professional knowledge and experience of operators. This not only increases the difficulty of operation, but also increases the requirements for the professional skills of technicians, and consumes a lot of human resources, resulting in increased costs. Therefore, there are still technical problems that need to be solved in related technologies. Summary of the invention

[0003] The purpose of this application is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0004] To this end, an object of an embodiment of the present application is to provide a data processing method, system, device and storage medium for an indoor electronic map. This solution can improve data processing efficiency and save costs.

[0005] In order to achieve the above-mentioned technical objectives, the technical solution adopted by the embodiment of the present application includes: a data processing method for an indoor electronic map, comprising the following steps: obtaining the original data and the original attribute set of the indoor map conversion; generating the first coordinate data after the coordinate conversion according to the original data; generating new attribute data corresponding to the coordinate data according to the first coordinate data; adding the new attribute data to the original attribute set to obtain the first attribute set; screening the first attribute set to obtain the target attribute set; inputting the first coordinate data and the target attribute set into a JSON template to obtain the target data.

[0006] In addition, the method for processing data of an indoor electronic map according to the above embodiment of the present invention may also have the following additional technical features:

[0007] Furthermore, in an embodiment of the present application, generating first coordinate data after coordinate conversion based on the original data specifically includes: performing data conversion on the original data through a Reprojector converter to obtain first coordinate data under the WGS84 coordinate system; wherein the accuracy of the first coordinate data is seven decimal places.

[0008] Furthermore, in an embodiment of the present application, generating new attribute data corresponding to the coordinate data based on the first coordinate data includes: extracting geometric information from the first coordinate data; and generating new attribute data corresponding to the geometric information through a GeometryExtractor tool.

[0009] Further, in an embodiment of the present application, the screening of the first attribute set to obtain a target attribute set specifically includes: determining a second attribute set corresponding to the original data; deleting all attributes in the first attribute set that are different from any attribute in the second attribute set to obtain a target attribute set; wherein the target attribute set includes at least the new attribute data.

[0010] Furthermore, in an embodiment of the present application, the JSON template is obtained by the following steps: creating an initial JSON template and setting a placeholder for the initial JSON template; establishing a mapping relationship between fields in the input data and the placeholder to obtain the JSON template.

[0011] Furthermore, in the embodiment of the present application, the method further includes: using an IMDFValidator automated validation tool to validate the target data.

[0012] Furthermore, in an embodiment of the present application, the raw data for indoor map conversion is obtained by the following steps: obtaining a building plan, a building elevation, and LiDAR data; and digitizing the building plan, the building elevation, and the LiDAR data to obtain the raw data for indoor map conversion.

[0013] On the other hand, the embodiment of the present application further provides a data processing system for an indoor electronic map, comprising:

[0014] An acquisition unit, used for acquiring raw data and raw attribute sets for indoor map conversion;

[0015] A first processing unit, used for generating first coordinate data after coordinate transformation according to the original data;

[0016] A second processing unit, configured to generate new attribute data corresponding to the coordinate data according to the first coordinate data;

[0017] A third processing unit, configured to add the new attribute data to the original attribute set to obtain a first attribute set;

[0018] A fourth processing unit, configured to filter the first attribute set to obtain a target attribute set;

[0019] The fifth processing unit is used to input the first coordinate data and the target attribute set into a JSON template to obtain target data.

[0020] On the other hand, the present application also provides a data processing device for an indoor electronic map, comprising:

[0021] at least one processor;

[0022] at least one memory for storing at least one program;

[0023] When the at least one program is executed by the at least one processor, the at least one processor implements a data processing method for an indoor electronic map as described in any one of the invention contents.

[0024] In addition, the present application also provides a computer-readable storage medium, which stores processor-executable instructions. When the processor-executable instructions are executed by the processor, they are used to execute a data processing method for an indoor electronic map as described in any of the above items.

[0025] The advantages and benefits of the present application will be partially given in the following description, and partially become apparent from the following description, or be understood through the practice of the present application:

[0026] This application can obtain the original data and original attribute set of indoor map conversion; generate the first coordinate data after coordinate conversion based on the original data; generate new attribute data corresponding to the coordinate data based on the first coordinate data; add the new attribute data to the original attribute set to obtain the first attribute set; filter the first attribute set to obtain the target attribute set; input the first coordinate data and the target attribute set into the JSON template to obtain the target data. This application reduces the participation of relevant personnel in the data processing process through automated processing, thereby improving data processing efficiency and saving human and material resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the steps of a data processing method for an indoor electronic map in a specific embodiment of the present invention;

[0028] Figure 2 It is a flow chart of a data processing method of an indoor electronic map in a specific embodiment of the present invention;

[0029] Figure 3 A schematic diagram of the steps of building an indoor map IMDF data conversion model framework in a specific embodiment of the present invention;

[0030] Figure 4 A schematic diagram of a floor (Level) template constructed in a specific embodiment of the present invention;

[0031] Figure 5It is a schematic diagram of the definition of each attribute of a floor (Level) in the IMDF standard in a specific embodiment of the present invention;

[0032] Figure 6 A schematic diagram of a process for realizing batch automatic conversion in a specific embodiment of the present invention;

[0033] Figure 7 It is a structural schematic diagram of a data processing system for an indoor electronic map in a specific embodiment of the present invention;

[0034] Figure 8 The figure is a schematic diagram of the structure of a data processing device for an indoor electronic map in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0035] The embodiments of the present invention are described in detail below with reference to the accompanying drawings to explain the principles and processes of the data processing method, system, device and storage medium of the indoor electronic map in the embodiments of the present invention.

[0036] Reference Figure 1 , the present application provides a data processing method for an indoor electronic map, which may include the following steps S101-S106.

[0037] S101: Obtaining original data and original attribute sets for indoor map conversion.

[0038] S102: Generate first coordinate data after coordinate transformation according to the original data.

[0039] S103. Generate new attribute data corresponding to the first coordinate data.

[0040] S104: Add the new attribute data to the original attribute set to obtain a first attribute set.

[0041] S105: Screen the first attribute set to obtain a target attribute set.

[0042] S106: Input the first coordinate data and the target attribute set into the JSON template to obtain the target data.

[0043] Further, in some feasible embodiments of the present application, generating first coordinate data after coordinate transformation according to the original data may specifically include: performing data transformation on the original data through a Reprojector converter to obtain first coordinate data in the WGS84 coordinate system, wherein the precision of the first coordinate data is seven decimal places.

[0044] Further, in some feasible embodiments of the present application, the step of generating new attribute data corresponding to the coordinate data according to the first coordinate data may include: extracting geometric information from the first coordinate data and generating new attribute data corresponding to the geometric information by using a GeometryExtractor tool.

[0045] Further, in some feasible embodiments of the present application, the process of screening the first attribute set to obtain the target attribute set may specifically include: determining the second attribute set corresponding to the original data. Deleting all attributes in the first attribute set that are different from any attribute in the second attribute set to obtain the target attribute set. The target attribute set may include at least the new attribute data.

[0046] Further, in some feasible embodiments of the present application, the JSON template can be obtained by the following steps: creating an initial JSON template and setting placeholders of the initial JSON template. Establishing a mapping relationship between fields in the input data and placeholders to obtain the JSON template.

[0047] Furthermore, in some feasible embodiments of the present application, the method may also include: using the IMDFValidator automated verification tool to verify the target data.

[0048] Further, in some feasible embodiments of the present application, the raw data for indoor map conversion can be obtained by the following steps: obtaining a building plan, a building elevation, and LiDAR data. The building plan, the building elevation, and LiDAR data are digitized to obtain the raw data for indoor map conversion.

[0049] The specific implementation principle of this application is described below with reference to the accompanying drawings:

[0050] like Figure 2 As shown, the method for efficiently converting indoor electronic map IMDF data based on FME proposed in this embodiment may include the following steps A to D.

[0051] A. Data preparation.

[0052] B. Build the indoor map IMDF data conversion model framework.

[0053] C. Batch automatic conversion is realized.

[0054] D. Conversion results data verification.

[0055] Step A may specifically include: collecting raw data for indoor map conversion, where the raw data is the result of indoor map digitization, generally a geographic database (GDB) as source data. The construction of source data is based on the digital processing of building floor plans, elevations (to obtain elevation information) and LiDAR data. GDB is selected as the storage format for indoor electronic map digitization mainly based on the following three reasons:

[0056] 1. The GDB geographic database is presented in the form of a single folder in the Windows operating system, rather than being scattered into multiple independent files. This format effectively avoids the risk of file loss during data transmission.

[0057] 2. Using the geographic database, you can set the fields in the feature class attribute table as required or optional, thereby preventing the omission of attribute information.

[0058] 3. The geographic database allows domains to be set for fields in the feature class attribute table, which means that users need to choose from preset fixed options when filling in field values, thereby enhancing the standardization and accuracy of the data.

[0059] Reference Figure 3-Figure 5 , step B may specifically include step B1-step B6.

[0060] B1. The original data sources used in this study are stored in the geographic database (GDB). According to the IMD F standard, all data must use the WGS84 coordinate system. Therefore, at the beginning of the data conversion process, the data must be converted to the coordinate system through the Reprojector transformer to ensure that it is compatible with the WGS84 coordinate system.

[0061] B2. In order to embed the geometric information (X, Y, Z data does not exist in the original data attributes) into the final generated GeoJSON file, this study will use the GeometryExtractor tool to store the coordinate information in the GeoJSON format into the corresponding fields. According to the IMDF standard, the accuracy of the coordinate data must be accurate to seven decimal places. Therefore, in the process of extracting coordinate data, this study will ensure that the data accuracy meets the requirements of the IMDF standard.

[0062] B3. Apply the AttributeManager converter to perform necessary management and adjustments on the attribute fields to ensure the accuracy and completeness of the data.

[0063] B4. Use the JSONTemplater converter to construct the JSON template of each feature data, extract specific information from the existing data format (taking the Level layer as an example, it is necessary to extract the layer's attributes and geometric information, where the attributes may include categories, Chinese and English names, Chinese and English abbreviations, address ID, building ID), and organize it into a JSON object or array that meets the IMDF standard requirements.

[0064] B5. Use the JSONFormatter converter to format the data constructed by JSONTemplater to ensure that the generated data strictly complies with the requirements of the JSON standard format.

[0065] B6. Use the AttributeFileWriter converter, select the UTF-8 data encoding format, and ensure that the output file name has ".geojson" as the suffix to map the attribute fields of the input data to the corresponding fields in the GeoJS ON format, output and save to a geojson file.

[0066] For example, taking the Level layer as an example, it is necessary to extract the attributes and geometric information of the layer, where the attributes may include categories, Chinese and English names, Chinese and English abbreviations, address ID, building ID, etc.). Geometric information may include the length, width, and height of the building. First, the user must create a JSON template, which is a file that follows the JSON format and is used to specify the structure of the output JSON and the layout of the required data. In the template, some placeholders can be set, which will be replaced by the corresponding actual data in the subsequent data processing process. Next, the user needs to correspond the fields in the input data to the placeholders defined in the JSON template to complete the mapping. When the input data flows through the JSONTemplater converter, the converter will identify these placeholders and replace them with the actual attribute values ​​from the input data. Through this process, each input feature will be converted into a structured JSON object that conforms to the template definition. If the output needs to be a JSON array, JSONTemplater can combine multiple JSON objects together to form an array containing all objects. The JSON template of the Level layer constructed in JSONTemplater. First, you need to understand the requirements of the IMDF standard for Level data, which can include necessary attribute fields, geometry types, and any specific encoding or structure. According to the IMDF specification, design the Level.geojson template. Then map the Level data fields in the GDB to the corresponding positions of the GeoJSON template. Finally, the Level data in the original geographic database (GDB) is output as a GeoJSON file that meets the IMDF requirements through template mapping and conversion.

[0067] Reference Figure 6 The core of step C is to dynamically set the release parameters. Step C may specifically include steps C1 to C4.

[0068] C1. Confirm parameter settings: First, you need to review the indoor map IMDF data conversion model framework established in step B.

[0069] Confirm the input and output parameters defined in the framework, which are the basis for the model to perform automated data transformation.

[0070] C2. Automatically extract FME publishing parameters.

[0071] Automatically extract the required publishing parameters. First, perform tag filtering, using tags to filter out the parameters that users need to publish. Next, use GUI identification to identify the type of parameters through the graphical user interface (GUI) to ensure the correctness and applicability of the parameters. Next, split the parameters, using line feeds "\" and separators to split the parameters to obtain independent publishing parameters. Then perform program reading, write a program to read these segmented parameters to ensure that they can be correctly identified and used.

[0072] C3. Dynamically execute data conversion model file.

[0073] Using FME's batch processing capabilities, dynamically apply the read parameters to the data conversion model workspace file. Use the program to read the published parameters extracted in step C2. According to the read parameters, dynamically adjust the settings in the data conversion model to achieve dynamic configuration of parameters. Then, execute multiple data conversion models through automated scripts or commands to achieve batch data conversion.

[0074] C4. Data conversion and output.

[0075] After the parameters are set dynamically, FME will perform the data conversion according to these parameters. FME automatically executes the data conversion process according to the configured parameters. After the conversion is completed, FME will output the conversion results, usually a new data format or a processed dataset.

[0076] Step D may specifically include:

[0077] D1. Use the IMDFValidator automated validation tool to check whether the data structure, attribute values, and geometric shapes meet the IMDF standard requirements according to the requirements of the IMDF specification. Using IMDFValidator helps ensure that the submitted data set is complete and accurate, and reduces the risk of submission failure due to data problems. By performing validation during the conversion process, IMDFValidator helps reduce the time spent on manual checking and correcting data, improving overall work efficiency.

[0078] In summary, the data processing method of the indoor electronic map of the present application has the following advantages:

[0079] 1. This application simplifies the complex data processing process through automation technology, reduces the reliance on manual operations, and thus significantly improves the efficiency and accuracy of data processing. At the same time, by optimizing the data conversion algorithm, the data processing time is shortened, ensuring that indoor map data can quickly respond to environmental changes, ensuring the accuracy and up-to-dateness of map information, and meeting users' needs for real-time information. In addition, the design of the conversion framework reduces the reliance on professional technicians and effectively reduces labor costs.

[0080] In addition, refer to Figure 7 ,and Figure 1 Corresponding to the method, an embodiment of the present application also provides a data processing system for an indoor electronic map. The system may include: an acquisition unit 1001, a first processing unit 1002, a second processing unit 1003, a third processing unit 1004, a fourth processing unit 1005 and a fifth processing unit 1006. The acquisition unit 1001 can be used to acquire the original data and the original attribute set of the indoor map conversion. The first processing unit 1002 can be used to generate the first coordinate data after the coordinate conversion according to the original data. The second processing unit 1003 can be used to generate new attribute data corresponding to the coordinate data according to the first coordinate data. The third processing unit 1004 can be used to add the new attribute data to the original attribute set to obtain the first attribute set. The fourth processing unit 1005 can be used to filter the first attribute set to obtain the target attribute set. The fifth processing unit 1006 can be used to input the first coordinate data and the target attribute set into the JS ON template to obtain the target data.

[0081] It should be noted that the acquisition unit 1001 may be any unit connected to a processor inside a gateway or a device. The specific device connection mode and device settings between the acquisition unit 1001 and the first processing unit 1002, and between the first processing unit 1002 and the second processing unit 1003 are not limited.

[0082] It should be noted that the contents of the above-mentioned indoor electronic map data processing method embodiment are all applicable to the data processing system embodiment of the present indoor electronic map. The functions specifically implemented by the data processing system embodiment of the present indoor electronic map are the same as those of the above-mentioned indoor electronic map data processing method embodiment, and the beneficial effects achieved are also the same as those achieved by the above-mentioned indoor electronic map data processing method embodiment.

[0083] and Figure 1 Corresponding to the method, the embodiment of the present application also provides a data processing device for indoor electronic maps, and its specific structure can be referred to Figure 8 ,include:

[0084] At least one processor 1011.

[0085] At least one memory 1012 is used to store at least one program.

[0086] When the at least one program is executed by the at least one processor, the at least one processor implements the data processing method for the indoor electronic map.

[0087] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0088] and Figure 1 Corresponding to the method, an embodiment of the present application further provides a computer-readable storage medium, which stores processor-executable instructions, and the processor-executable instructions are used to execute the data processing method of the indoor electronic map when executed by the processor.

[0089] The contents of the above-mentioned indoor electronic map data processing method embodiment are all applicable to the present storage medium embodiment. The functions specifically implemented by the present storage medium embodiment are the same as those of the above-mentioned indoor electronic map data processing method embodiment, and the beneficial effects achieved are also the same as those achieved by the above-mentioned indoor electronic map data processing method embodiment.

[0090] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are expected, wherein the order of various operations is changed and the sub-operation described as a part of a larger operation is performed independently.

[0091] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0092] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several programs to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0093] The logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable programs for implementing the logical functions, and may be embodied in any computer-readable medium for use by a program execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch and execute a program from a program execution system, device or apparatus), or in conjunction with such program execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by a program execution system, device or apparatus, or in conjunction with such program execution systems, devices or apparatuses.

[0094] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0095] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable program execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0096] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0097] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0098] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the described embodiments. Technical personnel familiar with the field may make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A data processing method for an indoor electronic map, characterized in that: The following steps are involved: Obtaining raw data and raw attribute sets for indoor map conversion; Generate first coordinate data after coordinate transformation according to the original data; generating new attribute data corresponding to the coordinate data according to the first coordinate data; Adding the new attribute data to the original attribute set to obtain a first attribute set; Screening the first attribute set to obtain a target attribute set; The first coordinate data and the target attribute set are input into a JSON template to obtain target data.

2. The method for processing indoor electronic map data according to claim 1, characterized in that: The step of generating first coordinate data after coordinate transformation according to the original data specifically includes: The original data is converted by a Reprojector converter to obtain first coordinate data in a WGS84 coordinate system; wherein the precision of the first coordinate data is seven decimal places.

3. The data processing method for indoor electronic maps according to claim 1, characterized in that: The step of generating new attribute data corresponding to the coordinate data according to the first coordinate data includes: extracting geometric information from the first coordinate data; The new attribute data corresponding to the geometric information is generated by the GeometryExtractor tool.

4. The data processing method for indoor electronic maps according to claim 1, characterized in that: The screening of the first attribute set to obtain a target attribute set specifically includes: Determining a second attribute set corresponding to the original data; All attributes in the first attribute set that are different from any attribute in the second attribute set are deleted to obtain a target attribute set; wherein the target attribute set at least includes the new attribute data.

5. The data processing method for indoor electronic maps according to claim 1, characterized in that: The JSON template is obtained by the following steps: Creating an initial JSON template and setting placeholders for the initial JSON template; A mapping relationship between the fields in the input data and the placeholders is established to obtain the JSON template.

6. The method for processing indoor electronic map data according to claim 1, characterized in that: The method further comprises: The target data is validated using the IMDFValidator automated validation tool.

7. The data processing method for indoor electronic maps according to claim 1, characterized in that: The raw data of the indoor map conversion is obtained by the following steps: Obtain building floor plans, building elevations, and LiDAR data; The building plan, building elevation and LiDAR data are digitally processed to obtain raw data for indoor map conversion.

8. A data processing system for indoor electronic maps, characterized in that: include: An acquisition unit, used for acquiring raw data and raw attribute sets for indoor map conversion; A first processing unit, used for generating first coordinate data after coordinate transformation according to the original data; A second processing unit, configured to generate new attribute data corresponding to the coordinate data according to the first coordinate data; A third processing unit, configured to add the new attribute data to the original attribute set to obtain a first attribute set; A fourth processing unit, configured to filter the first attribute set to obtain a target attribute set; The fifth processing unit is used to input the first coordinate data and the target attribute set into a JSON template to obtain target data.

9. A data processing device for indoor electronic maps, characterized in that include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the data processing method for an indoor electronic map as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing instructions executable by a processor, characterized in that: The processor-executable instructions are used to execute the data processing method for an indoor electronic map as described in any one of claims 1 to 7 when executed by the processor.

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