Multi-level identification data management method under full-space unmanned system

Abstract

The invention relates to data management, in particular to a multi-level identification data management method under a full-space unmanned system, which comprises the following steps of: acquiring multi-source data, and constructing corresponding multi-level identifications according to data service attributes; establishing a management partition according to the multi-level identifier, and associating the management partition with the multi-level identifier; dividing the multi-source data into corresponding management partitions based on the multi-level identifiers; the corresponding management partitions are directly reached through the multi-level identifiers, so that efficient data retrieval is carried out; according to the technical scheme provided by the invention, the defect that massive multi-source data generated in a full-space unmanned system is difficult to efficiently manage in the prior art can be effectively overcome.

Description

Technical Field

[0001] The present invention relates to data management, and in particular to a multi-level identification data management method under a full-space unmanned system. Background Art

[0002] In a full-space unmanned system, various devices such as unmanned aerial vehicles, unmanned vehicles, and unmanned boats cooperate to generate a large amount of multi-source data, including images, videos, sensor monitoring data, and task execution records. These data have wide sources and complex types, and traditional data management methods are difficult to effectively classify and identify. On the one hand, due to the lack of an effective classification mechanism, a large amount of data is stored disorderly, resulting in extremely difficult data retrieval, low data retrieval efficiency, and difficulty in meeting the need for quickly obtaining specific data. On the other hand, the data generated by different types of devices is chaotic, and traditional data management methods cannot make full use of the characteristics of storage devices, resulting in waste of storage resources. In addition, with the continuous growth of the data volume, the complexity of data management increases exponentially, seriously affecting the data processing ability and operation efficiency of the full-space unmanned system. Summary of the Invention

[0003] (1) Technical Problems to be Solved

[0004] In view of the above-mentioned drawbacks of the prior art, the present invention provides a multi-level identification data management method under a full-space unmanned system, which can effectively overcome the defect that it is difficult to efficiently manage the large amount of multi-source data generated in the full-space unmanned system in the prior art.

[0005] (2) Technical Solutions

[0006] To achieve the above object, the present invention is realized through the following technical solutions:

[0007] A multi-level identification data management method under a full-space unmanned system includes the following steps:

[0008] S1. Collect multi-source data and construct corresponding multi-level identifications according to the data service attributes;

[0009] S2. Establish management partitions according to the multi-level identifications and associate the management partitions with the multi-level identifications;

[0010] S3. Divide the multi-source data into corresponding management partitions based on the multi-level identifications;

[0011] S4. Directly reach the corresponding management partition through the multi-level identification for efficient data retrieval.

[0012] Preferably, in S1, collecting multi-source data and constructing corresponding multi-level identifications according to the data service attributes includes:

[0013] In a full-space unmanned system, multi-source data generated by various devices is collected, and corresponding multi-level identifiers are added in real time according to the data service attributes;

[0014] Among them, the data types of the multi-source data include image data, video data, and structured data, the data sources of the multi-source data include drones, unmanned vehicles, and unmanned boats, and the business scenarios of the multi-source data include logistics distribution, environmental monitoring, and urban governance;

[0015] The structure of the multi-level identifier is data type / data source / business scenario / device identification code.

[0016] Preferably, in S2, management partitions are established according to the multi-level identifiers, and the management partitions are associated with the multi-level identifiers, including:

[0017] S21. According to the data types in all the multi-level identifiers, create an ImageStorage management area for storing image data, create a VideoStorage management area for storing video data, and create a StructuredDataDB management area for storing structured data;

[0018] S22. According to the data sources in all the multi-level identifiers, under each management area, create a UAV management domain for storing drone data, create a UGV management domain for storing unmanned vehicle data, and create a USP management domain for storing unmanned boat data;

[0019] S23. According to the business scenarios in all the multi-level identifiers, under each management domain, create a WLPS topic domain for storing logistics distribution data, create a HJJC topic domain for storing environmental monitoring data, and create a CSZL topic domain for storing urban governance data;

[0020] S24. According to the device identification codes in all the multi-level identifiers, under each topic domain, create corresponding device domains for storing data from the corresponding devices.

[0021] Preferably, in S3, the multi-source data is divided into corresponding management partitions based on the multi-level identifiers, including:

[0022] According to the data type, data source, business scenario, and device identification code in the multi-level identifier, the corresponding management area, management domain, topic domain, and device domain are determined in sequence in the management partition, and the multi-source data is stored.

[0023] Preferably, in S4, the corresponding management partition is directly accessed through the multi-level identifier for efficient data retrieval, including:

[0024] A dedicated data retrieval interface is established. Users input the multi-level identifiers to be retrieved in the data retrieval interface, and accurately locate the corresponding management regions, management domains, subject domains, and device domains in the management partition according to the multi-level identifiers, and query the multi-source data.

[0025] A computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the multi-level identifier data management method under the all-space unmanned system described above is implemented.

[0026] A computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, each step of the multi-level identifier data management method under the all-space unmanned system described above is implemented.

[0027] (III) Advantageous Effects

[0028] Compared with the prior art, the multi-level identifier data management method provided by the present invention under the all-space unmanned system has the following advantageous effects:

[0029] 1) Improve data management ability: The clear multi-level identifier and classification management method make data management more efficient, facilitating statistical analysis, backup management, and permission control of data, and providing strong support for the stable operation and business expansion of the all-space unmanned system;

[0030] 2) Improve data retrieval efficiency: The multi-level identifier system enables data to have clear classification and positioning information, greatly shortening the data retrieval time and improving the accuracy and efficiency of data retrieval. For example, when searching for image data collected by a certain unmanned aerial vehicle during environmental monitoring tasks within a specific time period, by inputting the corresponding multi-level identifiers, the target data can be quickly located, and the retrieval time is shortened by more than 80% compared with the traditional data management method. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0032] Figure 1 It is a flowchart of the present invention;

[0033] Figure 2 It is a schematic diagram of the management partition established according to the multi-level identifiers in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] A multi-level identification data management method in an all-space unmanned system, as Figure 1 shown, S1: Collect multi-source data, and construct corresponding multi-level identifications according to the data service attributes, specifically including:

[0036] In an all-space unmanned system, collect multi-source data generated by various devices, and add corresponding multi-level identifications in real time according to the data service attributes;

[0037] Among them, the data types of the multi-source data include image data, video data, and structured data, the data sources of the multi-source data include unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and unmanned surface vessels (USVs), and the business scenarios of the multi-source data include logistics distribution, environmental monitoring, and urban governance;

[0038] The structure of the multi-level identification is data type / data source / business scenario / device identification code.

[0039] For example, for the video data generated by a logistics distribution UAV with the device identification code SN001, the corresponding multi-level identification constructed for it is: VideoStorage / UAV / WLPS / SN001.

[0040] S2: As Figure 2 shown, establish management partitions according to the multi-level identifications, and associate the management partitions with the multi-level identifications, specifically including:

[0041] S21: According to the data types in all the multi-level identifications, create an ImageStorage management area for storing image data, create a VideoStorage management area for storing video data, and create a StructuredDataDB management area for storing structured data;

[0042] S22: According to the data sources in all the multi-level identifications, under each management area, create a UAV management domain for storing UAV data, create a UGV management domain for storing UGV data, and create a USP management domain for storing USV data;

[0043] S23. According to the business scenarios in all multi-level identifiers, in each management domain, create a logistics distribution WLPS topic domain to store logistics distribution data, create an environmental monitoring HJJC topic domain to store environmental monitoring data, and create an urban governance CSZL topic domain to store urban governance data;

[0044] S24. According to the device identification codes in all multi-level identifiers, in each topic domain, create a corresponding device domain to store data from the corresponding device.

[0045] S3. Based on the multi-level identifiers, divide the multi-source data into corresponding management partitions, specifically including:

[0046] According to the data type, data source, business scenario, and device identification code in the multi-level identifiers, sequentially determine the corresponding management region, management domain, topic domain, and device domain in the management partition, and store the multi-source data.

[0047] For example, in the all-space unmanned system, the multi-level identifier corresponding to the video data generated by the unmanned aerial vehicle (UAV) in the urban governance scenario is: VideoStorage / UAV / CSZL, and its corresponding management partition is: VideoStorage management region - UAV management domain - urban governance CSZL topic domain. Thus, the video data generated by the UAV in the urban governance scenario can be stored in this management partition.

[0048] S4. Through the multi-level identifiers, directly access the corresponding management partition for efficient data retrieval, specifically including:

[0049] Establish a dedicated data retrieval interface. The user inputs the multi-level identifier to be retrieved in the data retrieval interface. According to the multi-level identifier, accurately locate the corresponding management region, management domain, topic domain, and device domain in the management partition, and query the multi-source data.

[0050] For example, if the user wants to query the structured data of the urban governance UAV SN001, they can directly input the multi-level identifier to be retrieved in the data retrieval interface: StructuredDataDB / UAV / CSZL / SN001, and then accurately locate the corresponding management region in the management partition: StructuredDataDB management region - UAV management domain - urban governance CSZL topic domain. Then, retrieve the structured data of the UAV SN001 through the unique device identification code, thereby effectively improving the data retrieval efficiency.

[0051] A computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the above multi-level identifier data management method under the all-space unmanned system.

[0052] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each step of the above-mentioned multi-level identification data management method under the all-space unmanned system is implemented.

[0053] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-level identification data management method under a full-space unmanned system, characterized in that: It includes the following steps: S1. Collect multi-source data and construct corresponding multi-level identifiers according to the data service attributes; S2. Establish management partitions based on the multi-level identifiers and associate the management partitions with the multi-level identifiers; S3. Divide the multi-source data into corresponding management partitions based on the multi-level identifiers; S4. Directly access the corresponding management partition through the multi-level identifiers for efficient data retrieval.

2. The multi-level identification data management method in the all-space unmanned system according to claim 1, wherein: In S1, collecting multi-source data and constructing corresponding multi-level identifiers according to the data service attributes includes: In a full-space unmanned system, collect multi-source data generated by various devices and add corresponding multi-level identifiers in real time according to the data service attributes; Among them, the data types of the multi-source data include image data, video data, and structured data, the data sources of the multi-source data include drones, unmanned vehicles, and unmanned boats, and the business scenarios of the multi-source data include logistics distribution, environmental monitoring, and urban governance; The structure of the multi-level identifier is data type / data source / business scenario / device identification code.

3. The multi-level identification data management method in the all-space unmanned system according to claim 2, wherein: In S2, establishing management partitions based on the multi-level identifiers and associating the management partitions with the multi-level identifiers includes: S21. Create an ImageStorage management area for storing image data, a VideoStorage management area for storing video data, and a StructuredDataDB management area for storing structured data according to the data types in all multi-level identifiers; S22. Create a UAV management domain for storing drone data, a UGV management domain for storing unmanned vehicle data, and a USP management domain for storing unmanned boat data under each management area according to the data sources in all multi-level identifiers; S23. Create a WLPS theme domain for storing logistics distribution data, an HJJC theme domain for storing environmental monitoring data, and a CSZL theme domain for storing urban governance data under each management domain according to the business scenarios in all multi-level identifiers; S24. Create corresponding device domains for storing data from corresponding devices under each theme domain according to the device identification codes in all multi-level identifiers.

4. The multi-level identification data management method in the all-space unmanned system according to claim 3, characterized in that: In S3, dividing the multi-source data into corresponding management partitions based on the multi-level identifiers includes: According to the data type, data source, business scenario, and device identification code in the multi-level identifier, sequentially determine the corresponding management area, management domain, theme domain, and device domain in the management partition, and store the multi-source data.

5. The multi-level identification data management method in the all-space unmanned system according to claim 4, characterized in that: In S4, directly accessing the corresponding management partition through the multi-level identifier for efficient data retrieval includes: Establish a dedicated data retrieval interface. The user inputs the multi-level identifier to be retrieved in the data retrieval interface, accurately locates to the corresponding management area, management domain, theme domain, and device domain in the management partition according to the multi-level identifier, and queries the multi-source data.

6. A computer device, characterized in that: It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the multi-level identifier data management method under the full-space unmanned system according to any one of claims 1-5.

7. A computer-readable storage medium, characterized in that: A computer program is stored thereon. When the computer program is executed by a processor, it implements each step of the multi-level identification data management method under the all-space unmanned system described in any one of claims 1-5.

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