Automatic MQTT data integration method and system and electronic equipment
By using an automated MQTT data integration method, the MQTT topic structure and payload information are parsed, and the data receiver mode is intelligently inferred. This enables automatic configuration of the data receiver, solves the problems of data latency and manual configuration errors, and ensures timely data processing and storage.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HANGZHOU YINGYUN TECH CO LTD
- Filing Date
- 2026-02-03
- Publication Date
- 2026-05-01
AI Technical Summary
In existing technologies, manual data pipeline configuration between MQTT brokers and backend data systems suffers from data latency and human configuration errors, leading to data loss or delayed processing.
By parsing the MQTT topic structure or examining the topic structure and payload published to the topic, the target data pattern required by the data receiver can be intelligently inferred.
It enables real-time monitoring of new topics, automatic configuration of data receivers, avoidance of data loss or delayed processing, reduction of operational costs, reduction of manual configuration errors, and ensures the correct capture and storage of data.
Smart Images
Figure CN121967528A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of Internet of Things (IoT) data processing technology, and in particular to an automated MQTT data integration method, system, and electronic device. Background Technology
[0002] In IoT systems, one of the core functions of the Message Queuing Telemetry Transport (MQTT) agent is to act as a central hub for data collection, forwarding the collected data to various data storage and processing systems, such as time-series databases (e.g., TimescaleDB, InfluxDB), data warehouses, or logistics processing platforms. This process is often referred to as data integration or data bridging.
[0003] Currently, data bridging generally requires manual configuration. However, this configuration method has the following drawbacks: (1) Manual configuration is prone to human error. When introducing new device types or data streams, developers or maintenance personnel must manually create the corresponding data tables, sets, or metrics in the target database and configure the correct schema. This process is time-consuming and prone to human error. (2) Data availability delay. Manually configuring the backend data receiving system takes time, which may result in the loss or delayed processing of data generated by new topics before the backend is ready. (3) Lack of tight coupling and flexibility. Data integration logic is usually hard-coded, making it difficult for the system to adapt to changes in topic structure or data format.
[0004] Therefore, the current manual data pipeline configuration between the MQTT broker and the backend data system suffers from data latency and human configuration errors, which is an operational bottleneck in current IoT deployments. Summary of the Invention
[0005] This application provides an automated MQTT data integration method, system, and electronic device to at least address the problems of data latency and human configuration errors in related technologies.
[0006] In a first aspect, embodiments of this application provide an automated MQTT data integration method, the method being applied to an MQTT broker, the MQTT broker cooperating with a client and a data receiving end, the method comprising: Receive a message sent by the client and determine whether the target topic in the message is different from the topic in the proxy; If so, the message is parsed to obtain the topic structure and payload information, and the target data mode of the data receiving end is determined from the predefined structure patterns based on the topic structure and payload information. The corresponding target template is determined according to the pre-configured data receiver type. The data receiver is configured according to the target data mode and the target template, and the target message related to the target topic is sent to the data receiver.
[0007] In one embodiment, parsing the message to obtain the topic structure and payload information includes: The name of the target topic in the message is parsed to extract metadata; The message payload in the message is analyzed to identify field names and data types.
[0008] In one embodiment, determining the target data pattern of the data receiver from predefined structural patterns based on the topic structure and payload information includes: Based on preset application rules, intermediate modes are obtained by filtering predefined structural patterns according to the topic structure and load information; The target data pattern is determined from the intermediate patterns using a machine learning classification algorithm based on the topic structure and payload information.
[0009] In one embodiment, the target template includes preset commands and API call formats for interacting with the data receiving end, and configuring the data receiving end according to the target data pattern and the target template includes: Determine the target supply instruction based on the target data pattern and target template; Connect to the data receiving end according to the API call format, and execute the target supply instruction to configure the data receiving end.
[0010] In one embodiment, sending the target message related to the target topic to the data receiving end includes: In response to the completion of the configuration of the data receiving end, all target messages related to the target topic will be automatically forwarded to the corresponding configured data receiving end.
[0011] In one embodiment, before parsing the message to obtain the topic structure and payload information, the method further includes: Determine whether the target topic can match at least one of the predefined structural patterns; If so, the message is parsed to obtain the topic structure and payload information; If not, the message will be processed according to a preset standard topic.
[0012] Secondly, embodiments of this application provide an automated MQTT data integration system. The system is applied to an MQTT broker, which cooperates with a client and a data receiver. The system includes: Judgment module: Used to receive messages sent by the client and determine whether the target topic in the message is different from the topic in the proxy; Inference module: When the target topic in the message is different from the topic in the agent, it parses the message to obtain topic structure and payload information, and determines the target data pattern of the data receiving end from the predefined structure pattern based on the topic structure and payload information; Integration module: used to determine the corresponding target template according to the pre-configured data receiving end type, configure the data receiving end according to the target data mode and target template, and send the target message related to the target topic to the data receiving end.
[0013] Thirdly, embodiments of this application provide a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement an automated MQTT data integration method as described in the first aspect above.
[0014] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an automated MQTT data integration method as described in the first aspect above.
[0015] The automated MQTT data integration method, system, and electronic device provided in this application have at least the following technical effects.
[0016] This application monitors new topics in real time, shifting the responsibility of configuring the data receiver from manual operation to the MQTT broker itself. When a client device publishes a new, unseen message topic to the MQTT broker, it intelligently infers the target data pattern required by the data receiver by parsing the MQTT topic structure or examining the initial message payload published to that topic. The data receiver is then automatically configured by combining the inferred target data pattern with the target template of the data receiver. This eliminates the need for manual configuration of the backend data receiver, preventing data generated by new topics from being lost or delayed before the backend is ready. It reduces operational overhead, minimizes manual configuration errors, and ensures that new IoT device data is correctly captured and stored from the very first message. Furthermore, by using predefined templates to guide the pattern inference and configuration process, the MQTT broker maintains automation while possessing a high degree of customization capability. Attached Figure Description
[0017] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating an automated MQTT data integration method according to an embodiment of this application; Figure 2 This is a structural block diagram of an automated MQTT data integration system according to an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0018] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.
[0019] Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, any changes to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.
[0020] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.
[0021] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects are in an "or" relationship. The terms "first," "second," and "third" used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.
[0022] In a first aspect, embodiments of this application provide an automated MQTT data integration method, which is applied to an MQTT broker, and the MQTT broker cooperates with a client and a data receiving end. Figure 1 This is a flowchart illustrating an automated MQTT data integration method according to an embodiment of this application, such as... Figure 1 As shown, the method includes: Step S101: Receive a message sent by the client and determine whether the target topic in the message is different from the topic in the proxy.
[0023] Optionally, the MQTT broker is configured to monitor new MQTT topics. When a client device publishes a message to the MQTT broker on a new, unseen topic, it will automatically trigger a subsequent provisioning workflow.
[0024] Step S102: If the target topic in the message is different from the topic in the agent, the message is parsed to obtain the topic structure and payload information, and the target data pattern of the data receiver is determined from the predefined structure pattern based on the topic structure and payload information.
[0025] Optionally, when a client device publishes a new, unseen message topic to the MQTT broker, the target data pattern corresponding to the data receiver can be intelligently inferred by parsing the MQTT topic structure or analyzing the message payload. For example, the target data pattern of the data receiver can be determined from a predefined structural pattern using predefined application rules, exact matching algorithms (such as hash index matching), similarity calculation methods, machine learning algorithms, etc. (e.g., automatically inferring what table structure the target database should have). The topic structure could be, for example, company / device type / device ID / measurement metric; the message payload could be, for example, a JSON structure.
[0026] In this way, when introducing new device types or data streams, developers or operations personnel do not need to manually configure the correct schema, which helps reduce errors in subsequent data integration and simplifies and accelerates the MQTT data integration process. Furthermore, by using predefined templates to guide schema inference and subsequent configuration, the MQTT broker maintains automation while possessing a high degree of customization capability.
[0027] In one example, before parsing the message to obtain the topic structure and payload information, the method further includes: determining whether the target topic matches at least one predefined structural pattern. If yes, the message is parsed to obtain the topic structure and payload information. If not, the message is processed according to a preset standard topic.
[0028] Optionally, when the target topic is a new topic, the MQTT broker determines whether the new topic matches a user-defined pattern. If it does not match, it is processed as a standard topic; if it matches, an automated provisioning workflow is triggered. Predefined structural patterns include, for example, devices / + / telemetry.
[0029] In one example, step S102 parses the message to obtain the topic structure and payload information, including: parsing the name of the target topic in the message to extract metadata; and analyzing the message payload in the message to identify field names and data types.
[0030] Optionally, based on the initial message of the new topic, the topic name is parsed in parallel to extract metadata (such as device type), and the message payload (such as a JSON object) is analyzed to identify field names and data types. This facilitates subsequent inference of the target data pattern at the data receiver based on the payload information and topic structure.
[0031] In one example, step S102, which determines the target data pattern of the data receiver from a predefined structural pattern based on the subject structure and load information, includes: Step S1021: Based on preset application rules, filter the predefined structural patterns according to the theme structure and load information to obtain intermediate patterns.
[0032] Optionally, the application rules include: topic-level mapping rules and payload format verification rules. Topic-level mapping rules strongly bind a fixed topic level to the core identifier of the schema. For example, if the third level of the topic is "data type," then only schemas with the same "data type" field in the schema library will be matched. Payload format verification rules only match schemas with the same payload format type. In this way, irrelevant schemas can be quickly excluded through preset application rules, reducing the computational load of subsequent algorithms.
[0033] Step S1022: Determine the target data pattern from the intermediate patterns using a machine learning classification algorithm based on the topic structure and payload information.
[0034] Optionally, features are extracted from the topic structure and payload information to train a classification model. The model is then used to match target data patterns. Topic features include the number of levels and word vectors for each level's strings; payload features include the number of fields, word vectors for field names, value types, and whether timestamps are included. Classification models include Naive Bayes, Random Forest, or deep learning models.
[0035] In this way, when a new topic emerges, the target data pattern required by the data receiver is intelligently inferred by parsing the MQTT topic structure or examining the initial message payload published to that topic. This eliminates the need for manual configuration of the correct pattern, reducing errors in subsequent data integration and simplifying and accelerating the MQTT data integration process.
[0036] Step S103: Determine the corresponding target template according to the pre-configured data receiver type, configure the data receiver according to the target data mode and target template, and send the target message related to the target topic to the data receiver.
[0037] Optionally, a corresponding template can be automatically selected based on the configured target data receiver type (such as TimescaleDB, InfluxDB). The MQTT broker communicates directly with the data receiver through the API in the target template, configures the data receiver using the inferred target data pattern, and automatically sends instructions (such as CREATE TABLE) to the data receiver to create the required data tables, measures, or collections and start forwarding data, thus eliminating the need for any manual intervention in the database.
[0038] This approach eliminates the need for manual configuration of the backend data receiver, preventing data generated by new topics from being lost or delayed before the backend is ready. It reduces operational overhead, minimizes manual configuration errors, and ensures that new IoT device data is correctly captured and stored from the very first message. Furthermore, predefined templates guide the pattern inference and configuration process, enabling the MQTT broker to maintain automation while offering a high degree of customization.
[0039] In one example, the target template includes preset commands and API call formats for interacting with the data receiver. Step S103 includes: determining the target supply instruction based on the target data pattern and the target template; connecting the data receiver according to the API call format; and executing the target supply instruction to configure the data receiver.
[0040] Optionally, the system selects a corresponding target template based on the configured target data receiver type (e.g., TimescaleDB, InfluxDB). The target template contains the specific commands and API call formats required to interact with the data receiver. Combining the target data schema with the data receiver's target template generates the actual target provisioning commands, such as a SQL CREATE TABLE statement. The MQTT broker, acting as a client, connects to the data receiver's management API and executes the generated target provisioning commands to create the required data tables, measures, or collections, without any manual intervention on the data receiver.
[0041] In this way, the responsibility for configuring the data receiver is transferred from manual operation to the MQTT broker itself. By combining the inferred target data pattern with the target template of the data receiver, the actual target supply command is generated, automatically configuring the data receiver. This simplifies and accelerates the MQTT data integration process, reduces operational overhead, and prevents data generated by new topics from being lost or delayed before the backend is ready. Furthermore, by using predefined templates to guide the pattern inference and configuration process, the MQTT broker maintains automation while possessing a high degree of customization capability.
[0042] In one example, step S103 includes: in response to the data receiver being configured, all target messages related to the target topic are automatically forwarded to the corresponding configured data receiver.
[0043] Optionally, once the data receiver is configured, the MQTT broker will automatically begin forwarding all subsequent messages for the new topic to the newly created table or metric, ensuring seamless data persistence and preventing data generated by the new topic from being lost or delayed before the backend is ready.
[0044] In summary, this application monitors new topics in real time, shifting the responsibility for configuring the data receiver from manual operation to the MQTT broker itself. When a client device publishes a new, unseen message topic to the MQTT broker, the target data pattern required by the data receiver is intelligently inferred by parsing the MQTT topic structure or examining the initial message payload published to that topic. The inferred target data pattern is then combined with the data receiver's target template to generate the actual target provisioning command, automatically configuring the data receiver. This eliminates the need for manual configuration of the backend data receiver, preventing data generated by new topics from being lost or delayed before the backend is ready. It reduces operational overhead, minimizes manual configuration errors, and ensures that new IoT device data is correctly captured and stored from the very first message. Furthermore, by using predefined templates to guide the pattern inference and configuration process, the MQTT broker maintains automation while possessing a high degree of customization capability.
[0045] Secondly, embodiments of this application provide an automated MQTT data integration system, which is applied to an MQTT broker, and the MQTT broker works in conjunction with the client and the data receiver. Figure 2 This is a structural block diagram of an automated MQTT data integration system according to an embodiment of this application, such as... Figure 2 As shown, the system includes: Judgment module 100: Used to receive messages sent by the client and determine whether the target topic in the message is different from the topic in the proxy.
[0046] Inference module 200: When the target topic in the message is different from the topic in the agent, it parses the message to obtain the topic structure and payload information, and determines the target data pattern of the data receiver from the predefined structural pattern based on the topic structure and payload information.
[0047] Integration module 300: Used to determine the corresponding target template according to the pre-configured data receiver type, configure the data receiver according to the target data mode and target template, and send the target message related to the target topic to the data receiver.
[0048] In one example, the inference module 200 includes: Used to parse the name of the target topic in the message to extract metadata.
[0049] Analyze the message payload in the message to identify field names and data types.
[0050] In one example, the inference module 200 includes: This is used to filter predefined structural patterns based on the theme structure and load information to obtain intermediate patterns according to preset application rules.
[0051] The target data pattern is determined from the pattern based on the topic structure and payload information using a machine learning classification algorithm.
[0052] In one example, the target template includes preset commands and API call formats for interacting with the data receiver, and the integration module 300 includes: Used to determine target supply instructions based on target data patterns and target templates. Connects to the data receiver according to the API call format and executes the target supply instructions to configure the data receiver.
[0053] In one example, the integration module 300 includes: in response to the data receiver being configured, automatically forwarding all target messages related to the target topic to the correspondingly configured data receiver.
[0054] In one example, the system also includes: determining whether the target topic can match at least one predefined structural pattern; if so, parsing the message to obtain topic structure and payload information; if not, processing the message according to a preset standard topic.
[0055] In summary, this application utilizes a judgment module to monitor new topics in real time, shifting the responsibility for configuring the data receiver from manual operation to the MQTT broker itself. When a client device publishes a new, unseen message topic to the MQTT broker, the inference module parses the MQTT topic structure or examines the initial message payload published to that topic to intelligently infer the target data pattern required by the data receiver. The integration module combines the inferred target data pattern with the data receiver's target template to generate the actual target provisioning command, automatically configuring the data receiver. This eliminates the need for manual configuration of the backend data receiver, preventing data generated by new topics from being lost or delayed before the backend is ready. It reduces operational overhead, minimizes manual configuration errors, and ensures that new IoT device data is correctly captured and stored from the very first message. Furthermore, by using predefined templates to guide the pattern inference and configuration process, the MQTT broker maintains automation while possessing a high degree of customization capability.
[0056] Thirdly, embodiments of this application provide an electronic device, Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements an automated MQTT data integration method provided in the first aspect. Figure 3 The electronic device 60 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.
[0057] Electronic device 60 may be in the form of a general-purpose computing device, such as a server device. Components of electronic device 60 may include, but are not limited to: at least one processor 61, at least one memory 62, and a bus 63 connecting different system components (including memory 62 and processor 61).
[0058] Bus 63 includes a data bus, an address bus, and a control bus.
[0059] The memory 62 may include volatile memory, such as random access memory (RAM) 621 and / or cache memory 622, and may further include read-only memory (ROM) 623.
[0060] The memory 62 may also include a program / utility 625 having a set (at least one) of program modules 624, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.
[0061] The processor 61 executes various functional applications and data processing by running computer programs stored in the memory 62, such as the automated MQTT data integration method provided in the first aspect of this application.
[0062] Electronic device 60 can also communicate with one or more external devices 64 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 65. Furthermore, electronic device 60 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 66. Figure 3 As shown, network adapter 66 communicates with other modules of electronic device 60 via bus 63. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with electronic device 60, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.
[0063] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.
[0064] Fourthly, embodiments of this application provide a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements an automated MQTT data integration method provided in the first aspect.
[0065] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.
[0066] In a possible implementation, the invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform steps implementing an automated MQTT data integration method provided in the first aspect.
[0067] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.
[0068] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0069] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.
Claims
1. An automated MQTT data integration method, characterized in that, The method is applied to an MQTT broker, which works with a client and a data receiver. The method includes: Receive a message sent by the client and determine whether the target topic in the message is different from the topic in the proxy; If so, the message is parsed to obtain the topic structure and payload information, and the target data mode of the data receiving end is determined from the predefined structure patterns based on the topic structure and payload information. The corresponding target template is determined according to the pre-configured data receiver type. The data receiver is configured according to the target data mode and the target template, and the target message related to the target topic is sent to the data receiver.
2. The automated MQTT data integration method according to claim 1, characterized in that, The process of parsing the message to obtain the topic structure and payload information includes: The name of the target topic in the message is parsed to extract metadata; The message payload in the message is analyzed to identify field names and data types.
3. The automated MQTT data integration method according to claim 1, characterized in that, The step of determining the target data pattern of the data receiver from the predefined structural patterns based on the topic structure and payload information includes: Based on preset application rules, intermediate modes are obtained by filtering predefined structural patterns according to the topic structure and load information; The target data pattern is determined from the intermediate patterns using a machine learning classification algorithm based on the topic structure and payload information.
4. The automated MQTT data integration method according to claim 1, characterized in that, The target template includes preset commands and API call formats for interacting with the data receiving end. Configuring the data receiving end according to the target data pattern and target template includes: Determine the target supply instruction based on the target data pattern and target template; Connect to the data receiving end according to the API call format, and execute the target supply instruction to configure the data receiving end.
5. The automated MQTT data integration method according to claim 1, characterized in that, Sending the target message related to the target topic to the data receiving end includes: In response to the completion of the configuration of the receiving end, all target messages related to the target topic will be automatically forwarded to the corresponding configured data receiving end.
6. The automated MQTT data integration method according to claim 1, characterized in that, Before parsing the message to obtain the topic structure and payload information, the method further includes: Determine whether the target topic can match at least one of the predefined structural patterns; If so, the message is parsed to obtain the topic structure and payload information; If not, the message will be processed according to a preset standard topic.
7. An automated MQTT data integration system, characterized in that, The system is applied to an MQTT broker, which works in conjunction with a client and a data receiver. The system includes: Judgment module: Used to receive messages sent by the client and determine whether the target topic in the message is different from the topic in the proxy; Inference module: When the target topic in the message is different from the topic in the agent, it parses the message to obtain topic structure and payload information, and determines the target data pattern of the data receiving end from the predefined structure pattern based on the topic structure and payload information; Integration module: used to determine the corresponding target template according to the pre-configured data receiving end type, configure the data receiving end according to the target data mode and target template, and send the target message related to the target topic to the data receiving end.
8. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the computer program, implements an automated MQTT data integration method as described in any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements an automated MQTT data integration method as described in any one of claims 1 to 6.