Configurable intelligent household electrical appliance data consistency test method and system

Abstract

The invention provides a configurable intelligent household electrical appliance data consistency test method and system, and the method comprises the steps: configuring protocol information corresponding to a to-be-tested device, the protocol information comprising a field bit, an attribute name and an attribute description; the intelligent WiFi module and the upper computer software system are connected through a serial port; capturing a device printing log in the intelligent WiFi module according to the keyword and storing the device printing log to a log module; analyzing the device printing log according to the protocol information to obtain local analysis data and a unique identifier; requesting data from a data platform through the unique identifier to obtain data platform analysis data; comparing whether the local analysis data is consistent with the data platform analysis data; if the local analysis data is consistent with the data platform analysis data, judging that the test is passed; and if the local analysis data is inconsistent with the data platform analysis data, determining that the test is not passed, so as to solve the problems of insufficient efficiency, coverage and reliability of the data test.

Description

Technical Field

[0001] The present application relates to the technical field of smart home appliance data testing, and in particular to a configurable smart home appliance data consistency testing method and system. Background Art

[0002] In the field of smart home appliances, the deepening of the digitalization process has made it increasingly important to mine the value of data to drive intelligent product applications. Data quality has become a core factor in ensuring the reliability of these applications. Specifically, the electronic control panel of a smart home appliance reports the device status data in hexadecimal format to the smart module, which further forwards the data to the cloud platform based on the reporting rules. The cloud platform is responsible for parsing the hexadecimal data into JSON format and transmitting the data to the data platform through push rules. It is finally stored in the data warehouse to support subsequent data mining and analysis. This data flow process involves multi-level format conversion and processing. Data consistency testing is particularly critical because only by ensuring the correctness and validity of the data can the efficient operation of data-driven applications be supported.

[0003] To meet the needs of data consistency testing, related methods have evolved from early manual testing to tool-based testing. These methods rely on the development of specialized testing tools to verify data consistency at different flow nodes through automated means. For example, tool testing systems parse and compare data using preset rules to improve test efficiency and coverage.

[0004] However, this type of testing approach has significant shortcomings: when smart home appliance features are rapidly updated or communication protocols are iterated, the test system must be upgraded simultaneously to adapt. For example, after fine-tuning the protocol, the test system must be redeveloped and redeployed. This leads to high barriers to entry and long iteration cycles, seriously hindering product delivery progress. Therefore, a configurable test solution that can adapt to various product types and improve data testing efficiency, coverage, and reliability is urgently needed. Summary of the Invention

[0005] The present application provides a configurable smart home appliance data consistency testing method and system to solve the problems of insufficient efficiency, coverage and reliability of data testing.

[0006] A first aspect of the present application provides a configurable smart appliance data consistency test method, the method comprising:

[0007] Configure the protocol information corresponding to the device to be tested, the protocol information including field bits, attribute names and attribute descriptions;

[0008] Connect the smart WiFi module and the host computer software system through the serial port;

[0009] Capture the device printing log in the smart WiFi module according to the keyword and store it in the log module;

[0010] parsing the device print log according to the protocol information to obtain local parsing data and a unique identifier;

[0011] Request data from the data platform through the unique identifier to obtain data parsed by the data platform;

[0012] Compare the local parsed data and the data platform parsed data to see if they are consistent:

[0013] If the local parsed data is consistent with the data platform parsed data, the test is determined to be passed;

[0014] If the local parsed data is inconsistent with the data platform parsed data, the test is determined to have failed.

[0015] The above method configures protocol information and uses the serial port to connect the smart WiFi module to the host computer system. It captures and stores device print logs according to keywords, then parses the logs to obtain local parsed data and unique identifiers, and then requests corresponding data from the data platform for consistency comparison. This method can improve the efficiency, coverage, and reliability of data testing. At the same time, it reduces manual intervention through automated log capture and data comparison, lowers the probability of errors during the test process, and improves the accuracy of test results.

[0016] Optionally, comparing whether the local parsed data and the data platform parsed data are consistent includes:

[0017] Comparing the local parsed data with the data platform parsed data field by field;

[0018] If all fields are consistent, the test is considered passed;

[0019] If there is at least one inconsistent field, the test is judged to have failed, and the inconsistent fields are marked with colors in the upper computer interface.

[0020] By comparing local parsed data with data platform parsed data field by field and marking the different fields with colors when there are inconsistencies, the intuitiveness and readability of test results can be improved, helping testers quickly locate the specific location of data inconsistencies, thereby improving test efficiency, reducing the workload of manual verification, and improving the accuracy of error detection.

[0021] Optionally, after the determination test fails, the method further includes:

[0022] Request data from the cloud platform through the unique identifier to obtain the cloud platform parsed data;

[0023] Compare the local parsed data and the cloud platform parsed data to see if they are consistent:

[0024] If the local parsed data is consistent with the cloud platform parsed data, it is determined that the error occurred in the data platform;

[0025] If the local parsed data is inconsistent with the cloud platform parsed data, it is determined that the error occurs on the cloud platform.

[0026] When the test fails, the above method further requests data from the cloud platform and performs consistency comparison, which can help distinguish whether the source of the error is the data platform or the cloud platform, thereby narrowing the scope of investigation, improving the efficiency of problem location, reducing debugging time, and improving the accuracy of error diagnosis.

[0027] Optionally, requesting data from a data platform or a cloud platform using the unique identifier includes:

[0028] A data request is sent to the data platform or cloud platform via the HTTP protocol, and the obtained data platform parsed data or cloud platform parsed data is visualized in the host computer interface.

[0029] Sending data requests to the data platform or cloud platform via the HTTP protocol and visually displaying the returned parsed data on the host computer interface can improve the standardization of data transmission, enhance the readability of test data, and facilitate intuitive comparison and analysis by testers, thereby reducing the difficulty of data understanding and improving the efficiency and accuracy of the testing process.

[0030] Optionally, the device print log includes: log time, device serial number, hexadecimal device status data and a unique identifier.

[0031] By collecting device printed logs containing log time, device serial number, hexadecimal device status data and unique identifiers, a more comprehensive source of test data can be provided, ensuring the integrity and traceability of log information, thereby improving the basic reliability of data comparison, and providing more sufficient data support for subsequent fault analysis, improving the accuracy of problem diagnosis.

[0032] Optionally, before capturing the device print log in the smart WiFi module according to the keyword and storing it in the log module, the method further includes:

[0033] When connected to the Internet, the smart WiFi module receives the hexadecimal device status data reported by the electronic control module of the device under test;

[0034] Pack the hexadecimal device status data according to preset rules and send it to the cloud platform;

[0035] During the packaging process, log information containing keywords is printed and a unique identifier is appended to each device status data;

[0036] The cloud platform parses the received packaged hexadecimal device status data into JSON format and pushes it to the data platform for storage according to preset push rules.

[0037] By receiving the hexadecimal status data of the device to be tested when the smart WiFi module is connected to the Internet, packaging it according to preset rules, attaching a unique identifier, and uploading it to the cloud, while printing log information containing keywords, and then having the cloud platform convert the data into JSON format and push it to the data platform, it is possible to achieve standardized collection and structured processing of device status data, improve the standardization of data transmission, enhance data compatibility between different platforms, thereby optimizing the data processing process, reducing the risk of data conversion errors, and providing a more reliable data foundation for subsequent consistency testing.

[0038] Optionally, the field bits of the protocol information are accurate to the bit.

[0039] By defining the field bits of protocol information precisely down to the bit position, the precision of data analysis can be improved, ensuring accurate matching of protocol fields, thereby reducing the risk of data misjudgment due to unclear data bit width, improving the reliability of test results, and providing a more rigorous technical basis for the accurate analysis of device communication data.

[0040] A second aspect of the present application provides a configurable smart home appliance data consistency test system, which is applied to the configurable smart home appliance data consistency test method described in the first aspect. The test system includes: a smart WiFi module and a host computer software system, wherein the smart WiFi module and the host computer software system are connected via a serial port;

[0041] The host computer software system includes: a protocol configuration module, an electronic control data capture module, a local analysis module, a data platform acquisition module, a comparison module and a log module;

[0042] The protocol configuration module is used to configure the protocol information corresponding to the device to be tested, and the protocol information includes field bits, attribute names and attribute descriptions;

[0043] The electronic control data capture module is used to capture the device printing log in the smart WiFi module according to the keyword and store it in the log module;

[0044] The local parsing module is used to parse the device print log according to the protocol information to obtain local parsing data and a unique identifier;

[0045] The data platform acquisition module requests data from the data platform through the unique identifier to obtain data parsed by the data platform;

[0046] The comparison module is used to compare whether the local parsed data and the data platform parsed data are consistent;

[0047] The log module stores device print logs.

[0048] The test system is connected to the serial port of the host computer software system through an intelligent WiFi module, and is equipped with a protocol configuration module, an electronic control data capture module, a local analysis module, a data platform acquisition module, a comparison module and a log module. It can realize flexible configuration of protocol information, automatic capture and storage of device logs, and local and platform analysis and comparison of data, thereby improving the degree of automation of the test process, reducing manual operation links, and lowering the probability of test errors. At the same time, the modular design improves the maintainability and scalability of the system, improves the overall efficiency of smart home appliance data consistency testing, and solves the problems of insufficient efficiency, coverage and reliability of data testing.

[0049] Optionally, the host computer software system further includes a cloud platform acquisition module;

[0050] The cloud platform acquisition module is used to request data from the cloud platform through the unique identifier to obtain cloud platform parsed data.

[0051] By adding a cloud platform acquisition module to the original host computer software system, automatic request and acquisition of cloud platform data can be realized, which expands the source range of data comparison and helps to more comprehensively verify data consistency, thereby improving test coverage and result credibility. At the same time, it provides a more dimensional reference basis for fault location and optimizes the comprehensive detection capabilities of the test system.

[0052] Optionally, the host computer software system further includes a host computer interface;

[0053] The host computer interface is used to display local analysis data, cloud platform analysis data and data platform analysis data.

[0054] By setting up the host computer interface to display local analysis data, cloud platform analysis data, and data platform analysis data, the test data can be visualized, making it easier for testers to intuitively view the comparison results, thereby improving data analysis efficiency, reducing manual verification time, and improving the transparency and operability of the testing process.

[0055] It can be seen from the above technical solution that the present application provides a configurable smart home appliance data consistency testing method and system, the method comprising: configuring protocol information corresponding to the device to be tested, the protocol information including field bits, attribute names and attribute descriptions; connecting the smart WiFi module and the host computer software system through a serial port; capturing the device print log in the smart WiFi module according to keywords and storing it in a log module; parsing the device print log according to the protocol information to obtain local parsed data and a unique identifier; requesting data from the data platform through the unique identifier to obtain data platform parsed data; comparing the local parsed data and the data platform parsed data for consistency: if the local parsed data and the data platform parsed data are consistent, the test is determined to have passed; if the local parsed data and the data platform parsed data are inconsistent, the test is determined to have failed, so as to solve the problems of insufficient efficiency, coverage and reliability of data testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0057] Figure 1 A flowchart of a configurable smart home appliance data consistency testing method provided in an embodiment of the present application;

[0058] Figure 2 A schematic diagram of the data flow link of the configurable smart home appliance data consistency test method provided in an embodiment of the present application;

[0059] Figure 3 A schematic diagram illustrating the principles of a configurable smart home appliance data consistency testing method provided in an embodiment of the present application;

[0060] Figure 4 This is a schematic diagram of the internal structure of the host computer software system in the configurable smart home appliance data consistency test system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following embodiments are described in detail, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following embodiments are not intended to represent all possible implementations consistent with the present application. They are merely examples of systems and methods consistent with certain aspects of the present application.

[0062] As home appliances become increasingly digital, mining data to drive increasingly diverse intelligent product applications becomes increasingly crucial, making data quality crucial. The electrical control panel of a smart appliance reports device status data in hexadecimal format to the intelligent module, which then forwards the data to the cloud platform based on reporting rules. The cloud platform parses the hexadecimal data into JSON format and transmits it to the data platform using push rules. Ultimately, the data is stored in a data warehouse to support subsequent data mining and analysis. This data flow involves multiple levels of format conversion and processing, making data consistency testing crucial. Only by ensuring the correctness and validity of the data can the efficient operation of data-driven applications be supported.

[0063] To meet the needs of data consistency testing, methods have evolved from early manual testing to tool-based testing. These methods rely on the development of specialized testing tools to automatically verify data consistency at different flow nodes. However, when smart home appliance features are rapidly updated or communication protocols are iterated, the test system must be upgraded simultaneously to adapt to the changes. This leads to high barriers to entry and long iteration cycles, seriously hindering product delivery and affecting the efficiency, coverage, and reliability of data testing.

[0064] To address the issues of insufficient efficiency, coverage, and reliability of data testing, see Figures 1-4 Some embodiments of the present application provide a configurable smart appliance data consistency testing method, the method comprising:

[0065] S100: Configure protocol information corresponding to the device to be tested.

[0066] It should be understood that the protocol information includes field bits, attribute names, and attribute descriptions. By configuring unique protocol information for different types and models of devices under test, a customized "one device, one configuration" test mode can be implemented. By reading this protocol configuration information, the host computer test software can automatically identify and display the corresponding attribute names. The attribute description refers to the specific parsing rules. By configuring the protocol, the standardization of the test process is maintained while providing flexibility to adapt to different devices, ensuring test accuracy while increasing the applicability of the test system.

[0067] In some embodiments, the fields of the protocol information are bit-accurate.

[0068] By defining the field bits of protocol information precisely down to the bit position, the precision of data analysis can be improved, ensuring accurate matching of protocol fields, thereby reducing the risk of data misjudgment due to unclear data bit width, improving the reliability of test results, and providing a more rigorous technical basis for the accurate analysis of device communication data.

[0069] S200: Connect the smart WiFi module and the host computer software system through the serial port.

[0070] It should be understood that the electronic control module of the device to be tested is connected to the smart WiFi module. After the device to be tested is powered on, data transmission between the electronic control module and the smart WiFi module can be realized. After the smart WiFi module is online, data transmission between the smart WiFi module and the cloud platform can be realized.

[0071] S300: Capture the device printing log in the smart WiFi module according to the keyword and store it in the log module.

[0072] It should be understood that when the smart WiFi module is packaged, it automatically prints specific keywords (such as "big") for the host computer software system to quickly identify and capture the device print log.

[0073] In some embodiments, before capturing the device print log in the smart WiFi module based on the keyword and storing it in the log module, the method further includes:

[0074] When connected to the Internet, the smart WiFi module receives the hexadecimal device status data reported by the electronic control module of the device under test;

[0075] Pack the hexadecimal device status data according to preset rules and send it to the cloud platform;

[0076] During the packaging process, log information containing keywords is printed and a unique identifier is appended to each device status data;

[0077] The cloud platform parses the received packaged hexadecimal device status data into JSON format and pushes it to the data platform for storage according to preset push rules for subsequent data application.

[0078] It should be understood that the cloud platform parses the received packaged hexadecimal device status data into JSON format in the following specific process: first, the packaged hexadecimal device status data is split into hexadecimal data segments according to preset rules, and then each field is converted into a corresponding JSON key-value pair, and metadata such as device ID and timestamp are added to output structured JSON format data.

[0079] By receiving the hexadecimal status data of the device to be tested when the smart WiFi module is connected to the Internet, packaging it according to preset rules, attaching a unique identifier, and uploading it to the cloud, while printing log information containing keywords, and then having the cloud platform convert the data into JSON format and push it to the data platform, it is possible to achieve standardized collection and structured processing of device status data, improve the standardization of data transmission, enhance data compatibility between different platforms, thereby optimizing the data processing process, reducing the risk of data conversion errors, and providing a more reliable data foundation for subsequent consistency testing.

[0080] In some embodiments, the device print log includes: log time, device serial number, hexadecimal device status data, and a unique identifier.

[0081] By collecting device printed logs containing log time, device serial number, hexadecimal device status data and unique identifiers, a more comprehensive source of test data can be provided, ensuring the integrity and traceability of log information, thereby improving the basic reliability of data comparison, and providing more sufficient data support for subsequent fault analysis, improving the accuracy of problem diagnosis.

[0082] S400: Parse the device printing log according to the protocol information to obtain local parsing data and a unique identifier.

[0083] It should be understood that when the smart WiFi module reports to the cloud platform, each piece of data needs to include a unique identifier, such as a millisecond timestamp.

[0084] S500: Requesting data from the data platform through the unique identifier to obtain data parsed by the data platform.

[0085] S600: Compare the local parsed data and the data platform parsed data to see if they are consistent:

[0086] S610: If the local parsed data is consistent with the data platform parsed data, the test is determined to be passed;

[0087] S620: If the local parsed data is inconsistent with the data platform parsed data, the test is determined to have failed.

[0088] In some embodiments, comparing the local parsed data and the data platform parsed data to see whether they are consistent includes:

[0089] Comparing the local parsed data with the data platform parsed data field by field;

[0090] If all fields are consistent, the test is considered passed;

[0091] If there is at least one inconsistent field, the test is judged to have failed, and the inconsistent fields are marked with colors in the upper computer interface.

[0092] By comparing local parsed data with data platform parsed data field by field and marking the different fields with colors when there are inconsistencies, the intuitiveness and readability of test results can be improved, helping testers quickly locate the specific location of data inconsistencies, thereby improving test efficiency, reducing the workload of manual verification, and improving the accuracy of error detection.

[0093] The above method configures protocol information and uses the serial port to connect the smart WiFi module to the host computer system. It captures and stores device print logs according to keywords, then parses the logs to obtain local parsed data and unique identifiers, and then requests corresponding data from the data platform for consistency comparison. This method can improve the efficiency, coverage, and reliability of data testing. At the same time, it reduces manual intervention through automated log capture and data comparison, lowers the probability of errors during the test process, and improves the accuracy of test results.

[0094] In some embodiments, after the determination test fails, the method further comprises:

[0095] Request data from the cloud platform through the unique identifier to obtain the cloud platform parsed data;

[0096] Compare the local parsed data and the cloud platform parsed data to see if they are consistent:

[0097] If the local parsed data is consistent with the cloud platform parsed data, it is determined that the error occurred in the data platform;

[0098] If the local parsed data is inconsistent with the cloud platform parsed data, it is determined that the error occurs on the cloud platform.

[0099] When the test fails, the above method further requests data from the cloud platform and performs consistency comparison, which can help distinguish whether the source of the error is the data platform or the cloud platform, thereby narrowing the scope of investigation, improving the efficiency of problem location, reducing debugging time, and improving the accuracy of error diagnosis.

[0100] In some embodiments, requesting data from a data platform or a cloud platform using the unique identifier includes:

[0101] A data request is sent to the data platform or cloud platform via the HTTP protocol, and the obtained data platform parsed data or cloud platform parsed data is visualized in the host computer interface.

[0102] It should be understood that the specific process of requesting data through the HTTP protocol is as follows: first embed the unique identifier into the HTTP request (such as GET / POST) and set the standard request header (such as Content-Type: application / json); then encrypt the transmission through HTTPS to ensure security. After the data platform or cloud platform receives the request, it returns the data parsed by the data platform or the cloud platform parsed data, and finally checks the HTTP status code (such as 200 success, 404 not found) to extract the data parsed by the data platform or the cloud platform parsed data.

[0103] Sending data requests to the data platform or cloud platform via the HTTP protocol and visually displaying the returned parsed data on the host computer interface can improve the standardization of data transmission, enhance the readability of test data, and facilitate intuitive comparison and analysis by testers, thereby reducing the difficulty of data understanding and improving the efficiency and accuracy of the testing process.

[0104] Some embodiments of the present application also provide a configurable smart home appliance data consistency test system, which is applied to the configurable smart home appliance data consistency test method described in the above embodiments. The test system includes: a smart WiFi module and a host computer software system, wherein the smart WiFi module and the host computer software system are connected via a serial port;

[0105] The host computer software system includes: a protocol configuration module, an electronic control data capture module, a local analysis module, a data platform acquisition module, a comparison module and a log module;

[0106] The protocol configuration module is used to configure the protocol information corresponding to the device to be tested, and the protocol information includes field bits, attribute names and attribute descriptions;

[0107] The electronic control data capture module is used to capture the device printing log in the smart WiFi module according to the keyword and store it in the log module;

[0108] The local parsing module is used to parse the device print log according to the protocol information to obtain local parsing data and a unique identifier;

[0109] The data platform acquisition module requests data from the data platform through the unique identifier to obtain data parsed by the data platform;

[0110] The comparison module is used to compare whether the local parsed data and the data platform parsed data are consistent;

[0111] The log module stores device print logs.

[0112] The test system is connected to the serial port of the host computer software system through an intelligent WiFi module, and is equipped with a protocol configuration module, an electronic control data capture module, a local analysis module, a data platform acquisition module, a comparison module and a log module. It can realize flexible configuration of protocol information, automatic capture and storage of device logs, and local and platform analysis and comparison of data, thereby improving the degree of automation of the test process, reducing manual operation links, and lowering the probability of test errors. At the same time, the modular design improves the maintainability and scalability of the system, improves the overall efficiency of smart home appliance data consistency testing, and solves the problems of insufficient efficiency, coverage and reliability of data testing.

[0113] In some embodiments, the host computer software system further includes a cloud platform acquisition module;

[0114] The cloud platform acquisition module is used to request data from the cloud platform through the unique identifier to obtain cloud platform parsed data.

[0115] By adding a cloud platform acquisition module to the original host computer software system, automatic request and acquisition of cloud platform data can be realized, which expands the source range of data comparison and helps to more comprehensively verify data consistency, thereby improving test coverage and result credibility. At the same time, it provides a more dimensional reference basis for fault location and optimizes the comprehensive detection capabilities of the test system.

[0116] In some embodiments, the host computer software system further includes a host computer interface;

[0117] The host computer interface is used to display local analysis data, cloud platform analysis data and data platform analysis data.

[0118] By setting up the host computer interface to display local analysis data, cloud platform analysis data, and data platform analysis data, the test data can be visualized, making it easier for testers to intuitively view the comparison results, thereby improving data analysis efficiency, reducing manual verification time, and improving the transparency and operability of the testing process.

[0119] It can be seen from the above technical solution that the embodiment of the present application provides a configurable smart home appliance data consistency testing method and system, the method including: configuring protocol information corresponding to the device to be tested, the protocol information including field bits, attribute names and attribute descriptions; connecting the smart WiFi module and the host computer software system through the serial port; capturing the device print log in the smart WiFi module according to keywords and storing it in the log module; parsing the device print log according to the protocol information to obtain local parsed data and a unique identifier; requesting data from the data platform through the unique identifier to obtain data platform parsed data; comparing the local parsed data and the data platform parsed data for consistency: if the local parsed data and the data platform parsed data are consistent, the test is determined to have passed; if the local parsed data and the data platform parsed data are inconsistent, the test is determined to have failed, so as to solve the problems of insufficient efficiency, coverage and reliability of data testing.

[0120] Similar parts between the embodiments provided in this application can be referenced to each other. The specific implementation methods provided above are only a few examples under the overall concept of this application and do not constitute a limitation on the scope of protection of this application. For those skilled in the art, any other implementation methods expanded based on the scheme of this application without expending creative work shall fall within the scope of protection of this application.

Claims

1. A configurable smart home appliance data consistency test method, characterized in that: The method comprises: Configure the protocol information corresponding to the device to be tested, the protocol information including field bits, attribute names and attribute descriptions; Connect the smart WiFi module and the host computer software system through the serial port; Capture the device printing log in the smart WiFi module according to the keyword and store it in the log module; parsing the device print log according to the protocol information to obtain local parsing data and a unique identifier; Request data from the data platform through the unique identifier to obtain data parsed by the data platform; Compare the local parsed data and the data platform parsed data to see if they are consistent: If the local parsed data is consistent with the data platform parsed data, the test is determined to be passed; If the local parsed data is inconsistent with the data platform parsed data, the test is determined to have failed.

2. The configurable smart home appliance data consistency test method according to claim 1, characterized in that: Comparing the local parsed data and the data platform parsed data to see whether they are consistent includes: Comparing the local parsed data with the data platform parsed data field by field; If all fields are consistent, the test is considered passed; If there is at least one inconsistent field, the test is judged to have failed, and the inconsistent fields are marked with colors in the upper computer interface.

3. The configurable smart home appliance data consistency test method according to claim 1, characterized in that: After the determination test fails, the method further includes: Request data from the cloud platform through the unique identifier to obtain the cloud platform parsed data; Compare the local parsed data and the cloud platform parsed data to see if they are consistent: If the local parsed data is consistent with the cloud platform parsed data, it is determined that the error occurred in the data platform; If the local parsed data is inconsistent with the cloud platform parsed data, it is determined that the error occurs on the cloud platform.

4. The configurable smart home appliance data consistency test method according to claim 3, characterized in that: Requesting data from the data platform or cloud platform using the unique identifier includes: A data request is sent to the data platform or cloud platform via the HTTP protocol, and the obtained data platform parsed data or cloud platform parsed data is visualized in the host computer interface.

5. The configurable smart home appliance data consistency test method according to claim 1, characterized in that: The device print log includes: log time, device serial number, hexadecimal device status data and a unique identifier.

6. The configurable smart home appliance data consistency test method according to claim 5, characterized in that: Before capturing the device print log in the smart WiFi module according to the keyword and storing it in the log module, the method further includes: When connected to the Internet, the smart WiFi module receives the hexadecimal device status data reported by the electronic control module of the device under test; Pack the hexadecimal device status data according to preset rules and send it to the cloud platform; During the packaging process, log information containing keywords is printed and a unique identifier is appended to each device status data; The cloud platform parses the received packaged hexadecimal device status data into JSON format and pushes it to the data platform for storage according to preset push rules.

7. The configurable smart home appliance data consistency test method according to claim 1, characterized in that: The fields of the protocol information are accurate to the bit.

8. A configurable smart home appliance data consistency test system, characterized in that: The configurable smart home appliance data consistency test method according to any one of claims 1 to 7, wherein the test system comprises: a smart WiFi module and a host computer software system, wherein the smart WiFi module and the host computer software system are connected via a serial port; The host computer software system includes: a protocol configuration module, an electronic control data capture module, a local analysis module, a data platform acquisition module, a comparison module and a log module; The protocol configuration module is used to configure the protocol information corresponding to the device to be tested, and the protocol information includes field bits, attribute names and attribute descriptions; The electronic control data capture module is used to capture the device printing log in the smart WiFi module according to the keyword and store it in the log module; The local parsing module is used to parse the device print log according to the protocol information to obtain local parsing data and a unique identifier; The data platform acquisition module requests data from the data platform through the unique identifier to obtain data parsed by the data platform; The comparison module is used to compare whether the local parsed data and the data platform parsed data are consistent; The log module stores device print logs.

9. The configurable smart home appliance data consistency test system according to claim 8, characterized in that: The host computer software system also includes a cloud platform acquisition module; The cloud platform acquisition module is used to request data from the cloud platform through the unique identifier to obtain cloud platform parsed data.

10. The configurable smart home appliance data consistency test system according to claim 8, characterized in that: The host computer software system also includes a host computer interface; The host computer interface is used to display local analysis data, cloud platform analysis data and data platform analysis data.

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