Household equipment operation monitoring method and device and household equipment operation monitoring platform

Abstract

The invention relates to the field of smart home, and provides a home equipment operation monitoring method and device and a home equipment operation monitoring platform, and the method comprises the steps: constructing a business burying point strategy matched with an operation parameter carried by a monitoring content demand instruction based on the monitoring content demand instruction; wherein the monitoring content demand instruction is used for representing an instruction for monitoring operation parameters of the to-be-monitored home equipment under the operation parameter type; under the condition that the to-be-monitored household equipment operates, generating a buried point file of the to-be-monitored household equipment under the operation parameter type carried by the monitoring content demand instruction based on a service buried point strategy; sampling the buried point file to obtain a sampled buried point file; and on the basis of the sampled buried point file, generating monitoring data of the to-be-monitored household equipment under the operation parameter type, thereby realizing high-efficiency and low-cost supervision of the operation condition of the household equipment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home, and particularly relates to a smart home device operation monitoring method and device and a smart home device operation monitoring platform. BACKGROUND

[0002] With the rapid development of the Internet of Things technology, network home appliance devices realize remote state monitoring, fault early warning and energy efficiency management through a monitoring access platform, which has become a core trend in the field of smart home.

[0003] However, the existing monitoring access platform generally has a technical bottleneck of low efficiency in processing massive buried point log data generated in the running process of network home appliance devices. Specifically, the traditional monitoring system usually adopts a full log collection and centralized processing architecture, and needs to perform real-time or quasi-real-time full analysis, storage and analysis on the original buried point data of all access devices. This leads to an increase in computing cost.

[0004] Therefore, finding a low-cost method for supervising the running state of smart home devices has become a current research hotspot. SUMMARY

[0005] The present application provides a smart home device operation monitoring method, device and platform, which realizes efficient and low-cost supervision of the running state of smart home devices.

[0006] The present application provides a smart home device operation monitoring method, which comprises the following steps: based on a monitoring content requirement instruction, a business buried point strategy matching the running parameter carried by the monitoring content requirement instruction is constructed; wherein the monitoring content requirement instruction is used to represent an instruction for monitoring the running parameter of a to-be-monitored smart home device under a running parameter type; under the running state of the to-be-monitored smart home device, based on the business buried point strategy, a buried point file of the to-be-monitored smart home device under the running parameter type carried by the monitoring content requirement instruction is generated; the buried point file is subjected to sampling sampling processing to obtain a sampled buried point file; and based on the sampled buried point file, monitoring data of the to-be-monitored smart home device under the running parameter type is generated.

[0007] According to a home appliance operation monitoring method provided by the present invention, before performing sampling processing on the embedded point file to obtain a sampled embedded point file, the method further includes: extracting features from the operation parameter types carried by the monitoring content requirement instruction to obtain parameter features corresponding to the operation parameter types; determining a sampling time interval matching the parameter features based on the parameter features; the sampling processing on the embedded point file to obtain a sampled embedded point file includes: performing sampling processing on the embedded point file according to the sampling time interval to obtain a sampled embedded point file.

[0008] According to a home appliance operation monitoring method provided by the present invention, the parameter features include data update frequency and / or data importance level; the step of determining a sampling time interval matching the parameter features includes: determining a sampling time interval matching the data update frequency based on the data update frequency, wherein the sampling time interval and the data update frequency are negatively correlated; or determining a sampling time interval matching the data importance level based on the data importance level, wherein the sampling time interval and the data importance level are negatively correlated.

[0009] According to a home appliance operation monitoring method provided by the present invention, the monitoring data includes detailed operation monitoring data and summary result monitoring data; the step of generating monitoring data of the home appliance to be monitored under the operation parameter type based on the sampling and embedding file includes: generating detailed operation monitoring data of the home appliance to be monitored under the operation parameter type based on the sampling and embedding file; and summarizing the detailed operation monitoring data to obtain summary result monitoring data.

[0010] According to a home appliance operation monitoring method provided by the present invention, after generating monitoring data of the home appliance to be monitored under the specified operation parameter type, the method further includes: storing the monitoring data in a database; and upon receiving a display instruction, retrieving the monitoring data from the database and visually displaying the monitoring data.

[0011] According to a home appliance operation monitoring method provided by the present invention, the database includes a first database and a second database, wherein the first database is a relational database and the second database is a time-series database; the monitoring data includes detailed operation monitoring data and summary result monitoring data; storing the monitoring data in the database includes storing the detailed operation monitoring data in the first database and storing the summary result monitoring data in the second database; and retrieving the monitoring data from the database and visualizing the monitoring data upon receiving a display instruction includes retrieving the detailed operation monitoring data from the first database and visualizing the detailed operation monitoring data upon receiving a first display instruction, or retrieving the summary result monitoring data from the second database and visualizing the summary result monitoring data upon receiving a second display instruction, wherein the first display instruction is used to represent an instruction to display the detailed operation monitoring data; and the second display instruction is used to represent an instruction to display the summary result monitoring data.

[0012] According to a home appliance operation monitoring method provided by the present invention, before summarizing the detailed operation monitoring data to obtain summarized monitoring data, the method further includes: deduplicating the detailed operation monitoring data to obtain deduplicated detailed operation monitoring data; formatting the deduplicated detailed operation monitoring data to obtain formatted detailed operation monitoring data; the summarizing the detailed operation monitoring data to obtain summarized monitoring data includes: summarizing the formatted detailed operation monitoring data to obtain summarized monitoring data.

[0013] According to a home appliance operation monitoring method provided by the present invention, after obtaining the summarized monitoring data, the method further includes: when it is detected that the summarized monitoring data does not meet preset requirements, issuing an alarm reminder to the user, wherein the alarm reminder is used to indicate to the user that the home appliance to be monitored has a malfunction in operation under preset operating parameter types.

[0014] This invention also provides a home appliance operation monitoring device, comprising: a construction module, configured to construct a business tracking strategy matching the operation parameters carried by the monitoring content requirement instruction based on the monitoring content requirement instruction; wherein the monitoring content requirement instruction is used to characterize the instruction for monitoring the operation parameters of the home appliance to be monitored under the operation parameter type; a generation module, configured to generate a tracking file of the home appliance to be monitored under the operation parameter type carried by the monitoring content requirement instruction based on the business tracking strategy when the home appliance to be monitored is in operation; a sampling module, configured to perform sampling processing on the tracking file to obtain a sampled tracking file; and a monitoring module, configured to generate monitoring data of the home appliance to be monitored under the operation parameter type based on the sampled tracking file.

[0015] The present invention also provides a home appliance operation monitoring platform, the home appliance operation monitoring platform comprising: a platform interface for connecting the home appliance to be monitored to the home appliance operation monitoring platform, and a processor, wherein the processor is used to execute any of the home appliance operation monitoring methods described herein.

[0016] The present invention also provides an electronic 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 the home appliance operation monitoring method described above.

[0017] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the home appliance operation monitoring method as described above.

[0018] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the home appliance operation monitoring method described above.

[0019] This invention provides a method, device, and platform for monitoring the operation of home appliances. The method includes: constructing a business-based data entry strategy that matches the operating parameters carried by the monitoring content requirement instruction based on the monitoring content requirement instruction; wherein, the monitoring content requirement instruction is used to characterize the operating parameters of the home appliance to be monitored under the operating parameter type; when the home appliance to be monitored is in operation, generating a data entry file for the home appliance to be monitored under the operating parameter type carried by the monitoring content requirement instruction based on the business-based data entry strategy; performing sampling processing on the data entry file to obtain a sampled data entry file; and generating monitoring data for the home appliance to be monitored under the operating parameter type based on the sampled data entry file, thereby achieving efficient and low-cost supervision of the operation of home appliances. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the hardware environment for a home appliance operation monitoring method according to an embodiment of this application; Figure 2 This is a flowchart illustrating the home appliance operation monitoring method provided by the present invention.

[0022] Figure 3 This is a schematic diagram of the process of sampling the embedded point file to obtain the sampled embedded point file provided by the present invention.

[0023] Figure 4 This is a schematic diagram of the home appliance operation monitoring device provided by the present invention.

[0024] Figure 5 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] According to one aspect of the embodiments of this application, a method for monitoring the operation of home appliances is provided. This method is widely applicable to whole-house intelligent digital control application scenarios such as smart homes, smart home ecosystems, and intelligence house ecosystems. Optionally, in this embodiment, the above-mentioned method for monitoring the operation of home appliances can be applied to, for example... Figure 1 The hardware environment shown consists of terminal device 102 and server 104. For example... Figure 1 As shown, server 104 is connected to terminal device 102 via a network and can be used to provide services (such as application services) to the terminal or clients installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data processing services for server 104.

[0028] The aforementioned network may include, but is not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network, metropolitan area network, local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth. The terminal device 102 may not be limited to PC, mobile phone, tablet computer, smart air conditioner, smart range hood, smart refrigerator, smart oven, smart stove, smart washing machine, smart water heater, smart washing equipment, smart dishwasher, smart projector, smart TV, smart clothes rack, smart curtains, smart audio-visual equipment, smart socket, smart speaker, smart speaker box, smart fresh air equipment, smart kitchen and bathroom equipment, smart bathroom equipment, smart robot vacuum cleaner, smart window cleaning robot, smart mopping robot, smart air purifier, smart steam oven, smart microwave oven, smart water heater, smart air purifier, smart water dispenser, smart door lock, etc.

[0029] In another embodiment, the home appliance operation monitoring method provided in this application can be applied to smart home appliances. Smart home appliances refer to home appliance products formed by incorporating microprocessors, sensor technology, and network communication technology. They are capable of automatically sensing the status of the residential space, the status of the appliances themselves, and the service status of the appliances, and can automatically control and receive control commands from the home user inside or remotely. It is understood that smart home appliances are a component of smart homes.

[0030] Figure 2 This is a flowchart illustrating the home appliance operation monitoring method provided by the present invention.

[0031] The following will combine Figure 2 The process of the home appliance operation monitoring method provided by the present invention will be described.

[0032] In an exemplary embodiment of the present invention, combined with Figure 2 As can be seen, the home appliance operation monitoring method may include steps 210 to 240, and each step will be described below.

[0033] In step 210, based on the monitoring content requirement instruction, a business tracking strategy matching the operating parameters carried by the monitoring content requirement instruction is constructed; wherein, the monitoring content requirement instruction is used to characterize the instructions for monitoring the operating parameters of the home device to be monitored under the operating parameter type.

[0034] In one embodiment, a monitoring content request instruction initiated by a user can be received. This instruction can indicate that the user wants to monitor a specific home appliance, such as a smart air conditioner, under preset operating parameter types, such as energy consumption parameter types. The monitoring content request instruction can be used to specify the operating parameters of the home appliance under the desired operating parameter type.

[0035] Furthermore, based on the monitoring content requirement instructions, the type of device to be monitored, parameter type, and specific parameters can be parsed. Then, a data acquisition template related to the type of device to be monitored, parameter type, and specific parameters can be retrieved from the specification library. Based on this template and specific preset operating parameters, such as average hourly power consumption and cumulative electricity consumption for the month, a business data tracking strategy can be constructed.

[0036] In step 220, when the home appliance to be monitored is running, a data entry file is generated based on the business data entry strategy, under the type of running parameters carried by the monitoring content requirement instruction for the home appliance to be monitored.

[0037] In step 230, the embedded point file is sampled to obtain the sampled embedded point file.

[0038] In step 240, based on the sampled data file, monitoring data of the home appliances to be monitored under the operating parameter type is generated.

[0039] In another embodiment, when the home appliance to be monitored is in operation, a data entry file can be generated based on a business-specific data entry strategy, specifying the type of operating parameters carried in the monitoring content requirement instruction. During application, not every generated data entry file is monitored; instead, it is cached and sampled locally to obtain a sampled data entry file. Furthermore, monitoring data for the home appliance under the specified operating parameter type can be generated based on the sampled data entry file. In this embodiment, by acquiring user-defined monitoring content requirement instructions, it can flexibly respond to users' personalized monitoring needs for different devices and different operating parameters, achieving a shift from generalized data collection to precise target monitoring, avoiding the blindness and redundancy of data collection.

[0040] This invention provides a method, device, and platform for monitoring the operation of home appliances. The method includes: constructing a business-based data collection strategy that matches the operating parameters carried by the monitoring content requirement instruction based on the monitoring content requirement instruction; wherein, the monitoring content requirement instruction is used to characterize the operating parameters of the home appliance to be monitored under the operating parameter type; when the home appliance to be monitored is in operation, generating a data collection file for the home appliance to be monitored under the operating parameter type carried by the monitoring content requirement instruction based on the business-based data collection strategy; performing sampling processing on the data collection file to obtain a sampled data collection file; and generating monitoring data for the home appliance to be monitored under the operating parameter type based on the sampled data collection file. In this invention, by acquiring user-defined monitoring content requirement instructions, it can flexibly respond to users' personalized monitoring needs for different devices and different operating parameters, realizing the transformation from generalized data collection to precise target monitoring, avoiding the blindness and redundancy of data collection. In addition, based on the sampling processing, it can efficiently and accurately generate monitoring data, realizing efficient and low-cost supervision of the operation of home appliances.

[0041] Figure 3 This is a schematic diagram of the process of sampling the embedded point file to obtain the sampled embedded point file provided by the present invention.

[0042] The following will combine Figure 3 The process of sampling the embedded point file to obtain the sampled embedded point file provided by the present invention is described.

[0043] In an exemplary embodiment of the present invention, combined with Figure 3 As can be seen, sampling the embedded point file to obtain the sampled embedded point file may include steps 310 to 330, and each step will be described below.

[0044] In step 310, the operation parameter types carried by the monitoring content requirement instruction are feature extracted to obtain parameter features corresponding to the operation parameter types.

[0045] In step 320, a sampling time interval matching the parameter characteristics is determined based on the parameter characteristics; In step 330, the embedded point file is sampled according to the sampling time interval to obtain the sampled embedded point file.

[0046] In one embodiment, features can be extracted from the operational parameter types carried by the monitoring content requirement instructions to obtain parameter features corresponding to the operational parameter types. Different parameter features correspond to different sampling time intervals.

[0047] Furthermore, continuing with the example described above, we can obtain a sampling time interval that matches the extracted parameter features corresponding to the running parameter type, based on the correspondence between different parameter features and different sampling time intervals. If the matching result is 5 minutes, this 5 minutes is determined as the sampling time interval that matches the currently processed data entry file.

[0048] In another embodiment, during operation, the device timestamps each generated tracking file. Only the last (or first) tracking file within each 5-minute time window is retained as a representative sample for that window. For example, among multiple tracking files generated within the window from 14:00 to 14:05, only the one generated at 14:04:59 is marked as a sampled tracking file; other data within the same window is discarded. This process continues, generating a sampled data set every 5 minutes. Furthermore, based on these tracking files sampled at fixed time intervals, monitoring data is generated, resulting in the sampled tracking files.

[0049] In this embodiment, the optimal sampling strategy can be automatically matched based on the inherent characteristics of the operating parameter type, such as its frequency of change and importance. This achieves on-demand sampling and avoids data distortion or resource waste caused by a one-size-fits-all sampling approach.

[0050] In yet another exemplary embodiment of the present invention, continuing with the previously described embodiments, the parameter features may include data update frequency and / or data importance level; wherein, determining the sampling time interval matching the parameter features based on the parameter features can be achieved in the following manner: Based on the data update frequency, determine a sampling time interval that matches the data update frequency, where the sampling time interval and the data update frequency are negatively correlated, or Based on the data importance level, a sampling time interval is determined that matches the data importance level, wherein the sampling time interval and the data importance level are negatively correlated.

[0051] In one embodiment, a sampling time interval matching the data update frequency can be determined based on the data update frequency, wherein the sampling time interval and the data update frequency are negatively correlated. In other words, the faster the data update frequency, the smaller the corresponding sampling time interval; the slower the data update frequency, the larger the corresponding sampling time interval.

[0052] In another embodiment, a sampling time interval matching the data importance level can be determined based on the data importance level, wherein the sampling time interval and the data importance level are negatively correlated. In other words, the higher the data importance level, the shorter the corresponding sampling time interval; the lower the data importance level, the longer the corresponding sampling time interval.

[0053] In yet another exemplary embodiment of the present invention, continuing with the previously described embodiments, the monitoring data may include detailed operational monitoring data and summary result monitoring data; wherein, based on the sampling and embedded point file, generating the monitoring data of the home appliance to be monitored under the operational parameter type can be achieved in the following manner: Based on the sampling and embedding file, detailed monitoring data of the home appliances to be monitored under the operating parameter type is generated; The detailed monitoring data is then aggregated to obtain the aggregated monitoring data.

[0054] In one embodiment, the sampled data file can be parsed and preliminarily calculated to obtain sampled data. For specific parameters under the operating parameter type, such as energy consumption parameters, based on the sampled data (e.g., instantaneous power data every 5 minutes), an interpolation algorithm is used to calculate a continuous power consumption sequence in hours, thereby obtaining detailed operating monitoring data, which is a detailed data list.

[0055] Furthermore, detailed monitoring data can be aggregated and summarized. For the same monitoring target, such as the cumulative electricity consumption for this month, all hourly average power consumption details within a specified time period can be summed up to obtain the final summarized monitoring data. It's understandable that the summarized monitoring data is a highly generalized numerical value.

[0056] In another embodiment, the Prometheus interface can be called. In Prometheus, data aggregation rules need to be set in advance. According to the rules, the indicator details data processed by the Java program are automatically aggregated to obtain the corresponding indicator result data, thereby obtaining the aggregated monitoring data.

[0057] In this embodiment, by generating two types of monitoring data—detailed operation data and summary results—the dual needs of users for both micro-level insight and macro-level control are simultaneously met. Users can use the detailed data to conduct in-depth analysis of the precise operational fluctuations of the equipment within a specific time period, and can also use the summary data to quickly grasp the overall operational status and cumulative effects.

[0058] In yet another exemplary embodiment of the present invention, continuing with the aforementioned embodiments as an example, after generating monitoring data for the home appliance to be monitored under the operating parameter type, the home appliance operation monitoring method may further include the following steps: Store monitoring data in a database; Upon receiving a display instruction, the system retrieves monitoring data from the database and then visualizes and displays the monitoring data.

[0059] In one embodiment, the generated monitoring data can be encapsulated and persistently stored in a designated database. Furthermore, upon receiving a display command, the monitoring data can be retrieved from the database and then visualized.

[0060] In this embodiment, by storing the generated monitoring data in a database, the monitoring results of each instance can be preserved long-term, establishing a complete historical archive of equipment operation. This allows users to review and trace the operating status of the equipment at any point in the past, providing a data foundation for analyzing long-term trends and troubleshooting historical problems, greatly enhancing the practical value of the monitoring method.

[0061] In another exemplary embodiment of the present invention, continuing with the previously described embodiments, the database may include a first database and a second database, wherein the first database is a relational database; the second database is a time-series database; the monitoring data includes detailed operation monitoring data and summary result monitoring data; wherein storing the monitoring data in the database can be achieved in the following manner: The detailed monitoring data of the operation is stored in the first database, and the summary monitoring data is stored in the second database; Upon receiving a display command, the monitoring data is retrieved from the database and then visualized. This can be achieved in the following ways: Upon receiving the first display instruction, the system retrieves detailed operational monitoring data from the first database and visualizes the data. Upon receiving the second display instruction, the summary result monitoring data is retrieved from the second database and then visualized. The first display instruction represents the instruction to display the detailed monitoring data; the second display instruction represents the instruction to display the summary result monitoring data.

[0062] In one embodiment, the generated detailed monitoring data can be formatted, organized, and persistently stored in a designated first database. This first database can be a MySQL relational database. During application, the generated detailed data can be inserted into this database as individual records. The transaction characteristics of the relational database ensure the integrity and consistency of this data write. Furthermore, during the generation of summary monitoring data, efficient aggregation queries can be performed based on the detailed data in this first database.

[0063] In another embodiment, upon receiving the first display instruction, parameters such as the device ID and date that the user wants to query can be parsed. Subsequently, a standard SQL query command is initiated to the first database (MySQL). After the database executes the query, it returns the operational detail monitoring data that meets the criteria, and can transform the operational detail monitoring data into a richer visualization format for display.

[0064] In another embodiment, the generated summary monitoring data can be formatted and persistently stored in a designated second database. This second database can be an SLS database. Upon receiving a second display instruction, the target device, indicator type, and time range can be parsed. Subsequently, an efficient time-series query command is initiated to the second database to obtain the summary monitoring data, which can then be visualized, thereby efficiently and intuitively meeting the user's need to view macro trends.

[0065] In yet another exemplary embodiment of the present invention, before summarizing the detailed operation monitoring data to obtain the summarized monitoring data, the home appliance operation monitoring method further includes the following steps: The running detailed monitoring data is deduplicated to obtain the deduplicated running detailed monitoring data; The deduplicated running detailed monitoring data is formatted and standardized to obtain the formatted running detailed monitoring data. The process of summarizing and processing detailed monitoring data to obtain summarized monitoring data can be achieved in the following ways: After standardizing the format, the detailed monitoring data is summarized to obtain the summarized monitoring data.

[0066] In one embodiment, for the initially generated operational detail monitoring data, data cleaning can be initiated to deduplicate the data, resulting in deduplicated operational detail monitoring data. Further, the deduplicated data can be formatted to obtain format-standardized operational detail monitoring data. This step aims to unify the data format, units, and precision, eliminating inconsistencies that may be introduced during data source or transmission.

[0067] After processing, the system can output standardized, formatted, and structurally consistent detailed monitoring data. Furthermore, this formatted detailed monitoring data can be aggregated to obtain summarized monitoring data. In this embodiment, because the input data has been free of duplicates and format errors, this aggregation calculation completely avoids errors in the summarized results caused by repeated additions or inconsistent units, ultimately generating accurate summarized monitoring data conforming to the preset standard format.

[0068] In yet another exemplary embodiment of the present invention, continuing with the above-described embodiments as an example, after obtaining the summarized monitoring data, the home appliance operation monitoring method may further include the following steps: If the monitored data in the summary results does not meet the preset requirements, an alarm will be issued to the user. The alarm is used to remind the user that the home device under monitoring has a malfunction under the preset operating parameter type.

[0069] In one embodiment, a series of monitoring rules and requirements for different types of operating parameters can be preset. Taking the monitoring of "daily electricity consumption this month" in "energy consumption" as an example, the preset requirement is set as a threshold rule: "If the electricity consumption on a certain day exceeds 20 kWh, it is judged as abnormally high power consumption."

[0070] During application, after generating the daily summary monitoring data, for example, after calculating the "electricity consumption on October 26, 2023" to be 25 kWh, it is immediately compared with preset requirements. The monitoring logic finds that the value 25 > the threshold 20, and determines that the preset requirements are not met. Subsequently, an alarm process is immediately triggered, generating an alarm reminder message. This message is sent to the user through preset channels, such as a push notification service linked to the user's app.

[0071] In this embodiment, after generating the summary results data, an automated result evaluation and alarm process is added. This makes the system not just a recorder and displayer of data, but also capable of proactively detecting anomalies based on preset logic such as thresholds, and promptly pushing key risk information to users. This greatly enhances the initiative and timeliness of monitoring, helping users to intervene in a timely manner before problems occur or before significant losses are incurred.

[0072] As described above, this invention provides a method for monitoring the operation of home appliances. To avoid the impact of large log files on the average observation indicators, data collection rules are edited to facilitate data sampling by the collection tool. This significantly reduces data computing resources and time. A MySQL database is used to store detailed indicator records, addressing the issue that Prometheus's SLS database only stores indicator results and lacks detailed data, enabling drill-down queries of detailed data in the data dashboard. Furthermore, a data alarm function is added to address the problem that observable data is only available through proactive data queries, lacking data alerts.

[0073] Based on the same inventive concept, the present invention also provides a home equipment operation monitoring platform. The structure of the home equipment operation monitoring platform will be described below with reference to the following embodiments.

[0074] In an exemplary embodiment of the present invention, the home appliance operation monitoring platform may include a platform interface and a processor. The platform interface is used to connect the home appliance to be monitored to the home appliance operation monitoring platform; the processor is used to execute any of the home appliance operation monitoring methods described herein. This embodiment achieves efficient and low-cost monitoring of the operation of home appliances.

[0075] The home equipment operation monitoring device provided by the present invention is described below. The home equipment operation monitoring device described below can be referred to in correspondence with the home equipment operation monitoring method described above.

[0076] Figure 4 This is a schematic diagram of the home appliance operation monitoring device provided by the present invention.

[0077] In an exemplary embodiment of the present invention, combined with Figure 4 As can be seen, the home equipment operation monitoring device may include a construction module 410, a generation module 420, a sampling module 430, and a monitoring module 440. Each module will be described in detail below.

[0078] The construction module 410 can be configured to construct a business tracking strategy that matches the operating parameters carried by the monitoring content requirement instruction based on the monitoring content requirement instruction; wherein, the monitoring content requirement instruction is an instruction used to characterize the operating parameters of the home device to be monitored under the operating parameter type. The generation module 420 can be configured to generate, based on the business data point tracking strategy, a data point file for the home device under the type of operating parameters carried by the monitoring content requirement instruction, when the home device to be monitored is in operation; The sampling module 430 can be configured to perform sampling processing on the embedded point file to obtain a sampled embedded point file. The monitoring module 440 can be configured to generate monitoring data of the home appliance to be monitored under the operating parameter type based on the sampling and embedding file.

[0079] In yet another exemplary embodiment of the present invention, the sampling module 430 may also be configured to: Feature extraction is performed on the type of operating parameters carried by the monitoring content requirement instruction to obtain parameter features corresponding to the type of operating parameters; Based on the parameter characteristics, determine the sampling time interval that matches the parameter characteristics; The sampling module 430 can perform sampling processing on the embedded point file in the following manner to obtain the sampled embedded point file: The embedded point file is sampled according to the sampling time interval to obtain the sampled embedded point file.

[0080] In yet another exemplary embodiment of the present invention, the parameter features include data update frequency and / or data importance level; The sampling module 430 can determine the sampling time interval that matches the parameter characteristics based on the parameter characteristics in the following manner: Based on the data update frequency, a sampling time interval matching the data update frequency is determined, wherein the sampling time interval and the data update frequency are negatively correlated, or Based on the data importance level, a sampling time interval matching the data importance level is determined, wherein the sampling time interval and the data importance level are negatively correlated.

[0081] In another exemplary embodiment of the present invention, the monitoring data includes detailed operation monitoring data and summary result monitoring data; the monitoring module 440 can generate monitoring data of the home appliance to be monitored under the operation parameter type based on the sampling and embedding file in the following manner: Based on the sampling and embedding file, detailed monitoring data of the home appliances to be monitored under the operating parameter type is generated; The detailed monitoring data is then aggregated to obtain the aggregated monitoring data.

[0082] In yet another exemplary embodiment of the present invention, the monitoring module 440 may also be configured to: The monitoring data is stored in a database; Upon receiving a display instruction, the monitoring data is retrieved from the database and then visualized.

[0083] In another exemplary embodiment of the present invention, the database includes a first database and a second database, wherein the first database is a relational database; the second database is a time-series database; and the monitoring data includes detailed operation monitoring data and summary result monitoring data. The monitoring module 440 can store the monitoring data in the database in the following ways: The detailed operation monitoring data is stored in the first database, and the summary result monitoring data is stored in the second database; The monitoring module 440 can retrieve the monitoring data from the database and visualize the monitoring data upon receiving a display command in the following manner: Upon receiving the first display instruction, the detailed operation monitoring data is retrieved from the first database and then visualized. Upon receiving the second display instruction, the summarized result monitoring data is retrieved from the second database and the summarized result monitoring data is visualized. The first display instruction is used to represent an instruction to display the detailed operation monitoring data; the second display instruction is used to represent an instruction to display the summarized result monitoring data.

[0084] In yet another exemplary embodiment of the present invention, the monitoring module 440 may also be configured to: The detailed operation monitoring data is deduplicated to obtain the deduplicated detailed operation monitoring data. The deduplicated running detail monitoring data is formatted and standardized to obtain formatted running detail monitoring data. The monitoring module 440 can summarize the detailed monitoring data of the operation in the following way to obtain the summarized monitoring data: The detailed monitoring data after the format specification is processed is summarized to obtain the summarized monitoring data.

[0085] In yet another exemplary embodiment of the present invention, the monitoring module 440 may also be configured to: If the monitored data of the aggregated results does not meet the preset requirements, an alarm is issued to the user. The alarm is used to remind the user that the home device to be monitored has a malfunction under the preset operating parameter type.

[0086] Figure 5 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 5 As shown, the electronic device may include: a processor 510, a communications interface 520, a memory 530, and a communication bus 540, wherein the processor 510, communications interface 520, and memory 530 communicate with each other through the communication bus 540. The processor 510 can call logical instructions in the memory 530 to execute a home appliance operation monitoring method. This method includes: constructing a business tracking strategy matching the operating parameters carried by the monitoring content requirement instruction based on the monitoring content requirement instruction; wherein the monitoring content requirement instruction is used to characterize the instructions for monitoring the operating parameters of the home appliance under the operating parameter type; when the home appliance is operating, generating a tracking file for the home appliance under the operating parameter type carried by the monitoring content requirement instruction based on the business tracking strategy; performing sampling processing on the tracking file to obtain a sampled tracking file; and generating monitoring data for the home appliance under the operating parameter type based on the sampled tracking file.

[0087] Furthermore, the logical instructions in the aforementioned memory 530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0088] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the home appliance operation monitoring method provided by the above methods. The method includes: constructing a business tracking strategy that matches the operation parameters carried by the monitoring content requirement instruction based on the monitoring content requirement instruction; wherein the monitoring content requirement instruction is used to characterize the instruction for monitoring the operation parameters of the home appliance to be monitored under the operation parameter type; generating a tracking file of the home appliance to be monitored under the operation parameter type carried by the monitoring content requirement instruction based on the business tracking strategy when the home appliance to be monitored is running; performing sampling processing on the tracking file to obtain a sampled tracking file; and generating monitoring data of the home appliance to be monitored under the operation parameter type based on the sampled tracking file.

[0089] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the home appliance operation monitoring method provided by the above methods. This method includes: constructing a business tracking strategy matching the operating parameters carried by the monitoring content requirement instruction based on a monitoring content requirement instruction; wherein the monitoring content requirement instruction is used to characterize the instructions for monitoring the operating parameters of the home appliance to be monitored under the operating parameter type; when the home appliance to be monitored is running, generating a tracking file for the home appliance to be monitored under the operating parameter type carried by the monitoring content requirement instruction based on the business tracking strategy; performing sampling processing on the tracking file to obtain a sampled tracking file; and generating monitoring data for the home appliance to be monitored under the operating parameter type based on the sampled tracking file.

[0090] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0091] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do 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 method for monitoring the operation of home appliances, characterized in that, The method includes: Based on the monitoring content requirement instruction, a business data entry strategy matching the operating parameters carried by the monitoring content requirement instruction is constructed; wherein, the monitoring content requirement instruction is used to characterize the operating parameters of the home device to be monitored under the operating parameter type. When the home appliance to be monitored is in operation, based on the business data collection strategy, a data collection file is generated for the home appliance to be monitored under the type of operating parameters carried by the monitoring content requirement instruction; The embedded point file is sampled to obtain the sampled embedded point file; Based on the sampling and embedding file, monitoring data of the home appliances to be monitored under the specified operating parameter type is generated.

2. The home appliance operation monitoring method according to claim 1, characterized in that, Before performing sampling processing on the embedded data point file to obtain the sampled embedded data point file, the method further includes: Feature extraction is performed on the type of operating parameters carried by the monitoring content requirement instruction to obtain parameter features corresponding to the type of operating parameters; Based on the parameter characteristics, determine the sampling time interval that matches the parameter characteristics; The sampling process of the embedded data file to obtain the sampled embedded data file includes: The embedded point file is sampled according to the sampling time interval to obtain the sampled embedded point file.

3. The home appliance operation monitoring method according to claim 2, characterized in that, The parameter characteristics include data update frequency and / or data importance level; The step of determining the sampling time interval matching the parameter characteristics based on the parameter characteristics includes: Based on the data update frequency, a sampling time interval matching the data update frequency is determined, wherein the sampling time interval and the data update frequency are negatively correlated, or Based on the data importance level, a sampling time interval matching the data importance level is determined, wherein the sampling time interval and the data importance level are negatively correlated.

4. The home appliance operation monitoring method according to claim 1, characterized in that, The monitoring data includes detailed operational monitoring data and summary result monitoring data; the generation of monitoring data for the home appliances to be monitored under the operational parameter type based on the sampled data file includes: Based on the sampling and embedding file, detailed monitoring data of the home appliances to be monitored under the operating parameter type is generated; The detailed monitoring data is then aggregated to obtain the aggregated monitoring data.

5. The home appliance operation monitoring method according to claim 1, characterized in that, After generating the monitoring data of the home appliance to be monitored under the specified operating parameter type, the method further includes: The monitoring data is stored in a database; Upon receiving a display instruction, the monitoring data is retrieved from the database and then visualized.

6. The home appliance operation monitoring method according to claim 5, characterized in that, The database includes a first database and a second database, wherein the first database is a relational database; the second database is a time-series database; and the monitoring data includes detailed operation monitoring data and summary result monitoring data. The step of storing the monitoring data in the database includes: The detailed operation monitoring data is stored in the first database, and the summary result monitoring data is stored in the second database; Upon receiving a display instruction, the step of retrieving the monitoring data from the database and visually displaying the monitoring data includes: Upon receiving the first display instruction, the detailed operation monitoring data is retrieved from the first database and then visualized. Upon receiving the second display instruction, the summarized result monitoring data is retrieved from the second database and the summarized result monitoring data is visualized. The first display instruction is used to represent an instruction to display the detailed operation monitoring data; the second display instruction is used to represent an instruction to display the summarized result monitoring data.

7. The home appliance operation monitoring method according to claim 4, characterized in that, Before summarizing the detailed monitoring data to obtain the summarized monitoring data, the method further includes: The detailed operation monitoring data is deduplicated to obtain the deduplicated detailed operation monitoring data. The deduplicated running detail monitoring data is formatted and standardized to obtain formatted running detail monitoring data. The process of summarizing the detailed monitoring data to obtain the summarized monitoring data includes: The detailed monitoring data after the format specification is processed is summarized to obtain the summarized monitoring data.

8. The home appliance operation monitoring method according to claim 4, characterized in that, After obtaining the summarized monitoring data, the method further includes: If the monitored data of the aggregated results does not meet the preset requirements, an alarm is issued to the user. The alarm is used to remind the user that the home device to be monitored has a malfunction under the preset operating parameter type.

9. A home appliance operation monitoring device, characterized in that, The device includes: The construction module is used to construct a business tracking strategy that matches the operating parameters carried by the monitoring content requirement instruction based on the monitoring content requirement instruction; wherein, the monitoring content requirement instruction is used to characterize the instructions for monitoring the operating parameters of the home device to be monitored under the operating parameter type; The generation module is used to generate, based on the business data point tracking strategy, a data point file for the home device under the type of operating parameters carried by the monitoring content requirement instruction, when the home device to be monitored is in operation. The sampling module is used to perform sampling processing on the embedded point file to obtain the sampled embedded point file; The monitoring module is used to generate monitoring data of the home appliances to be monitored under the operating parameter type based on the sampling and embedded point files.

10. A home appliance operation monitoring platform, characterized in that, The home appliance operation monitoring platform includes: The platform interface is used to connect the home appliances to be monitored to the home appliance operation monitoring platform, and A processor, wherein the processor is configured to perform the home appliance operation monitoring method according to any one of claims 1 to 8.

11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the home appliance operation monitoring method as described in any one of claims 1 to 8.

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