Method and device for reporting equipment information

Abstract

The invention discloses a method and a device for reporting equipment information. The method comprises the steps that when it is determined that target intelligent equipment executes equipment information reporting operation according to an initial information reporting strategy, actual equipment related data of the target intelligent equipment is acquired, and the initial information reporting strategy is a reporting strategy determined according to historical equipment related data of the target intelligent equipment; the historical equipment related data is data related to the use of the target intelligent equipment; adjusting the initial information reporting strategy according to the actual equipment related data to obtain a real-time information reporting strategy; and issuing the real-time information reporting strategy to the target intelligent equipment, so that the target intelligent equipment reports the equipment information according to the real-time information reporting strategy. According to the method and the device, the technical problem that in the related technology, the Internet of Things equipment reports the state to the cloud server at a fixed time, and when the quantity of the equipment is large and the access quantity of a third-party cloud platform is large, the reporting mode is easy to bring pressure to the server is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent device control, and in particular to a method and apparatus for reporting device information. Background Art

[0002] Most current IoT devices support control from various cloud platforms. For example, a single control software can control devices from multiple manufacturers. These IoT devices often report their status to their own cloud servers at fixed intervals, which then push the status to third-party cloud platforms, synchronizing device status across different apps. However, with a large number of devices and connections to numerous third-party cloud platforms, this data reporting method can put pressure on servers. In many cases, the reported data is not used, resulting in high server pressure and wasted resources.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] An embodiment of the present invention provides a method and apparatus for reporting device information, so as to at least solve the technical problem in the related art that IoT devices use a fixed time to report their status to a cloud server. When the number of devices is large and the number of third-party cloud platforms connected is large, this reporting method easily puts pressure on the server.

[0005] According to one aspect of an embodiment of the present invention, a method for reporting device information is provided, comprising: when determining that a target smart device performs a device information reporting operation according to an initial information reporting policy, obtaining actual device-related data of the target smart device, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device; adjusting the initial information reporting policy based on the actual device-related data to obtain a real-time information reporting policy; and issuing the real-time information reporting policy to the target smart device so that the target smart device reports device information according to the real-time information reporting policy.

[0006] Optionally, before determining that the target smart device performs a device information reporting operation according to the initial information reporting strategy, the device information reporting method also includes: obtaining the historical device-related data of the target smart device; analyzing and processing the historical device-related data through a prediction model to obtain the initial information reporting strategy, wherein the prediction model is a model obtained by machine learning training using multiple sets of training data, and each of the multiple sets of training data includes: sample device-related data and a sample information reporting strategy corresponding to the sample device-related data.

[0007] Optionally, obtaining the historical device-related data of the target smart device includes at least one of the following: obtaining user interaction data of the target smart device, wherein the user interaction data is operation data performed on the target smart device; obtaining device status data of the target smart device, wherein the device status data is used to record operating information of the target smart device; obtaining time data of the target smart device, wherein the time data is used to record the time when the target smart device performs various operations; obtaining power usage data of the target smart device.

[0008] Optionally, the initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: determining the current information reporting frequency of the target smart device according to the actual device-related data; determining whether the target smart device is currently in a peak usage period according to the historical device-related data, wherein the peak usage period indicates that the number of access devices to the target service platform exceeds the access device threshold, and the target service platform is the platform to which the target smart device accesses; when the current information reporting frequency is higher than the frequency threshold and the target smart device is currently in the peak usage period, the initial information reporting strategy is adjusted to obtain the real-time information reporting strategy.

[0009] Optionally, the initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: obtaining the data to be reported of the target smart device; classifying the data to be reported to obtain sub-data to be reported; determining the priority of each sub-data to be reported; and adjusting the initial information reporting strategy according to the priority to obtain the real-time information reporting strategy.

[0010] Optionally, the initial information reporting strategy is adjusted according to the priority to obtain the real-time information reporting strategy, including: determining the high-priority data and low-priority data in each of the sub-data to be reported, wherein the high-priority data is the following data in the data to be reported: instruction execution result data, device online status data, and the low-priority data is the log record data in the data to be reported; adjusting the initial information reporting strategy to: give priority to reporting the high-priority data and reduce the reporting frequency of the low-priority data.

[0011] Optionally, reducing the reporting frequency of the low-priority data includes: compressing the low-priority data to obtain a compressed data packet; and reporting the compressed data packet when the amount of the low-priority data in the compressed data packet reaches a quantity threshold.

[0012] Optionally, the initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: when it is determined that the target smart device has an abnormality according to the actual device-related data, obtaining the abnormal data of the target smart device; adjusting the initial information reporting strategy to: prioritize reporting the abnormal data.

[0013] Optionally, after the real-time information reporting strategy is sent to the target smart device so that the target smart device reports the device information according to the real-time information reporting strategy, the device information reporting method also includes: after determining that the time for the target smart device to report the device information according to the real-time information reporting strategy reaches a predetermined time, obtaining the interaction data received by the target smart device in the process of reporting the device information according to the real-time information reporting strategy; and adjusting the real-time information reporting strategy according to the interaction data.

[0014] According to another aspect of an embodiment of the present invention, a device information reporting device is also provided, including: a first acquisition unit, used to obtain actual device-related data of the target smart device when it is determined that the target smart device performs a device information reporting operation according to an initial information reporting policy, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device; an adjustment unit, used to adjust the initial information reporting policy based on the actual device-related data to obtain a real-time information reporting policy; and a reporting unit, used to send the real-time information reporting policy to the target smart device so that the target smart device reports device information according to the real-time information reporting policy.

[0015] Optionally, the device information reporting apparatus further includes: a second acquisition unit, for acquiring the historical device-related data of the target smart device before determining that the target smart device performs a device information reporting operation according to an initial information reporting strategy; a processing unit, for analyzing and processing the historical device-related data through a prediction model to obtain the initial information reporting strategy, wherein the prediction model is a model obtained by machine learning training using multiple sets of training data, and each of the multiple sets of training data includes: sample device-related data and a sample information reporting strategy corresponding to the sample device-related data.

[0016] Optionally, the second acquisition unit includes at least one of the following: a first acquisition module, used to acquire user interaction data of the target smart device, wherein the user interaction data is operation data performed on the target smart device; a second acquisition module, used to acquire device status data of the target smart device, wherein the device status data is used to record operating information of the target smart device; a third acquisition module, used to acquire time data of the target smart device, wherein the time data is used to record the time when the target smart device performs various operations; a fourth acquisition module, used to acquire power usage data of the target smart device.

[0017] Optionally, the adjustment unit includes: a first determination module, used to determine the current information reporting frequency of the target smart device based on the actual device-related data; a second determination module, used to determine whether the target smart device is currently in a peak usage period based on the historical device-related data, wherein the peak usage period indicates that the number of access devices to the target service platform exceeds the access device threshold, and the target service platform is the platform to which the target smart device accesses; the first adjustment module, used to adjust the initial information reporting strategy when the current information reporting frequency is higher than the frequency threshold and the target smart device is currently in the peak usage period, to obtain the real-time information reporting strategy.

[0018] Optionally, the adjustment unit includes: a fifth acquisition module, used to obtain the data to be reported of the target smart device; a classification module, used to classify the data to be reported to obtain sub-data to be reported; a third determination module, used to determine the priority of each sub-data to be reported; and a second adjustment module, used to adjust the initial information reporting strategy according to the priority to obtain the real-time information reporting strategy.

[0019] Optionally, the second adjustment module includes: a determination submodule for determining high-priority data and low-priority data in each of the sub-data to be reported, wherein the high-priority data is the following data in the data to be reported: instruction execution result data, device online status data, and the low-priority data is log record data in the data to be reported; an adjustment submodule for adjusting the initial information reporting strategy to: give priority to reporting the high-priority data and reduce the reporting frequency of the low-priority data.

[0020] Optionally, the entire submodule includes: a compression submodule, used to compress the low-priority data to obtain a compressed data packet; and a reporting submodule, used to report the compressed data packet when the amount of the low-priority data in the compressed data packet reaches a quantity threshold.

[0021] Optionally, the adjustment unit includes: a sixth acquisition module, used to obtain abnormal data of the target smart device when it is determined that the target smart device has an abnormality based on the actual device-related data; and a third adjustment module, used to adjust the initial information reporting strategy to: prioritize reporting the abnormal data.

[0022] Optionally, the device information reporting device also includes: a third acquisition unit, which is used to, after sending the real-time information reporting policy to the target smart device so that the target smart device reports the device information according to the real-time information reporting policy, obtain the interaction data received by the target smart device in the process of reporting the device information according to the real-time information reporting policy after determining that the time for the target smart device to report the device information according to the real-time information reporting policy reaches a predetermined time; the adjustment unit is used to adjust the real-time information reporting policy according to the interaction data.

[0023] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein the program executes any one of the above-mentioned methods for reporting device information.

[0024] According to another aspect of an embodiment of the present invention, a processor is provided, which is configured to run a program, wherein the program executes any one of the above-mentioned methods for reporting device information when running.

[0025] According to another aspect of an embodiment of the present invention, a computer program product is provided, including computer instructions, which, when executed by a processor, execute any one of the above-mentioned methods for reporting device information.

[0026] In an embodiment of the present invention, when determining that a target smart device performs a device information reporting operation according to an initial information reporting policy, actual device-related data of the target smart device is obtained, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device; the initial information reporting policy is adjusted based on the actual device-related data to obtain a real-time information reporting policy; and the real-time information reporting policy is issued to the target smart device so that the target smart device reports device information according to the real-time information reporting policy. The technical solution provided by the present invention, compared with the prior art, in which smart devices always report device information in a fixed manner, which causes a large pressure on the server during peak hours, realizes the dynamic adjustment of the device information reporting policy so that the smart device can report information according to the information reporting policy suitable for the current moment, thereby achieving the technical effect of reducing the pressure on the server, thereby solving the technical problem that the related art IoT devices use a fixed time to report status to the cloud server, which is easy to cause pressure on the server when the number of devices is large and the number of third-party cloud platforms connected is large. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0028] Figure 1 This is a hardware structure block diagram of a mobile terminal according to a method for reporting device information according to an embodiment of the present invention;

[0029] Figure 2 is a flowchart of a method for reporting device information according to an embodiment of the present invention;

[0030] Figure 3 is a flowchart of an optional method for reporting device information according to an embodiment of the present invention;

[0031] Figure 4 2 is a schematic diagram of a device for reporting device information according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] As described in the background, IoT devices typically report their status to cloud servers at fixed intervals. However, this reporting method can easily overwhelm the server when a large number of devices and third-party cloud platforms are connected. Embodiments of the present invention provide a method and apparatus for reporting device information, a computer-readable storage medium, a processor, and a computer program product.

[0035] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0036] The method embodiments provided in the embodiments of the present invention can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG is a hardware structure block diagram of a mobile terminal of a device information reporting method according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown) a processor 102 (the processor 102 may include but is not limited to a microprocessor MCU or a programmable logic device FPGA and other processing devices) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0037] The memory 104 can be used to store computer programs, such as software programs and modules of application software, such as the computer program corresponding to the device information reporting method in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implementing the above-mentioned method. The memory 104 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned networks include but are not limited to the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the above-mentioned network may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0038] Example 1

[0039] According to an embodiment of the present invention, a method embodiment of a method for reporting device information is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0040] Figure 2 FIG. 1 is a flow chart of a method for reporting device information according to an embodiment of the present invention. Figure 2 As shown, the method for reporting device information includes the following steps:

[0041] In step S202, when it is determined that the target smart device performs a device information reporting operation according to an initial information reporting policy, actual device-related data of the target smart device is obtained, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device.

[0042] Optionally, the target smart devices may include but are not limited to: air conditioners, washing machines, rice cookers, broom robots, etc.

[0043] Optionally, the initial information reporting strategy can be obtained by learning and predicting user behavior patterns through machine learning algorithms. The initial information reporting strategy is the device information reporting method adopted by the target smart device at the current moment, such as reporting frequency, reporting order, etc.

[0044] Optionally, the actual device-related data is the device data of the target smart device at the current moment, such as device power, device operating status, humidity and temperature of the room where the device is located, etc.

[0045] In this embodiment, the user's behavior pattern can be learned and predicted through a machine learning algorithm based on the historical device-related data of the target smart device to obtain the device information reporting method of the target smart device at that moment.

[0046] Step S204: Adjust the initial information reporting strategy according to actual device-related data to obtain a real-time information reporting strategy.

[0047] In this embodiment, the initial information reporting strategy obtained above can be fine-tuned based on the actual device-related data of the target smart device to obtain a device information reporting strategy suitable for the current moment, that is, a real-time information reporting strategy, so that the information reporting method of the target smart device is more in line with the current moment, reducing the server pressure.

[0048] Step S206: Send the real-time information reporting policy to the target smart device, so that the target smart device reports the device information according to the real-time information reporting policy.

[0049] From the above, it can be seen that when determining that the target smart device performs the device information reporting operation according to the initial information reporting strategy, the actual device-related data of the target smart device is obtained, wherein the initial information reporting strategy is a reporting strategy determined based on the historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device; the initial information reporting strategy is adjusted according to the actual device-related data to obtain the real-time information reporting strategy; the real-time information reporting strategy is sent to the target smart device, so that the target smart device reports the device information according to the real-time information reporting strategy. Compared with the prior art, the smart device always reports the device information in a fixed manner, which leads to the defect of greater server pressure during peak hours, the device information reporting strategy is dynamically adjusted so that the smart device can report information according to the information reporting strategy suitable for the current moment, thereby achieving the technical effect of reducing the pressure on the server.

[0050] Therefore, the above-mentioned technical solution provided by the embodiment of the present invention solves the technical problem in the related technology that IoT devices use a fixed time to report their status to the cloud server. When the number of devices is large and the number of third-party cloud platforms connected is large, this reporting method easily puts pressure on the server.

[0051] According to the above embodiment of the present invention, before determining that the target smart device performs the device information reporting operation according to the initial information reporting strategy, the device information reporting method may also include: obtaining historical device-related data of the target smart device; analyzing and processing the historical device-related data through a prediction model to obtain an initial information reporting strategy, wherein the prediction model is a model obtained by machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: sample device-related data and a sample information reporting strategy corresponding to the sample device-related data.

[0052] In this embodiment, before the target smart device starts running, historical operating data over a period of time can be collected first, and a pre-trained prediction model can be used to determine the above-mentioned initial information reporting strategy. The model is trained based on a large number of similar device data sets to identify effective information reporting strategies. For example, the cloud platform collects usage data from smart TVs for the past month, including user viewing time, channel preferences, device failure rates, etc. Then, using historical data as input, the machine learning model is trained to analyze the user's viewing habits and device operation patterns, and predict the optimal initial information reporting strategy. The model outputs a strategy that stipulates that during the user's peak viewing period (7pm to 10pm), the reporting frequency should be once every 5 minutes; and during the non-peak period (2am to 5am), the reporting frequency is reduced to once every 30 minutes.

[0053] The initial information reporting strategy determined above will guide the device to report appropriate data at a specific time.

[0054] The introduction of machine learning prediction models here makes strategy formulation more intelligent and able to adapt to changes in equipment operating characteristics.

[0055] Through data analysis, predictive models can identify which data is critical to improving user experience and monitoring device health, thereby developing strategies that meet functional requirements without wasting resources.

[0056] This predictive model addresses the problem of rigid reporting strategies caused by unforeseen changes in user behavior. Furthermore, dynamically adjusted strategies not only reduce the transmission of unnecessary data but also ensure the timeliness of critical data during high-demand moments, effectively balancing resource consumption and information value.

[0057] It should be noted that Figure 3is a flow chart of an optional method for reporting device information according to an embodiment of the present invention. Figure 3 As shown, the target smart device in the embodiment of the present invention can be connected to the Internet and report device status data, and the device manufacturer cloud and the third-party cloud can communicate with each other. The user can control the device and view the device status through the APP provided by the third party, and is required to allow the cloud to collect the user's usage habits and device status data through the device's built-in sensors or user interaction records, that is, device usage-related data.

[0058] According to the above embodiment, obtaining historical device-related data of the target smart device may include at least one of the following: obtaining user interaction data of the target smart device, wherein the user interaction data is operation data performed on the target smart device; obtaining device status data of the target smart device, wherein the device status data is used to record operating information of the target smart device; obtaining time data of the target smart device, wherein the time data is used to record the time when the target smart device performs various operations; obtaining power usage data of the target smart device.

[0059] In this embodiment, user interaction data of the device (target smart device), such as command input, status query requests, etc., can be collected; device operating status data, including various parameters and indicators of the device, can be recorded; device timestamp data can be obtained to understand the precise time when the device was running; and the power usage of the device can be monitored to ensure long-term stable operation of the device. In addition, taking the refrigerator as an example, user interaction data collection: the smart refrigerator records each operation such as opening the door, temperature adjustment, and food storage. Device status data recording: Continuously monitor and record key operating parameters such as the internal temperature, humidity, and compressor operating status of the refrigerator. Time data recording: Track when the user uses the refrigerator most frequently every day. Power usage data acquisition: Monitor the power consumption of the refrigerator at different time periods throughout the day.

[0060] This multi-dimensional data collection overcomes the problem of a single data source being insufficient for a comprehensive assessment of device status. Furthermore, this detailed data helps build more accurate device usage models, enabling the development of more refined and personalized information reporting strategies.

[0061] It should be noted that the data acquisition method here can be completed in the following ways: 1) Direct collection: by analyzing user voice commands, touch screens, key operation records, etc.; 2) Indirect collection: by analyzing device execution logs, error codes and other information, or, collection mechanisms or algorithms, that is, pre-processing of data to screen valid data, and obtaining valid data through clustering algorithms, noise filtering, unsupervised / supervised learning and other algorithms.

[0062] In addition, when using the app, users can select the authorized scope of privacy information through the app. For example, they can obtain the device's successful operation records or voice command content, but prohibit the content obtained by the camera, etc., to ensure user privacy.

[0063] From the above, it can be seen that in the embodiment of the present invention, user data collection includes: user interaction data such as recording the user's operations on the air conditioner switch, temperature adjustment, mode switching, etc.; device status data such as recording the air conditioner's operating status, temperature, humidity and other environmental information; time information such as recording the time point when the operation occurs to identify peak usage periods; other information such as power usage, changes in user sleep curves, etc., are also used to provide data to third-party cloud platforms.

[0064] Comprehensive device data collection ensures extensive coverage of the underlying data for policy adjustments, enabling assessment of device operating status and user usage patterns from multiple perspectives. This data collection helps build more accurate user behavior models, enabling the development of reporting strategies that better meet user needs and enhance the user experience.

[0065] According to the above embodiment of the present invention, the initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: determining the current information reporting frequency of the target smart device according to the actual device-related data; determining whether the target smart device is currently in a peak usage period according to historical device-related data, wherein the peak usage period indicates that the number of access devices to the target service platform exceeds the access device threshold, and the target service platform is the platform to which the target smart device accesses; when the current information reporting frequency is higher than the frequency threshold and the target smart device is currently in a peak usage period, the initial information reporting strategy is adjusted to obtain a real-time information reporting strategy.

[0066] In this embodiment, the user interaction data obtained above can be analyzed to identify the user's usage habits, such as daily usage time period, preferred temperature and mode; and the operating efficiency of the device can be analyzed, such as energy consumption and performance in different time periods.

[0067] In addition, the current reporting frequency of the target smart device can be determined by evaluating actual device data. For example, if the current reporting frequency is once every 10 minutes, the system will then check whether it is during a peak period when the number of devices connected to the server exceeds 10,000. If both the current reporting frequency is higher than once every 15 minutes and it is during a peak period, the reporting policy will be adjusted to reduce the reporting frequency to once every 20 minutes.

[0068] Specifically, machine learning algorithms are used to learn and predict user behavior patterns and identify peak and off-peak periods for device usage. Figure 3As shown, some device usage habits are strongly correlated with chronological order. Clustering algorithms and time series analysis can be used to predict user usage habits for these devices. The cloud can "predict" user device usage and increase the frequency of status reporting for certain devices (such as air conditioners, which are generally manually controlled by users) before and after use.

[0069] For example, the initial reporting frequency is set to once every 15 minutes, which applies to all time periods. By analyzing user data, it is identified that 8 a.m. to 10 a.m. is the high-frequency usage period for refrigerators. During this peak period, the reporting frequency is adjusted to once every 5 minutes to ensure that changes in device status can be captured in a timely manner when user activity is frequent. During the inactive period at night (such as 11 p.m. to 6 a.m.), the reporting frequency is reduced to once every hour due to the decrease in device usage frequency. The adjustment of the reporting frequency is based on the time period, which effectively reduces the data traffic during the non-peak period and reduces the burden on the server. The threshold setting (peak period: 8 a.m. to 10 a.m.; non-peak period: 11 p.m. to 6 a.m.) ensures the targeted and feasible nature of the policy adjustment.

[0070] The peak hours here can help prevent network congestion and server overload caused by a large number of devices reporting data simultaneously. Lowering the reporting frequency reduces unnecessary data transmission, helping to maintain system stability and reduce operating costs. The introduction of thresholds (such as exceeding 10,000 devices) provides a quantitative standard to facilitate automated policy adjustments.

[0071] According to the above embodiment of the present invention, the initial information reporting strategy is adjusted according to the actual device-related data to obtain the real-time information reporting strategy, which may include: obtaining the data to be reported of the target smart device; classifying the data to be reported to obtain sub-data to be reported; determining the priority of each sub-data to be reported; and adjusting the initial information reporting strategy according to the priority to obtain the real-time information reporting strategy.

[0072] In this embodiment, the data to be reported can be classified according to the type of data to be reported, and different priorities can be set for different types of data to determine the data reporting method based on the priority, and then the initial information reporting strategy can be adjusted to make the information reporting of the target smart device more reasonable.

[0073] For example, the reporting strategy can be adjusted according to the actual usage of the device. For example, data such as the power usage of a sweeping robot has the characteristics of large data volume, fast changes, and low usage times, and requires a third party to analyze such data. Therefore, when reporting such data, the reported data can be compressed based on the user's usage habits. For example, 5-10 data packets can be compressed together and reported once to reduce the reporting frequency, avoid network congestion and increased server pressure caused by too frequent reporting, and complete the fine-tuning of the reporting strategy based on the user usage habit model.

[0074] According to the above embodiment of the present invention, the initial information reporting strategy is adjusted according to the priority to obtain a real-time information reporting strategy, including: determining the high-priority data and low-priority data in each sub-data to be reported, wherein the high-priority data is the following data in the data to be reported: instruction execution result data, device online status data, and the low-priority data is the log record data in the data to be reported; adjusting the initial information reporting strategy to: give priority to reporting high-priority data and reduce the reporting frequency of low-priority data.

[0075] Here we take a washing machine as an example to illustrate data classification: the data to be reported by the smart washing machine is divided into instruction execution results, online status (high priority) and log records (low priority).

[0076] Priority setting: After the washing machine completes the wash command, it immediately reports the execution result data; online status data is reported every 3 minutes to ensure that the device can be remotely controlled at any time; log record data is compressed and packaged, and is uploaded only once the data packet accumulates to at least contain all log records in the past 24 hours.

[0077] Data classification and prioritization ensure the real-time delivery of high-priority data and the efficient storage of low-priority data. Threshold settings (reporting online status every three minutes; log data packets contain at least 24 hours of data) optimize server storage and processing capabilities while ensuring the transmission of critical information.

[0078] For example, you can first check the current device reporting frequency to see if it is a usage peak period. If not, report normally. If it is a peak period, prioritize the data to be reported, such as command execution results (success / failure) and offline device reporting as high priority, and other log records as low priority. For high priority, report in a timely manner, and for low priority, you can appropriately reduce the reporting frequency, such as compressing 5-10 data times and reporting them together.

[0079] According to the above embodiment of the present invention, the reporting frequency of low-priority data is reduced, including: compressing the low-priority data to obtain a compressed data packet; when the amount of low-priority data in the compressed data packet reaches a quantity threshold, reporting the compressed data packet.

[0080] In this embodiment, multiple data to be reported can be compressed, for example, 5-10 data packets can be compressed together and reported once, thereby reducing the reporting frequency and avoiding network congestion and increased server pressure caused by too frequent reporting.

[0081] According to the above embodiment of the present invention, the initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: when it is determined that the target smart device has an abnormality according to the actual device-related data, obtaining the abnormal data of the target smart device; adjusting the initial information reporting strategy to: give priority to reporting abnormal data.

[0082] For example, if a smartwatch detects an abnormal heart rate (outside the normal range of 100 to 120 beats per minute), it will immediately report the abnormal data to the health monitoring cloud platform. At the same time, the watch's daily usage data, such as step count and sleep quality analysis, will be reported at a preset lower frequency (for example, once a day).

[0083] The immediate reporting of abnormal data here improves the response speed of health monitoring, facilitating early symptom detection and intervention. The low-frequency reporting strategy for daily data reduces network transmission load without affecting long-term health trend analysis. The threshold setting (abnormal heart rate: 100 to 120 beats / minute) reflects the emphasis on health monitoring and the precise control of data transmission.

[0084] In addition, in embodiments of the present invention, abnormal device states can also be detected. When an abnormal device state is detected, the data reported by the device is differentiated, and data such as device status and fault codes are reported promptly. Other data characteristics are still compressed and reported to ensure that the abnormal state can be reported to the cloud immediately.

[0085] According to the above embodiment of the present invention, after the real-time information reporting strategy is sent to the target smart device so that the target smart device reports the device information according to the real-time information reporting strategy, the device information reporting method also includes: after determining that the time duration for the target smart device to report the device information according to the real-time information reporting strategy reaches a predetermined time duration, obtaining the interaction data received by the target smart device in the process of reporting the device information according to the real-time information reporting strategy; and adjusting the real-time information reporting strategy according to the interaction data.

[0086] In this embodiment, for example, after a smart lamp has been operating for 30 days, user control data and device operation data from that period are collected, including on / off frequency, brightness adjustment, and peak usage periods. This data is analyzed to evaluate the effectiveness of the real-time information reporting strategy and adjust the strategy based on recent changes in user behavior. If the data shows that users use the lamp significantly more frequently on weekend nights than on weekdays, the strategy might be adjusted to increase the frequency of lamp status reporting to every 10 minutes between 6:00 PM and 10:00 PM on weekends.

[0087] like Figure 3 As shown, based on the different configurations of the third-party cloud, the required reporting information can be analyzed, a reporting policy model can be trained, and the corresponding reporting policy can be distributed to the device, which then executes the new reporting policy. After completing the reporting, the device monitors user usage and performs cross-validation to examine the impact of the modification on the user experience. For example, it can check whether the user's operation frequency or refresh rate has changed. If the user refreshes too frequently, it indicates dissatisfaction with the synchronization rate of the reported information, indicating that the reporting policy does not meet the user's needs.

[0088] Through subsequent data collection and analysis, we can continuously optimize information reporting strategies to adapt to dynamic changes in user behavior, improving overall system responsiveness and resource utilization. The threshold settings here (strategy adjustment cycle: 30 days; weekend evening usage boost period: 6:00 PM to 10:00 PM) reflect the strategy's flexibility and sensitivity to changes in user behavior, ensuring efficient system operation in different usage scenarios.

[0089] As can be seen from the above, in an embodiment of the present invention, the device reporting type is judged, and the cloud evaluates the priority of the reported data based on the data reported by the device and changes its priority strategy. The device adjusts the reporting plan according to the strategy. The server monitors the usage of the device reported information, adjusts the priority of the necessary data required, generates a new device reporting strategy, and fine-tunes the reporting frequency. It reports on demand for users without affecting the user experience while reducing the reporting pressure on the server. It can achieve less reporting data when the user usage frequency is low, and can adjust the reporting strategy (compressed reporting, time-clustered reporting, etc.) based on the usage of the third-party cloud platform, avoiding the situation of continuous device reporting, reducing unnecessary network communication and resource consumption, and improving user experience and device performance. That is, for different users and different third-party apps, the cloud determines the necessary reporting plan, dynamically adjusts the device status reporting strategy, and sends the adjusted plan to the device, which executes the corresponding plan, reducing the reporting pressure on the server.

[0090] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0091] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0092] Example 2

[0093] According to an embodiment of the present invention, there is also provided a device information reporting apparatus for implementing the above device information reporting method. Figure 4 is a schematic diagram of a device for reporting device information according to an embodiment of the present invention. Figure 4 As shown, the apparatus includes: a first acquiring unit 401, an adjusting unit 403, and a reporting unit 405. The apparatus is described below.

[0094] The first acquisition unit 401 is used to acquire actual device-related data of the target smart device when it is determined that the target smart device performs a device information reporting operation according to an initial information reporting policy, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device.

[0095] The adjusting unit 403 is configured to adjust the initial information reporting strategy according to actual device-related data to obtain a real-time information reporting strategy.

[0096] The reporting unit 405 is configured to send the real-time information reporting policy to the target smart device, so that the target smart device reports the device information according to the real-time information reporting policy.

[0097] It should be noted here that the above-mentioned first acquisition unit 401, adjustment unit 403 and reporting unit 405 correspond to steps S202 to S206 in the above-mentioned embodiment. The three units and the corresponding steps implement the same instances and application scenarios, but are not limited to the contents disclosed in the above-mentioned embodiment.

[0098] As can be seen from the above, in the scheme recorded in the above embodiment of the present invention, the first acquisition unit can be used to obtain the actual device-related data of the target smart device when determining that the target smart device performs the device information reporting operation according to the initial information reporting strategy, wherein the initial information reporting strategy is a reporting strategy determined based on the historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device; then the adjustment unit is used to adjust the initial information reporting strategy according to the actual device-related data to obtain the real-time information reporting strategy; and the reporting unit is used to send the real-time information reporting strategy to the target smart device, so that the target smart device reports the device information according to the real-time information reporting strategy. Compared with the prior art, the smart device reports the device information in a fixed manner at any time, which leads to the defect of greater server pressure during peak hours. The device information reporting strategy is dynamically adjusted so that the smart device can report information according to the information reporting strategy suitable for the current moment, thereby achieving the technical effect of reducing the pressure on the server.

[0099] Optionally, the device information reporting device also includes: a second acquisition unit, used to obtain historical device-related data of the target smart device before determining that the target smart device performs the device information reporting operation according to the initial information reporting strategy; a processing unit, used to analyze and process the historical device-related data through a prediction model to obtain the initial information reporting strategy, wherein the prediction model is a model obtained by machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: sample device-related data and a sample information reporting strategy corresponding to the sample device-related data.

[0100] Optionally, the second acquisition unit includes at least one of the following: a first acquisition module, used to acquire user interaction data of the target smart device, wherein the user interaction data is operation data performed on the target smart device; a second acquisition module, used to acquire device status data of the target smart device, wherein the device status data is used to record operating information of the target smart device; a third acquisition module, used to acquire time data of the target smart device, wherein the time data is used to record the time when the target smart device performs various operations; a fourth acquisition module, used to acquire power usage data of the target smart device.

[0101] Optionally, the adjustment unit includes: a first determination module, used to determine the current information reporting frequency of the target smart device based on actual device-related data; a second determination module, used to determine whether the target smart device is currently in a peak usage period based on historical device-related data, wherein the peak usage period indicates that the number of access devices to the target service platform exceeds the access device threshold, and the target service platform is the platform to which the target smart device accesses; the first adjustment module is used to adjust the initial information reporting strategy to obtain a real-time information reporting strategy when the current information reporting frequency is higher than the frequency threshold and the target smart device is currently in a peak usage period.

[0102] Optionally, the adjustment unit includes: a fifth acquisition module, used to obtain the data to be reported of the target smart device; a classification module, used to classify the data to be reported to obtain sub-data to be reported; a third determination module, used to determine the priority of each sub-data to be reported; and a second adjustment module, used to adjust the initial information reporting strategy according to the priority to obtain a real-time information reporting strategy.

[0103] Optionally, the second adjustment module includes: a determination sub-module for determining high-priority data and low-priority data in each sub-data to be reported, wherein the high-priority data is the following data in the data to be reported: instruction execution result data, device online status data, and the low-priority data is log record data in the data to be reported; an adjustment sub-module for adjusting the initial information reporting strategy to: give priority to reporting high-priority data and reduce the reporting frequency of low-priority data.

[0104] Optionally, the entire submodule includes: a compression submodule, used to compress low-priority data to obtain a compressed data packet; and a reporting submodule, used to report the compressed data packet when the amount of low-priority data in the compressed data packet reaches a quantity threshold.

[0105] Optionally, the adjustment unit includes: a sixth acquisition module, used to obtain abnormal data of the target smart device when it is determined that the target smart device has an abnormality based on actual device-related data; and a third adjustment module, used to adjust the initial information reporting strategy to: give priority to reporting abnormal data.

[0106] Optionally, the device information reporting device also includes: a third acquisition unit, which is used to, after sending the real-time information reporting policy to the target smart device so that the target smart device reports the device information in accordance with the real-time information reporting policy, obtain the interaction data received by the target smart device in the process of reporting the device information in accordance with the real-time information reporting policy after determining that the time for the target smart device to report the device information in accordance with the real-time information reporting policy reaches a predetermined time; an adjustment unit, which is used to adjust the real-time information reporting policy according to the interaction data.

[0107] According to another aspect of an embodiment of the present invention, a processor is provided. The processor is configured to run a program, wherein the program executes any one of the above-mentioned methods for reporting device information when the program is running.

[0108] According to another aspect of an embodiment of the present invention, a computer program product is provided, including computer instructions, which, when executed by a processor, execute any one of the above-mentioned methods for reporting device information.

[0109] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored program, wherein the program executes any one of the above-mentioned methods for reporting device information.

[0110] Optionally, in this embodiment, the computer-readable storage medium may be located in any one of the computer terminals in a computer terminal group in a computer network, or in any one of the communication devices in a communication device group.

[0111] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: when determining that the target smart device performs a device information reporting operation according to an initial information reporting policy, obtaining actual device-related data of the target smart device, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device; adjusting the initial information reporting policy based on the actual device-related data to obtain a real-time information reporting policy; and sending the real-time information reporting policy to the target smart device so that the target smart device reports device information according to the real-time information reporting policy.

[0112] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: before determining that the target smart device performs a device information reporting operation according to an initial information reporting strategy, obtaining historical device-related data of the target smart device; analyzing and processing the historical device-related data through a prediction model to obtain an initial information reporting strategy, wherein the prediction model is a model obtained by machine learning training using multiple sets of training data, and each set of the multiple sets of training data includes: sample device-related data and a sample information reporting strategy corresponding to the sample device-related data.

[0113] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: obtaining user interaction data of the target smart device, wherein the user interaction data is operation data performed on the target smart device; obtaining device status data of the target smart device, wherein the device status data is used to record operating information of the target smart device; obtaining time data of the target smart device, wherein the time data is used to record the time when the target smart device performs various operations; and obtaining power usage data of the target smart device.

[0114] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining the current information reporting frequency of the target smart device based on actual device-related data; determining whether the target smart device is currently in a peak usage period based on historical device-related data, wherein the peak usage period indicates that the number of access devices to the target service platform exceeds the access device threshold, and the target service platform is the platform to which the target smart device accesses; when the current information reporting frequency is higher than the frequency threshold and the target smart device is currently in a peak usage period, adjusting the initial information reporting strategy to obtain a real-time information reporting strategy.

[0115] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: obtaining the data to be reported of the target smart device; classifying the data to be reported to obtain sub-data to be reported; determining the priority of each sub-data to be reported; adjusting the initial information reporting strategy according to the priority to obtain a real-time information reporting strategy.

[0116] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: determining high-priority data and low-priority data in each sub-data to be reported, wherein the high-priority data is the following data in the data to be reported: instruction execution result data, device online status data, and the low-priority data is log record data in the data to be reported; adjusting the initial information reporting strategy to: give priority to reporting high-priority data and reduce the reporting frequency of low-priority data.

[0117] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: compressing low-priority data to obtain a compressed data packet; and reporting the compressed data packet when the amount of low-priority data in the compressed data packet reaches a quantity threshold.

[0118] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: when it is determined that an abnormality occurs in the target smart device based on actual device-related data, obtaining abnormal data of the target smart device; and adjusting the initial information reporting strategy to: prioritize reporting abnormal data.

[0119] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for executing the following steps: after sending the real-time information reporting policy to the target smart device so that the target smart device reports device information in accordance with the real-time information reporting policy, after determining that the time for the target smart device to report device information in accordance with the real-time information reporting policy reaches a predetermined time, obtaining the interaction data received by the target smart device in the process of reporting device information in accordance with the real-time information reporting policy; and adjusting the real-time information reporting policy based on the interaction data.

[0120] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0121] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0122] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0123] The units described as separate components may or may not be physically separate, and 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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0124] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0125] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it 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 all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0126] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for reporting device information, characterized in that: include: When determining that the target smart device performs a device information reporting operation according to an initial information reporting policy, obtaining actual device-related data of the target smart device, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to the use of the target smart device; Adjusting the initial information reporting strategy according to the actual device-related data to obtain a real-time information reporting strategy; The real-time information reporting policy is issued to the target smart device, so that the target smart device reports device information according to the real-time information reporting policy.

2. The method for reporting device information according to claim 1, characterized in that: Before determining that the target smart device performs the device information reporting operation according to the initial information reporting policy, the following steps are also included: Acquire the historical device-related data of the target smart device; The historical device-related data is analyzed and processed through a prediction model to obtain the initial information reporting strategy, wherein the prediction model is a model obtained through machine learning training using multiple sets of training data, and each of the multiple sets of training data includes: sample device-related data and a sample information reporting strategy corresponding to the sample device-related data.

3. The method for reporting device information according to claim 2, characterized in that: Acquiring the historical device-related data of the target smart device includes at least one of the following: Acquire user interaction data of the target smart device, wherein the user interaction data is operation data performed on the target smart device; Acquire device status data of the target smart device, wherein the device status data is used to record operating information of the target smart device; Acquire time data of the target smart device, wherein the time data is used to record the time when the target smart device performs various operations; Obtain power usage data of the target smart device.

4. The method for reporting device information according to claim 1, wherein: The initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: Determine the current information reporting frequency of the target smart device according to the actual device-related data; determining, based on the historical device-related data, whether the target smart device is currently in a peak usage period, wherein the peak usage period indicates that the number of devices connected to a target service platform exceeds an access device threshold, and the target service platform is a platform connected by the target smart device; When the current information reporting frequency is higher than a frequency threshold and the target smart device is currently in the peak usage period, the initial information reporting strategy is adjusted to obtain the real-time information reporting strategy.

5. The method for reporting device information according to claim 1, wherein: The initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: Obtaining data to be reported by the target smart device; Classifying the data to be reported to obtain sub-data to be reported; Determining the priority of each of the sub-data to be reported; The initial information reporting strategy is adjusted according to the priority to obtain the real-time information reporting strategy.

6. The method for reporting device information according to claim 5, characterized in that: Adjusting the initial information reporting strategy according to the priority to obtain the real-time information reporting strategy includes: Determining high-priority data and low-priority data in each of the sub-data to be reported, wherein the high-priority data is the following data in the data to be reported: instruction execution result data, device online status data, and the low-priority data is log record data in the data to be reported; The initial information reporting strategy is adjusted to: give priority to reporting the high-priority data and reduce the reporting frequency of the low-priority data.

7. The method for reporting device information according to claim 6, characterized in that: Reducing the reporting frequency of the low-priority data includes: Compressing the low-priority data to obtain a compressed data packet; When the quantity of the low-priority data in the compressed data packet reaches a quantity threshold, the compressed data packet is reported.

8. The method for reporting device information according to claim 1, wherein: The initial information reporting strategy is adjusted according to the actual device-related data to obtain a real-time information reporting strategy, including: When it is determined according to the actual device-related data that the target smart device is abnormal, acquiring abnormal data of the target smart device; The initial information reporting strategy is adjusted to give priority to reporting the abnormal data.

9. The method for reporting device information according to any one of claims 1 to 8, characterized in that: After the real-time information reporting policy is issued to the target smart device so that the target smart device reports device information according to the real-time information reporting policy, the method further includes: After determining that a time duration for the target smart device to report the device information according to the real-time information reporting strategy reaches a predetermined time duration, acquiring interaction data received by the target smart device during the process of reporting the device information according to the real-time information reporting strategy; The real-time information reporting strategy is adjusted according to the interaction data.

10. A device for reporting device information, characterized in that: include: a first acquiring unit, configured to acquire actual device-related data of the target smart device when it is determined that the target smart device performs a device information reporting operation according to an initial information reporting policy, wherein the initial information reporting policy is a reporting policy determined based on historical device-related data of the target smart device, and the historical device-related data is data related to usage of the target smart device; an adjusting unit, configured to adjust the initial information reporting strategy according to the actual device-related data to obtain a real-time information reporting strategy; The reporting unit is configured to send the real-time information reporting policy to the target smart device, so that the target smart device reports device information according to the real-time information reporting policy.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium includes a stored program, wherein the program executes the device information reporting method according to any one of claims 1 to 9.

12. A processor, characterized in that: The processor is configured to run a program, wherein the program, when running, executes the method for reporting device information according to any one of claims 1 to 9.

13. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the device information reporting method according to any one of claims 1 to 9 is executed.

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