Method, device and equipment for monitoring power consumption of household electrical appliance and medium

Abstract

The embodiment of the invention belongs to the technical field of household appliances, and provides a method, device and equipment for monitoring power consumption of a household appliance and a medium. The method comprises the following steps: a cloud server can determine whether the household electrical appliance is disconnected in a current monitoring period; if yes, multiple first historical power consumption is obtained, and for any historical power consumption, the historical power consumption is determined according to the operation parameters of the refrigerator in the corresponding monitoring period. And inputting the plurality of first historical power consumptions into a first model to obtain a first power consumption of the current monitoring period, the first model being obtained by training according to a plurality of second historical power consumptions. And then the actual power consumption of the household appliance in the current preset period is determined based on the first power consumption. Therefore, the problem that the calculation of the actual power consumption generates a large deviation due to the loss of the operating parameters during the network disconnection period of the household electrical appliance is solved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of household appliance technology, and more specifically, to a method, apparatus, device, and medium for monitoring the power consumption of household appliances. Background Art

[0002] When using household appliances, users are usually more concerned about their power consumption. The power consumption of household appliances is usually the power consumption under standard operating conditions. For example, the standard operating conditions of a refrigerator are fixed environmental stability and humidity. However, there is a large gap between the actual power consumption of a refrigerator and the power consumption under standard operating conditions. Users are usually more concerned about the actual power consumption.

[0003] With the development of artificial intelligence, it is now possible to monitor the actual power consumption of household appliances using deep learning monitoring models, such as refrigerators. This monitoring model can be deployed on a cloud server, and the household appliances' networking capabilities can be used to report operating parameters to the cloud server, which can then calculate power consumption based on the monitoring model and operating parameters.

[0004] However, when home appliances are disconnected from the network, they are unable to upload their operating data during the disconnection period to the cloud server, resulting in data loss, which causes a large deviation in the calculation of the actual power consumption of home appliances. Summary of the Invention

[0005] The embodiments of the present application provide a method, device, equipment, and medium for monitoring the power consumption of household appliances, which can be used to solve the problem of large deviations in the calculation of actual power consumption caused by household appliances being disconnected from the Internet.

[0006] In a first aspect, an embodiment of the present application provides a method for monitoring power consumption of a household appliance, which is applied to a cloud server. The method includes:

[0007] Determining whether the household appliance is disconnected from the network during a current monitoring period;

[0008] If the household appliance is disconnected from the network during the current monitoring period, obtaining a plurality of first historical power consumptions;

[0009] Inputting the plurality of first historical power consumptions into a first model to obtain the first power consumption of the current monitoring period, wherein the first model is trained based on the plurality of second historical power consumptions;

[0010] saving the first power consumption;

[0011] Based on the first power consumption, actual power consumption of the household appliance in a current preset period is determined, wherein the current preset period includes the current monitoring period.

[0012] In this embodiment, the cloud server can determine whether the household appliance was disconnected from the internet during the current monitoring period. If so, multiple first historical power consumption records are obtained. For each historical power consumption record, the historical power consumption is determined based on the refrigerator's operating parameters during the corresponding monitoring period. These multiple first historical power consumption records are then input into a first model to obtain the first power consumption for the current monitoring period. The first model is trained based on multiple second historical power consumption records. The first power consumption records are saved and then used to determine the actual power consumption of the household appliance during the current preset period. This solves the problem of significant deviations in the calculation of actual power consumption due to loss of operating parameters during periods when the household appliance is disconnected from the internet.

[0013] In some embodiments of the present application, determining the actual power consumption of the household appliance in a current preset cycle based on the first power consumption includes:

[0014] If the current preset period is the current monitoring period, determining the first power consumption as the actual power consumption of the household appliance in the current preset period;

[0015] If the current preset cycle includes multiple monitoring cycles, multiple second power consumptions are obtained, and the actual power consumption of the household appliance within the current preset cycle is determined based on the multiple second power consumptions and the first power consumption; wherein the multiple second power consumptions are the power consumptions corresponding to the monitoring cycles in the multiple monitoring cycles except the current monitoring cycle.

[0016] In this embodiment, if the preset period includes one monitoring period, the power consumption of the current monitoring period can be determined as the actual power consumption within the preset period. If the preset period includes multiple monitoring periods, the actual power consumption within the preset period can be determined based on the power consumption of the multiple monitoring periods.

[0017] In some embodiments of the present application, determining whether the household appliance is disconnected from the network during the current monitoring period includes:

[0018] At the end of the current monitoring period, sending first information to the household appliance, where the first information is used to obtain operating parameters of the household appliance during the current monitoring period;

[0019] If the operating parameter is not received, determining that the household appliance is disconnected from the network during the current monitoring period;

[0020] If the operating parameters are received, it is determined that the household appliance is not disconnected from the network during the current monitoring period.

[0021] In this embodiment, at the end of each monitoring cycle, a first message can be sent to the household appliance to request the operating parameters of the household appliance during the monitoring cycle. If the operating parameters sent by the household appliance can be received, it can be determined that the network is not disconnected. If the operating parameters cannot be received, it can be determined that the household appliance is disconnected from the network.

[0022] In some embodiments of the present application, the method further includes:

[0023] If it is determined that the household appliance is not disconnected from the network during the current monitoring period, inputting the operating parameters of the household appliance during the current monitoring period into a second model to obtain a third power consumption during the current monitoring period, wherein the second model is trained based on multiple sets of historical operating parameters and the power consumption corresponding to each set of historical operating parameters;

[0024] saving the third power consumption;

[0025] Based on the third power consumption, actual power consumption of the household appliance in a current preset cycle is determined.

[0026] In this embodiment, if the household appliance is not disconnected from the network, the power consumption of the current monitoring period can be calculated based on the operating parameters and the second model, which can avoid the use of hardware structures such as smart sockets or electricity meters with power statistics functions to detect the power consumption of household appliances, thereby reducing the cost of household appliances.

[0027] In some embodiments of the present application, the method further includes:

[0028] Acquire first training data, where the first training data includes multiple sets of operating parameters and power consumption corresponding to each set of operating parameters, wherein the multiple sets of operating parameters include the operating parameters of the current monitoring period;

[0029] The second model is updated based on the first training data to obtain an updated second model, and the updated second model is used to predict the power consumption of the household appliance during a monitoring period when the household appliance is not disconnected from the network.

[0030] In this embodiment, the second model may be updated to improve the accuracy of the second model in determining power consumption.

[0031] In some embodiments of the present application, the method further includes:

[0032] Acquire second training data, where the second training data includes a plurality of second historical power consumptions and a plurality of first historical power consumptions;

[0033] The first model is updated based on the second training data to obtain an updated first model, and the updated first model is used to predict the power consumption of the household appliance during a monitoring period when the household appliance is disconnected from the network.

[0034] In this embodiment, the first model may be updated to improve the accuracy of the first model in determining power consumption.

[0035] In some embodiments of the present application, the method further includes:

[0036] The power information is sent to the user's terminal device and / or the household appliance, where the power information includes the actual power consumption of the household appliance in the current preset cycle and the time period corresponding to the actual power consumption.

[0037] In this embodiment, the actual power consumption of the household appliance is fed back to the user by sending power information to the terminal device.

[0038] In a second aspect, the present application provides a device for monitoring power consumption of a household appliance, comprising:

[0039] A first determining module, configured to determine whether the household appliance is disconnected from the network during a current monitoring period;

[0040] An acquisition module, configured to acquire a plurality of first historical power consumptions if the household appliance is disconnected from the network during the current monitoring period;

[0041] a prediction module, configured to input the plurality of first historical power consumptions into a first model to obtain the first power consumption of the current monitoring period, wherein the first model is trained based on the plurality of second historical power consumptions;

[0042] a storage module, configured to store the first power consumption;

[0043] The second determining module is configured to determine the actual power consumption of the household appliance within a current preset period based on the first power consumption, wherein the current preset period includes the current monitoring period.

[0044] The device provided in the embodiment of the present application can execute the technical solution in the above method embodiment, and its beneficial effects are similar, which will not be repeated here.

[0045] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0046] The memory stores computer-executable instructions;

[0047] The processor executes the computer-executable instructions stored in the memory to implement the method for monitoring power consumption of a household appliance as described in the first aspect.

[0048] The electronic device provided in the embodiment of the present application can execute the technical solutions in the above method embodiments, and its beneficial effects are similar, which will not be described in detail here.

[0049] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a computer, they are used to implement the method for monitoring the power consumption of a household appliance as described in the first aspect.

[0050] The computer-readable storage medium provided in the embodiment of the present application can execute the technical solutions in the above method embodiments, and its beneficial effects are similar and will not be repeated here.

[0051] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a computer, is used to implement the method for monitoring the power consumption of a household appliance described in the first aspect.

[0052] The computer program product provided in the embodiment of the present application can execute the technical solutions in the above method embodiments, and its beneficial effects are similar, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the implementation methods in the embodiments of the present application or related technologies, the following is a brief introduction to the drawings required for use in the embodiments or related technology descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0054] Figure 1 A schematic diagram of an application scenario applicable to this application;

[0055] Figure 2 A flowchart of a method for monitoring power consumption of a household appliance provided in an embodiment of the present application;

[0056] Figure 3 A schematic diagram of a monitoring cycle during operation of a household appliance according to an embodiment of the present application;

[0057] Figure 4 A flowchart of another method for monitoring power consumption of household appliances provided in an embodiment of the present application;

[0058] Figure 5 A flowchart of another method for monitoring power consumption of a household appliance provided in an embodiment of the present application;

[0059] Figure 6A flowchart of another method for monitoring power consumption of a household appliance provided in an embodiment of the present application;

[0060] Figure 7 A flowchart of another method for monitoring power consumption of a household appliance provided in an embodiment of the present application;

[0061] Figure 8 A flowchart of another method for monitoring power consumption of a household appliance provided in an embodiment of the present application;

[0062] Figure 9 A schematic diagram of the structure of a device for monitoring power consumption of household appliances provided in this application;

[0063] Figure 10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the purpose, implementation mode and advantages of the present application clearer, the exemplary implementation mode of the present application will be clearly and completely described below in conjunction with the drawings in the exemplary embodiments of the present application. Obviously, the described exemplary embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0065] It should be noted that the brief descriptions of terms in this application are only for the purpose of facilitating the understanding of the embodiments described below, and are not intended to limit the embodiments of this application. Unless otherwise specified, these terms should be understood according to their ordinary and usual meanings.

[0066] In addition, the terms "comprises" and "comprising" and any variations thereof are intended to cover but not exclude inclusion, for example, a product or device comprising a list of components is not necessarily limited to those components expressly listed but may include other components not expressly listed or inherent to such product or device.

[0067] Since there is a large gap between the actual power consumption of household appliances and the power consumption under standard working conditions, it is necessary to monitor the actual power consumption of household appliances and display it to users so that users can understand the actual power consumption and adjust the usage habits of household appliances in time to reduce energy consumption.

[0068] Currently, there are approaches to deploying monitoring models on refrigerators, replacing the energy metering module installed on the refrigerator to calculate power consumption. However, due to the high storage space and computing power requirements of monitoring models, the hardware resources of most refrigerators cannot meet these requirements.

[0069] The monitoring model can be deployed on a cloud server, and the networking function of the home appliances can be used to report operating parameters to the cloud server. The cloud server can input the received operating parameters into the monitoring model and output the power consumption.

[0070] However, if a household appliance is disconnected from the network for a certain period of time, it will be unable to upload the operating data during the disconnection period to the cloud server, resulting in data loss, which will cause a large deviation in the calculation of the actual power consumption of the household appliance.

[0071] Therefore, the present application provides a method for monitoring the power consumption of household appliances. If the household appliance is disconnected from the network during the current monitoring period, multiple first historical power consumptions can be input into a first model, so that the first model outputs the first power consumption of the current monitoring period. This solves the problem of inaccurate calculation of actual power consumption due to loss of operating parameters during the period when the household appliance is disconnected from the network.

[0072] For ease of understanding, the following Figure 1 The examples are used to illustrate the application scenarios to which the embodiments of the present application are applicable.

[0073] Figure 1 For a schematic diagram of an application scenario applicable to this application, please see Figure 1 , including: a cloud server 101, a home appliance 102 and a terminal device 103.

[0074] The cloud server 101, the household appliance 102 and the terminal device 103 can communicate with each other through the Internet. During the operation of the household appliance 102, the cloud server 101 can monitor the power consumption of the household appliance 102 in each monitoring cycle, and send power information to the household appliance 102 or the user's terminal device 103, so that the user can conveniently check the actual power consumption of the household appliance.

[0075] The cloud server 101 has a first model deployed therein, and stores therein multiple first historical power consumptions of the household appliance 102. If the household appliance 102 is disconnected from the network during the current monitoring period, the cloud server can determine the power consumption of the household appliance 102 during the current monitoring period based on the multiple first historical power consumptions and the first model deployed therein.

[0076] For example, the household appliance 101 may be a refrigerator, an air conditioner, a water heater or other appliances, which is not limited in this application.

[0077] The technical solution of the present application is described in detail below in conjunction with specific embodiments. The following specific embodiments can be combined with each other or exist independently. For the same or similar concepts or processes, some embodiments may not be described in detail. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0078] Figure 2 A flow chart of a method for monitoring the power consumption of household appliances provided in an embodiment of the present application, which can be executed by a cloud server, such as Figure 2 As shown, the method includes the following steps.

[0079] S201: Determine whether the household appliance is disconnected from the network during a current monitoring period.

[0080] After the home appliance is powered on and the networking function is configured, during the operation of the home appliance, the cloud server can determine whether the home appliance is disconnected from the network during the current monitoring period.

[0081] In a possible implementation, the cloud server may send first information to the home appliance, and then monitor whether the home appliance sends operating parameters to determine whether the home appliance is disconnected from the network.

[0082] Figure 3 This is a schematic diagram of a monitoring cycle during the operation of a household appliance according to an embodiment of the present application. Figure 3 As shown, the cloud server monitors the power consumption of household appliances according to the monitoring cycle in the following two ways:

[0083] Method 1

[0084] The cloud server can monitor the power consumption of household appliances according to a monitoring period. For example, the monitoring period can be 30 minutes, 1 hour, or other durations, and this application does not impose any restrictions on this. Taking a monitoring period of 1 hour as an example, the cloud server can collect statistics on the power consumption of household appliances in the last hour every 1 hour.

[0085] Method 2

[0086] The cloud server can monitor the power consumption of household appliances according to different monitoring cycles within different time periods. For example, a refrigerator is used more frequently (e.g., the number of times the door is opened) between 7:00 AM and 9:00 AM, and between 6:00 PM and 10:00 PM. For example, the monitoring cycle during these two time periods can be 30 minutes, while the monitoring cycle during other time periods can be 2 hours.

[0087] Specifically, the cloud server can determine the time period to which the current moment belongs, and then monitor the power consumption of household appliances according to the monitoring cycle corresponding to that time period. By monitoring the power consumption of household appliances in different time periods and according to different monitoring cycles, the cloud server can then compile statistics on the power consumption of household appliances in different time periods, providing users with the actual power consumption of household appliances in different time periods. This allows users to have a more detailed understanding of the power consumption of household appliances, allowing them to accurately adjust their usage habits of household appliances to reduce energy consumption.

[0088] S202: If the household appliance is disconnected from the network during the current monitoring period, obtain multiple first historical power consumptions.

[0089] If the household appliance is disconnected from the network during the current monitoring period, the cloud service area can obtain multiple first historical power consumptions in a preset memory.

[0090] In a possible implementation, the multiple first historical power consumptions may include predicted power consumption, where the predicted power consumption is the power consumption of a monitoring period before a current monitoring period determined by the cloud server based on a first model.

[0091] In one possible implementation, for any one of the multiple first historical power consumptions, the first historical power consumption can be determined based on the operating parameters of the household appliance in its corresponding monitoring period. By predicting the first power consumption of the current monitoring period through multiple first power consumptions, the accuracy can be further improved.

[0092] Illustratively, the multiple first historical power consumptions may be power consumptions of multiple monitoring periods determined according to operating parameters of the household appliance in a month before the current monitoring period.

[0093] S203: Input multiple first historical power consumptions into the first model to obtain the first power consumption of the current monitoring period.

[0094] The first model is obtained by training based on multiple second historical power consumptions.

[0095] Specifically, the cloud server may use the plurality of second historical power consumptions as training data, and input the training data into the first preset model for training to obtain the first model.

[0096] That is to say, the first model is trained in advance based on multiple second historical power consumptions.

[0097] In one possible implementation, the multiple second historical power consumptions do not include the multiple first historical power consumptions, the multiple first historical power consumptions are the power consumptions in the most recent time period before the current monitoring cycle, and the multiple second historical power consumptions may be the earlier power consumptions of the household appliances.

[0098] In one possible implementation, the multiple second historical power consumptions may be generated during a testing phase of the household appliance, where testers test the household appliance according to the user's home environment and usage habits. The hardware module then collects the household appliance's power consumption over multiple monitoring periods, and determines the multiple power consumptions as the multiple second historical power consumptions. For example, the hardware power consumption module may be a smart socket or an electric meter with power monitoring capabilities.

[0099] It can be understood that the training data may include a large amount of first historical power consumption, which can improve the accuracy of the first model.

[0100] S204: Save the first power consumption.

[0101] After obtaining the first power consumption, the first power consumption may be stored in a preset memory to facilitate subsequent statistics of actual power consumption within a preset period.

[0102] S205: Determine actual power consumption of the household appliance in a current preset period based on the first power consumption.

[0103] After obtaining the first power consumption, the cloud server can determine the actual power consumption of the household appliance in the current preset period based on the first power consumption. The cloud server can send the actual power consumption in the current preset period to the user's terminal device or household appliance, so that the user can understand the power consumption of the household appliance in the current preset period.

[0104] The current preset period includes the current monitoring period. That is, the preset period may include one or more monitoring periods. The cloud server may determine the actual power consumption of the household appliance within the current preset period based on the monitoring periods included in the preset period.

[0105] It can be understood that if the household appliance is still in an off-grid state in the next monitoring cycle of the current monitoring cycle, the first power consumption can be used as the historical power consumption in the next monitoring cycle for input into the first model to predict the power consumption of the next monitoring cycle.

[0106] In this embodiment, the cloud server can determine whether the household appliance was disconnected from the internet during the current monitoring period. If so, multiple first historical power consumption records are obtained. For each historical power consumption record, the historical power consumption is determined based on the refrigerator's operating parameters during the corresponding monitoring period. These multiple first historical power consumption records are then input into a first model to obtain the first power consumption for the current monitoring period. The first model is trained based on multiple second historical power consumption records. The first power consumption records are saved and then used to determine the actual power consumption of the household appliance during the current preset period. This solves the problem of significant deviations in the calculation of actual power consumption due to loss of operating parameters during periods when the household appliance is disconnected from the internet.

[0107] Figure 4 This is a flow chart of another method for monitoring the power consumption of household appliances provided in an embodiment of the present application. The method can be executed by a cloud server, such as Figure 4 As shown, the method includes the following steps.

[0108] S401: Determine whether the household appliance is disconnected from the network during the current monitoring period.

[0109] S402: If the household appliance is disconnected from the network during the current monitoring period, obtain multiple first historical power consumptions.

[0110] S403: Input multiple first historical power consumptions into the first model to obtain the first power consumption of the current monitoring period.

[0111] S404: Save the first power consumption.

[0112] For the detailed description of the above steps, please refer to the above embodiments and will not be repeated here.

[0113] S405: Determine whether the preset period includes multiple monitoring periods.

[0114] If the preset period includes multiple monitoring periods, step S406 is executed. It is understood that the multiple monitoring periods include the current monitoring period.

[0115] If the preset period includes a monitoring period, that is, the current preset period is the current monitoring period, then S408 is executed.

[0116] S406: Obtain multiple second power consumptions.

[0117] S407: Determine the actual power consumption of the household appliance in the current preset period according to the multiple second power consumptions and the first power consumption.

[0118] The multiple second power consumptions are power consumptions corresponding to monitoring periods other than the current monitoring period in the multiple monitoring periods.

[0119] In a possible implementation, the cloud server may add the multiple second power consumptions and the first power consumption to obtain the actual power consumption of the household appliance in the current preset cycle.

[0120] In one possible implementation, the cloud server may determine, for any one of the plurality of second power consumptions, the preset time period to which the monitoring period corresponding to the second power consumption belongs. The second power consumptions of the monitoring periods belonging to the same preset time period are summed to obtain the power consumption for each preset time period. The power consumption corresponding to each preset time period is then summed to obtain the actual power consumption.

[0121] The duration of each preset time period can be the same or different. For example, 7:00 AM to 9:00 AM is a time period, 6:00 PM to 10:00 PM is a time period, and the rest of the time is a time period. Alternatively, 12:00 AM to 8:00 AM is a time period, 8:00 AM to 4:00 PM is a time period, and 4:00 PM to 12:00 AM is a time period. This application does not impose any restrictions on this.

[0122] In this way, after the cloud server calculates the actual power consumption, when sending power information to the user's terminal device or household appliance, the power information can also include the power consumption of the household appliance in each preset time period.

[0123] S408: Determine the first power consumption as the actual power consumption of the household appliance in the current preset cycle.

[0124] In this embodiment, if the preset period includes one monitoring period, the power consumption of the current monitoring period can be determined as the actual power consumption within the preset period. If the preset period includes multiple monitoring periods, the actual power consumption within the preset period can be determined based on the power consumption of multiple monitoring periods.

[0125] In one possible implementation, after the cloud server determines the actual power consumption, it can send power information to the user's terminal device and / or household appliances. The power information includes the actual power consumption of the household appliances in the current preset cycle and the time period corresponding to the actual power consumption.

[0126] In one possible implementation, if the cloud server adds the second power consumption of monitoring cycles belonging to the same preset time period to obtain the power consumption for each preset time period, the power information may include the actual power consumption of the household appliance in the current preset period, the time period corresponding to the actual power consumption, and the power consumption of the household appliance in each preset time period.

[0127] Figure 5A flow chart of another method for monitoring the power consumption of household appliances provided in an embodiment of the present application is provided. The method can be executed by a cloud server, such as Figure 5 As shown, the method includes the following steps.

[0128] S501: Send first information to a household appliance at the end of a current monitoring period.

[0129] The first information is used to obtain operating parameters of the household appliance in the current monitoring period.

[0130] S502: If the operating parameters are not received, it is determined that the household appliance is disconnected from the network during the current monitoring period.

[0131] S503: If the operating parameters are received, determine that the household appliance is not disconnected from the network during the current monitoring period.

[0132] For example, after the cloud server sends the first information to the home appliance, if the operating parameters are not received within a preset time period, it can be determined that the home appliance is disconnected from the network during the current monitoring period. If the operating parameters are received, it can be determined that the home appliance is not disconnected from the network during the current monitoring period.

[0133] In one possible implementation, the preset duration can be based on the maximum duration for the cloud server to send the first information and receive the operating parameters sent by the household appliance, to avoid the cloud server failing to receive the operating parameters within the preset duration due to network transmission speed, thereby misjudging the household appliance as being disconnected from the network.

[0134] It is understandable that if the operating parameters sent by the household appliance are received, the operating parameters can be stored in a preset memory for subsequent determination of power consumption.

[0135] In this embodiment, at the end of each monitoring cycle, a first message can be sent to the household appliance to request the operating parameters of the household appliance during the monitoring cycle. If the operating parameters sent by the household appliance can be received, it can be determined that the network is not disconnected. If the operating parameters cannot be received, it can be determined that the household appliance is disconnected from the network.

[0136] If the household appliance is not disconnected from the network during the current monitoring period, the power consumption of the household appliance during the current monitoring period can be monitored in the following ways.

[0137] Figure 6 A flow chart of another method for monitoring the power consumption of household appliances provided in an embodiment of the present application is provided. The method can be executed by a cloud server, such as Figure 6 As shown, the method includes the following steps.

[0138] S601: Determine whether the household appliance is disconnected from the network during the current monitoring period.

[0139] S602: If the household appliance is not disconnected from the network during the current monitoring period, obtain operating parameters of the household appliance during the current monitoring period.

[0140] S603: Input multiple operating parameters into the second model to obtain a third power consumption in the current monitoring period.

[0141] The second model is obtained by training based on multiple groups of historical operating parameters and the power consumption corresponding to each group of historical operating parameters.

[0142] Specifically, the cloud server may use multiple groups of historical operating parameters and the power consumption corresponding to each group of historical operating parameters as training data, wherein each group of historical operating parameters may be used as an input feature and its corresponding power consumption as a label.

[0143] The training data is input into a second preset model for training to obtain a second model.

[0144] That is to say, the second model is trained in advance based on multiple groups of historical operating parameters and the power consumption corresponding to each group of historical operating parameters.

[0145] In one possible implementation, the training data can be obtained by controlling the operation of the household appliance during the testing phase according to the user's home environment and usage habits. The operator then obtains the operating parameters of the household appliance over multiple monitoring cycles, as well as the power consumption corresponding to each set of operating parameters. For example, the power consumption of the household appliance during each monitoring cycle can be collected through a hardware module. Exemplary hardware power consumption modules can be smart sockets or electric meters with power monitoring functions. The operating parameters over multiple monitoring cycles and the power consumption corresponding to each set of operating parameters are then used as training data for the second preset model.

[0146] Taking a household appliance as an example, the operating parameters may include the working power of each load, the operating time in the current monitoring period, the ambient temperature, the set temperature of the refrigerator, etc.

[0147] S604: Save the third power consumption.

[0148] S605: Determine the actual power consumption of the household appliance in the current preset cycle based on the third power consumption.

[0149] Regarding the cloud server determining the actual power consumption of the household appliance in the current preset period based on the third power consumption, reference can be made to the above embodiment in which the actual power consumption of the household appliance in the current preset period is determined based on the first power consumption, which will not be repeated here.

[0150] It can be understood that in the current monitoring period, the first power consumption of the household appliance when the network is disconnected and the third power consumption when the network is not disconnected are roughly the same, that is, the difference is small.

[0151] In this embodiment, if the household appliance is not disconnected from the network, the power consumption of the current monitoring period can be calculated based on the operating parameters and the second model, which can avoid the use of hardware structures such as smart sockets or electricity meters with power statistics functions to detect the power consumption of household appliances, thereby reducing the cost of household appliances.

[0152] Figure 7 A flow chart of another method for monitoring the power consumption of household appliances provided in an embodiment of the present application is provided. The method can be executed by a cloud server, such as Figure 7 As shown, the method includes the following steps.

[0153] S701: Acquire first training data, where the first training data includes multiple sets of operating parameters and power consumption corresponding to each set of operating parameters.

[0154] The multiple groups of operating parameters include the operating parameters of the current monitoring period.

[0155] S702: Update the second model according to the first training data to obtain an updated second model.

[0156] Exemplarily, the cloud server may update the second model at a preset time interval. Specifically, the cloud server may input the first training data into the second model, train the second model, and obtain an updated second model.

[0157] The updated second model is used to predict the power consumption of the household appliances during the monitoring period when the household appliances are not disconnected from the network.

[0158] In this embodiment, the second model may be updated to improve the accuracy of the second model in determining power consumption.

[0159] Figure 8 A flow chart of another method for monitoring the power consumption of household appliances provided in an embodiment of the present application is provided. The method can be executed by a cloud server, such as Figure 8 As shown, the method includes the following steps.

[0160] S801: Acquire second training data, where the second training data includes a plurality of second historical power consumptions and a plurality of first historical power consumptions.

[0161] S802: Update the first model according to the second training data to obtain an updated first model.

[0162] Exemplarily, the cloud server may update the first model at a preset time interval. Specifically, the cloud server may input the second training data into the first model to train the first model to obtain an updated first model.

[0163] The updated first model is used to predict the power consumption of the household appliances during the monitoring period when the network is disconnected.

[0164] In this embodiment, the first model may be updated to improve the accuracy of the first model in determining power consumption.

[0165] Figure 9 This is a schematic diagram of the structure of a device for monitoring the power consumption of household appliances provided in this application. Figure 9 As shown, the device 90 includes:

[0166] The first determining module 901 is configured to determine whether the household appliance is disconnected from the network during a current monitoring period.

[0167] The acquisition module 902 is configured to acquire a plurality of first historical power consumptions if the household appliance is disconnected from the network during the current monitoring period.

[0168] The prediction module 903 is used to input multiple first historical power consumptions into a first model to obtain the first power consumption of the current monitoring period, where the first model is trained based on multiple second historical power consumptions.

[0169] The storage module 904 is configured to store the first power consumption.

[0170] The second determining module 905 is configured to determine the actual power consumption of the household appliance within a preset period based on the first power consumption, wherein the current preset period includes a current monitoring period.

[0171] In a possible implementation, the second determining module 905 is specifically configured to:

[0172] If the current preset period is the current monitoring period, the first power consumption is determined as the actual power consumption of the household appliance in the current preset period.

[0173] If the current preset period includes multiple monitoring periods, multiple second power consumptions are obtained, and the actual power consumption of the household appliance in the current preset period is determined based on the multiple second power consumptions and the first power consumption. The multiple second power consumptions are power consumptions corresponding to monitoring periods other than the current monitoring period in the multiple monitoring periods.

[0174] In a possible implementation, the first determining module 901 is specifically configured to:

[0175] At the end of the current monitoring period, first information is sent to the household appliance, where the first information is used to obtain operating parameters of the household appliance in the current monitoring period.

[0176] If the operating parameters are not received, it is determined that the household appliance is disconnected from the network during the current monitoring period.

[0177] If the operating parameters are received, it is determined that the household appliance is not disconnected from the network during the current monitoring period.

[0178] In a possible implementation, the apparatus 90 further includes an online prediction module, which is configured to:

[0179] If it is determined that the household appliance is not disconnected from the network during the current monitoring period, the operating parameters of the household appliance during the current monitoring period are input into the second model to obtain the third power consumption of the current monitoring period, wherein the second model is trained based on multiple sets of historical operating parameters and the power consumption corresponding to each set of historical operating parameters.

[0180] Save the third power consumption.

[0181] Based on the third power consumption, actual power consumption of the household appliance in a current preset cycle is determined.

[0182] In a possible implementation, the apparatus 90 further includes a first training module, where the first training module is configured to:

[0183] First training data is obtained, where the first training data includes multiple sets of operating parameters and power consumption corresponding to each set of operating parameters, wherein the multiple sets of operating parameters include operating parameters of a current monitoring period.

[0184] The second model is updated based on the first training data to obtain an updated second model. The updated second model is used to predict the power consumption of the household appliance during a monitoring period when the household appliance is not disconnected from the network.

[0185] In a possible implementation, the apparatus 90 further includes a second training module, which is configured to:

[0186] Second training data is obtained, where the second training data includes a plurality of second historical power consumptions and a plurality of first historical power consumptions.

[0187] The first model is updated based on the second training data to obtain an updated first model. The updated first model is used to predict the power consumption of the household appliance during a monitoring period when the household appliance is disconnected from the network.

[0188] In a possible implementation, the apparatus 90 further includes a sending module, which is configured to:

[0189] The power information is sent to the user's terminal device and / or household appliances, where the power information includes the actual power consumption of the household appliances in the current preset cycle and the time period corresponding to the actual power consumption.

[0190] The device for monitoring the power consumption of household appliances provided in the embodiment of the present application can execute the method for monitoring the power consumption of household appliances in the above-mentioned method embodiment. Its implementation principle and technical effects are similar and will not be repeated here.

[0191] It should be noted that the above Figure 9 The division of the modules shown is only a schematic illustration, and this application does not limit the division of the modules and the naming of the modules.

[0192] Figure 10 This is a structural diagram of an electronic device provided in an embodiment of the present application. As shown in the figure, the electronic device 100 may include: at least one processor 1001 and a memory 1002.

[0193] The memory 1002 is used to store programs. Specifically, the programs may include program codes, and the program codes include computer operating instructions.

[0194] The memory 1002 may include a random access memory (RAM), and may also include a non-volatile memory (Non-volatile Memory), such as at least one disk memory.

[0195] The processor 1001 is configured to execute computer-executable instructions stored in the memory 1002 to implement the method described in the aforementioned method embodiment. The processor 1001 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0196] Optionally, the electronic device 100 may further include a communication interface 1003. In a specific implementation, if the communication interface 1003, the memory 1002, and the processor 1001 are implemented independently, the communication interface 1003, the memory 1002, and the processor 1001 may be interconnected via a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified as address buses, data buses, control buses, etc., but this does not mean that there is only one bus or only one type of bus.

[0197] Optionally, in a specific implementation, if the communication interface 1003, the memory 1002 and the processor 1001 are integrated on a chip, the communication interface 1003, the memory 1002 and the processor 1001 can complete communication through an internal interface.

[0198] The electronic device 100 may be a cloud server, etc.

[0199] The electronic device of this embodiment can be used to execute the technical solution shown in the above method embodiment. The specific implementation method and technical effects are similar and will not be repeated here.

[0200] The present application also provides a computer-readable storage medium, which may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a RAM, a disk or an optical disk, and other media that can store program codes. Specifically, the computer-readable storage medium stores computer execution instructions, which are used to implement the technical solution shown in the above method embodiment when executed by a computer.

[0201] The present application also provides a program product, which includes execution instructions stored in a readable storage medium. When the computer program is executed by a computer, the technical solution shown in the above method embodiment is executed. The specific implementation method and technical effect are similar and will not be repeated here.

[0202] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

[0203] For ease of explanation, the above description has been presented in conjunction with specific embodiments. However, the above exemplary discussion is not intended to be exhaustive or to limit the embodiments to the specific forms disclosed above. Based on the above teachings, various modifications and variations are possible. The above embodiments have been selected and described to better explain the principles and practical applications, thereby enabling those skilled in the art to better utilize the embodiments and various variations of the embodiments suitable for specific use considerations.

[0204] In this application, "and / or" is simply a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document indicates that the related objects are in an "or" relationship.

[0205] In the embodiments of this application, "multiple" refers to two or more. The first, second, and other descriptions that appear in the embodiments of this application are only for illustration and to distinguish the objects being described. They are not in any particular order and do not represent a specific limit on the number of devices in the embodiments of this application. They do not constitute any limitation on the embodiments of this application. For example, the first and second thresholds are only used to distinguish between different thresholds and do not indicate a difference in size, priority, or importance between the two thresholds.

[0206] Throughout this application, the terms "exemplary," "in some embodiments," and "in other embodiments" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described in this application as "exemplary" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of the word "exemplary" is intended to present concepts in a concrete manner.

[0207] In this application, “of”, “corresponding, relevant”, “corresponding” and “associated” may sometimes be used interchangeably. It should be noted that when the distinction between them is not emphasized, the meanings they intend to express are consistent.

[0208] The use of “based on” in the embodiments of the present application means openness and inclusiveness, because the process, step, calculation or other action “based on” one or more conditions or values ​​may be based on additional conditions or beyond the value in practice.

[0209] Descriptions such as "about," "approximately," or "approximately" that appear in the embodiments of this application include the stated value and an average value that is within an acceptable deviation range for the particular value, where the acceptable deviation range is as determined by a person of ordinary skill in the art taking into account the measurement in question and the errors associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

Claims

1. A method for monitoring the power consumption of household appliances, characterized in that: Applied to a cloud server, the method includes: Determining whether the household appliance is disconnected from the network during a current monitoring period; If the household appliance is disconnected from the network during the current monitoring period, obtaining a plurality of first historical power consumptions; Inputting the plurality of first historical power consumptions into a first model to obtain the first power consumption of the current monitoring period, wherein the first model is trained based on the plurality of second historical power consumptions; saving the first power consumption; Based on the first power consumption, actual power consumption of the household appliance in a current preset period is determined, wherein the current preset period includes the current monitoring period.

2. The method according to claim 1, characterized in that The determining, based on the first power consumption, actual power consumption of the household appliance in a current preset cycle includes: If the current preset period is the current monitoring period, determining the first power consumption as the actual power consumption of the household appliance in the current preset period; If the current preset cycle includes multiple monitoring cycles, multiple second power consumptions are obtained, and the actual power consumption of the household appliance within the current preset cycle is determined based on the multiple second power consumptions and the first power consumption; wherein the multiple second power consumptions are the power consumptions corresponding to the monitoring cycles in the multiple monitoring cycles except the current monitoring cycle.

3. The method according to claim 1 or 2, characterized in that The determining whether the household appliance is disconnected from the network during the current monitoring period includes: At the end of the current monitoring period, sending first information to the household appliance, where the first information is used to obtain operating parameters of the household appliance during the current monitoring period; If the operating parameter is not received, determining that the household appliance is disconnected from the network during the current monitoring period; If the operating parameters are received, it is determined that the household appliance is not disconnected from the network during the current monitoring period.

4. The method according to claim 1, wherein The method further comprises: If it is determined that the household appliance is not disconnected from the network during the current monitoring period, inputting the operating parameters of the household appliance during the current monitoring period into a second model to obtain a third power consumption during the current monitoring period, wherein the second model is trained based on multiple sets of historical operating parameters and the power consumption corresponding to each set of historical operating parameters; saving the third power consumption; Based on the third power consumption, actual power consumption of the household appliance in a current preset cycle is determined.

5. The method according to claim 4, characterized in that The method further comprises: Acquire first training data, where the first training data includes multiple sets of operating parameters and power consumption corresponding to each set of operating parameters, wherein the multiple sets of operating parameters include the operating parameters of the current monitoring period; The second model is updated based on the first training data to obtain an updated second model, and the updated second model is used to predict the power consumption of the household appliance during a monitoring period when the household appliance is not disconnected from the network.

6. The method according to claim 1, characterized in that The method further comprises: Acquire second training data, where the second training data includes a plurality of second historical power consumptions and a plurality of first historical power consumptions; The first model is updated based on the second training data to obtain an updated first model, and the updated first model is used to predict the power consumption of the household appliance during a monitoring period when the household appliance is disconnected from the network.

7. The method according to any one of claims 1 to 4, characterized in that The method further comprises: The power information is sent to the user's terminal device and / or the household appliance, where the power information includes the actual power consumption of the household appliance in the current preset cycle and the time period corresponding to the actual power consumption.

8. A device for monitoring the power consumption of household appliances, characterized in that: include: A first determining module, configured to determine whether the household appliance is disconnected from the network during a current monitoring period; An acquisition module, configured to acquire a plurality of first historical power consumptions if the household appliance is disconnected from the network during the current monitoring period; a prediction module, configured to input the plurality of first historical power consumptions into a first model to obtain the first power consumption of the current monitoring period, wherein the first model is trained based on the plurality of second historical power consumptions; a storage module, configured to store the first power consumption; The second determining module is configured to determine the actual power consumption of the household appliance within a current preset period based on the first power consumption, wherein the current preset period includes the current monitoring period.

9. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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