Temperature control method and device of gas water heater, electronic equipment and storage medium

Abstract

This application relates to the field of equipment control technology, and provides a temperature control method, device, electronic device, and storage medium for a gas water heater. The method includes: constructing a dataset for the gas water heater, the dataset including historical usage data and historical weather data corresponding to various historical usage time periods of the gas water heater; predicting water usage events for the gas water heater in future time periods based on the dataset; determining the set temperature of the gas water heater in the future time periods based on the predicted water usage events, and then controlling the temperature of the gas water heater based on the set temperature of the future time periods. This application predicts water usage events for the gas water heater in future time periods, determines the set temperature of the gas water heater based on the predicted water usage events, and then controls the heating of the gas water heater in advance based on the set temperature, allowing users to use hot water immediately without waiting, while also improving the heating efficiency of the gas water heater.

Description

Technical Field

[0001] This application relates to the field of equipment control technology, and in particular to temperature control methods, devices, electronic equipment and storage media for gas water heaters. Background Technology

[0002] Users' use of gas water heaters is cyclical and habitual, and is also affected by external ambient temperature, weekdays, and weekends. Traditional gas water heaters require preheating before use, causing many inconveniences for users. Furthermore, during use, the gas water heater heats according to the user's set temperature; if the user wants to change the water temperature, they need to manually reset it, resulting in low heating efficiency. Summary of the Invention

[0003] This application aims to at least solve one of the technical problems existing in the prior art. To this end, this application proposes a temperature control method for a gas water heater, which predicts water usage events of the gas water heater in various future time periods, determines the set temperature of the gas water heater based on the predicted water usage events, and then controls the gas water heater to heat in advance based on the set temperature, so that users can use hot water in time without waiting, while improving the heating efficiency of the gas water heater.

[0004] This application also discloses a temperature control device, electronic device, storage medium, and computer program product for a gas water heater.

[0005] The temperature control method for a gas water heater according to the first aspect of this application includes:

[0006] Construct a dataset for gas water heaters, which includes historical usage data and historical weather data corresponding to each historical usage period of the gas water heaters;

[0007] Based on the dataset, predict the water usage events of the gas water heater in future time periods;

[0008] Based on the water usage events in the future time periods, the set temperature of the gas water heater in the future time periods is determined, so as to control the temperature of the gas water heater based on the set temperature in the future time periods.

[0009] This application embodiment predicts water usage events of the gas water heater in various future time periods, determines the set temperature of the gas water heater based on the predicted water usage events, and then controls the gas water heater to heat in advance based on the set temperature, so that users can use hot water in time without waiting, while improving the heating efficiency of the gas water heater.

[0010] According to one embodiment of this application, determining the set temperature of the gas water heater for any future time period includes:

[0011] If the water usage event is a kitchen water usage event, then the set temperature of the gas water heater at any future time period is determined to be the first temperature;

[0012] If the water usage event is not a kitchen water usage event, then the set temperature of the gas water heater in any future time period is determined to be the second temperature;

[0013] Wherein, the kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is less than or equal to the set water use duration; the non-kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is greater than the set water use duration; and the first temperature is less than or equal to the second temperature.

[0014] According to one embodiment of this application, predicting water usage events of the gas water heater in future time periods based on the dataset includes:

[0015] The dataset is input into the prediction model to obtain the probability of water usage events of the gas water heater in various future time periods, as output by the prediction model.

[0016] Based on the probability of water usage events of the gas water heater in various future time periods, determine the water usage events of the gas water heater in various future time periods;

[0017] The prediction model is obtained by training on a sample set, which includes historical sample usage data and historical sample weather data corresponding to each historical sample usage time period of the gas water heater.

[0018] According to one embodiment of this application, after predicting water usage events of the gas water heater in future time periods based on the dataset, the method further includes:

[0019] Based on the dataset, predict the water consumption of the gas water heater in future time periods;

[0020] Based on the water usage events and water consumption of the gas water heater in future time periods, the set temperature of the gas water heater in future time periods is determined.

[0021] According to one embodiment of this application, the temperature control of the gas water heater based on the set temperatures for the future time periods includes:

[0022] Determine the time to send the temperature control command;

[0023] Based on the set temperatures for each future time period and the sending time, the temperature control command is sent to the gas water heater;

[0024] The gas water heater adjusts the water temperature based on the received temperature control command.

[0025] According to one embodiment of this application, determining the second temperature includes:

[0026] Obtain the set temperature of non-kitchen water use events for each historical usage period of the gas water heater;

[0027] The second temperature is determined based on the set temperature of non-kitchen water use events during various historical usage periods.

[0028] According to one embodiment of this application, the construction of the dataset for gas water heaters includes:

[0029] Determine the usage time of the gas water heater;

[0030] If the usage duration is greater than or equal to the set duration, historical usage data and historical weather data corresponding to each historical usage time period of the gas water heater are collected to construct the dataset of the gas water heater.

[0031] The temperature control device for a gas water heater according to a second aspect embodiment of this application includes:

[0032] A dataset construction module is used to construct a dataset for the gas water heater, which includes historical usage data and historical weather data corresponding to each historical usage period of the gas water heater.

[0033] The prediction module is used to predict water usage events of the gas water heater in future time periods based on the dataset.

[0034] The temperature control module is used to determine the set temperature of the gas water heater for each future time period based on the water usage events in each future time period, so as to perform temperature control on the gas water heater based on the set temperature for each future time period.

[0035] An electronic device according to a third aspect of this application includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the temperature control method of any of the above-described gas water heaters.

[0036] A non-transitory computer-readable storage medium according to a fourth aspect of this application stores a computer program thereon, which, when executed by a processor, implements the temperature control method for a gas water heater as described above.

[0037] The above-described one or more technical solutions in the embodiments of this application have at least one of the following technical effects:

[0038] Users can use hot water immediately without waiting, while also improving the heating efficiency of gas water heaters.

[0039] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is one of the flowcharts illustrating the temperature control method for a gas water heater provided in the embodiments of this application;

[0042] Figure 2 This is a second schematic flowchart of the temperature control method for a gas water heater provided in the embodiments of this application;

[0043] Figure 3 This is a schematic diagram of the temperature control device of the gas water heater provided in the embodiments of this application;

[0044] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0045] The embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but should not be used to limit the scope of this application.

[0046] In the description of the embodiments of this application, it should be noted that the terms "first", "second" and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0047] In the embodiments of this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0048] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0049] Figure 1 This is one of the flowcharts illustrating the temperature control method for a gas water heater provided in this application. (Refer to...) Figure 1 This application provides a temperature control method for a gas water heater, including:

[0050] Step 100: Construct a dataset for the gas water heater, which includes historical usage data and historical weather data corresponding to each historical usage period of the gas water heater;

[0051] Historical usage data and historical weather data corresponding to various historical usage periods of the gas water heater are collected, and then a dataset of the gas water heater is constructed based on the collected data. The historical usage period can refer to different time periods within a day, such as 8:00-9:00, 10:00-11:00, 12:00-13:00; or different time periods within a week, such as Monday, Tuesday, Wednesday, etc.

[0052] For example, (1) Select the historical usage data reported by the gas water heater in the most recent year, and obtain the gas water heater's identification information (such as device ID), the city identification information (such as city ID) of the city where the gas water heater is located, the data reporting date, the water consumption per hour, and the set temperature for each heating based on the historical usage data. For each hour, if a water consumption event lasting more than 3 minutes occurs within that hour, the [Kitchen Water Consumption Event] field is set to 1; otherwise, it is set to 0. The processed data is shown in the table below:

[0053] Device ID City ID date Hour Is it a kitchen water incident?

[0054] It should be noted that, in this embodiment of the application, a kitchen water use event is defined as a continuous water use duration of less than or equal to 3 minutes, i.e., a temporary water use event, such as washing hands, washing vegetables and fruits, or washing dishes; a non-kitchen water use event is defined as a continuous water use duration of more than 3 minutes, such as washing up or taking a shower. The continuous water use duration corresponding to a kitchen water use event can be determined based on water demand and is not limited here.

[0055] Optionally, kitchen water use events can also be defined based on the continuous water use duration and water consumption of the gas water heater.

[0056] (2) Collect historical weather data for the area where the water heater is located for the past year. Based on this historical weather data, determine the highest and lowest temperatures for each day in history. Compare the temperature rise of the highest temperature the previous day with the temperature rise of the lowest temperature the previous day, and generate the following data table based on this information:

[0057]

[0058] (3) Collect the historical usage time period of the gas water heater over the past year, perform feature processing on the date data corresponding to the historical usage time period, and generate the following data table:

[0059]

[0060]

[0061]

[0062] (4) Integrate the data generated in steps (1)-(3) to generate the following data table:

[0063]

[0064]

[0065]

[0066] Based on the historical usage data and historical weather data of gas water heaters for various historical usage periods integrated in the table above, a dataset of gas water heaters is constructed.

[0067] Optionally, to improve the prediction accuracy of the prediction model, when constructing the dataset, it is necessary to determine the usage duration of the gas water heater. If the usage duration is greater than or equal to the set duration, historical usage data and historical weather data corresponding to each historical usage time period of the gas water heater are collected to construct the gas water heater dataset.

[0068] For example, assuming a usage period of 14 days, for water heaters used for less than 14 days, their corresponding historical data is directly filtered out and not included in the model construction; for water heaters used for 14 days or more, their historical data is collected to construct a dataset for the water heaters. Based on this, the prediction accuracy of the predictive model is improved, thereby improving the accuracy of the water heater temperature setting.

[0069] Step 200: Based on the dataset, predict the water usage events of the gas water heater in future time periods;

[0070] It should be noted that the prediction model is obtained by training on a sample set, which includes historical usage data and historical weather data corresponding to various historical usage time periods of the water heater. For example, the training steps for the prediction model are as follows:

[0071] (1) Collect historical sample usage data and historical sample weather data corresponding to each historical sample usage time period of the gas water heater to construct a sample set;

[0072] (2) For gas water heaters that have been used for less than 14 days, their corresponding sample data are directly filtered out and not included in the model construction.

[0073] (3) For records where the number of hours with a water usage event in the previous 48, 72, 96, 120, 144, and 168 hours is 0, the prediction value is set to 1, that is, the hour belongs to the kitchen water usage event;

[0074] (4) For records where the number of hours with a water usage event is greater than 0 in the previous 48, 72, 96, 120, 144, and 168 hours, a prediction model is constructed using a sample set and the Light GBM (Light Gradient Boosting Machine) algorithm. The objective variable of the prediction model is whether the hour belongs to a kitchen water usage event.

[0075] LightGBM is a gradient boosting framework that uses decision trees as base learners and employs the negative gradient of the loss function as an approximation of the residual of the current decision tree to fit a new decision tree. LightGBM has the following main advantages: high training efficiency; low memory usage, reducing the performance requirements of the training server for large amounts of prediction data related to a single long-term water usage event; and high accuracy.

[0076] After constructing the dataset, the dataset is input into a pre-trained prediction model to obtain the probability of water usage events of the gas water heater in each future time period. Then, based on the probability of water usage events of the gas water heater in each future time period, the water usage events of the gas water heater in each future time period are determined.

[0077] For example, the prediction model outputs a probability value. If the output probability value is greater than or equal to 0.765, it is judged as a kitchen water use event. In this case, the prediction model misclassifies the actual water use event as a kitchen water use event in 5% of all actual water use events. If the output probability value is less than 0.765, it is judged as a non-kitchen water use event. In this case, the prediction model misclassifies the actual water use event as a kitchen water use event in 5% of all actual water use events.

[0078] Step 300: Based on the water usage events in the future time periods, determine the set temperature of the gas water heater in the future time periods, and perform temperature control on the gas water heater based on the set temperature in the future time periods.

[0079] Different water usage events correspond to different set temperatures. After determining the water usage events for each future time period, the set temperature for the gas water heater is determined based on these events, and then the water heater's temperature is controlled accordingly. For example, assuming the water usage event from 12:00 to 13:00 the next day is a kitchen water usage event, then the set temperature for 12:00 to 13:00 would be 37℃.

[0080] To ensure users have hot water available between 12:00 and 13:00 the following day, the gas water heater needs to be pre-controlled. Specifically, the time for sending temperature control commands is determined. Based on the set temperatures for future time periods and the sending time, temperature control commands are sent to the gas water heater. The gas water heater then adjusts the water temperature based on the received commands. For example, if a temperature control command containing the set temperature is sent to the gas water heater at 11:58 the following day, the gas water heater will adjust its heating based on the device's set temperature, thus achieving temperature control.

[0081] The temperature control method for gas water heaters provided in this application involves constructing a dataset for the gas water heater, including historical usage data and historical weather data corresponding to various historical usage periods. Based on the dataset, the method predicts water usage events for the gas water heater in future time periods. Based on these future water usage events, the method determines the set temperature for the gas water heater in each future time period, and then controls the temperature of the gas water heater based on these set temperatures. This application predicts water usage events for the gas water heater in future time periods, determines the set temperature based on the predicted events, and then controls the heating of the gas water heater in advance based on this set temperature. This allows users to use hot water immediately without waiting, while also improving the heating efficiency of the gas water heater.

[0082] Based on the above embodiments, determining the set temperature of the gas water heater at any future time period includes:

[0083] Step 301: If the water usage event is a kitchen water usage event, then determine the set temperature of the gas water heater for any future time period as the first temperature;

[0084] Step 302: If the water usage event is not a kitchen water usage event, then determine the set temperature of the gas water heater for any future time period as the second temperature;

[0085] It should be noted that kitchen water use events are used to characterize water use events where the continuous water use duration of the gas water heater is less than or equal to the set water use duration (e.g., 3 minutes); non-kitchen water use events are used to characterize water use events where the continuous water use duration of the gas water heater is greater than the set water use duration (e.g., 3 minutes).

[0086] The first temperature is less than or equal to the second temperature. The first temperature can be the lowest temperature set by the gas water heater, such as 37°C, or a relatively low temperature, such as 40°C. The second temperature can be the user's preferred temperature, which can be determined based on historical temperature settings. Specifically, the set temperatures for non-kitchen water use events during various historical usage periods of the gas water heater are obtained, and then the second temperature is determined based on these historical non-kitchen water use event set temperatures. Based on this, the user's previous settings for the second temperature can be obtained, thereby determining the user's preferred temperature, improving the accuracy of the second temperature determination, and enhancing the user experience.

[0087] If the water usage event is a kitchen water usage event, then the set temperature of the gas water heater for any future time period is determined to be the first temperature, such as 37℃; if the water usage event is not a kitchen water usage event, then the set temperature of the gas water heater for any future time period is determined to be the second temperature, such as 60℃.

[0088] This application predicts water usage events for a gas water heater in various future time periods and determines the set temperature of the gas water heater based on the predicted water usage events, so that users can use hot water immediately without waiting, while also improving the heating efficiency of the gas water heater.

[0089] Based on the above embodiments, after predicting the water usage events of the gas water heater in future time periods based on the dataset, the method further includes:

[0090] Step 400: Based on the dataset, predict the water consumption of the gas water heater in future time periods;

[0091] Step 500: Based on the water usage events and water consumption of the gas water heater in future time periods, determine the set temperature of the gas water heater in future time periods.

[0092] After collecting the dataset, it is input into the water consumption prediction model to obtain the water consumption of the gas water heater in various future time periods. Then, based on the water consumption events and water usage in these future time periods, the set temperature of the gas water heater for each period is determined. For example, assuming the predicted water consumption of the gas water heater is 80L between 21:00 and 22:00 the next day, with a usage duration of 20 minutes, this can be identified as a non-kitchen water consumption event and a high-volume water consumption event, indicating that the user is taking a shower during this time. In this case, the temperature can be set to 75℃.

[0093] The water consumption prediction model was trained using a sample set, which included historical usage data and historical weather data corresponding to various historical usage periods of gas water heaters.

[0094] This application embodiment predicts the water usage events and water consumption of the gas water heater in future time periods, and determines the set temperature of the gas water heater based on the predicted water usage events and water consumption, so that users can use hot water in time without waiting, while improving the heating efficiency of the gas water heater.

[0095] refer to Figure 2 , Figure 2 This is the second schematic flowchart of the temperature control method for a gas water heater provided in the embodiments of this application.

[0096] In this embodiment of the application, historical usage data and historical weather data corresponding to each historical usage period of the gas water heater are collected, and then feature processing is performed on the collected data, and a dataset of the gas water heater is constructed based on the feature-processed data.

[0097] The LigthGBM model is built based on the dataset. For example, to improve the accuracy of model training, data on water heater usage time of less than 14 days (such as usage time period, usage data, and weather data) are directly filtered out and not included in the model construction. For records where the number of hours with a kitchen water usage event in the previous 48, 72, 96, 120, 144, and 168 hours is 0, the predicted value is directly set to 0 (i.e., there was no kitchen water usage event in that hour). For records where the number of hours with a non-kitchen water usage event in the previous 48, 72, 96, 120, 144, and 168 hours is greater than 0, the LigthGBM model is built using the dataset.

[0098] The LigthGBM model is used to predict the probability of kitchen water use events for each hour of the next day. If the output probability value is greater than or equal to 0.765, it is judged as a kitchen water use event, and the water heater temperature is set to the lowest temperature, such as 37℃. If the output probability value is less than 0.765, it is judged as a non-kitchen water use event, and the water heater temperature is set to the user's preferred temperature, such as 60℃.

[0099] After determining the water usage events and set temperatures for each hour of the coming day, a recommendation result table is determined based on the water usage events and set temperatures for each hour. This table enables the terminal to send temperature control commands to the gas water heater based on the recommendation result table, for example, sending control commands to the gas water heater according to the time points in the recommendation result table.

[0100] In one specific embodiment, the steps of predicting the water usage events for each gas water heater every hour on the next day, determining the set temperature corresponding to the water usage events, and then implementing temperature control of the gas water heater based on the set temperature are as follows:

[0101] (1) Select historical data of gas water heaters from the past 14 days, combine them with weather data and data from each usage period, and generate corresponding data tables. The data tables include features such as whether there were water usage events and actual water consumption within that hour. Use the dataset composed of the data tables to train the prediction model.

[0102] (2) Calculate the number of days each gas water heater has been used, and define a learning period flag. For gas water heaters that have been used for 14 days or more, the learning period flag is set to 1; otherwise, it is set to 0. For gas water heaters with a learning period flag of 1, the constructed model is used to predict water usage for each hour of the next day, generating the recommended data in the table below:

[0103]

[0104] (3) Based on the recommended data, temperature control commands are issued to each gas water heater at specific times to achieve temperature control of the gas water heater.

[0105] This application's embodiments predict a user's water usage behavior for the next day by using historical 14-day data on gas water heater usage, weather data, and usage time periods. Based on the prediction results, the gas water heater's temperature is set in advance, one hour before the user's water usage event. This allows for advance prediction of water usage events, enabling the gas water heater to be started in advance to heat water for the user, allowing the user to use hot water immediately without waiting, while also improving the heating efficiency of the gas water heater.

[0106] The temperature control device for a gas water heater provided in the embodiments of this application is described below. The temperature control device for a gas water heater described below can be referred to in correspondence with the temperature control method for a gas water heater described above.

[0107] refer to Figure 3 , Figure 3 This is a schematic diagram of the temperature control device for a gas water heater provided in an embodiment of this application. The temperature control device for a gas water heater in this application includes a dataset construction module 310, a prediction module 320, and a temperature control module 330.

[0108] Data set construction module 310 is used to construct a dataset of the gas water heater, the dataset including historical usage data and historical weather data corresponding to each historical usage period of the gas water heater;

[0109] Prediction module 320 is used to predict water usage events of the gas water heater in future time periods based on the dataset;

[0110] Temperature control module 330 is used to determine the set temperature of the gas water heater in the future time period based on the water usage events in the future time period, so as to perform temperature control on the gas water heater based on the set temperature in the future time period.

[0111] The temperature control device for a gas water heater provided in this application constructs a dataset for the gas water heater, which includes historical usage data and historical weather data corresponding to various historical usage time periods of the gas water heater. Based on the dataset, it predicts water usage events for the gas water heater in future time periods. Based on the water usage events in these future time periods, it determines the set temperature for the gas water heater in these future time periods, and then controls the temperature of the gas water heater based on these set temperatures. This application predicts water usage events for the gas water heater in future time periods, determines the set temperature based on the predicted water usage events, and then controls the gas water heater to heat in advance based on the set temperature, allowing users to use hot water immediately without waiting, while also improving the heating efficiency of the gas water heater.

[0112] In one embodiment, the temperature control module 330 specifically includes:

[0113] If the water usage event is a kitchen water usage event, then the set temperature of the gas water heater at any future time period is determined to be the first temperature;

[0114] If the water usage event is not a kitchen water usage event, then the set temperature of the gas water heater in any future time period is determined to be the second temperature;

[0115] Wherein, the kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is less than or equal to the set water use duration; the non-kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is greater than the set water use duration; and the first temperature is less than or equal to the second temperature.

[0116] In one embodiment, the prediction module 320 specifically includes:

[0117] The dataset is input into the prediction model to obtain the probability of water usage events of the gas water heater in various future time periods, as output by the prediction model.

[0118] Based on the probability of water usage events of the gas water heater in various future time periods, determine the water usage events of the gas water heater in various future time periods;

[0119] The prediction model is obtained by training on a sample set, which includes historical sample usage data and historical sample weather data corresponding to each historical sample usage time period of the gas water heater.

[0120] In one embodiment, the prediction module 320 further includes:

[0121] Based on the dataset, predict the water consumption of the gas water heater in future time periods;

[0122] Based on the water usage events and water consumption of the gas water heater in future time periods, the set temperature of the gas water heater in future time periods is determined.

[0123] In one embodiment, the temperature control module 330 specifically includes:

[0124] Determine the time to send the temperature control command;

[0125] Based on the set temperatures for each future time period and the sending time, the temperature control command is sent to the gas water heater;

[0126] The gas water heater adjusts the water temperature based on the received temperature control command.

[0127] In one embodiment, the temperature control module 330 further includes:

[0128] Obtain the set temperature of non-kitchen water use events for each historical usage period of the gas water heater;

[0129] The second temperature is determined based on the set temperature of non-kitchen water use events during various historical usage periods.

[0130] In one embodiment, the dataset construction module 310 specifically includes:

[0131] Determine the usage time of the gas water heater;

[0132] If the usage duration is greater than or equal to the set duration, historical usage data and historical weather data corresponding to each historical usage time period of the gas water heater are collected to construct the dataset of the gas water heater.

[0133] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include a processor 410, a communications interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute the following methods:

[0134] Construct a dataset for gas water heaters, which includes historical usage data and historical weather data corresponding to each historical usage period of the gas water heaters;

[0135] Based on the dataset, predict the water usage events of the gas water heater in future time periods;

[0136] Based on the water usage events in the future time periods, the set temperature of the gas water heater in the future time periods is determined, so as to control the temperature of the gas water heater based on the set temperature in the future time periods.

[0137] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0138] On the other hand, embodiments of this application also provide a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the temperature control method for the gas water heater provided in the above embodiments, for example including:

[0139] Construct a dataset for gas water heaters, which includes historical usage data and historical weather data corresponding to each historical usage period of the gas water heaters;

[0140] Based on the dataset, predict the water usage events of the gas water heater in future time periods;

[0141] Based on the water usage events in the future time periods, the set temperature of the gas water heater in the future time periods is determined, so as to control the temperature of the gas water heater based on the set temperature in the future time periods.

[0142] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0143] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

[0145] The above embodiments are for illustrative purposes only and are not intended to limit the scope of this application. Although this application has been described in detail with reference to the embodiments, those skilled in the art should understand that various combinations, modifications, or equivalent substitutions of the technical solutions of this application do not depart from the spirit and scope of the technical solutions of this application and should be covered within the scope of the claims of this application.

Claims

1. A temperature control method for a gas water heater, characterized in that, include: A dataset for a gas water heater is constructed, comprising historical usage data and historical weather data corresponding to various historical usage periods of the gas water heater. The historical usage data includes at least one of the following features: date information corresponding to the historical usage period, whether it is a rest day, the time interval with the most recent workday or rest day, water usage during the same hour of the same historical workday or rest day, and water usage statistics for multiple preset historical time points prior to the current moment. The historical weather data includes temperature information and temperature change range information for the historical usage period. Based on the dataset, predict the water usage events of the gas water heater in future time periods; Based on the water usage events in the future time periods, the set temperature of the gas water heater in the future time periods is determined, so as to control the temperature of the gas water heater based on the set temperature in the future time periods. Determining the set temperature of the gas water heater at any future time period includes: If the water usage event is a kitchen water usage event, then the set temperature of the gas water heater at any future time period is determined to be the first temperature; If the water usage event is not a kitchen water usage event, then the set temperature of the gas water heater in any future time period is determined to be the second temperature; Wherein, the kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is less than or equal to the set water use duration; the non-kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is greater than the set water use duration; the first temperature is less than or equal to the second temperature, the first temperature is a preset fixed low temperature value, and the second temperature is determined statistically based on the set temperature of the non-kitchen water use events in various historical usage time periods of the gas water heater.

2. The temperature control method for a gas water heater according to claim 1, characterized in that, The prediction of water usage events for the gas water heater in future time periods based on the dataset includes: The dataset is input into the prediction model to obtain the probability of water usage events of the gas water heater in various future time periods, as output by the prediction model. Based on the probability of water usage events of the gas water heater in various future time periods, determine the water usage events of the gas water heater in various future time periods; The prediction model is obtained by training on a sample set, which includes historical sample usage data and historical sample weather data corresponding to each historical sample usage time period of the gas water heater.

3. The temperature control method for a gas water heater according to claim 1, characterized in that, After predicting water usage events of the gas water heater in future time periods based on the dataset, the method further includes: Based on the dataset, predict the water consumption of the gas water heater in future time periods; Based on the water usage events and water consumption of the gas water heater in future time periods, the set temperature of the gas water heater in future time periods is determined.

4. The temperature control method for a gas water heater according to claim 1, characterized in that, The temperature control of the gas water heater based on the set temperatures for each future time period includes: Determine the time to send the temperature control command; Based on the set temperatures for each future time period and the sending time, the temperature control command is sent to the gas water heater; The gas water heater adjusts the water temperature based on the received temperature control command.

5. The temperature control method for a gas water heater according to claim 1, characterized in that, The dataset for constructing gas water heaters includes: Determine the usage time of the gas water heater; If the usage duration is greater than or equal to the set duration, historical usage data and historical weather data corresponding to each historical usage time period of the gas water heater are collected to construct the dataset of the gas water heater.

6. A temperature control device for a gas water heater, characterized in that, include: A dataset construction module is used to construct a dataset for the gas water heater. The dataset includes historical usage data and historical weather data corresponding to various historical usage time periods of the gas water heater. The historical usage data includes at least one of the following features: date information corresponding to the historical usage time period, whether it is a rest day, the time interval with the most recent workday or rest day, water usage in the same hour of the same historical workday or rest day, and water usage statistics for multiple preset historical time points before the current moment. The historical weather data includes temperature information and temperature change range information for the historical usage time period. The prediction module is used to predict water usage events of the gas water heater in future time periods based on the dataset. A temperature control module is used to determine the set temperature of the gas water heater in the future time period based on the water usage events in the future time period, so as to control the temperature of the gas water heater based on the set temperature in the future time period. The temperature control module is also used to determine the set temperature of the gas water heater at any future time period as the first temperature if the water use event is a kitchen water use event. If the water usage event is not a kitchen water usage event, then the set temperature of the gas water heater in any future time period is determined to be the second temperature; The kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is less than or equal to the set water use duration; the non-kitchen water use event is used to characterize a water use event in which the continuous water use duration of the gas water heater is greater than the set water use duration. The first temperature is less than or equal to the second temperature. The first temperature is a preset fixed low temperature value, and the second temperature is determined based on the set temperature statistics of non-kitchen water use events in various historical usage periods of the gas water heater.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the temperature control method for a gas water heater as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the temperature control method for a gas water heater as described in any one of claims 1 to 5.

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