Control method of kitchen equipment

Abstract

The invention relates to the technical field of smart home, and discloses a kitchen equipment control method, which comprises the steps of predicting tableware use time based on historical operation data of a range hood or a kitchen range to obtain predicted tableware use time; if the time difference between the current moment and the predicted tableware use time is smaller than the preset duration, the kitchen equipment is controlled to start working. According to the method, the use time of the tableware can be predicted by analyzing the historical operation data of the range hood or the kitchen range, so that the kitchen equipment is automatically started to start disinfection work at a certain moment, manual operation and appointment are not needed, the automation degree is improved, and the use experience of a user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart home, and in particular to a control method for kitchen equipment. Background Art

[0002] Existing household kitchen equipment such as dishwashers and disinfection cabinets usually have the function of disinfecting tableware, which has brought convenience and hygiene to modern families to a great extent. However, when using them, they usually need to be manually turned on or timed to control their operation. Not only can they not fully meet the personalized needs and usage habits of users, but they are also prone to forgetfulness or negligence, resulting in untimely disinfection of tableware and kitchen utensils, which in turn leads to the fact that there are no disinfected tableware available when tableware is needed, causing many inconveniences. Summary of the invention

[0003] The first technical problem solved by the present invention is to provide a control method for kitchen equipment, which effectively solves the problem that there are no sterilized tableware available when tableware is needed.

[0004] The first technical problem mentioned above is solved by the following technical solution:

[0005] A method for controlling a kitchen device, wherein the kitchen device is used to store tableware and has a tableware disinfection function, the method comprising:

[0006] Predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time;

[0007] If the time difference between the current moment and the predicted tableware usage time is less than a preset time length, the kitchen device is controlled to start working.

[0008] Compared with the background technology, the control method of the kitchen equipment described in the present invention has the following beneficial effects: the method provided in the embodiment of the present invention can predict the usage time of tableware by analyzing the historical operation data of the range hood or stove, so as to automatically start the kitchen equipment to start disinfection at a certain time without manual operation or appointment, thereby improving the degree of automation and enhancing the user experience.

[0009] In one embodiment, the kitchen device further includes a dishwashing function, and the step of controlling the kitchen device to start working includes:

[0010] Get the degree of dirtiness of the dishes stored in the kitchen equipment;

[0011] If the dirtiness level does not exceed a first preset dirtiness level, controlling the kitchen device to start the disinfection function;

[0012] If the dirtiness level exceeds a first preset dirtiness level, the kitchen device is controlled to start the dishwashing function.

[0013] In one embodiment, before obtaining the degree of dirtiness of tableware stored in the kitchen equipment, the method further includes:

[0014] Get the current status of the kitchen equipment;

[0015] If the current state is the standby state, obtaining the degree of dirtiness of the tableware stored in the kitchen equipment;

[0016] If the current state is a working state, the current state is maintained for operation.

[0017] In one embodiment, the dishwashing function of the kitchen device includes a normal washing mode and a quick washing mode, the washing time of the quick washing mode is shorter than the washing time of the normal washing mode, the amount of detergent used in the quick washing mode is greater than the amount of detergent used in the normal washing mode, and / or the flushing force of the quick washing mode is greater than the flushing force of the normal washing mode; the controlling the kitchen device to start the dishwashing function includes:

[0018] The kitchen device is controlled to select a quick cleaning mode to clean the dishes.

[0019] In one embodiment, the kitchen device further includes a tableware drying function; after controlling the kitchen device to start the tableware washing function, the method further includes:

[0020] Controlling the kitchen device to start the tableware drying function after the tableware washing function is finished;

[0021] The kitchen device is controlled to start the tableware disinfection function after the tableware drying function is completed.

[0022] In one embodiment, the predicting of tableware usage time based on historical operation data of the range hood or the stove to obtain the predicted tableware usage time includes:

[0023] The opening time and the corresponding closing time in the historical operation data of the range hood or the cooker are input into a time series prediction model for prediction to obtain a predicted tableware use time.

[0024] In one embodiment, the predicting of tableware usage time based on historical operation data of the range hood or the stove to obtain the predicted tableware usage time includes:

[0025] The start time or the shut down time in the historical operation data of the range hood or the cooker and the first time for characterizing the storage of dirty dishes in the kitchen equipment are input into a time series prediction model for prediction to obtain a predicted tableware usage time.

[0026] In one embodiment, the kitchen equipment includes a dining plate area and a bowl and chopstick area, wherein the dining plate area is used to store dining plates, and the bowl and chopstick area is used to store bowls and chopsticks;

[0027] The method of predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time includes:

[0028] Input the opening time and corresponding closing time in the historical operation data of the range hood or the stove into the time series prediction model for prediction, and obtain the predicted plate usage time;

[0029] Inputting the shutdown time in the historical operation data of the range hood or the stove and the first time for representing the storage of dirty dishes in the kitchen equipment into the time series prediction model for prediction, obtaining the predicted usage time of dishes;

[0030] If the time difference between the current moment and the predicted tableware usage time is less than a preset time, controlling the kitchen device to start working includes:

[0031] If the time difference between the current moment and the predicted plate usage time is less than a first preset time length, controlling the plate area of ​​the kitchen device to work;

[0032] If the time difference between the current moment and the predicted tableware usage time is less than a second preset time length, the tableware area of ​​the kitchen equipment is controlled to operate.

[0033] In one embodiment, the kitchen device further includes a tableware washing function, and the first time is the time when the dirtiness of the tableware stored in the kitchen device reaches a second preset dirtiness level or the time when the kitchen device manually starts the washing function.

[0034] In one embodiment, predicting the tableware usage time based on the historical operation data of the kitchen appliance to obtain the predicted tableware usage time includes:

[0035] Preprocessing the historical operation data of the kitchen equipment to determine a first time series;

[0036] Decomposing the first time series into a trend term, a seasonal term and a random term, and removing the random term to obtain a second time series;

[0037] The second time series is input into a time series prediction model to predict the tableware usage time to obtain the predicted tableware usage time. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 A schematic diagram of a flow chart of a method for controlling a kitchen device according to an embodiment of the present invention;

[0040] Figure 2 A schematic diagram of a flow chart of a method for controlling a kitchen device according to an embodiment of the present invention;

[0041] Figure 3 A schematic diagram of a flow chart of a method for controlling a kitchen device according to an embodiment of the present invention;

[0042] Figure 4 A schematic diagram of a control device for a kitchen appliance according to an embodiment of the present invention;

[0043] Figure 5 Schematic diagram of the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0046] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0047] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0048] Currently, kitchen appliances such as dishwashers and disinfection cabinets have tableware disinfection functions, which greatly improves the disinfection efficiency of tableware. However, these devices often require users to manually start or pre-set the running time, which limits the ability to meet users' personalized needs and usage preferences. It may also cause tableware and kitchen utensils to be disinfected in time due to users forgetting. Based on this, an embodiment of the present invention provides a control method for kitchen equipment, which is applied to a control terminal, and the control terminal can be a central control device or an intelligent gateway in a whole-house intelligent control system. In the whole-house intelligent control system, the control terminal is connected to each device by wire or wirelessly. The kitchen equipment is used to store tableware and has a tableware disinfection function, and can be a disinfection cabinet, a dishwasher, etc.

[0049] According to an embodiment of the present invention, a method for controlling kitchen equipment is provided. Figure 1 is a flow chart of a method for controlling a kitchen device according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0050] Step S101, predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time.

[0051] The historical operation data of the range hood or stove may include the time of each use, the duration of use, the frequency of use, and specific events related to the use of tableware, such as the start time and end time of cooking. The predicted tableware use time is obtained based on the historical operation data. The tableware use time can be the time when cooking starts or the time when eating starts. The predicted tableware use time can be a single moment or multiple moments. The predicted tableware use time obtained is different according to different historical operation data.

[0052] Before prediction, a large amount of historical operation data can be collected as training data, analyzed, and the usage characteristics of the range hood or stove can be determined. Based on the analysis results, a prediction model is built, which can output one or more predicted tableware usage times based on the input historical operation data.

[0053] Step S102: If the time difference between the current moment and the predicted tableware usage time is less than a preset time, the kitchen equipment is controlled to start working.

[0054] The preset duration is a preset duration threshold, which defines how long before the predicted tableware usage time to start controlling the kitchen equipment to work.

[0055] After the predicted tableware usage time is obtained, the current time is continuously compared with the predicted tableware usage time. If the time difference between the current time and the predicted tableware usage time is less than the preset time, the kitchen equipment is controlled to start working. The working operation mode of the kitchen equipment can be determined based on the operating status of the kitchen equipment at the current time and the status of the tableware stored therein.

[0056] When comparing the current time with the predicted tableware usage time, if the predicted tableware usage time includes multiple times, the earliest time is used to compare with the current time.

[0057] The control method of kitchen equipment provided by the embodiment of the present invention includes predicting the use time of tableware based on the historical operation data of the range hood or the stove to obtain the predicted use time of tableware; if the time difference between the current moment and the predicted use time of tableware is less than the preset time, the kitchen equipment is controlled to start working. This method can predict the use time of tableware by analyzing the historical operation data of the range hood or the stove, so as to automatically start the kitchen equipment to start disinfection work at a certain moment, without manual operation or appointment, thereby improving the degree of automation and the user experience.

[0058] In some optional embodiments, the kitchen device further includes a dishwashing function, and the step S102 of the control method embodiment of the kitchen device includes the following steps:

[0059] Step S201, obtaining the dirtiness of tableware stored in the kitchen equipment.

[0060] Before preparing to control the kitchen equipment to start working, first obtain the degree of dirtiness of the tableware stored therein. Specifically, the built-in infrared or ultrasonic equipment of the kitchen equipment can be used to detect whether there is oil stain, food residue, dust, etc. on the tableware. Specifically, the degree of dirtiness of the current tableware can be judged according to the type and amount of oil stain, food residue and dust. Different degrees of dirtiness correspond to specific judgment standards, which can be set in advance according to actual conditions.

[0061] Step S202: If the dirtiness level does not exceed the first preset dirtiness level, the kitchen equipment is controlled to start a disinfection function.

[0062] There are specific criteria for different degrees of dirtiness, which can be set in advance according to actual conditions. The first preset dirtiness can be used as the maximum dirtiness for disinfecting tableware. If the dirtiness of the detected tableware does not exceed the first preset dirtiness, the kitchen equipment is controlled to start the disinfection function.

[0063] If the dirtiness of the detected tableware does not exceed the first preset dirtiness, it indicates that the tableware is relatively clean and does not need to be washed, but only needs to be disinfected.

[0064] Step S203: If the dirtiness level exceeds a first preset dirtiness level, the kitchen device is controlled to start a dishwashing cleaning function.

[0065] If the dirtiness exceeds the first preset dirtiness, the tableware in the kitchen equipment is cleaned. The tableware cleaning function includes steps such as spraying water and scrubbing.

[0066] Furthermore, the dishwashing function of the kitchen equipment includes a normal cleaning mode and a quick cleaning mode, wherein the cleaning time of the quick cleaning mode is shorter than the cleaning time of the normal cleaning mode, the amount of detergent used in the quick cleaning mode is greater than the amount of detergent used in the normal cleaning mode and / or the rinsing force of the quick cleaning mode is greater than the rinsing force of the normal cleaning mode. The above step S203 includes: controlling the kitchen equipment to select the quick cleaning mode to wash the dishes.

[0067] When the time difference between the current moment and the predicted tableware usage time is less than the preset time, and the degree of dirtiness of the tableware in the kitchen device exceeds the first preset degree of dirtiness, the kitchen device can be controlled to start the quick cleaning mode to clean the tableware. The cleaning time of the normal cleaning mode is longer than that of the quick cleaning mode, so as to ensure that the tableware is thoroughly cleaned. The quick cleaning mode is designed to quickly clean the tableware, so the cleaning time is relatively short. In order to quickly clean in a short time, the amount of detergent will be increased to accelerate the decomposition of stains. In addition, the flushing force can also be increased.

[0068] In some optional implementations, before the above step S201, the method further includes:

[0069] Step S204, obtaining the current status of the kitchen equipment.

[0070] Before obtaining the degree of dirtiness of the dishes stored in the kitchen device, the current state of the kitchen device is obtained, and the current state can be obtained by reading the operation data of the kitchen device, and the state of the kitchen device includes a standby state and a working state. Specifically, the operation data of the kitchen device includes an identification number for characterizing the current state of the kitchen device, and the current state of the kitchen can be determined by reading the identification number.

[0071] Step S205: If the current state is the standby state, the degree of dirtiness of the tableware stored in the kitchen equipment is obtained.

[0072] If the current state is standby, the degree of dirtiness of the tableware stored in the kitchen device is obtained, and then the operation mode of the kitchen device can be determined according to the degree of dirtiness.

[0073] Step S206: If the current state is the working state, the current state is maintained.

[0074] If the current state is working, it indicates that the user may have actively issued instructions to control the operation of the kitchen equipment. In this case, no action is required to keep the kitchen equipment running in the current state.

[0075] This embodiment determines whether the kitchen device is in working state according to the working state of the kitchen device, and then determines whether the kitchen device needs to be controlled. The priority of user control is higher than the control of the kitchen device by the control device.

[0076] In some optional embodiments, the kitchen device further includes a tableware drying function. After the kitchen device is controlled to start the tableware washing function in the above step S203, the method further includes:

[0077] Step S301, controlling the kitchen device to start the tableware drying function after the tableware washing function is completed.

[0078] After controlling the kitchen device to start the tableware washing function, detecting whether the kitchen device has completed washing, and after the tableware washing function is completed, controlling the kitchen device to start the tableware drying function.

[0079] After washing the dishes, there may be residual moisture on their surface. The drying function can quickly remove the residual moisture through heating or ventilation to prevent the dishes from breeding bacteria or producing odors due to long-term moisture.

[0080] Step S302, controlling the kitchen device to start the tableware disinfection function after the tableware drying function is completed.

[0081] After the kitchen equipment starts the tableware drying function, it detects whether the kitchen equipment has completed the tableware drying, and after the tableware drying function is completed, the tableware disinfection function is turned on. The kitchen equipment has a built-in disinfection system, such as an ultraviolet lamp, a high-temperature heater, etc. After the tableware drying function is completed, the kitchen equipment is controlled to start the tableware disinfection function.

[0082] In some optional implementations, the above step S101 includes: inputting the opening time and the corresponding closing time in the historical operation data of the range hood or the stove into a time series prediction model for prediction to obtain the predicted tableware usage time.

[0083] The time series prediction model can capture patterns in time series data and make predictions about the future based on the patterns. In the scenarios related to this embodiment, the time series prediction model can identify the periodicity or regularity of cooking actions, thereby predicting the use time of tableware. Optionally, the time series prediction model can use an LSTM (Long Short-Term Memory) model.

[0084] The time series prediction model is used to predict the usage time of tableware. The time series prediction model can be defined and trained according to actual needs. Different time series prediction models have different input data and corresponding output results.

[0085] In this embodiment, the opening time and each closing time corresponding to the opening time in the historical operation data of the range hood or stove are used as the input of the time series prediction model. Specifically, each group of opening time and the corresponding closing time form a time series, and the time series is used as the input of the time series prediction model. The time series can also be processed and then input into the time series prediction model. The model outputs the predicted tableware usage time, which corresponds to the input data and may include the predicted working time of the range hood or stove.

[0086] In some optional embodiments, the above step S101 includes: inputting the start time or the shutdown time in the historical operation data of the range hood or the stove and the first time for characterizing the storage of dirty dishes in the kitchen equipment into the time series prediction model for prediction to obtain the predicted tableware usage time.

[0087] In this embodiment, the opening time or closing time and the first time in the historical operation data of the range hood or the stove are used as the input of the time series prediction model. Specifically, the time series can be composed of the opening time and the first time, or the closing time and the first time. The first time represents the time when the kitchen equipment stores dirty tableware. Tableware may be stored in the kitchen equipment after each use of the range hood or the stove. Corresponding to the input data, the predicted tableware use time obtained may include the predicted working time of the range hood or the stove, and the predicted time when the kitchen equipment stores dirty tableware.

[0088] In this embodiment, a method for controlling a kitchen device is provided. Figure 2As shown, the kitchen equipment includes a dining plate area and a bowl and chopstick area, the dining plate area is used to store dining plates, and the bowl and chopstick area is used to store bowls and chopsticks. The method includes the following steps:

[0089] Step S401, predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time.

[0090] Specifically, step S401 includes:

[0091] Step S4011, input the historical start time and the corresponding shut down time of the range hood or stove into the time series prediction model for prediction, and obtain the predicted plate usage time.

[0092] In this embodiment, the opening time and each closing time corresponding to the opening time in the historical operation data of the range hood or stove are used as the input of the time series prediction model. Specifically, each group of opening time and the corresponding closing time form a time series, and the time series is used as the input of the time series prediction model. The time series can also be processed and then input into the time series prediction model. Through the prediction of the time series prediction model, the predicted plate usage time is output. The opening and closing of the range hood or stove is usually related to cooking activities, and cooking activities are often accompanied by the use of plates, so the predicted plate usage time can be obtained accordingly.

[0093] Step S4012, inputting the closing time of the range hood or stove in history and the first time used to characterize the storage of dirty dishes in the kitchen equipment into the time series prediction model for prediction, and obtaining the predicted usage time of the dishes.

[0094] The first time refers to the time point when dirty dishes are detected in the kitchen equipment, which can also be considered as a time point within a specific time period after cooking. After cooking, the probability of using dishes increases. The predicted use time of dishes is obtained based on the opening time or closing time in the historical operation data of the range hood or stove and the first time. The predicted use time of dishes can be considered to be before and after meal time.

[0095] Step S402: If the time difference between the current moment and the predicted tableware usage time is less than a preset time, the kitchen equipment is controlled to start working.

[0096] Step S4021, if the time difference between the current moment and the predicted plate usage time is less than the first preset time length, the plate area of ​​the kitchen equipment is controlled to work.

[0097] Step S4022: If the time difference between the current moment and the predicted usage time of dishes and chopsticks is less than a second preset time length, the dishes and chopsticks area of ​​the kitchen equipment is controlled to work.

[0098] The first preset time and the second preset time are both time thresholds for triggering the control of the operation of the kitchen equipment. The first preset time is associated with the predicted plate usage time, and the second preset time is associated with the predicted bowl and chopstick usage time. After the predicted plate usage time is obtained, the time difference between the current moment and the predicted plate usage time is calculated. If the time difference is less than the first preset time, it can be considered that the plates need to be prepared in advance, so the bowl and chopstick area of ​​the kitchen equipment needs to be disinfected, cleaned, and dried.

[0099] After obtaining the predicted usage time of dishes and chopsticks, the time difference between the current moment and the predicted usage time of dishes and chopsticks is calculated. If the time difference is less than the second preset time, it can be considered that the dishes and chopsticks need to be prepared in advance, so the dishes and chopsticks area of ​​the kitchen equipment needs to be disinfected, cleaned and dried.

[0100] In some optional embodiments, the kitchen device further includes a dishwashing cleaning function, and the first time is the time when the dirtiness of the dishes stored in the kitchen device reaches a second preset dirtiness level or the time when the kitchen device manually starts the cleaning function.

[0101] The first time can be used to represent the moment when dirty tableware is stored in the kitchen device. When the dirty tableware is stored in the kitchen device, the degree of dirtiness of the tableware stored in the kitchen device reaches a second preset degree of dirtiness, and the user can manually start the cleaning function. The second preset degree of dirtiness can be used as a threshold for determining whether the tableware needs to be cleaned. The time when the degree of dirtiness of the tableware reaches the second preset degree of dirtiness can be used as the first time, and the time when the kitchen device manually starts the cleaning function can also be used as the first time.

[0102] In some optional embodiments, the above step S101 includes: preprocessing the historical operation data of the kitchen equipment to determine a first time series; decomposing the first time series into trend items, seasonal items and random items, and removing the random items to obtain a second time series; inputting the second time series into a time series prediction model to predict the tableware usage time to obtain the predicted tableware usage time.

[0103] Before making a prediction, the historical operation data of the range hood or stove is preprocessed, and the historical operation data used is the start time T of each range hood. on and closing time T off For example, during preprocessing, we determine whether the data has missing values ​​and outliers. If so, we delete the outliers. The first time series Yt obtained after processing is as follows:

[0104]

[0105] There are t groups of data in total.

[0106] The STL decomposition method (Seasonal and Trend decomposition using Loess) is used to decompose the first time series into trend term Tt, seasonal term St and random term Rt, namely:

[0107] Yt=Tt+St+Rt

[0108] The STL decomposition consists of an inner loop and an outer loop. The trend term and the seasonal term are updated each time the inner loop iterates. The complete inner loop includes n(i) iterations. The outer loop includes the inner loop and the calculation of the robustness weights, which are used to reduce the impact of temporary and discrete points on the trend term and the seasonal term in the next inner loop iteration, and executes n(o) iterations.

[0109] Suppose the trend term after the kth iteration is The seasonal term after the kth iteration is The specific steps are as follows:

[0110] Step (1): Detrending. Subtract the trend term obtained in the kth iteration from the first time series Yt Calculate the detrended periodic subseries Right now

[0111]

[0112] Step (2): Smoothing of detrended periodic subsequences. The periodic subsequences in the detrended sequence are smoothed using a local weighted regression method. The set of smoothed values ​​of all periodic subsequences is the temporary seasonal sequence.

[0113] Step (3): Low-pass filter of temporary seasonal series. The temporary seasonal series is processed using a low-pass filter, which includes a sliding average of length n(p) and a factor of 3. The result is locally weighted and regressed to output Example: The general cycle of usage habits is 7 days, and n(p)=7 when counted on a daily basis.

[0114] Step (4): Detrend the smoothed periodic subsequence. Use the temporary seasonal series obtained in step (2) Subtract the result obtained in step (3) Calculate the seasonal term in the k+1th iteration This step is to prevent low-frequency information from affecting the seasonal terms.

[0115] Step (5): Remove seasonal terms. Subtract the seasonal terms in the k+1th iteration from the first time series Yt Calculate the seasonal period subsequence Right now:

[0116]

[0117] Step (6): Smoothing of deseasonalized periodic subsequences. The periodic subsequences in the deseasonalized sequence are smoothed using a local weighted regression method to obtain the trend term after the k+1th iteration:

[0118] Step (7): At this time, the trend item Seasonal Items That is, the random term Rt = Yt-Tt-St. Determine whether it converges. If it converges, stop the iteration and output the trend term, seasonal term, and random term. Otherwise, calculate the robustness weight according to step (8) and return to step (1) to perform the next iteration of the inner loop.

[0119] Step (8): Robustness weight calculation. Calculate the robustness weight at time point t:

[0120] ρ t =B(|R t | / h)

[0121] Where h = 6 × median (|R t |), B represents the quadratic weight function,

[0122]

[0123] When performing local weighted regression in the inner loop steps (2) and (6), the neighborhood weights need to be multiplied by ρ t .

[0124] The second time series containing trend and seasonal terms after removing random terms is used as the input of the time series prediction model. When LSTM is used as the time series prediction model, the mean absolute error (MAE) of the LSTM neural network is used as the fitness function. The mean absolute error reflects the average difference between the predicted value and the true value. Using the absolute error can prevent the error from canceling each other out, thereby accurately reflecting the size of the model prediction error. The smaller the MAE value, the better the error performance of the model. Its function expression is as follows:

[0125]

[0126] Among them, f i is the predicted value of the model, y i is the true value of the sample, and n is the number of samples.

[0127] In this embodiment, a method for controlling kitchen equipment is also provided. Figure 3As shown, firstly, the predicted tableware usage time is predicted, and it is determined whether the time difference between the current time and the predicted tableware usage time is less than the preset time. If it is less than the preset time, it is further determined whether the kitchen equipment is in standby state. If it is not in standby state at this time, it indicates that the kitchen equipment is working, and the current state is maintained; if it is in standby state at this time, the degree of dirtiness of the tableware stored in the kitchen equipment is detected. If it does not exceed the first preset degree of dirtiness, the disinfection function is turned on; if it exceeds the first preset degree of dirtiness, the washing function is turned on until the washing is completed, and the drying function is turned on, and the disinfection function is turned on after the drying is completed.

[0128] In this embodiment, a control device for kitchen equipment is also provided, which is used to implement the above embodiments and implementation methods, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0129] This embodiment provides a control device for kitchen equipment, such as Figure 4 As shown, including:

[0130] A time prediction module is used to predict the tableware usage time based on the historical operation data of the range hood or stove to obtain the predicted tableware usage time; a control module is used to control the kitchen equipment to start working if the time difference between the current moment and the predicted tableware usage time is less than a preset duration.

[0131] The further functional description of each of the above modules is the same as that of the above corresponding embodiments and will not be repeated here.

[0132] The control device of the kitchen equipment in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0133] The embodiment of the present invention also provides an electronic device having the above Figure 4 The control device of the kitchen equipment shown.

[0134] See also Figure 5 , Figure 5 is a schematic diagram of the structure of an electronic device provided by an optional embodiment of the present invention, such as Figure 5As shown, the electronic device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.

[0135] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0136] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0137] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0138] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0139] The electronic device further comprises a communication interface 30 for the electronic device to communicate with other devices or a communication network.

[0140] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0141] In the specific contents of the above-mentioned specific implementation methods, the various technical features can be combined in any non-contradictory manner. In order to make the description concise, not all possible combinations of the above-mentioned technical features are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0142] The specific contents of the above specific embodiments only express several embodiments of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims.

Claims

1. A method for controlling a kitchen device, wherein the kitchen device is used to store tableware and has a tableware disinfection function, characterized in that: The method comprises: Predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time; If the time difference between the current moment and the predicted tableware usage time is less than a preset time length, the kitchen device is controlled to start working.

2. The method according to claim 1, characterized in that The kitchen device also includes a tableware washing function, and the control of the kitchen device to start working includes: Get the degree of dirtiness of the dishes stored in the kitchen equipment; If the dirtiness level does not exceed a first preset dirtiness level, controlling the kitchen device to start the disinfection function; If the dirtiness level exceeds a first preset dirtiness level, the kitchen device is controlled to start the dishwashing function.

3. The method according to claim 2, characterized in that Before obtaining the degree of dirtiness of the tableware stored in the kitchen equipment, the method further includes: Get the current status of the kitchen equipment; If the current state is the standby state, obtaining the degree of dirtiness of the tableware stored in the kitchen equipment; If the current state is a working state, the current state is maintained for operation.

4. The method according to claim 2, characterized in that: The tableware washing function of the kitchen device includes a normal washing mode and a quick washing mode, the washing time of the quick washing mode is shorter than the washing time of the normal washing mode, the amount of detergent used in the quick washing mode is greater than the amount of detergent used in the normal washing mode, and / or the rinsing force of the quick washing mode is greater than the rinsing force of the normal washing mode; The controlling the kitchen device to start the dishwashing function includes: The kitchen device is controlled to select a quick cleaning mode to clean the dishes.

5. The method according to claim 2, characterized in that: The kitchen device further includes a tableware drying function; after controlling the kitchen device to start the tableware washing function, the method further includes: Controlling the kitchen device to start the tableware drying function after the tableware washing function is completed; The kitchen device is controlled to start the tableware disinfection function after the tableware drying function is completed.

6. The method according to claim 1, characterized in that The method of predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time includes: The opening time and the corresponding closing time in the historical operation data of the range hood or the cooker are input into a time series prediction model for prediction to obtain a predicted tableware use time.

7. The method according to claim 1, characterized in that The method of predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time includes: The start time or the shut down time in the historical operation data of the range hood or the cooker and the first time for characterizing the storage of dirty dishes in the kitchen equipment are input into a time series prediction model for prediction to obtain a predicted tableware use time.

8. The method according to claim 1, characterized in that: The kitchen equipment includes a dining plate area and a bowl and chopstick area, wherein the dining plate area is used to store dining plates, and the bowl and chopstick area is used to store bowls and chopsticks; The method of predicting the tableware usage time based on the historical operation data of the range hood or the stove to obtain the predicted tableware usage time includes: Input the opening time and corresponding closing time in the historical operation data of the range hood or the stove into the time series prediction model for prediction, and obtain the predicted plate usage time; Inputting the shutdown time in the historical operation data of the range hood or the stove and the first time for representing the storage of dirty dishes in the kitchen equipment into the time series prediction model for prediction, obtaining the predicted usage time of dishes; If the time difference between the current moment and the predicted tableware usage time is less than a preset time, controlling the kitchen device to start working includes: If the time difference between the current moment and the predicted plate usage time is less than a first preset time length, controlling the plate area of ​​the kitchen device to work; If the time difference between the current moment and the predicted tableware usage time is less than a second preset time length, the tableware area of ​​the kitchen equipment is controlled to operate.

9. The method according to claim 7 or 8, characterized in that: The kitchen device also includes a tableware washing function, and the first time is the time when the dirtiness of the tableware stored in the kitchen device reaches a second preset dirtiness level or the time when the kitchen device manually starts the washing function.

10. The method according to claim 1, characterized in that The method of predicting the tableware usage time based on the historical operation data of the kitchen appliance to obtain the predicted tableware usage time includes: Preprocessing the historical operation data of the kitchen equipment to determine a first time series; Decomposing the first time series into a trend term, a seasonal term and a random term, and removing the random term to obtain a second time series; The second time series is input into a time series prediction model to predict the tableware usage time to obtain the predicted tableware usage time.

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