Cloud memory allocation method and cloud server, clothes treatment apparatus

Abstract

The application provides a cloud memory allocation method for a clothes processing device, and relates to the technical field of intelligent household appliances, and comprises the following steps: determining a first memory value according to a first average value obtained by dividing the sum of memory values used by a current clothes processing device in each washing in a set interval by the total number of washings; determining a personalized memory value of the current clothes processing device according to the first memory value and a second memory value corresponding to the current clothes processing device; and allocating memory to the current clothes processing device according to the personalized memory value when it is determined that operation notification information of the current clothes processing device is received. By determining the personalized memory value according to the first memory value and the second memory value, it can be avoided that too much memory is allocated when the clothes processing device does not need it, so that the cloud server can serve more clothes processing devices, and the demand of more and more operation modes of the clothes processing device can be met. The application also provides a cloud server and a clothes processing device.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent household appliances, in particular to a cloud memory allocation method for a clothes processing device, a cloud server and a clothes processing device. BACKGROUND

[0002] A washing machine is a cleaning appliance that uses electric energy to produce mechanical action to wash clothes.

[0003] With the development of the times, people's demand for home is getting higher and higher. In order to let users get a better experience, the development of washing machines gradually tends to have touch screens to better realize human-computer interaction, have more functions to meet the washing needs of users, and even develop towards multi-cylinder to allow different types of clothes to be washed at the same time. In order to meet the functional needs of diversification, the washing machine needs to have more running memory and storage memory. Since the running memory and storage memory of the washing machine now use the memory space of the cloud server, under the condition that millions of washing machines all need to use the memory space on the cloud server, there is a great demand for the memory on the cloud server.

[0004] Patent CN111962253A provides a washing machine running program extension method, which downloads a cloud running program from a cloud server and stores it in a washing machine. When the number of running programs in the washing machine or the occupied storage space reaches the upper limit, the running program with the lowest usage frequency in the washing machine is replaced.

[0005] This method can temporarily solve the problem of excessive demand for memory on the cloud server, but as technology updates and iterations, the number and style of washing machine programs are increasing, and this method will eventually be unable to meet the program running needs of the washing machine. SUMMARY

[0006] The present application provides a cloud memory allocation method for a clothes processing device, a cloud server and a clothes processing device to at least solve the technical problem that the memory space on the cloud server cannot meet the needs of all clothes processing devices connected thereto.

[0007] According to a first aspect of the embodiments of the present application, a cloud memory allocation method for a clothes processing device is provided, comprising:

[0008] determining a first memory value according to the memory values used by the current clothes processing device in each washing in a set interval;

[0009] determining a personalized memory value of the current clothes processing device according to the first memory value and a second memory value corresponding to the current clothes processing device;

[0010] determining, upon determining that the operation notification information of the current clothes processing device is received, a memory value for the current clothes processing device according to the personalized memory value.

[0011] In these embodiments, by determining the personalized memory value of the current clothes processing device according to the first memory value and the second memory value, and then allocating memory for each clothes processing device according to the personalized memory value of each clothes processing device, it can be avoided that too much memory is allocated for each clothes processing device when it is not needed, so that the cloud server can serve more clothes processing devices, and the demand for more and more operation modes of clothes processing devices can be met.

[0012] Optionally, the first memory value is determined according to the sum of the memory values used by the current clothes processing device for each washing in a set interval.

[0013] determining the sum of the memory values used by the current clothes processing device for each washing in the set interval.

[0014] dividing the sum of the memory values by the total number of washings of the current clothes processing device in the set interval to obtain a first average value.

[0015] determining the first memory value according to the first average value.

[0016] Optionally, the set interval is the n th washing to the m th washing of the current clothes processing device, where n and m are positive integers greater than 1, and m is greater than n.

[0017] Optionally, the first memory value is determined according to the first average value obtained by dividing the sum of the memory values used by the current clothes processing device for each washing in the set interval by the total number of washings.

[0018] obtaining the memory value used by the current clothes processing device for each washing from the n th washing to the m th washing.

[0019] adding the memory values used by the current clothes processing device for each washing to obtain a sum value.

[0020] determining the difference between m and n, dividing the sum value by the difference to obtain a first average value of the memory value used by the current clothes processing device for each washing in the set interval.

[0021] determining the first memory value as a value obtained by expanding the first average value by a first proportion.

[0022] In these embodiments, by determining the first memory value as a value obtained by expanding the first average value by a first proportion, the first memory value is greater than the first average value, so that the cloud server can allocate more memory space for the current clothes processing device.

[0023] Optionally, the determining the personalized memory value of the current clothes processing device according to the first memory value and a second memory value corresponding to the current clothes processing device comprises:

[0024] In a case where the first memory value is greater than or equal to the second memory value corresponding to the current clothes processing device, the first memory value is determined as the personalized memory value of the current clothes processing device.

[0025] In a case where the second memory value is greater than the first memory value, the second memory value is determined as the personalized memory value.

[0026] In these embodiments, selecting the greater value between the first memory value and the second memory value as the personalized memory value of the clothes processing device can make the memory space allocated by the cloud server to the clothes processing device more sufficient.

[0027] Optionally, before the determining the personalized memory value of the current clothes processing device according to the first memory value and a second memory value corresponding to the current clothes processing device, the method further comprises:

[0028] determining a second average value by dividing a sum of memory values used in each washing by a set number of washings, in a case where the running mode of the model corresponding to the current clothes processing device in each washing is not repeated within the set number of washings.

[0029] determining the second memory value as a value obtained by expanding the second average value by a second proportion.

[0030] In these embodiments, by determining the second memory value as a value obtained by expanding the second average value by a second proportion, the memory space allocated by the cloud server to the clothes processing device can be made more sufficient.

[0031] Optionally, after the determining the personalized memory value of the current clothes processing device, the method further comprises:

[0032] acquiring a memory value used by the current clothes processing device in each washing process of the current clothes processing device.

[0033] In a case where it is detected that the memory value used by the current clothes processing device in the current washing process of the current clothes processing device is greater than a value obtained by multiplying the personalized memory value by a third proportion, allocating a memory corresponding to a rated maximum memory value corresponding to the current clothes processing device to the current clothes processing device in a subsequent stage of the current washing process.

[0034] In these embodiments, by allocating the memory corresponding to the rated maximum memory value to the current clothes processing device, the situation that the memory allocated to the current clothes processing device is insufficient and affects the use of the current clothes processing device can be reduced.

[0035] Optionally, the cloud memory allocation method for the laundry treatment apparatus provided by the embodiments of the present application further comprises:

[0036] In the case that there are a first set number of values greater than a set threshold value in the memory values used in each washing process of the current laundry treatment apparatus, determining a sum of the values greater than the set threshold value and a second set number of the personalized memory values; wherein the set threshold value is a value that the personalized memory value is enlarged by a fourth proportion, and the second set number is a difference between a third set number and the first set number; dividing the sum of the values greater than the set threshold value and the second set number of the personalized memory values by the third set number to obtain a new personalized memory value; when it is determined that the memory allocation request of the current laundry treatment apparatus is received, allocating memory for the current laundry treatment apparatus according to the new personalized memory value.

[0037] In these embodiments, by adjusting the personalized memory value according to the memory values used in each washing process of the current laundry treatment apparatus, the problem that the previously determined personalized memory value is too small to meet the user's subsequent use requirements for the laundry treatment apparatus can be reduced. At the same time, by combining the previously determined personalized memory value and the memory values used in each washing process of the current laundry treatment apparatus to determine a new personalized memory value, the problem that too much memory space is allocated for the laundry treatment apparatus due to too much adjustment of the personalized memory value at one time can be reduced.

[0038] Optionally, the cloud storage stores the basic program information of each operation mode corresponding to each laundry treatment apparatus model, the personalized memory value of each laundry treatment apparatus, and further stores the operation mode information collected by the collection of each laundry treatment apparatus and / or the setting information of the display interface of each laundry treatment apparatus.

[0039] When it is determined that the operation notification information of the current laundry treatment apparatus is received, the cloud memory allocation method for the laundry treatment apparatus further comprises:

[0040] determining the operation mode selected for the current operation of the current laundry treatment apparatus according to the operation notification information;

[0041] obtaining the basic program information corresponding to the operation mode selected for the current operation from the basic program information of each operation mode corresponding to the current laundry treatment apparatus;

[0042] performing operation configuration for the current laundry treatment apparatus according to the basic program information corresponding to the operation mode selected for the current operation.

[0043] In the embodiments, by storing only the basic program information of each operation mode corresponding to each clothes processing device model, the personalized memory value of each clothes processing device, the operation mode information collected by each clothes processing device collection, and the setting information of the display interface of each clothes processing device in the cloud, compared with storing all program information of all operation modes for each clothes processing device in the prior art, the data storage amount in the cloud can be reduced.

[0044] Optionally, before determining the first memory value according to the average value of the memory values used by the current clothes processing device in each washing in the set interval, the method further comprises:

[0045] Before determining that the operation notification information of the current clothes processing device is received, allocating memory to the current clothes processing device according to the rated maximum memory value corresponding to the current clothes processing device.

[0046] When receiving the information of restoring the factory settings sent by the current clothes processing device, clearing the washing frequency of the current clothes processing device.

[0047] In the embodiments, by allocating memory to the current clothes processing device according to the rated maximum memory value corresponding to the current clothes processing device when it is determined that the operation notification information of the current clothes processing device is received before the set interval, the situation of insufficient memory allocation to the clothes processing device can be reduced. In addition, by clearing the washing frequency of the current clothes processing device when receiving the information of restoring the factory settings sent by the current clothes processing device, the use of the clothes processing device after it is manufactured can be avoided, and the determination of the personalized memory value after it is manufactured.

[0048] According to a second aspect of the embodiments of the present application, a cloud server is provided, comprising a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program to realize the cloud memory allocation method for clothes processing devices provided by the embodiments of the present application.

[0049] According to a third aspect of the embodiments of the present application, a cloud memory allocation method for clothes processing devices is provided, comprising:

[0050] Sending operation notification information to a cloud server;

[0051] Receiving memory allocation information sent by the cloud server;

[0052] Operating according to the memory allocation information sent by the cloud server.

[0053] According to a fourth aspect of the embodiments of the present application, a laundry processing device is provided, comprising a memory and a processor, the memory is configured to store a computer program, and the processor is configured to execute the computer program to implement the cloud memory allocation method for the laundry processing device provided by the embodiments of the present application.

[0054] In the embodiments of the present application, by determining the personalized memory value of the current laundry processing device according to the first memory value and the second memory value, and then allocating the memory for each laundry processing device according to the personalized memory value of each laundry processing device, it can avoid allocating too much memory for each laundry processing device when it is not needed, so that the cloud server can serve more laundry processing devices, and can meet the increasing demand for operation modes of the laundry processing devices. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 is a cloud memory allocation method flowchart for a laundry processing device provided by the embodiments of the present application;

[0056] Figure 2 is a method flowchart for determining a first memory value provided by the embodiments of the present application;

[0057] Figure 3 is a method flowchart for determining a personalized memory value provided by the embodiments of the present application;

[0058] Figure 4 is a method flowchart for determining a second memory value provided by the embodiments of the present application;

[0059] Figure 5 is another cloud memory allocation method flowchart for a laundry processing device provided by the embodiments of the present application;

[0060] Figure 6 is a method flowchart for updating a personalized memory value provided by the embodiments of the present application;

[0061] Figure 7 is a cloud operation mode configuration method flowchart for a laundry processing device provided by the embodiments of the present application;

[0062] Figure 8 is another cloud memory allocation method flowchart for a laundry processing device provided by the embodiments of the present application;

[0063] Figure 9 is another cloud memory allocation method flowchart for a laundry processing device provided by the embodiments of the present application;

[0064] Figure 10is a method flow diagram provided by an embodiment of the application for determining a first memory value;

[0065] Figure 11 is another method flow diagram provided by an embodiment of the application for cloud memory allocation of a clothes processing device;

[0066] Figure 12 is a structural diagram of a clothes processing device provided by an embodiment of the application;

[0067] Figure 13 is a structural diagram of a cloud server provided by an embodiment of the application. DETAILED DESCRIPTION

[0068] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the scope of protection of the present application.

[0069] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0070] According to an embodiment of the present application, a method embodiment of a cloud memory allocation method for a clothes processing device is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0071] Currently, the clothes processing device generally uses a color screen display to meet the human-computer interaction demand. To make the clothes processing device more comfortable to use, the displayed picture is generally high definition. The color screen display needs larger running memory and storage memory. In order to reduce the cost of the clothes processing device, the running memory and the storage memory of the clothes processing device are currently placed on a cloud server. The clothes processing device must be connected to the network to be used. The clothes processing device is connected to the network when it is turned on, and the clothes processing device is disconnected from the network when it is turned off.

[0072] Based on this, millions of clothes processing devices use the running memory and the storage memory allocated by the cloud server. If the cloud server allocates the maximum memory space to each clothes processing device, the cloud server may not have enough memory size. Moreover, when the user of the clothes processing device uses the clothes processing device to do laundry, the user will not use the maximum memory of the clothes processing device. The size of the memory is related to the number of programs and pictures loaded by the user when using the clothes processing device. Generally, when using the clothes processing device, the user will not use other modes after getting used to using certain modes. Thus, the required memory space is relatively small, and it is unnecessary to allocate the maximum memory resource. Therefore, the application provides a cloud memory allocation method for clothes processing devices and a cloud server.

[0073] The application provides a cloud memory allocation method for clothes processing devices and a cloud server to at least solve the technical problem that the memory space on the cloud server cannot meet the needs of all clothes processing devices connected thereto.

[0074] The application provides a cloud server, including a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program to realize the cloud memory allocation method for clothes processing devices provided by the application.

[0075] As shown in Figure 1 The application also provides a cloud memory allocation method for clothes processing devices, including:

[0076] S101, the processor determines a first memory value according to the memory values used by the current clothes processing device in each laundry within a set interval.

[0077] The set interval can be a time interval, for example, within the second month after the clothes processing device reaches the user's home. The set interval can also be a running time interval of the clothes processing device, for example, the 11th to 15th laundry of the clothes processing device.

[0078] The memory value used in each wash cycle can be either the maximum value among the memory values ​​used by the garment processing equipment during a single wash cycle, or the average value of the memory values ​​used by the garment processing equipment obtained multiple times during a single wash cycle. The maximum value can be determined by obtaining the memory values ​​used by the garment processing equipment multiple times during a single wash cycle.

[0079] The total number of washes is the total number of washes performed by the current garment processing equipment within the set range.

[0080] The first memory value is determined based on the memory values ​​used by the current garment processing equipment during each wash within a set interval. This can be achieved by dividing the sum of the memory values ​​used by the current garment processing equipment during each wash within the set interval by the total number of washes performed within that interval, obtaining a first average value. Alternatively, the first memory value can be determined based on the maximum value among the memory values ​​used by the current garment processing equipment during each wash within the set interval.

[0081] S102. The processor determines the personalized memory value of the current clothing processing device based on the first memory value and the second memory value corresponding to the current clothing processing device.

[0082] The second memory value can be a standard memory value common to the current garment processing device model, or it can be determined based on the memory used by the current garment processing device model when running in different modes during a set number of washes. These different modes can be selected from the modes that consume the most memory for the current garment processing device model.

[0083] S103. When the processor determines that it has received the operation notification information of the current clothing processing device, it allocates memory for the current clothing processing device according to the personalized memory value.

[0084] The current operation notification information of the garment processing equipment can be a network connection request from the current garment processing equipment or a power-on notification from the current garment processing equipment.

[0085] In these implementations, by determining the personalized memory value of the current garment processing device based on the first memory value and the second memory value, and then allocating memory to each garment processing device based on the personalized memory value of each garment processing device, it is possible to avoid allocating excessive memory to each garment processing device when it is not needed. This allows the cloud server to serve more garment processing devices and meet the increasing operational needs of the garment processing devices.

[0086] Optionally, the first memory value is determined based on the memory value used by the current garment processing equipment for each wash within a set interval, including:

[0087] The processor determines the sum of memory values ​​used by the current garment processing equipment for each wash within a set interval;

[0088] The processor divides the sum of the memory values ​​by the total number of washes performed by the current garment processing device within a set interval to obtain a first average value.

[0089] The processor determines the first memory value based on the first average value.

[0090] The first memory value can be equal to or greater than the first average value.

[0091] Optionally, the range can be set from the nth wash to the mth wash of the current garment processing device, where n and m are positive integers greater than 1, and m is greater than n.

[0092] In some implementations, the value of n can be between 6 and 13, and the value of m can be between 11 and 18.

[0093] In some implementations, n can be 11 and m can be 15.

[0094] like Figure 2 As shown, the first memory value is determined by dividing the sum of the memory values ​​used by the current garment processing equipment in each wash within a set interval by the total number of washes, and then determining the first average value, which includes:

[0095] S201. The processor obtains the memory value used for each wash from the nth to the mth wash of the current clothing processing device.

[0096] S202, The processor sums the memory values ​​used for each wash to obtain a sum value.

[0097] S203. The processor determines the difference between m and n, divides the sum by the difference, and obtains the first average value of the memory value used by the current clothing processing device for each wash within the set interval.

[0098] S204. The processor determines that the first memory value is a value that is the first average value multiplied by a first percentage, wherein the first percentage may be a first percentage, and in some embodiments, the first percentage is 110% to 130%, and in some embodiments, the first percentage is 120%.

[0099] In these implementations, by determining the first memory value as a value that expands the first average value by a first proportion, making the first memory value greater than the first average value, the cloud server can allocate more memory space to the current clothing processing device.

[0100] Optional, such as Figure 3As shown, based on the first memory value and the second memory value corresponding to the current clothing processing device, the personalized memory value of the current clothing processing device is determined, including:

[0101] S301. If the processor determines the first memory value as the personalized memory value of the current clothing processing device when the first memory value is greater than or equal to the second memory value corresponding to the current clothing processing device.

[0102] S302. If the processor determines the second memory value as the personalized memory value when the second memory value is greater than the first memory value.

[0103] In these implementations, selecting the larger of the first and second memory values ​​as the personalized memory value for the clothing processing device allows the cloud server to allocate more memory space to the clothing processing device.

[0104] Optional, such as Figure 4 As shown, before determining the personalized memory value of the current clothing processing device based on the first memory value and the second memory value corresponding to the current clothing processing device, the process further includes:

[0105] S401. The processor determines that, within a set number of washes, when the operating mode of the current clothing processing device is not repeated in each wash, the second average value is obtained by dividing the sum of the memory values ​​used in each wash by the set number of washes.

[0106] In some implementations, the different operating modes may be the few operating modes that use the most memory among all operating modes of the current clothing processing device model. In other implementations, the different operating modes may be several random operating modes among all operating modes of the current clothing processing device model.

[0107] The memory value used in each wash cycle can be either the maximum memory value used by the garment processing device in that wash cycle, or the average of the memory values ​​used multiple times during that wash cycle. The maximum memory value used by the garment processing device in a single wash cycle can be determined by obtaining the memory values ​​used multiple times during that wash cycle.

[0108] S402, The processor determines that the second memory value is a value that is a second average value multiplied by a second ratio.

[0109] The second ratio can be a second percentage. In some embodiments, the second ratio can be 110% to 130%. In some embodiments, the second ratio can be equal to the first ratio. In some embodiments, the second ratio can be 120%.

[0110] In these implementations, by determining the second memory value as a value that is a second average value multiplied by a second ratio, the cloud server can allocate more memory space to the clothing processing device.

[0111] Optional, such as Figure 5 As shown, after determining the personalized memory value of the current garment processing device, the following is also included:

[0112] S501. The processor obtains the memory value used by the current clothing processing device during each washing process.

[0113] The memory value used by the current clothing processing device during the washing process can be obtained periodically or randomly.

[0114] S502. When the processor detects that the memory value used by the current clothing processing device during the current washing process is greater than the personalized memory value multiplied by the third ratio, it allocates memory corresponding to the rated maximum memory value of the current clothing processing device to the current clothing processing device in the subsequent stages of the current washing process.

[0115] The third ratio can be a third percentage. In some embodiments, the third ratio can be 60% to 90%. In some embodiments, the third ratio can be 80%.

[0116] The rated maximum memory value can be the general rated maximum memory value for the current clothing processing equipment model, or a rated maximum memory value set specifically for the current clothing processing equipment.

[0117] Typically, the maximum rated memory value is greater than the first memory value and the second memory value.

[0118] In these embodiments, by allocating memory corresponding to the maximum rated memory value to the current garment processing device, the situation where insufficient memory is allocated to the current garment processing device, affecting the use of the current garment processing device, can be reduced.

[0119] Optional, such as Figure 6 As shown in the embodiments of this application, the cloud memory allocation method for clothing processing equipment further includes:

[0120] S601. If the processor finds that there are a first set number of values ​​in the memory used during each washing process of the current clothing processing device that are greater than a set threshold, it determines the sum of the values ​​greater than the set threshold and the second set number of personalized memory values.

[0121] Wherein, the set threshold is the value of the fourth ratio of the personalized memory value expansion, and the second set number is the difference between the third set number and the first set number.

[0122] The fourth ratio can be a fourth percentage. In some embodiments, the fourth ratio can be 110% to 130%. In some embodiments, the fourth ratio can be 120%.

[0123] In some embodiments, the third set number can be 4 to 6. In some embodiments, the third set number can be 5. In some embodiments, the first set number can be 2 to 3. In some embodiments, the first set number can be 2. For example, when the third set number is 5 and the first set number is 2, the second set number is 3. Taking a fourth ratio of 120% as an example, the sum of the fourth ratio (greater than the personalized memory value) and the second set number of personalized memory values ​​is determined. When the personalized memory value is 300M, if the memory values ​​used by the current clothing processing device in each washing process contain 365M and 375M, the sum of the fourth ratio (greater than the personalized memory value) and the second set number of personalized memory values ​​can be determined to be 365M + 375M + 300M + 300M + 300M, where M stands for megabyte (MByte).

[0124] S602. The processor divides the sum of the value greater than the set threshold and the second set number of personalized memory values ​​by the third set number to obtain a new personalized memory value.

[0125] For example, if the sum of a value greater than the set threshold and a second set number of personalized memory values ​​is determined to be 365M+375M+300M+300M+300M, the new personalized memory value is (365M+375M+300M+300M+300M)÷5.

[0126] S603. When the processor determines that it has received a memory allocation request from the current clothing processing device, it allocates memory to the current clothing processing device according to the new personalized memory value.

[0127] In these implementations, by adjusting the personalized memory value based on the memory used during each wash cycle of the current garment processing device, the problem of previously determined personalized memory values ​​being too small and unable to meet the user's subsequent needs for the garment processing device can be reduced. Simultaneously, by combining the previously determined personalized memory value with the memory used during each wash cycle of the current garment processing device to determine the new personalized memory value, the problem of excessive adjustments to the personalized memory value at once, leading to the allocation of excessive memory space to the garment processing device, can be reduced.

[0128] Optionally, the cloud can store the basic program information for each operating mode corresponding to each model of clothing processing equipment, the personalized memory value of each clothing processing equipment, and also store the operating mode information or the display interface settings of each clothing processing equipment.

[0129] In some implementations, the cloud stores the basic program information for each operating mode corresponding to each model of clothing processing equipment, the personalized memory value of each clothing processing equipment, the operating mode information saved in the favorites of each clothing processing equipment, and the setting information of the display interface of each clothing processing equipment.

[0130] The basic program information for each operating mode includes image and animation information that occupy a significant amount of space. The operating mode information in the favorites folder for each garment processing device can be the operating modes that users have saved in their favorites folders. The display interface settings for each garment processing device can be personalized settings such as background images, animations, the arrangement of operating modes, and display information for any software installed on the device.

[0131] like Figure 7 As shown, when it is determined that the current clothing processing equipment's operation notification information has been received, the cloud memory allocation method for the clothing processing equipment also includes:

[0132] S701 The processor determines the operating mode selected by the current clothing processing equipment for this operation based on the operation notification information.

[0133] S702. The processor obtains the basic program information corresponding to the selected operating mode from the basic program information of each operating mode corresponding to the current clothing processing equipment.

[0134] S703 The processor configures the current garment processing equipment based on the basic program information corresponding to the operating mode selected for this operation.

[0135] In some implementations, the operation configuration of the current garment processing equipment can be based on the basic program information corresponding to the selected operation mode and the personalized settings of the current garment processing equipment for that operation mode.

[0136] In these implementations, by storing only the basic program information of each operating mode corresponding to each clothing processing device model, the personalized memory value of each clothing processing device, the operating mode information collected in the favorites of each clothing processing device, and the setting information of the display interface of each clothing processing device in the cloud, the amount of data stored in the cloud can be reduced compared to the prior art which stores all program information of all operating modes for each clothing processing device.

[0137] Optional, such as Figure 8 As shown, before determining the first memory value based on the average memory value used by the current garment processing equipment in each wash within a set interval, the process also includes:

[0138] S801: Before the processor reaches the set interval, upon confirming that it has received the operation notification information of the current clothing processing device, it allocates memory to the current clothing processing device according to the rated maximum memory value corresponding to the current clothing processing device.

[0139] For example, if the washing interval is set to the 11th to 15th washing cycle, then during the 1st to 10th washing cycles, the memory allocated to the current clothing processing device is based on the rated maximum memory value corresponding to the current clothing processing device.

[0140] S802. When the processor receives the factory reset message from the current garment processing device, it resets the number of washes for the current garment processing device to zero.

[0141] Typically, garment processing equipment undergoes testing before leaving the factory. Including the number of tests in the normal usage count to determine the runtime for a set range would affect the personalized memory settings. Therefore, a factory reset trigger is configured on the garment processing equipment. This allows for a factory reset when needed, resetting the current number of washes to zero. This enables a re-determination of the runtime for the set range, resulting in a more accurate determination of the personalized memory values.

[0142] In these implementations, by allocating memory to the current garment processing device according to its rated maximum memory value before the set interval is reached, and upon receiving the operation notification information from the current garment processing device, the possibility of insufficient memory allocation for the garment processing device can be reduced. Furthermore, by resetting the washing cycle of the current garment processing device to zero upon receiving a factory reset message, it is possible to prevent the testing during the manufacturing process from affecting the post-shipment use of the garment processing device and the determination of its personalized memory value.

[0143] like Figure 9 As shown in the embodiments of this application, a cloud memory allocation method for a garment processing device is also provided, including:

[0144] S901. When the processor receives a factory reset message from the current garment processing device, it resets the number of washes for the current garment processing device to zero.

[0145] Before the nth wash cycle of the current garment processing device, the S902 processor, upon receiving the operation notification information from the current garment processing device, allocates memory to the current garment processing device according to the rated maximum memory value corresponding to the current garment processing device.

[0146] S903: The processor obtains the memory value used for each wash from the nth to the mth wash of the current clothing processing device.

[0147] S904: The processor sums the memory values ​​used for each wash to obtain a sum value.

[0148] S905. The processor determines the difference between m and n, divides the sum by the difference, and obtains the first average value of the memory value used by the current clothing processing device for each wash within the set interval.

[0149] S906, The processor determines that the first memory value is a value that is the first average value multiplied by a first ratio.

[0150] S907. The processor determines that, within a set number of washes, when the operating mode of the current clothing processing device is not repeated in each wash, the second average value is obtained by dividing the sum of the memory values ​​used in each wash by the set number of washes.

[0151] S908, The processor determines that the second memory value is a value that is a second average value multiplied by a second ratio.

[0152] S909: If the processor determines the first memory value as the personalized memory value of the current clothing processing device when the first memory value is greater than or equal to the second memory value corresponding to the current clothing processing device.

[0153] S910: If the processor determines the second memory value as the personalized memory value when the second memory value is greater than the first memory value.

[0154] S911. When the processor determines that it has received the operation notification information of the current clothing processing device, it allocates memory for the current clothing processing device according to the personalized memory value.

[0155] S912, the processor determines the operating mode selected by the current clothing processing equipment for this operation based on the operation notification information.

[0156] S913: The processor obtains the basic program information corresponding to the selected operating mode from the basic program information of each operating mode corresponding to the current clothing processing equipment.

[0157] S914: The processor configures the current garment processing equipment based on the basic program information corresponding to the operating mode selected for this operation.

[0158] S915: After determining the personalized memory value of the current garment processing device, the processor obtains the memory value used by the current garment processing device during each washing process.

[0159] S916. When the processor detects that the memory value used by the current clothing processing device during the current washing process is greater than the personalized memory value multiplied by the third ratio, it allocates memory corresponding to the rated maximum memory value of the current clothing processing device to the current clothing processing device in the subsequent stages of the current washing process.

[0160] S917. If the processor finds that there are a first set number of values ​​in the memory used during each washing process of the current clothing processing device that are greater than a set threshold, it determines the sum of the values ​​greater than the set threshold and the second set number of personalized memory values.

[0161] S918. The processor divides the sum of the value greater than the set threshold and the second set number of personalized memory values ​​by the third set number to obtain a new personalized memory value.

[0162] S919: When the processor determines that it has received a memory allocation request from the current clothing processing device, it allocates memory to the current clothing processing device according to the new personalized memory value.

[0163] Optional, such as Figure 10 As shown, based on the memory values ​​used by the current garment processing equipment for each wash within a set interval, the first memory value is determined, including:

[0164] S1001, The processor determines the sum of the memory values ​​used by the current clothing processing device for each wash within the set interval.

[0165] S1002, The processor divides the sum of the memory values ​​by the total number of washes performed by the current clothing processing device within a set range to obtain a first average value.

[0166] S1003. The processor determines the first memory value based on the first average value.

[0167] like Figure 11 As shown in the embodiments of this application, a cloud memory allocation method for a garment processing device is also provided, including:

[0168] S1101, The processor sends a running notification message to the cloud server;

[0169] S1102, The processor receives memory allocation information sent by the cloud server;

[0170] S1103 The processor runs according to the memory allocation information sent by the cloud server.

[0171] likeFigure 12 As shown in the figure, this application embodiment also provides a clothing processing device, including a memory 1201 and a processor 1202. The memory is used to store a computer program, and the processor is used to execute the computer program to implement the cloud memory allocation method for clothing processing device provided in this application embodiment.

[0172] like Figure 13 As shown, this disclosure provides a cloud server. It includes a memory 1301 and a processor 1302; the memory 1301 and processor 1302 can communicate via a bus 1303. The memory 1301 is used to store computer programs. The processor 1302 is used to execute the computer programs to implement the cloud memory allocation method for clothing processing equipment provided in this application embodiment.

[0173] Optionally, the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps in the method embodiments disclosed in this application can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0174] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the above method embodiments.

[0175] In this embodiment of the application, by determining the personalized memory value of the current clothing processing device based on the first memory value and the second memory value, and then allocating memory to each clothing processing device based on the personalized memory value of each clothing processing device, it is possible to avoid allocating too much memory to each clothing processing device when it is not needed, so that the cloud server can serve more clothing processing devices and meet the needs of more and more operating modes of clothing processing devices.

[0176] The serial numbers in the embodiments of this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0177] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0178] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0179] 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 units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0180] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0181] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. 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 a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0182] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A cloud memory allocation method for clothing processing equipment, characterized in that, include: Determine the first memory value based on the memory value used by the current garment processing equipment for each wash within a set range; Based on the first memory value and the second memory value corresponding to the current clothing processing device, the personalized memory value of the current clothing processing device is determined; Upon receiving the operation notification information of the current clothing processing device, memory is allocated to the current clothing processing device according to the personalized memory value; The step of determining the personalized memory value of the current clothing processing device based on the first memory value and the second memory value corresponding to the current clothing processing device includes: If the first memory value is greater than or equal to the second memory value corresponding to the current clothing processing device, the first memory value is determined as the personalized memory value of the current clothing processing device. If the second memory value is greater than the first memory value, the second memory value is determined as the personalized memory value; Before determining the personalized memory value of the current clothing processing device based on the first memory value and the second memory value corresponding to the current clothing processing device, the method further includes: The second average value is obtained by dividing the sum of the memory values ​​used in each wash by the set number of washes, assuming that the operating mode of the current clothing processing equipment is not repeated in each wash within a set number of washes. The second memory value is determined to be a value that is the second average value multiplied by a second ratio.

2. The cloud memory allocation method for clothing processing equipment according to claim 1, characterized in that, Based on the memory values ​​used by the current garment processing equipment for each wash within a set range, determine the first memory value, including: Determine the sum of memory values ​​used by the current garment processing equipment for each wash within a set interval; The sum of the memory values ​​is divided by the total number of washes performed by the current clothing processing device within a set interval to obtain the first average value; The first memory value is determined based on the first average value.

3. The cloud memory allocation method for clothing processing equipment according to claim 1, characterized in that, The set interval is from the nth wash to the mth wash of the current clothing processing device, where n and m are positive integers greater than 1, and m is greater than n; Based on the memory values ​​used by the current garment processing equipment for each wash within a set range, determine the first memory value, including: Obtain the memory values ​​used for each wash from the nth to the mth wash of the current clothing processing device; The sum of the memory values ​​used for each wash is obtained by adding the sum of the values ​​used for each wash. Determine the difference between m and n, and divide the sum by the difference to obtain the first average value of the memory value used by the current clothing processing device for each wash within the set interval; The first memory value is determined to be the value of the first average value multiplied by a first ratio.

4. The cloud memory allocation method for a garment processing device according to any one of claims 1 to 3, characterized in that, After determining the personalized memory value of the current clothing processing device, the process also includes: During each wash cycle of the current garment processing equipment, obtain the memory value used by the current garment processing equipment; If it is detected that the memory value used by the current clothing processing device during the current washing process is greater than the personalized memory value multiplied by a third ratio, memory corresponding to the rated maximum memory value of the current clothing processing device will be allocated to the current clothing processing device in subsequent stages of the current washing process.

5. The cloud memory allocation method for clothing processing equipment according to claim 4, characterized in that, Also includes: If, during each washing cycle of the current clothing processing equipment, there are a first set number of memory values ​​that exceed a set threshold, the sum of the values ​​exceeding the set threshold and a second set number of personalized memory values ​​is determined; wherein, the set threshold is the value of the personalized memory value multiplied by a fourth ratio, and the second set number is the difference between the third set number and the first set number; The sum of the value greater than the set threshold and the second set number of personalized memory values ​​is divided by the third set number to obtain a new personalized memory value; Upon receiving a memory allocation request from the current clothing processing device, memory is allocated to the current clothing processing device according to the new personalized memory value.

6. The cloud memory allocation method for a garment processing device according to any one of claims 1 to 3, characterized in that, The cloud storage includes basic program information for each operating mode corresponding to each model of clothing processing equipment, personalized memory values ​​for each clothing processing equipment, operating mode information saved in the favorites of each clothing processing equipment, and / or setting information for the display interface of each clothing processing equipment. When it is determined that the current clothing processing equipment operation notification information has been received, the cloud memory allocation method for the clothing processing equipment further includes: The operating mode selected by the current clothing processing equipment for this operation is determined based on the operation notification information; Obtain the basic program information corresponding to the operating mode selected for this operation from the basic program information of each operating mode corresponding to the current clothing processing equipment; Based on the basic program information corresponding to the operating mode selected in this operation, the current clothing processing equipment is configured for operation.

7. The cloud memory allocation method for a garment processing device according to any one of claims 1 to 3, characterized in that, Before determining the first memory value based on the average memory value used by the current garment processing equipment in each wash within a set range, the process also includes: Before setting the interval, when it is determined that the operation notification information of the current clothing processing device has been received, memory is allocated to the current clothing processing device according to the rated maximum memory value corresponding to the current clothing processing device; Upon receiving a factory reset message from the current garment processing device, the number of washes performed on the current garment processing device will be reset to zero.

8. A cloud server, characterized in that, It includes a memory and a processor, the memory being used to store a computer program and the processor being used to execute the computer program to implement the cloud memory allocation method for a garment processing device as described in any one of claims 1 to 7.

9. A cloud memory allocation method for clothing processing equipment, characterized in that, include: Send runtime notification information to the cloud server; Receive memory allocation information sent by the cloud server; It runs based on the memory allocation information sent by the cloud server.

10. A garment processing device, characterized in that, It includes a memory and a processor, the memory being used to store a computer program and the processor being used to execute the computer program to implement the cloud memory allocation method for a clothing processing device as described in claim 9.

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