Control method of smart home system

Abstract

The present application relates to the field of smart home system, and specifically provides a control method of a smart home system, aiming at solving the problem that the existing washing machine cannot accurately judge the material of the laundry to be washed. For this purpose, the smart home system of the present application comprises a laundry processing device and a server, the laundry processing device can communicate with the server, the control method comprises: the laundry processing device acquires a current laundry image and uploads the laundry image to the server; the server receives the laundry image and acquires laundry attribute information based on the laundry image; the server determines the accurate laundry material based on the laundry attribute information and the pre-stored user portrait. Through the above method, the material of the laundry can be accurately obtained, and then the washing machine can match the appropriate washing program and washing parameter, avoiding the phenomenon that the washed laundry is not clean, and even causing the damage of the laundry.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home systems, and specifically provides a control method of a smart home system. BACKGROUND

[0002] With the continuous improvement of living standards, washing machines have entered thousands of households and become a necessity for home life.

[0003] At present, some intelligent washing machines can infer the washing program and parameters through the water absorption of the laundry or the infrared spectrum sensor, but since they cannot accurately determine the material information of the laundry to be washed, there are serious deficiencies in the recommended program and program parameter settings, and the washed laundry may have unclean places, or even cause the laundry to be damaged.

[0004] Based on the above problems, in the prior art, the material of the laundry to be washed is usually preliminarily identified by an image sensor, but due to the limitations of image technology, some materials are still not accurately identified, so accurate material information cannot be obtained.

[0005] Correspondingly, there is a need in the art for a new control method of a smart home system to solve the problem that existing washing machines cannot accurately determine the material of the laundry to be washed. SUMMARY

[0006] The present application aims to solve the above technical problems, i.e., to solve the problem that existing washing machines cannot accurately determine the material of the laundry to be washed.

[0007] In a first aspect, the present application provides a control method of a smart home system, the smart home system comprising a laundry processing device and a server, the laundry processing device being capable of communicating with the server, the control method comprising: the laundry processing device acquiring a current laundry image and uploading the laundry image to the server; the server receiving the laundry image and acquiring laundry attribute information based on the laundry image; and the server determining an accurate laundry material based on the laundry attribute information and a pre-stored user profile.

[0008] In the preferred technical solution of the above control method of a smart home system, the laundry attribute information is the laundry material and the laundry type.

[0009] In the preferred technical solution of the above control method of a smart home system, the step of "the server determining an accurate laundry material based on the laundry attribute information and a pre-stored user profile" further comprises: the server determining an accurate laundry material based on the laundry material, the laundry type, the pre-stored user profile, and current weather information.

[0010] In the preferred technical solutions of the control method of the smart home system, after the step of "the server receiving the clothes image and obtaining clothes attribute information based on the clothes image", the control method further comprises the following steps: the server determines whether the clothes material is a pre-stored fuzzy material; the server determines whether the clothes material needs to be corrected based on the determination result; if so, the server corrects the clothes material; the step of "the server determining the accurate clothes material based on the clothes material, the clothes type, the pre-stored user image, and the current weather information" further comprises: when the server needs to correct the clothes material, the server determines the accurate clothes material based on the clothes material, the clothes type, the pre-stored user image, and the current weather information.

[0011] In the preferred technical solutions of the control method of the smart home system, while the server receives the clothes image and obtains clothes attribute information based on the clothes image, the control method further comprises the following steps: the server obtains the number of clothes based on the clothes image.

[0012] In the preferred technical solutions of the control method of the smart home system, after the step of "when the server needs to correct the clothes material, the server determines the accurate clothes material based on the clothes material, the clothes type, the pre-stored user image, and the current weather information", the control method further comprises: the server determines the washing program and the washing parameter based on the accurate clothes material, the clothes type, and the number of clothes, and sends the washing program and the washing parameter to the clothes processing device; the clothes processing device receives the washing program and the washing parameter, and executes the washing function based on the washing program and the washing parameter.

[0013] In the preferred technical solutions of the control method of the smart home system, the step of "the server determining whether the clothes material needs to be corrected based on the determination result" further comprises: if not, the server does not correct the clothes material; after the step of "if not, the server does not correct the clothes material", the control method further comprises: the server determines the washing program and the washing parameter based on the clothes material, the clothes type, and the number of clothes; and sends the washing program and the washing parameter to the clothes processing device; the clothes processing device receives the washing program and the washing parameter, and executes the washing function based on the washing program and the washing parameter.

[0014] In the preferred technical scheme of the control method of the smart home system, before the step of the clothes processing device obtaining the current clothes image, the control method further comprises: the clothes processing device judging whether a user enters a preset range; if yes, the clothes processing device performs the operation of obtaining the current clothes image.

[0015] In the second aspect, the present application further provides a control method of a smart home system, the smart home system comprising a clothes processing device and a server, the clothes processing device being capable of communicating with the server, the control method comprising: the clothes processing device obtaining a current clothes image; and uploading the clothes image to the server, so that the server performs the following operations: the server receiving the clothes image, and obtaining clothes attribute information based on the clothes image; the server determining accurate clothes material based on the clothes attribute information and a pre-stored user portrait.

[0016] In the third aspect, the present application further provides a control method of a smart home system, the smart home system comprising a clothes processing device and a server, the clothes processing device being capable of communicating with the server, the control method comprising: after the clothes processing device obtains a current clothes image and uploads the clothes image to the server, the server receiving the clothes image, and obtaining clothes attribute information based on the clothes image, the server determining accurate clothes material based on the clothes attribute information and a pre-stored user portrait.

[0017] Those skilled in the art can understand that the control method of the present application comprises: the clothes processing device obtaining a current clothes image, and uploading the clothes image to the server; the server receiving the clothes image, and obtaining clothes attribute information based on the clothes image; the server determining accurate clothes material based on the clothes attribute information and a pre-stored user portrait.

[0018] By the method of the server determining accurate clothes material based on the clothes attribute information and a pre-stored user portrait, the material of the clothes can be accurately obtained, and then the washing machine can be matched with appropriate washing program and washing parameters, so as to avoid the clothes being not clean after washing, and even the phenomenon of clothes damage. BRIEF DESCRIPTION OF DRAWINGS

[0019] The preferred embodiments of the present application will be described below with reference to the accompanying drawings, in which:

[0020] Figure 1 is a structural schematic diagram of the smart home system of the present application;

[0021] Figure 2 is a main flowchart of the control method of the smart home system of the present application;

[0022] Figure 3is a logic diagram of one possible implementation of the control method of the smart home system of the present application.

[0023] List of reference signs:

[0024] 1-human body detection module; 2-image acquisition module; 21-camera module; 22-illumination module; 3-controller; 4-communication module; 5-actuator; 6-server. DETAILED DESCRIPTION

[0025] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art will understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the protection scope of the present application. For example, although the present application is described in conjunction with a washing machine, the technical solutions of the present application are not limited thereto, and the smart home system and the control method can obviously be applied to other washing devices such as a clothes dryer, a washer-dryer, a shoe washing machine, and a care machine, and such changes do not deviate from the principles and scope of the present application.

[0026] In addition, it also needs to be explained that, in the description of the present application, unless otherwise explicitly specified and limited, the terms "arrangement", "connection" and the like should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be connected inside two elements. Those skilled in the art can understand the specific meaning of the above terms in the present application according to the specific circumstances.

[0027] As shown in Figure 1 The smart home system of the present application includes a washing machine (not shown) and a server 6, and the washing machine can communicate with the server 6. Specifically, the washing machine includes a human body detection module 1, an image acquisition module 2, a controller 3, a communication module 4, and an actuator 5. The human body detection module 1, the image acquisition module 2, and the actuator 5 are all in communication connection with the controller 3. The controller 3 is in communication connection with the server 6 through the communication module 4. The human body detection module 1 is used to detect whether there is a person within a preset range. The image acquisition module 2 is used to acquire images of clothes. The actuator 5 can execute corresponding washing functions based on the instructions issued by the controller 3.

[0028] The human body detection module 1 is preferably a single or multiple infrared sensor, of course, it can also be a radar sensor or a laser sensor, etc. In addition, the present application does not limit the setting position thereof, for example, it can be arranged on the outside of the shell of the washing machine, etc. As long as it can judge whether there is a person within a preset range, the specific structure and the setting position thereof can be adjusted accordingly.

[0029] The image acquisition module 2 preferably comprises a camera module 21 and an illumination module 22, the camera module 21 can comprise a single or multiple cameras, and the illumination module 22 can comprise a single or multiple illumination lamps, wherein through the setting of the illumination module 22, sufficient light can be provided for the clothes to optimize the shooting environment and improve the shooting image effect, in addition, the cameras and the illumination lamps are preferably multiple to obtain images of different angles of the clothes, so as to facilitate the server 6 to analyze the material and type of the clothes. In addition, the cameras and the illumination lamps can be arranged on the outside of the shell of the washing machine, in this case, when the user holds the clothes close, the illumination lamps provide illumination light, and the cameras shoot the clothes to obtain clear pictures of the clothes, of course, they can also be arranged at the disc seat or the bucket cover of the washing tub, etc., in this case, when the user puts the clothes into the washing tub, the illumination lamps start to provide illumination light for the inside of the washing tub, and the cameras shoot the clothes to obtain clear images, wherein the illumination lamps can be arranged according to the specific position of the cameras, as long as the light emitted by the illumination lamps is within the scanning range of the cameras and the image of the clothes can be obtained, in addition, although the above embodiment is introduced by taking that the image acquisition module 2 comprises the camera module 21 and the illumination module 22, this is not intended to limit the protection scope of the present application, as long as the image of the clothes can be acquired, the setting mode can be adjusted, for example, the image acquisition module 2 can only comprise a camera, etc., which do not deviate from the principles of the present application and are within the protection scope of the present application, in addition, the cameras can be replaced by cameras, etc.

[0030] In addition, the communication module is preferably a wifi module, of course, it can also be a Bluetooth module, a ZigBee module, a "WiFi+access internet router", etc. The server 6 is preferably a cloud server, of course, it can also be a background server, etc.

[0031] As shown in Figure 2 In order to solve the problem that the existing washing machine cannot accurately judge the material of the clothes to be washed, the present application provides a control method of an intelligent home system, which comprises the following steps:

[0032] Step S100: The washing machine acquires a current clothes image and uploads the clothes image to the server.

[0033] Preferably, the timing of the washing machine acquiring the current clothes image is: when the washing machine detects that a user has entered a preset range through a human body detection module, the washing machine acquires the clothes image through an image acquisition module, wherein the preset range can be obtained based on experience value, or based on big data acquisition, etc., after the washing machine acquires the clothes image, the clothes image is uploaded to the server.

[0034] Of course, the timing of the current clothes image acquisition is not limited to this, for example, the washing machine can also start to acquire the current clothes image when it is detected that the barrel cover of the washing machine is opened, wherein the manner of detecting whether the barrel cover is opened includes various manners, for example, a signal switch is arranged on the shell of the washing machine, when the barrel cover is opened, the signal switch is triggered, after receiving the opening signal, it is judged that the barrel cover is opened, etc.

[0035] Step S200: The server receives the clothes image, and acquires clothes attribute information based on the clothes image.

[0036] Preferably, the clothes attribute information includes clothes material and clothes type, that is, after the server receives the clothes image, the server acquires the clothes material and the clothes type based on the clothes image. Of course, the specific content of the clothes attribute information can be adjusted, for example, it can be only the clothes material, or it can be the clothes material, the clothes type and the clothes color, etc. In order to facilitate the introduction, the clothes material and the clothes type will be introduced in the following invention. Specifically, the clothes material can be divided into: chemical fiber, jeans, wool, leather, fur, down. The clothes type can be divided into: down jacket, suit, overcoat, coat, knitwear, T-shirt, shirt, top, long pants, short pants, skirt, dress and jacket. It can be understood that the clothes material and the clothes type can be classified according to different standards, and the present application does not make any limitation thereto.

[0037] The manner in which the server obtains the clothing material and the clothing type based on the clothing image includes various manners, such as the clothing material and the clothing type can be recognized through a pre-trained model, that is, the clothing image is input into the trained model, and then the clothing type and the clothing material are obtained, wherein the model is trained through machine learning, and in the process of machine learning training, the parameters of the algorithm are adjusted based on the obtained multiple sample clothing images, clothing materials and clothing types, so as to optimize the model by adjusting the parameters. As a possible implementation manner, a ResNet101+FCN+FCOS model can be used for recognition, that is, a clothing image dataset is input into a ResNet101 backbone network as an input end, the ResNet101 backbone network extracts a basic feature map of the image, the obtained basic feature map is input into an FCN intermediate layer, the FCN intermediate layer outputs an overall feature map after mutual fusion, and then the overall feature map is input into an FCOS detection model, and then the clothing material and the clothing type are obtained; of course, the clothing material and the category can also be recognized through other manners, such as recognition through an SSD algorithm, a Yolo series algorithm, a CornerNet algorithm and a Detr algorithm. In addition, the clothing quantity can also be taken as the output end of the above-mentioned model, that is, the server can also obtain the clothing quantity based on the clothing image. Of course, the specific method of obtaining the clothing material, the clothing type and the clothing quantity based on the clothing image is not limited in the present application, as long as the clothing material, the clothing type and the quantity can be obtained, and the specific method can be adjusted.

[0038] When the server determines the clothing material and the clothing type based on the clothing image, the server judges whether the clothing material is a pre-stored ambiguous material, and then determines whether the clothing material needs to be corrected based on the judgment result, if the clothing material needs to be corrected, the clothing material needs to be corrected, and if the clothing material does not need to be corrected, the clothing material does not need to be corrected. For example, the pre-stored ambiguous material is chemical fiber, when the clothing material determined based on the clothing image is chemical fiber, the chemical fiber material needs to be corrected, and when the clothing material is leather, the chemical fiber material does not need to be corrected. Of course, the above-mentioned ambiguous material is only exemplary and is not intended to limit the protection scope of the present application, and the specific ambiguous material can be adjusted, such as wool, fur and the like.

[0039] Due to the limitation of the existing image technology, some materials cannot be accurately identified, such as the chemical fiber material mentioned in the above example, specifically, the fine chemical fiber materials and the mixed materials include cotton, hemp, silk, fiber, blended and wool, that is, the chemical fiber material cannot be identified as silk, cotton or blended, etc., and the present application can obtain accurate materials by correcting the fuzzy chemical fiber material, such as the corrected material is silk, and the washing machine can match the washing program based on the corrected silk material, thereby facilitating the reliability of the washing program matched by the washing machine.

[0040] The correction method of the present application is the specific content of step S300.

[0041] Step S300: The server determines the accurate clothing material based on the clothing type, clothing material and pre-stored user portrait.

[0042] It can be understood that the user portrait refers to abstracting the specific information of the user into a label, and using the label to visualize the user image, for example, the user portrait (including family portrait) includes: income level (high, medium, low); consumption frequency (high, medium, low); consumption behavior (net shopping expert, money-saving small wonder, careful calculation); dressing habit (jeans, blended shirt, cotton T-shirt, etc.), of course, the above is only exemplary, and in general, the specific content it includes is not limited to this, and its content can be adjusted.

[0043] Possibly, the user portrait can be obtained based on user input, etc., which can be pre-stored in the server, and the user portrait corresponds to the MAC address of the washing machine, when the washing machine uses the function, the washing machine uploads the MAC address, the server receives the MAC address, and then calls the user portrait corresponding to the MAC address, of course, the MAC address described above is only exemplary, as long as it is the unique identity of the washing machine, the specific way can be adjusted, such as the MAC address can be replaced by a combination of numerical and alphabetical codes, etc., in addition, the user portrait can also be pre-stored in the washing machine, sent to the server by the washing machine, and the server receives the user portrait to determine the accurate clothing material.

[0044] Specifically, the specific implementation of the server determining the accurate clothing material based on the clothing type, clothing material and pre-stored user portrait includes multiple ways.

[0045] For example, a machine learning method can be used, for example, a large number of input data samples (clothing material, clothing type, user portrait) and output data samples (accurate clothing material) are first collected, then a trained prediction model is obtained through XGBoost algorithm model training, and then the user portrait, clothing material and clothing type obtained based on the clothing image of the application are input into the prediction model as data input ends, and then the prediction model outputs the accurate clothing material. Of course, other algorithms can also be used for model training, for example, LightGBM algorithm, etc.

[0046] Alternatively, the server's database has pre-stored mapping relationships between clothing material, clothing type, user portrait and accurate clothing material, and the accurate clothing material can be determined according to the mapping relationship. When the clothing type determined based on the clothing image is a top and the clothing material is chemical fiber, the accurate clothing material can be determined to be blended based on the dressing habit (jeans, blended top, cotton T-shirt, etc.) in the user portrait. Or, when the clothing type determined based on the clothing image is a T-shirt and the clothing material is chemical fiber, the accurate clothing material can be determined to be cotton based on the dressing habit (jeans, blended top, cotton T-shirt, etc.) in the user portrait. Of course, the above is only exemplary, and the content of the user portrait can be adjusted as long as the accurate clothing material can be determined.

[0047] As a more preferred embodiment, the server can determine the accurate clothing material based on the clothing material, clothing type, pre-stored user portrait and current weather information, that is, through the current weather condition, the clothing material can be further distinguished in combination with the clothing type and user portrait, thereby further improving the accuracy of the corrected clothing material. The weather information can be divided into spring, summer, autumn and winter, or it can be the weather forecast information in recent days, such as recent temperature, wind grade, etc.

[0048] Specifically, the specific implementation of the server to determine the accurate clothing material based on the clothing type, clothing material, pre-stored user portrait and current weather information includes multiple methods.

[0049] For example, the above-mentioned machine learning method is used, that is, the input data of the weather information is added to the input end, that is, a large number of input data samples (clothing material, clothing type, user portrait and weather information) and output data samples (accurate clothing material) are first collected, then a trained prediction model is obtained through XGBoost algorithm model training, and then the user portrait, current weather information, clothing material and clothing type obtained based on the clothing image of the application are input into the prediction model as data input ends, and then the prediction model outputs the accurate clothing material.

[0050] Of course, other ways can also be used to obtain the accurate clothing material, such as the server's database pre-storing a mapping relationship between clothing material, clothing type, user portrait, weather information and accurate clothing material, such as the following table:

[0051] Table 1

[0052]

[0053] For example, when the ambiguous material is chemical fiber, the clothing type is a suit, the current weather information is autumn, and the user portrait content includes a high-income group, it can be determined that the accurate clothing material is wool, or when the ambiguous material is chemical fiber, the clothing type is a down jacket, and the weather information is winter, it can be determined that the accurate clothing material is down. Of course, the above table only lists part of the content, and the specific content can be expanded and adjusted.

[0054] When the clothing material is corrected, the server determines the washing program and washing parameter based on the accurate clothing material, the clothing type and the clothing quantity, and sends the washing program and washing parameter to the washing machine; when the clothing material is not corrected, the server determines the washing program and washing parameter based on the uncorrected clothing material, the clothing type and the clothing quantity, and the washing machine receives the determined washing program and washing parameter, and executes the washing function based on the washing program and washing parameter. It can be understood that although the present application is described as determining the washing program and washing parameter at the same time, this does not intend to limit the protection scope of the present application, for example, only the washing program can be determined.

[0055] The specific implementation of the server determining the washing program and washing parameter based on the accurate clothing material / uncorrected clothing material, the clothing type and the clothing quantity includes multiple modes, for example, the server's database pre-stores a mapping relationship between clothing type, clothing material, clothing quantity and washing program and washing parameter, such as the washing program including: down program, children's clothing program, ordinary washing program, etc., and the washing parameter including: washing temperature, washing water quantity and detergent dosage, etc. Specifically, the washing program can be determined according to the clothing type, such as down jacket selecting down program, children's clothes selecting children's clothing program, sportswear selecting ordinary washing program, etc.; the washing temperature can be determined according to the clothing material, such as the washing temperature of wool, cashmere, etc. being 30℃, and the washing temperature of cotton, hemp, etc. being 50℃; the washing water quantity and detergent dosage can be selected according to the clothing quantity, such as 10 pieces of clothing, selecting detergent dosage 30g, and washing water quantity 70L.

[0056] Of course, the washing program and the washing parameter can be determined by using the machine learning method, such as determining the washing program and the washing parameter by using a pre-trained artificial neural network model; in the model establishment, the correlation between the washing program and the washing parameter is determined by the clothes type, the clothes material, and the clothes quantity in the user historical data or in the big data, and the model is continuously optimized by continuously learning and training and adjusting the parameters; and then the clothes type, the clothes material / precise clothes material, and the clothes quantity can be used as the input end of the artificial neural network model, and the washing program and the washing parameter are output.

[0057] After the server determines the optimal washing program and the washing parameter, the server recommends the washing program and the washing parameter to the washing machine, so that the washing machine executes the washing function based on the washing program and the washing parameter.

[0058] In summary, the clothes material, the clothes type, and the clothes quantity are accurately recognized by the image acquisition module, the user only needs to start the washing machine, and the washing machine automatically sets the appropriate washing program and the washing parameter, so that the clothes are not dirty after washing, and the phenomenon of clothes damage is avoided.

[0059] As shown in Figure 3 , the following describes one possible specific embodiment of the present application, which includes the following steps:

[0060] Step S401: control the infrared sensor to be enabled.

[0061] Step S402: determine whether a person enters a preset range? If yes, execute step S403, and if no, return to execute step S401.

[0062] Step S403: obtain a clothes image by using a camera module.

[0063] Step S404: upload the clothes image to a server.

[0064] Step S405: the server identifies the clothes type, the clothes material, and the clothes quantity based on the clothes image.

[0065] Step S406: the server determines whether the clothes material is a fuzzy material? If yes, execute step S407, and if no, execute step S408.

[0066] Step S407: the server determines a corrected clothes material based on the clothes material, the clothes type, current weather information, and a user portrait.

[0067] Step S408: the server recommends a washing program and a washing parameter based on the clothes material, the clothes type, and the clothes quantity, and sends the washing program and the washing parameter to a washing machine.

[0068] Step S409: The washing machine performs a washing function based on the received washing program and washing parameters.

[0069] Those skilled in the art can understand that the above washing machine further comprises some other well-known structures, such as a processor and a memory, etc., wherein the memory includes but is not limited to a random memory, a flash memory, a read-only memory, a programmable read-only memory, a volatile memory, a non-volatile memory, a serial memory, a parallel memory, or a register, etc., and the processor includes but is not limited to a CPLD / FPGA, a DSP, an ARM processor, a MIPS processor, etc. In order not to unnecessarily obscure the embodiments of the present disclosure, these well-known structures are not shown in the drawings.

[0070] Although the steps in the above embodiments are described in the above-mentioned order, those skilled in the art can understand that, in order to achieve the effects of the embodiments, the different steps do not have to be executed in such an order, and can be executed simultaneously (in parallel) or in a reversed order.

[0071] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will all fall within the protection scope of the present application.

Claims

1. A control method of a smart home system, the method comprising: The smart home system includes a clothes processing device and a server, the clothes processing device is capable of communicating with the server, and the control method includes: The clothes processing device acquires a current clothes image and uploads the clothes image to the server; The server receives the clothes image and acquires clothes attribute information based on the clothes image; The server determines an accurate clothes material based on the clothes attribute information and a pre-stored user profile.

2. The control method of the smart home system according to claim 1, wherein The clothes attribute information is a clothes material and a clothes type. 3.The control method of the smart home system according to claim 2, characterized in that, The step of "the server determining an accurate clothes material based on the clothes attribute information and a pre-stored user profile" further includes: The server determines an accurate clothes material based on the clothes material, the clothes type, the pre-stored user profile, and current weather information.

4. The control method of the smart home system according to claim 3, wherein After the step of "the server receiving the clothes image and acquiring clothes attribute information based on the clothes image", the control method further includes the following steps: The server determines whether the clothes material is a pre-stored ambiguous material; The server determines whether the clothes material needs to be corrected based on the determination result; If so, the server corrects the clothes material; The step of "the server determining an accurate clothes material based on the clothes material, the clothes type, the pre-stored user profile, and current weather information" further includes: When the server needs to correct the clothes material, the server determines an accurate clothes material based on the clothes material, the clothes type, the pre-stored user profile, and current weather information.

5. The control method of the smart home system according to claim 4, wherein At the same time of "the server receiving the clothes image and acquiring clothes attribute information based on the clothes image", the control method further includes the following step: The server acquires a clothes quantity based on the clothes image.

6. The control method of the smart home system according to claim 5, wherein After the step of "when the server needs to correct the clothes material, the server determines an accurate clothes material based on the clothes material, the clothes type, the pre-stored user profile, and current weather information", the control method further includes: The server determines a washing program and a washing parameter based on the accurate clothes material, the clothes type, and the clothes quantity, and sends the washing program and the washing parameter to the clothes processing device; The clothes processing device receives the washing program and the washing parameter, and performs a washing function based on the washing program and the washing parameter.

7. The control method of the smart home system according to claim 5, wherein The step of "the server determining whether the clothes material needs to be corrected based on the determination result" further includes: If not, the server does not correct the clothes material; After the step of "if not required, the server does not correct the clothing material", the control method further comprises: The server determines the washing program and washing parameters based on the clothing material, the clothing type and the clothing quantity; and sends the washing program and washing parameters to the clothing treatment device; The clothing treatment device receives the washing program and washing parameters, and performs the washing function based on the washing program and washing parameters. 8.The control method of the smart home system according to claim 1, wherein, Before the step of "the clothing treatment device acquires the current clothing image", the control method further comprises: The clothing treatment device determines whether a user enters a preset range; If yes, the clothing treatment device performs the operation of acquiring the current clothing image. 9.A control method of a smart home system, the method comprising: The smart home system comprises a clothing treatment device and a server, the clothing treatment device can communicate with the server, and the control method comprises: The clothing treatment device acquires a current clothing image; and uploads the clothing image to the server, so that the server performs the following operations: The server receives the clothing image, and acquires clothing attribute information based on the clothing image; The server determines the accurate clothing material based on the clothing attribute information and a pre-stored user portrait. 10.A control method of a smart home system, the method comprising: The smart home system comprises a clothing treatment device and a server, the clothing treatment device can communicate with the server, and the control method comprises: After the clothing treatment device acquires a current clothing image, and uploads the clothing image to the server, the server receives the clothing image, and acquires clothing attribute information based on the clothing image, and the server determines the accurate clothing material based on the clothing attribute information and a pre-stored user portrait.

Images