Clothes drying reminder method, device, equipment and storage medium

Abstract

The present application relates to the field of smart home appliances, and in particular to a method, device, equipment and storage medium for reminding clothes to dry. The method includes: when clothes are dried on a clothes drying rack, obtaining the weight difference between the clothes before and after washing; obtaining the light intensity of the environment in which the clothes are located; determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity; when the current drying time of the clothes reaches the drying time threshold, generating a drying completion instruction to prompt the completion of drying of the clothes through the drying completion instruction. The present application cannot recycle clothes in time, resulting in a poor drying effect of clothes.

Description

Technical Field

[0001] The present application relates to the field of smart home appliances, and in particular to a clothes drying reminder method, device, equipment and storage medium. Background Art

[0002] In recent decades, with the rapid development of the domestic economy, the decoration and home furnishing industry has been rapidly developed, among which clothes drying racks have developed rapidly. Since hand-cranked and mobile clothes drying racks have structural defects and few functions, they cannot meet the growing needs of consumers for home intelligence. Smart clothes drying racks have gradually replaced hand-cranked clothes drying racks and entered the lives of every household. Smart clothes drying racks generally integrate value-added functions such as lighting, drying, disinfection, home decoration or safety protection.

[0003] However, in the prior art, users' drying of clothes is a subjective behavior, and clothes are not dried regularly. For example, when users use clothes drying racks to dry clothes, they often forget to collect clothes, which causes the clothes to be on the clothes drying rack for too long and become dirty again. Alternatively, users need to frequently check whether the clothes are dry, or the clothes fade and become damaged due to long exposure to direct sunlight. In short, users can only subjectively check whether the clothes are dry and recycle them, but cannot recycle the clothes in time when the clothes drying effect is the best, resulting in poor clothes drying effect. Summary of the invention

[0004] The present application provides a clothes drying reminder method, device, equipment and storage medium, which are used to solve the problem that clothes cannot be recycled in time, resulting in poor clothes drying effect.

[0005] In a first aspect, an embodiment of the present application provides a method for reminding clothes to dry, comprising: when clothes are dried on a clothes drying rack, obtaining the weight difference between the clothes before and after washing; obtaining the light intensity of the environment in which the clothes are located; determining a drying time threshold corresponding to the clothes based on the weight difference and the light intensity; when the current drying time of the clothes reaches the drying time threshold, generating a drying completion instruction to prompt that the clothes are dried through the drying completion instruction.

[0006] Optionally, before determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity, it also includes: obtaining at least one influencing factor affecting the drying time of the clothes; obtaining at least one factor weight corresponding to the at least one influencing factor; determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity includes: determining the basic drying time corresponding to the clothes according to the weight difference and the light intensity; and obtaining the drying time threshold corresponding to the clothes after weighted processing of the basic drying time by the at least one factor weight.

[0007] Optionally, the influencing factors include at least one of the category, current season information, current geographical area, and current weather information.

[0008] Optionally, the influencing factor is the category to which the clothing belongs; before determining the drying time threshold corresponding to the clothing according to the weight difference and the light intensity, it also includes: obtaining the category to which the clothing belongs; determining the category time weight corresponding to the category; determining the drying time threshold corresponding to the clothing according to the weight difference and the light intensity includes: determining the basic drying time corresponding to the clothing according to the weight difference and the light intensity; obtaining the drying time threshold corresponding to the clothing after weighted processing of the basic drying time by the category time weight.

[0009] Optionally, the category is a material category of the clothing, or a user category corresponding to the clothing.

[0010] Optionally, obtaining the category to which the clothing belongs includes: obtaining an image of the clothing acquired by an image acquisition device; inputting the image into a preset convolutional neural network learning model to obtain the category corresponding to the image output by the convolutional neural network learning model; wherein the convolutional neural network learning model is obtained by training an original convolutional neural network learning model using image sample data, and the image sample data includes M sample images and sample categories corresponding to each of the M sample images, wherein M is an integer greater than 1.

[0011] Optionally, after obtaining the category corresponding to the image output by the convolutional neural network learning model, it also includes: taking the image of the clothing as a sample image and the category corresponding to the image as a sample category, and adding them to the image sample data; using the updated image sample data to train the original convolutional neural network learning model to obtain the latest convolutional neural network learning model.

[0012] In a second aspect, an embodiment of the present application provides a clothing drying reminder device, comprising: a first acquisition module, used to obtain the weight difference of the clothing before and after washing when the clothing is hung on a clothes drying rack; a second acquisition module, used to obtain the light intensity of the environment in which the clothing is located; a threshold determination module, used to determine the drying time threshold corresponding to the clothing based on the weight difference and the light intensity; an instruction generation module, used to generate a drying completion instruction when the current drying time of the clothing reaches the drying time threshold, so as to prompt the completion of the drying of the clothing through the drying completion instruction.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory and a communication bus, wherein the processor and the memory communicate with each other through the communication bus; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to implement the clothing drying reminder method described in the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the clothing drying reminder method described in the first aspect.

[0015] The above technical solution provided by the embodiment of the present application has the following advantages over the prior art: the method provided by the embodiment of the present application determines the drying time threshold corresponding to the clothes by the weight difference before and after washing the clothes, and the light intensity of the environment in which the clothes are located. When the current drying time of the clothes reaches the drying time threshold, a drying completion instruction is generated, and the drying completion instruction is used to prompt that the clothes are dried. In this method, the weight difference before and after washing the clothes indicates the moisture content of the clothes after washing. The light intensity is a factor that directly affects the drying time of clothes. The greater the light intensity, the faster the water on the clothes evaporates, and the shorter the time required for the clothes to dry. The drying time threshold is obtained by the weight difference and the light intensity, and the best recycling time when drying clothes is clarified. Then, when the clothes are dried, the user is prompted to recycle the clothes to avoid the clothes from being dirty or damaged again. At the same time, the user no longer needs to move to the clothes frequently to check, which improves the drying effect of the clothes and provides users with a good user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0018] Figure 1 A schematic diagram of the process steps for implementing the clothes drying reminder method provided in an embodiment of the present application;

[0019] Figure 2 This is a schematic diagram of the structural connection of the clothes drying reminder device provided in an embodiment of the present application;

[0020] Figure 3 This is a schematic diagram of the structural connection of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0022] The clothes drying method provided in the embodiment of the present application is used to remind the user when the clothes are dried. The method is implemented in a device that can obtain and process various data in the method. Preferably, the method is implemented in a smart clothes drying rack, but the scope of protection of the present application is not limited to the specific device type implemented by the method.

[0023] In one embodiment, if Figure 1 As shown, the specific process steps of the clothes drying reminder method are as follows:

[0024] Step 101, when clothes are hung on a clothes drying rack, the weight difference between the clothes before and after washing is obtained.

[0025] In this embodiment, drying clothes mainly involves drying the moisture in the clothes after washing, so that the clothes become dry and comfortable. Specifically, the weight difference between the clothes before and after washing can accurately represent the amount of moisture contained in the clothes, and the weight value of the clothes can be conveniently obtained through a variety of means.

[0026] In a specific example, the process of obtaining the weight difference between clothes before and after washing is obtained through a gravity sensor installed in a washing machine. When a user puts clothes into a washing machine, the washing machine obtains the weight value of the clothes before washing through the gravity sensor; when the washing program of the washing machine ends, the washing machine obtains the weight value of the clothes after washing through the weight sensor. The difference between the weight value of the clothes before washing and the weight value of the clothes after washing is the weight difference.

[0027] In another specific example, the process of obtaining the weight difference between the clothes before and after washing is obtained by a gravity sensor installed in the clothes drying rack. The weight value of the clothes after washing can be obtained by the gravity sensor installed in the clothes drying rack. The weight value of the clothes before washing can be obtained by the washing machine.

[0028] Step 102, obtaining the light intensity of the environment in which the clothes are located.

[0029] In this embodiment, light intensity refers to the energy of visible light received per unit area. Light intensity is an important factor affecting clothes drying. The greater the light intensity, the faster the water on the clothes evaporates, and the shorter the time required for clothes to dry.

[0030] In one embodiment, when obtaining the light intensity of the environment in which the clothes are located, the light intensity of the environment in which the clothes are located is obtained through a light sensor, and the light sensor is based on a photoresistor. The greater the light intensity, the smaller the resistance value of the photoresistor, and the greater the current passing through the photoresistor. The corresponding light intensity can be obtained through the signal output by the light sensor.

[0031] Step 103, determining a drying time threshold corresponding to the clothes according to the weight difference and the light intensity.

[0032] In this embodiment, the corresponding relationship between the weight difference and the light intensity, and the drying time is preset. Through this corresponding relationship, the drying time threshold corresponding to the weight difference and the light intensity is queried. Specifically, the above corresponding relationship can be set according to the principle that the weight difference is positively correlated with the drying time threshold, and the light intensity is negatively correlated with the drying time threshold. For example, when the weight difference is 0.5 kg and the light intensity is 800 lux, the corresponding drying time threshold is 1 hour; when the weight difference is 0.8 kg and the light intensity is 800 lux, the corresponding drying time threshold is 1.5 hours; when the weight difference is 0.5 kg and the light intensity is 1300 lux, the corresponding drying time threshold is 0.5 hours; when the weight difference is 0.8 kg and the light intensity is 500 lux, the corresponding drying time threshold is 2 hours. The corresponding relationship can be set in the form of a numerical corresponding list, or it can be set in the form of a calculated relationship. It should be noted that the above-mentioned corresponding relationship is set according to actual conditions and / or experimental data, and the protection scope of this application is not limited to the setting principles and specific rules of the corresponding relationship.

[0033] In one embodiment, the drying time of clothes is affected by objective factors. The drying time of clothes is adjusted by the influencing factors in the form of weights, so that the obtained drying time threshold can be more accurate. Specifically, before determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity, at least one influencing factor affecting the drying time of clothes is obtained; and at least one factor weight corresponding to the at least one influencing factor is obtained. The drying time threshold corresponding to the clothes is determined according to the weight difference and the light intensity, specifically: according to the weight difference and the light intensity, the basic drying time corresponding to the clothes is determined; after weighting the basic drying time by at least one factor weight, the drying time threshold corresponding to the clothes is obtained.

[0034] In a specific embodiment, at least one influencing factor includes factor 1, factor 2, ..., factor N, where N is an integer greater than 1. The factor weights corresponding to the influencing factors are weight 1, weight 2, ..., weight N. Then, after weighting the basic drying time by at least one factor weight, the drying time threshold corresponding to the clothes can be obtained, which can be calculated by the following formula:

[0035] Drying time threshold = basic drying time × weight 1 × weight 2 × ... × weight N.

[0036] In one embodiment, the influencing factors include at least one of the category, current season information, current geographical area, and current weather information. Factors such as humidity and temperature may also be included.

[0037] In one embodiment, different categories of clothes require different drying times. When the influencing factor is the category to which the clothes belong, before determining the drying time threshold corresponding to the clothes based on the weight difference and light intensity, the category to which the clothes belong is obtained, and the category time weight corresponding to the category is determined; the drying time threshold corresponding to the clothes is determined based on the weight difference and light intensity, specifically: the basic drying time corresponding to the clothes is determined based on the weight difference and light intensity; the basic drying time is weighted by the category time weight to obtain the drying time threshold corresponding to the clothes.

[0038] In a specific embodiment, the category is the material category of the clothing, or the user category corresponding to the clothing.

[0039] In this embodiment, different types of clothes require different amounts of time to dry. For example, moisture in clothes made of silk material evaporates more easily, while moisture in clothes made of pure cotton material evaporates more slowly. In addition, silk clothes are more easily damaged than pure cotton clothes. Therefore, silk clothes require a shorter drying time than pure cotton clothes, and the corresponding time weight set for silk material is smaller than the time weight for pure cotton material.

[0040] For another example, children's clothes need to be drier than adults' clothes and require longer drying time, so the time weight set for children's clothes is greater than the time weight set for adults' clothes.

[0041] In a specific embodiment, the category to which the clothes belong is obtained by image processing technology. Specifically, the image of the clothes is collected by an image acquisition device, and the image acquisition device can be installed at a position where the image of the clothes can be collected. Preferably, the image acquisition device is installed on the smart clothes drying rack, or installed in the surrounding environment of the smart clothes drying rack. After the image acquisition device collects the image of the clothes, the image acquisition device transmits the image of the clothes to the clothes drying rack. The clothes drying rack obtains the image of the clothes collected by the image acquisition device, analyzes and processes the image, and obtains the category to which the processed image belongs.

[0042] In one example, a convolutional neural network learning model is used in the process of analyzing and processing an image. Specifically, an image is input into a preset convolutional neural network learning model to obtain a category to which the image output by the convolutional neural network learning model belongs; wherein the convolutional neural network learning model is obtained by training an original convolutional neural network learning model using image sample data, and the image sample data includes M sample images and sample categories corresponding to each of the M sample images, wherein M is an integer greater than 1.

[0043] Specifically, the training process of the convolutional neural network learning model includes: inputting the sample image into the original convolutional neural network learning model to obtain the predicted categories corresponding to each sample image output by the original convolutional neural network learning model; comparing the predicted category with the sample category, and if they are inconsistent, adjusting the parameters of the original convolutional neural network learning model, and repeating the step of inputting the sample image into the original convolutional neural network learning model until the predicted category is consistent with the sample category, and using the original convolutional neural network learning model as the final convolutional neural network learning model.

[0044] In this embodiment, during the use of the convolutional neural network learning model, the model can be continuously trained to obtain a more accurate category. Specifically, after obtaining the category of the clothing, it also includes: taking the image of the clothing as a sample image and the category as a sample category, adding them to the image sample data; using the updated image sample data to train the original convolutional neural network learning model to obtain the latest convolutional neural network learning model.

[0045] In this embodiment, the image is processed through a convolutional neural network learning model to obtain the accurate category to which it belongs, and the model is continuously learned and trained during use to further improve the accuracy of the model output results and the accuracy of the clothes drying reminder process.

[0046] In one embodiment, even if the light intensity is the same in different seasons, the drying time required for the same piece of clothing is different. For example, the drying time required for the same piece of clothing in winter and summer is different. When the influencing factor is the current season information, before determining the drying time threshold corresponding to the clothing according to the weight difference and the light intensity, the method further includes: obtaining the current season information; determining the season weight corresponding to the current season information; determining the drying time threshold corresponding to the clothing according to the weight difference and the light intensity, specifically: determining the basic drying time corresponding to the clothing according to the weight difference and the light intensity; and obtaining the drying time threshold corresponding to the clothing after weighting the basic drying time by the season weight.

[0047] In this embodiment, the current season information can be obtained remotely through the Internet, and can also be obtained based on the current date information. For example, if the date of the day is December 15, the corresponding current season information is winter, and if the date of the day is August 13, the corresponding current season information is summer. The season weight corresponding to the current season information is pre-set based on actual conditions and / or experimental data. For example, the weight corresponding to summer is 0.5, the weight corresponding to winter is 1.0, the weight corresponding to spring is 0.7, and the weight corresponding to autumn is 0.8. The scope of protection of this application is not limited to the setting method and specific values ​​of the season weights.

[0048] In one embodiment, in different geographical regions, even if the light intensity is the same, the drying time required to dry the same piece of clothing is different. For example, the northern region is drier than the southern region, and the drying time required to dry clothing in the northern region is less than the drying time required to dry clothing in the southern region. When the influencing factor is the current geographical region, before determining the drying time threshold corresponding to the clothing according to the weight difference and the light intensity, the method further includes: obtaining the current geographical region; determining the regional weight corresponding to the current geographical region; determining the drying time threshold corresponding to the clothing according to the weight difference and the light intensity, specifically: determining the basic drying time corresponding to the clothing according to the weight difference and the light intensity; and obtaining the drying time threshold corresponding to the clothing after weighting the basic drying time by the regional weight.

[0049] In this embodiment, the current geographical area can be obtained remotely through the Internet, or the corresponding latitude information can be obtained through a positioning system to determine the corresponding geographical area. Since the clothes drying rack is generally used in the same place, the regional weight is determined once when the clothes drying rack is used for the first time, and there is no need to repeatedly obtain the regional weight when the clothes drying rack is used again until the current geographical area changes.

[0050] In one embodiment, in the same season, the drying time required in different weather conditions is also different. When the influencing factor is the current weather information, before determining the drying time threshold corresponding to the clothes according to the weight difference and light intensity, it also includes: obtaining the current weather information; determining the weather weight corresponding to the current weather information; determining the drying time threshold corresponding to the clothes according to the weight difference and light intensity, specifically: determining the basic drying time corresponding to the clothes according to the weight difference and light intensity; after weighting the basic drying time by the weather weight, obtaining the drying time threshold corresponding to the clothes. The current weather information can be obtained remotely through the Internet.

[0051] In one embodiment, when the influencing factors are the category of the clothing, the current season information, and the current weather information, the final drying time threshold is obtained by the category time weight, the season weight, and the weather weight according to the following calculation formula:

[0052] Drying time threshold = basic drying time × category time weight × season weight × weather weight.

[0053] It should be noted that the weights may also include any one of the factors affecting the drying time, such as temperature, humidity, wind speed, etc. The scope of protection of this application is not limited to the number and content of the weights.

[0054] In the above embodiment, different weights can be used to adjust the drying time threshold according to the degree of influence of different factors, so that the drying time threshold is more in line with the environment in which the clothes are located.

[0055] Step 104, when the current drying time of the clothes reaches the drying time threshold, a drying completion instruction is generated to prompt that the clothes drying is completed through the drying completion instruction.

[0056] In this embodiment, after the drying completion instruction is generated, the user is reminded to recycle the clothes. The reminder method includes but is not limited to voice prompts, text prompts, and screen prompts. The drying completion instruction can also be transmitted to smart terminals such as smart phones and tablets, and the user is reminded to recycle the clothes through the smart terminals.

[0057] Based on the same concept, a clothes drying reminder device is provided in the embodiment of the present application. The specific implementation of the device can refer to the description of the method embodiment part, and the repeated parts will not be repeated. Figure 2 As shown, the device mainly includes:

[0058] The first acquisition module 201 is used to acquire the weight difference between the clothes before and after washing when the clothes are hung on the clothes drying rack;

[0059] A second acquisition module 202 is used to acquire the light intensity of the environment where the clothing is located;

[0060] A threshold determination module 203, configured to determine a drying time threshold corresponding to the clothes according to the weight difference and the light intensity;

[0061] The instruction generation module 204 is used to generate a drying completion instruction when the current drying time of the clothes reaches the drying time threshold, so as to prompt the completion of drying the clothes through the drying completion instruction.

[0062] Based on the same concept, an electronic device is also provided in the embodiment of the present application, such as Figure 3 As shown, the electronic device mainly includes: a processor 301, a memory 302 and a communication bus 303, wherein the processor 301 and the memory 302 communicate with each other through the communication bus 303. The memory 302 stores a program executable by the processor 301, and the processor 301 executes the program stored in the memory 302 to implement the following steps of the clothing drying reminder method described in the above embodiment.

[0063] The communication bus 303 mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus 303 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0064] The memory 302 may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Alternatively, the memory may also be at least one storage device located away from the processor 301 .

[0065] The above-mentioned processor 301 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc., and can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0066] In another embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed on a computer, the computer executes the clothing drying reminder method described in the above embodiment.

[0067] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instruction is loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instruction can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instruction is transmitted from a website site, a computer, a server or a data center by wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, a data center, etc. that contains one or more available media integration. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape, etc.), an optical medium (such as a DVD) or a semiconductor medium (such as a solid-state hard disk), etc.

[0068] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0069] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for reminding clothes to dry, characterized in that: include: When the clothes are hung on the clothes drying rack, the weight difference between the clothes before and after washing is obtained; Obtaining the light intensity of the environment in which the clothing is located; Determining a drying time threshold corresponding to the clothes according to the weight difference and the light intensity; When the current drying time of the clothes reaches the drying time threshold, a drying completion instruction is generated to prompt that the clothes are dried completely through the drying completion instruction; Wherein, before determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity, the method further includes: obtaining at least one influencing factor affecting the drying time of the clothes; obtaining at least one factor weight corresponding to the at least one influencing factor; determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity includes: determining the basic drying time corresponding to the clothes according to the weight difference and the light intensity; obtaining the drying time threshold corresponding to the clothes after weighting the basic drying time according to the at least one factor weight; Among them, at least one influencing factor includes factor 1 to factor N, wherein N is an integer greater than 1, and the factor weights corresponding to each influencing factor are weight 1 to weight N respectively. The basic drying time is weighted by at least one factor weight, and the drying time threshold corresponding to the clothes is calculated by the following formula: Drying time threshold = basic drying time × weight 1 × weight 2 × ... × weight N.

2. The clothes drying reminder method according to claim 1, characterized in that: The influencing factors include at least one of the category, current season information, current geographical area, and current weather information.

3. The clothes drying reminder method according to claim 1, characterized in that: The influencing factor is the category to which the clothing belongs; Before determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity, the method further includes: Obtain the category to which the clothing belongs; Determine the category duration weight corresponding to the category to which the category belongs; The step of determining a drying time threshold corresponding to the clothes according to the weight difference and the light intensity includes: Determining a basic drying time corresponding to the clothes according to the weight difference and the light intensity; After weighting the basic drying time by the category time weight, a drying time threshold corresponding to the clothes is obtained.

4. The clothes drying reminder method according to claim 3, characterized in that: The category is the material category of the clothing, or the user category corresponding to the clothing.

5. The clothes drying reminder method according to claim 1, characterized in that: The obtaining of the category of the clothing includes: Acquire an image of the clothing captured by an image acquisition device; The image is input into a preset convolutional neural network learning model to obtain the category corresponding to the image output by the convolutional neural network learning model; wherein the convolutional neural network learning model is obtained by training the original convolutional neural network learning model using image sample data, and the image sample data includes M sample images and sample categories corresponding to each of the M sample images, wherein M is an integer greater than 1.

6. The clothes drying reminder method according to claim 5, characterized in that: After obtaining the category corresponding to the image output by the convolutional neural network learning model, the method further includes: Taking the image of the clothing as a sample image and the category corresponding to the image as a sample category, and adding them to the image sample data; The updated image sample data is used to train the original convolutional neural network learning model to obtain the latest convolutional neural network learning model.

7. A clothes drying reminder device, characterized in that: include: A first acquisition module, used for acquiring the weight difference between the clothes before and after washing when the clothes are hung on the clothes drying rack; A second acquisition module, used to acquire the light intensity of the environment where the clothing is located; A threshold determination module, used to determine a drying time threshold corresponding to the clothes according to the weight difference and the light intensity; An instruction generating module, configured to generate an instruction for completing the drying of the clothes when the current drying time of the clothes reaches the drying time threshold, so as to prompt the completion of drying of the clothes through the drying completion instruction; Wherein, before determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity, the method further includes: obtaining at least one influencing factor affecting the drying time of the clothes; obtaining at least one factor weight corresponding to the at least one influencing factor; determining the drying time threshold corresponding to the clothes according to the weight difference and the light intensity includes: determining the basic drying time corresponding to the clothes according to the weight difference and the light intensity; obtaining the drying time threshold corresponding to the clothes after weighting the basic drying time according to the at least one factor weight; Among them, at least one influencing factor includes factor 1 to factor N, wherein N is an integer greater than 1, and the factor weights corresponding to each influencing factor are weight 1 to weight N respectively. The basic drying time is weighted by at least one factor weight, and the drying time threshold corresponding to the clothes is calculated by the following formula: Drying time threshold = basic drying time × weight 1 × weight 2 × ... × weight N.

8. An electronic device, characterized in that: include: A processor, a memory and a communication bus, wherein the processor and the memory communicate with each other via the communication bus; The memory is used to store computer programs; The processor is used to execute the program stored in the memory to implement the clothing drying reminder method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the clothing drying reminder method according to any one of claims 1 to 6 is implemented.

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