Washing machine control method and device based on weather information and storage medium

Abstract

The invention provides a washing machine control method and device based on weather information and a storage medium. The method comprises the steps that the weather information of the position where a washing machine is located is obtained; whether a washing program is started or not is judged based on the weather information and first set time; and if the washing program is not started, selectively starting a reservation program or starting the washing program based on the weather information and a second set time. According to the technical scheme, whether the washing program is started or not is intelligently judged by obtaining the weather information of the position where the washing machine is located. Therefore, the problem that a traditional washing machine cannot adaptively adjust a washing program according to weather conditions is solved, and washing under the weather conditions which are not beneficial to airing of clothes is avoided. Besides, the condition that weather becomes good in a short time is considered, the requirement when weather is bad in a long time is also considered, intelligent and self-adaptive clothes washing scheduling is achieved, the clothes washing efficiency is improved, and the user experience is optimized.

Description

Technical Field

[0001] The present invention relates to the field of washing machines, and specifically provides a washing machine control method, a control device and a storage medium based on weather information. Background Art

[0002] In traditional washing machine technology, users need to manually set the washing time and program, and the washing machine itself cannot make adaptive adjustments based on environmental factors such as weather conditions. This leads to a situation where users start the washing program under high humidity, rainy or snowy weather or other environmental conditions that are not conducive to drying clothes, and the clothes cannot be dried within the expected time, causing inconvenience to users.

[0003] Washing machines in the prior art cannot intelligently adjust the washing program and reservation time according to weather information, and cannot maximize the washing efficiency and user experience.

[0004] Accordingly, the art needs a new laundry solution to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects, the present invention is proposed to provide a solution or at least partially solve the technical problem that the washing machine in the prior art cannot wash in consideration of weather reasons.

[0006] In a first aspect, the present invention provides a washing machine control method based on weather information, the method comprising: obtaining weather information of the location of the washing machine; determining whether to start a washing program based on the weather information and a first set time; if the washing program is not started, selectively starting a reservation program or starting the washing program based on the weather information and a second set time.

[0007] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, the determination of whether to start the laundry program based on the weather information and the first set time includes: predicting a first probability of drying within the first set time based on the weather information; if the first probability is greater than or equal to a preset first probability threshold, starting the laundry program.

[0008] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, predicting the first probability of drying within a first set time based on the weather information includes: inputting the weather information and the first set time into a trained neural network to obtain a first probability.

[0009] As an alternative or supplement to the above solution, in a method according to an embodiment of the present invention, the neural network is a deep feedforward neural network.

[0010] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, the selectively starting the reservation program or the laundry program based on the weather information and the second set time includes: judging whether there is no weather suitable for drying within the preset second set time based on the weather information; if there is no weather suitable for drying within the preset second set time, starting the laundry program; if there is weather suitable for drying within the preset second set time, starting the reservation program.

[0011] As an alternative or supplement to the above scheme, in a method according to an embodiment of the present invention, the starting reservation program includes: obtaining the most suitable time period for drying clothes within the second set time based on weather information; and controlling the washing machine to start the washing program based on the time period.

[0012] As an alternative or supplement to the above solution, in a method according to an embodiment of the present invention, the reservation procedure includes: sending a reservation laundry information to the user

[0013] As an alternative or supplement to the above solution, in a method according to an embodiment of the present invention,

[0014] In a second aspect, a control device is provided, which includes a processor and a storage device, wherein the storage device is suitable for storing multiple computer programs, and the computer programs are suitable for being loaded and run by the processor to execute the washing machine control method based on weather information described in any one of the technical solutions of the above-mentioned washing machine control method based on weather information.

[0015] In a third aspect, a computer-readable storage medium is provided, which stores a plurality of computer programs, wherein the computer programs are suitable for being loaded and run by a processor to execute the washing machine control method based on weather information as described in any one of the technical solutions of the above-mentioned washing machine control method based on weather information.

[0016] In a fourth aspect, a washing machine is provided, comprising a control device, wherein the control device operates to execute the washing machine control method based on weather information as described in any one of the technical solutions of the above-mentioned washing machine control method based on weather information.

[0017] The above one or more technical solutions of the present invention have at least one or more of the following Beneficial effects:

[0018] In the technical solution of the present invention, by obtaining the weather information of the location of the washing machine, it is intelligently determined whether to start the laundry program. This is intended to solve the problem that traditional washing machines cannot adaptively adjust the laundry program according to weather conditions, and avoid washing clothes under weather conditions that are not conducive to drying. If the laundry program is not started, this technology will selectively start the reservation program or directly start the laundry program based on the weather information, taking into account both the situation of short-term improvement in weather and the needs of long-term bad weather, realizing intelligent and adaptive laundry scheduling, improving laundry efficiency, and optimizing user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The disclosure of the present invention will become more easily understood with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. In addition, similar numbers in the figures are used to represent similar components, among which:

[0020] Figure 1 is a schematic flow chart of main steps of a method for controlling a washing machine based on weather information according to an embodiment of the present invention;

[0021] Figure 2 is a flowchart of the secondary steps of a washing machine control method based on weather information according to an embodiment of the present invention;

[0022] Figure 3 1 is a flow chart of the secondary steps of a washing machine control method based on weather information according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] Some embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0024] In the description of the present invention, "module" and "processor" may include hardware, software or a combination of the two. A module may include hardware circuits, various suitable sensors, communication ports, and memories, and may also include software parts, such as computer programs, or a combination of software and hardware. The processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. The processor has data and / or signal processing functions. The processor may be implemented in software, hardware, or a combination of the two. Non-temporary computer-readable storage media include any suitable medium that can store computer programs, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one A or B" or "at least one of A and B" has a similar meaning to "A and / or B", and may include only A, only B, or A and B. The singular terms "one" and "the" may also include plural forms.

[0025] See attached Figure 1 , Figure 1 FIG. 1 is a flow chart showing the main steps of a method for controlling a washing machine based on weather information according to an embodiment of the present invention. Figure 1 As shown, the washing machine control method based on weather information in the embodiment of the present invention mainly includes the following steps S10 to S30.

[0026] Step S10: Obtain weather information at the location of the washing machine.

[0027] In this embodiment, the weather information includes current weather information and weather forecast information, wherein the current weather information includes weather condition information at the current moment, and the weather forecast information is the weather condition information predicted for a period of time in the future.

[0028] In one embodiment, first, the control system of the washing machine determines the geographical location of the washing machine.

[0029] In this embodiment, geographic location information is obtained by pairing with a mobile phone and a built-in GPS module of the mobile phone. Specifically, the user pairs his smart phone with the washing machine. The pairing process can be completed in various ways, such as through Bluetooth, Wi-Fi or a proprietary pairing protocol. In this process, preferably, in this embodiment, the user downloads and installs a corresponding application on the mobile phone, and this application can communicate with the washing machine and obtain control of the washing machine.

[0030] After the washing machine and the phone are successfully paired, the application can access the phone's GPS module or other location services. The location information obtained by the phone through its built-in GPS module or network location services is usually more accurate, so the washing machine can obtain more accurate location information. Once the phone obtains the location information, the application can transmit this information to the washing machine. After the washing machine receives the location information, it stores it on the internal storage device for later use. This information will be used by the washing machine to obtain corresponding weather information or for other functions that use location information.

[0031] After that, the system needs to connect to a network service that can provide weather information. To do this, you first need to ensure that the washing machine can access the Internet and access the network service that provides weather information. This step may require the user to connect the washing machine to a local Wi-Fi network, or the washing machine may have a module that can access the mobile network. The setting of this network access capability depends on the design and configuration of the washing machine.

[0032] Once the washing machine is successfully connected to the Internet, its control system can begin communicating with the weather information provider. This communication is done through an application or built-in software developed specifically for the washing machine control system. The software sends a request to a designated weather information provider (such as the National Weather Service's web service or a commercial weather forecast service) to obtain current and predicted weather information for the location of the washing machine. This information typically includes temperature, humidity, wind speed, and probability of rainfall.

[0033] After receiving the returned weather information, the washing machine control system needs to parse and process it for subsequent decision-making operations. This includes parsing the returned data packets, extracting useful information from them, converting weather parameters such as temperature and humidity into a format that the washing machine control system can recognize and process, and converting some weather information into a format that is more in line with user preferences based on user settings, such as converting temperature units from Celsius to Fahrenheit.

[0034] In this embodiment, preferably, the part of the washing machine control system design data processing is stored in the cloud server. The role of the cloud server is to manage and process location information and weather information requests, and use the processed weather information to make subsequent laundry decisions according to the request. At the same time, the cloud server can also provide services for multiple washing machines, share processing and storage resources, and improve efficiency and reliability.

[0035] Step S20: determining whether to start the washing program based on the weather information and the first set time.

[0036] In this embodiment, the system predicts the drying conditions of clothes in the next period of time based on the acquired weather information.

[0037] In one embodiment, the system will take into account factors such as temperature, humidity, dust and rainfall probability to make a rough estimate of the drying time of clothes. Specifically, in this embodiment, it is determined whether to start the washing program through steps S201-S202. Figure 2 As shown, the details are as follows:

[0038] Step S201: predicting a first probability of drying within a first set time based on weather information.

[0039] In this embodiment, the first set time may be a time preset by the manufacturer or a time defined by the user.

[0040] In one embodiment, the first set time is a time window, for example, a time window is: within the next 24 hours. When selecting the set time, the conventional requirements of the ordinary washing process and the clothes drying are taken into consideration, and it can be set as adjustable in the user interface. Then, the weather forecast information obtained in the previous step is used to perform a probability prediction.

[0041] In this embodiment, preferably, the weather information and the first set time are input into a trained neural network to obtain a first probability.

[0042] Here is a detailed description: First, the washing machine control system will collect and combine various weather information into a standardized input vector. This weather information may include factors such as current and predicted temperature, humidity, wind speed, and precipitation probability, all of which may affect the drying time of clothes. Specifically, temperature and wind speed usually have a positive effect on drying time, because the higher the temperature and the faster the wind speed, the faster the clothes will dry. However, humidity and precipitation probability usually have a negative impact on drying time, because the higher the humidity and the greater the probability of precipitation, the slower the clothes will dry.

[0043] At the same time, the washing machine control system also needs to obtain a first set time. Specifically, the washing machine control system can set a time window, such as the next 24 hours, and this time window will be encoded as a standardized input value. In this preferred embodiment, the user can be allowed to set and adjust this set time in a user interface according to the user's habits and needs.

[0044] Next, the washing machine control system sends the sorted and combined input vectors to the pre-trained neural network model, which processes these inputs, performs complex nonlinear transformations through the neurons and activation functions of the hidden layer, and finally produces a predicted value in the output layer.

[0045] This prediction value represents the probability of whether the clothes can be dried within the set time. This probability value is called the first probability, which is a value between 0 and 1, where 0 means that the clothes cannot be dried within the set time, and 1 means that the clothes can definitely be dried within the set time. This first probability will be stored by the washing machine control system for use in subsequent steps.

[0046] In this embodiment, a specific neural network is given. Preferably, in this embodiment, a deep feedforward neural network is used. A deep feedforward neural network is also called a multilayer perceptron (MLP). A deep feedforward neural network is mainly composed of an input layer, a hidden layer, and an output layer, which are described separately here.

[0047] Input layer: The input layer is used to receive and process the weather information and the first set time obtained by the washing machine control system. This information is preprocessed into a format that can be understood and operated by the neural network. Specifically, since neural networks are generally more sensitive to input data within this range, they can be better learned and optimized. Therefore, weather information, including temperature, humidity, wind speed, and rainfall probability, needs to be standardized to values ​​between 0 and 1. The set time (for example, the next 24 hours) is also encoded into a suitable numerical value to reflect its importance in the neural network. These preprocessed data sets form a one-dimensional input vector, which is ready for subsequent calculations of the neural network.

[0048] Hidden layer: The goal of the hidden layer is to learn and extract meaningful features from the input data, which helps to understand the complex relationship between weather information and laundry time. The hidden layer may contain multiple neurons and multiple levels, depending on the complexity of the input data and the difficulty of the problem to be solved. For this problem, at least one hidden layer is required to ensure that there is enough ability to capture the deep relationships and patterns in the input data. In addition, in order to prevent the model from overfitting the data during training, techniques such as Dropout or regularization may be used in the hidden layer to limit the complexity of the model by randomly discarding some neurons or adding regularization terms.

[0049] Output layer: The output layer is the last layer of the neural network, and its main task is to generate the prediction results of the neural network. In this problem, the output layer has only one neuron, which outputs a value between 0 and 1, which represents the probability of the clothes being dried within a given set time. This probability value directly affects the decision of the washing machine control system whether to start the washing program, so its accuracy is crucial.

[0050] In summary, in this embodiment, the deep feedforward neural network is used to successfully integrate the washing machine control system and the acquired weather information, providing an effective tool for solving the problem of how weather information affects laundry decisions. Moreover, this structure also enables the washing machine control system to learn and optimize based on continuously updated and accumulated data, further improving the accuracy of its decision-making and the user experience.

[0051] Step S202: If the first probability is greater than or equal to a preset first probability threshold, the washing process is started.

[0052] In this embodiment, the first probability threshold is a preset probability threshold used to determine whether to start the washing program under the first probability.

[0053] In one embodiment, the first probability refers to the possibility that the clothes can be dried within a set time under given weather conditions. The preset first probability threshold is a set value, such as 0.5. This threshold can be regarded as a decision boundary for determining whether to start the laundry program.

[0054] When the first probability is greater than or equal to the preset first probability threshold, it means that the possibility that the clothes can be dried is high under the given weather conditions and the set time. In this case, the control system of the washing machine will decide to start the washing program. Starting the washing program may include starting the power of the washing machine, selecting a preset washing mode, filling water, adding detergent, starting the washing cycle, etc.

[0055] If the first probability is less than the preset first probability threshold, it means that the clothes may not be dried under the given weather conditions and the set time. In this case, the control system of the washing machine will not start the washing program, but will enter the next step to make a more in-depth judgment and schedule a subsequent washing task.

[0056] Step S30: If the washing program is not started, the reservation program or the washing program is selectively started based on the weather information and the second set time.

[0057] In one embodiment, the control system will continue to analyze weather forecast information, including factors such as temperature, humidity, and precipitation probability in the next few days, to determine whether there is a suitable drying time in the future (within the second set time). For example, if it is predicted that it will continue to rain in the next week, the system will choose to directly start the washing program even if the washing conditions are not optimal. If it is predicted that there will be good weather in the short term in the future, the system may choose to start the reservation program and preset the washing time during the predicted good weather period.

[0058] In this embodiment, the reservation process or the washing process is started through steps S301-S303. Figure 3 As shown, the details are as follows:

[0059] Step S301: determining whether there is no weather suitable for drying within a preset second set time based on weather information.

[0060] In one embodiment, the system analyzes the predicted weather conditions at future time points (e.g., every hour or every half day), including temperature, humidity, and precipitation probability. This information has been obtained through the network service in the previous step and converted into a data format suitable for processing.

[0061] Secondly, for each predicted time point, the system needs to determine whether the weather at this time point is suitable for drying clothes. For example, if the predicted temperature at a time point is higher than a certain threshold (e.g., 20 degrees Celsius), the humidity is lower than a certain threshold (e.g., 60%), and the probability of precipitation is lower than a certain threshold (e.g., 10%), then this time point may be judged to be suitable for drying clothes.

[0062] If at least one time point that is judged to be suitable for drying clothes is found within the second set time, the system will record this information and perform further processing in the next step. If no suitable time point is found, the system will directly enter step S302 to start the washing program. The second set time is greater than the first set time.

[0063] Step S302: If there is no weather suitable for drying within the preset second set time, the washing process is started.

[0064] Step S303: If the weather is suitable for drying within the preset second set time, the reservation procedure is started.

[0065] In this embodiment, the scheduled program is a special automatic washing program, which automatically starts the washing process at a preset time.

[0066] In one embodiment, the control system predicts the most suitable time period for drying the clothes within the second set time based on data obtained from weather information.

[0067] Next, the washing machine is controlled to start the washing program based on the time period. Specifically, the system will calculate when the washing process should start based on the predicted optimal drying time and the time required for washing and drying. For example, if tomorrow afternoon is expected to be the best time to dry clothes, and washing and drying will take a total of 3 hours, the system will be set to start washing 3 hours before tomorrow afternoon.

[0068] After starting the reservation process, the system will send the user the reservation laundry information. Specifically,

[0069] After starting the reservation procedure, the washing machine control system sends the reservation information by connecting to the user's mobile device or other network connection device. The reservation information mainly includes the reservation start time, the expected washing cycle, and the expected completion time of the clothes drying. This information will be packaged into concise and easy-to-understand messages and pushed to the user through SMS, email, application notification, etc.

[0070] For example, a notification might be like this: "You have successfully scheduled your laundry. The washing machine will automatically start the laundry cycle at 3 pm today. The laundry cycle is expected to end at 4 pm. Since tomorrow is a sunny day, your clothes should be dry before noon tomorrow." In this way, even if the user is not at the washing machine, they can still know the progress of the laundry and better arrange their time. In addition, if the user changes the scheduled time or other parameters, they can directly operate through the received notification, such as changing the scheduled time, canceling the reservation, etc., which greatly improves the convenience of users and the intelligence of the washing machine.

[0071] When the scheduled time arrives, the washing machine will automatically start the washing process. Before the washing process starts, the system can also send a notification to the user through the interface or the network, so that the user has time to prepare the clothes to be washed.

[0072] If the weather conditions change during the reservation process, the system can adjust the reservation time or start washing directly according to the new weather forecast information. If adjustments are needed, the system will notify the user through the interface or the network.

[0073] Through such a scheduling program, users can wash and dry clothes at the most suitable time, thereby improving laundry efficiency and avoiding drying clothes in unsuitable weather conditions.

[0074] It is understood by those skilled in the art that the present invention implements all or part of the processes in the method of the above embodiment, and can also be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of each of the above method embodiments when executed by the processor. Among them, the computer program includes a computer program, and the computer program can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device, medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium that can carry the computer program. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0075] Furthermore, the present invention also provides a control device. In one embodiment of the control device according to the present invention, the control device includes a processor and a storage device, the storage device can be configured to store a program for executing the washing machine control method based on weather information of the above method embodiment, and the processor can be configured to execute the program in the storage device, which includes but is not limited to the program for executing the washing machine control method based on weather information of the above method embodiment. For ease of explanation, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The control device can be a control device device formed by various electronic devices.

[0076] Furthermore, the present invention also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present invention, the computer-readable storage medium can be configured to store a program for executing the washing machine control method based on weather information of the above-mentioned method embodiment, and the program can be loaded and run by the processor to implement the above-mentioned washing machine control method based on weather information. For ease of explanation, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present invention is a non-temporary computer-readable storage medium.

[0077] Furthermore, the present invention also provides a washing machine, comprising a control device, wherein the control device operates to execute the washing machine control method based on weather information described in any one of the technical solutions of the above-mentioned washing machine control method based on weather information.

[0078] Further, it should be understood that since the setting of each module is only for illustrating the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor itself, or a part of the software in the processor, a part of the hardware, or a part of the combination of software and hardware. Therefore, the number of each module in the figure is only schematic.

[0079] Those skilled in the art will appreciate that the modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principle of the present invention, and therefore, the technical solutions after splitting or merging will fall within the protection scope of the present invention.

[0080] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A washing machine control method based on weather information, characterized in that: include: Obtaining weather information at a location where the washing machine is located; Determining whether to start a laundry program based on the weather information and the first set time; If the washing program is not started, the reservation program or the washing program is selectively started based on the weather information and a second set time, wherein the second set time is greater than the first set time.

2. The washing machine control method based on weather information according to claim 1, characterized in that: The determining whether to start the laundry process based on the weather information and the first set time includes: Predicting a first probability of drying within a first set time based on the weather information; If the first probability is greater than or equal to a preset first probability threshold, the washing program is started.

3. The washing machine control method based on weather information according to claim 2, characterized in that: The predicting of a first probability of drying within a first set time based on the weather information includes: The weather information and the first set time are input into a trained neural network to obtain a first probability.

4. The washing machine control method based on weather information according to claim 3, characterized in that: The neural network is a deep feedforward neural network.

5. The washing machine control method based on weather information according to any one of claims 1 to 4, characterized in that: The selectively starting the reservation program or the laundry program based on the weather information and the second set time includes: Based on the weather information, determining whether there is no weather suitable for drying within a preset second set time; If there is no suitable weather for drying within the preset second setting time, the washing program is started; If the weather is suitable for drying within the preset second setting time, the reservation program is started.

6. The washing machine control method based on weather information according to any one of claims 1 to 4, characterized in that: The start-up reservation procedure includes: Obtaining the most suitable time period for drying clothes within the second set time based on weather information; The washing machine is controlled to start a washing program based on the time period.

7. The washing machine control method based on weather information according to claim 1, characterized in that: The reservation procedure includes: sending laundry reservation information to the user.

8. A control device, comprising a processor and a storage device, wherein the storage device is suitable for storing a plurality of computer programs, characterized in that: The computer program is suitable for being loaded and run by the processor to execute the washing machine control method based on weather information according to any one of claims 1 to 7.

9. A computer-readable storage medium storing a plurality of computer programs, characterized in that: The computer program is suitable for being loaded and run by a processor to execute the washing machine control method based on weather information according to any one of claims 1 to 7.

10. A washing machine, comprising a control device, characterized in that: The control device is operated to execute the washing machine control method based on weather information according to any one of claims 1 to 7.

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