Clothes drying machine control method and intelligent clothes drying system

Abstract

The present application relates to the technical field of clothes drying machine, and particularly relates to a clothes drying machine control method, wherein when calculating the actual drying time required by clothes drying, the actual drying time required by clothes drying after comprehensive consideration of real-time environment, weather forecast information and month season compensation information based on standard drying time, the influence of real-time environment on clothes drying is considered, so that the actual drying time required by clothes drying calculated can more efficiently dry clothes. Meanwhile, the weather forecast information and the month season compensation information are comprehensively considered, and the influence of future weather on clothes re-moistening is considered. The present application also provides an intelligent clothes drying system comprising a cloud server and a clothes drying machine, and the clothes drying machine control method can be implemented.

Description

Technical Field

[0001] This invention relates to the field of clothes drying rack technology, specifically to a clothes drying rack control method and an intelligent clothes drying system comprising a cloud server and a clothes drying rack. Background Technology

[0002] Most mainstream clothes dryers nowadays have integrated drying functions, so that clothes can be dried in time even in humid environments or rainy weather.

[0003] However, the current smart clothes drying racks mainly control their drying function using the following two methods:

[0004] 1. Controlled according to a preset program. If the user selects the drying function on the main control panel of the clothes dryer or on the APP interface of a terminal device (such as a smartphone or tablet) connected to the clothes dryer, the clothes dryer will dry the clothes according to the set time and temperature. Some dryers offer more detailed options, such as light drying, standard drying, and intensive drying. Light drying aims to remove some moisture from the clothes, making them less prone to odors and bacterial growth; the remaining moisture can be removed through natural light or air circulation. Standard drying is set to a level where the clothes are ready to use, while intensive drying is designed for more humid air by extending the drying time or increasing the drying temperature to overcome the effects of humid air. Regardless of the drying mode selected, the clothes dryer operates according to a fixed time and temperature schedule. This control method, due to the many factors affecting clothing drying, may result in under-drying or over-drying, wasting energy.

[0005] 2. Humidity control based on ambient humidity or clothing humidity detected by a humidity sensor. This involves setting a target humidity level for the clothes before stopping the drying function. This method only focuses on achieving the preset dryness level, without considering how to dry the clothes more effectively or whether environmental factors will cause them to become damp again after reaching the preset dryness level. As a result, although the clothes dryer may dry the clothes to the preset dryness level, they may become damp again when the user actually wants to use them, making them unwearable or causing discomfort. Summary of the Invention

[0006] In view of the problems existing in the prior art, this application provides a clothes drying rack control method to solve the above problems.

[0007] The clothes drying rack control method provided in this application includes the following steps: Data acquisition steps: Obtain the location information of the clothes drying rack and the real-time environmental information of the location of the clothes drying rack; Based on the location information, obtain the weather forecast information for the area where the clothes drying rack is located; Obtain the current date information, and based on the date information and location information, obtain seasonal compensation information; The actual required drying time is determined based on the standard drying time and calculated by combining real-time environmental information, weather forecast information and seasonal compensation information. Control the clothes dryer to dry and care for clothes according to the actual required drying time.

[0008] The clothes drying rack control method provided in this application is based on a preset standard drying time and fully considers the actual indoor environmental factors. The standard drying time setting is based on the ideal drying effect achieved when the weather and humidity are both ideal, resulting in optimal drying efficiency and energy savings. However, since the drying process is affected by various factors, the clothes drying rack control method provided in this application, based on the standard drying time and considering real-time environmental information, obtains the actual required drying time. This overcomes the influence of actual environmental factors on drying and achieves the best drying effect. Furthermore, if the weather remains rainy or humid, the dried clothes may become damp again, causing discomfort when worn. The clothes drying rack control method provided in this application fully considers future weather conditions in calculating the actual required drying time. It adds weather forecast information and seasonal compensation information. When future weather or seasonal climate has an adverse effect on clothes and increases the possibility of clothes becoming damp, the drying time is increased by combining the weather forecast information and seasonal compensation information, so that the clothes are dried more thoroughly. Even if affected by humid weather or rainfall, the clothes can maintain the required dryness for a long time.

[0009] This application also discloses an intelligent clothes drying system, including a cloud server and a clothes drying machine. The cloud server is communicatively connected to the clothes drying machine. The cloud server receives the location information and real-time environmental information of the clothes drying machine; executes the clothes drying machine control method to calculate the actual required drying time, and sends a clothing care instruction containing the actual required drying time to the clothes drying machine. The clothes drying machine performs clothing drying and care according to the clothing care instruction and the actual required drying time.

[0010] The main improvement of the intelligent clothes drying system provided in this application is that the cloud server calculates the actual required drying time by executing a clothes drying control method, and controls the clothes drying machine to perform drying care according to the actual required drying time. The intelligent clothes drying system provided in this application takes into account the influence of actual environmental factors and future weather factors during the drying operation, which can carry out the drying operation more efficiently. At the same time, the dried clothes can also avoid becoming damp again on rainy or humid days.

[0011] Based on the same inventive purpose, this application provides a storage medium, which is a computer-readable storage medium, and stores a computer-executable program thereon. When the computer-executable program is executed by a processor, it implements the above-described clothes drying rack control method. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram of an intelligent clothes drying system provided in an embodiment of this application; Figure 2 This is a schematic flowchart of the clothes drying rack control method provided in the embodiments of this application.

[0014] In the diagram: 100, clothes drying rack; 110, main unit; 120, drying rack; 111, drying module; 112, disinfection module; 130, steel wire rope; 140, transmission mechanism; 200, cloud server. Detailed Implementation

[0015] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0016] It is important to note that terms such as "first," "second," "symmetric," and "array" are used only to distinguish between descriptive and positional descriptions and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features specified with terms such as "first" or "symmetric" may explicitly or implicitly include one or more of that feature; similarly, when the quantity of certain features is not limited by words such as "two" or "three," it should be noted that such features also explicitly or implicitly include one or more features. In this invention, unless otherwise explicitly specified and limited, terms such as "installation," "connection," and "fixation" should be interpreted broadly; for example, they can refer to a fixed connection, a detachable connection, or an integral molding; they can refer to a mechanical connection, a direct connection, a welding connection, or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the accompanying drawings and specific circumstances.

[0017] The technical solution of this application will now be described in detail with reference to the accompanying drawings.

[0018] like Figure 1As shown, this application embodiment provides an intelligent clothes drying system, including a clothes drying machine 100 and a cloud server 200. The cloud server is communicatively connected to the clothes drying machine. The clothes drying machine 100 provided in this application embodiment includes a main unit 110 and a drying rack 120. The main unit 110 is equipped with a motor and a winding device, and also includes a steel wire rope 130. One end of the steel wire rope 130 is fixed to the winding device. Driven by the motor, the winding device can wind the steel wire rope onto the winding wheel of the winding device, or release it from the winding wheel. The other end of the steel wire rope 130 is fixed to the drying rack 120. By controlling the winding and releasing of the steel wire rope 130, the raising and lowering of the drying rack 120 is achieved. The clothes drying rack provided in this application may also include components for other functions, such as a transmission mechanism 140, located at both ends of the main unit 110 and the drying rack 120, which mainly serves to buffer, balance, and protect the drying rack 120 during opening and closing; a memory, located on the main unit, storing executable programs and data related to clothes drying; and a control unit, located on the main unit and communicatively connected to the memory, used to execute the executable programs in the memory, call data from the memory or send data to the memory for storage, and receive control commands from sources such as remote controls, smart terminals, and cloud servers. It also includes a drying module 111 and a disinfection module 112, which are respectively connected to the control unit and operate under the control commands of the control unit. One embodiment of the drying module includes a PTC heater and a fan. The PTC heater is located in the fan's duct and is used to heat the air, which is then blown onto the clothes to be dried by the fan. One embodiment of the disinfection module includes an ultraviolet lamp, which generates ultraviolet light, which is then irradiated onto the clothes to sterilize and disinfect them. The clothes drying rack provided in this application also includes a wireless communication module, through which the main control unit connects to a network. It also includes a temperature and humidity sensor, which can be installed on the main unit; in a preferred embodiment, the sensor is installed on the drying rack. An energy storage unit is also provided on the drying rack, and this unit has electrode contacts. The main unit has electrode connection points that match the electrode contacts. When the drying rack rises to be level with the main unit, the electrode contacts and electrode connection points connect, thereby charging the energy storage unit. The energy storage unit then provides energy to the temperature and humidity sensor. The temperature and humidity sensor is connected to the main control unit via Bluetooth communication, used to send the detected temperature and humidity data to the main control unit. The intelligent clothes drying rack provided in this application, by providing an energy storage unit on the drying rack, can be charged through electrode contacts when the drying rack rises to be level with the main unit. During normal operation of the intelligent clothes drying rack, the energy storage unit supplies power to the temperature and humidity sensor.The intelligent clothes drying rack provided in this application solves the problem of powering the sensors operating on the drying rack, thereby allowing the temperature and humidity sensors to be placed very close to the clothes drying on the rack, enabling more accurate detection of indoor temperature and humidity near the clothes. In this embodiment, a pollen sensor is also installed on the drying rack to detect indoor pollen concentration parameters. Pollen is a strong allergen that can easily cause allergic diseases such as allergic rhinitis, conjunctivitis, and asthma. Pollen particles can adhere to clothing fibers, causing allergic reactions in susceptible individuals upon contact. The pollen sensor is electrically connected to an energy storage unit, which powers the sensor. The pollen sensor is connected to the main control unit of the host computer via a Bluetooth module, thereby transmitting the data detected by the pollen sensor to the main control unit.

[0019] The cloud server 200 acts as the brain of the clothes drying rack, thus solving the problem of insufficient computing power of the main control unit due to limitations in size, energy consumption, and heat dissipation. The cloud server 120 and the clothes drying rack 130 can communicate via the internet or the Internet of Things (IoT). The cloud server 200 can communicate with multiple clothes drying racks, providing computing and decision-making functions for multiple networked racks. The cloud server receives data detected by the clothes drying racks, performs intelligent calculations and decisions, and then sends the decision instructions to the clothes drying racks via the communication module, allowing the racks to perform garment care according to the instructions.

[0020] The intelligent clothes drying system provided in this application includes a cloud server that receives the location information and real-time environmental information of the clothes drying machine; executes the clothes drying machine control method to calculate the actual required drying time, and sends a clothing care instruction containing the actual required drying time to the clothes drying machine. The clothes drying machine then dries the clothes according to the instructions and the actual required drying time. The cloud server further calculates the actual required disinfection time, and the clothing care instruction sent to the clothes drying machine includes both the actual required drying time and the actual required disinfection time. After receiving the clothing care instruction, the clothes drying machine dries the clothes according to the instructions and disinfects them according to the actual required drying time and disinfects them according to the actual required disinfection time.

[0021] Based on the aforementioned intelligent clothes drying system, this application provides a clothes drying rack control method, executed by a cloud server. For example... Figure 2 As shown in the embodiment of this application, the clothes drying rack control method includes the following steps: Data acquisition steps: Obtain the location information of the clothes drying rack and the real-time environmental information of the location of the clothes drying rack.

[0022] In this application, the location information of the clothes drying rack can be obtained in various ways. One embodiment provides that the location information is obtained by setting a positioning module on the clothes drying rack's main unit, such as a Wi-Fi positioning module, which enables city-level location positioning. In a preferred embodiment, during the clothes drying rack's initial setup, a connection is established between the clothes drying rack and a cloud server. At this time, the clothes drying rack's location information can be set. The cloud server can obtain the clothes drying rack's location information through the physical address or IP address of the wireless communication module of the clothes drying rack with which it communicates. By setting the location information by the user, a dedicated positioning module is not required, reducing hardware costs and avoiding problems such as poor signal strength and location drift in balcony environments. Real-time environmental information of the clothes drying rack's location includes indoor temperature, humidity, and pollen concentration, which can be detected and obtained through temperature and humidity sensors and pollen sensors on the clothes drying rack, and then sent to the cloud server.

[0023] Based on the location information, the weather forecast information for the area where the clothes drying rack is located is obtained. Using the detailed location information of the clothes drying rack, the cloud server can obtain accurate real-time weather, and forecasts for the next few hours and the week for that location via third-party weather APIs, such as China Weather Network and Hefeng Weather. This includes temperature, humidity, probability of rainfall, wind speed, and air quality reports. For example, through... In this embodiment of the application, after the cloud server obtains the real-time environmental information of the location of the clothes drying rack and the weather forecast information, it also cleans and aligns the data, including timestamp alignment, format standardization and validity verification of multi-source data from the clothes drying rack and external APIs, to form a unified data frame that can be used by the model.

[0024] Obtain the current date information, and obtain seasonal month compensation information based on the date information.

[0025] The monthly seasonal compensation information is obtained using a lookup table method based on the date and location information. The pre-defined monthly seasonal table in this application provides a base value for each month and typical climate zone. This base value can be determined experimentally and subsequently optimized and modified during process optimization in various specific work processes. An example is shown in the table below:

[0026] And through a simple function Sure.

[0027] The actual required drying time is calculated using the following formula: ; The standard drying time can be determined experimentally. It can be set at the factory or during the initialization of the clothes dryer. It is based on the climate settings of the actual location of the clothes dryer, such as the average temperature and average humidity of a certain region. Then, based on the average temperature and average humidity, the actual drying time required for the clothes dryer's drying module to dry the target clothes from the washing machine's spin state to the standard dryness state under rated power drying operation is measured, such as 60 minutes. This is the real-time environmental compensation coefficient. This is the weather forecast compensation coefficient. This is the seasonal / monthly compensation coefficient.

[0028] Real-time environmental compensation coefficient C real The formula used to quantify the negative impact of the current indoor environment on drying efficiency is as follows: ; The current indoor humidity is between 0 and 1, or between 0 and 100%; the higher the humidity, the slower the evaporation. The ideal humidity for drying is determined experimentally. Current indoor temperature; The ideal drying environment temperature is determined experimentally. β: Humidity weighting coefficient; β: Temperature weighting coefficient, calibrated experimentally, representing the degree of influence of humidity and temperature on efficiency.

[0029] The ideal drying environment humidity and ideal drying environment temperature are reference standards established based on studies of the effects of humidity and temperature. They are "reference benchmarks" used for calibration and calculation, not theoretical limits. For example, in a drying experiment, the initial humidity of the experimental environment is 80%, and the experimental environment temperature is a set value, such as room temperature (25 degrees Celsius). The test examines the effect of environmental humidity on drying efficiency when the drying equipment is operating at its rated power. For instance, it measures the time taken for a sample of clothing to reach the standard dryness level from its initial dryness. Then, by changing the experimental environment humidity and conducting repeated experiments, an ideal drying environment humidity can be determined, such as 40%. When the experimental environment humidity is higher than the ideal drying humidity, the increase in humidity has a significant impact on the actual required drying time. Conversely, when the experimental environment humidity is lower than the ideal drying humidity, the decrease in humidity has no significant impact on the actual required drying time. The experimental determination of the ideal drying temperature can refer to the setting of the ideal drying humidity. If the ideal ambient temperature is determined to be 25 degrees Celsius, when the ambient temperature is higher than 25 degrees Celsius, the effect of the increase in ambient temperature on drying efficiency is significantly weakened, while when the ambient temperature is lower than 25 degrees Celsius, the effect of the decrease in ambient temperature on drying efficiency is significantly enhanced.

[0030] Assuming the current indoor humidity is 60% and the temperature is 20℃, let the RH be... ideal =40%, T ideal =25℃, α=0.5, β=0.3, calculate as: C real =0.5×((60 40) / 40)+0.3×((25 20) / 25)=0.5×0.5+0.3×0.2=0.25+0.06=0.31, which means that the actual required drying time needs to be increased by 31% from the standard drying time.

[0031] The weather forecast compensation coefficient The calculation formula is: ; Among them, short-term coefficient ; : Probability of precipitation in the next n hours, such as 3 hours; determined based on weather forecast.

[0032] : Humidity forecast for the next n hours, e.g., 3 hours; determined based on weather forecast.

[0033] : The safe humidity threshold for storing clothing; determined by experiments, such as 55%, clothing is prone to becoming damp if the value is higher than this.

[0034] Weighting of future precipitation probability; Humidity weighting; e.g., γ1=0.4, γ2=0.3; Long-term coefficient ; The number of days in the weather forecast where the probability of precipitation is greater than 50% in the next 7 days.

[0035] λ: The weight of the trend influence.

[0036] If the weather forecast shows a 70% chance of precipitation in the next 3 hours, the humidity will rise to 75%. There will be 5 cloudy and rainy days this week.

[0037] Let γ1 = 0.4, γ2 = 0.3, RH safe =55%, λ=0.2.

[0038] Calculate: C short =0.4×0.7+0.3×((75 55) / 55)=0.28+0.3×0.36≈0.28+0.11=0.39.

[0039] C long =0.2×(5 / 7)≈0.14.

[0040] Then C forecast =0.39 + 0.14 = 0.53. The system will not only extend the drying time by 53%, but may also increase the dryness target from 95% to 98%, and prompt the user "This week is humid, it is recommended to use the extended mode".

[0041] The clothes drying rack controls the drying process to dry and care for clothes according to the calculated actual required drying time. The drying rack receives clothing care instructions from a cloud server, which include the calculated actual required drying time. Based on the clothing care instructions, the main control unit of the drying rack activates the PTC heater in the drying module and starts the fan to blow heated air onto the clothes until the clothes are dried and cared for according to the actual required drying time.

[0042] The clothes drying rack control method provided in this application does not base the actual required drying time for clothes on a fixed setting or on the detected dryness of the clothes. Instead, it calculates the actual required drying time based on a preset standard drying time, while fully considering the influence of indoor temperature and humidity. The standard drying time is set based on the ideal drying effect achieved when the clothes drying rack is in ideal weather and humidity conditions. That is, if the environment of the clothes drying rack meets ideal conditions, the clothes can be dried efficiently, saving energy. However, since the clothes drying process is affected by various factors, including ambient temperature and humidity, the clothes drying rack control method provided in this application, based on the standard drying time and performing real-time environmental compensation calculations, obtains the actual required drying time that overcomes the influence of ambient humidity and temperature during the actual drying process, achieving the best drying effect. Furthermore, most of the dried clothes are not used immediately but are hung on the drying rack of the clothes drying rack or in a wardrobe. If the air remains consistently rainy or humid, dried clothes will become damp again, causing discomfort when worn. Existing technologies address this by real-time monitoring of the clothes' moisture content; when the detected moisture level exceeds a certain threshold, the clothes are re-dried. While this method solves the problem, frequent switching on and off of the drying function reduces drying efficiency and increases energy consumption. Furthermore, it doesn't prevent clothes from becoming damp after leaving the drying rack. The drying rack control method provided in this application, however, fully considers future weather conditions in calculating the actual drying time. It incorporates weather compensation and seasonal / monthly compensation coefficients. When future weather or monthly climate conditions adversely affect the clothes, increasing the likelihood of dampness, these coefficients are used to extend the actual required drying time, ensuring more thorough drying. Even under humid weather or rainfall, the clothes maintain the required dryness for an extended period. The technical solution provided in this application eliminates the need for frequent checks on the dryness of clothing and frequent activation of the drying function. At the same time, it can maintain the required dryness level for clothing that has already been stored away.

[0043] The clothes drying rack control method provided in this application embodiment also includes a step of calculating the actual required disinfection time. The formula for calculating the actual required disinfection time is as follows: ; The basic time required to achieve the standard sterilization rate; determined based on experimental testing, such as 30 minutes.

[0044] Air quality compensation coefficient; in, ; Indoor PM2.5 real-time concentration; obtained from air quality data in weather forecasts.

[0045] National standard limits; can be set according to national standards.

[0046] Pollen concentration index; η: Control quality weighting coefficient, representing the impact of particulate matter on the difficulty of disinfection; Pollen weighting coefficient indicates the impact of pollen on the difficulty of disinfection; The clothes drying rack also disinfects clothes according to the actual required disinfection time.

[0047] For example, during spring pollen season, PM2.5 levels can be obtained through weather forecasts. in The concentration was 50 μg / m³; the national standard limit (PM2.5_std) was 35 μg / m³ (using the 24-hour average Class I limit in China's "Ambient Air Quality Standard" GB 3095-2012 as a reference); the pollen concentration index was 0.8 (this is a normalized index, ranging from 0 to 1, where 0 indicates no pollen and 1 indicates extremely high concentration, obtained through pollen sensor detection); the particulate matter weighting coefficient η was 0.6. Pollen weighting coefficient θ: 0.4, base duration (T_ster_base): 30 minutes.

[0048] The calculation process is as follows: Calculate the air quality supplement factor: +0.32=0.577.

[0049] Due to the current poor air quality (particulate pollution + pollen allergens), the system believes that the disinfection time needs to be increased by 57.7% to achieve the expected health protection effect.

[0050] Calculate the actual required disinfection time:

[0051] Based on the above calculations, in this specific scenario, the actual required disinfection time in the clothing care instructions output by the cloud server is 47.3 minutes.

[0052] In the data acquisition phase, the pollen concentration of the indoor environment where the clothes dryer is located is obtained through the pollen sensor on the clothes dryer. The pollen concentration, as a type of real-time environmental information, is sent to the cloud server.

[0053] The clothes drying rack control method provided in this application differs from the previous method of disinfecting clothes for a predetermined time. It incorporates PM2.5 levels from air quality monitoring and the pollen concentration in the environment where the clothes drying rack is located. A high PM2.5 level indicates a higher concentration of fine particles in the air, which may carry bacteria and viruses that could adhere to clothing. Therefore, the PM2.5 index is increased to adjust the disinfection time when calculating the actual required disinfection time. A higher PM2.5 index allows for a longer disinfection time, more thoroughly killing bacteria and viruses attached to fine particles. Furthermore, pollen is a typical airborne allergen. For susceptible individuals, pollen attached to clothing can trigger allergic rhinitis, conjunctivitis, asthma, etc., upon skin contact or inhalation. The clothes drying rack disinfection control method provided in this application uses an ultraviolet lamp that generates specific wavelengths of ultraviolet light to destroy the structure of pollen proteins, thus inactivating them and reducing their allergenicity. Pollen concentrations typically increase significantly in spring and autumn. The clothes drying rack control method provided in this application, when an increase in indoor pollen concentration is detected during pollen season, can more thoroughly eliminate pollen by extending the disinfection time, thereby completely removing allergens and providing better protection for people with allergies.

[0054] The clothes drying rack control method provided in this application embodiment further includes a drying parameter optimization step, which records the actual drying effect after the clothes drying rack dries and cares for the clothes according to the calculated actual required drying time, and receives feedback on the drying effect. Based on the recorded drying effect and the feedback drying effect, the compensation coefficient for the actual required drying time is adjusted. Specifically, as follows: Feedback data collection: After the drying process is completed, the actual dryness of the clothes is detected by temperature and humidity sensors. The actual drying effect of the clothes drying machine after drying the clothes for the calculated actual required drying time is recorded. Alternatively, a user satisfaction feedback entry can be reserved to receive user feedback on the drying effect. If the system detects or the user reports that the clothes are not dry enough, the relevant weighting parameters will be automatically adjusted (e.g., the α value will be increased).

[0055] Clothing dryness is both an objectively defined indicator and a subjective experience. For example, user A might find a garment dry enough and comfortable to wear, while user B might find it insufficiently dry and uncomfortable. By receiving user feedback, the system can gradually learn and develop personalized coefficient preferences for each user.

[0056] Based on the same inventive purpose, this application also provides a storage medium, which is a computer-readable storage medium, and stores a computer-executable program thereon. When the computer-executable program is executed by a processor, it implements the above-described clothes drying rack control method.

[0057] Those skilled in the art will understand that all or part of the steps in the methods disclosed above, the functional modules / units in the system, and the devices can be implemented as software, firmware, hardware, and suitable combinations thereof. In hardware implementation, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components. For example, a physical component may have multiple functions, or a function or step may be composed of multiple physical components that work together. Some or all components can be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or hardware, or an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable medium, which may include computer storage media (or non-temporary media) and communication media (or temporary media). As those skilled in the art will understand, the term computer storage media includes volatile and non-volatile data implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other flexible, portable and removable data. Non-removable media. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other storage technologies, CD-ROM, digital versatile disk (DVD) or other optical disc storage, magnetic tape cassettes, magnetic tape, disk storage or other magnetic storage devices, or any other medium used to store desired information and accessible by a computer. Furthermore, communication media typically embody computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information transmission medium, such as those commonly known in the art.

[0058] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in the present invention, and these should all be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for controlling a clothes drying rack, characterized in that, Includes the following steps: Data acquisition steps: Obtain the location information of the clothes drying rack and the real-time environmental information of the location of the clothes drying rack; Based on the location information, obtain the weather forecast information for the area where the clothes drying rack is located; Obtain the current date information, and based on the date information and location information, obtain the monthly seasonal compensation information; The actual required drying time is determined based on the standard drying time and calculated by combining real-time environmental information, weather forecast information and monthly seasonal compensation information. Control the clothes dryer to dry and care for clothes according to the actual required drying time.

2. The method as described in claim 1, characterized in that, The actual required drying time is calculated using the following formula: ； The set standard drying time, The real-time environmental compensation coefficient is obtained based on real-time environmental information. This refers to the weather forecast compensation coefficient obtained based on weather forecast information. This is the seasonal compensation coefficient obtained based on monthly seasonal compensation information.

3. The method as described in claim 2, characterized in that, The real-time environmental compensation coefficient C real The formula used to quantify the negative impact of the current indoor environment on drying efficiency is as follows: ; Current indoor relative humidity; Ideal drying environment humidity; Current indoor temperature; Ideal drying environment temperature; β: Humidity weighting coefficient; β: Temperature weighting coefficient, calibrated experimentally, representing the degree of influence of humidity and temperature on drying efficiency.

4. The method as described in claim 3, characterized in that, The weather forecast compensation coefficient The calculation formula is: Among them, short-term coefficient ; : Probability of precipitation in the next n hours; Humidity forecast for the next n hours; : Humidity threshold for safe storage of clothing; Weighting of future precipitation probability; Humidity weighting; Long-term coefficient ; The number of days in the weather forecast where the probability of precipitation is greater than 50% in the next 7 days; λ: The weight of the trend influence.

5. The method as described in claim 4, characterized in that, The seasonal compensation coefficient is obtained using a lookup table method based on the date and location information: 。 6. The method according to any one of claims 1 to 5, characterized in that, Also includes: Determine the actual required disinfection time, and control the clothes drying machine to disinfect and care for the clothes according to the actual required disinfection time; The formula for calculating the actual required disinfection time is as follows: ； The basic time required to achieve the standard sterilization rate; Air quality compensation coefficient; in, ; Indoor PM2.5 real-time concentration; National standard limits; Pollen concentration index; η: Control quality weighting coefficient, representing the impact of particulate matter on the difficulty of disinfection; The pollen weighting coefficient represents the impact of pollen on the difficulty of disinfection.

7. An intelligent clothes drying system, characterized in that, The system includes a cloud server and a clothes drying rack. The cloud server is communicatively connected to the clothes drying rack. The cloud server receives the location information and real-time environmental information of the clothes drying rack. It executes the clothes drying rack control method according to any one of claims 1 to 5 to calculate the actual required drying time and sends a clothing care instruction containing the actual required drying time to the clothes drying rack. The clothes drying rack performs clothing drying and care according to the clothing care instruction and the actual required drying time.

8. The intelligent clothes drying system as described in claim 7, characterized in that, The cloud server executes the clothes drying machine control method as described in claim 6 to calculate the actual required drying time and the actual required disinfection time, and sends the clothing care instruction containing the actual required drying time and the actual required disinfection time to the clothes drying machine. The clothes drying machine performs clothing drying care according to the clothing care instruction, and performs clothing disinfection care according to the actual required drying time.

9. The intelligent clothes drying system as described in claim 8, characterized in that, The clothes drying rack includes a main unit and a drying rack. The main unit is equipped with a motor and a winding device, as well as a steel wire rope. One end of the steel wire rope is fixed to the winding device, and the other end is fixed to the drying rack. The drying rack is also equipped with an energy storage unit, which has electrode contacts. The main unit has electrode connection points that match the electrode contacts. When the drying rack rises to be flush with the main unit, the electrode contacts and electrode connection points connect. The drying rack is equipped with a temperature and humidity sensor, which is connected to the main control unit via Bluetooth communication to send the detected temperature and humidity data to the main control unit. The drying rack is also equipped with a pollen sensor, which is electrically connected to the energy storage unit and connected to the main control unit of the main unit via a Bluetooth module.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer-executable program is stored on the computer-readable storage medium. When the computer-executable program is executed by a processor, it implements the clothes drying rack control method as described in any one of claims 1 to 6.

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