Intelligent clothes drying machine, adaptive light control method thereof and computer equipment

Abstract

The application relates to an intelligent clothes airing machine and a self-adaptive light control method and computer equipment thereof, and relates to the technical field of smart home control; the method receives multi-dimensional environment sensing data, wherein the multi-dimensional environment sensing data comprises outdoor meteorological data and indoor environment data; the outdoor meteorological data and the indoor environment data are subjected to fusion analysis to determine a current comprehensive environment feature; according to the current comprehensive environment feature, a target light scene mode is matched from a preset light scene mode library; and a light emitting unit of the intelligent clothes airing machine is controlled to output a light effect corresponding to the target light scene mode.Compared with the prior art, the technical scheme of the application realizes self-adaptive matching of a light scene by fusing and analyzing multi-dimensional data of outdoor meteorological conditions and indoor environments, effectively solves the problem that light adjustment in the prior art is disconnected with a real microenvironment, and improves the environment adaptability and intelligent level of light control of the intelligent clothes airing machine.

Description

Technical Field

[0001] This application relates to the technical field of smart home control, and more particularly to a smart clothes dryer and its adaptive lighting control method and computer equipment. Background Technology

[0002] Currently, lighting functionality has become an industry standard for smart clothes drying racks. Existing technology can achieve basic brightness adjustment and switching between fixed color ambient light modes. As a result, the industry's design requirements for the environmental adaptability and intelligence level of clothes drying rack lighting control are gradually increasing.

[0003] However, existing smart clothes drying rack lighting control solutions rely solely on indoor environmental or time information collected by a single sensor as the basis for light adjustment. They switch lights by setting a fixed lighting mode and combining manual operation or simple environmental information triggers, without comprehensively collecting and analyzing outdoor meteorological data and indoor environmental data.

[0004] Because existing technologies lack the ability to integrate and analyze multi-dimensional data on outdoor weather and indoor environment, they cannot form a comprehensive and accurate perception of the overall indoor and outdoor environmental conditions. This directly leads to a serious disconnect between lighting adjustment and the actual microenvironment in which the user is located. Even if changes occur in the outdoor environment, such as sunshine, rain, and sunlight, and affect indoor lighting, the lighting mode cannot make targeted dynamic adaptations and remains in a passive control state, making it difficult to match the user's actual lighting needs. Summary of the Invention

[0005] This application provides an intelligent clothes drying rack and its adaptive lighting control method and computer equipment. By integrating and analyzing multi-dimensional data of outdoor weather and indoor environment, it achieves adaptive matching of lighting scenes, effectively solving the problem of existing lighting adjustment being disconnected from the real microenvironment, and improving the environmental adaptability and intelligence level of the intelligent clothes drying rack's lighting control.

[0006] In a first aspect, this application provides an adaptive lighting control method for a smart clothes drying rack, comprising: receiving multi-dimensional environmental perception data, wherein the multi-dimensional environmental perception data includes outdoor meteorological data and indoor environmental data; performing fusion analysis on the outdoor meteorological data and the indoor environmental data to determine the current comprehensive environmental characteristics; matching a target lighting scene mode from a preset lighting scene mode library according to the current comprehensive environmental characteristics; and controlling the light-emitting unit of the smart clothes drying rack to output the light effect corresponding to the target lighting scene mode.

[0007] In one possible implementation, the step of fusing and analyzing the outdoor meteorological data and the indoor environmental data to determine the current comprehensive environmental characteristics specifically includes: inputting the outdoor meteorological data and the indoor environmental data into a preset rule base; wherein the rule base contains multiple mapping rules, each mapping rule defining a correspondence between outdoor meteorological-indoor environmental combination conditions and comprehensive environmental characteristics; determining whether the outdoor meteorological data and the indoor environmental data satisfy the combination conditions defined in each mapping rule; determining the mapping rule that satisfies the combination conditions as the target mapping rule, and determining the comprehensive environmental characteristics corresponding to the target mapping rule as the current comprehensive environmental characteristics.

[0008] In one possible implementation, the fusion analysis of the outdoor meteorological data and the indoor environmental data to identify the current comprehensive environmental characteristics specifically includes: converting the outdoor meteorological data and the indoor environmental data into feature vectors of a preset dimension; inputting the feature vectors into a pre-trained classification model, wherein the classification model is trained based on multiple historical feature vector samples and corresponding comprehensive environmental feature labels; calculating the probability value of the feature vector corresponding to each comprehensive environmental feature label through the classification model; determining the comprehensive environmental feature label with the highest probability value among the various comprehensive environmental feature labels as the classification result; and determining the current comprehensive environmental characteristics based on the classification result.

[0009] In one possible implementation, the adaptive lighting control method for a smart clothes drying rack provided in this application further includes: detecting the operating status of the smart clothes drying rack and identifying environmental change events based on the multi-dimensional environmental perception data; matching the operating status and the environmental change events with a preset event library to determine a successfully matched target event, wherein the target event includes at least one of a clothesline descent event, a rainfall warning event, a clothes sterilization event, and a clothes drying event; and in response to the target event, executing the linkage control corresponding to the target event.

[0010] In one possible implementation, the step of responding to the target event and executing the linkage control corresponding to the target event specifically includes: when the target event is a clothes drying rack descent event, controlling the light-emitting unit to output the light effect corresponding to the drying auxiliary light mode; when the target event is a rain warning event, controlling the light-emitting unit to output the light effect corresponding to the warning light mode, and controlling the lifting motor of the smart clothes drying rack to perform the clothes drying rack retraction operation within a preset time; when the target event is a clothes sterilization event, controlling the disinfection equipment of the smart clothes drying rack to perform the disinfection operation, and controlling the light-emitting unit to output the light effect corresponding to the disinfection function light mode; when the target event is a clothes drying event, controlling the drying equipment of the smart clothes drying rack to perform the drying operation, and controlling the light-emitting unit to output the light effect corresponding to the drying function light mode.

[0011] In one possible implementation, after matching the target lighting scene mode from a plurality of preset lighting scene modes, the method further includes: receiving the user's physiological state data; determining whether the user is in a preset abnormal physiological state based on the physiological state data; and when it is determined that the user is in the abnormal physiological state, updating the target lighting scene mode to the lighting scene mode corresponding to the abnormal physiological state.

[0012] In one possible implementation, the preset lighting scene mode library contains multiple lighting scene modes, each lighting scene mode having a preset correspondence with at least one comprehensive environmental feature; the step of matching a target lighting scene mode from the preset lighting scene mode library according to the current comprehensive environmental feature specifically includes: querying and selecting a lighting scene mode that matches the current comprehensive environmental feature from the correspondence as the target lighting scene mode according to the current comprehensive environmental feature.

[0013] Secondly, this application provides an intelligent clothes drying rack, comprising: an environmental sensing unit for acquiring multi-dimensional environmental sensing data, wherein the multi-dimensional environmental sensing data includes outdoor meteorological data and indoor environmental data; a control unit connected to the environmental sensing unit and configured to execute the adaptive lighting control method as described in any of the above claims; and a light-emitting unit connected to the control unit for outputting the light effect corresponding to the target lighting scene mode matched by the control unit.

[0014] In one possible implementation, the smart clothes drying rack provided in this application further includes: a physiological data interface for acquiring user physiological state data; the control unit is connected to the physiological data interface for receiving the user's physiological state data.

[0015] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0016] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0017] This application provides an intelligent clothes drying rack, its adaptive lighting control method, and a computer device, which have the following advantages compared with the prior art: The technical solution of this application abandons the existing technology of adjusting lights based on only a single dimension of information. By simultaneously receiving outdoor meteorological data and indoor environmental data, it achieves a comprehensive and accurate perception of the overall indoor and outdoor environmental conditions. Then, it integrates and analyzes the outdoor meteorological data and indoor environmental data to determine the current comprehensive environmental characteristics. It matches the target lighting scene mode corresponding to the current comprehensive environmental characteristics from a preset lighting scene mode library, and controls the light-emitting unit of the smart clothes dryer to output the light effect corresponding to the target lighting scene mode. This allows the lighting adjustment to no longer be limited to fixed modes and passive triggering. It can make targeted dynamic adaptations based on outdoor weather conditions, changes in light intensity, and the actual indoor microenvironment. This makes the lighting control of the smart clothes dryer highly consistent with the user's actual usage scenario, meets the industry's design requirements for the environmental adaptability and intelligence of the clothes dryer's lighting control, and optimizes the user's actual user experience. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0021] Figure 1 This is a flowchart illustrating one embodiment of the adaptive lighting control method for an intelligent clothes drying rack provided in this application; Figure 2This is a structural schematic diagram of one embodiment of an intelligent clothes drying rack provided in this application; Figure 3 This is another structural schematic diagram of an embodiment of an intelligent clothes drying rack provided in this application; Figure 4 This is a schematic diagram of the structure of a computer device provided in this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0024] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0025] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0026] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0027] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]." Example 1, see Figure 1 , Figure 1 This is a flowchart illustrating one embodiment of the adaptive lighting control method for an intelligent clothes drying rack provided in this application, as shown below. Figure 1 As shown, the method includes steps 101-104, as detailed below: Step 101: Receive multi-dimensional environmental perception data, wherein the multi-dimensional environmental perception data includes outdoor meteorological data and indoor environmental data.

[0028] In one embodiment, an environmental sensing unit based on a smart clothes dryer collects multi-dimensional environmental sensing data. The environmental sensing unit includes a local sensor module and a cloud data interface. The local sensor module is integrated on the clothes dryer host and is used to collect indoor environmental data in real time. The cloud data interface is connected to the Internet via a WiFi / Bluetooth module to obtain outdoor meteorological data from a third-party meteorological service platform.

[0029] In one embodiment, the local sensor module includes, but is not limited to, a light sensor and a temperature and humidity sensor; wherein, the light sensor is used to collect indoor ambient light intensity in real time; and the temperature and humidity sensor is used to collect indoor temperature and indoor humidity in real time.

[0030] Preferably, the local sensor module may also be equipped with a particulate matter sensor, which is used to measure indoor particulate matter concentrations such as indoor PM2.5 concentration and indoor PM10 concentration.

[0031] In one embodiment, the indoor environmental data includes, but is not limited to, indoor ambient light intensity, indoor temperature, and indoor humidity.

[0032] Preferably, when the local sensor module is equipped with a particulate matter sensor, the indoor environmental data may further include indoor particulate matter concentration, wherein the indoor particulate matter concentration includes, but is not limited to, indoor PM2.5 particulate matter concentration and indoor PM10 particulate matter concentration.

[0033] In one embodiment, the outdoor meteorological data includes, but is not limited to, real-time meteorological data, ultraviolet index, sunrise and sunset times, and outdoor air quality index; wherein, the real-time meteorological data includes, but is not limited to, rainfall probability, weather phenomena, outdoor temperature, outdoor humidity, and wind direction and speed, and the weather phenomena include sunny, cloudy, rainy, snowy, foggy, etc.; the ultraviolet index includes, but is not limited to, real-time ultraviolet intensity level, and the outdoor air quality index includes, but is not limited to, outdoor PM2.5 particulate matter concentration, outdoor PM10 particulate matter concentration, and ozone concentration; the sunrise and sunset times are the specific times of sunrise and sunset on the same day.

[0034] In one embodiment, the control unit of the smart clothes dryer is connected to the environmental sensing unit and is used to receive multi-dimensional environmental sensing data collected by the environmental sensing unit.

[0035] Specifically, the control unit synchronously initiates local sensor data reading and cloud data interface query operations at a fixed frequency to ensure that the received multi-dimensional environmental perception data is consistent in the time dimension.

[0036] Preferably, the fixed frequency is once every 5 minutes.

[0037] In one embodiment, after receiving the multi-dimensional environmental perception data, the method further includes: preprocessing the multi-dimensional environmental perception data to obtain preprocessed multi-dimensional environmental perception data, wherein the preprocessing includes outlier removal processing, differential filtering processing, and multi-source data fusion and alignment processing.

[0038] In one embodiment, the preprocessing of the multi-dimensional environmental perception data specifically includes: verifying the multi-dimensional environmental perception data based on a preset physical threshold range, identifying data exceeding the physical threshold range or with invalid format as abnormal data, and replacing the abnormal data with historical valid data to obtain first multi-dimensional environmental perception data; performing noise reduction processing on each dimension of the environmental perception data using an appropriate filtering algorithm based on the data change characteristics of each dimension of the first multi-dimensional environmental perception data to obtain second multi-dimensional environmental perception data; performing time alignment on the second multi-dimensional environmental perception data with different acquisition frequencies based on a preset time window, and normalizing the aligned second multi-dimensional environmental perception data to obtain standardized multi-dimensional environmental perception data.

[0039] Specifically, when performing outlier removal, the system presets clear and physically consistent threshold ranges for each dimension of environmental perception data, including outdoor meteorological data and indoor environmental data, as the basis for data validity verification. These thresholds include: indoor light intensity (0-100,000 Lux), indoor temperature (-20℃-60℃), indoor humidity (0%-100%RH), outdoor UV index (0-15), and rainfall probability (0%-100%). After receiving the multi-dimensional environmental perception data, the control unit performs physical threshold verification on each dimension, while also checking for invalid data in non-numerical formats. All data exceeding the preset physical threshold range or in invalid formats are uniformly classified as outlier data. For the identified outlier data, the system discards it directly and automatically retrieves the previously collected valid data for that dimension to replace it. After processing all outlier data, a first set of multi-dimensional environmental perception data without invalid or outlier data is generated.

[0040] Specifically, the data change characteristics include slowly varying parameters and parameters requiring trend prediction. The slowly varying parameters are denoised using a moving average filtering algorithm, while the parameters requiring trend prediction are denoised using a Kalman filtering algorithm.

[0041] Specifically, the control unit first identifies the data change characteristics of each dimension indicator in the first multi-dimensional environmental perception data. For indicators with different characteristics, it uses appropriate filtering algorithms for denoising to eliminate interference from sensor random noise and small fluctuations in data transmission. For slowly varying parameters such as indoor lighting, temperature, and humidity, a moving average filtering algorithm is used, taking the arithmetic mean of the most recent 5-10 samples as the current valid value. For parameters requiring trend prediction in scenarios, such as judging changes in indoor ambient light intensity under sunset mode, a Kalman filter algorithm is used to make optimal estimates based on a state-space model. Even in the event of temporary sensor failure or data loss, it can provide reasonable predictions by combining historical data, ensuring the continuity of data trends. After denoising of all dimensions using the appropriate filtering algorithms, the second multi-dimensional environmental perception data, with higher stability and accuracy, is obtained.

[0042] Specifically, indoor environmental data is collected by local sensors at a sampling frequency of seconds to minutes, while outdoor meteorological data is obtained from a cloud data interface and its update frequency may be 15 minutes to 1 hour. Due to the difference in collection frequencies, the system uses a preset fixed time window of 5 minutes to perform time alignment processing on the second multi-dimensional environmental perception data. For example, the latest valid value of the cloud-based outdoor meteorological data within the fixed time window is used, while the average value of the local indoor environmental data within the fixed time window is used, ensuring consistency in the time dimension for data from different collection frequencies. After time alignment, for indicators with different dimensions such as light intensity, UV index, humidity, and air quality index, a Min-Max normalization algorithm is used to uniformly map the environmental perception data of each dimension to a standard numerical range of 0-1, completely eliminating the impact of dimensional differences on subsequent fusion analysis. This results in standardized multi-dimensional environmental perception data for subsequent environmental feature analysis.

[0043] Step 102: Perform fusion analysis on the outdoor meteorological data and the indoor environmental data to determine the current comprehensive environmental characteristics.

[0044] In one embodiment, the outdoor meteorological data and the indoor environmental data are input into a preset rule base; wherein, the rule base contains multiple mapping rules, each mapping rule defining a correspondence between outdoor meteorological-indoor environmental combination conditions and comprehensive environmental characteristics; it is determined whether the outdoor meteorological data and the indoor environmental data satisfy the combination conditions defined in each mapping rule; the mapping rule that satisfies the combination conditions is determined as the target mapping rule, and the comprehensive environmental characteristics corresponding to the target mapping rule are determined as the current comprehensive environmental characteristics.

[0045] Specifically, the preset rule base is an expert system preset by the control unit of the smart clothes dryer based on the actual usage scenario. It stores multiple independent mapping rules. Each mapping rule predefines a clear combination of outdoor weather and indoor environment conditions, as well as the comprehensive environmental characteristics that uniquely correspond to that combination of outdoor weather and indoor environment conditions.

[0046] Specifically, the mapping rules include at least one of the first mapping rule, the second mapping rule, the third mapping rule, the fourth mapping rule, and the fifth mapping rule.

[0047] Specifically, the first mapping rule is that when the outdoor weather is sunny, the ultraviolet index is greater than the first preset threshold, the indoor light intensity is greater than the second preset threshold, and the current time is between the first preset period after sunrise and the second preset period before sunset, the comprehensive environmental characteristics corresponding to the outdoor meteorological-indoor environment combination conditions are true clear sky characteristics.

[0048] Preferably, the first preset threshold is 5, which indicates that the outdoor ultraviolet intensity level is moderate or above; the second preset threshold is 500 Lux, which indicates that the indoor brightness is high; the current time being between the first preset period after sunrise and the second preset period before sunset means that the current time is between 1 hour after sunrise and 1 hour before sunset.

[0049] Specifically, the characteristics of a realistic clear sky represent bright sunshine outdoors and ample natural light indoors. This should mimic the feeling of sunlight filtering through the clouds.

[0050] Specifically, the second mapping rule is that when the difference between the current time and the sunset time is within a preset range, the outdoor weather is sunny or partly cloudy, and the indoor light intensity shows a continuous downward trend, the comprehensive environmental characteristics corresponding to the outdoor meteorological-indoor environmental combination conditions are the true sunset characteristics.

[0051] Preferably, the preset range is ±15 minutes.

[0052] Specifically, the realistic sunset characteristic represents dusk, when the sky is gradually darkening. At this time, the warm afterglow of the setting sun should be simulated.

[0053] Specifically, the third mapping rule is that when the outdoor weather phenomenon is a preset severe weather type or the outdoor air quality index is greater than the third preset threshold and the indoor light intensity is less than the fourth preset threshold, the comprehensive environmental characteristic corresponding to the outdoor meteorological-indoor environment combination condition is the rainy and cloudy compensation characteristic; wherein, the preset severe weather type includes at least one of cloudy, rain, snow and fog.

[0054] Preferably, the third preset threshold is 150, indicating that the outdoor air quality is at or above the level of light pollution; the fourth preset threshold is 200 Lux, indicating that the indoor air is dim.

[0055] Specifically, the rain compensation feature indicates that a harsh outdoor environment leads to insufficient indoor lighting and a depressing atmosphere. In this case, bright and refreshing compensatory lighting should be provided to simulate the feeling of a sunny day and dispel the user's sense of oppression.

[0056] Specifically, the fourth mapping rule is that when the current time is between sunset and the third preset period of late night, the indoor light intensity is less than the fifth preset threshold, and a user-set leisure mode instruction is received, the comprehensive environmental characteristic corresponding to the outdoor weather-indoor environment combination condition is the aurora characteristic.

[0057] Specifically, the fifth mapping rule is that when the current time is after the third preset period of late night, the indoor light intensity is less than the fifth preset threshold, and the user-set leisure mode instruction is received, the comprehensive environmental characteristic corresponding to the outdoor weather-indoor environment combination condition is the "slightly tipsy" characteristic.

[0058] Preferably, the fourth preset time period at night is 11 PM; the fifth preset threshold is 50 Lux, indicating that only a night light is left on indoors; the user-defined leisure mode command includes, but is not limited to, manually setting to leisure mode or sleep mode via voice / APP.

[0059] Specifically, the leisure characteristics indicate the transition to nighttime relaxation or sleep preparation time. During this period, blue light should be reduced, and soft, dreamy colors with slow, gradual changes should be used.

[0060] Specifically, the control unit will search the mapping rules in the rule base one by one, and determine whether the input outdoor meteorological data and indoor environmental data meet the outdoor meteorological-indoor environmental combination conditions defined by each rule. The judgment process strictly follows the threshold requirements, logical relationships and triggering premises of each indicator in the rule. If any indicator fails to meet the requirements of the mapping rule, the mapping rule will be skipped and the next mapping rule will be searched. Only when all combination conditions in a mapping rule are met will the mapping rule be determined as the target mapping rule.

[0061] In one embodiment, after matching the target lighting scene mode from a plurality of preset lighting scene modes based on the current comprehensive environmental characteristics, the method further includes: receiving the user's physiological state data; determining whether the user is in a preset abnormal physiological state based on the physiological state data; and updating the target lighting scene mode to the lighting scene mode corresponding to the abnormal physiological state when the user is determined to be in the abnormal physiological state.

[0062] Specifically, the pre-defined abnormal physiological state includes at least one of the following: abnormally high heart rate, enhanced skin conductance, high blood pressure, low heart rate, or extremely low activity level.

[0063] Specifically, the physiological data interface of the smart clothes dryer connects to the user's smartwatch, wristband, and other wearable devices via wireless communication methods such as Wi-Fi and Bluetooth to obtain the user's physiological status data in real time. The physiological status data includes, but is not limited to, physiological indicators such as heart rate, skin conductance, blood pressure, and activity level.

[0064] Specifically, the control unit will verify the collected user physiological state data item by item according to the preset judgment criteria to determine whether the user is in a preset abnormal physiological state. For example, the real-time values ​​of each physiological indicator are compared with the preset normal threshold range. If any physiological indicator exceeds the normal threshold, the user is determined to be in the corresponding abnormal physiological state. If all physiological indicators are within the normal threshold range, the user's physiological state is determined to be normal, and the previously matched target lighting scene mode remains unchanged.

[0065] In one embodiment, the target lighting scene mode updated based on the abnormal physiological state has a higher priority than the target lighting scene mode matched based on the comprehensive environmental features.

[0066] Specifically, when the control unit determines that the user is in a preset abnormal physiological state, it will trigger the lighting scene mode update mechanism. According to the priority rule that the user's physiological state takes precedence over environmental features, the original target lighting scene mode matched based on comprehensive environmental features will be discarded, and the lighting scene mode that uniquely corresponds to the abnormal physiological state will be retrieved from the preset lighting scene mode library and updated as the new target lighting scene mode. If an abnormally high heart rate or enhanced skin conductance is detected, indicating a stress state, the lighting scene mode will be updated to a soothing and stress-relieving lighting scene mode. If a user's heart rate is too low or activity level is extremely low, indicating a fatigue state, the lighting scene mode will be updated to a gentle and relaxing lighting scene mode, ensuring that the lighting scene is adapted to the user's current physical and mental state.

[0067] In one embodiment, after matching the target lighting scene mode from a plurality of preset lighting scene modes based on the current comprehensive environmental characteristics, the method further includes: responding to a manual command issued by the user via voice, application, or remote control, and using the lighting scene mode specified by the manual command as the target lighting scene mode.

[0068] In one embodiment, the priority of the target lighting scene mode determined based on the user's manual instructions is higher than the priority of the target lighting scene mode updated based on the abnormal physiological state.

[0069] Specifically, after the control unit matches the target lighting scene mode from the preset lighting scene mode library based on comprehensive environmental characteristics, it will always maintain a real-time listening state for the user's manual control commands. It supports users to issue manual commands to switch lighting scene modes through three mainstream interaction methods: voice, smart device application, and clothes dryer remote control. The basic process of environmental perception and automatic matching is not interrupted throughout the process, taking into account both the intelligent lighting control and the user's autonomous operation needs.

[0070] Specifically, upon receiving a manual command from the user in any way, the control unit will immediately parse the manual command, extract the lighting scene mode specified in the manual command, directly retrieve the lighting scene mode specified by the manual command from the preset lighting scene mode library, and re-determine it as the new target lighting scene mode. At the same time, it will interrupt the current target lighting scene mode based on environmental feature matching or the target lighting scene mode updated based on the abnormal physiological state.

[0071] Specifically, by setting the priority of the target lighting scene mode determined by the user's manual command to the highest priority, which is higher than the priority of the target lighting scene mode updated based on the user's abnormal physiological state, and also higher than the priority of the target lighting scene mode matched based on the current comprehensive environmental characteristics; even if the control unit has updated the current target lighting scene mode to a target lighting scene mode adapted to the user's abnormal physiological state, such as abnormally high heart rate or enhanced skin conductance, the control unit will still unconditionally respond and directly switch to the target lighting scene mode specified by the manual command as long as it receives the user's manual command, so as to fully respect the user's autonomous control wishes and ensure that the user can adjust the lighting scene according to their own needs under any circumstances.

[0072] Step 103: Based on the current comprehensive environmental characteristics, match the target lighting scene mode from the preset lighting scene mode library.

[0073] In one embodiment, the preset lighting scene mode library contains multiple lighting scene modes, and each lighting scene mode has a preset correspondence with at least one comprehensive environmental feature.

[0074] Specifically, multiple lighting scene modes include, but are not limited to, clear sky mode, sunset mode, rainy compensation mode, aurora mode, and tipsy mode.

[0075] Specifically, the Clear Sky mode is used to output lighting effects that mimic clear sky lighting, including: adjusting the color temperature of the main lighting to the preset daytime color temperature value, adjusting the brightness to the preset daytime brightness value, and setting the ambient light to a light blue effect.

[0076] Preferably, in the clear sky mode, the color temperature of the main lighting is adjusted to 6000K (pure white light), and the brightness is set to the highest level to simulate midday sunlight. The ambient lights are controlled to emit a soft, bright, pale blue light, dynamically simulating the depth of the sky. This allows users to feel the sunshine and vitality of the outdoors even when indoors.

[0077] Specifically, the sunset mode is used to output lighting effects that simulate the afterglow of a sunset. Specifically, it includes: gradually transitioning the color temperature of the main lighting from a preset first color temperature value to a preset second color temperature value, while simultaneously gradually reducing the brightness, and slowly transitioning the ambient light from orange to deep red.

[0078] Preferably, in sunset mode, the color temperature of the main lighting gradually transitions from 4000K to 2700K warm yellow light, while the brightness gradually decreases simultaneously; the ambient light slowly transitions from bright orange to deep red, simulating the changing process of the sunset; allowing users to enjoy the beautiful sunset at home and naturally perceive the changes in their day-night rhythm.

[0079] Specifically, the rain compensation mode is used to output lighting effects that provide compensatory illumination. This includes adjusting the color temperature of the main lighting to a preset compensation color temperature value and increasing the brightness to a level higher than normal, while setting the ambient lights to a fresh color scheme. Preferably, in the rainy weather compensation mode, the color temperature of the main lighting is adjusted to 5000K (neutral light), and the brightness is adjusted to a level higher than usual to compensate for insufficient indoor lighting. The ambient light can be controlled to project a light effect that simulates sunlight passing through clouds (bright spots move slowly), or turn on a refreshing mint green / light blue light to relieve the feeling of oppression. This ensures that even on rainy days, the user's home is always bright and fresh, and their mood improves accordingly.

[0080] Specifically, the Aurora mode is used to output a lighting effect with a cool color tone as the main color and colors cycling in a fixed sequence. This includes: adjusting the brightness of the main lighting to the lowest level or turning it off, and controlling the ambient lights to cycle with cool colors in a preset fixed sequence, so that the light effect presents a unidirectional flowing feeling.

[0081] Preferably, in Aurora Mode, the main lighting brightness is adjusted to the lowest level or completely turned off, and the ambient lights are controlled to cycle through cool colors such as green, purple, and pink in a fixed sequence, creating a unidirectional flowing light effect and a dreamy, relaxing atmosphere; allowing users to lie on the sofa as if they are in the polar night sky, and obtain the ultimate relaxation experience.

[0082] Specifically, the "Tipsy Mode" is used to output a lighting effect with a warm color tone as the main color, random color gradient, and light effect that presents a slow breathing and local random fluctuation. Specifically, it includes: adjusting the brightness of the main lighting to the lowest level or turning it off, and controlling the ambient light to change with a warm color tone in a random gradient, with the light effect presenting a slow breathing and local random fluctuation.

[0083] Preferably, in the "Tipsy Mode," the main lighting brightness is adjusted to the lowest level or turned off completely, while the ambient lighting is controlled to randomly and gradually change in warm colors such as orange, red, and pink. The lighting effect presents a hazy feeling of slow breathing and local random fluctuations, creating a tipsy and relaxing atmosphere; allowing users to obtain the ultimate relaxation and sleep aid experience late at night.

[0084] Specifically, the preset correspondences include: real clear sky features corresponding to clear sky mode; real sunset features corresponding to sunset mode; rainy / overcast compensation features corresponding to rainy / overcast compensation mode; aurora features corresponding to aurora mode; and tipsy features corresponding to tipsy mode.

[0085] In one embodiment, based on the current comprehensive environmental characteristics, a lighting scene mode that matches the current comprehensive environmental characteristics is queried from the correspondence and selected as the target lighting scene mode.

[0086] Specifically, the control unit uses the currently determined comprehensive environmental characteristics as the query basis, performs a search operation in the preset correspondence, compares the comprehensive environmental characteristics with the trigger conditions bound to each lighting scene mode, and filters out the lighting scene modes that completely match the current comprehensive environmental characteristics. This search process is a direct table lookup matching, requiring no additional calculation or secondary judgment, and can quickly and accurately locate the target lighting scene mode.

[0087] Specifically, when a lighting scene mode that matches the current overall environmental characteristics is found, the control unit determines the mode as the final target lighting scene mode, thereby achieving precise adaptive matching between the lighting scene and the overall environmental characteristics.

[0088] Step 104: Control the light-emitting unit of the smart clothes drying rack to output the light effect corresponding to the target lighting scene mode.

[0089] In one embodiment, after determining the target lighting scene mode, the control unit sends a mode execution command to the light-emitting unit of the smart clothes drying rack. The command includes standardized light effect parameters such as brightness, color temperature, color, light distribution and working sequence corresponding to the target lighting scene mode. After receiving the mode execution command, the light-emitting unit analyzes the various control parameters and starts the light output process according to preset rules to achieve a light effect presentation that is adapted to the current comprehensive environmental characteristics.

[0090] Specifically, the light-emitting unit maintains a stable output according to the operating logic of the target lighting scene mode. Before receiving new current comprehensive environmental characteristics and a new target lighting scene mode, it continues to maintain the current light effect state. When the current comprehensive environmental characteristics change, or the control unit re-matches or updates the new target lighting scene mode, the light-emitting unit receives the update command and smoothly switches the light effect to avoid visual discomfort caused by sudden changes in light. Ultimately, it achieves adaptive, stable, and scene-specific precise output of light for the smart clothes drying rack.

[0091] In one embodiment, the control unit of the smart clothes drying rack also detects the operating status of the smart clothes drying rack and identifies environmental change events based on the multi-dimensional environmental perception data; matches the operating status and the environmental change events with a preset event library to determine a successfully matched target event, wherein the target event includes at least one of the following: drying rod descent event, rainfall warning event, clothing sterilization event, and clothing drying event; and in response to the target event, executes the linkage control corresponding to the target event.

[0092] Specifically, the rainfall warning event includes calculating the indoor-outdoor temperature difference between outdoor temperature in outdoor meteorological data and indoor temperature in indoor environmental data based on the multi-dimensional environmental perception data; dynamically adapting the corresponding preset rainfall probability threshold according to the comparison result of the indoor-outdoor temperature difference and the preset temperature difference threshold; and determining whether the rainfall probability in the future preset time period is greater than the dynamically adapted preset rainfall probability threshold. If so, a rainfall warning event is triggered.

[0093] Preferably, when the indoor and outdoor temperature difference is not greater than a preset temperature difference threshold, it is determined that the indoor and outdoor air exchange is sufficient and the drying conditions are highly correlated with the outdoor weather. A lower preset rainfall probability threshold is then used to improve the response sensitivity of the rainfall forecast. Otherwise, a default or higher preset rainfall probability threshold may be used.

[0094] Preferably, the preset future time period is 15-30 minutes in the future; the preset rainfall probability threshold is 80%.

[0095] Specifically, the clothing sterilization event includes: determining, based on the multi-dimensional environmental perception data, that the duration of continuous rainy weather exceeds a first preset duration, and the indoor humidity is higher than a first preset humidity threshold.

[0096] Preferably, the first preset duration is 24 hours and the first preset humidity threshold is 70%.

[0097] Specifically, the clothes drying event includes: based on the multi-dimensional environmental perception data, calculating the indoor-outdoor temperature difference between the outdoor temperature in the outdoor meteorological data and the indoor temperature in the indoor environmental data, determining that the indoor-outdoor temperature difference is greater than a preset temperature difference threshold, the outdoor humidity is higher than a second preset humidity threshold, and there is no trend of clearing up within a preset time period.

[0098] Preferably, when the temperature difference between indoors and outdoors exceeds the preset temperature difference threshold, it indicates that the degree of indoor and outdoor air exchange is low, ventilation is poor, and the efficiency of natural drying of clothes is low. Combined with the outdoor high humidity and no clearing conditions, a clothes drying event is triggered.

[0099] Preferably, the first preset humidity threshold is 80%, and the preset future duration is 2 hours in the future.

[0100] In one embodiment, in response to the target event, the linkage control corresponding to the target event is executed, specifically including: when the target event is a clothes drying rack descent event, controlling the light-emitting unit to output the light effect corresponding to the drying auxiliary light mode; when the target event is a rain warning event, controlling the light-emitting unit to output the light effect corresponding to the warning light mode, and controlling the lifting motor of the smart clothes drying rack to perform the clothes drying rack retraction operation within a preset time; when the target event is a clothes sterilization event, controlling the disinfection equipment of the smart clothes drying rack to perform the disinfection operation, and controlling the light-emitting unit to output the light effect corresponding to the disinfection function light mode; when the target event is a clothes drying event, controlling the drying equipment of the smart clothes drying rack to perform the drying operation, and controlling the light-emitting unit to output the light effect corresponding to the drying function light mode.

[0101] Specifically, controlling the output of the drying auxiliary light mode by the light-emitting unit includes: controlling the main light to be adjusted to maximum brightness.

[0102] Specifically, controlling the output of the warning light mode by the light-emitting unit includes controlling the ambient light to periodically and slowly blink in low-brightness orange or red.

[0103] Specifically, controlling the light-emitting unit to output the light effect corresponding to the disinfection function light mode includes: during the execution of the disinfection function, controlling the light-emitting unit to periodically flash purple light; when a human body is detected to enter the preset distance range, interrupting the disinfection operation and controlling the light-emitting unit to switch to the safety warning light mode.

[0104] Preferably, the preset distance range is a circular area with a radius of 3m centered on the smart clothes drying machine.

[0105] Specifically, controlling the output of the light-emitting unit to produce the light effect corresponding to the drying function light mode includes: during the execution of the drying function, controlling the light-emitting unit to periodically breathe and flash with warm yellow light, with the color temperature stable within a preset warm color temperature range; when the drying temperature is detected to exceed the safety threshold, turning off the drying equipment and controlling the light-emitting unit to switch to the fault warning light mode.

[0106] In one embodiment, the step of responding to the target event and executing the linkage control corresponding to the target event further includes: when the rain warning event is detected to have ended and the weather clears up, controlling the light-emitting unit to switch to clear sky mode and issuing a voice prompt.

[0107] The linkage control corresponding to each target event mentioned in the embodiments of this application is described in detail below: For the linkage control corresponding to the clothesline descent event: the trigger condition is: the user issues the command "I want to hang clothes" via voice, or manually lowers the clothesline via remote control or mobile APP. After the control unit detects the start signal of the clothesline descent, it immediately triggers the clothesline descent event. The linkage control execution process is as follows: after the clothesline descent event is triggered, the control unit drives the lifting motor to automatically lower the clothesline to the user's pre-set "drying height" without the need for secondary adjustment by the user. At the same time, it controls the light-emitting unit to output drying auxiliary lighting effects and adjusts the main light to the maximum brightness of 6000K to provide sufficient lighting for the user to hang clothes. If the control unit detects that the current target lighting scene mode is the rain compensation mode, it will actively prompt via voice after determining that the user has finished hanging clothes: "High outdoor humidity detected, would you like to turn on the drying / dehumidification function for you?", achieving seamless connection between drying and moisture-proof auxiliary functions.

[0108] For the linkage control corresponding to the rainfall warning event: the trigger condition is as follows: the control unit obtains data from a third-party meteorological service platform through a cloud data interface. When it determines that the probability of rainfall within the next 15-30 minutes is greater than 80%, it immediately triggers the rainfall warning event and initiates the rain prevention linkage process. The linkage control execution process is as follows: the clothes dryer simultaneously activates auditory and visual reminders. On the one hand, it issues a voice warning: "Rain is detected. It is recommended to bring in the clothes. The system will automatically raise the drying rack for you." On the other hand, the lights switch to "warning / reminder mode," and the ambient lights periodically and slowly flash orange or red at low brightness to ensure that users can perceive the warning in different areas of the room. After the warning, users who have been in the room for 2 minutes can take off their clothes dryers. During the cancellation window, if the user does not issue a cancellation command via voice, APP, or remote control, the control unit drives the lifting motor to automatically raise the drying rack to the top storage position to prevent clothes from getting wet. If the user cancels in time, the system immediately exits the warning light mode, restores the original scene lighting, and announces "Cancelled" via voice. After the drying rack is retracted, the control unit continuously monitors outdoor weather data. When it detects that the rain has stopped and judges that the sun has reappeared based on the indoor light intensity or weather data, the light unit immediately switches to the real clear sky mode to simulate the lighting effect of a sunny outdoor environment. At the same time, it announces "The rain has stopped, the sun is shining, you can lower the drying rack again to dry clothes," completing the entire process of warning, protection, and recovery.

[0109] For the linkage control corresponding to the clothing sterilization event: the triggering conditions are as follows: the control unit continuously monitors cloud-based meteorological data and indoor environmental data in active sensing mode. When both conditions are met—"continuous rainy weather lasting more than 24 hours" and "the indoor humidity sensor detects a relative humidity consistently higher than 70%"—it determines that clothing poses a risk of bacterial growth and triggers the clothing sterilization event. The linkage control execution process is as follows: the system simultaneously reminds the user through two channels: first, a voice broadcast: "Continuous rainy weather has been detected, and clothing is prone to bacterial growth. It is recommended to turn on ultraviolet disinfection. Do you want to proceed?"; second, the same content is pushed to the APP. At the same time, the light-emitting unit switches to "health reminder mode," using a low-brightness, pale purple light to slowly flash, strengthening the reminder through a dedicated light signal to prevent the user from missing it. If the user confirms the start of disinfection via voice, APP, or remote control, the system first detects the drying rack. If the clothes drying rack is in a lowered position, it will automatically retract to the top. After a 5-second delay, the ultraviolet disinfection lamp will be activated, and a standard disinfection time of 30 minutes will be set. At the same time, the light will switch to "disinfection warning mode," flashing purple light periodically to visually inform the user that disinfection is in progress and that they should not approach the clothes drying rack area. During the disinfection process, a human infrared sensor or millimeter-wave radar will continuously monitor human activity within a 3-meter range of the clothes drying rack. If someone is detected approaching, the disinfection operation will be immediately interrupted, the ultraviolet lamp will be turned off, and the light will switch to "safety warning mode," flashing red light rapidly, with a voice announcement: "Disinfection interrupted, please be careful," to eliminate the risk of ultraviolet radiation. After the 30-minute disinfection time is completed, the light will switch to "completion prompt mode," flashing green light softly 3 times, accompanied by a voice announcement: "Disinfection completed, clothes are healthier." The light-emitting unit will then automatically return to the scene mode before disinfection.

[0110] For the linkage control corresponding to the clothes drying event: the triggering condition is as follows: after the user finishes hanging the clothes, they give the voice command "I'm done drying", or the control unit detects that the drying rod is lowering and the load is steadily increasing. The control unit simultaneously monitors that the outdoor humidity is higher than 80% and the weather forecast for the next 2 hours shows no sign of clearing up, determining that the clothes are difficult to dry naturally, thus triggering the clothes drying event. The linkage control execution process is as follows: a suggestion is simultaneously initiated through voice broadcast and APP message push: "High outdoor humidity detected, clothes are difficult to dry naturally, it is recommended to turn on the drying function, do you want to execute?" At the same time, the light unit switches to "dehumidification reminder mode", using a warm orange light that slowly changes to simulate the visual feeling of warm air drying, allowing the user to intuitively perceive the suitable scenario for the drying function. When the user confirms to execute the drying function, the drying program is started, including ① detecting whether the drying rod is at the preset drying height, if not, it automatically lowers to the corresponding position; ② starting the drying fan, according to the material of the clothes and indoor and outdoor conditions. ① Humidity: Automatically selects between gentle, standard, and powerful airflow; ② Basic drying time is 2 hours, which is dynamically adjusted based on the real-time weight and humidity of the clothes to avoid over-drying or incomplete drying; ③ The light unit switches to drying mode, using warm yellow light that flashes periodically, with the color temperature stable in the 3000K warm yellow light range to create a warm and dry atmosphere; During the drying process, the temperature sensor continuously monitors the ambient temperature of the drying area. If the temperature exceeds the safety threshold, the drying fan is immediately turned off, and the light switches to fault warning mode, such as a solid red light, with a voice announcement: "Drying temperature abnormal, automatically shut down, please check," to ensure the safety of the equipment and clothes; After the drying time ends or the moisture content of the clothes is detected to be lower than the preset standard (such as 15%), the light switches to "completion prompt mode," with a soft green light flashing 3 times, accompanied by a voice announcement: "Clothes are dried, please collect them in time"; Then the light unit returns to the scene mode before drying.

[0111] Example 2, an adaptive lighting control method for an intelligent clothes drying rack provided in this application, differs from Example 1 in that the implementation method for fusing and analyzing the outdoor meteorological data and the indoor environmental data in step 102 to determine the current comprehensive environmental characteristics is different, as follows: In one embodiment, the step of fusing and analyzing the outdoor meteorological data and the indoor environmental data to determine the current comprehensive environmental characteristics specifically includes: converting the outdoor meteorological data and the indoor environmental data into feature vectors of a preset dimension; inputting the feature vectors into a pre-trained classification model, wherein the classification model is trained based on multiple historical feature vector samples and corresponding comprehensive environmental feature labels; calculating the probability value of the feature vector corresponding to each comprehensive environmental feature label through the classification model; determining the comprehensive environmental feature label with the highest probability value among the various comprehensive environmental feature labels as the classification result; and determining the current comprehensive environmental characteristics based on the classification result.

[0112] In one embodiment, converting the outdoor meteorological data and the indoor environmental data into feature vectors of a preset dimension specifically includes: converting the weather and meteorological data in the outdoor meteorological data into numerical codes to obtain weather and meteorological numerical codes; calculating the indoor-outdoor temperature difference based on the outdoor temperature in the outdoor meteorological data and the indoor temperature in the indoor environmental data, and normalizing the indoor-outdoor temperature difference to obtain a normalized indoor-outdoor temperature difference value; and normalizing the ultraviolet index and air quality index in the outdoor meteorological data, as well as the indoor light intensity and indoor humidity in the indoor environmental data, to obtain a normalized indoor-outdoor temperature difference value. Normalized ultraviolet (UV) index, normalized air quality index, normalized indoor light intensity, and normalized indoor humidity are obtained. The current time is encoded based on sunrise and sunset times to obtain a time code. The trend features of indoor ambient light intensity changes are extracted from the acquired historical indoor ambient light intensity sequence. The weather and meteorological numerical codes, the normalized UV index, the normalized air quality index, the normalized indoor light intensity, the normalized indoor-outdoor temperature difference, the normalized indoor humidity, the time code, and the trend features of indoor ambient light intensity changes are integrated to obtain a multi-dimensional feature vector.

[0113] In one embodiment, after calculating the probability value of the feature vector corresponding to each comprehensive environmental feature label through the classification model, the method further includes: determining whether the probability value corresponding to the comprehensive environmental feature label with the highest probability value is greater than a preset confidence threshold; if so, then the comprehensive environmental feature label is determined as the classification result; if not, then the method of determining the current comprehensive environmental feature based on the rule base in Embodiment 1 is reverted to.

[0114] Preferably, when the classification model performs scene recognition and judgment based on multi-dimensional environmental features, the indoor and outdoor temperature difference value can achieve differentiated scene output under the same outdoor meteorological conditions. For example, when the outdoor meteorological data is all judged to be clear sky conditions, if the calculated indoor and outdoor temperature difference value is large, it indicates poor indoor ventilation and a sense of oppression. The classification model will output a rainy compensation feature label to match the corresponding lighting mode. If the indoor and outdoor temperature difference value is small, it indicates that the indoor and outdoor environments are synchronized well and the air exchange is sufficient. The classification model will output a true clear sky feature label so that the light-emitting unit presents a clear sky mode light effect that is adapted to the clear outdoor weather.

[0115] In one embodiment, the current comprehensive environmental characteristics and the lighting scene mode selected by the user when manually switching lighting scenes are also recorded; when the number of recorded samples reaches a preset threshold, incremental training is triggered to fine-tune the classification model to gradually adapt to the user's personal preferences.

[0116] In one embodiment, the various integrated environmental feature tags include a true clear sky feature tag, a true sunset feature tag, a rainy day compensation feature tag, an aurora feature tag, and a tipsy feature tag.

[0117] In one embodiment, the classification model is a neural network-based classifier or a random forest-based classifier.

[0118] Specifically, the classification model includes an input layer, two hidden layers, and a softmax output layer. The output layer outputs the probability distributions of the true clear sky feature label, the true sunset feature label, the rainy compensation feature label, the aurora feature label, and the slightly tipsy feature label.

[0119] Example 3, see Figures 2-3 The smart clothes drying rack includes an environmental sensing unit 1, a control unit 2, and a light-emitting unit 3, as detailed below: The environmental sensing unit 1 is used to acquire multi-dimensional environmental sensing data, which includes outdoor meteorological data and indoor environmental data.

[0120] Control unit 2, connected to the environment sensing unit 1, is configured to execute the adaptive illumination control method as described in Embodiment 1 above.

[0121] The light-emitting unit 3 is connected to the control unit 2 and is used to output the light effect corresponding to the target lighting scene mode matched by the control unit 2.

[0122] In one embodiment, the environmental sensing unit 1 includes a local sensor module 10 and a cloud data interface 11; wherein, the local sensor module 10 is integrated on the clothes drying rack host and includes at least a light sensor for collecting indoor ambient light intensity and a temperature and humidity sensor for collecting indoor temperature and indoor humidity; the cloud data interface 11 is used to obtain at least one of outdoor meteorological data, ultraviolet index, sunrise and sunset times and air quality index from a third-party meteorological service platform via a wireless network.

[0123] Preferably, the local sensor module 10 may also be configured with a particulate matter sensor for real-time collection of indoor particulate matter concentration, such as PM2.5, PM10 and other particulate matter concentrations.

[0124] In one embodiment, the light-emitting unit 3 is a colorful light-emitting unit 3, wherein the light-emitting unit 3 includes an RGB-LED light strip or a light panel.

[0125] Preferably, the light-emitting unit 3, by using RGB-LED light strips or light panels, can mix more than 16 million colors; and supports independent brightness, color temperature (for the white light part), and color adjustment channels; at the same time, the light-emitting unit 3 is divided into different light-emitting areas, such as the main lighting area and the ambient light area, and the different light-emitting areas can be controlled independently.

[0126] In one embodiment, the light-emitting unit 3 further includes a micro projection module; the micro projection module is connected to the control unit 2 and is used to project dynamic images under the control of the control unit 2.

[0127] Specifically, the control unit 2 is also used to: control the micro projection module to project dynamic images when the target lighting scene mode is aurora mode.

[0128] Specifically, when entering aurora mode, not only do the ambient lights change, but the micro projection module, under the control of the control unit 2, can project dynamic images of slowly drifting clouds or stars onto the ceiling, further enhancing the immersive experience.

[0129] In one embodiment, the intelligent clothes drying rack provided in this application further includes: a physiological data interface 5 for acquiring the user's physiological state data; the control unit 2 is connected to the physiological data interface 5 and is used to receive the user's physiological state data.

[0130] Specifically, the physiological data interface 5 connects to the user's wearable device via wireless communication methods such as Bluetooth and Wi-Fi to acquire the user's physiological status data, which includes physiological indicators such as heart rate, skin conductance, blood pressure, and activity level.

[0131] In one embodiment, the control unit 2 is an MCU, which is used to receive and process multi-dimensional environmental perception data collected by the environmental perception unit 1; and the control unit 2 is also pre-loaded with a variety of environmental feature recognition algorithms and lighting scene matching logic. Based on the matching results, it sends corresponding control commands to the light-emitting unit 3 and the clothes drying machine execution unit 4 to realize the linkage control of the lighting and the execution device.

[0132] In one embodiment, the intelligent clothes drying rack provided in this application further includes: a clothes drying rack execution unit 4; wherein the clothes drying rack execution unit 4 includes at least one of a lifting motor, a disinfection device, and a drying device; the control unit 2 is connected to the clothes drying rack execution unit 4.

[0133] In one embodiment, the control unit 2 is further configured to: detect the operating status of the smart clothes dryer and identify environmental change events based on the multi-dimensional environmental perception data; match the operating status and the environmental change events with a preset event library to determine a successfully matched target event, wherein the target event includes at least one of a clothes drying rod descent event, a rainfall warning event, a clothes sterilization event, and a clothes drying event; in response to the target event, send a corresponding control command to the clothes dryer execution unit 4 to perform a clothes drying rod lifting operation, a disinfection operation, or a drying operation, and send a corresponding light control command to the light-emitting unit 3 to output a corresponding light mode.

[0134] In one embodiment, the control unit 2 is specifically used to: control the light-emitting unit 3 to output a drying auxiliary light mode when the target event is a clothes drying rod descent event; control the light-emitting unit 3 to output a warning light mode when the target event is a rain warning event, and control the lifting motor to perform a clothes drying rod retraction operation within a preset time; control the disinfection equipment to perform a disinfection operation when the target event is a clothes sterilization event, and control the light-emitting unit 3 to output a disinfection function light mode; and control the drying equipment to perform a drying operation when the target event is a clothes drying event, and control the light-emitting unit 3 to output a drying function light mode.

[0135] The aforementioned smart clothes drying rack can implement the adaptive lighting control method of the smart clothes drying rack described in the above method embodiments. The options in the above method embodiments are also applicable to this embodiment, and will not be detailed here.

[0136] like Figure 4 As shown, Figure 4 This is a schematic diagram of the structure of a computer device provided in this application; it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114, and the memory 113 is used to store computer programs.

[0137] In one embodiment of this application, the processor 111, when executing the program stored in the memory 113, implements the adaptive lighting control method for the smart clothes drying rack provided in any of the foregoing method embodiments.

[0138] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0139] Therefore, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the adaptive lighting control method for an intelligent clothes drying rack as provided in any of the foregoing method embodiments.

[0140] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, or any other physical storage medium capable of storing program code. The computer-readable storage medium can be non-volatile or volatile.

[0141] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0143] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0144] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0145] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0146] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Since these modifications and variations fall within the scope of the claims and their equivalents, this application also intends to include these modifications and variations.

[0147] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An adaptive lighting control method for an intelligent clothes drying rack, characterized in that, include: Receive multi-dimensional environmental sensing data, wherein the multi-dimensional environmental sensing data includes outdoor meteorological data and indoor environmental data; The outdoor meteorological data and the indoor environmental data are fused and analyzed to determine the current comprehensive environmental characteristics; Based on the current comprehensive environmental characteristics, a target lighting scene mode is matched from a preset lighting scene mode library; The light-emitting unit of the smart clothes dryer is controlled to output the light effect corresponding to the target lighting scene mode.

2. The method as described in claim 1, characterized in that, The process of fusing and analyzing the outdoor meteorological data and the indoor environmental data to determine the current comprehensive environmental characteristics specifically includes: The outdoor meteorological data and the indoor environmental data are input into a preset rule base; wherein, the rule base contains multiple mapping rules, and each mapping rule defines the correspondence between the outdoor meteorological-indoor environmental combination conditions and the comprehensive environmental characteristics; Determine whether the outdoor meteorological data and the indoor environmental data satisfy the combination conditions defined in each mapping rule; The mapping rule that satisfies the combined conditions is determined as the target mapping rule, and the comprehensive environmental feature corresponding to the target mapping rule is determined as the current comprehensive environmental feature.

3. The method as described in claim 1, characterized in that, The process of fusing and analyzing the outdoor meteorological data and the indoor environmental data to identify the current comprehensive environmental characteristics specifically includes: The outdoor meteorological data and the indoor environmental data are converted into feature vectors of a preset dimension. The feature vector is input into a pre-trained classification model, wherein the classification model is trained based on multiple historical feature vector samples and corresponding comprehensive environmental feature labels; The probability value of the feature vector corresponding to each comprehensive environmental feature label is calculated using the classification model. The comprehensive environmental feature label with the highest probability value among all the comprehensive environmental feature labels is determined as the classification result; Based on the classification results, the current comprehensive environmental characteristics are determined.

4. The method as described in claim 1, characterized in that, Also includes: The system detects the operating status of the smart clothes drying rack and identifies environmental change events based on the multi-dimensional environmental perception data. The operating status and the environmental change events are matched with a preset event library to determine the target events that are successfully matched. The target events include at least one of the following: clothesline descent event, rain warning event, clothes sterilization event, and clothes drying event. In response to the target event, execute the linkage control corresponding to the target event.

5. The method as described in claim 4, characterized in that, The step of responding to the target event and executing the linkage control corresponding to the target event specifically includes: When the target event is a clothesline descent event, the light-emitting unit is controlled to output the light effect corresponding to the clothes drying auxiliary light mode; When the target event is a rain warning event, the light-emitting unit is controlled to output the light effect corresponding to the warning light mode, and the lifting motor of the smart clothes drying rack is controlled to perform the clothes drying rod retraction operation within a preset time. When the target event is a clothing sterilization event, the disinfection equipment of the smart clothes drying rack is controlled to perform a disinfection operation, and the light-emitting unit is controlled to output the light effect corresponding to the disinfection function light mode; When the target event is a clothes drying event, the drying equipment of the smart clothes dryer is controlled to perform the drying operation, and the light-emitting unit is controlled to output the light effect corresponding to the drying function light mode.

6. The method as described in claim 1, characterized in that, After matching the target lighting scene mode from a set of preset lighting scene modes based on the current comprehensive environmental characteristics, the process further includes: Receive user's physiological status data; Based on the physiological state data, determine whether the user is in a preset abnormal physiological state; When it is determined that the user is in the abnormal physiological state, the target lighting scene mode is updated to the lighting scene mode corresponding to the abnormal physiological state.

7. The method as described in claim 1, characterized in that, The preset lighting scene mode library contains multiple lighting scene modes, and each lighting scene mode has a preset correspondence with at least one comprehensive environmental feature; The step of matching a target lighting scene mode from a preset lighting scene mode library based on the current comprehensive environmental characteristics specifically includes: Based on the current comprehensive environmental characteristics, a lighting scene mode that matches the current comprehensive environmental characteristics is queried from the correspondence and selected as the target lighting scene mode.

8. A smart clothes drying rack, characterized in that, include: An environmental sensing unit is used to acquire multi-dimensional environmental sensing data, wherein the multi-dimensional environmental sensing data includes outdoor meteorological data and indoor environmental data; The control unit, connected to the environment sensing unit, is configured to perform the adaptive lighting control method as described in any one of claims 1 to 7; The light-emitting unit is connected to the control unit and is used to output the light effect corresponding to the target lighting scene mode matched by the control unit.

9. A smart clothes drying rack as described in claim 8, characterized in that, Also includes: Physiological data interface, used to obtain users' physiological state data; The control unit is connected to the physiological data interface and is used to receive the user's physiological state data.

10. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

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