Multi-degree-of-freedom environment self-adaptive intelligent clothes hanger and control method
By integrating sensors and implementing dynamic path planning in a multi-degree-of-freedom environmentally adaptive smart clothes drying rack, the problem of insufficient environmental adaptability and intelligence in existing clothes drying racks has been solved, achieving efficient and safe clothes drying and adaptive control.
Patent Information
- Application Number
- CN202511128981.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-13
- Publication Date
- 2025-11-14
AI Technical Summary
Existing smart clothes racks have shortcomings in terms of environmental adaptability and intelligent functions. They cannot accurately identify the type of clothing and the best drying area, and they cannot respond automatically when there are sudden environmental changes, resulting in low drying efficiency and easy bacterial growth.
The multi-degree-of-freedom environmentally adaptive smart clothes drying rack integrates multiple sensor modules and intelligent decision learning modules. Through environmental parameter analysis and load zoning, it achieves dynamic path planning and adaptive motion control. Combined with ultraviolet sterilization function, it enhances the system's environmental adaptability and intelligence level.
It significantly improves drying efficiency and safety, enhances clothing drying rate and system robustness through multi-dimensional collaborative regulation, achieves proactive response and autonomous learning to complex weather conditions, and reduces the risk of bacterial growth.
Smart Images
Figure CN120945642A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the technical field of smart home automation, and in particular to a multi-degree-of-freedom environmentally adaptive smart clothes rack and its control method. Background Technology
[0002] With the rapid development of technology and the improvement of living standards, people's demand for convenience, comfort and intelligence in home life is increasing. As part of smart homes, smart clothes drying racks have gradually become more popular in recent years. However, due to space limitations, most traditional smart clothes drying racks are lift-type. Lift-type clothes drying racks mostly use a fixed structure with a simple mechanical movement path, which cannot accurately meet the needs of drying clothes.
[0003] Current smart clothes drying racks primarily rely on electric lifting to adjust the drying position, depending on a single sensor. While they possess basic sensing functions, they cannot accurately match high-humidity clothing with the optimal sunlight area, and they cannot automatically respond to sudden environmental changes. Traditional clothes drying racks depend on outdoor sunlight, but rainy, foggy, or cold weather can affect drying efficiency, and damp clothes are prone to bacterial and mold growth, leading to health problems.
[0004] Existing smart clothes drying racks suffer from poor environmental adaptability and limited practicality of their smart functions. This stems from limitations in sensors, inflexible motion structures, and integration with the home ecosystem. Therefore, a more versatile and adaptable smart clothes drying rack structure is needed. Summary of the Invention
[0005] The purpose of this invention is to provide a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack and control method, thereby solving at least one of the above-mentioned technical problems.
[0006] The preliminary investigation of this invention can be achieved through the following technical solutions: In a first aspect, the present invention provides a control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack, comprising: Step S1: Initialize the smart clothes drying rack; Step S2: Perform gravity detection on the effective load to determine whether there is an effective load. If yes, proceed to step S3; otherwise, return to step S2. Step S3: Obtain environmental parameter data through the sensor module, and divide the drying environment into environmental zones based on the drying score; Step S4: Based on the gravity detection results and the environmental zoning, the effective load is divided into load zones; the number of environmental zones is the same as the number of load zones. Step S5: Configure the load partition and the environment partition in descending order and enter monitoring mode; Step S6: If the specified time or degree of drying has not been reached, return to step S3; otherwise, proceed to step S7. Step S7: Perform a sterilization procedure on the payload; The drying score is obtained based on the environmental parameter data.
[0007] As a further technical solution, step S3 includes: Step S31: Divide the total drying area of the smart clothes rack into n equal parts by the Kth division. , ; Step S32: Obtain the environmental parameter data for each of the drying zones; Step S33: Evaluate each of the drying zones to obtain a regional drying score, and obtain a total drying score based on the regional drying scores; Step S34: Determine whether K > K th If so, proceed to step S35; otherwise, increment K by 1 and return to step S31; where K th The preset number of loops; Step S35: Select the equal division result corresponding to the highest total drying score as the current partition result.
[0008] As a further technical solution, the process of dividing the drying environment into zones based on the drying score also includes: Step S36: For the partition with the highest drying score in the current partitioning results, rotate the slider's spin axis by a fixed angle and recalculate the drying score to perform fine-grained area division.
[0009] As a further technical solution, the environmental parameter data includes light intensity, temperature, humidity, wind speed, sun position, and wind direction; The method for obtaining the drying score includes:
[0010] in, For the drying area in During the period The drying score, For the drying area exist The average light intensity over a given period of time. For the drying area exist The average temperature over the period of time For the drying area exist Average humidity over the period of time For the drying area exist The average wind speed over the period of time This is the coefficient corresponding to the light intensity. This is the coefficient corresponding to temperature. This is the corresponding coefficient for humidity. This is the corresponding coefficient for wind speed. For light intensity parameters, For temperature parameters, For humidity parameters, For wind speed parameters, In order to be in The drying zones within the specified time period Effective light reception time of the payload.
[0011] As a further technical solution, the process of load partitioning the effective load in step S4 includes: Step S41: Obtain the water content of each payload; Step S42: Based on the statistical results of the water content, all the effective loads are approximately divided into n load partitions of equal quantity. , .
[0012] As a further technical solution, step S5 includes: The load zones are sorted in descending order according to the moisture content. After matching them one-to-one with the zones that are also sorted in descending order of drying score in the current zone results, the monitoring mode is entered. The monitoring modes include: The environmental parameter data, current drying time, and effective load dryness are periodically acquired. When the re-optimization conditions are met, the re-optimization process is triggered, and the process returns to step S31; otherwise, the process proceeds to step S7. The re-optimization conditions include: the current drying time reaches the preset time and the dryness of the effective load does not reach the specified threshold. As a further technical solution, the configuration method of n includes: During the drying cycle of the current payload, n is configured according to the execution value of K in step S31, with a minimum value of 2 for n.
[0013] As a further technical solution, step S1 includes: Step S11: Calibrate the sensor module; Step S12: Drive the slider to return the telescopic clothes drying rod to its initial position; During the movement of the slider, an infrared ranging sensor detects obstacles in the chain clothes drying assembly as it moves, and performs obstacle avoidance actions.
[0014] As a further technical solution, step S7 includes: When the dryness of the payload reaches the sterilization activation threshold, the payload is moved to a position close to the ultraviolet sterilization lamp module and the ultraviolet sterilization lamp module is activated. When the dryness of the effective load reaches the sterilization stop threshold, the ultraviolet sterilization lamp module is turned off. The dryness of the effective load for the effective load numbered m The methods for obtaining it include:
[0015] in, The initial water content of the payload numbered m is... Let m be the weight of the payload at time t. Let m be the weight of the payload in a completely dry state.
[0016] Secondly, this invention provides a multi-degree-of-freedom environment-adaptive intelligent clothes drying rack, employing the following technical solution: A multi-degree-of-freedom environmentally adaptive smart clothes drying rack includes a fixed plate for a preset slide rail, a sliding component, a multi-functional load-bearing module, a sensor module, and a chain clothes drying component; The multi-functional load-bearing module includes a load-bearing plate, an ultraviolet germicidal lamp module, and a main control unit; the ultraviolet germicidal lamp module includes multiple ultraviolet germicidal lamp units arranged in an array on the side of the load-bearing plate closest to the effective load. The sensor module is connected to the main control unit and includes multiple gravity sensors, multiple temperature and humidity sensors, multiple infrared ranging sensors, multiple light intensity sensors, and wind direction and speed sensors. The wind direction and speed sensors are installed on the outer surface of the load-bearing plate. The sliding assembly includes a slider and a driver that are fixed to the multifunctional load-bearing module; The chain clothes drying assembly includes a telescopic clothes drying rod and multiple drive chains; The driver is connected to the main control unit and is used to drive the slider to slide or spin along the slide rail according to the control command issued by the main control unit. The drive chain is connected to one end of the telescopic clothes drying rod, and the other end is connected to the multi-functional load-bearing module. The telescopic clothes drying rod has weight-reducing perforations and clothes-drying slots evenly distributed along its length. Each weight-reducing perforation has a groove at its bottom, and the gravity sensor is installed in the groove. The temperature and humidity sensor is suspended below the telescopic clothes drying rod. The infrared distance sensor is installed at both ends of the telescopic clothes drying rod. The light intensity sensor is installed between each clothes-drying slot. The clothes-drying slot has a bidirectional inclined surface, which uses the weight of the clothes hanger to achieve a sliding self-locking mechanism.
[0017] In summary, the present invention has at least one of the following beneficial technical effects: 1. This invention integrates an intelligent decision-making learning module, which autonomously optimizes migration logic by analyzing historical operational data over a set time period, effectively suppressing the probability of unnecessary operational behaviors. Simultaneously, it incorporates an environmental trend prediction model, establishing a light intensity variation pattern map based on time-series analysis. By predicting environmental change trends, it achieves forward-looking migration decisions, forming a three-dimensional intelligent control system encompassing real-time response, autonomous learning, and trend prediction, significantly improving the system's adaptability and operational efficiency under complex meteorological conditions.
[0018] 2. This invention optimizes the shortest path strategy for dynamic path planning in the target area, ensuring that the light intensity of the target area is effectively improved after migration. The system significantly improves the rate of humidity decrease of the load per unit time through multi-dimensional collaborative regulation, effectively suppresses the frequency of invalid migration behavior, and optimizes the overall energy utilization efficiency based on an adaptive motion strategy. Compared with traditional solutions, it achieves a breakthrough improvement in drying performance and operational efficiency.
[0019] 3. This invention achieves full-domain perception of the pole's spatial state and establishes an emergency braking trigger mechanism based on motion trajectory prediction. An innovative adaptive load protection module is designed, which evaluates the load state in real time through dynamic threshold judgment technology. When abnormal operating conditions are detected, it simultaneously executes mechanism locking and graded alarm strategies, and generates a fault feature map for system diagnosis. This technical solution, through the synergistic effect of multi-source data fusion, predictive safety protection, and intelligent fault-tolerant mechanisms, forms a multi-dimensional reliability assurance architecture covering mechanical motion control, environmental perception, and equipment protection, significantly improving the robustness and safety of system operation. Attached Figure Description
[0020] Figure 1 This is a schematic diagram of the intelligent clothes drying rack's workflow.
[0021] Figure 2 This is a schematic diagram of the overall structure of a multi-degree-of-freedom environment-adaptive intelligent clothes drying rack.
[0022] Figure 3 This is a schematic diagram of a single clothesline.
[0023] Figure 4This is a schematic diagram of a suspended moving structure.
[0024] Reference numerals in the attached diagram: 1. Fixed plate; 2. Slider; 3. Ultraviolet germicidal lamp; 4. Drive chain; 5. Telescopic clothes drying rod; 6. Infrared distance sensor; 7. Light intensity sensor; 8. Gravity sensor; 9. Temperature and humidity sensor; 10. Clothes drying hole slot; 11. Telescopic slot of drive chain; 12. Wind direction and speed sensor; 13. Slide rail. Detailed Implementation
[0025] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings.
[0026] In the description of this specification, the references to "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples" indicate that a specific feature, structure, material, or characteristic described in connection with the described embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0027] Please refer to Figure 1 As shown, this invention discloses a control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack, the control method comprising the following steps: Step S1: Initialize the smart clothes drying rack, calibrate the sensor module, and drive the slider 2 to return the telescopic clothes drying rod 5 to its initial position. During the movement of the slider 2, the infrared ranging sensor 6 detects obstacles in the chain clothes drying assembly and performs obstacle avoidance actions.
[0028] Step S2: Use gravity sensor 8 to detect the gravity of the payload and determine whether there is a payload. If yes, proceed to step S3; otherwise, return to step S2. Step S3: Obtain environmental parameter data through the sensor module, and divide the drying environment into environmental zones based on the drying score; Step S4: Based on the gravity detection results and the environmental zoning, the effective load is divided into load zones; the number of environmental zones is the same as the number of load zones. Step S5: Configure the load partition and the environment partition in descending order and enter monitoring mode; Step S6: If the specified time or degree of drying has not been reached, return to step S3; otherwise, proceed to step S7. Step S7: Perform a sterilization procedure on the payload; The drying score is based on the environmental parameter data, with humidity weighting at 60% and light weighting at 40%.
[0029] In this embodiment, after detecting the payload in step S2, the process proceeds to step S3: Step S31: Divide the total drying area of the smart clothes rack into n equal parts by the Kth division. , Where K=6, n=6; The configuration method of n includes: During the drying cycle of the current payload, n is configured according to the execution value of K in step S31. The minimum value of n is 2, which allows for continuous and accurate calculation of the drying score of each environmental zone during the division of environmental zones, while ensuring that the entire division process is simple and fast.
[0030] Step S32: Obtain the environmental parameter data of each of the drying zones by using the light intensity sensor 7, temperature and humidity sensor 9, and wind direction and speed sensor 12 to obtain the average light intensity, average temperature, average humidity and average wind speed of the current environment. Step S33: Evaluate each of the drying zones to obtain a regional drying score, and obtain a total drying score based on the regional drying scores; The method for obtaining the drying score includes:
[0031] in, For the drying area exist Drying score within a certain time period For the drying area exist The average light intensity over a given period of time. For the drying area exist The average temperature over the period of time For the drying area exist Average humidity over the period of time For the drying area exist The average wind speed over the period of time This is the coefficient corresponding to the light intensity. This is the coefficient corresponding to temperature. This is the corresponding coefficient for humidity. This is the corresponding coefficient for wind speed. For light intensity parameters, For temperature parameters, For humidity parameters, For wind speed parameters, In order to be in The drying zones within the specified time period Effective light reception duration of the payload; in, =0.2, =0.2, =0.1, =0.15; In this embodiment, The duration of the payload under strong light illumination is defined as the strong light illuminance threshold, H. imax =0.75, by capturing light and temperature through camera and temperature and humidity sensor 9, the duration of strong light irradiation on the payload is calculated.
[0032] Step S34: Determine whether K > K th If so, proceed to step S35; otherwise, increment K by 1 and return to step S31; where K th The preset number of loops is set to K. th =6; Step S35: Based on the calculation results after the loop of steps S33 and S34, select the equal division result corresponding to the highest total drying score as the current partition result.
[0033] In this embodiment, the process of dividing the drying environment into zones based on the drying score further includes: Step S36: For the partition with the highest drying score in the current partitioning results, rotate the slider 2 by a fixed angle using the slider's spin axis as the rotation axis, and then recalculate the drying score to perform fine-grained area division. First, rotate 10° clockwise. Then, recalculate the drying score based on the environmental parameter data after the rotation. If the drying score decreases, return to the original position and continue to rotate 10° in the opposite direction for measurement. If the drying score increases after rotating 10° clockwise, continue rotating 10° to calculate the drying score until the drying score starts to decrease. At this point, return to the previous rotation position and determine that the current position is the one with the highest drying score.
[0034] In this embodiment, after environmental partitioning is completed in step S3, step S4 performs load partitioning on the effective load based on the gravity detection results and the environmental partitioning situation: Step S41: Accurately identify the type of payload based on the payload material property library, obtain the initial gravity of the payload, and determine the water content of the payload based on the difference between the current gravity and the initial gravity. Step S42: Based on the statistical results of the water content, all the effective loads are approximately divided into n load partitions of equal quantity. , .
[0035] In this embodiment, step S5 includes: The load zones are sorted in descending order according to the moisture content. After matching them one-to-one with the zones that are also sorted in descending order of drying score in the current zone results, the monitoring mode is entered. The monitoring modes include: The environmental parameter data, current drying time, and effective load dryness are periodically acquired. When the re-optimization conditions are met, the re-optimization process is triggered, and the process returns to step S31; otherwise, the process proceeds to step S7. The re-optimization conditions include: the current drying time reaches the preset time T0=1h and the dryness of the effective load does not reach the specified threshold. When ≥0.9.
[0036] In this embodiment, a WIFI communication module is integrated to achieve wireless networking with the smart home network, forming an intelligent terminal with scenario environment perception and autonomous decision-making capabilities. When rainy weather is detected, an anti-wet-water recovery strategy is automatically triggered, forming an intelligent management architecture that includes dynamic data visualization and climate adaptive decision-making.
[0037] In this embodiment, step S7 includes: When the dryness of the effective payload reaches the sterilization activation threshold When the value is 0.9, the payload is moved to a position close to the ultraviolet germicidal lamp module 3 and the ultraviolet germicidal lamp module 3 is activated; When the dryness of the effective payload reaches the sterilization stop threshold When =1, the ultraviolet germicidal lamp module 3 is turned off; The dryness of the effective load for the effective load numbered m The methods for obtaining it include:
[0038] in, The effective payload weight when wet. Let be the effective load weight at time t. This represents the effective load weight in the initial dry state.
[0039] This embodiment provides a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack. Please refer to the accompanying drawings. Figure 2 , Figure 3 , Figure 4 As shown: A multi-degree-of-freedom environment-adaptive intelligent clothes drying rack includes a fixed plate 1 with a preset slide rail, a sliding component, a multi-functional load-bearing module, a sensor module, and a chain clothes drying component; The multi-functional load-bearing module includes a load-bearing plate, an ultraviolet germicidal lamp module 3, and a main control unit; the ultraviolet germicidal lamp module 3 includes multiple ultraviolet germicidal lamp units arranged in an array on the side of the load-bearing plate near the effective load. The sensor module is connected to the main control unit and includes multiple gravity sensors 8, multiple temperature and humidity sensors 9, multiple infrared ranging sensors 6, multiple light intensity sensors 7, and wind direction and wind speed sensors 12. The wind direction and wind speed sensors 12 are installed on the outer surface of the load-bearing plate. The sliding assembly includes a slider 2 fixed to the multifunctional load-bearing module and a driver; The chain clothes drying assembly includes a telescopic clothes drying rod 5 and multiple drive chains 4; In this embodiment, each telescopic clothes drying rod 5 is equipped with three light intensity sensors 7 (L1-L6) and corresponding temperature and humidity sensors 9 (H1-H6 / T1-T6) to form a six-quadrant gridded monitoring system. The driver is connected to the main control unit and is used to drive the slider 2 to slide or spin along the slide rail 13 according to the control command issued by the main control unit. The drive chain 4 is connected to one end of the telescopic clothes drying rod 5, and the other end is connected to the multi-functional load-bearing module. The telescopic clothes drying rod 5 has weight-reducing perforations and clothes drying slots 10 evenly distributed along its length. Each weight-reducing perforation has a groove at its bottom, and the gravity sensor 8 is installed in the groove. The temperature and humidity sensor 9 is suspended below the telescopic clothes drying rod 5. The infrared distance sensor 6 is installed at both ends of the telescopic clothes drying rod 5. The light intensity sensor 7 is installed between each of the clothes drying slots 10. The clothes drying slots 10 have a bidirectional inclined surface, which uses the weight of the clothes hanger to achieve a sliding self-locking mechanism.
[0040] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.
Claims
1. A control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack, characterized in that, include: Step S1: Initialize the smart clothes drying rack; Step S2: Perform gravity detection on the effective load to determine whether there is an effective load. If yes, proceed to step S3; otherwise, return to step S2. Step S3: Obtain environmental parameter data through the sensor module, and divide the drying environment into environmental zones based on the drying score; Step S4: Based on the gravity detection results and the environmental zoning, the effective load is divided into load zones; the number of environmental zones is the same as the number of load zones. Step S5: Configure the load partition and the environment partition in descending order and enter monitoring mode; Step S6: If the specified time or degree of drying has not been reached, return to step S3; otherwise, proceed to step S7. Step S7: Perform a sterilization procedure on the payload; The drying score is obtained based on the environmental parameter data.
2. The control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack according to claim 1, characterized in that, The process of zoning the drying environment based on the drying score includes: Step S31: Divide the total drying area of the smart clothes rack into n equal parts by the Kth division. , ; Step S32: Obtain the environmental parameter data for each of the drying zones; Step S33: Evaluate each of the drying zones to obtain a regional drying score, and obtain a total drying score based on the regional drying scores; Step S34: Determine whether K > K th If so, proceed to step S35; otherwise, increment K by 1 and return to step S31; where K th The preset number of loops; Step S35: Select the equal division result corresponding to the highest total drying score as the current partition result.
3. The control method for a multi-degree-of-freedom environment-adaptive intelligent clothes drying rack according to claim 2, wherein the process of dividing the drying environment into environmental zones based on drying scores further includes: Step S36: For the zone with the highest drying score in the current partitioning results, the drying score is recalculated after rotating by a fixed angle with the spin axis of slider (2) as the rotation axis, and fine regional division is performed.
4. The control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack according to claim 2, wherein the environmental parameter data includes light intensity, temperature, humidity, wind speed, sun position, and wind direction; The method for obtaining the drying score includes: ； in, For the drying area exist Drying score within a specific time period For the drying area exist The average light intensity over a given period of time. For the drying area exist The average temperature over the period of time For the drying area exist Average humidity over the period of time For the drying area exist The average wind speed over the period of time This is the coefficient corresponding to the light intensity. This is the coefficient corresponding to temperature. This is the corresponding coefficient for humidity. This is the corresponding coefficient for wind speed. For light intensity parameters, For temperature parameters, For humidity parameters, For wind speed parameters, In order to be in The drying zones within the specified time period Effective light reception time of the payload.
5. The control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack according to claim 2, characterized in that, The process of load partitioning the effective load in step S4 includes: Step S41: Obtain the water content of each payload; Step S42: Based on the statistical results of the water content, all the effective loads are approximately divided into n load partitions of equal quantity. , .
6. The control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack according to claim 5, characterized in that, Step S5 includes: The load zones are sorted in descending order according to the moisture content. After matching them one-to-one with the zones that are also sorted in descending order of drying score in the current zone results, the monitoring mode is entered. The monitoring modes include: The environmental parameter data, current drying time, and effective load dryness are periodically acquired. When the re-optimization conditions are met, the re-optimization process is triggered, and the process returns to step S31; otherwise, the process proceeds to step S7. The re-optimization conditions include: the current drying time reaches the preset time and the dryness of the effective load does not reach the specified threshold.
7. The control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack according to claim 2, characterized in that, The configuration method of n includes: During the drying cycle of the current payload, n is configured according to the execution value of K in step S31, with n having a minimum value of 2.
8. The control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack according to claim 1, characterized in that, Step S1 includes: Step S11: Calibrate the sensor module; Step S12, drive the slider (2) to return the telescopic clothes drying rod to its initial position; During the movement of the slider (2), the infrared ranging sensor (6) detects obstacles in the chain clothes drying assembly during its movement and performs obstacle avoidance actions.
9. The control method for a multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack according to claim 6, characterized in that, Step S7 includes: When the dryness of the payload reaches the sterilization start threshold, the payload is moved to a position close to the ultraviolet sterilization lamp module (3) and the ultraviolet sterilization lamp module (3) is started. When the dryness of the effective load reaches the sterilization stop threshold, the ultraviolet sterilization lamp module (3) is turned off. The dryness of the effective load for the effective load numbered m The methods for obtaining it include: ； in, Let m be the initial water content of the effective load. Let m be the weight of the payload at time t. Let m be the weight of the payload in a completely dry state.
10. A multi-degree-of-freedom environmentally adaptive intelligent clothes drying rack, characterized in that, The control method described in any one of claims 1-9 includes a fixed plate (1) for a preset slide rail, a sliding component, a multi-functional load-bearing module, a sensor module, and a chain clothes drying component; The multi-functional load-bearing module includes a load-bearing plate, an ultraviolet germicidal lamp module (3) and a main control unit; the ultraviolet germicidal lamp module (3) includes multiple ultraviolet germicidal lamp units arranged in an array on the side of the load-bearing plate close to the effective load. The sensor module is connected to the main control unit and includes multiple gravity sensors (8), multiple temperature and humidity sensors (9), multiple infrared ranging sensors (6), multiple light intensity sensors (7), and wind direction and wind speed sensors (12). The wind direction and wind speed sensors (12) are installed on the outer surface of the load-bearing plate. The sliding assembly includes a slider (2) fixed to the multifunctional load-bearing module and a driver; The chain clothes drying assembly includes a telescopic clothes drying rod (5) and multiple drive chains (4). The driver is connected to the main control unit and is used to drive the slider (2) to slide or spin along the slide rail (13) according to the control command issued by the main control unit; The drive chain (4) is connected to one end of the telescopic clothes drying rod (5), and the other end is connected to the multi-functional load-bearing module. The telescopic clothes drying rod (5) is evenly provided with weight-reducing perforations and clothes drying slots (10) along its length. Each weight-reducing perforation has a groove at the bottom, and the gravity sensor (8) is installed in the groove. The temperature and humidity sensor (9) is suspended below the telescopic clothes drying rod (5). The infrared distance sensor (6) is installed at both ends of the telescopic clothes drying rod (5). The light intensity sensor (7) is installed between each clothes drying slot (10). The clothes drying slot (10) has a bidirectional inclined surface, which uses the weight of the clothes hanger to achieve a sliding self-locking mechanism.