An intelligent wardrobe control system based on the Internet of Things

Abstract

The invention relates to the field of intelligent control, and discloses an intelligent wardrobe control system based on the Internet of Things, comprising: a cabinet state data acquisition module for acquiring environmental data in the wardrobe; a clothing data acquisition module for photographing clothing in the wardrobe to obtain the number of clothing; a data analysis and processing module, comprising a drying analysis unit for obtaining a drying demand index and a disinfection and sterilization analysis unit for obtaining a disinfection and sterilization demand index; a control module for comparing the drying demand index and the disinfection and sterilization demand index with corresponding preset threshold intervals respectively, and judging whether to start a drying module and / or a disinfection and sterilization module according to the comparison result; a correction and adjustment module for performing correction analysis on the drying time and / or the disinfection and sterilization time set by a user, and judging whether to adjust according to the result of the correction analysis; and a communication module for connecting the cabinet state data acquisition module, the clothing state data acquisition module, the data analysis and processing module and the control module for communication.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control, and in particular to an intelligent wardrobe control system based on the Internet of Things. Background Art

[0002] The coal industry has a huge workforce. Today's society generally pays less attention to employees in special industries such as coal miners. Their work clothes are often not cleaned and disinfected in time, and there are many problems such as odor caused by long-term wearing of work clothes and substandard hygiene. The safety and comfort are low. Workers wearing unhygienic and unrefreshing work clothes will not only fail to protect the human body during work, but also affect work efficiency, especially in high-risk industries. Improper wearing of work clothes can cause serious accidents and threaten the lives of employees.

[0003] Due to the fatigue of working underground, the shortage of water in mines and the humid working environment, employees are unable to wash their work clothes in time. They often go down the mine wearing dirty and damp work clothes, which affects their work enthusiasm and physical health.

[0004] Therefore, there is a need for a smart wardrobe that can automatically disinfect and dry work clothes. Although the existing smart wardrobes can realize the disinfection and drying functions, there are still some problems. For example, during the disinfection and drying process of work clothes, due to the lack of operating knowledge of smart wardrobes, the same disinfection or drying time is used for work clothes of different degrees when in use, resulting in an increase in overall energy consumption and unnecessary energy waste. Summary of the invention

[0005] The purpose of the present invention is to provide a smart wardrobe control system based on the Internet of Things to solve the technical problem that due to the lack of operating knowledge of the smart wardrobe, the same disinfection or drying time is used for work clothes of different degrees during use, resulting in an increase in overall energy consumption and unnecessary energy waste.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An intelligent wardrobe control system based on the Internet of Things, comprising:

[0008] The cabinet status data collection module collects the environmental data inside the wardrobe based on the detection instruments arranged inside the wardrobe, including humidity, temperature, air quality and odor data;

[0009] The clothing data collection module takes pictures of the clothing in the closet based on the surveillance camera installed inside the closet to obtain the number of clothing;

[0010] Data analysis and processing module, including a drying analysis unit and a disinfection and sterilization analysis unit;

[0011] A drying analysis unit is used to analyze and calculate based on humidity, temperature and the amount of clothes to obtain a drying demand index;

[0012] The disinfection and sterilization analysis unit is used to analyze and calculate the humidity, air quality and odor data to obtain the disinfection and sterilization demand index;

[0013] A control module, used to compare the drying demand index and the disinfection demand index with the corresponding preset threshold intervals, and determine whether to start the drying module and / or the disinfection module according to the comparison results;

[0014] A correction and adjustment module is used to perform correction analysis on the drying time and / or disinfection and sterilization time set by the user, and determine whether to adjust according to the result of the correction analysis;

[0015] The communication module is used to connect the cabinet status data acquisition module, the clothing status data acquisition module, the data analysis and processing module and the control module for communication.

[0016] Furthermore, the working process of the drying analysis unit is:

[0017] Based on the temperature and humidity sensor, the temperature T and humidity RH inside the wardrobe are detected in real time;

[0018] Based on the surveillance camera, the number of clothes m1 and the number of newly added clothes m2 in the closet are obtained, and the total amount of clothes M is obtained by m1+m2;

[0019] Substitute the temperature T, humidity RH and total amount of clothing M into the formula The drying demand index H of the αth wardrobe is calculated α ; In the formula is the preset weight coefficient, which is selected and determined based on historical data and empirical data, and q is the impact factor;

[0020] The calculated drying demand index H α And the preset drying demand threshold H αth Make comparisons;

[0021] If H α ≥H αth , the drying module is started, otherwise, the drying module is not started.

[0022] Furthermore, the process of obtaining the impact factor is:

[0023] Get the time points of the wardrobe door opening and closing for the i-th time, and mark them as

[0024] H α ≥Hαth The moment of time is taken as the end time point of the detection period t B , find the first closing time backward as the starting time point of the detection period t A ;

[0025] Establish a drying demand index H with time as the horizontal axis α is the coordinate system of the ordinate;

[0026] Plotted at the detection period t A ~t B Curve H of drying demand index changing with time α (t) and the preset reference curve H α0 (t), preset reference curve H α0 (t) Based on comprehensive analysis of historical data and empirical data;

[0027] By formula The influence factor q is calculated; where ω 1 It is a preset proportional coefficient, determined based on historical experimental data.

[0028] Furthermore, the system further comprises an early warning module, which is used to issue an early warning of the state of the wardrobe;

[0029] The working process of the early warning module is:

[0030] By formula Calculate the drying evaluation coefficient k α ; In the formula, ω 2 is a preset proportional coefficient determined based on historical experimental data, IF(m2) is a judgment function for the number of newly added clothes, when m2≤0, IF(m2)=1, when m2>0, IF(m2)=m2;

[0031] The drying evaluation factor k α And the drying evaluation interval [k αx , k αy ] for comparison;

[0032] If k α ∈[k αx , k αy ], the wardrobe is judged to be in normal state; otherwise, the wardrobe is judged to be abnormal and an early warning signal is issued.

[0033] Furthermore, the working process of the disinfection and sterilization analysis unit is as follows:

[0034] The ammonia concentration P inside the closet is detected based on the odor sensor, and the air quality AQI inside the closet is detected based on the air quality sensor;

[0035] Substitute ammonia concentration P, air quality AQI and humidity RH into the formula Calculate the disinfection demand index X of the αth wardrobe α ; In the formula, RH 0 、AQI 0 , P 0 They are the warning values ​​for humidity, air quality, and ammonia concentration, which are formulated based on historical and empirical data;

[0036] The calculated disinfection and sterilization demand index X α The preset drying requirement threshold X αth Make comparisons;

[0037] If X α ≥X αth , the drying module is started, otherwise, the drying module is not started.

[0038] Furthermore, the working process of the correction and adjustment module is:

[0039] The current wardrobe drying demand index H α And disinfection and sterilization demand index X α Substitute into the formula group;

[0040] Calculate the theoretical drying time Δη H And theoretical disinfection and sterilization time Δη X , τ 1 , τ 2 is the conversion factor, which is determined based on the analysis of historical and experimental data;

[0041] According to Δη H The drying time η set by the user H , if |Δη H -η H |≤θ H , the drying time is set by the user, otherwise, the drying time is adjusted to η′. H Drying;

[0042] According to Δη X The disinfection and sterilization time η set by the user X , if |Δη X -η X |≤θ X , disinfection and sterilization are carried out according to the disinfection and sterilization time set by the user, otherwise, disinfection and sterilization are carried out according to the adjusted disinfection and sterilization time η′ X Disinfection and sterilization; where θ H ,θ X It is the preset difference, which is obtained based on the analysis of empirical data and experimental data.

[0043] Furthermore, when Δη H >η H hour, When Δη H <η H hour,

[0044] When Δη X >η X hour, When Δη X <η X hour,

[0045] Furthermore, the process of evaluating the status of the overall wardrobe is as follows:

[0046] Divide a working cycle into several sub-cycles and mark the start time of each sub-cycle as t j0 , the end time point is marked as t j1 ;

[0047] Mark the sub-periods without new clothes as yellow periods, and the remaining sub-periods as red periods;

[0048] Count the number of wardrobes N in the yellow cycle in each sub-cycle j黄 and the number of wardrobes in the red cycle N j红 ;

[0049] Then through the formula The overall wardrobe status evaluation coefficient G is calculated, where m is the total number of wardrobes, μ i1 , μ i2 is a preset coefficient, selected and determined based on historical data, Δβ is a reference value obtained based on historical data, n is the number of sub-periods, j is the jth sub-period, γ j is the weight coefficient corresponding to the j-th sub-period.

[0050] Beneficial effects of the present invention:

[0051] (1) The present invention evaluates the actual drying demand and disinfection demand inside the wardrobe by means of real-time humidity, temperature, air quality, odor data and the number of clothes, and compares the drying demand index and the disinfection demand index with the corresponding preset threshold intervals through a control module, and determines whether to start the drying module and / or the disinfection module according to the comparison result, so as to avoid energy waste caused by arbitrarily starting the drying module and the disinfection module;

[0052] (2) The present invention is provided with a correction and adjustment module, which performs correction and analysis on the drying time and / or disinfection time set by the user based on the theoretical drying time and theoretical disinfection time obtained after processing the drying demand index and the disinfection demand index, thereby alleviating the situation where the user sets the drying time or disinfection time too long or too short due to lack of operating knowledge, preventing the situation where insufficient time leads to poor effect or excessive time leads to excessive drying and disinfection, thereby achieving a balance between user operation and actual needs of the wardrobe, and improving the user's final satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The present invention will be further described below in conjunction with the accompanying drawings.

[0054] Figure 1 It is a system structure block diagram of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] See also Figure 1 As shown, the present invention is a smart wardrobe control system based on the Internet of Things, comprising:

[0057] The cabinet status data collection module collects the environmental data inside the wardrobe based on the detection instruments arranged inside the wardrobe, including humidity, temperature, air quality and odor data;

[0058] The clothing data collection module takes pictures of the clothing in the closet based on the surveillance camera installed inside the closet to obtain the number of clothing;

[0059] Data analysis and processing module, including a drying analysis unit and a disinfection and sterilization analysis unit;

[0060] A drying analysis unit is used to analyze and calculate based on humidity, temperature and the amount of clothes to obtain a drying demand index;

[0061] The disinfection and sterilization analysis unit is used to analyze and calculate the humidity, air quality and odor data to obtain the disinfection and sterilization demand index;

[0062] A control module, used to compare the drying demand index and the disinfection demand index with the corresponding preset threshold intervals, and determine whether to start the drying module and / or the disinfection module according to the comparison results;

[0063] A correction and adjustment module is used to perform correction analysis on the drying time and / or disinfection and sterilization time set by the user, and determine whether to adjust according to the result of the correction analysis;

[0064] The communication module is used to connect the cabinet status data acquisition module, the clothing status data acquisition module, the data analysis and processing module and the control module for communication.

[0065] The working process of the drying analysis unit is as follows:

[0066] Based on the temperature and humidity sensor, the temperature T and humidity RH inside the wardrobe are detected in real time;

[0067] Based on the surveillance camera, the number of clothes m1 and the number of newly added clothes m2 in the closet are obtained, and the total amount of clothes M is obtained by m1+m2;

[0068] Substitute the temperature T, humidity RH and total amount of clothing M into the formula The drying demand index H of the αth wardrobe is calculated α ; In the formula is the preset weight coefficient, which is selected and determined based on historical data and empirical data, and q is the impact factor;

[0069] The calculated drying demand index H α And the preset drying demand threshold H αth Make comparisons;

[0070] If H α ≥H αth , the drying module is started, otherwise, the drying module is not started. Through the above technical scheme, it can be clearly seen that the present invention selects indicators such as humidity, temperature and number of clothes in the wardrobe, and Establish an association model. When the temperature of the wardrobe increases, the humidity decreases. At this time, the wardrobe is less likely to need drying, that is, the drying demand is small. When the number of clothes is large, the demand for drying is greater than when the number of clothes is small. The drying demand index H is reflected. α The larger it is, the influence factor q is set to react according to the cumulative changes in the history of the wardrobe to ensure whether the humidity in the wardrobe increases due to the moisture of the newly added clothes.

[0071] The working process of the disinfection and sterilization analysis unit is as follows:

[0072] The ammonia concentration P inside the closet is detected based on the odor sensor, and the air quality AQI inside the closet is detected based on the air quality sensor;

[0073] Substitute ammonia concentration P, air quality AQI and humidity RH into the formula Calculate the disinfection demand index X of the αth wardrobe α ; In the formula, RH 0 、AQI 0 , P 0 They are the warning values ​​for humidity, air quality, and ammonia concentration, which are formulated based on historical and empirical data;

[0074] Through the above technical solution, the disinfection and sterilization needs in the closet are quantified. Since the clothes in the closet have a strong sweat odor, the ammonia concentration is used for side detection, and the air quality is used for expression. Obviously, when the ammonia concentration and the air quality level both increase, it means that the environment in the closet is poor and disinfection and sterilization operations are required. The closet environment with high humidity is more likely to breed bacteria. Therefore, the above three parameters are comprehensively selected to pass Establish a correlation model to calculate the disinfection and sterilization demand index X in real time. α The preset drying requirement threshold X αth Make comparisons;

[0075] If X α ≥X αth , the drying module is started, otherwise, the drying module is not started.

[0076] Through the above technical scheme, in order to reduce the situation that the set drying time and disinfection time exceed the actual demand due to subjective operation of the user, which ultimately leads to waste of resources, the present invention evaluates the actual drying demand and disinfection demand inside the wardrobe by means of real-time humidity, temperature, air quality, odor data and the number of clothes, and compares the drying demand index and the disinfection demand index with the corresponding preset threshold intervals through the control module, and judges whether to start the drying module and / or the disinfection module according to the comparison result, so as to avoid the energy waste caused by arbitrarily starting the drying module and the disinfection module, and at the same time, a correction and adjustment module is also provided, based on the theoretical drying time and the theoretical disinfection time obtained after processing the drying demand index and the disinfection demand index, so as to correct and analyze the drying time and / or disinfection time set by the user, and then alleviate the situation that the drying time or disinfection time set by the user due to lack of operation knowledge is too long or too short, prevent the situation that insufficient time leads to poor effect or excessive time leads to excessive drying and disinfection, and achieve a balance between user operation and actual needs of the wardrobe, so as to improve the final satisfaction of the user.

[0077] The process of obtaining the impact factor is:

[0078] Get the time points of the wardrobe door opening and closing for the i-th time, and mark them as

[0079] H α≥H αth The moment of time is taken as the end time point of the detection period t B , find the first closing time backward as the starting time point of the detection period t A ;

[0080] Establish a drying demand index H with time as the horizontal axis α is the coordinate system of the ordinate;

[0081] Plotted at the detection period t A ~t B Curve H of drying demand index changing with time α (t) and the preset reference curve H α0 (t), preset reference curve H α0 (t) Based on comprehensive analysis of historical data and empirical data;

[0082] By formula The influence factor q is calculated; where ω 1 It is a preset proportional coefficient, determined based on historical experimental data.

[0083] Through the above technical solution, after the drying demand index exceeds the drying demand threshold, the current moment is traced back to the first door closing time as the previous detection period, and the drying demand index is changed over time through the drying demand index change curve H α (t) and the preset reference curve H α0 (t) deviation state analysis, and then through The influencing factor q is calculated and reacted by the ratio of the cumulative change amplitude of the actual drying demand index during the detection period to the cumulative change amplitude of the reference drying demand index. Obviously, the larger the ratio, the greater the actual drying demand, so as to dynamically update the influencing factor, and judge the reason for the change of the above drying demand index according to the situation after closing the door and adding new clothes. If no new clothes were added after the last closing of the door, but the actual drying demand index of the wardrobe increases, it means that there is a problem with the exhaust system in the wardrobe or the wardrobe with clothes stored last time was not thoroughly dried, which provides direction guidance for subsequent maintenance of the wardrobe.

[0084] The system further comprises an early warning module, which is used to issue an early warning of the state of the wardrobe;

[0085] The working process of the early warning module is:

[0086] By formula Calculate the drying evaluation coefficient k α ; In the formula, ω 2is a preset proportional coefficient determined based on historical experimental data, IF(m2) is a judgment function for the number of newly added clothes, when m2≤0, IF(m2)=1, when m2>0, IF(m2)=m2;

[0087] The drying evaluation factor k α And the drying evaluation interval [k αx , k αy ] for comparison;

[0088] If k α ∈[k αx , k αy ], the wardrobe is judged to be in normal state; otherwise, the wardrobe is judged to be abnormal and an early warning signal is issued.

[0089] Through the above technical solution, using the newly added early warning module, when working, Calculate the drying evaluation coefficient k α The wardrobe is evaluated after each drying operation. Obviously, if there are many new clothes and the influencing factor is large, it means that the changes of the two are consistent, and the above changes all come from the new clothes. On the contrary, if the drying evaluation coefficient is too large or too small, it means that there is an error between the influencing factor and the new clothes. In other words, the larger the drying evaluation coefficient, the greater the probability of problems with the wardrobe itself. This indirectly realizes the predictive self-inspection of the wardrobe, which improves the maintenance response efficiency to a certain extent.

[0090] The working process of the correction and adjustment module is as follows:

[0091] The current wardrobe drying demand index H α And disinfection and sterilization demand index X α Substitute into the formula group;

[0092] Calculate the theoretical drying time Δη H And theoretical disinfection and sterilization time Δη X , τ 1 , τ 2 is the conversion factor, which is determined based on the analysis of historical and experimental data;

[0093] According to Δη H The drying time η set by the user H , if |Δη H -η H |≤θ H , the drying time is set by the user, otherwise, the drying time is adjusted to η′. H Drying;

[0094] According to Δη XThe disinfection and sterilization time η set by the user X , if |Δη X -η X |≤θ X , disinfection and sterilization are carried out according to the disinfection and sterilization time set by the user, otherwise, disinfection and sterilization are carried out according to the adjusted disinfection and sterilization time η′ X Disinfection and sterilization; where θ H ,θ X It is the preset difference, which is obtained based on the analysis of empirical data and experimental data.

[0095] When Δη H >η H hour, When Δη H <η H hour,

[0096] When Δη X >η X hour, When Δη X <η X hour,

[0097] Through the above technical solution, according to the current wardrobe drying demand index H α And disinfection and sterilization demand index X α Predict the theoretical drying time Δη H And theoretical disinfection and sterilization time Δη X , and then the theoretical drying time Δη H And theoretical disinfection and sterilization time Δη X The drying time η set by the user H , Disinfection and sterilization time η X Obviously, if the two are within a reasonable deviation range, it means that the user has certain operating knowledge and the set time is reasonable. Therefore, it only needs to be executed according to the time set by the user. If it exceeds the reasonable deviation, it means that the time set by the user is too long or too short. If the setting time is too long, on the one hand, it will lead to unnecessary increase in energy consumption, and on the other hand, it will cause excessive damage to the clothes and affect the life of the clothes. Therefore, in this embodiment, by respectively setting Δη H >η H hour, When Δη H <η H hour, And when Δη X >η X hour, When Δη X<η X hour, That is to say, after the user sets the time, the system will calibrate and analyze it. If it is reasonable, it will be executed. If it is unreasonable, the actual operating time of the drying module or the disinfection and sterilization module will be adjusted while keeping the user-set time unchanged, so as to achieve the purpose of adapting the actual needs of the user and the wardrobe, thereby achieving energy saving and consumption reduction while improving user satisfaction.

[0098] The process of evaluating the status of the overall wardrobe is:

[0099] Divide a working cycle into several sub-cycles and mark the start time of each sub-cycle as t j0 , the end time point is marked as t j1 ;

[0100] Mark the sub-periods without new clothes as yellow periods, and the remaining sub-periods as red periods;

[0101] Count the number of wardrobes N in the yellow cycle in each sub-cycle j黄 and the number of wardrobes in the red cycle N j红 ;

[0102] Then through the formula The overall wardrobe status evaluation coefficient G is calculated, where m is the total number of wardrobes, μ i1 , μ i2 is a preset coefficient, selected and determined based on historical data, Δβ is a reference value obtained based on historical data, n is the number of sub-periods, j is the jth sub-period, γ j is the weight coefficient corresponding to the j-th sub-period.

[0103] Through the above technical solution, a method for evaluating the entire wardrobe area is given. By dividing the sub-cycles, the change amplitudes of the drying demand index and the disinfection demand index in each sub-cycle are accumulated and then summed to obtain the change of each wardrobe in each sub-cycle, so as to realize the evaluation of the overall wardrobe area. Obviously, if the overall wardrobe state evaluation coefficient G ≥ the preset warning value, it means that the state stability of the entire wardrobe area is poor, indicating that there is a large volatility problem in the use of the drying module or the disinfection module of the wardrobe. At the same time, in combination with The relationship between the status of each wardrobe and newly added clothing can be analyzed more accurately, further improving the accuracy of the overall wardrobe area assessment.

[0104] It should be noted that the calculation formulas and various parameters involved in the calculation in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0105] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An intelligent wardrobe control system based on the Internet of Things, characterized in that: include: The cabinet status data collection module collects the environmental data inside the wardrobe based on the detection instruments arranged inside the wardrobe, including humidity, temperature, air quality and odor data; The clothing data collection module takes pictures of the clothing in the closet based on the surveillance camera installed inside the closet to obtain the number of clothing; Data analysis and processing module, including a drying analysis unit and a disinfection and sterilization analysis unit; A drying analysis unit is used to analyze and calculate according to humidity, temperature and the amount of clothes to obtain a drying demand index; The disinfection and sterilization analysis unit is used to analyze and calculate the humidity, air quality and odor data to obtain the disinfection and sterilization demand index; A control module, used to compare the drying demand index and the disinfection demand index with the corresponding preset threshold intervals, and determine whether to start the drying module and / or the disinfection module according to the comparison results; A correction and adjustment module is used to perform correction analysis on the drying time and / or disinfection and sterilization time set by the user, and determine whether to adjust according to the result of the correction analysis; A communication module, used to communicate and connect the cabinet status data acquisition module, the clothing status data acquisition module, the data analysis and processing module and the control module; The working process of the drying analysis unit is as follows: Based on the temperature and humidity sensor, the temperature T and humidity RH inside the wardrobe are detected in real time; Based on the surveillance camera, the number of clothes m1 and the number of newly added clothes m2 in the closet are obtained, and the total amount of clothes M is obtained by adding m1+m2; Substitute the temperature T, humidity RH and total amount of clothing M into the formula The drying demand index H of the αth wardrobe is calculated α ; In the formula is the preset weight coefficient, q is the impact factor; The calculated drying demand index H α And the preset drying demand threshold H αth Make comparisons; If H α ≥H αth , the drying module is started, otherwise, the drying module is not started; The process of obtaining the impact factor is: Get the time points of the wardrobe door opening and closing for the i-th time, and mark them as H α ≥H αth The moment of time is taken as the end time point of the detection period t B , find the first closing time backward as the starting time point of the detection period t A ; Establish a drying demand index H with time as the horizontal axis α is the coordinate system of the ordinate; Plotted at the detection period t A ~t B Curve H of drying demand index changing with time α (t) and the preset reference curve H α0 (t); By formula The influence factor q is calculated; where ω1 is the preset proportional coefficient.

2. The smart wardrobe control system based on the Internet of Things according to claim 1 is characterized in that: The system further comprises an early warning module, which is used to issue an early warning of the state of the wardrobe; The working process of the early warning module is: By formula Calculate the drying evaluation coefficient k α ; In the formula, ω2 is the preset proportional coefficient, IF(m2) is the judgment function about the number of newly added clothes, when m2≤0, IF(m2)=1, when m2>0, IF(m2)=m2; The drying evaluation factor k α And the drying evaluation interval [k αx , k αy ] for comparison; If k α ∈[k αx , k αy ], the wardrobe is judged to be in normal state; otherwise, the wardrobe is judged to be abnormal and an early warning signal is issued.

3. The smart wardrobe control system based on the Internet of Things according to claim 2 is characterized in that: The working process of the disinfection and sterilization analysis unit is as follows: The ammonia concentration P inside the closet is detected based on the odor sensor, and the air quality AQI inside the closet is detected based on the air quality sensor; Substitute ammonia concentration P, air quality AQ I and humidity RH into the formula Calculate the disinfection demand index X of the αth wardrobe α ; In the formula, RH0, AQI0, and P0 are the warning values ​​of humidity, air quality, and ammonia concentration, respectively, which are comprehensively formulated based on historical data and empirical data; The calculated disinfection and sterilization demand index X α The preset drying requirement threshold X αth Make comparisons; If X α ≥X αth , the drying module is started, otherwise, the drying module is not started.

4. The smart wardrobe control system based on the Internet of Things according to claim 1 or 3, characterized in that: The working process of the correction and adjustment module is as follows: The current wardrobe drying demand index H α And disinfection and sterilization demand index X α Substitute into the formula group; Calculate the theoretical drying time Δη H And theoretical disinfection and sterilization time Δη X , τ1 and τ2 are conversion coefficients; According to Δη H The drying time η set by the user H ,like The drying time is set by the user, otherwise, the drying time is adjusted. Drying; According to Δη X The disinfection and sterilization time η set by the user X ,like The disinfection and sterilization will be carried out according to the disinfection and sterilization time set by the user, otherwise, the disinfection and sterilization will be carried out according to the adjusted disinfection and sterilization time. To disinfect and sterilize; is the preset difference.

5. The smart wardrobe control system based on the Internet of Things according to claim 4 is characterized in that: When H >the H when When H <the> H when When X >the X when When X <the> X when 6. The smart wardrobe control system based on the Internet of Things according to claim 1 is characterized in that: The process of evaluating the status of the overall wardrobe is: Divide a working cycle into several sub-cycles and mark the start time of each sub-cycle as t j0 , the end time point is marked as t j1 ; Mark the sub-periods without new clothes as yellow periods, and the remaining sub-periods as red periods; Count the number of wardrobes N in the yellow cycle in each sub-cycle j黄 and the number of wardrobes in the red cycle N j红 ; Then through the formula The overall wardrobe status evaluation coefficient G is calculated, where m is the total number of wardrobes, μ i1 , μ i2 is the preset coefficient, Δβ is the reference value based on historical data, n is the number of sub-periods, j is the jth sub-period, γ j is the weight coefficient corresponding to the j-th sub-period.

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