Intelligent control method for storage environment of tea storage cabinet

Abstract

The invention discloses an intelligent control method for a storage environment of a tea storage cabinet, and relates to the technical field of big data mining, and the method comprises the steps: obtaining the attribute data of tea leaves in the tea storage cabinet based on a heterogeneous sensor; initializing the storage environment range of the tea storage cabinet according to the attribute storage preference of the tea based on the attribute data of the tea in the tea storage cabinet; obtaining a historical tea taking record of the tea storage cabinet, analyzing a change trend of the tea taking record, and evaluating a tea taking demand preference of a user; based on the tea taking demand preference of the user, generating a user taking habit influence coefficient, and compensating for the storage environment range of the initialized tea storage cabinet to obtain a dynamic storage environment range of the tea storage cabinet; and generating a storage environment control scheme of the storage cabinet based on the dynamic storage environment range of the tea storage cabinet. The tea storage device has the advantages that the tea storage effect is improved, and user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data mining, and in particular to a method for intelligently controlling the storage environment of a tea storage cabinet. Background Art

[0002] The storage environment control of the tea cabinet refers to ensuring that the tea can be stored in the best conditions by adjusting and managing various factors in the tea storage environment (such as temperature and humidity) to maintain its quality, aroma and taste.

[0003] The current intelligent control of the storage environment of tea cabinets mainly adjusts the environmental range inside the tea cabinet by identifying the type of tea. It is unable to dynamically condition the storage environment based on the state of the tea cabinet, resulting in a rapid decline in the storage quality of tea. Summary of the invention

[0004] In order to solve the above technical problems, a method for intelligent control of the storage environment of a tea storage cabinet is provided. This technical solution solves the problem that the existing intelligent control of the storage environment of the tea storage cabinet mentioned above mainly adjusts the environmental range inside the tea storage cabinet by fixedly identifying the type of tea, and cannot dynamically condition the storage environment based on the state of the tea storage cabinet, resulting in a rapid decline in the storage quality of the tea.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is: A method for intelligently controlling the storage environment of a tea storage cabinet, comprising: Based on heterogeneous sensors, the attribute data of tea leaves in the tea storage cabinet are obtained; the attribute data of tea leaves include: tea year, tea light, and tea production time; Based on the attribute data of the tea in the tea storage cabinet, and according to the attribute storage preference of the tea, the storage environment range of the tea storage cabinet is initialized; the storage environment range includes: temperature data and humidity data; Obtain the historical tea collection cabinet's tea use records, analyze the changing trends of tea use records, and evaluate users' tea use demand preferences; Based on the user's tea taking demand preference, the user's taking habit influence coefficient is generated, and the storage environment range of the initial tea storage cabinet is compensated to obtain the dynamic storage environment range of the tea storage cabinet; Based on the dynamic storage environment range of the tea storage cabinet, a storage environment control solution for the tea storage cabinet is generated.

[0006] Preferably, based on the attribute data of the tea in the tea storage cabinet and according to the attribute storage preference of the tea, the storage environment range of the initialization tea storage cabinet specifically includes: Based on the attribute data of tea in the tea storage cabinet, the attribute data of tea is converted into numerical form using unique hot encoding, and the association between tea type and tea year is converted into tea attribute data vector matrix A using linear mapping;

[0007] in, is the jth tea attribute vector of the ith tea type, m is the total number of tea types, is the total number of tea attributes; Based on the tea attribute data vector matrix, the upper and lower limits of the corresponding storage environment are determined by the tea type, and the tea attribute vector of the tea is used as the storage preference influencing factor to construct a multinomial regression preference model for the tea storage environment, and calculate the storage environment range of the initial tea cabinet; The storage environment range of the calculation initialization tea storage cabinet is specifically:

[0008] In the formula, is the storage environment range value of the initialization tea cabinet for the j-th tea attribute vector of the i-th tea type, are the upper and lower limits of the storage environment for the i-th tea type, is the intercept, , , All are regression coefficients.

[0009] Preferably, obtaining the historical tea collection records of the tea cabinet, analyzing the changing trend of the tea collection records, and evaluating the user's tea collection demand preference specifically include: Obtain the tea taking record of the historical tea storage cabinet, perform standardization on the tea taking record, and obtain standardized data of the tea taking record of the historical tea storage cabinet; According to the standardized data of the tea taking record of the historical tea storage cabinet, the tea taking record is segmented by unit time to obtain the time series data of the tea taking record of the historical tea storage cabinet; Based on the time series data of tea use records in the historical tea cabinet, the unit time is used as the observation window, the time series data of tea use records is used as the observation attribute, and the sliding window is used to obtain the time series characteristic data of tea use per unit time. Based on the time series characteristic data of tea use per unit time, the tea use trend in the time series characteristic data of tea use is analyzed by time series analysis, and the tea use value per unit time in the future is predicted; According to the predicted tea consumption value per unit time in the future, the overall tea consumption value under the statistical time length is calculated to calculate the user's tea consumption demand preference index; The predicted tea usage value per unit time in the future is specifically:

[0010] In the formula, is the usage value of the i-th tea type in t unit time, is a constant term, For the The lag coefficient, t- The usage value of the i-th tea type per unit time of lag period, For the The sliding average coefficient, for The error term per unit time is a moving average, is the white noise error term of t time units.

[0011] The calculation of the user's tea use demand preference index is specifically:

[0012] In the formula, is the demand preference index of the i-th tea type in t unit time, is the total usage value of the i-th tea type in t unit time.

[0013] Preferably, based on the user's tea taking demand preference, the user's taking habit influence coefficient is generated, and compensation is performed for the storage environment range of the initialized tea storage cabinet. The dynamic storage environment range of the tea storage cabinet is obtained specifically including: Normalizing the user's tea-taking demand preference index, performing several rounds of iterative division and clustering according to the tea-taking demand preference index per unit time, and obtaining the tea-taking demand preference cluster per unit time; According to the tea type access demand preference cluster per unit time, weights are assigned to the tea type access demand preference index that affects the storage environment in the tea storage cabinet in the tea type access demand preference cluster according to the entropy weight method; According to the weight of the usage preference index and the user's tea usage preference index, the user's usage habit influence coefficient is calculated; The storage environment range of the initial tea storage cabinet is supplemented by using the user's usage habit influence coefficient to obtain the dynamic storage environment range of the tea storage cabinet; The dynamic storage environment range of the tea storage cabinet is obtained as follows:

[0014] In the formula, is the dynamic storage environment range value of the tea cabinet of the i-th tea type, Obtain the influence coefficient of user habits, is the weight of the preference index for the i-th tea type, is the global parameter of temperature and humidity, The lower limit of the storage temperature of the tea type. The upper limit of the storage environment temperature for tea types.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes an intelligent control scheme for the storage environment of a tea storage cabinet. Based on the storage preference of tea leaves, the storage environment of the tea storage cabinet is initialized, and by analyzing the user's tea taking record and evaluating the taking demand preference, a personalized taking habit influence coefficient is generated, and the storage environment range is dynamically adjusted to generate a suitable control scheme. The beneficial effects are: improving the preservation effect of tea leaves and increasing user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of a method for intelligently controlling the storage environment of a tea storage cabinet; Figure 2 A flow chart of a method for initializing the storage environment range of a tea storage cabinet; Figure 3 A flow chart of the method for evaluating users' tea access demand preference; Figure 4 A flow chart of a method for obtaining a dynamic storage environment range of a tea storage cabinet; Figure 5 It is a schematic diagram of the structure of the electronic device of the present invention; Figure 6 It is a schematic diagram of the computer-readable storage medium structure of the present invention. DETAILED DESCRIPTION

[0017] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0018] Reference Figure 1 As shown, a method for intelligently controlling the storage environment of a tea storage cabinet comprises: Based on heterogeneous sensors, the attribute data of tea leaves in the tea storage cabinet are obtained; the attribute data of tea leaves include: tea year, tea light, and tea production time (before Qingming Festival, after Qingming Festival); Based on the attribute data of the tea in the tea storage cabinet, and according to the attribute storage preference of the tea, the storage environment range of the tea storage cabinet is initialized; the storage environment range includes: temperature data and humidity data; Obtain the historical tea collection cabinet's tea use records, analyze the changing trends of tea use records, and evaluate users' tea use demand preferences; Based on the user's tea taking demand preference, the user's taking habit influence coefficient is generated, and the storage environment range of the initial tea storage cabinet is compensated to obtain the dynamic storage environment range of the tea storage cabinet; Based on the dynamic storage environment range of the tea storage cabinet, a storage environment control solution for the tea storage cabinet is generated.

[0019] This solution initializes the storage environment of the tea cabinet based on the storage preference of tea leaves. By analyzing the user's tea retrieval records and evaluating the retrieval demand preferences, it generates a personalized retrieval habit influence coefficient, dynamically adjusts the storage environment range, and generates a suitable control solution. The beneficial effects are: improving the preservation effect of tea leaves and increasing user experience.

[0020] Reference Figure 2 As shown, based on the attribute data of the tea in the tea storage cabinet and according to the attribute storage preference of the tea, the storage environment range of the initialization tea storage cabinet specifically includes: Based on the attribute data of tea in the tea storage cabinet, the attribute data of tea is converted into numerical form using unique hot encoding, and the association between tea type and tea year is converted into tea attribute data vector matrix A using linear mapping;

[0021] in, is the jth tea attribute vector of the ith tea type, m is the total number of tea types, is the total number of tea attributes; Based on the tea attribute data vector matrix, the upper and lower limits of the corresponding storage environment are determined by the tea type, and the tea attribute vector of the tea is used as the storage preference influencing factor to construct a multinomial regression preference model for the tea storage environment, and calculate the storage environment range of the initial tea cabinet; The storage environment range of the calculation initialization tea storage cabinet is specifically:

[0022] In the formula, is the storage environment range value of the initialization tea cabinet for the j-th tea attribute vector of the i-th tea type, are the upper and lower limits of the storage environment for the i-th tea type, is the intercept, , , All are regression coefficients.

[0023] This solution converts the attribute data of tea (such as type, year, etc.) into numerical form, generates a tea attribute vector matrix using one-hot encoding and linear mapping, and builds a multinomial regression model based on these attribute data to determine the storage environment requirements of each type of tea. The model automatically calculates the upper and lower limits of the optimal storage environment by calculating the association between the type of tea and its storage environment, and realizes the intelligent initialization setting of the tea cabinet. The beneficial effect is to ensure that the tea is stored under optimal conditions, thereby maximizing its flavor and quality.

[0024] Reference Figure 3 As shown, obtaining the historical tea collection cabinet's tea use records, analyzing the changing trend of tea use records, and evaluating the user's tea use demand preferences specifically include: Obtain the tea taking record of the historical tea storage cabinet, perform standardization on the tea taking record, and obtain standardized data of the tea taking record of the historical tea storage cabinet; According to the standardized data of the tea taking record of the historical tea storage cabinet, the tea taking record is segmented by unit time to obtain the time series data of the tea taking record of the historical tea storage cabinet; Based on the time series data of tea use records in the historical tea cabinet, the unit time is used as the observation window, the time series data of tea use records is used as the observation attribute, and the sliding window is used to obtain the time series characteristic data of tea use per unit time. Based on the time series characteristic data of tea use per unit time, the tea use trend in the time series characteristic data of tea use is analyzed by time series analysis, and the tea use value per unit time in the future is predicted; According to the predicted tea consumption value per unit time in the future, the overall tea consumption value under the statistical time length is calculated to calculate the user's tea consumption demand preference index; The predicted tea usage value per unit time in the future is specifically:

[0025] In the formula, is the usage value of the i-th tea type in t unit time, is a constant term, For the The lag coefficient, t- The usage value of the i-th tea type per unit time of lag period, For the The sliding average coefficient, for The error term per unit time is a moving average, is the white noise error term of t time units.

[0026] The tea taking demand preference index of the user is calculated as follows:

[0027] In the formula, is the demand preference index of the i-th tea type in t unit time, is the total usage value of the i-th tea type in t unit time.

[0028] This solution constructs time series data of tea use by standardizing the historical tea cabinet tea use records, and uses sliding windows to extract characteristic data per unit time. Through time series analysis methods, the changing trend of tea use is identified and analyzed, and the future tea use demand per unit time is predicted. According to the prediction results, the overall tea use value within a certain time range is counted to calculate the user's tea use demand preference index. The beneficial effect is to provide a target object for the environmental control of the tea cabinet and improve the accuracy of storage environment decision-making.

[0029] Reference Figure 4 As shown, based on the user's tea taking demand preference, the user's taking habit influence coefficient is generated, and the storage environment range of the initial tea storage cabinet is compensated to obtain the dynamic storage environment range of the tea storage cabinet, which specifically includes: Normalizing the user's tea-taking demand preference index, performing several rounds of iterative division and clustering according to the tea-taking demand preference index per unit time, and obtaining the tea-taking demand preference cluster per unit time; According to the tea type access demand preference cluster per unit time, weights are assigned to the tea type access demand preference index that affects the storage environment in the tea storage cabinet in the tea type access demand preference cluster according to the entropy weight method; According to the weight of the usage preference index and the user's tea usage preference index, the user's usage habit influence coefficient is calculated; The storage environment range of the initial tea storage cabinet is supplemented by using the user's usage habit influence coefficient to obtain the dynamic storage environment range of the tea storage cabinet; The dynamic storage environment range of the tea storage cabinet is obtained as follows:

[0030] In the formula, is the dynamic storage environment range value of the tea cabinet of the i-th tea type, Obtain the influence coefficient of user habits, is the weight of the preference index for the i-th tea type, is the global parameter of temperature and humidity, The lower limit of the storage temperature of the tea type. The upper limit of the storage environment temperature for tea types.

[0031] It is understandable that since the tea in the tea storage cabinet is under the optimal storage environment, the oxidation state of the tea is slow. However, when faced with the external environment interference when the tea is taken for a long time, the internal oxidation rate of the tea will be aggravated. Therefore, based on the user's tea taking demand preference index, the influence coefficient of the user's taking habit is analyzed, and the tea is replenished synchronously (providing temperature or lowering temperature) when it is taken to maximize the state of the tea in the tea storage cabinet.

[0032] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

[0033] Furthermore, the method or system according to the embodiment of the present application can also be Figure 5 The electronic device architecture shown in FIG. Figure 5 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store a method for intelligently controlling the storage environment of a tea storage cabinet provided in the present application. The electronic device 500 may also include a user interface 508. Of course, Figure 5 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 5 One or more components of an electronic device are shown.

[0034] Figure 6 Schematic diagram of a computer-readable storage medium structure provided by an embodiment of the present application. Figure 6 As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, a method for intelligently controlling the storage environment of a tea storage cabinet according to an embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0035] When the computer program is executed by a central processing unit (CPU), the above functions defined in the method of the present application are performed.

[0036] The methods, apparatuses, and devices of the present application may be implemented in many ways. For example, the methods, apparatuses, and devices of the present application may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present application are not limited to the order specifically described above unless otherwise specified. In addition, in some embodiments, the present application may also be implemented as programs recorded in a recording medium, which include machine-readable instructions for implementing the method according to the present application. Therefore, the present application also covers recording media storing programs for executing the method according to the present application.

Claims

1. A method for intelligently controlling the storage environment of a tea storage cabinet, characterized in that: include: Based on heterogeneous sensors, the attribute data of tea leaves in the tea storage cabinet is obtained; The attribute data of the tea include: tea year, tea light, and tea production time; Based on the attribute data of the tea in the tea storage cabinet, and according to the attribute storage preference of the tea, the storage environment range of the tea storage cabinet is initialized; the storage environment range includes: temperature data and humidity data; Obtain the historical tea collection cabinet's tea use records, analyze the changing trends of tea use records, and evaluate users' tea use demand preferences; Based on the user's tea taking demand preference, the user's taking habit influence coefficient is generated, and the storage environment range of the initial tea storage cabinet is compensated to obtain the dynamic storage environment range of the tea storage cabinet; Based on the dynamic storage environment range of the tea storage cabinet, a storage environment control solution for the tea storage cabinet is generated.

2. The method for intelligently controlling the storage environment of a tea storage cabinet according to claim 1, characterized in that: Based on the attribute data of the tea in the tea cabinet, according to the attribute storage preference of the tea, the storage environment range of the tea cabinet is initialized to include: Based on the attribute data of tea in the tea storage cabinet, the attribute data of tea is converted into numerical form using unique hot encoding, and the association between tea type and tea year is converted into tea attribute data vector matrix A using linear mapping; ； in, is the jth tea attribute vector of the ith tea type, m is the total number of tea types, is the total number of tea attributes; Based on the tea attribute data vector matrix, the upper and lower limits of the corresponding storage environment are determined by the tea type. The tea attribute vector of the tea is used as the storage preference influencing factor to construct a multinomial regression preference model of the tea storage environment, and the storage environment range of the initialized tea cabinet is calculated.

3. The method for intelligently controlling the storage environment of a tea storage cabinet according to claim 2, characterized in that: The storage environment range of the calculation initialization tea storage cabinet is specifically: ； In the formula, is the storage environment range value of the initialization tea cabinet for the j-th tea attribute vector of the i-th tea type, are the upper and lower limits of the storage environment for the i-th tea type, is the intercept, , , All are regression coefficients.

4. The method for intelligently controlling the storage environment of a tea storage cabinet according to claim 3, characterized in that: Obtain the historical tea collection cabinet's tea use records, analyze the changing trends of tea use records, and evaluate the user's tea use demand preferences, including: Obtain the tea taking record of the historical tea storage cabinet, perform standardization on the tea taking record, and obtain standardized data of the tea taking record of the historical tea storage cabinet; According to the standardized data of the tea taking record of the historical tea storage cabinet, the tea taking record is segmented by unit time to obtain the time series data of the tea taking record of the historical tea storage cabinet; Based on the time series data of tea use records in the historical tea cabinet, the unit time is used as the observation window, the time series data of tea use records is used as the observation attribute, and the sliding window is used to obtain the time series characteristic data of tea use per unit time. Based on the time series characteristic data of tea use per unit time, the tea use trend in the time series characteristic data of tea use is analyzed by time series analysis, and the tea use value per unit time in the future is predicted; According to the predicted tea consumption value per unit time in the future, the overall tea consumption value under the statistical time length is calculated to calculate the user's tea consumption demand preference index.

5. The method for intelligently controlling the storage environment of a tea storage cabinet according to claim 4, characterized in that: The predicted tea usage value per unit time in the future is specifically: ； In the formula, is the usage value of the i-th tea type in t unit time, is a constant term, For the The lag coefficient, t- The usage value of the i-th tea type per unit time of lag period, For the The sliding average coefficient, for The error term per unit time is a moving average, is the white noise error term of t unit time; The calculation of the user's tea use demand preference index is specifically: ； In the formula, is the demand preference index of the i-th tea type in t unit time, is the total usage value of the i-th tea type in t unit time.

6. The method for intelligently controlling the storage environment of a tea storage cabinet according to claim 5, characterized in that: Based on the user's tea taking demand preference, the user's taking habit influence coefficient is generated, and compensation is performed for the storage environment range of the initialized tea storage cabinet. The dynamic storage environment range of the tea storage cabinet is obtained, which specifically includes: Normalizing the user's tea-taking demand preference index, performing several rounds of iterative division and clustering according to the tea-taking demand preference index per unit time, and obtaining the tea-taking demand preference cluster per unit time; According to the tea type access demand preference cluster per unit time, weights are assigned to the tea type access demand preference index that affects the storage environment in the tea storage cabinet in the tea type access demand preference cluster according to the entropy weight method; According to the weight of the usage preference index and the user's tea usage preference index, the user's usage habit influence coefficient is calculated; The user's usage habit influence coefficient is used to supplement the storage environment range of the initialized tea storage cabinet to obtain the dynamic storage environment range of the tea storage cabinet.

7. The method for intelligently controlling the storage environment of a tea storage cabinet according to claim 6, characterized in that: The dynamic storage environment range of the tea cabinet is specifically obtained as follows: ； In the formula, is the dynamic storage environment range value of the tea cabinet of the i-th tea type, Obtain the influence coefficient of user habits, is the weight of the preference index for the i-th tea type, is the global parameter of temperature and humidity, The lower limit of the storage temperature of the tea type. The upper limit of the storage environment temperature for tea types.

8. An electronic device, characterized in that: include: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the storage environment intelligent control method of a tea storage cabinet as described in any one of claims 1-7.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a method for intelligently controlling the storage environment of a tea storage cabinet according to any one of claims 1 to 7 is implemented.

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