Intelligent control method and system applied to intelligent showcase

Abstract

The invention provides an intelligent control method and system applied to an intelligent showcase, and belongs to the technical field of intelligent control. The intelligent control method applied to the intelligent showcase comprises the following steps: acquiring historical working data of the intelligent showcase; calculating comprehensive reliability data of each intelligent showcase according to the historical working data; determining a plurality of intelligent showcase groups based on preset intelligent showcase partitions; based on preset showcase importance data and the comprehensive reliability data of each intelligent showcase, analyzing maintenance priority data of each intelligent showcase group; by adopting the scheme, the maintenance of the intelligent showcase can be reasonably arranged, and the exhibition viewing experience of tourists is ensured.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology, and in particular to an intelligent control method and system applied to an intelligent showcase. Background Art

[0002] An intelligent showcase is a new type of showcase that can protect and monitor the exhibits inside the cabinet and interact with people; generally, various types of sensors such as temperature and humidity are set in the intelligent showcase to monitor the preservation status of the exhibits inside the cabinet; however, as a comprehensive item containing electronic devices and physical material structures, the main function of the intelligent showcase is to protect the exhibits, interact with tourists, introduce the exhibits, and provide tourists with viewing. Therefore, the higher the reliability of the intelligent showcase, the higher its protection performance for the exhibits; when the reliability of the intelligent showcase decreases, maintenance of the intelligent showcase is required. At this time, the intelligent showcase cannot continue to provide exhibits for tourists to view. Therefore, it is necessary to reasonably arrange the maintenance of the intelligent showcase without affecting the viewing experience of tourists. Summary of the Invention

[0003] This application provides an intelligent control method and system applied to an intelligent showcase, which can reasonably arrange the maintenance of the intelligent showcase and ensure the viewing experience of tourists.

[0004] In a first aspect, this application provides an intelligent control method applied to an intelligent showcase. The method includes: Obtain the historical working data of the intelligent showcase; the historical working data includes the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the single - time exhibition interaction person - times data from the last maintenance of the intelligent showcase to the current moment; Calculate the comprehensive reliability data of each intelligent showcase according to the historical working data; the comprehensive reliability data is associated with the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the single - time exhibition interaction person - times data; Determine multiple intelligent showcase groups based on a preset intelligent showcase partition; there are intelligent showcases with associated exhibits among multiple exhibitions within the preset intelligent showcase partition; the intelligent showcase group is a combination of intelligent showcases belonging to the same preset intelligent showcase partition; Analyze the maintenance priority data of each intelligent showcase group based on the preset showcase importance data and the comprehensive reliability data of each intelligent showcase; the maintenance priority data is associated with the preset showcase importance data and the comprehensive reliability data of each intelligent showcase.

[0005] Further, calculate the comprehensive reliability data of each intelligent display cabinet according to the historical working data; the comprehensive reliability data associated with the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the single - time exhibition interaction person - times data includes: Obtain the number - of - times - exceeding - threshold impact data based on the single - time exhibition interaction person - times data and a preset person - times threshold; the number - of - times - exceeding - threshold impact data is the number - of - times data when the single - time exhibition interaction person - times data is not less than the preset person - times threshold; Calculate the basic reliability data of each intelligent display cabinet according to the comprehensive reliability data associated with the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the number - of - times - exceeding - threshold impact data; Calculate the reliability trend impact data according to the preset historical maintenance records and the basic reliability data of each intelligent display cabinet; Calculate the comprehensive reliability data of each intelligent display cabinet according to the basic reliability data and the reliability trend impact data.

[0006] Further, the calculation method of the basic reliability data includes: ; In the formula, is the basic reliability data, is the total working duration data; is the single - time average working duration data; is the total number of exhibition interaction person - times data; is the number - of - times - exceeding - threshold impact data, is the natural constant; are the preset first weight, the preset second weight, and the preset third weight respectively; and, .

[0007] Further, the calculation method of the reliability trend impact data includes: Select a preset number of historical time periods with the same duration according to the preset historical maintenance records; the preset historical maintenance records include all the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the single - time exhibition interaction person - times data from when the intelligent display cabinet is put into exhibition work to the current moment; Suppose there are n historical time periods, then the basic reliability data of the i - th historical time period is ; where the first historical time period is the historical time period closest to the current moment, and the n - th historical time period is the historical time period farthest from the current moment; Calculate n - 1 reliability differences ; where, ; Judge whether all the above reliability differences are greater than 0 or all not greater than 0; If so, the calculation method of the reliability trend influence data is ; If not, the calculation method of the reliability trend influence data is ; where is the number of reliability differences greater than 0, is the number of reliability differences not greater than 0.

[0008] Furthermore, the calculation method of the maintenance priority data includes: Taking any intelligent display cabinet group as an example, assuming that there are m intelligent display cabinets in the intelligent display cabinet group, then the basic reliability data of the th intelligent display cabinet is , and the reliability trend influence data of the th intelligent display cabinet is ; ; In the formula, is the maintenance priority data, is the preset display cabinet importance data of the th intelligent display cabinet, is the reliability trend influence data of the th intelligent display cabinet.

[0009] In a second aspect, the present application provides an intelligent control system applied to an intelligent display cabinet. The system includes: An acquisition module, configured to acquire historical working data of the intelligent display cabinet; the historical working data includes total working duration data, single - time average working duration data, total number of exhibition interaction person - times data, and single - time exhibition interaction person - times data between the last maintenance of the intelligent display cabinet and the current moment; A calculation module, configured to calculate comprehensive reliability data of each intelligent display cabinet according to the historical working data; the comprehensive reliability data is associated with the total working duration data, single - time average working duration data, total number of exhibition interaction person - times data, and single - time exhibition interaction person - times data; A determination module, configured to determine a plurality of intelligent display cabinet groups based on a preset intelligent display cabinet partition; there are associated intelligent display cabinets among the exhibits of multiple exhibitions within the preset intelligent display cabinet partition; the intelligent display cabinet group is a combination of intelligent display cabinets belonging to the same preset intelligent display cabinet partition; An analysis module, configured to analyze the maintenance priority data of each intelligent display cabinet group based on the preset display cabinet importance data and the comprehensive reliability data of each intelligent display cabinet; the maintenance priority data is associated with the preset display cabinet importance data and the comprehensive reliability data of each intelligent display cabinet.

[0010] Further, the calculation module is further configured to calculate the comprehensive reliability data of each intelligent display cabinet according to the historical working data; the comprehensive reliability data is associated with the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the single - time exhibition interaction person - times data, and includes: Obtain the number - of - times - over - limit influence data based on the single - time exhibition interaction person - times data and a preset person - times threshold; the number - of - times - over - limit influence data is the number - of - times data when the single - time exhibition interaction person - times data is not less than the preset person - times threshold; Calculate the basic reliability data of each intelligent display cabinet according to the comprehensive reliability data associated with the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the number - of - times - over - limit influence data; Calculate the reliability trend influence data according to the preset historical maintenance records and the basic reliability data of each intelligent display cabinet; Calculate the comprehensive reliability data of each intelligent display cabinet according to the basic reliability data and the reliability trend influence data.

[0011] Further, the calculation module is further configured to, the calculation method of the basic reliability data includes: ; In the formula, is the basic reliability data, is the total working duration data; is the single - time average working duration data; is the total number of exhibition interaction person - times data; is the number - of - times - over - limit influence data, is the natural constant; are the preset first weight, the preset second weight, and the preset third weight respectively; and, .

[0012] Further, the calculation module is further configured to, the calculation method of the reliability trend influence data includes: Select a preset number of historical time periods with the same duration according to the preset historical maintenance records; the preset historical maintenance records include all the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the single - time exhibition interaction person - times data from when the intelligent display cabinet is put into exhibition work to the current moment; Suppose there are n historical time periods, then the basic reliability data of the i - th historical time period is ; where, the first historical time period is the historical time period closest to the current moment, and the n - th historical time period is the historical time period farthest from the current moment; Calculate n - 1 reliability differences ; where, ; Determine whether all of the above reliability differences are greater than 0 or all not greater than 0; If so, the calculation method of the reliability trend influence data is ; If not, the calculation method of the reliability trend influence data is ; where is the number of reliability differences greater than 0, is the number of reliability differences not greater than 0.

[0013] Furthermore, the analysis module is further configured such that the calculation method of the maintenance priority data includes: Taking any intelligent display cabinet group as an example, assuming that there are m intelligent display cabinets in the intelligent display cabinet group, then the basic reliability data of the th intelligent display cabinet is , and the reliability trend influence data of the th intelligent display cabinet is ; ; In the formula, is the maintenance priority data, is the preset display cabinet importance data of the th intelligent display cabinet, is the reliability trend influence data of the th intelligent display cabinet.

[0014] It should be understood that the content described in the Summary of the Invention section is not intended to limit the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] With reference to the accompanying drawings and the following detailed description, the above and other features, advantages, and aspects of the embodiments of the present application will become more apparent. In the drawings, the same or similar reference numerals denote the same or similar elements, where: Figure 1 shows a flowchart of an intelligent control method applied to an intelligent display cabinet in an embodiment of the present application; Figure 2 shows a block diagram of an intelligent control system applied to an intelligent display cabinet in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Apparently, the described embodiments are some but not all of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0017] In addition, the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after.

[0018] This application provides an intelligent control method and system for an intelligent display cabinet, which can reasonably arrange the maintenance of the intelligent display cabinet and ensure the viewing experience of visitors.

[0019] In a first aspect, this application provides an intelligent control method for an intelligent display cabinet. Refer to Figure 1 , and the specific steps included in the method are as follows.

[0020] Step S110: Obtain the historical working data of the intelligent display cabinet; the historical working data includes the total working duration data, the single - time average working duration data, the total number of exhibition interactions, and the single - time number of exhibition interactions between the last maintenance of the intelligent display cabinet and the current moment.

[0021] In the embodiments of this application, the intelligent display cabinet can not only interact with visitors using an electronic display screen, but some intelligent display cabinets can also perform mechanical actions such as rising, falling, and rotating. Therefore, to ensure the reliability of the intelligent display cabinet and the electronic devices inside it, to ensure the protection performance of the intelligent display cabinet for exhibits, and to reasonably arrange the maintenance of the intelligent display cabinet, it is necessary to ensure the viewing experience of visitors.

[0022] It can be understood that the above total working duration data refers to the total working time of the intelligent display cabinet; the single - time average working duration refers to, under normal circumstances, the working duration from the last power - on to the next power - off of the intelligent display cabinet. Calculate the sum of all single - time working durations and then find the average, which is the single - time average working duration; the total number of exhibition interaction person - times data refers to the total number of visitors who interact with the intelligent display cabinet. The intelligent display cabinet is equipped with devices such as infrared cameras to record the number of interactions; similarly, the single - time exhibition interaction person - times data refers to the person - times data of interactions with the intelligent display cabinet from the last power - on to the next power - off of the intelligent display cabinet under normal circumstances; it should be noted that generally, during an exhibition, when the exhibition starts, the intelligent display cabinet is powered on, and when the exhibition ends, the intelligent display cabinet is powered off; therefore, the general single - time data refers to the data generated during one exhibition.

[0023] Step S120: Calculate the comprehensive reliability data of each intelligent display cabinet according to the historical working data; the comprehensive reliability data is associated with the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the single - time exhibition interaction person - times data.

[0024] In the embodiment of the present application, calculating the comprehensive reliability data of each intelligent display cabinet according to the historical working data specifically includes obtaining the influence data of the number of times of exceeding the threshold based on the single - time exhibition interaction person - times data and a preset person - times threshold; the influence data of the number of times of exceeding the threshold is the number - times data when the single - time exhibition interaction person - times data is not less than the preset person - times threshold; calculate the basic reliability data of each intelligent display cabinet according to the comprehensive reliability data associated with the total working duration data, the single - time average working duration data, the total number of exhibition interaction person - times data, and the influence data of the number of times of exceeding the threshold; calculate the reliability trend influence data according to the preset historical maintenance records and the basic reliability data of each intelligent display cabinet; calculate the comprehensive reliability data of each intelligent display cabinet according to the basic reliability data and the reliability trend influence data.

[0025] Specifically, the calculation method of the basic reliability data includes: ; In the formula, is the basic reliability data, is the total working duration data; is the single - time average working duration data; is the total number of exhibition interaction person - times data; is the influence data of the number of times of exceeding the threshold, is the natural constant; are the preset first weight, the preset second weight, and the preset third weight respectively; and, .

[0026] It can be understood that the calculation formula for the part of the data corresponding to the over - limit number of person - times here uses the activation function. Corresponding to the actual showcase interaction situation, it means that after exceeding the established number of interacting people, the impact on the intelligent showcase will increase sharply. However, after exceeding this threshold, the impact will not increase significantly. Therefore, the number data of the over - limit person - times is used as the parameter of the activation function here. It should be noted that the higher the basic reliability data here, the lower the actual reliability of the intelligent showcase, and maintenance needs to be carried out in a timely manner.

[0027] Specifically, the calculation method of the reliability trend impact data includes: Select a preset number of historical time periods with the same duration according to the preset historical maintenance records; the preset historical maintenance records include all the total working duration data, single - time average working duration data, total exhibition interaction person - times data, and single - time exhibition interaction person - times data from the time when the intelligent showcase was put into exhibition work to the current moment. Suppose there are n historical time periods, then the basic reliability data of the i - th historical time period is ; where the first historical time period is the historical time period closest to the current moment, and the n - th historical time period is the historical time period farthest from the current moment. Calculate n - 1 reliability differences ; where ; Judge whether the above - mentioned reliability differences are all greater than 0 or all not greater than 0; If so, the calculation method of the reliability trend impact data is ; If not, the calculation method of the reliability trend impact data is ; where is the number of reliability differences greater than 0, is the number of reliability differences not greater than 0.

[0028] It can be understood that the trend change of the reliability here is an analysis of the trend change based on the basic reliability data. Therefore, the correlation between this kind of reliability trend impact data and the actual reliability of the intelligent showcase is the same as the correlation between the basic reliability data and the actual reliability of the intelligent showcase; that is, if the reliability trend shows an upward trend, the higher the comprehensive reliability data, the lower the actual reliability of the intelligent showcase, and the more urgent the need for timely maintenance; vice versa.

[0029] Step S130: Determine multiple intelligent showcase groups based on the preset intelligent showcase partition; there are intelligent showcases with associated exhibits in multiple exhibitions within the preset intelligent showcase partition; the intelligent showcase group is a combination of intelligent showcases belonging to the same preset intelligent showcase partition.

[0030] It is understandable that the existence of a relationship between the exhibits here generally means that there is a certain relationship between the exhibits, such as paintings by the same painter, cultural relics unearthed from the same era, etc.

[0031] Step S140: Analyze the maintenance priority data of each intelligent showcase group based on the preset showcase importance data and the comprehensive reliability data of each intelligent showcase; the maintenance priority data is associated with the preset showcase importance data and the comprehensive reliability data of each intelligent showcase.

[0032] In the embodiment of the present application, the calculation method of the maintenance priority data specifically includes: Taking any intelligent showcase group as an example, assume that there are m intelligent showcases in the intelligent showcase group, then the basic reliability data of the th intelligent showcase is , and the reliability trend influence data of the th intelligent showcase is ; ; In the formula, is the maintenance priority data, is the preset showcase importance data of the th intelligent showcase, is the reliability trend influence data of the th intelligent showcase.

[0033] It is understandable that since the comprehensive reliability data of the intelligent showcase is inversely proportional to the reliability of the actual intelligent showcase, then the comprehensive reliability data is directly proportional to the maintenance priority data, and the preset showcase importance data is also directly proportional to the maintenance priority data. Therefore, the larger the maintenance priority data calculated by the above formula, the higher the maintenance priority of the intelligent showcase group.

[0034] It is understandable that generally, there is a relationship between the intelligent showcases in the intelligent showcase group. Therefore, for the exhibition organizer, when tourists visit the exhibition, all the intelligent showcases in the intelligent showcase group will be allocated to one area for the convenience of tourists to view as a whole; then for the actual showcase maintenance work, if only one or several intelligent showcases in an intelligent showcase group are maintained, it will inevitably affect the viewing experience of tourists, making it impossible for tourists to view all the exhibits in this area uniformly. Therefore, in this solution, the above method is used to uniformly maintain the intelligent showcase group, which not only ensures the safety of the exhibits but also improves the viewing experience of tourists.

[0035] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that this application is not limited by the described action sequence, because according to the embodiments of this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0036] In a second aspect, this application provides an intelligent control system applied to an intelligent display cabinet. As Figure 2 shown, the system includes an acquisition module 210, configured to acquire historical working data of the intelligent display cabinet; the historical working data includes total working duration data, single - time average working duration data, total number of exhibition interaction person - times data, and single - time exhibition interaction person - times data from the last maintenance of the intelligent display cabinet to the current moment; a calculation module 220, configured to calculate comprehensive reliability data of each intelligent display cabinet according to the historical working data; the comprehensive reliability data is associated with the total working duration data, single - time average working duration data, total number of exhibition interaction person - times data, and single - time exhibition interaction person - times data; a determination module 230, configured to determine a plurality of intelligent display cabinet groups based on a preset intelligent display cabinet partition; there are associated intelligent display cabinets among the exhibits of multiple exhibitions within the preset intelligent display cabinet partition; the intelligent display cabinet group is a combination of intelligent display cabinets belonging to the same preset intelligent display cabinet partition; an analysis module 240, configured to analyze maintenance priority data of each intelligent display cabinet group based on preset display cabinet importance data and the comprehensive reliability data of each intelligent display cabinet; the maintenance priority data is associated with the preset display cabinet importance data and the comprehensive reliability data of each intelligent display cabinet.

[0037] Further, the calculation module 220 is further configured to calculate the comprehensive reliability data of each intelligent display cabinet according to the historical working data; the comprehensive reliability data is associated with the total working duration data, single - time average working duration data, total number of exhibition interaction person - times data, and single - time exhibition interaction person - times data, including: Obtaining person - times over - limit times impact data based on the single - time exhibition interaction person - times data and a preset person - times threshold; the person - times over - limit times impact data is the number of times the single - time exhibition interaction person - times data is not less than the preset person - times threshold; Calculating basic reliability data of each intelligent display cabinet according to the comprehensive reliability data associated with the total working duration data, single - time average working duration data, total number of exhibition interaction person - times data, and person - times over - limit times impact data; Calculating reliability trend impact data according to a preset historical maintenance record and the basic reliability data of each intelligent display cabinet; Calculate the comprehensive reliability data of each intelligent display cabinet according to the basic reliability data and the reliability trend impact data.

[0038] Further, the calculation module 220 is further configured such that the calculation method of the basic reliability data includes: ; In the formula, is the basic reliability data, is the total working duration data; is the average working duration data per single time; is the total number of exhibition interaction person-times data; is the person-time overlimit times impact data, is the natural constant; are the preset first weight, the preset second weight, and the preset third weight respectively; and, .

[0039] Further, the calculation module 220 is further configured such that the calculation method of the reliability trend impact data includes: Select a preset number of historical time periods with the same duration according to the preset historical maintenance records; the preset historical maintenance records include all the total working duration data, the average working duration data per single time, the total number of exhibition interaction person-times data, and the number of person-times of single exhibition interaction data from the time when the intelligent display cabinet is put into exhibition work to the current moment; Suppose there are n historical time periods, then the basic reliability data of the i-th historical time period is ; where the first historical time period is the historical time period closest to the current moment, and the n-th historical time period is the historical time period farthest from the current moment; Calculate n - 1 reliability differences ; where, ; Judge whether the above reliability differences are all greater than 0 or all not greater than 0; If so, the calculation method of the reliability trend impact data is ; If not, the calculation method of the reliability trend impact data is ; where, is the number of reliability differences greater than 0, is the number of reliability differences not greater than 0.

[0040] Further, the analysis module 240 is further configured such that the calculation method of the maintenance priority data includes: Taking any intelligent display cabinet group as an example, suppose there are m intelligent display cabinets in the intelligent display cabinet group, then the basic reliability data of the -th intelligent display cabinet is , the reliability trend impact data of the th intelligent display cabinet is ; ; In the formula, is the maintenance priority data, is the preset display cabinet importance data of the th intelligent display cabinet, is the reliability trend impact data of the th intelligent display cabinet.

[0041] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the described device can refer to the corresponding process in the foregoing method embodiment, which will not be elaborated here.

[0042] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the disclosed scope in the present application is not limited to the technical solution formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the foregoing disclosed concept. For example, the technical solution formed by mutually replacing the above features with the (but not limited to) technical features with similar functions disclosed in the present application.

Claims

1. An intelligent control method applied to an intelligent showcase, characterized in that: include: Acquire historical working data of the smart showcase; the historical working data includes total working time data from the last maintenance of the smart showcase to the current moment, single average working time data, total exhibition interaction data, and single exhibition interaction data; Calculate the comprehensive reliability data of each smart showcase according to the historical working data; the comprehensive reliability data is associated with the total working time data, the single average working time data, the total number of exhibition interaction data and the single exhibition interaction data; Determine multiple smart showcase groups based on preset smart showcase partitions; The preset smart showcase partition includes multiple smart showcases with associated exhibits; the smart showcase group is a combination of smart showcases belonging to the same preset smart showcase partition; The maintenance priority data of each smart showcase group is analyzed based on the preset showcase importance data and the comprehensive reliability data of each smart showcase; the maintenance priority data is associated with the preset showcase importance data and the comprehensive reliability data of each smart showcase.

2. The method according to claim 1, characterized in that The comprehensive reliability data of each smart showcase is calculated based on the historical working data; the comprehensive reliability data is associated with the total working time data, the single average working time data, the total exhibition interaction data and the single exhibition interaction data, including: Based on the single exhibition interaction person-time data and the preset person-time threshold, the person-time exceeding limit impact data is obtained; the person-time exceeding limit impact data is the number of times the single exhibition interaction person-time data is not less than the preset person-time threshold; Calculate the basic reliability data of each smart showcase according to the comprehensive reliability data in association with the total working time data, the single average working time data, the total number of exhibition interaction data and the data on the impact of the number of excessive number of people; Calculate reliability trend impact data based on preset historical maintenance records and basic reliability data of each smart showcase; The comprehensive reliability data of each smart showcase is calculated according to the basic reliability data and the reliability trend impact data.

3. The method according to claim 2, characterized in that The calculation method of the basic reliability data includes: ； In the formula, As basic reliability data, Total working time data; The average working time for a single session; The total number of visitors who interacted with the exhibition; The data is affected by the number of times the limit is exceeded. is a natural constant; are respectively a preset first weight, a preset second weight and a preset third weight; and, .

4. The method according to claim 3, characterized in that: The calculation method of the reliability trend impact data includes: Select a preset number of historical time periods of the same duration according to the preset historical maintenance records; the preset historical maintenance records include all total working time data from the time when the smart showcase was put into exhibition work to the current moment, the average working time data of a single time, the total number of exhibition interaction data, and the number of single exhibition interaction data; Assuming there are n historical time periods, the basic reliability data of the i-th historical time period is ; Among them, the first historical time period is the historical time period closest to the current moment, and the nth historical time period is the historical time period farthest from the current moment; Calculate n-1 reliability differences ;in, ; Determine whether the above reliability differences are all greater than 0 or not greater than 0; If so, the reliability trend impact data is calculated as, ; If not, the reliability trend impact data is calculated as, ;in, is the number of reliability differences greater than 0, is the number of reliability differences not greater than 0.

5. The method according to claim 4, characterized in that The calculation method of the maintenance priority data includes: Take any smart showcase group as an example, assuming that the smart showcase group includes m smart showcases, then The basic reliability data of a smart showcase is , No. The reliability trend of smart showcases has an impact on the data ; ； In the formula, To maintain priority data, For the The preset showcase importance data of each smart showcase, For the The reliability trend of smart showcases affects the data.

6. An intelligent control system applied to an intelligent display cabinet, characterized in that: include: An acquisition module (210) is used to acquire historical working data of the smart showcase; the historical working data includes total working time data from the last maintenance of the smart showcase to the current moment, single average working time data, total exhibition interaction data, and single exhibition interaction data; A calculation module (220) is used to calculate comprehensive reliability data of each smart display cabinet based on the historical working data; the comprehensive reliability data is associated with the total working time data, the single average working time data, the total exhibition interaction person-time data and the single exhibition interaction person-time data; A determination module (230), configured to determine a plurality of smart showcase groups based on preset smart showcase partitions; The preset smart showcase partition includes multiple smart showcases with associated exhibits; the smart showcase group is a combination of smart showcases belonging to the same preset smart showcase partition; The analysis module (240) is used to analyze the maintenance priority data of each smart showcase group based on the preset showcase importance data and the comprehensive reliability data of each smart showcase; the maintenance priority data is associated with the preset showcase importance data and the comprehensive reliability data of each smart showcase.

7. The system according to claim 6, characterized in that The calculation module (220) is further configured to calculate comprehensive reliability data of each smart showcase based on the historical working data; the comprehensive reliability data is associated with the total working time data, the single average working time data, the total exhibition interaction person-time data and the single exhibition interaction person-time data, and includes: Based on the single exhibition interaction person-time data and the preset person-time threshold, the person-time exceeding limit impact data is obtained; the person-time exceeding limit impact data is the number of times the single exhibition interaction person-time data is not less than the preset person-time threshold; Calculate the basic reliability data of each smart showcase according to the comprehensive reliability data in association with the total working time data, the single average working time data, the total number of exhibition interaction data and the data on the impact of the number of excessive number of people; Calculate reliability trend impact data based on preset historical maintenance records and basic reliability data of each smart showcase; The comprehensive reliability data of each smart showcase is calculated according to the basic reliability data and the reliability trend impact data.

8. The system according to claim 7, characterized in that The calculation module (220) is further configured such that the calculation method of the basic reliability data includes: ； In the formula, As basic reliability data, Total working time data; The average working time for a single session; The total number of visitors who interacted with the exhibition; The data is affected by the number of times the limit is exceeded. is a natural constant; are respectively a preset first weight, a preset second weight and a preset third weight; and, .

9. The system according to claim 8, characterized in that The calculation module (220) is further configured such that the calculation method of the reliability trend impact data includes: Select a preset number of historical time periods of the same duration according to the preset historical maintenance records; the preset historical maintenance records include all total working time data from the time when the smart showcase was put into exhibition work to the current moment, the average working time data of a single time, the total number of exhibition interaction data, and the number of single exhibition interaction data; Assuming there are n historical time periods, the basic reliability data of the i-th historical time period is ; Among them, the first historical time period is the historical time period closest to the current moment, and the nth historical time period is the historical time period farthest from the current moment; Calculate n-1 reliability differences ;in, ; Determine whether the above reliability differences are all greater than 0 or not greater than 0; If so, the reliability trend impact data is calculated as, ; If not, the reliability trend impact data is calculated as, ;in, is the number of reliability differences greater than 0, is the number of reliability differences not greater than 0.

10. The system according to claim 9, characterized in that The analysis module (240) is further configured such that the calculation method of the maintenance priority data includes: Take any smart showcase group as an example, assuming that the smart showcase group includes m smart showcases, then The basic reliability data of a smart showcase is , No. The reliability trend of smart showcases has an impact on the data ; ； In the formula, To maintain priority data, For the The preset showcase importance data of each smart showcase, For the The reliability trend of smart showcases affects the data.

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