An information visualization management system and method based on digital twin

Abstract

The present invention discloses an information visualization management system and method based on digital twins, belonging to the field of digital twin technology. The present invention comprises the following steps: defining interest tags; calculating comprehensive interest values ​​of visitors to interest tags; screening exhibits in a venue to be visited; planning tour routes, obtaining the best tour route and pushing it to visitors; calculating the popularity index of exhibits in the venue to be visited, and obtaining a first exhibit set; obtaining a second exhibit set according to the best tour route; screening the first exhibit set and the second exhibit set, and obtaining a third exhibit set; generating an optimization plan for exhibits; the present invention can not only recommend suitable exhibits according to visitors' interest preferences, but also optimize the exhibit content in real time by analyzing the popularity of the exhibits and the interaction of the visitors, thereby timely adjusting the display mode and interactive content of the exhibits, and comprehensively improving the visiting experience and exhibition effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital twins, and specifically relates to an information visualization management system and method based on digital twins. Background Art

[0002] Digital twins make full use of data such as physical models, sensor updates, and operation history, integrate multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, and complete mapping in virtual space, thereby reflecting the full life cycle of the corresponding physical equipment; it has the following characteristics: Full life cycle means that digital twins can run through the entire cycle of the exhibits, including design, development, manufacturing, service, maintenance, and even scrap recycling;

[0003] With the rapid development of information technology, the digital transformation of museums has become an important trend in the cultural industry. As an important means of deep integration of virtual and reality, the introduction of digital twin technology into museums can achieve high-precision digital modeling and virtual display of exhibits, upgrade the traditional static exhibition mode to a dynamic interactive experience, and provide visitors with a variety of service methods.

[0004] However, the guided tour services provided by most museums currently mainly focus on fixed routes and general explanations, which are difficult to meet the diverse interests of visitors and cannot dynamically optimize the content of exhibits, affecting the visiting experience and exhibition effect;

[0005] Therefore, people urgently need an information visualization management system based on digital twins to solve the above problems. Summary of the invention

[0006] The purpose of the present invention is to provide an information visualization management system based on digital twins to solve the problems raised in the above-mentioned background technology.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] An information visualization management method based on digital twins, the method comprising the following steps:

[0009] S1. Obtain the visitor's historical visit data and define interest tags; calculate the visitor's comprehensive interest value for the interest tags based on the visitor's historical visit data;

[0010] S2. Obtain the data of exhibits in the venues to be visited, and screen the exhibits in the venues to be visited based on the comprehensive interest values ​​of the visitors to the interest tags; plan the tour routes based on the screened exhibits, obtain the best tour routes and push them to the visitors;

[0011] S3, obtaining real-time visit data of visitors, collecting statistics on the real-time visit data of visitors, calculating the popularity index of exhibits in the venues to be visited, classifying the exhibits in the venues to be visited, and obtaining a first exhibit set;

[0012] S4. According to the best tour route, the number of times the exhibits appear in the best tour route is counted, and the exhibits in the venue to be visited are classified to obtain a second exhibit set; the first exhibit set and the second exhibit set are screened to obtain a third exhibit set;

[0013] S5. Generate an optimization plan for the exhibits according to the third exhibit set; and push the optimization plan for the exhibits to the management visitor of the venue to be visited.

[0014] According to the above technical solution, step S1 includes the following:

[0015] S1-1, each time a visitor visits a venue recorded by the system, the visitor's visit data is obtained through sensors and guide equipment in the corresponding venue, all the visit data of the visitor are counted, and the visitor's historical visit data is generated;

[0016] The visit data includes exhibits visited, exhibit types, stay time and number of interactions; the exhibit types include history, art, technology, culture, nature, industry, commerce and education; the number of interactions includes the number of touch screen usage, voice usage, virtual exhibit viewing, game participation, etc.;

[0017] Define interest tags according to the exhibit type, where the interest tag corresponding to historical exhibits is history, the interest tag corresponding to art exhibits is art, the interest tag corresponding to science and technology exhibits is science and technology, the interest tag corresponding to cultural exhibits is culture, the interest tag corresponding to natural exhibits is nature, the interest tag corresponding to industrial exhibits is industry, the interest tag corresponding to commercial exhibits is business, and the interest tag corresponding to educational exhibits is education;

[0018] S1-2, based on the visitor's historical visit data, counting all the visited exhibits with the same interest tag; based on all the visited exhibits with the same interest tag, extracting the visitor's stay time and number of interactions when visiting the corresponding visited exhibits;

[0019] Calculate the average of the stay time corresponding to all the exhibits visited with the same interest tag, and use it as the average stay time of the visitor when visiting the exhibits with the corresponding interest tag; calculate the average of the number of interactions corresponding to all the exhibits visited with the same interest tag, and use it as the average number of interactions of the visitor when visiting the exhibits with the corresponding interest tag;

[0020] Calculate the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags, and calculate the ratio of the average stay time of the visitor when visiting exhibits with a certain interest tag to the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags, as the first interest value of the visitor for the interest tag;

[0021] Calculate the cumulative value of the average number of interactions of the visitor when visiting exhibits with different interest tags, and calculate the ratio of the average number of interactions of the visitor when visiting exhibits with a certain interest tag to the cumulative value of the average number of interactions of the visitor when visiting exhibits with different interest tags, as the second interest value of the visitor for the interest tag;

[0022] The visitor's comprehensive interest value for the interest tag is calculated using the formula: A=α×A1+(1-α)×A2; wherein A represents the visitor's comprehensive interest value for the interest tag, A1 represents the visitor's first interest value for the interest tag, A2 represents the visitor's second interest value for the interest tag, and α represents an adjustment parameter;

[0023] Based on historical data, the comprehensive interest value of visitors for each interest tag is calculated, and personalized interest tags are generated for each visitor, so that subsequent exhibit screening and route planning are more in line with the interests of visitors and enhance the visiting experience.

[0024] According to the above technical solution, step S2 includes the following:

[0025] S2-1, acquiring exhibit data in the venue to be visited from a database, wherein the exhibit data includes exhibit type and exhibit location;

[0026] S2-2, matching the exhibit types corresponding to the exhibits in the venue to be visited with the interest tags corresponding to the exhibit types, and matching each interest tag with a number of exhibits;

[0027] When a visitor makes an appointment to visit, the comprehensive interest value of the visitor for different interest tags is extracted, and the interest tags are arranged in descending order according to the size of the comprehensive interest value;

[0028] The result of multiplying the number of exhibits matched by a certain interest tag by the average stay time of the visitor when visiting the exhibits with the corresponding interest tag is used as the estimated visit time of the visitor at the exhibits matched by the corresponding interest tag;

[0029] According to the arrangement order of the interest tags, the estimated visiting time of the visitor at the exhibits matched by the corresponding interest tags is calculated in sequence;

[0030] The total duration of the visitor's scheduled visit is obtained, and a first threshold is set; according to the arrangement order of the interest tags, the cumulative value of the estimated visit duration of the visitor for a number of exhibits matched by different interest tags is calculated, and the interest tags and their corresponding exhibits whose cumulative value is less than or equal to the first threshold are screened out;

[0031] Extracting the exhibit positions of the selected exhibits corresponding to the same interest tag, and sorting the exhibits corresponding to the interest tag so that the distance between adjacent exhibits is the shortest after sorting;

[0032] According to the arrangement order of the filtered interest tags and the order of the exhibits corresponding to the interest tags, the exhibits are arranged in sequence, the best tour route is generated, and pushed to the visitor;

[0033] According to the visitors' interest tags, personalized tour routes are provided to optimize the visiting time and exhibit displays, so that visitors can visit the exhibits of interest more efficiently.

[0034] According to the above technical solution, step S3 includes the following:

[0035] Acquire real-time visit data of visitors through sensors and guide equipment in the venue to be visited, set a first interval, and the first interval includes a start time and an end time; count the number of visitors to a certain exhibit in the venue to be visited in the first interval, and calculate the average length of time that visitors stay at the exhibit in the first interval, and the average number of times that visitors interact with the exhibit in the first interval;

[0036] The heat index of a certain exhibit in the venue to be visited in the first interval is calculated using the formula: B=β1×B1+β2×B2+β3×A3; where B1 represents the number of visitors to the exhibit in the venue to be visited in the first interval, B2 represents the average length of time that visitors stay at the exhibit in the first interval, A3 represents the average number of times that visitors interact with the exhibit in the first interval, and β1, β2 and β3 all represent weight coefficients;

[0037] A second threshold is set. If the heat index B of a certain exhibit in the venue to be visited within the first interval is greater than or equal to the second threshold, the exhibit is classified as a high-heat exhibit; if the heat index B of a certain exhibit in the venue to be visited within the first interval is less than the second threshold, the exhibit is classified as a low-heat exhibit;

[0038] Count all low-heat exhibits and generate the first exhibit set;

[0039] Based on real-time data, the popularity index of each exhibit is calculated, and the exhibits are divided into high-popularity exhibits and low-popularity exhibits according to the popularity, making the subsequent optimization of exhibits more valuable for reference.

[0040] According to the above technical solution, step S4 includes the following:

[0041] S4-1, setting a second interval, wherein the second interval includes a start time and an end time, and the end time of the second interval is before the start time of the first interval; extracting the best tour route for all visitors in the second interval, and counting the number of times each exhibit in the venue to be visited in the best tour route appears in the second interval;

[0042] Since it takes time for visitors to visit the exhibits, the best visiting route should be selected before the start of the first interval, so as to ensure that the data have a high correlation and improve the accuracy and practicality of the system;

[0043] A third threshold is set. If the number of times a certain exhibit in the venue to be visited appears in the best visiting route within the second interval is greater than or equal to the third threshold, the exhibit is classified as a highly recommended exhibit; if the number of times a certain exhibit appears in the best visiting route within the second interval is less than the third threshold, the exhibit is classified as a low recommended exhibit;

[0044] Count all highly recommended exhibits and generate a second exhibit set;

[0045] S4-2, screening out exhibits common to the first exhibit set and the second exhibit set to generate a third exhibit set;

[0046] According to the real-time popularity and recommendation of the exhibits, special exhibits are screened out and the exhibits are optimized in a targeted manner.

[0047] According to the above technical solution, step S5 includes the following:

[0048] S5-1. For the exhibits in the third exhibit set, obtain the average length of time that visitors stay at the corresponding exhibits in the first interval; calculate the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval; if the average length of time that visitors stay at the corresponding exhibits in the first interval is less than the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to increase the display content; if the average length of time that visitors stay at the corresponding exhibits in the first interval is greater than or equal to the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to reduce the display content; the display content mainly refers to the static information display of the exhibit itself and related multimedia elements, such as the historical background introduction of the exhibit, detailed pictures, production process videos, commentary audio, etc.;

[0049] Obtain an average number of interactions of visitors with the corresponding exhibits in the first interval; calculate an average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval; if the average number of interactions of visitors with the corresponding exhibits in the first interval is less than the average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to increase the interactive content; if the average number of interactions of visitors with the corresponding exhibits in the first interval is greater than or equal to the average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to reduce the interactive content; the interactive content refers to the part where visitors can interact with the exhibit, the purpose of which is to make visitors understand the exhibit more deeply or enhance their sense of participation through participation, such as touch screen interaction, voice interaction, virtual exhibit interaction, game interaction, etc.;

[0050] S5-2. Sorting out the optimization plans for all exhibits in the third set, forming visual data, and pushing it to the management visitors of the venues to be visited.

[0051] An information visualization management system based on digital twins, the system comprising an information acquisition module, an information processing module and an execution module;

[0052] The information acquisition module is used to acquire the information required by the system; the information processing module is used to store, analyze and transmit the information of each module; and the execution module is used to execute the information of the information processing module.

[0053] According to the above technical solution, the information collection module includes a visitor unit and an exhibit unit;

[0054] The visitor unit is used to collect visitor's visiting data; the exhibit unit is used to collect exhibit data of exhibits.

[0055] According to the above technical solution, the information processing module includes an information storage unit, an information analysis unit and an information transmission unit;

[0056] The information storage unit is used to store the information acquired by the information acquisition module; the information analysis unit is used to analyze the information acquired by the information acquisition module; and the information transmission unit is used for information transmission of each module in the system.

[0057] According to the above technical solution, the execution module includes a visualization unit and a push unit;

[0058] The visualization unit is used to form visualization data of the best tour route and the optimization plan; the push unit is used to push the best tour route and the optimization plan.

[0059] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0060] The present invention monitors and analyzes the historical visit data, real-time visit data and display data of museum visitors to obtain visitors' interest tags, exhibition popularity indicators and the like, realizes accurate visit route planning through analysis of visitors' historical visit data, and dynamically monitors the popularity of exhibits through real-time visit data; it can not only recommend suitable exhibits according to visitors' interest preferences, but also optimize the exhibit content in real time by analyzing the popularity of exhibits and visitors' interactions, thereby timely adjusting the exhibition display method and interactive content, and comprehensively improving the visiting experience and exhibition effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0062] Figure 1 It is a flow chart of an information visualization management method based on digital twins of the present invention;

[0063] Figure 2 It is a structural schematic diagram of an information visualization management system based on digital twins of the present invention. DETAILED DESCRIPTION

[0064] 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 technical visitors in this field without creative work are within the scope of protection of the present invention.

[0065] See also Figure 1 , the present invention provides a technical solution:

[0066] An information visualization management method based on digital twins, the method comprising the following steps:

[0067] S1. Obtain the visitor's historical visit data and define interest tags; calculate the visitor's comprehensive interest value for the interest tags based on the visitor's historical visit data;

[0068] According to the above technical solution, step S1 includes the following:

[0069] S1-1, each time a visitor visits a venue recorded by the system, the visitor's visit data is obtained through sensors and guide equipment in the corresponding venue, all the visit data of the visitor are counted, and the visitor's historical visit data is generated;

[0070] The visit data includes exhibits visited, exhibit types, stay time and number of interactions; the exhibit types include history, art, technology, culture, nature, industry, commerce and education; the number of interactions includes the number of touch screen usage, voice usage, virtual exhibit viewing, game participation, etc.;

[0071] For example, the number of interactions when a visitor uses a touch screen will be increased by one, the number of interactions when a visitor uses voice will be increased by one, the number of interactions when a visitor uses a virtual device to view a virtual exhibit will be increased by one, the number of interactions when a visitor participates in a game will be increased by one, etc.;

[0072] Define interest tags according to the exhibit type, where the interest tag corresponding to historical exhibits is history, the interest tag corresponding to art exhibits is art, the interest tag corresponding to science and technology exhibits is science and technology, the interest tag corresponding to cultural exhibits is culture, the interest tag corresponding to natural exhibits is nature, the interest tag corresponding to industrial exhibits is industry, the interest tag corresponding to commercial exhibits is business, and the interest tag corresponding to educational exhibits is education;

[0073] S1-2, based on the visitor's historical visit data, counting all the visited exhibits with the same interest tag; based on all the visited exhibits with the same interest tag, extracting the visitor's stay time and number of interactions when visiting the corresponding visited exhibits;

[0074] Calculate the average of the stay time corresponding to all the exhibits visited with the same interest tag, and use it as the average stay time of the visitor when visiting the exhibits with the corresponding interest tag; calculate the average of the number of interactions corresponding to all the exhibits visited with the same interest tag, and use it as the average number of interactions of the visitor when visiting the exhibits with the corresponding interest tag;

[0075] For example:

[0076] There are 3 exhibits with the same interest tags, and the stay times for the 3 exhibits are 50, 55, and 60 respectively; the number of interactions for the 3 exhibits are 5, 6, and 7 respectively; the average stay time for all exhibits with the same interest tags is (50+55+60) / 3=55; the average number of interactions for all exhibits with the same interest tags is (5+6+7) / 3=6.

[0077] Calculate the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags, and calculate the ratio of the average stay time of the visitor when visiting exhibits with a certain interest tag to the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags, as the first interest value of the visitor for the interest tag;

[0078] For example:

[0079] The average stay time of a visitor when visiting exhibits with three different interest tags is 55, 60, and 65 respectively; the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags is calculated to be 55+60+65=180; and the average stay time of the visitor when visiting an exhibit with a certain interest tag is calculated to be 60, and the ratio of the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags is 60 / 180≈0.33;

[0080] Calculate the cumulative value of the average number of interactions of the visitor when visiting exhibits with different interest tags, and calculate the ratio of the average number of interactions of the visitor when visiting exhibits with a certain interest tag to the cumulative value of the average number of interactions of the visitor when visiting exhibits with different interest tags, as the second interest value of the visitor for the interest tag;

[0081] The visitor's comprehensive interest value for the interest tag is calculated using the formula: A=α×A1+(1-α)×A2; wherein A represents the visitor's comprehensive interest value for the interest tag, A1 represents the visitor's first interest value for the interest tag, A2 represents the visitor's second interest value for the interest tag, and α represents an adjustment parameter;

[0082] Based on historical data, the comprehensive interest value of visitors for each interest tag is calculated, and personalized interest tags are generated for each visitor, so that subsequent exhibit screening and route planning are more in line with the interests of visitors and enhance the visiting experience.

[0083] S2. Obtain the data of exhibits in the venues to be visited, and screen the exhibits in the venues to be visited based on the comprehensive interest values ​​of the visitors to the interest tags; plan the tour routes based on the screened exhibits, obtain the best tour routes and push them to the visitors;

[0084] According to the above technical solution, step S2 includes the following:

[0085] S2-1, acquiring exhibit data in the venue to be visited from a database, wherein the exhibit data includes exhibit type and exhibit location;

[0086] S2-2, matching the exhibit types corresponding to the exhibits in the venue to be visited with the interest tags corresponding to the exhibit types, and matching each interest tag with a number of exhibits;

[0087] When a visitor makes an appointment to visit, the comprehensive interest value of the visitor for different interest tags is extracted, and the interest tags are arranged in descending order according to the size of the comprehensive interest value;

[0088] The result of multiplying the number of exhibits matched by a certain interest tag by the average stay time of the visitor when visiting the exhibits with the corresponding interest tag is used as the estimated visit time of the visitor at the exhibits matched by the corresponding interest tag;

[0089] According to the arrangement order of the interest tags, the estimated visiting time of the visitor at the exhibits matched by the corresponding interest tags is calculated in sequence;

[0090] The total duration of the visitor's scheduled visit is obtained, and a first threshold is set; according to the arrangement order of the interest tags, the cumulative value of the estimated visit duration of the visitor for a number of exhibits matched by different interest tags is calculated, and the interest tags and their corresponding exhibits whose cumulative value is less than or equal to the first threshold are screened out;

[0091] Extracting a number of exhibits corresponding to the same selected interest tag, and sorting the exhibits corresponding to the interest tag so that the distance between adjacent exhibits is the shortest after sorting;

[0092] For example, through the location of exhibits, an exhibit location graph is constructed, and the exhibits are regarded as nodes in the graph. The edge weights between nodes represent the distances between exhibits. The shortest path algorithm, such as the A* algorithm, is used to sort these exhibits so that the distances between adjacent exhibits are the shortest, thereby forming an optimized exhibit arrangement order.

[0093] According to the arrangement order of the filtered interest tags and the order of the exhibits corresponding to the interest tags, the exhibits are arranged in sequence, the best tour route is generated, and pushed to the visitor;

[0094] For example, according to the order of interest tags and the order of exhibits, the entrance of the venue to be visited is used as the starting position, and the exit of the venue to be visited is used as the ending position, and each position is connected in sequence to generate the best tour route;

[0095] According to the visitors' interest tags, personalized tour routes are provided to optimize the visiting time and exhibit displays, so that visitors can visit the exhibits of interest more efficiently.

[0096] S3, obtaining real-time visit data of visitors, collecting statistics on the real-time visit data of visitors, calculating the popularity index of exhibits in the venues to be visited, classifying the exhibits in the venues to be visited, and obtaining a first exhibit set;

[0097] According to the above technical solution, step S3 includes the following:

[0098] Acquire real-time visit data of visitors through sensors and guide equipment in the venue to be visited, set a first interval, and the first interval includes a start time and an end time; count the number of visitors to a certain exhibit in the venue to be visited in the first interval, and calculate the average length of time that visitors stay at the exhibit in the first interval, and the average number of times that visitors interact with the exhibit in the first interval;

[0099] The heat index of a certain exhibit in the venue to be visited in the first interval is calculated using the formula: B=β1×B1+β2×B2+β3×A3; where B1 represents the number of visitors to the exhibit in the venue to be visited in the first interval, B2 represents the average length of time that visitors stay at the exhibit in the first interval, A3 represents the average number of times that visitors interact with the exhibit in the first interval, and β1, β2 and β3 all represent weight coefficients;

[0100] A second threshold is set. If the heat index B of a certain exhibit in the venue to be visited within the first interval is greater than or equal to the second threshold, the exhibit is classified as a high-heat exhibit; if the heat index B of a certain exhibit in the venue to be visited within the first interval is less than the second threshold, the exhibit is classified as a low-heat exhibit;

[0101] Count all low-heat exhibits and generate the first exhibit set;

[0102] Based on real-time data, the popularity index of each exhibit is calculated, and the exhibits are divided into high-popularity exhibits and low-popularity exhibits according to the popularity, making the subsequent optimization of exhibits more valuable for reference.

[0103] S4. According to the best tour route, the number of times the exhibits appear in the best tour route is counted, and the exhibits in the venue to be visited are classified to obtain a second exhibit set; the first exhibit set and the second exhibit set are screened to obtain a third exhibit set;

[0104] According to the above technical solution, step S4 includes the following:

[0105] S4-1, setting a second interval, wherein the second interval includes a start time and an end time, and the end time of the second interval is before the start time of the first interval; extracting the best tour route for all visitors in the second interval, and counting the number of times each exhibit in the venue to be visited in the best tour route appears in the second interval;

[0106] Since it takes time for visitors to visit the exhibits, the best visiting route should be selected before the start of the first interval, so as to ensure that the data have a high correlation and improve the accuracy and practicality of the system;

[0107] For example: the first interval includes a start time of 10:00:00 and an end time of 12:00:00, then the end time of the second interval is set to 09:59:59 before the start time of the first interval, 10:00:00;

[0108] A third threshold is set. If the number of times a certain exhibit in the venue to be visited appears in the best visiting route within the second interval is greater than or equal to the third threshold, the exhibit is classified as a highly recommended exhibit; if the number of times a certain exhibit appears in the best visiting route within the second interval is less than the third threshold, the exhibit is classified as a low recommended exhibit;

[0109] Count all highly recommended exhibits and generate a second exhibit set;

[0110] S4-2, screening out exhibits common to the first exhibit set and the second exhibit set to generate a third exhibit set;

[0111] According to the real-time popularity and recommendation of the exhibits, special exhibits are screened out and the exhibits are optimized in a targeted manner.

[0112] S5. Generate an optimization plan for the exhibits according to the third exhibit set; and push the optimization plan for the exhibits to the management visitor of the venue to be visited;

[0113] According to the above technical solution, step S5 includes the following:

[0114] S5-1. For the exhibits in the third exhibit set, obtain the average length of time that visitors stay at the corresponding exhibits in the first interval; calculate the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval; if the average length of time that visitors stay at the corresponding exhibits in the first interval is less than the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to increase the display content; if the average length of time that visitors stay at the corresponding exhibits in the first interval is greater than or equal to the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to reduce the display content; the display content mainly refers to the static information display of the exhibit itself and related multimedia elements, such as the historical background introduction of the exhibit, detailed pictures, production process videos, commentary audio, etc.;

[0115] Obtain an average number of interactions of visitors with the corresponding exhibits in the first interval; calculate an average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval; if the average number of interactions of visitors with the corresponding exhibits in the first interval is less than the average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to increase the interactive content; if the average number of interactions of visitors with the corresponding exhibits in the first interval is greater than or equal to the average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to reduce the interactive content; the interactive content refers to the part where visitors can interact with the exhibit, the purpose of which is to make visitors understand the exhibit more deeply or enhance their sense of participation through participation, such as touch screen interaction, voice interaction, virtual exhibit interaction, game interaction, etc.;

[0116] S5-2. Sorting out the optimization plans for all exhibits in the third set, forming visual data, and pushing it to the management visitors of the venues to be visited.

[0117] See also Figure 2 , an information visualization management system based on digital twins, the system includes an information acquisition module, an information processing module and an execution module;

[0118] The information acquisition module is used to acquire the information required by the system; the information processing module is used to store, analyze and transmit the information of each module; and the execution module is used to execute the information of the information processing module.

[0119] According to the above technical solution, the information collection module includes a visitor unit and an exhibit unit;

[0120] The visitor unit is used to collect visitor's visiting data; the exhibit unit is used to collect exhibit data of exhibits.

[0121] According to the above technical solution, the information processing module includes an information storage unit, an information analysis unit and an information transmission unit;

[0122] The information storage unit is used to store the information acquired by the information acquisition module; the information analysis unit is used to analyze the information acquired by the information acquisition module; and the information transmission unit is used for information transmission of each module in the system.

[0123] According to the above technical solution, the execution module includes a visualization unit and a push unit;

[0124] The visualization unit is used to form visualization data of the best tour route and the optimization plan; the push unit is used to push the best tour route and the optimization plan.

[0125] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0126] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, a technical visitor in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An information visualization management method based on digital twins, characterized by: The method comprises the following steps: S1. Obtain the visitor's historical visit data and define interest tags; calculate the visitor's comprehensive interest value for the interest tags based on the visitor's historical visit data; S2. Obtain the data of exhibits in the venues to be visited, and screen the exhibits in the venues to be visited based on the comprehensive interest values ​​of the visitors to the interest tags; plan the tour route based on the screened exhibits, obtain the best tour route and push it to the visitors; S3, obtaining real-time visit data of visitors, collecting statistics on the real-time visit data of visitors, calculating the popularity index of exhibits in the venues to be visited, classifying the exhibits in the venues to be visited, and obtaining a first exhibit set; S4. According to the best tour route, the number of times the exhibits appear in the best tour route is counted, and the exhibits in the venue to be visited are classified to obtain a second exhibit set; the first exhibit set and the second exhibit set are screened to obtain a third exhibit set; S5. Generate an optimization plan for the exhibits according to the third exhibit set; and push the optimization plan for the exhibits to the management visitor of the venue to be visited; The step S1 comprises the following: S1-1, each time a visitor visits a venue recorded by the system, the visitor's visit data is obtained through sensors and guide equipment in the corresponding venue, all the visit data of the visitor are counted, and the visitor's historical visit data is generated; The visit data includes exhibits visited, exhibit types, stay time and number of interactions; the exhibit types include history, art, science and technology, culture, nature, industry, commerce and education; Define interest tags according to the exhibit type, where the interest tag corresponding to historical exhibits is history, the interest tag corresponding to art exhibits is art, the interest tag corresponding to science and technology exhibits is science and technology, the interest tag corresponding to cultural exhibits is culture, the interest tag corresponding to natural exhibits is nature, the interest tag corresponding to industrial exhibits is industry, the interest tag corresponding to commercial exhibits is business, and the interest tag corresponding to educational exhibits is education; S1-2, based on the visitor's historical visit data, counting all the visited exhibits with the same interest tag; based on all the visited exhibits with the same interest tag, extracting the visitor's stay time and number of interactions when visiting the corresponding visited exhibits; Calculate the average of the stay time corresponding to all the exhibits visited with the same interest tag, and use it as the average stay time of the visitor when visiting the exhibits with the corresponding interest tag; calculate the average of the number of interactions corresponding to all the exhibits visited with the same interest tag, and use it as the average number of interactions of the visitor when visiting the exhibits with the corresponding interest tag; Calculate the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags, and calculate the ratio of the average stay time of the visitor when visiting exhibits with a certain interest tag to the cumulative value of the average stay time of the visitor when visiting exhibits with different interest tags, as the first interest value of the visitor for the interest tag; Calculate the cumulative value of the average number of interactions of the visitor when visiting exhibits with different interest tags, and calculate the ratio of the average number of interactions of the visitor when visiting exhibits with a certain interest tag to the cumulative value of the average number of interactions of the visitor when visiting exhibits with different interest tags, as the second interest value of the visitor for the interest tag; The visitor's comprehensive interest value for the interest tag is calculated using the formula: A=α×A1+(1-α)×A2; wherein A represents the visitor's comprehensive interest value for the interest tag, A1 represents the visitor's first interest value for the interest tag, A2 represents the visitor's second interest value for the interest tag, and α represents an adjustment parameter.

2. According to claim 1, the information visualization management method based on digital twins is characterized by: The step S2 comprises the following: S2-1, acquiring exhibit data in the venue to be visited from a database, wherein the exhibit data includes exhibit type and exhibit location; S2-2, matching the exhibit types corresponding to the exhibits in the venue to be visited with the interest tags corresponding to the exhibit types, and matching each interest tag with a number of exhibits; When a visitor makes an appointment to visit, the comprehensive interest value of the visitor for different interest tags is extracted, and the interest tags are arranged in descending order according to the size of the comprehensive interest value; The result of multiplying the number of exhibits matched by a certain interest tag by the average stay time of the visitor when visiting the exhibits with the corresponding interest tag is used as the estimated visit time of the visitor at the exhibits matched by the corresponding interest tag; According to the arrangement order of the interest tags, the estimated visiting time of the visitor at the exhibits matched by the corresponding interest tags is calculated in sequence; The total duration of the visitor's scheduled visit is obtained, and a first threshold is set; according to the arrangement order of the interest tags, the cumulative value of the estimated visit duration of the visitor for a number of exhibits matched by different interest tags is calculated, and the interest tags and their corresponding exhibits whose cumulative value is less than or equal to the first threshold are screened out; Extracting the exhibit positions of the selected exhibits corresponding to the same interest tag, and sorting the exhibits corresponding to the interest tag so that the distance between adjacent exhibits is the shortest after sorting; According to the arrangement order of the filtered interest tags and the order of the exhibits corresponding to the interest tags, the exhibits are arranged in sequence, the best tour route is generated, and pushed to the visitor.

3. According to claim 2, the information visualization management method based on digital twins is characterized in that: The step S3 includes the following: Acquire real-time visit data of visitors through sensors and guide equipment in the venue to be visited, set a first interval, and the first interval includes a start time and an end time; count the number of visitors to a certain exhibit in the venue to be visited in the first interval, and calculate the average length of time that visitors stay at the exhibit in the first interval, and the average number of times that visitors interact with the exhibit in the first interval; The heat index of a certain exhibit in the venue to be visited in the first interval is calculated using the formula: B=β1×B1+β2×B2+β3×A3; where B1 represents the number of visitors to the exhibit in the venue to be visited in the first interval, B2 represents the average length of time that visitors stay at the exhibit in the first interval, A3 represents the average number of times that visitors interact with the exhibit in the first interval, and β1, β2 and β3 all represent weight coefficients; A second threshold is set. If the heat index B of a certain exhibit in the venue to be visited within the first interval is greater than or equal to the second threshold, the exhibit is classified as a high-heat exhibit; if the heat index B of a certain exhibit in the venue to be visited within the first interval is less than the second threshold, the exhibit is classified as a low-heat exhibit; Count all low-heat exhibits and generate the first exhibit set.

4. The information visualization management method based on digital twin according to claim 3 is characterized in that: The step S4 comprises the following: S4-1, setting a second interval, wherein the second interval includes a start time and an end time, and the end time of the second interval is before the start time of the first interval; extracting the best tour route for all visitors in the second interval, and counting the number of times each exhibit in the venue to be visited in the best tour route appears in the second interval; A third threshold is set. If the number of times a certain exhibit in the venue to be visited appears in the best visiting route within the second interval is greater than or equal to the third threshold, the exhibit is classified as a highly recommended exhibit; if the number of times a certain exhibit appears in the best visiting route within the second interval is less than the third threshold, the exhibit is classified as a low recommended exhibit; Count all highly recommended exhibits and generate a second exhibit set; S4-2. Filter out the exhibits common to the first exhibit set and the second exhibit set to generate a third exhibit set.

5. The information visualization management method based on digital twin according to claim 4 is characterized in that: The step S5 comprises the following: S5-1. For the exhibits in the third exhibit set, obtain the average length of time that visitors stay at the corresponding exhibits in the first interval; calculate the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval; if the average length of time that visitors stay at the corresponding exhibits in the first interval is less than the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to increase the display content; if the average length of time that visitors stay at the corresponding exhibits in the first interval is greater than or equal to the average length of time that visitors stay at all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to reduce the display content; Obtain an average number of interactions of visitors with the corresponding exhibits in the first interval; calculate an average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval; if the average number of interactions of visitors with the corresponding exhibits in the first interval is less than the average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to increase the interactive content; if the average number of interactions of visitors with the corresponding exhibits in the first interval is greater than or equal to the average number of interactions of visitors with all exhibits with the same interest tag as the exhibit in the first interval, then the optimization plan for the exhibit is to reduce the interactive content; S5-2. Sorting out the optimization plans for all exhibits in the third set, forming visual data, and pushing it to the management visitors of the venues to be visited.

6. An information visualization management system based on digital twins, such as using an information visualization management method based on digital twins according to any one of claims 1 to 5, characterized in that: The system includes an information collection module, an information processing module and an execution module; The information acquisition module is used to acquire the information required by the system; the information processing module is used to store, analyze and transmit the information of each module; and the execution module is used to execute the information of the information processing module.

7. The information visualization management system based on digital twin according to claim 6 is characterized in that: The information collection module includes a visitor unit and an exhibit unit; The visitor unit is used to collect visitor's visiting data; the exhibit unit is used to collect exhibit data of exhibits.

8. The information visualization management system based on digital twin according to claim 6 is characterized by: The information processing module includes an information storage unit, an information analysis unit and an information transmission unit; The information storage unit is used to store the information acquired by the information acquisition module; the information analysis unit is used to analyze the information acquired by the information acquisition module; and the information transmission unit is used for information transmission of each module in the system.

9. The information visualization management system based on digital twin according to claim 6 is characterized in that: The execution module includes a visualization unit and a pushing unit; The visualization unit is used to form visualization data of the best tour route and the optimization plan; the push unit is used to push the best tour route and the optimization plan.

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