Personalized exhibition path planning method, device and equipment based on map information

Abstract

The invention relates to a personalized exhibition path planning method, device and equipment based on map information, and relates to the technical field of path planning, and the method comprises the steps: obtaining the actual crowd type of a target visitor of a to-be-planned visiting path; determining at least one target exhibit interested by the target visitor based on the actual crowd type, the at least one target tasting duration range of the historical visitor for each exhibit and the corresponding at least one target crowd type; determining at least one target visiting path corresponding to the target visitor based on the current target position of the target visitor and the exhibit position of each target exhibit, and determining an optimal visiting path from each target visiting path; and determining voice introduction information of the target exhibit in the optimal visiting path, and sending the optimal visiting path and each piece of voice introduction information to a terminal of the target visitor. The method has the effect of improving the visiting experience of visitors for exhibition.

Description

Technical Field

[0001] The present application relates to the technical field of route planning, and in particular to a method, device and equipment for personalized exhibition route planning based on map information. Background Art

[0002] With the rapid development of the cultural and entertainment industry and the people's demand for high-quality cultural life, the number of cultural exhibitions has increased significantly, the pace of new exhibition facilities in various places has accelerated, the number of exhibition halls and the indoor rentable area have increased, and the exhibition content has become richer and more diverse, covering art, history, science and technology, cultural heritage and other fields. At the same time, the exhibition format is constantly innovating, such as the application of digitalization, intelligence and other technical means, making the exhibition more vivid and interesting, the audience experience stronger, and the number of visitors participating in cultural exhibitions has also increased significantly, so it is particularly important to guide visitors in the exhibition in the exhibition hall.

[0003] At present, the way to navigate visitors in exhibition halls is usually to use a pre-set universal fixed tour path to guide visitors to visit, and visitors observe exhibits in the exhibition hall according to this fixed tour path. Because different visitors have different exhibition viewing needs when visiting exhibitions in exhibition halls, the universal tour path in this way makes it impossible for visitors to better observe the exhibits they want to see, and cannot better meet the exhibition viewing needs of different visitors, resulting in poor exhibition viewing experience for visitors. Summary of the invention

[0004] In order to improve visitors' experience of visiting an exhibition, the present application provides a method, device, storage medium and electronic device for personalized exhibition route planning based on map information.

[0005] In a first aspect of the present application, a personalized exhibition route planning method based on map information is provided, which specifically includes: Obtain the actual population type of the target visitors of the planned tour route; Determine at least one target exhibit that the target visitor is interested in based on the actual crowd type, at least one target tasting time range for each exhibit by historical visitors, and at least one corresponding target crowd type, wherein the target tasting time range is a time range that the tasting time of historical visitors for a single exhibit is likely to be within, and the target crowd type is a crowd type of historical visitors whose tasting time is likely to be within the corresponding target tasting time range; Based on the target location currently located by the target visitor and the exhibit locations of each of the target exhibits, determining at least one target visiting path corresponding to the target visitor, and determining the best visiting path from among the target visiting paths; Determine the voice introduction information of the target exhibits in the optimal visiting route, and send the optimal visiting route and each voice introduction information to the terminal of the target visitor.

[0006] By adopting the above technical solution, after obtaining the actual population type of the target visitor, based on the target tasting time range of historical visitors for each exhibit and the corresponding target population type, the target visitor of the actual population type is analyzed, and the possible tasting time range for each exhibit in the exhibition venue is analyzed, so as to more accurately determine whether the target visitor is interested in it based on the length of the tasting time for each exhibit, and then determine at least one target exhibit of interest. Then, according to each target exhibit, the target tour path for the target visitor to visit is determined, and the optimal tour path is determined therefrom, so that the tour path can better fit the needs of the target visitor, and finally the optimal tour path and each voice introduction information are sent to the terminal of the target visitor, thereby improving the visitor's experience of visiting the exhibition.

[0007] Optionally, determining at least one target exhibit that the target visitor is interested in based on the actual crowd type, at least one target tasting time range of each exhibit by historical visitors, and at least one corresponding target crowd type specifically includes: Obtaining the historical tasting time ranges of each historical visitor for a single exhibit, counting the first occurrence times of each of the historical tasting time ranges, and selecting a first number of historical tasting time ranges from each of the historical tasting time ranges in descending order of the first occurrence times as target tasting time ranges; Obtaining historical population types of historical visitors whose tasting duration is within the single target tasting duration range, counting the second number of occurrences of each of the historical population types, and selecting a second number of historical population types from each of the historical population types in descending order of the second number of occurrences as target population types, wherein the target population types are historical population types corresponding to the single target tasting duration range; Determine a first weight for each of the target tasting time ranges, and determine a second weight for each of the target population types corresponding to each of the target tasting time ranges, wherein the first weight is a ratio of a first occurrence number of each target tasting time range to a sum of first occurrence numbers of all target tasting time ranges, and the second weight is a ratio of a second occurrence number of a single target population type corresponding to the target tasting time range to a sum of second occurrence numbers of all corresponding target population types; At least one target exhibit that the target visitor is interested in is determined from among the exhibits according to the actual crowd type, the first weight of a single exhibit and the corresponding second weights.

[0008] By adopting the above technical solution, the larger the first occurrence number, the more likely the visitor's tasting time for the corresponding exhibit is within the corresponding historical tasting time range, thereby determining the target tasting time range; the larger the second occurrence number, the more likely the visitor's tasting time for the corresponding historical population type is within the target tasting time range, thereby determining the target population type. Finally, combining the first weight and the corresponding second weight, the possible tasting time range for each exhibit by the target visitor is analyzed and determined, thereby accurately determining whether the target visitor is interested in the exhibit.

[0009] Optionally, determining at least one target exhibit that the target visitor is interested in from the exhibits according to the actual crowd type, the first weight of a single exhibit and the corresponding second weights specifically includes: For a single exhibit, if the actual population type exists in each of the target population types corresponding to the target tasting time range, the corresponding target tasting time range is determined as the key time range; Determine the key time range before the preset tasting time threshold as the first time range, and determine the key time range after the tasting time threshold as the second time range, wherein each tasting time in the first time range is less than the tasting time threshold, and each tasting time in the second time range is not less than the tasting time threshold; Calculate a first product of a first weight of each of the first time ranges and a second weight of a corresponding actual crowd type, and sum each of the first products to obtain a sum of the first products; Calculate the second product of the first weight of each of the second time ranges and the second weight of the corresponding actual crowd type, sum the second products to obtain the sum of the second products, and if the sum of the second products is greater than the sum of the first products, determine the corresponding exhibit as the target exhibit of interest to the target visitor.

[0010] By adopting the above technical solution, the larger the sum of the first products is, the more likely it is that the target visitor will have a short tasting time when tasting the single exhibit, which further indicates that the target visitor is less likely to be interested in the single exhibit; the larger the sum of the second products is, the more likely it is that the target visitor will have a long tasting time when tasting the single exhibit, which further indicates that the target visitor is more likely to be interested in the single exhibit; if the sum of the second products is greater than the sum of the first products, it means that the target visitor is more likely to be interested in the single exhibit than not to be interested in it, and the corresponding exhibit is determined as the target exhibit of interest to the target visitor, thereby facilitating the subsequent accurate recommendation of personalized visiting routes for the target visitor.

[0011] Optionally, the determining at least one target visiting path corresponding to the target visitor based on the target location currently located by the target visitor and the exhibit location of each target exhibit specifically includes: Determine the visiting order of the corresponding target exhibits according to the sum of the second products corresponding to each of the target exhibits, wherein the larger the sum of the second products is, the higher the corresponding visiting order is; At least one target visiting path corresponding to the target visitor is determined according to the target location currently located by the target visitor, the exhibit location of each of the target exhibits and the corresponding visiting sequence.

[0012] By adopting the above technical solution, the larger the sum of the second products is, the more likely the target visitors are to be interested in the corresponding target exhibits, the earlier the corresponding visiting order is, and the more preferentially the target visitors are guided to visit the corresponding target exhibits, thereby improving the visiting experience of the target visitors.

[0013] Optionally, the determining the best visiting route from the target visiting routes specifically includes: Obtaining the first occurrence frequency of a crowd density lower than a preset density threshold in historical exhibitions of a single exhibit; Obtaining a historical period in which a single exhibit has a crowd density lower than the density threshold, counting the second occurrence frequency of each historical period, and selecting a third number of historical periods from each of the historical periods in descending order of the second occurrence frequency to determine as target periods, wherein the target period is a historical period corresponding to the single exhibit; Determine a third weight for each of the exhibits, and determine a fourth weight for each of the target time periods corresponding to each of the exhibits, wherein the third weight is a ratio of a first occurrence frequency of each exhibit to a sum of first occurrence frequencies of all exhibits, and the fourth weight is a ratio of a second occurrence frequency of a single target time period corresponding to the exhibit to a sum of second occurrence frequencies of all corresponding target time periods; According to the third weight and the corresponding fourth weights, an optimal visiting route is determined from the target visiting routes.

[0014] By adopting the above technical solution, the greater the first occurrence frequency, the less likely the viewing area of ​​the corresponding exhibit will be crowded when the exhibit is on display; the greater the second occurrence frequency, the less likely the exhibit will be crowded in the corresponding historical period, and then the target period is determined. Finally, the third weight and the corresponding fourth weight are combined to analyze the possibility of subsequent target visitors encountering crowded traffic when visiting along the target visiting route, and then the best visiting route is screened out to avoid crowding to a certain extent.

[0015] Optionally, determining the best visiting path from the target visiting paths according to the third weight and the corresponding fourth weights specifically includes: In a single target visiting path, determining the estimated walking time of the target visitor from the last position to each target exhibit; when the last position is not the exhibit position of the last target exhibit, determining the estimated arrival time of the target visitor to the corresponding target exhibit based on the arrival time of the target visitor to the last position and the estimated walking time; When the previous position is the exhibit position of the previous target exhibit, selecting the maximum second product from the second products corresponding to the previous target exhibit, and determining the second duration range corresponding to the maximum second product as the reference duration range; Determine the estimated arrival time of the target visitor at the corresponding target exhibit based on the arrival time of the last location, the estimated walking time and the reference time range; If each target time period corresponding to the target exhibit contains a corresponding estimated arrival time, the corresponding target exhibit is determined as an important exhibit, the target time period containing the estimated arrival time is determined as an important time period, and the third product of the third weight of each important exhibit and the fourth weight of the corresponding important time period is calculated and summed to obtain the sum of the third products of the corresponding target visiting paths; A maximum sum of the third products is selected from the sums of the third products, and a target tour path corresponding to the maximum sum of the third products is determined as an optimal tour path.

[0016] By adopting the above technical solution, the second duration range corresponding to the maximum second product is determined as the reference duration range, that is, the duration range in which the target visitor is more likely to spend time tasting at the previous target exhibit. Further, the arrival time at the previous location, the expected walking time, and the reference duration range are comprehensively considered to ultimately determine the expected arrival time of the target visitor at the corresponding target exhibit. Furthermore, the larger the sum of the third products, the smaller the overall possibility of the target visitor encountering congestion when visiting along the corresponding target tour path. The target tour path corresponding to the maximum sum of the third products is determined as the optimal tour path, and subsequent target visitors visit along this optimal tour path, which can not only better meet the needs of the target visitors, but also avoid the congestion of each target exhibit as much as possible, greatly improving the visiting experience.

[0017] Optionally, the method further includes: Counting the actual tasting time of the target exhibits visited by the target visitor under the optimal visiting route, if the actual tasting time is within the target tasting time range of the corresponding target exhibit, determining the corresponding target tasting time range as the key time range; Calculate the fourth product of the first weight of each of the important time ranges and the second weight of each corresponding target population type, select the maximum fourth product from the fourth products, and determine the target population type corresponding to the maximum fourth product as the final population type; If the number of identical final crowd types exceeds a preset number threshold, when the identical final crowd type is not the actual crowd type, the actual crowd type is replaced with the identical final crowd type, and a visiting route adapted to the target visitor is re-determined.

[0018] By adopting the above technical solution, the larger the fourth product is, the easier it is for visitors of the corresponding target population type to be within the important time range when visiting the corresponding target exhibits. Furthermore, if the number of identical people in each final population type exceeds the preset number threshold, and the identical final population type is not the actual population type, it means that the actual tasting time of the target visitor for more target exhibits does not match the actual population type, and it may be that the actual population type is incorrectly determined. In this case, the identical final population type is replaced with the actual population type, so that the population type corresponding to the target visitor is more accurate.

[0019] In a second aspect of the present application, a personalized exhibition route planning device based on map information is provided, which specifically includes: An information acquisition module is used to obtain the actual population type of the target visitors of the planned tour route; An exhibit screening module, for determining at least one target exhibit that the target visitor is interested in based on the actual crowd type, at least one target tasting time range of each exhibit by historical visitors, and at least one corresponding target crowd type, wherein the target tasting time range is a time range that the tasting time of historical visitors for a single exhibit is likely to fall within, and the target crowd type is a crowd type of historical visitors whose tasting time is likely to fall within the corresponding target tasting time range; A path planning module, used to determine at least one target visiting path corresponding to the target visitor based on the target location currently located by the target visitor and the exhibit location of each target exhibit, and determine the best visiting path from each target visiting path; The path sending module is used to determine the voice introduction information of the target exhibits in the optimal visiting path, and send the optimal visiting path and each voice introduction information to the terminal of the target visitor.

[0020] By adopting the above technical solution, the information acquisition module obtains the actual population type of the target visitors, the exhibit screening module determines at least one target exhibit that the target visitors are interested in from all the exhibits, and then the path planning module determines at least one target visiting path corresponding to the target visitors according to the exhibit positions of each target exhibit, and determines the best visiting path therefrom, and finally the path sending module determines the voice introduction information of the target exhibits in the best visiting path, and sends the best visiting path and each voice introduction information to the terminal of the target visitor.

[0021] In a third aspect of the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is loaded and executed by a processor, the method steps described in any one of the first aspects are performed.

[0022] In a fourth aspect of the present application, an electronic device is provided, specifically comprising: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the processor is used to load and execute the computer program stored in the memory so that the electronic device performs the method as described in any one of the first aspects.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: based on the target tasting time range of historical visitors for each exhibit and the corresponding target population type, the target visitors of the actual population type are analyzed, and the possible tasting time range for each exhibit in the exhibition venue is determined more accurately based on the length of the tasting time for each exhibit, and then at least one target exhibit of interest is determined. Then, according to each target exhibit, the target tour path for the target visitor to visit is determined, and the optimal tour path is determined therefrom, so that the tour path can better fit the needs of the target visitor, and finally the optimal tour path and each voice introduction information are sent to the terminal of the target visitor, thereby improving the visitor's experience of visiting the exhibition. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of a personalized exhibition route planning method based on map information provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a personalized exhibition route planning device based on map information provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of another personalized exhibition route planning device based on map information provided in an embodiment of the present application.

[0025] Description of reference numerals: 11. information acquisition module; 12. exhibit screening module; 13. path planning module; 14. path sending module; 15. type adjustment module. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0028] In the description of the embodiments of the present application, the term "and / or" is only a kind of association relationship describing the associated objects, indicating that there may be three kinds of relationships, for example, A and / or B, which can represent: A exists alone, B exists alone, and A and B exist at the same time. In addition, unless otherwise specified, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" can explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] See also Figure 1 The embodiment of the present application discloses a flowchart of a personalized exhibition path planning method based on map information, which can be implemented by a computer program or run on a personalized exhibition path planning device based on map information based on the von Neumann system. The computer program can be integrated into an application or run as an independent tool application, specifically including: S101: Obtain the actual population type of the target visitors of the planned tour route.

[0030] Specifically, in an embodiment of the present application, the target visitor is an exhibitor who has just arrived at the exhibition site and needs to provide a personalized tour route. In other embodiments, the target visitor may also be an exhibitor who has entered the exhibition site and is visiting. The exhibition site may be a museum or art gallery, or a cultural and entertainment venue such as a large exhibition venue. The actual crowd type can be understood as a description of a user group such as a target visitor determined based on the basic information of the target visitor, and the basic information includes but is not limited to information such as gender, hobbies, and occupation. In addition, the execution subject of a personalized exhibition route planning method based on map information disclosed in an embodiment of the present application is a server, and the server is wirelessly connected to the terminal of the target visitor, and the terminal may be a smart phone or a tablet computer. The terminal is installed with a client or applet of the exhibition navigation corresponding to the exhibition site currently visited by the target visitor, and the server may be a background server of the client or applet, and may specifically be an independent physical server, or a server cluster composed of multiple physical servers. It should be noted that the target visitor can share daily dynamic information in the client.

[0031] Furthermore, the implementation scenario of the personalized exhibition route planning method based on map information is: when the target visitor has a need for a recommended visiting route, by clicking the "route recommendation" button in the client, the server responds and obtains the actual population type of the target visitor. Finally, based on the actual population type, a personalized visiting route is recommended for the target visitor and sent to the terminal of the target visitor, so that the target visitor can obtain a better visiting experience when visiting the exhibition venue. Among them, a feasible way to obtain the actual population type is: on the premise of obtaining the authorization and consent of the target visitor, the registration information of the target visitor on the client is obtained, and the registration information includes but is not limited to age, nickname, gender, and occupation, and then according to the daily dynamic information shared by the target visitor in the client, the interests and hobbies of the target visitor are analyzed and determined, and then their basic information is determined. Finally, this basic information is input into the preset population type prediction model to determine the actual population type of the target visitor. The population type prediction model can use a trained random forest model or a deep neural network model. The training process is briefly described as follows: the basic information of historical users marked with the correct population type is used as a training sample, the model is trained, and the model parameters are optimized by the reverse gradient algorithm.

[0032] S102: Determine at least one target exhibit that the target visitor is interested in based on the actual crowd type, at least one target tasting time range of each exhibit by historical visitors, and at least one corresponding target crowd type.

[0033] Specifically, the target tasting time range is the time range that the historical visitors are likely to be in for the tasting time of a single exhibit, and the target population type is the population type of historical visitors whose tasting time is likely to be in the corresponding target tasting time range. In an embodiment of the present application, the historical visitor exhibition analysis record is retrieved from the database, and the historical visitor exhibition analysis record includes the tasting time of different historical visitors for a single exhibit and the population type of historical visitors. Based on this historical visitor exhibition analysis record, the historical tasting time range of each historical visitor for a single exhibit is obtained, and the single exhibit is an exhibit displayed in the exhibition venue. The first number of occurrences of each historical tasting time range is counted. The larger the first number of occurrences, the easier it is for the visitor to be in the corresponding historical tasting time range for the corresponding exhibit. The tasting time refers to the time for viewing and appreciating the exhibit. Then, in order from the largest to the smallest number of first occurrences, the first number of historical tasting time ranges is selected from each historical tasting time range to be determined as the target tasting time range. Furthermore, for a single exhibit, historical population types of historical visitors whose tasting time is within a single target tasting time range are obtained, and the second occurrence number of each historical population type is counted. The larger the second occurrence number, the more likely the tasting time of visitors of the corresponding historical population type is within the target tasting time range. In descending order of the second occurrence number, a second number of historical population types are selected from each historical population type to be determined as the target population type corresponding to the target tasting time range.

[0034] Further, the first weight of each target tasting time range is determined, and the first weight is the ratio of the first occurrence number of each target tasting time range to the sum of the first occurrence numbers of all target tasting time ranges. Then, the second weight of each target population type corresponding to each target tasting time range is determined, and the second weight is the ratio of the second occurrence number of a single target population type corresponding to the target tasting time range to the sum of the second occurrence number of all corresponding target population types. Then, in combination with the actual population type of the target visitor, at least one target exhibit that the target visitor is interested in is determined from each exhibit. A feasible determination method is: for a single exhibit, if there is an actual population type in each target population type corresponding to its target tasting time range, then the corresponding target tasting time range is determined as the key time range. Then, the key time range before the preset tasting time threshold is determined as the first time range. The key time range after the tasting time threshold is determined as the second time range. Among them, each tasting time in the first time range is less than the tasting time threshold, and each tasting time in the second time range is not less than the tasting time threshold. The tasting time threshold is the critical value of the tasting time for measuring whether the visitor is interested in the exhibits.

[0035] Calculate the first product of the first weight of each first duration range and the second weight of the corresponding actual crowd type. The larger the first product, the easier it is for the tasting time of the actual crowd type to be within the corresponding first duration range when tasting the single exhibit. Then sum each first product to obtain the corresponding sum of the first products. The larger the sum of the first products, the greater the possibility that the tasting time is short when the target visitor tastes the single exhibit, which further indicates that the target visitor is less likely to be interested in the single exhibit. Further, calculate the second product of the first weight of each second duration range and the second weight of the corresponding actual crowd type, sum each second product to obtain the sum of the second products. The larger the sum of the second products, the greater the possibility that the tasting time is long when the target visitor tastes the single exhibit, which further indicates that the target visitor is more likely to be interested in the single exhibit. Finally, if the sum of the second products is greater than the sum of the first products, it means that for the single exhibit, the possibility that the target visitor is interested is greater than the possibility that he is not interested, then the corresponding exhibit is determined as the target exhibit of interest to this target visitor.

[0036] S103: Based on the target location currently located by the target visitor and the exhibit locations of each target exhibit, at least one target visiting path corresponding to the target visitor is determined, and an optimal visiting path is determined from each target visiting path.

[0037] Specifically, after the target exhibits that the target visitor is interested in in the exhibition venue are determined, it is necessary to determine a personalized visiting path for the target visitor, that is, the optimal visiting path, to guide the target visitor to visit each target exhibit in turn. In an embodiment of the present application, a method for determining the optimal visiting path is to obtain the plan map information of the exhibition venue, and then determine the target location of the target visitor in the exhibition venue based on the indoor positioning technology. In other embodiments, the target location can also be obtained through the GPS module preset in the terminal with the consent of the target visitor. In addition, each exhibit in the exhibition venue is installed with a (Radio Frequency Identification, RFID) tag, and the RFID tag on the target exhibit is used to determine the exhibit location of each target exhibit using the radio frequency identification technology. Further, according to the sum of the second products corresponding to each target exhibit, the visiting order of the corresponding target exhibit is determined. The larger the sum of the second products, the greater the possibility that the target visitor is interested in the corresponding target exhibit, the higher the corresponding visiting order, and the more priority is given to guiding the target visitor to visit the corresponding target exhibit, thereby improving the visiting experience of the target visitor. Finally, the floor plan map information of the exhibition venue is imported into the navigation tool, and combined with the target location and the locations of each exhibit, at least one target visiting path corresponding to the target visitor under each visiting sequence is determined, that is, the path from the target location to the location of the first target exhibit visited, then to the location of the next target exhibit visited, and so on until the location of the last target exhibit visited. The navigation tool may be an Aowei interactive map tool.

[0038] Furthermore, a more reasonable optimal visiting path is determined from each target visiting path. A feasible determination method is: retrieve the historical crowd flow monitoring records of each exhibit, and the historical crowd flow monitoring records include but are not limited to the crowd flow density of visitors to a single exhibit in different time periods. Based on this historical crowd flow monitoring record, obtain the first occurrence frequency of the crowd flow density lower than the preset density threshold in the historical exhibition of a single exhibit. The crowd flow density lower than the density threshold indicates that the crowding degree is low. The greater the first occurrence frequency, the less likely it is that the viewing area of ​​the corresponding exhibit will be crowded when the exhibit is exhibited. Then obtain the historical time period when the crowd flow density of a single exhibit is lower than the density threshold, and count the second occurrence frequency of each historical time period. The greater the second occurrence frequency, the less likely it is that the exhibit will be crowded in the corresponding historical time period. Finally, in the order of the second occurrence frequency from large to small, select the third number of historical time periods from each historical time period to determine as the target time period corresponding to the exhibit, that is, the time period that is less likely to be crowded when visiting.

[0039] Further, the third weight of each exhibit is calculated, the third weight is the ratio of the first appearance frequency of each exhibit to the sum of the first appearance frequencies of all exhibits, and then the fourth weight of each target time period corresponding to each exhibit is calculated, the fourth weight is the ratio of the second appearance frequency of a single target time period corresponding to the exhibit to the sum of the second appearance frequencies of all corresponding target time periods. Further, in a single target visiting path, the estimated walking time of the target visitor from the previous position to the single target exhibit is determined, which can be specifically determined based on the distance from the previous position to the exhibit position of the single target exhibit divided by the walking speed of the target visitor, and the walking speed can be determined by a speed sensor. The previous position can be the position where the target visitor is before the official visit, or it can be the previous target exhibit.

[0040] When the previous position is not the exhibit position of the previous target exhibit, the arrival time of the target visitor at the previous position and the expected walking time are summed to obtain the expected arrival time of the target visitor at the corresponding target exhibit; when the previous position is the exhibit position of the previous target exhibit, since the target visitor will stay at the previous target exhibit for tasting, the maximum second product is selected from the second products corresponding to the previous target exhibit, and the second time range corresponding to the maximum second product is determined as the reference time range, that is, the time range in which the target visitor is more likely to spend tasting at the previous target exhibit. Further, the arrival time of the previous position, the expected walking time, and the reference time range (reflecting the time the target visitor stayed at the previous position) are comprehensively considered to finally determine the expected arrival time of the target visitor at the corresponding target exhibit, and the expected arrival time of the target visitor at each target exhibit in a single target visiting path can be determined by analogy.

[0041] Furthermore, for a single target visiting path, if each target time period corresponding to a target exhibit contains a corresponding estimated arrival time, then the corresponding target exhibit is determined as an important exhibit, and the target time period containing the estimated arrival time is determined as an important time period, and the third product of the third weight of each important exhibit and the fourth weight of the corresponding important time period is calculated and summed to obtain the sum of the third products of the corresponding target visiting path. The larger the sum of the third products, the smaller the overall possibility of the target visitor encountering congestion when visiting along the corresponding target visiting path. Finally, the maximum sum of the third products is selected from the sums of the third products, and the target visiting path corresponding to the maximum sum of the third products is determined as the optimal visiting path. Subsequent target visitors visit along this optimal visiting path, which can not only better meet the needs of the target visitors, but also avoid the congestion of each target exhibit as much as possible, greatly improving the visiting experience.

[0042] S104: Determine the voice introduction information of the target exhibits in the best visiting route, and send the best visiting route and each voice introduction information to the terminal of the target visitor.

[0043] Specifically, after the best visiting path for the target visitor is determined, the voice introduction information of each target exhibit is obtained from the database, wherein the database includes the voice introduction information of all exhibits in the exhibition venue, and the voice introduction information is used to introduce the detailed information of the exhibits to the visitors in the form of voice broadcast. Further, the best visiting path and each voice introduction information are sent to the terminal of the target visitor together, so as to achieve targeted visiting guidance for the target visitor, and when the target visitor visits the target exhibit, the corresponding voice introduction information can be viewed, which can not only enable the target visitor to visit the exhibits of interest, but also avoid crowding to a certain extent, and improve the visiting experience. In other embodiments, according to the sum of the second products corresponding to each target exhibit, the playing time of the voice introduction information of the corresponding target exhibit is determined, the larger the sum of the second products, the greater the possibility that the target visitor is interested, the longer the probability of long tasting time, and the longer the playing time of the corresponding voice introduction information, so as to bring the target visitor a better exhibit tasting experience.

[0044] In one embodiment, when the target visitor visits according to the best visiting route, the actual tasting time of the target exhibits visited by the target visitor is counted. A feasible statistical method is: select a video containing the target visitor from the surveillance video of the camera at the visited target exhibit, and then determine the video duration as the actual tasting time of the target visitor. If the actual tasting time is within the target tasting time range of the corresponding target exhibit, then the corresponding target tasting time range is determined as an important time range, and then the fourth product of the first weight of each important time range and the second weight of each corresponding target population type is calculated. The larger the fourth product, the easier it is for the visitor of the corresponding target population type to be within the important time range when visiting the corresponding target exhibit. Then, the maximum fourth product is selected from each fourth product, and the maximum fourth product is determined as the final crowd type. Finally, if the same number of each final crowd type exceeds the preset number threshold, and the same final crowd type is not the actual crowd type, it means that the actual tasting time of the target visitor for more target exhibits does not match the actual crowd type, and the actual crowd type may be incorrectly determined. Then, the same final crowd type is replaced with the actual crowd type, and finally, according to the same final crowd type, the tour path adapted to the target visitor is re-determined. For details, please refer to steps S102-S103, which will not be repeated here. Not only can the crowd type corresponding to the target visitor be made more accurate, but also the provided tour path can be made more adapted to the target visitor.

[0045] The implementation principle of the personalized exhibition path planning method based on map information in the embodiment of the present application is as follows: based on the target tasting time range of historical visitors for each exhibit and the corresponding target population type, the target visitors of the actual population type are analyzed, and the possible tasting time range for each exhibit in the exhibition venue is analyzed, so as to more accurately determine whether the target visitor is interested in it based on the length of the tasting time for each exhibit, and then determine at least one target exhibit of interest. Then, according to each target exhibit, the target visiting path for the target visitor to visit is determined, and the optimal visiting path is determined therefrom, so that the visiting path can better fit the needs of the target visitor, and finally the optimal visiting path and each voice introduction information are sent to the terminal of the target visitor, thereby improving the visitor's visiting experience of the exhibition.

[0046] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0047] See also Figure 2 , is a schematic diagram of the structure of a personalized exhibition path planning device based on map information provided in an embodiment of the present application. The personalized exhibition path planning device based on map information can be implemented as all or part of the device through software, hardware or a combination of both. The device includes an information acquisition module 11, an exhibit screening module 12, a path planning module 13 and a path sending module 14.

[0048] The information acquisition module 11 is used to obtain the actual population type of the target visitors of the planned tour route; The exhibit screening module 12 is used to determine at least one target exhibit that the target visitor is interested in based on the actual crowd type, at least one target tasting time range of each exhibit by the historical visitors, and at least one corresponding target crowd type, wherein the target tasting time range is a time range that the historical visitors tend to spend tasting a single exhibit, and the target crowd type is a crowd type of the historical visitors whose tasting time tends to fall within the corresponding target tasting time range; A path planning module 13 is used to determine at least one target visiting path corresponding to the target visitor based on the target location currently located by the target visitor and the exhibit location of each target exhibit, and determine the best visiting path from each target visiting path; The path sending module 14 is used to determine the voice introduction information of the target exhibits in the best visiting path, and send the best visiting path and each voice introduction information to the terminal of the target visitor.

[0049] Optionally, the exhibit screening module 12 is specifically used for: Obtain the historical tasting time ranges of each historical visitor for a single exhibit, count the first occurrence times of each historical tasting time range, and select the first number of historical tasting time ranges from each historical tasting time range in descending order of the first occurrence times to determine as the target tasting time range; Obtain historical population types of historical visitors whose tasting duration is within a single target tasting duration range, count the second occurrence times of each historical population type, and select a second number of historical population types from each historical population type in descending order of the second occurrence times to determine as the target population type, the target population type being the historical population type corresponding to the single target tasting duration range; Determine a first weight for each target tasting time range, and determine a second weight for each target population type corresponding to each target tasting time range, wherein the first weight is a ratio of a first occurrence number of each target tasting time range to a sum of first occurrence numbers of all target tasting time ranges, and the second weight is a ratio of a second occurrence number of a single target population type corresponding to the target tasting time range to a sum of second occurrence numbers of all corresponding target population types; At least one target exhibit that the target visitor is interested in is determined from among the exhibits according to the actual crowd type, the first weight of the single exhibit and the corresponding second weights.

[0050] Optionally, the exhibit screening module 12 is specifically used for: For a single exhibit, if there is an actual population type in each target population type corresponding to the target tasting time range, the corresponding target tasting time range will be determined as the key time range; The key time range before the preset tasting time threshold is determined as the first time range, and the key time range after the tasting time threshold is determined as the second time range, each tasting time in the first time range is less than the tasting time threshold, and each tasting time in the second time range is not less than the tasting time threshold; Calculate the first product of the first weight of each first time range and the second weight of the corresponding actual crowd type, and sum the first products to obtain the sum of the first products; Calculate the second product of the first weight of each second time range and the second weight of the corresponding actual crowd type, sum the second products to obtain the sum of the second products, and if the sum of the second products is greater than the sum of the first products, determine the corresponding exhibit as the target exhibit of interest to the target visitor.

[0051] Optionally, the path planning module 13 is specifically used for: According to the sum of the second products corresponding to each target exhibit, the visiting order of the corresponding target exhibit is determined. The larger the sum of the second products is, the higher the corresponding visiting order is. At least one target visiting path corresponding to the target visitor is determined according to the target location currently located by the target visitor, the exhibit locations of the target exhibits, and the corresponding visiting sequence.

[0052] Optionally, the path planning module 13 is specifically used for: Obtain the first occurrence frequency of a single exhibit in historical exhibitions where the crowd density is lower than a preset density threshold; Obtain historical time periods in which the crowd density of a single exhibit is lower than the density threshold, count the second occurrence frequency of each historical time period, and select a third number of historical time periods from each historical time period in descending order of the second occurrence frequency to determine as the target time period, the target time period being the historical time period corresponding to the single exhibit; Determine the third weight of each exhibit, and determine the fourth weight of each target time period corresponding to each exhibit, the third weight being the ratio of the first occurrence frequency of each exhibit to the sum of the first occurrence frequencies of all exhibits, and the fourth weight being the ratio of the second occurrence frequency of a single target time period corresponding to the exhibit to the sum of the second occurrence frequencies of all corresponding target time periods; According to the third weight and the corresponding fourth weights, the best visiting path is determined from the target visiting paths.

[0053] Optionally, the path planning module 13 is specifically used for: In a single target visiting path, the estimated walking time of the target visitor from the last position to each target exhibit is determined. When the last position is not the exhibit position of the last target exhibit, the estimated arrival time of the target visitor to the corresponding target exhibit is determined based on the arrival time of the target visitor to the last position and the estimated walking time. When the previous position is the exhibit position of the previous target exhibit, a maximum second product is selected from the second products corresponding to the previous target exhibit, and the second duration range corresponding to the maximum second product is determined as the reference duration range; Based on the arrival time of the last location, the estimated walking time and the reference time range, determine the estimated arrival time of the target visitor to the corresponding target exhibit; If each target time period corresponding to the target exhibit contains a corresponding estimated arrival time, the corresponding target exhibit is determined as an important exhibit, and the target time period containing the estimated arrival time is determined as an important time period, and the third product of the third weight of each important exhibit and the fourth weight of the corresponding important time period is calculated and summed to obtain the sum of the third products of the corresponding target visiting paths; The maximum sum of the third products is selected from the sums of the third products, and the target tour path corresponding to the maximum sum of the third products is determined as the optimal tour path.

[0054] Optional, such as Figure 3 As shown, the device also includes a type adjustment module 15, which is specifically used to: The actual tasting time of the target exhibits visited by the target visitors under the best visiting route is counted. If the actual tasting time is within the target tasting time range of the corresponding target exhibits, the corresponding target tasting time range is determined as the key time range; Calculate the fourth product of the first weight of each important time range and the second weight of each corresponding target population type, select the maximum fourth product from each fourth product, and determine the target population type corresponding to the maximum fourth product as the final population type; If the number of identical final crowd types exceeds a preset number threshold, when the identical final crowd type is not the actual crowd type, the actual crowd type is replaced with the identical final crowd type, and a visiting route adapted to the target visitor is re-determined.

[0055] It should be noted that the personalized exhibition path planning device based on map information provided in the above embodiment only uses the division of the above functional modules as an example when executing the personalized exhibition path planning method based on map information. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the personalized exhibition path planning device based on map information provided in the above embodiment and the personalized exhibition path planning method based on map information belong to the same concept. The implementation process is detailed in the method embodiment and will not be repeated here.

[0056] The embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, a personalized exhibition route planning method based on map information of the above embodiment is adopted.

[0057] Among them, the computer program can be stored in a computer-readable medium, the computer program includes computer program code, the computer program code can be in the form of source code, object code, executable file or certain middleware, etc. The computer-readable medium includes any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the computer-readable medium includes but is not limited to the above-mentioned components.

[0058] Among them, through this computer-readable storage medium, a personalized exhibition path planning method based on map information in the above embodiment is stored in a computer-readable storage medium, and is loaded and executed on a processor to facilitate the storage and application of the above method.

[0059] The embodiment of the present application further discloses an electronic device, wherein a computer program is stored in a computer-readable storage medium, and when the computer program is loaded and executed by a processor, the above-mentioned personalized exhibition route planning method based on map information is adopted.

[0060] The electronic device may be a desktop computer, a laptop computer, a cloud server or other electronic device, and the electronic device includes but is not limited to a processor and a memory. For example, the electronic device may also include input and output devices, a network access device, and a bus.

[0061] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0062] Among them, the memory can be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device, or it can be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD) or a flash memory card (FC) equipped on the electronic device. Moreover, the memory can also be a combination of an internal storage unit and an external storage device of the electronic device. The memory is used to store computer programs and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or is to be output, and this application does not impose any restrictions on this.

[0063] Among them, through this electronic device, a personalized exhibition route planning method based on map information of the above embodiment is stored in the memory of the electronic device, and is loaded and executed on the processor of the electronic device for easy use.

[0064] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A personalized exhibition route planning method based on map information, characterized in that: The method comprises: Obtain the actual population type of the target visitors of the planned tour route; Determine at least one target exhibit that the target visitor is interested in based on the actual crowd type, at least one target tasting time range for each exhibit by historical visitors, and at least one corresponding target crowd type, wherein the target tasting time range is a time range that the tasting time of historical visitors for a single exhibit is likely to be within, and the target crowd type is a crowd type of historical visitors whose tasting time is likely to be within the corresponding target tasting time range; Based on the target location currently located by the target visitor and the exhibit locations of each of the target exhibits, determining at least one target visiting path corresponding to the target visitor, and determining the best visiting path from among the target visiting paths; Determine the voice introduction information of the target exhibits in the optimal visiting route, and send the optimal visiting route and each voice introduction information to the terminal of the target visitor.

2. The personalized exhibition route planning method based on map information according to claim 1 is characterized in that: The determining, based on the actual crowd type, at least one target tasting time range of each exhibit by historical visitors, and at least one corresponding target crowd type, at least one target exhibit that the target visitor is interested in specifically includes: Obtaining the historical tasting time ranges of each historical visitor for a single exhibit, counting the first occurrence times of each of the historical tasting time ranges, and selecting a first number of historical tasting time ranges from each of the historical tasting time ranges in descending order of the first occurrence times as target tasting time ranges; Obtaining historical population types of historical visitors whose tasting duration is within the single target tasting duration range, counting the second number of occurrences of each of the historical population types, and selecting a second number of historical population types from each of the historical population types in descending order of the second number of occurrences as target population types, wherein the target population types are historical population types corresponding to the single target tasting duration range; Determine a first weight for each of the target tasting time ranges, and determine a second weight for each of the target population types corresponding to each of the target tasting time ranges, wherein the first weight is a ratio of a first occurrence number of each target tasting time range to a sum of first occurrence numbers of all target tasting time ranges, and the second weight is a ratio of a second occurrence number of a single target population type corresponding to the target tasting time range to a sum of second occurrence numbers of all corresponding target population types; At least one target exhibit that the target visitor is interested in is determined from among the exhibits according to the actual crowd type, the first weight of a single exhibit and the corresponding second weights.

3. The personalized exhibition route planning method based on map information according to claim 2 is characterized in that: The determining, from the exhibits according to the actual crowd type, the first weight of a single exhibit and the corresponding second weights, at least one target exhibit that the target visitor is interested in specifically includes: For a single exhibit, if the actual population type exists in each of the target population types corresponding to the target tasting time range, the corresponding target tasting time range is determined as the key time range; Determine the key time range before the preset tasting time threshold as the first time range, and determine the key time range after the tasting time threshold as the second time range, wherein each tasting time in the first time range is less than the tasting time threshold, and each tasting time in the second time range is not less than the tasting time threshold; Calculate a first product of a first weight of each of the first time ranges and a second weight of a corresponding actual crowd type, and sum each of the first products to obtain a sum of the first products; Calculate the second product of the first weight of each of the second time ranges and the second weight of the corresponding actual crowd type, sum the second products to obtain the sum of the second products, and if the sum of the second products is greater than the sum of the first products, determine the corresponding exhibit as the target exhibit of interest to the target visitor.

4. The personalized exhibition route planning method based on map information according to claim 3 is characterized in that: The determining, based on the target location currently located by the target visitor and the exhibit location of each of the target exhibits, at least one target visiting path corresponding to the target visitor specifically includes: Determine the visiting order of the corresponding target exhibits according to the sum of the second products corresponding to each of the target exhibits, wherein the larger the sum of the second products is, the higher the corresponding visiting order is; At least one target visiting path corresponding to the target visitor is determined according to the target location currently located by the target visitor, the exhibit location of each of the target exhibits and the corresponding visiting sequence.

5. The personalized exhibition route planning method based on map information according to claim 3 is characterized in that: Determining the best visiting route from each of the target visiting routes specifically includes: Obtaining the first occurrence frequency of a crowd density lower than a preset density threshold in historical exhibitions of a single exhibit; Obtaining a historical period in which a single exhibit has a crowd density lower than the density threshold, counting the second occurrence frequency of each historical period, and selecting a third number of historical periods from each of the historical periods in descending order of the second occurrence frequency to determine as target periods, wherein the target period is a historical period corresponding to the single exhibit; Determine a third weight for each of the exhibits, and determine a fourth weight for each of the target time periods corresponding to each of the exhibits, wherein the third weight is a ratio of a first occurrence frequency of each exhibit to a sum of first occurrence frequencies of all exhibits, and the fourth weight is a ratio of a second occurrence frequency of a single target time period corresponding to the exhibit to a sum of second occurrence frequencies of all corresponding target time periods; According to the third weight and the corresponding fourth weights, an optimal visiting route is determined from the target visiting routes.

6. The personalized exhibition route planning method based on map information according to claim 5 is characterized in that: Determining the best visiting path from each of the target visiting paths according to the third weight and the corresponding fourth weights specifically includes: In a single target visiting path, determining the estimated walking time of the target visitor from the last position to each target exhibit; when the last position is not the exhibit position of the last target exhibit, determining the estimated arrival time of the target visitor to the corresponding target exhibit based on the arrival time of the target visitor to the last position and the estimated walking time; When the previous position is the exhibit position of the previous target exhibit, selecting the maximum second product from the second products corresponding to the previous target exhibit, and determining the second duration range corresponding to the maximum second product as the reference duration range; Determine the estimated arrival time of the target visitor at the corresponding target exhibit based on the arrival time of the last location, the estimated walking time and the reference time range; If each target time period corresponding to the target exhibit contains a corresponding estimated arrival time, the corresponding target exhibit is determined as an important exhibit, the target time period containing the estimated arrival time is determined as an important time period, and the third product of the third weight of each important exhibit and the fourth weight of the corresponding important time period is calculated and summed to obtain the sum of the third products of the corresponding target visiting paths; A maximum sum of the third products is selected from the sums of the third products, and a target tour path corresponding to the maximum sum of the third products is determined as an optimal tour path.

7. The personalized exhibition route planning method based on map information according to claim 2 is characterized in that: The method further comprises: Counting the actual tasting time of the target exhibits visited by the target visitor under the optimal visiting route, if the actual tasting time is within the target tasting time range of the corresponding target exhibit, determining the corresponding target tasting time range as the key time range; Calculate the fourth product of the first weight of each of the important time ranges and the second weight of each corresponding target population type, select the maximum fourth product from the fourth products, and determine the target population type corresponding to the maximum fourth product as the final population type; If the number of identical final crowd types exceeds a preset number threshold, when the identical final crowd type is not the actual crowd type, the actual crowd type is replaced with the identical final crowd type, and a visiting route adapted to the target visitor is re-determined.

8. A personalized exhibition route planning device based on map information, characterized in that: include: An information acquisition module (11) is used to obtain the actual population type of the target visitors of the planned tour route; An exhibit screening module (12) is used to determine at least one target exhibit that the target visitor is interested in based on the actual crowd type, at least one target tasting time range of each exhibit by the historical visitors, and at least one corresponding target crowd type, wherein the target tasting time range is a time range that the historical visitors tend to spend tasting a single exhibit, and the target crowd type is a crowd type of the historical visitors whose tasting time tends to fall within the corresponding target tasting time range; A path planning module (13) is used to determine at least one target visiting path corresponding to the target visitor based on the target location currently located by the target visitor and the exhibit location of each target exhibit, and determine the best visiting path from each target visiting path; A path sending module (14) is used to determine the voice introduction information of the target exhibits in the optimal visiting path, and send the optimal visiting path and each voice introduction information to the terminal of the target visitor.

9. A computer-readable storage medium having a computer program stored therein, characterized in that: When the computer program is loaded and executed by a processor, the method according to any one of claims 1 to 7 is adopted.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor loads and executes the computer program, the method according to any one of claims 1 to 7 is adopted.

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