Smart culture park management method and system, medium and electronic equipment

Abstract

The invention provides a smart culture park management method and system, a medium and electronic equipment, and relates to the technical field of data processing. The method comprises the following steps: acquiring reservation information of visitors in a culture park on the same day, wherein the reservation information comprises identity information, an interested theme set and a visiting time period; for any visitor, determining a plurality of target visiting areas in the culture park based on the interested theme set; determining a target visiting strategy based on each target visiting area and the visiting time period; expanding the target visiting strategy based on the historical visiting record of the cultural park and the identity information to obtain a standby visiting strategy; and sending the target visiting strategy and the standby visiting strategy to intelligent terminals corresponding to the visitors. By implementing the technical scheme provided by the invention, the management efficiency of the culture park can be improved.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly relates to a management method, system, medium, and electronic device for an intelligent cultural park. Background Art

[0002] With the booming development of the cultural industry, various cultural parks play an important role in enriching people's spiritual and cultural lives. A cultural park usually contains multiple exhibition areas, each of which displays different cultural theme contents, providing rich cultural experiences for visitors.

[0003] Currently, the visit management of cultural parks mainly adopts a reservation system. Visitors can reserve the visit time through online or offline methods. Visitors can freely visit according to the park map and exhibition area information. In actual operation, due to the large number and uneven distribution of visitors, the existing system usually can only provide static information and services, and cannot provide dynamic visit suggestions for visitors according to the real-time situation of the park. Visitors cannot obtain a good visit experience within a limited time, resulting in low management efficiency of cultural parks. Summary of the Invention

[0004] This application provides a management method, system, medium, and electronic device for an intelligent cultural park, which can improve the management efficiency of cultural parks.

[0005] In a first aspect, this application provides a management method for an intelligent cultural park, and the method includes: Obtain the reservation information of each visitor in the cultural park on the current day, where the reservation information includes identity information, an interest theme set, and a visit time period; For any one of the visitors, determine a plurality of target visit areas in the cultural park based on the interest theme set; Determine a target visit strategy based on each of the target visit areas and the visit time period; Expand the target visit strategy based on the historical visit records of the cultural park and the identity information to obtain a backup visit strategy; Send the target visit strategy and the backup visit strategy to the intelligent terminals corresponding to each of the visitors.

[0006] By adopting the above technical solution, based on the identity information, the set of interested themes, and the visiting time period included in the reservation information of the visitors, the target visiting areas that match the interests of each visitor are intelligently determined, and a reasonable target visiting strategy is generated based on the visiting time period. At the same time, the historical visiting records of the cultural park and the identity information of the visitors are used to expand the target visiting strategy to generate a backup visiting strategy, so that the visitors can adjust the visiting route in time when encountering situations such as congestion in the exhibition areas. This not only ensures that the visitors can obtain a visiting experience that matches their interests within their reserved time period, but also can dynamically optimize the visiting route according to the real-time situation of the park, effectively avoiding the problem of excessive concentration of visitors in some exhibition areas, thereby improving the management efficiency of the cultural park.

[0007] In the second aspect of the present application, a management system for an intelligent cultural park is provided. The system includes: A reservation information acquisition module, configured to acquire the reservation information of each visitor to the cultural park on the current day, where the reservation information includes identity information, a set of interested themes, and a visiting time period; A visiting area determination module, configured to determine, for any one of the visitors, a plurality of target visiting areas in the cultural park based on the set of interested themes; A visiting strategy determination module, configured to determine a target visiting strategy based on each of the target visiting areas and the visiting time period; A backup strategy determination module, configured to expand the target visiting strategy based on the historical visiting records of the cultural park and the identity information to obtain a backup visiting strategy; A strategy sending module, configured to send the target visiting strategy and the backup visiting strategy to the intelligent terminals corresponding to each of the visitors.

[0008] In the third aspect of the present application, a computer storage medium is provided. The computer storage medium stores a plurality of instructions, and the instructions are adapted to be loaded and executed by a processor to perform the above method steps.

[0009] In the fourth aspect of the present application, an electronic device is provided, including: a processor and a memory; wherein, the memory stores a computer program, and the computer program is adapted to be loaded and executed by the processor to perform the above method steps.

[0010] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: Based on the identity information, set of interested topics, and visiting time period included in the reservation information of visitors, this application intelligently determines the target visiting areas that match the interests of each visitor, generates a reasonable target visiting strategy based on the visiting time period, and at the same time expands the target visiting strategy using the historical visiting records of the cultural park and the identity information of the visitors to generate a backup visiting strategy. As a result, when visitors encounter situations such as congestion in exhibition areas, they can adjust their visiting routes in a timely manner, not only ensuring that visitors obtain a visiting experience that matches their interests within their reserved time period, but also being able to dynamically optimize the visiting route according to the real-time situation of the park, effectively avoiding the problem of excessive concentration of visitors in certain exhibition areas, thereby improving the management efficiency of the cultural park. Description of the Drawings

[0011] Figure 1 is a schematic flowchart of a management method for an intelligent cultural park provided by an embodiment of the present application; Figure 2 is a schematic block diagram of a management system for an intelligent cultural park provided by an embodiment of the present application; Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0012] Description of the reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed Embodiments

[0013] 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 accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0014] In the description of the embodiments of the present application, words such as "for example" or "for instance" are used to represent examples, illustrations, or explanations. Any embodiment or design solution described as "for example" or "for instance" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, using words such as "for example" or "for instance" is intended to present relevant concepts in a specific manner.

[0015] In the description of the embodiments of the present application, the term "a plurality of" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0016] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments.

[0017] Please refer to Figure 1 , and a schematic flowchart of a management method for a smart cultural park is specifically proposed. This method can be implemented depending on a computer program, can be implemented depending on a single-chip microcomputer, or can run on a management system for a smart cultural park. This computer program can be integrated in a computer device or can run as an independent tool-type application. Specifically, this method includes steps 10 to 50, and the above steps are as follows: Step 10: Obtain the reservation information of each visitor in the cultural park on the current day. The reservation information includes identity information, a set of interested themes, and the visiting time period.

[0018] In the embodiments of the present application, a cultural park refers to a place that includes multiple exhibition areas showing different cultural theme contents and serves visitors through an intelligent management system. This place can be a cultural exhibition and education institution such as a museum, an art gallery, a science and technology museum, a theme park, etc.

[0019] In the embodiments of the present application, reservation information refers to the visit application data submitted by visitors through a smart terminal and verified by the system. Specifically, it includes identity information for identity authentication, a set of interested themes for determining visit preferences, and the visiting time period for arranging a visit plan. Among them, the set of interested themes can be a collection of themes actively selected by visitors and themes obtained by the system based on the analysis of visitors' behavior data.

[0020] Specifically, the intelligent management system of the cultural park receives the reservation requests submitted by visitors through the reservation interface of the intelligent terminal. When a reservation request is submitted, the system requires visitors to provide identity information such as ID numbers and names, and conducts real-name identity verification to ensure the authenticity and validity of the reservation information. After the identity verification is passed, the system will display the theme introductions of each exhibition area in the cultural park on the reservation theme interface. Visitors can actively select the themes they are interested in according to their personal interests. At the same time, the system will collect behavioral data such as the stay duration, click times, and browsing order of visitors on the reservation theme interface, identify the interest tendencies of visitors through data analysis algorithms, and merge the theme set actively selected by visitors with the theme set obtained through behavioral analysis to form the final interested theme set. This two-way determination method can more comprehensively reflect the interest preferences of visitors. Subsequently, the system will display the remaining reservation capacity information for each time period of the day, and visitors can choose a suitable visiting time period. After the system receives the selection of the visiting time period, it will check the remaining reservation capacity for that time period. When the capacity is sufficient, the system will confirm the reservation and generate a complete reservation information including identity information, the interested theme set, and the visiting time period.

[0021] Based on the above embodiments, as an alternative embodiment, the step of obtaining the reservation information of each visitor in the cultural park on the same day may further include the following steps: Step 101: Receive the reservation requests sent by each visitor through the intelligent terminal, and conduct identity verification based on the identity information in the reservation requests.

[0022] Specifically, visitors first access the reservation system of the cultural park through intelligent terminals such as mobile phone apps and mini-programs. The reservation system will guide visitors to fill in a reservation application form containing identity information such as name, ID number, and contact information. After the system receives the reservation request, it will call the real-name authentication interface to verify the identity information filled in by visitors with the identity information database of the public security department. The system will also check whether there are duplicate reservations or bad records for this identity information, so as to ensure the authenticity and validity of the reservation.

[0023] Step 102: When the identity verification is valid, determine the interested themes of each visitor.

[0024] Specifically, after the authentication is passed, the system will display a theme selection interface for the visitors. This interface shows the theme content of each exhibition area in the park in a combination of pictures and texts. Visitors can select the themes they are interested in by clicking, collecting, etc. The system will record data such as the stay duration, click times, sliding speed, and browsing order of the visitors when viewing the introduction pages of each theme. For example, when a visitor views the "Ancient Ceramic Art" theme, the system will record whether the stay duration of the visitor on this page exceeds a preset threshold (such as 30 seconds), whether the visitor clicks on the exhibit details multiple times, whether the visitor takes a page screenshot or makes a collection, etc. At the same time, the system will also track the switching behavior of the visitors between different themes and record their browsing paths and repeated visit patterns.

[0025] Based on the collected behavior data, the system analyzes the interest tendencies of the visitors through machine learning algorithms. The system has pre-established a model of the correlation between behavior characteristics and interests, which is trained with a large amount of historical data. By inputting the behavior data of the visitors into this model, the system can calculate the interest degree scores of the visitors for each theme. When the interest degree score of a certain theme exceeds the preset threshold, this theme will be included in the first set of interested themes. At the same time, the system will provide a theme selection function on the reserved theme interface. Visitors can directly select the themes they are interested in by checking, marking, etc. These actively selected themes form the second set of interested themes.

[0026] To comprehensively grasp the interest preferences of the visitors, the system combines the first set of interested themes obtained through behavior analysis with the second set of interested themes actively selected by the visitors. During the combination process, the system will remove duplicate themes and organize and sort them according to the relevance between themes. For example, if a visitor selects "Ming and Qing Porcelain" in the second set of interested themes, and the first set of interested themes contains "Ancient Ceramic Art", the system will associate these two related themes to form a more complete interest theme chain. The finally formed set of interested themes includes both the interest preferences clearly expressed by the visitors and the potential interests discovered through behavior analysis, thus more accurately reflecting the real needs of the visitors.

[0027] Step 103: Receive the visiting time periods of each visitor. When the remaining reservation capacity during the visiting time period is sufficient, determine that the reservation is completed, and generate reservation information corresponding to each visitor, including identity information, interested themes, and visiting time periods.

[0028] Specifically, after the theme selection is completed, the system will display the reservation status for each time slot of the day. There is a maximum reservation limit for each time slot, and the system will display the remaining available reservation slots for each time slot in real time. After the visitor selects the desired visiting time slot, the system will immediately check the remaining reservation capacity for that time slot. If the remaining capacity is sufficient, the system will automatically lock a reservation slot and generate reservation information that includes the visitor's identity information, the set of interested themes, and the visiting time slot. At the same time, the system will push a confirmation message of successful reservation to the visitor's smart device and provide an electronic version of the reservation voucher.

[0029] Step 20: For any visitor, determine multiple target visiting areas in the cultural park based on the set of interested themes.

[0030] Specifically, in the intelligent management system of the cultural park, there is an electronic map of the park and a database of the correspondence between themes and exhibition areas stored. This database details the theme attributes of each exhibition area, including the main display theme and secondary related themes of the exhibition area. For any visitor, after the system reads the set of the visitor's interested themes, it retrieves and matches each interested theme in the theme-exhibition area correspondence database to find all candidate exhibition areas related to that theme. During the matching process, the system uses a similarity calculation method. When the similarity between the theme and the exhibition area exceeds a preset threshold, that exhibition area is determined as a candidate exhibition area. For example, when the interested theme is "Ancient Ceramic Art", the system will not only match the exhibition areas with exactly the same theme but also include the historical and cultural exhibition areas containing relevant ceramic exhibits in the candidate set. The system will then calculate the overall matching degree between each candidate exhibition area and the set of interested themes. The calculation of the matching degree comprehensively considers factors such as theme relevance, the number of exhibits, and content quality, and sorts and filters the candidate exhibition areas according to the matching degree. Finally, multiple exhibition areas with the highest matching degree are selected as the target visiting areas. This way of determining exhibition areas based on theme mapping can accurately correspond the visitor's interest needs with the actual exhibition areas, ensuring the relevance and integrity of the visiting content, while avoiding visitors missing important exhibition areas and improving the visiting efficiency.

[0031] Based on the above embodiments, as an optional embodiment, the step of determining multiple target visiting areas in the cultural park based on the set of interested themes may further include the following steps: Step 201: Construct the theme feature vectors of each exhibition area in the cultural park.

[0032] Specifically, in the intelligent management system of the cultural park, first, by extracting and quantifying the characteristics such as the display content, exhibit attributes, and cultural elements of each exhibition area, a theme feature vector for each exhibition area is constructed. Natural language processing technology can be used to perform semantic analysis on the text content such as the theme description text, exhibit descriptions, and commentary of the exhibition area, extract keywords and assign weights, and at the same time combine structured features such as exhibit types, historical eras, and art genres to form a multi-dimensional feature vector. For example, for the "Ming and Qing Porcelain Exhibition Area", its feature vector includes numerical representations of dimensions such as "porcelain craftsmanship", "court culture", and "historical value".

[0033] Step 202: Calculate the similarity between each interesting theme in the set of interesting themes and the theme feature vector.

[0034] Specifically, when calculating the similarity between an interesting theme and the theme feature vector of the exhibition area, the cosine similarity algorithm is used. The interesting theme is converted into a vector representation with the same dimension as the theme feature vector of the exhibition area, and then the cosine value of the angle between the two vectors is calculated as the similarity index. The value range of the similarity is from 0 to 1, and the larger the value, the higher the correlation between the theme and the exhibition area. The system will calculate the similarity for each theme in the set of interesting themes and take the weighted average as the overall similarity between the exhibition area and the entire set of interesting themes.

[0035] Step 203: Predict the crowding degree of each exhibition area and calculate the recommended score for each exhibition area based on the similarity and crowding degree data.

[0036] Specifically, based on the real-time collected passenger flow data and historical visit records, the system uses a time series prediction model to predict the crowding degree of each exhibition area during the target visit period. The prediction model takes into account multiple influencing factors such as time, season, weather, and holidays, calculates the expected pedestrian flow density of each exhibition area, and the crowding degree data is normalized and converted into a value between 0 and 1, where 1 represents the most crowded and 0 represents the least crowded. The similarity data and crowding degree data are combined to calculate the recommended score for each exhibition area. The specific calculation formula is: recommended score = α × similarity - β × crowding degree, where α and β are weight coefficients used to balance the influence of similarity and crowding degree on the final recommendation result. The values of α and β can be adjusted according to the actual operation requirements of the park. In the embodiment of this application, α is taken as 0.7 and β is taken as 0.3 to highlight the importance of theme relevance.

[0037] Step 204: Sort each exhibition area according to the recommended score, and select several exhibition areas with higher rankings as the target visit areas.

[0038] Specifically, all exhibition areas are sorted in descending order according to the calculated recommendation scores, and the top N exhibition areas with the highest rankings are selected as the target visiting areas, where the value of N is determined according to the expected visiting duration. This exhibition area recommendation method based on the theme feature vector and crowding degree not only ensures a high correlation between the recommended exhibition areas and the interests of visitors, but also balances the passenger flow distribution among exhibition areas to a certain extent, avoiding the problem of overcrowding in popular exhibition areas and providing a better visiting experience for visitors. At the same time, through adjustable weight parameters, the system can flexibly adapt to the recommendation requirements in different periods and different scenarios, with good versatility and scalability.

[0039] Step 30: Determine the target visiting strategy based on each target visiting area and the visiting time period.

[0040] Specifically, detailed information of the target visiting area is retrieved from the park database, including basic data such as the geographical location coordinates, exhibition area, standard visiting time, walking distance between exhibition areas, and opening hours of each exhibition area. Then, the total available visiting time is calculated based on the start and end times of the visiting period, and appropriate rest time is reserved considering the physical consumption and rest needs of visitors. For example, for a 3-hour visiting period, the system reserves about 30 minutes of rest time and plans the remaining 2.5 hours as the actual visiting time. An intelligent path planning algorithm is used to construct a weighted directed graph based on the exhibition area distribution, where the nodes of the graph represent each target visiting area, and the weights of the edges comprehensively consider factors such as walking distance, expected passenger flow congestion level, and theme relevance between exhibition areas. Through the dynamic programming algorithm, the system calculates the optimal visiting route that can cover the most target visiting areas within a limited time. During the path planning process, the system preferentially arranges exhibition areas with higher recommended scores and tries to select a visiting order with natural theme connection and reasonable walking distance. At the same time, the system takes the opening time limit as a hard constraint condition to ensure that the generated visiting route is feasible within the opening hours of each exhibition area. Based on the optimal visiting route, the visiting time arrangement is further refined, and a reasonable visiting duration is allocated to each exhibition area. When allocating the duration, both the standard visiting time of the exhibition area and the similarity between the exhibition area and the visitor's interest theme are considered for appropriate adjustment. For exhibition areas with higher similarity, the system appropriately increases the visiting duration to meet the visitor's need for in-depth understanding. The system also reserves appropriate walking time between adjacent exhibition areas and arranges rest points after sections with high visiting intensity, recommending nearby rest facilities. The finally generated target visiting guide contains a detailed schedule, clearly marking the visiting time period, walking route, estimated time, and recommended rest time for each exhibition area. The system also provides visiting suggestions according to the characteristics of each exhibition area, such as the location of key exhibits, the best viewing angle, and the time of the explanation service, to help visitors better arrange their visiting itinerary. At the same time, the system monitors the actual passenger flow situation of each exhibition area in real time, and when it is found that a certain exhibition area is temporarily congested or needs to be adjusted, it can timely push alternative route suggestions to visitors.

[0041] On the basis of the above embodiments, as another alternative embodiment, the step of determining the target visiting guide based on each target visiting area and the visiting period may further include the following steps: Step 301: Based on the total duration of the visiting period, allocate the visiting time for each target visiting area to obtain the target visiting time.

[0042] Specifically, the visiting time is allocated based on the total duration of the visiting time period. The reference visiting duration of each target visiting area is obtained from the park database, and the weight is adjusted considering the similarity between the area and the theme that the visitor is interested in. A time allocation algorithm can be used to allocate the total duration T to each target visiting area according to the weighted ratio. The calculation formula is: Target visiting time = Total duration × (Reference duration × Similarity weight) / ∑(Reference duration × Similarity weight of all areas). For example, when the total duration is 180 minutes, the reference duration of a certain exhibition area is 30 minutes, and the similarity weight is 1.2, the target visiting time of this exhibition area is about 36 minutes.

[0043] Step 302: Calculate the walking time between adjacent target visiting areas, perform a spatial distance score on the target visiting areas according to the walking time, and determine the optimal connection relationship of each target visiting area based on the spatial distance score.

[0044] Specifically, calculate the walking time between adjacent target visiting areas. When determining the walking time, the system calculates the walking time used between any two adjacent target visiting areas based on the actual distance data in the park electronic map, combined with the standard walking speed (usually taken as 1.2 m / s). To more accurately reflect the actual situation, the system also considers influencing factors such as the park terrain, path type, and passenger flow density to correct the basic walking time. Based on the calculated walking time, the system performs a spatial distance score on each adjacent exhibition area pair. The score is normalized, converting the walking time into a score between 0 and 1. The shorter the walking time, the higher the score. Use the improved minimum spanning tree algorithm to determine the optimal connection relationship between the exhibition areas. Take each target visiting area as a node of the graph, and the reciprocal of the spatial distance score as the weight of the edge. Construct a minimum spanning tree through the Prim algorithm to obtain the optimal connection relationship between each exhibition area. This connection relationship ensures the minimization of the walking distance between adjacent exhibition areas and improves the visiting efficiency.

[0045] Step 303: Generate the visiting order based on the optimal connection relationship, and calculate the visiting time points of each target visiting area in combination with the target visiting time.

[0046] Specifically, based on the optimal connection relationship, the system generates the visiting order through the depth-first search algorithm. During the search process, the exhibition area with a higher recommendation score is preferentially considered as the starting point, and the path is optimized in combination with the opening time limit of the exhibition area. After determining the visiting order, the system calculates the specific visiting time points of each target visiting area according to the starting time of the visiting time period, combined with the target visiting time of each exhibition area and the walking time between the exhibition areas. For example, if the visiting time period starts at 9:00, the visiting time of the first exhibition area is 36 minutes, and it takes 8 minutes to walk to the second exhibition area, then the visiting time point of the second exhibition area is 9:44.

[0047] Step 304: Generate a target visit guide that includes the visit order and visit time points of each target visit area.

[0048] Specifically, the finally generated target visit guide includes complete visit route information, clearly listing the visit order and specific time points of each target visit area. This method of generating a guide based on time allocation and space optimization not only ensures the reasonable allocation of visit time but also guarantees the spatial efficiency of the visit route, enabling visitors to maximize their visit experience within a limited time. At the same time, due to considering various actual influencing factors, the generated visit guide has strong executability and adaptability, and can effectively guide visitors to complete the visit activities in the cultural park.

[0049] Step 40: Expand the target visit guide based on the historical visit records and identity information of the cultural park to obtain a backup visit guide.

[0050] Specifically, in the intelligent guide system of the cultural park, the target visit guide is expanded and optimized by data mining and analysis of the stored historical visit records and in combination with the identity information of the visitors. The system first extracts historical visit records from the park database, including data such as the actual visit routes, stay times, and visit feedback of various visitors. Using a collaborative filtering algorithm, based on the identity characteristics of the visitors (such as age group, occupation, educational background, etc.), a group of historical visitors with similar characteristics is found, and the visit behavior patterns and preference characteristics of this group are analyzed. Through a deep learning model, the historical visit data is analyzed to extract the visit rules of different visitor types. Based on the analysis results, the system calculates the similarity between each exhibition area in the target visit guide and the highly satisfactory exhibition areas in the historical data, and adds the important exhibition areas that may be missed as alternative visit points. At the same time, the target visit time is optimized according to the actual stay times in the historical data to make it more in line with the visit habits of a specific group. When generating the backup visit guide, the system considers sudden situations such as temporary closure of exhibition areas, passenger flow congestion, and weather changes. Based on the response plans of visitors in similar situations in the historical data, the system designs alternative plans for each key node. For example, when there is congestion in a popular exhibition area, the system will recommend adjacent related exhibition areas as alternative options based on the selection patterns of historical visitors. The system will also add rest points and flexible time in the backup guide according to the physical strength and interest endurance characteristics of different groups.

[0051] On the basis of the above embodiments, as another alternative embodiment, the step of expanding the target visit guide based on the historical visit records and identity information of the cultural park to obtain a backup visit guide may further include the following steps: Step 401: Screen historical visitor data with similar identity information characteristics from the historical visit records of the cultural park.

[0052] Specifically, in the intelligent guided tour system of the cultural park, in order to provide a more personalized visiting experience, the system needs to extract the visiting preferences of similar groups to the current visitors from historical visiting records. Based on the identity information provided by the visitors, including characteristics such as age group, professional background, and education level, the system constructs a feature vector. Using a multi-dimensional similarity calculation method, the feature vector of the current visitor is matched with the visitor characteristics in the historical visiting records, the similarity score is calculated, and the historical visitor data with a similarity score higher than the threshold is filtered out to form a similar group sample set, that is, the historical visitor data.

[0053] Step 402: In the historical visitor data, count the visit frequencies of each historical visitor in each other visiting area outside the target visiting areas included in the target visiting guide.

[0054] Specifically, in the historical visitor data, the system compares the target visiting areas included in the target visiting guide and identifies the visiting behaviors of the similar group outside the target visiting areas. The system counts the visit frequencies of each other visiting area among the similar group. The calculation method is the cumulative number of visits to this area divided by the total number of the similar group to obtain the standardized visit frequency data. This frequency statistics method can objectively reflect the preference degree of the similar group for different visiting areas.

[0055] Step 403: Sort each other visiting area in descending order of visit frequency, and select several visiting areas with the top rankings as alternative visiting areas.

[0056] Specifically, sort the obtained other visiting areas in descending order of visit frequency to construct a priority queue. To ensure the quality and practicality of the alternative plans, the system sets the minimum threshold of the visit frequency and the upper limit of the number of alternative areas. The system selects the top N visiting areas with visit frequencies higher than the minimum threshold from the priority queue as alternative visiting areas, where the value of N is dynamically adjusted according to the length of the visiting time period and the actual operation situation of the park.

[0057] Step 404: Generate a visiting guide based on each alternative visiting area.

[0058] Specifically, in the intelligent guided tour system of the cultural park, in order to anticipate and address potential visit congestion issues in advance, this application optimizes and adjusts the target visit itinerary to generate a reasonable alternative visit itinerary. First, based on historical passenger flow data and real-time monitoring data, the system uses a time series prediction model to predict the congestion situation of each target visit area in the planned visit time point in the target visit itinerary. The prediction model comprehensively considers multi-dimensional features such as periodic patterns, holiday effects, and weather factors to calculate the expected congestion index for each visit area. The system compares the preset risk threshold (e.g., congestion index 0.8) with the prediction results and marks the visit areas with congestion indices exceeding the threshold as areas to be replaced.

[0059] To ensure the coherence and thematic nature of the visit experience, the system needs to find suitable replacement options among the alternative visit areas. First, through natural language processing techniques, the system extracts semantic features from the text information such as exhibition content and theme descriptions of the areas to be replaced and the alternative visit areas, and constructs theme feature vectors. The cosine similarity algorithm is used to calculate the theme similarity between the areas to be replaced and each alternative visit area. At the same time, the system also predicts the congestion risk of the alternative visit areas during the corresponding time period.

[0060] When selecting replacement areas, the system gives priority to alternative visit areas with the highest theme similarity and predicted congestion indices lower than the risk threshold. For example, when a exhibition area displaying ancient pottery is predicted to be congested, the system will preferentially select other exhibition areas that also display ancient handicrafts and have less passenger flow as replacement options. This replacement strategy not only ensures the continuity of the visit theme but also effectively avoids congestion problems.

[0061] After selecting the replacement areas, the system updates the visit route and time arrangement to generate an alternative visit itinerary. During the generation process, the system recalculates the adjusted walking distance and visit time to ensure the overall feasibility of the itinerary. To improve service quality, the system also continuously monitors the actual passenger flow situation and automatically pushes alternative itinerary suggestions to visitors when a preset trigger condition is detected (such as the actual congestion index of a certain exhibition area exceeding the threshold).

[0062] Step 50: Send the target visit itinerary and the alternative visit itinerary to the smart terminals of the corresponding visitors.

[0063] Specifically, after generating the target visit guide and alternative visit guide for each visitor, in order to ensure that visitors can obtain personalized visit plans in a timely manner and flexibly respond to possible emergencies, the embodiments of the present application establish an efficient and reliable information push mechanism. First, through the network communication platform of the park, the generated target visit guide and alternative visit guide are packaged using an encrypted data transmission protocol to form a digital visit plan package containing content such as visit routes, time arrangements, and exhibition area information. The system assigns a unique identification code to each visit plan package and establishes an associated mapping with the identity information of the corresponding visitor. After receiving the visit plan package, the intelligent terminal automatically analyzes the data content therein and saves the visit guide information through a local storage mechanism to ensure that visitors can still view the visit plan when the network signal is poor. The system visually displays the visit route and time arrangement on the intelligent terminal and provides an interactive operation interface to facilitate visitors to switch and view the detailed information of the target visit guide and alternative visit guide at any time. At the same time, the system continuously monitors the real-time status of the park in the background of the intelligent terminal and, when a preset trigger condition occurs, promptly pushes a suggestion to switch to the alternative visit guide to the visitors.

[0064] Please refer to Figure 2 , which is a schematic diagram of the modules of a management system for a smart cultural park provided by the embodiments of the present application. The management system for the smart cultural park may include: a reservation information acquisition module, a visit area determination module, a visit guide determination module, an alternative guide determination module, and a guide sending module, where: The reservation information acquisition module is used to acquire the reservation information of each visitor in the cultural park on the current day. The reservation information includes identity information, an interest theme set, and a visit time period; The visit area determination module is used to determine, for any one of the visitors, a plurality of target visit areas in the cultural park based on the interest theme set; The visit guide determination module is used to determine a target visit guide based on each of the target visit areas and the visit time period; The alternative guide determination module is used to expand the target visit guide based on the historical visit records of the cultural park and the identity information to obtain an alternative visit guide; The guide sending module is used to send the target visit guide and the alternative visit guide to the intelligent terminals of the corresponding visitors.

[0065] Optionally, the reservation information acquisition module is further used to receive reservation requests sent by each visitor through the intelligent terminal and perform identity verification based on the identity information in the reservation requests; When the identity verification is valid, determine the interest themes of each visitor; Receive the visiting time periods of each of the visitors, determine that the reservation is completed when the remaining reservation capacity during the visiting time period is sufficient, and generate reservation information corresponding to each of the visitors, including the identity information, the interested themes, and the visiting time period.

[0066] Optionally, the reservation information acquisition module is further configured to collect the behavior data of each of the visitors on the reservation theme interface; Determine the first set of interested themes of each of the visitors based on the behavior data, and obtain the second set of interested themes selected by each of the visitors; Merge the first set of interested themes and the second set of interested themes to obtain the set of interested themes.

[0067] Optionally, the visiting area determination module is further configured to construct the theme feature vectors of each exhibition area in the cultural park; Calculate the similarity between each interested theme in the set of interested themes and the theme feature vectors; Predict the congestion degree of each exhibition area, and calculate the recommended scores of each exhibition area based on the similarity and the congestion degree data; Sort each exhibition area according to the recommended scores, and select several exhibition areas with higher rankings as the target visiting areas.

[0068] Optionally, the visiting strategy determination module is further configured to allocate the visiting time of each of the target visiting areas based on the total duration of the visiting time period to obtain the target visiting time; Calculate the walking time between adjacent target visiting areas, perform a spatial distance scoring on the target visiting areas according to the walking time, and determine the optimal connection relationship of each target visiting area based on the spatial distance scoring; Generate a visiting order based on the optimal connection relationship, and calculate the visiting time points of each target visiting area in combination with the target visiting time; Generate a target visiting strategy including the visiting order and visiting time points of each of the target visiting areas.

[0069] Optionally, the backup strategy determination module is further configured to screen the historical visitor data with similar identity information characteristics from the historical visiting records of the cultural park; Count the visit frequencies of each historical visitor in each other visiting area outside the target visiting areas included in the target visiting strategy in the historical visitor data; Sort each of the other visiting areas in descending order of the visit frequencies, and select several visiting areas with higher rankings as the alternative visiting areas; Generate the backup visiting strategy based on each of the alternative visiting areas.

[0070] Optionally, the backup strategy determination module is further configured to predict the congestion risk of each target visit area in the target visit strategy at the corresponding time point, and mark the visit areas with congestion risk higher than the risk threshold as areas to be replaced; Select, from the alternative visit areas, the area with the highest theme similarity to the area to be replaced and with a congestion risk lower than the risk threshold as the replacement area; Replace the area to be replaced with the corresponding replacement area, and generate the backup visit strategy.

[0071] It should be noted that: when the system provided in the above embodiments realizes its functions, only the division of the above function modules is used for illustration. In actual applications, the above functions can be allocated to different function modules according to needs, that is, the internal structure of the device is divided into different function modules to complete all or part of the functions described above. In addition, the systems and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be elaborated here.

[0072] The embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded and executed by a processor to execute the management method of a smart cultural park in the above embodiments. The specific execution process can refer to the specific description in the above embodiments, and will not be elaborated here.

[0073] Please refer to Figure 3 The present application also discloses an electronic device. Figure 3 It is a schematic structural diagram of an electronic device disclosed in the embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0074] Among them, the communication bus 302 is used to realize the connection and communication between these components.

[0075] Among them, the user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may further include a standard wired interface and a wireless interface.

[0076] Among them, the network interface 304 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0077] Among them, the processor 301 may include one or more processing cores. The processor 301 connects various parts within the entire server through various interfaces and lines. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by invoking the data stored in the memory 305, it executes various functions of the server and processes data. Optionally, the processor 301 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 301 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301 and may be implemented separately through a single chip.

[0078] Among them, the memory 305 may include random access memory (RAM) and may also include read-only memory. Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store the data involved in the above-mentioned method embodiments. Optionally, the memory 305 may also be at least one storage device located far from the aforementioned processor 301. Refer to Figure 3 , the memory 305, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a management method of an intelligent cultural park.

[0079] In Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an interface for the user to input and obtain the data input by the user; and the processor 301 can be used to call the application program stored in the memory 305 that manages a smart cultural park. When executed by one or more processors 301, the electronic device 300 is caused to execute one or more of the methods as described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, some steps can be adopted in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0080] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0081] In several implementation manners provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some service interfaces. The indirect couplings or communication connections of the devices or units can be in electrical or other forms.

[0082] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0083] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0084] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned memory includes various media that can store program codes, such as USB flash drives, mobile hard disks, magnetic disks, or optical discs.

[0085] The above are only exemplary embodiments of the present disclosure, and the scope of the present disclosure cannot be limited thereby. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. After considering the specification and the disclosure of the practical truth, those skilled in the art will easily think of other implementation manners of the present disclosure.

[0086] The present application aims to cover any variations, uses, or adaptive changes of the present disclosure. These variations, uses, or adaptive changes follow the general principles of the present disclosure and include common general knowledge or conventional technical means in the technical field not recorded in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A management method for a smart cultural park, characterized in that: The method comprises: Obtaining reservation information of each visitor of the cultural park on the day, the reservation information including identity information, set of interested topics and visiting time period; For any of the visitors, determining a plurality of target visiting areas in the cultural park based on the set of interested topics; Determine a target visiting strategy based on each of the target visiting areas and the visiting time period; Expanding the target visiting strategy based on the historical visiting records of the cultural park and the identity information to obtain a backup visiting strategy; The target visiting strategy and the backup visiting strategy are sent to the smart terminals corresponding to the visitors.

2. The management method of the smart cultural park according to claim 1, characterized in that: The obtaining of reservation information of each visitor of the cultural park on the day includes: Receiving reservation requests sent by each visitor through the smart terminal, and performing identity authentication based on the identity information in the reservation request; When the identity verification is valid, determining the topics of interest of each of the visitors; The visiting time period of each visitor is received, and when the remaining reservation capacity of the visiting time period is sufficient, the reservation completion is determined, and reservation information corresponding to each visitor including the identity information, the subject of interest, and the visiting time period is generated.

3. The management method of the smart cultural park according to claim 2, characterized in that: Determining the topics of interest to each visitor includes: Collecting the behavior data of each visitor on the reservation theme interface; Determine a first set of topics of interest to each of the visitors based on the behavior data, and obtain a second set of topics of interest selected by each of the visitors; The first interest topic set and the second interest topic set are merged to obtain the interest topic set.

4. The management method of the smart cultural park according to claim 1, characterized in that: The determining of a plurality of target visiting areas in the cultural park based on the set of interested topics includes: Constructing a theme feature vector for each exhibition area in the cultural park; Calculate the similarity between each topic of interest in the topic set and the topic feature vector; Predicting the congestion of each of the exhibition areas, and calculating a recommendation score for each of the exhibition areas based on the similarity and the congestion data; The exhibition areas are ranked according to the recommendation scores, and a number of exhibition areas with the highest rankings are selected as the target visiting areas.

5. The management method of the smart cultural park according to claim 1, characterized in that: The determining of the target visiting strategy based on each of the target visiting areas and the visiting time period includes: Based on the total duration of the visiting time period, the visiting time of each target visiting area is allocated to obtain a target visiting time; Calculating the walking time between adjacent target visiting areas, performing spatial distance scoring on the target visiting areas according to the walking time, and determining the optimal connection relationship between the target visiting areas based on the spatial distance scoring; Generate a visiting sequence based on the optimal connection relationship, and calculate the visiting time point of each target visiting area in combination with the target visiting time; Generate a target visiting guide including the visiting sequence and visiting time points of each target visiting area.

6. The management method of the smart cultural park according to claim 1, characterized in that: The target visiting strategy is expanded based on the historical visiting records of the cultural park and the identity information to obtain a backup visiting strategy, including: Filter historical visitor data similar to the identity information characteristics from the historical visit records of the cultural park; Counting the visit frequencies of each historical visitor in the historical visitor data to each other visiting area other than the target visiting area included in the target visiting strategy; Sorting the other visiting areas in descending order of the visiting frequency, and selecting several visiting areas with the highest ranking as candidate visiting areas; The alternative visiting guide is generated based on each of the alternative visiting areas.

7. The management method of the smart cultural park according to claim 6, characterized in that: The generating the alternative visiting guide based on each of the candidate visiting areas includes: Predicting the congestion risk of each target visiting area in the target visiting strategy at a corresponding time point, and marking the visiting area with a congestion risk higher than a risk threshold as an area to be replaced; Selecting from the candidate visiting areas an area with the highest theme similarity to the area to be replaced and a congestion risk lower than the risk threshold as a replacement area; The area to be replaced is replaced with a corresponding replacement area, and the backup visiting guide is generated.

8. A management system for a smart cultural park, characterized in that: The system comprises: The reservation information acquisition module is used to obtain the reservation information of each visitor of the cultural park on the day, and the reservation information includes identity information, interest theme set and visiting time period; A visiting area determination module, for determining, for any of the visitors, a plurality of target visiting areas in the cultural park based on the set of interested topics; A visiting strategy determination module, used to determine a target visiting strategy based on each of the target visiting areas and the visiting time period; A backup strategy determination module, used to expand the target visiting strategy based on the historical visiting records of the cultural park and the identity information to obtain a backup visiting strategy; The strategy sending module is used to send the target visiting strategy and the backup visiting strategy to the smart terminal corresponding to each of the visitors.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-7.

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