Scenic area touring path determination method, system, device, medium and program product

Abstract

The invention discloses a scenic spot sightseeing path determination method, system and device, a medium and a program product, and relates to the technical field of scenic spot intelligent navigation. The method comprises the following steps: acquiring a current user position, a current remaining sightseeing duration, current state data and current environment data of a scenic spot; determining user portrait information based on the current remaining touring duration and the current state data; determining a current sightseeing experience value of each scenic spot based on the current environment data; determining a plurality of to-be-selected scenic spots based on the user portrait information and the current touring experience value, and determining a plurality of to-be-selected touring paths based on the current user position and the to-be-selected scenic spots; based on the current environment data and the user portrait information, determining total touring cost and total touring time consumption corresponding to each to-be-selected touring path; and the target touring path of the user is determined based on the touring total cost, the touring total time consumption and the current remaining touring duration, so that the dynamic intelligent determination of the scenic spot touring path is realized, and the feasibility and flexibility of the touring path are improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to computer technology and intelligent scenic area navigation, and particularly to a method, system, device, medium and program product for determining scenic area tour routes. Background Technology

[0002] With the development of smart tourism, scenic area guidance is gradually evolving from traditional paper maps and manual explanations towards intelligent systems. Existing methods for determining scenic area tour routes typically rely on fixed route planning, such as based on preset attraction priorities, or static time estimation, such as based on historical average tour durations. However, in developing this invention, the inventors discovered at least the following problems in the existing technology:

[0003] Because existing technologies do not fully consider the impact of real-time environmental factors in scenic areas, such as crowding, temporary traffic control, and weather changes, on the visitor experience, the feasibility of the final determined tour route is poor. Furthermore, the tour route is not dynamically adjusted based on the user's location and remaining tour time, resulting in a low degree of matching between the final determined tour route and the user, thereby reducing the user's tour experience. Summary of the Invention

[0004] This invention provides a method, system, device, medium, and program product for determining scenic area tour routes, thereby enabling dynamic and intelligent determination of scenic area tour routes, improving the feasibility and flexibility of tour routes, as well as the matching degree between tour routes and users, and thus improving the user tour experience.

[0005] In a first aspect, embodiments of the present invention provide a method for determining a scenic area tour route, including:

[0006] The system acquires the user's current tour data and the scenic area's current environmental data, wherein the current tour data includes the user's current location, current remaining tour time, and current status data;

[0007] Based on the remaining tour duration and the current status data, the user profile information of the user is determined;

[0008] Based on the current environmental data, determine the current visitor experience value for each attraction in the scenic area;

[0009] Based on the user profile information and the current tour experience value, multiple candidate attractions for the user are determined, and based on the current user location and the multiple candidate attractions, multiple candidate tour routes for the user are determined;

[0010] Based on the current environment data and the user profile information, determine the total cost and total time spent on each candidate tour path;

[0011] The user's target tour path is determined based on the total tour cost, the total tour time, and the current remaining tour time.

[0012] Secondly, embodiments of the present invention also provide a scenic area tour route determination system, comprising:

[0013] The current data acquisition module is used to acquire the user's current tour data and the scenic area's current environmental data. The current tour data includes the user's current location, current remaining tour time, and current status data.

[0014] The user profile information determination module is used to determine the user profile information of the user based on the current remaining tour time and the current status data;

[0015] The visitor experience value determination module is used to determine the current visitor experience value of each attraction in the scenic area based on the current environmental data.

[0016] The candidate tour route determination module is used to determine multiple candidate attractions for the user based on the user profile information and the current tour experience value, and to determine multiple candidate tour routes for the user based on the current user location and the multiple candidate attractions;

[0017] The path information determination module is used to determine the total cost and total time spent on each candidate tour path based on the current environment data and the user profile information.

[0018] The target tour path determination module is used to determine the user's target tour path based on the total tour cost, the total tour time, and the current remaining tour time.

[0019] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0020] At least one processor; and

[0021] A memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to execute the scenic area tour route determination method provided in any embodiment of the present invention.

[0023] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute the scenic area tour path determination method provided in any embodiment of the present invention.

[0024] Fifthly, embodiments of the present invention also provide a computer program product, including a computer program that, when executed by a processor, implements the scenic area tour route determination method provided in any embodiment of the present invention.

[0025] One embodiment of the above invention has the following advantages or beneficial effects:

[0026] By acquiring the user's current tour data and the scenic area's current environmental data, dynamic spatiotemporal data is obtained. Based on the remaining tour time and current status data in the current tour data, user profile information is determined to dynamically construct the user profile. Based on the current environmental data, the current tour experience value of each attraction in the scenic area is determined to dynamically measure the impact of the scenic area environment on the tour experience. Based on the user profile information and the current tour experience value, multiple candidate attractions are identified for the user, and based on the current user location and multiple candidate attractions, multiple candidate tour routes are determined for the user. Based on the current environmental data and user profile information, the total tour cost and total tour time corresponding to each candidate tour route are determined. Based on the total tour cost, total tour time, and current remaining tour time, a target tour route matching the user is determined. This achieves dynamic and intelligent determination of scenic area tour routes, improving the feasibility and flexibility of tour routes, as well as the matching degree between tour routes and users, thereby improving the user's tour experience.

[0027] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart of a method for determining a scenic area tour route according to an embodiment of the present invention;

[0030] Figure 2 This is a flowchart of another method for determining a scenic area tour route provided in one embodiment of the present invention;

[0031] Figure 3 This is a flowchart of another method for determining a scenic area tour route provided in one embodiment of the present invention;

[0032] Figure 4 This is a flowchart of another method for determining a scenic area tour route provided in one embodiment of the present invention;

[0033] Figure 5 This is a schematic diagram of a scenic area tour route determination system provided in one embodiment of the present invention;

[0034] Figure 6 This is a schematic diagram of the structure of an electronic device that implements the scenic area tour route determination method of this invention. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0038] It should be noted that the collection, updating, analysis, use, transmission, and storage of user personal information involved in the technical solution disclosed herein all comply with relevant laws and regulations, are used for legitimate and reasonable purposes, and are not shared, disclosed, or sold outside of these legitimate uses, and are subject to supervision and management by national regulatory authorities. Necessary measures should be taken to selectively block the use or access to personal information data to prevent unauthorized access to such personal information data, ensure that personnel authorized to access personal information data comply with relevant laws and regulations, and ensure the security of user personal information. Furthermore, once this user personal information data is no longer needed, the risk should be minimized by restricting or even prohibiting data collection and / or deleting the data.

[0039] Figure 1 This is a flowchart illustrating a method for determining a scenic area tour route according to an embodiment of the present invention. This embodiment is applicable to situations where a tour route matching a user is dynamically determined while the user is touring a scenic area. This method can be executed by a scenic area tour route determination system, which can be implemented in software and / or hardware, and this system can be configured in an electronic device. Figure 1 As shown, the method specifically includes the following steps:

[0040] S110. Obtain the user's current tour data and the scenic area's current environment data, wherein the current tour data includes the user's current location, current remaining tour time, and current status data.

[0041] In this context, "user" refers to any tourist visiting the scenic area. "User's current visit data" refers to the user's visit data collected at the current moment. "Current user location" can refer to the user's current geographical location, which can be obtained through GPS or BeiDou Navigation Satellite System positioning of the user's terminal. "Current remaining visit time" refers to the remaining time the user has spent visiting the scenic area at the current moment. The current remaining visit time can be determined based on the user's estimated visit time, the time the user entered the scenic area, and the current time. For example, the user can input the total desired visit time (estimated visit time) on their terminal. Based on the current time and the time the user entered the scenic area, the user's current visited time is determined. Subtracting the current visited time from the estimated visit time yields the current remaining visit time. It's important to note that if the current time is earlier than the scenic area's opening time (i.e., the user has not yet entered the scenic area), the estimated visit time can be directly used as the current remaining visit time. If the current time is later than the scenic area's opening time, the remaining time before closing is determined based on the current time and the scenic area's closing time. The smaller of the calculated remaining tour time and the remaining closing time is then used to determine the user's final remaining tour time. Current status data represents the user's tour status. The scenic area can be any type, such as a natural scenic area, a historical and cultural scenic area, or a theme park. The scenic area's current environmental data can be collected at the current moment. This data can be obtained from the environmental database stored in real-time on the scenic area's server. The current environmental data may include visitor density, queue length, weather conditions, and temporary announcements for each attraction within the scenic area.

[0042] For example, the current status data may include: the user's tour interest characteristics, current movement speed, and current tour duration. The user's tour interest characteristics can be data characterizing the user's tour interests, such as the user's historical tour records, currently visited attraction types, and user-defined points of interest. Current movement speed refers to the user's current walking speed between attractions, which can be obtained through user reporting or automatically determined by collecting the user's movement distance and time.

[0043] It should be noted that the user's current tour data can be updated once every first time interval, and the scenic area's current environmental data can be updated once every second time interval. The first time interval can be 30 seconds, and the second time interval can be 5 minutes. Based on the updated current tour data and current environmental data, the following steps S120-S160 are re-executed to achieve dynamic perception of spatiotemporal data and dynamic determination of the tour path.

[0044] S120. Based on the current remaining tour time and current status data, determine the user profile information.

[0045] Specifically, based on the user's current remaining browsing time and current status data, quantitative or tagging processing is performed to dynamically construct a specific user profile, thereby obtaining accurate user profile information.

[0046] For example, user profile information may include: core preference tags, physical condition parameters, and time sensitivity. Core preference tags can characterize the types of attractions a user prefers to visit. For example, core preference tags may include: "historical culture," "natural scenery," and "parent-child interaction," etc. Physical condition parameters can characterize the user's physical condition while visiting the attraction. For example, physical condition parameters may be "low," "moderate," or "high." Time sensitivity can characterize the user's available time while visiting the attraction. For example, time sensitivity may be "efficient," "regular," or "leisurely." Different time sensitivities can correspond to different needs regarding the tightness of the itinerary.

[0047] In some optional implementations, step S120 may include: determining the user's core preference tags based on the user's browsing interest feature data; determining the user's physical condition parameter information based on the user's current movement speed and / or current browsing time; and determining the user's time sensitivity based on the current remaining browsing time.

[0048] Specifically, the system analyzes users' browsing interest data to determine their core preference tags. For example, it analyzes users' historical browsing records (such as the descriptions of attractions they clicked on), the types of attractions they have currently visited (such as the lengthy stays they have made at several historical sites), and the points of interest they have actively set (such as collecting attractions related to "ancient architecture"). Through preset tag matching rules or classification models (such as keyword-based or attraction category statistics), the system dynamically assigns users core preference tags such as "historical culture," "natural scenery," or "leisure and entertainment."

[0049] The user's stamina status parameters can be determined solely based on their current movement speed. For example, if the current movement speed is less than or equal to a first preset speed, the user's stamina status parameter is determined to be "low"; if the current movement speed is greater than the first preset speed but less than or equal to a second preset speed, the user's stamina status parameter is determined to be "medium"; and if the current movement speed is greater than the second preset speed, the user's stamina status parameter is determined to be "high". Alternatively, the user's stamina status parameters can be determined solely based on their current browsing time. For example, if the current browsing time is less than or equal to a first preset time, the user's stamina status parameter is determined to be "low"; if the current browsing time is greater than the first preset time but less than or equal to a second preset time, the user's stamina status parameter is determined to be "medium"; and if the current browsing time is greater than the second preset time, the user's stamina status parameter is determined to be "high". It can also determine the user's physical condition parameters based on the user's current movement speed and current browsing time. For example, if the current movement speed is less than the preset speed and the current browsing time is greater than the preset time, the user's physical condition parameters are determined to be "low". If the current movement speed is greater than the preset speed or the current browsing time is less than the preset time, the user's physical condition parameters are determined to be "high".

[0050] The user's time sensitivity can also be determined based on the user's current remaining tour time. For example, if the current remaining tour time is less than or equal to the first preset time, the user's physical condition parameter information is determined to be "high efficiency". If the current remaining tour time is greater than the first preset time and less than or equal to the second preset time, the user's physical condition parameter information is determined to be "normal". If the current remaining tour time is greater than the second preset time, the user's physical condition parameter information is determined to be "leisure".

[0051] S130. Based on the current environmental data, determine the current visitor experience value for each attraction in the scenic area.

[0052] The current visit experience value of a scenic spot can be used to characterize the actual experience of visiting that spot. The higher the current visit experience value, the better the experience of visiting that spot.

[0053] Specifically, by analyzing the current environmental data of each attraction within the scenic area, the current visitor experience value for each attraction is quantitatively calculated. For instance, lower visitor density and more suitable weather conditions result in a higher visitor experience value. For a historical and cultural attraction, if the environmental data shows sunny weather, fewer visitors, and recent renovations leading to better visibility, the current visitor experience value will be higher. Conversely, for a water-based attraction, if the data indicates low temperatures, potentially leading to a poor visitor experience, the current visitor experience value will decrease. Furthermore, well-developed surrounding facilities, such as ample dining and rest areas, also enhance the visitor experience value. Traffic conditions within the scenic area also affect the visitor experience value. Smooth roads allow for quick and convenient access, increasing the experience value; conversely, congested roads and long travel times reduce it. Additionally, opening hours are also considered; an attraction about to close will significantly diminish its current visitor experience value. By comprehensively analyzing the environmental data of these scenic spots, the current visitor experience value of each attraction can be accurately determined in real time.

[0054] S140. Based on user profile information and current tour experience value, determine multiple candidate attractions for the user, and based on the current user location and multiple candidate attractions, determine multiple candidate tour routes for the user.

[0055] Among them, the candidate attractions can refer to attractions within the scenic area that match the user and offer a better tour experience. The candidate tour route can refer to a tour route composed of the current user's location and all candidate attractions.

[0056] Specifically, based on user profile information and the current visit experience value of each attraction, all candidate attractions within the scenic area that the user wants to visit and that offer the best visit experience can be identified. Using the current user location as the starting point of the tour path, each candidate attraction is treated as an attraction the user needs to visit. All candidate attractions are enumerated and sorted, and each sorting combination is considered a candidate tour path, thus obtaining all selectable tour paths. For example, if the current user location is A, and there are three candidate attractions B, C, and D, then the identified candidate tour paths include ABCD and ACBD, etc.

[0057] In some optional implementations, step S140, "determining multiple candidate attractions for the user based on user profile information and current tour experience value", may include: selecting attractions that match the core preference tags and attraction types in the user profile information as the user's preferred attractions; and determining multiple candidate attractions for the user from the preferred attractions based on the current tour experience value of the preferred attractions.

[0058] Specifically, the attraction type of each scenic spot in the area can be obtained from the environmental database, such as historical and cultural, or natural. Based on the core preference tags in the user profile information and the attraction type of each spot, attractions that match the core preference tags with the attraction type are identified as the user's preferred attractions. The current visit experience value of each preferred attraction is compared with the preset visit experience value, and those attractions with a higher preset visit experience value are identified as candidate attractions, thus obtaining all candidate attractions that the user prefers and that offer a better visit experience. For example, for a user whose core preference tag is "historical and cultural," the identified candidate attractions include ancient temples and museums.

[0059] In some optional implementations, step S140, "determining multiple candidate tour routes for the user based on the current user location and multiple candidate attractions", may include: taking the current user location as the starting point of the tour route, sorting and combining the multiple candidate attractions, and taking each sorting and combination result as a candidate tour route for the user.

[0060] Starting from the current user's location, the system enumerates and sorts all potential attractions, treating each sorted combination as a potential tour path, thus obtaining all selectable tour paths. For example, if the current user's location is A, and there are three potential attractions B, C, and D, then the determined potential tour paths include ABCD and ACBD, etc.

[0061] S150. Based on the current environmental data and user profile information, determine the total cost and total time spent on each candidate tour route.

[0062] The total cost of a proposed tour route can refer to the total cost incurred by a user in following that route, which can be used to characterize the ease of the tour. For example, a lower total cost indicates a more comfortable tour. The total time required for a proposed tour route can refer to the total time needed for a user to follow that route.

[0063] Specifically, for each candidate tour route, a tour cost analysis is performed based on current environmental data and user profile information to determine the tour cost between each adjacent node in the candidate tour route. All tour costs are then summed to obtain the total tour cost for the candidate tour route. Similarly, a tour time analysis is performed based on current environmental data and user profile information to determine the current travel time between each pair of adjacent candidate attractions in the candidate tour route, as well as the current queue time and suggested tour time for each candidate attraction. All current travel times, current queue times, and suggested tour times are then summed to obtain the total tour time for the candidate tour route.

[0064] S160. Based on the total tour cost, total tour time, and current remaining tour time, determine the user's target tour path.

[0065] The target tour path refers to the final tour path recommended to the user. There can be one or more target tour paths; for example, two target tour paths can be determined so that two target tour paths can be recommended to the user at once, allowing the user to choose.

[0066] Specifically, the goal is to minimize the cost of the tour within the remaining tour time. A target tour route matching the user is determined from all candidate routes. For example, the total tour time for each candidate route is compared with the remaining tour time to obtain candidate routes whose total tour time is less than or equal to the remaining tour time. The user's target tour route is then determined based on the total cost of each candidate route. For example, all candidate routes are arranged in ascending order of total cost, and the first preset number of ranked candidate routes are used as the target tour route. For instance, the first ranked candidate route or the first two ranked candidate routes are used as the target tour route. By planning tour routes based on spatiotemporal data such as the user's current tour data and the scenic area's current environmental data, accurate route recommendations are achieved through a three-dimensional synergy of "spatiotemporal-user-environment," ensuring that the planned tour route closely matches the actual situation. For example, during peak tourist seasons, queue times at popular attractions may change at any time. This embodiment can obtain this information in a timely manner to plan a tour route that avoids peak times and ensures efficient travel for the user.

[0067] The technical solution of this embodiment obtains dynamic spatiotemporal data by acquiring the user's current tour data and the scenic area's current environmental data. Based on the remaining tour time and current status data in the current tour data, it determines the user's profile information to dynamically construct the user profile. Based on the current environmental data, it determines the current tour experience value of each attraction in the scenic area to dynamically measure the impact of the scenic area's environment on the tour experience. Based on the user profile information and the current tour experience value, it determines multiple candidate attractions for the user, and based on the current user location and multiple candidate attractions, it determines multiple candidate tour routes for the user. Based on the current environmental data and user profile information, it determines the total tour cost and total tour time corresponding to each candidate tour route. Based on the total tour cost, total tour time, and the remaining tour time, it determines a target tour route that matches the user. This achieves dynamic and intelligent determination of scenic area tour routes, improving the feasibility and flexibility of tour routes, as well as the matching degree between tour routes and users, thereby improving the user's tour experience.

[0068] In some optional implementations, after step S160, the following may be included: displaying the target tour path and the target attraction information corresponding to each target attraction in the target tour path on the user's terminal interface.

[0069] The target attraction information includes: the name of the target attraction, its current visit experience value, current queue time, and recommended visit duration. The user's terminal interface can refer to the interface of a scenic area application installed on the user's terminal, a public WeChat account interface, or the interface of interactive terminal devices within the scenic area. For example, the target tour route and the corresponding target attraction information for each target attraction along the route can be displayed on a map within the scenic area application interface. This could involve using different colors to mark different target tour routes, and simultaneously marking the name, current visit experience value, current queue time, and recommended visit duration of each target attraction along the route on the map. This allows users to more intuitively and conveniently view the recommended target tour route information, further improving the user's tour experience. This embodiment can also provide users with a voice guide function; for example, users can click on the attraction icon to hear a detailed introduction and travel suggestions for that attraction.

[0070] In some alternative implementations, the method may also include at least one of the following:

[0071] If it is detected that the user's actual tour path deviates from the target tour path, or if the current environmental data of the scenic area changes abruptly, the user's current tour data and the current environmental data of the scenic area will be reacquired to update the determined target tour path.

[0072] Every preset time interval or every preset distance the user moves, the system re-acquires the user's current tour data and the scenic area's current environmental data to update the determined target tour path;

[0073] Based on user feedback on the displayed target tour path, the target tour path is redefined.

[0074] Specifically, during a user's visit to a scenic area, the system can detect in real time whether the user's actual tour path deviates from the recommended target tour path. If so, a path replanning operation is triggered. At this time, the user's current tour data and the scenic area's current environmental data are reacquired, and based on the reacquired data, steps S120-S160 are executed again to determine the latest target tour path, thus updating and displaying the target tour path. Furthermore, the system can monitor changes in real-time environmental data within the scenic area, such as visitor flow, queue times, and weather. If the queue time at a particular attraction suddenly increases, or if weather changes affect the visitor experience at certain attractions, steps S110-S160 will also be executed again to determine the latest target tour path, thus updating and displaying the target tour path.

[0075] Every preset time interval or every preset distance the user moves, such as every 15 minutes or when the user moves more than 500 meters, the current user location and remaining tour time can be automatically updated, and the above steps S110-S160 can be re-executed to redetermine the latest target tour path, thereby realizing the updated display of the target tour path.

[0076] Furthermore, users can provide feedback on the recommended tour routes and attractions via the terminal interface. For example, users can express satisfaction or dissatisfaction with a particular tour route, or raise questions or suggestions about specific attractions. The tour routes are dynamically adjusted based on user feedback. For instance, if a user is dissatisfied with a route, the reasons for dissatisfaction are analyzed, such as an overly long route or duplicate attractions, and the route is replanned. If a user reports too many duplicate attractions on a route, the recommendations for similar attractions are reduced, the selection of other types of attractions is increased, and a new tour route is generated. By continuously adjusting the tour routes based on user feedback and changes in real-time environmental data of the scenic area, more personalized and real-time guided tour services can be provided, enhancing the user's tour experience.

[0077] Figure 2 This is a flowchart illustrating another method for determining a scenic area tour route according to an embodiment of the present invention. Based on the above embodiments, this embodiment describes in detail the process of determining the current tour experience value of each attraction in the scenic area. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0078] See Figure 2 The alternative method for determining a scenic area tour route provided in this embodiment specifically includes the following steps:

[0079] S210. Obtain the user's current tour data and the scenic area's current environment data, wherein the current tour data includes the user's current location, current remaining tour time, and current status data.

[0080] S220. Based on the current remaining tour duration and current status data, determine the user's profile information.

[0081] S230. For each attraction in the scenic area, based on the current environmental data of the attraction, determine the corresponding visitor flow suitability, weather suitability, supporting facility completeness, traffic flow, and opening time suitability.

[0082] Among them, visitor flow suitability is used to quantitatively describe the suitability of the attraction for visitor flow. Weather suitability is used to quantitatively describe the suitability of the attraction for weather conditions. Supporting facilities completeness is used to quantitatively describe the completeness of the attraction's facilities. Traffic flow is used to quantitatively describe the traffic flow at the attraction. Opening hours suitability is used to quantitatively describe the suitability of the attraction's opening hours.

[0083] Specifically, for each attraction in the scenic area, quantitative calculations are performed based on the current environmental data of the attraction across six dimensions: visitor flow, weather, supporting facilities, traffic, and opening hours. This yields the attraction's suitability for visitor flow, weather, supporting facilities, traffic flow, and opening hours.

[0084] In some optional implementations, step S230 may include: determining the visitor flow suitability of the attraction based on the current visitor flow density and the preset visitor flow density of the attraction; determining the weather suitability of the attraction based on the current weather information and the suitable weather information of the attraction; determining the completeness of the supporting facilities of the attraction based on the supporting facility information of the attraction; determining the traffic flow of the attraction based on the road congestion information leading to the attraction; and determining the opening time suitability of the attraction based on the closing time of the attraction and the current time.

[0085] Specifically, for each attraction within the scenic area, the ratio of its current visitor density to its preset carrying capacity is defined as its visitor flow suitability. The closer this ratio is to 1, the higher the suitability. The preset carrying capacity refers to the optimal visitor flow density for that attraction. Suitable weather information for the attraction can be pre-set, including the weather suitability for each type of weather. For example, for outdoor scenic spots, the weather suitability is 0.8 on sunny days and 0.3 on rainy days. The weather suitability is determined by matching the current weather information of the scenic area with the suitable weather information for the attraction. The completeness of the supporting facilities at the attraction can be determined in real-time based on their quantity and quality, or it can be pre-determined and stored based on the quantity and quality of surrounding restaurants, rest areas, and other supporting facilities. This stored completeness information can then be directly obtained during practical applications. Traffic flowability can be assessed based on road congestion information leading to attractions to obtain a congestion coefficient, and traffic flowability can be determined based on this coefficient; for example, the lower the congestion coefficient, the higher the traffic flowability. Opening time suitability can be determined based on the time remaining until the attraction's closing time; for example, the closer the current time is to the attraction's closing time, the lower the opening time suitability.

[0086] S240. Based on the suitability of visitor flow, weather, supporting facilities, traffic flow, and opening hours, determine the current visitor experience value of the attraction.

[0087] Specifically, the current visitor experience value of a scenic spot is obtained by integrating factors such as visitor flow suitability, weather suitability, completeness of supporting facilities, traffic flow, and opening hours suitability. A comprehensive evaluation of the visitor experience across six dimensions—visitor flow, weather, supporting facilities, traffic, and opening hours—allows for a more accurate assessment of the current visitor experience value.

[0088] In some optional implementations, step S240 may include: weighting and summing the crowd flow adaptability, weather adaptability, supporting facility completeness, and traffic flow to obtain a reference visitor experience value for the attraction; multiplying the reference visitor experience value for the attraction by the opening time adaptability, and using the multiplication result as the current visitor experience value for the attraction.

[0089] Specifically, the factors influencing visitor flow, weather, supporting facilities, and traffic are weighted and summed to evaluate visitor flow suitability, weather suitability, supporting facility completeness, and traffic flow smoothness. The weighted sum is then used as the reference visitor experience value for the attraction. The factors influencing visitor flow, weather, supporting facilities, and traffic can be adjusted in advance based on actual conditions to highlight the different levels of influence of each factor on the visitor experience; their sum is 1. Since opening time suitability significantly impacts the overall visitor experience, it can be directly used as an influencing factor. The reference visitor experience value is multiplied by the opening time suitability, and the result is used as the final current visitor experience value for the attraction. Through comprehensive analysis of scenic area environmental data, the current visitor experience value for each attraction can be accurately determined.

[0090] S250. Based on user profile information and current tour experience value, determine multiple candidate attractions for the user, and based on the current user location and multiple candidate attractions, determine multiple candidate tour routes for the user.

[0091] S260. Based on the current environmental data and user profile information, determine the total cost and total time spent on each candidate tour route.

[0092] S270. Based on the total tour cost, total tour time, and current remaining tour time, determine the user's target tour path.

[0093] The technical solution of this embodiment determines the suitability of each scenic spot in the scenic area for visitor flow, weather, supporting facilities, traffic flow, and opening hours based on the current environmental data of that scenic spot. Based on these factors, the current visitor experience value of the scenic spot is determined. This fully considers the impact of environmental factors on the visitor experience, more accurately measures the current visitor experience value of each scenic spot in the scenic area, and further improves the feasibility of the tour route.

[0094] Figure 3 This is a flowchart illustrating another method for determining a scenic tour route according to an embodiment of the present invention. Based on the above embodiments, this embodiment describes in detail the process of determining the total tour cost and total tour time corresponding to each candidate tour route. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0095] See Figure 3 The alternative method for determining a scenic area tour route provided in this embodiment specifically includes the following steps:

[0096] S310. Obtain the user's current tour data and the scenic area's current environment data, wherein the current tour data includes the user's current location, current remaining tour time, and current status data.

[0097] S320. Based on the current remaining tour duration and current status data, determine the user's profile information.

[0098] S330. Based on the current environmental data, determine the current visitor experience value for each attraction in the scenic area.

[0099] S340. Based on user profile information and current tour experience value, determine multiple candidate attractions for the user, and based on the current user location and multiple candidate attractions, determine multiple candidate tour routes for the user.

[0100] S350. Based on the current environmental data, determine the distance to each candidate attraction in each candidate tour route, and determine the total tour cost for each candidate tour route based on the distance to the attraction.

[0101] The reach distance for a candidate attraction refers to the distance from the previous candidate attraction to the current candidate attraction within the candidate tour route. If the candidate attraction is the first candidate attraction in the candidate tour route, then the reach distance refers to the distance from the current user's location to that candidate attraction.

[0102] Specifically, for each candidate tour route, based on the current environmental data, the distance between every two adjacent nodes in the candidate tour route is determined, thereby obtaining the arrival distance corresponding to each candidate attraction in the candidate tour route. The arrival distance corresponding to the candidate attraction can be directly used as the tour cost of the candidate attraction. Therefore, the arrival distances corresponding to all candidate attractions in the candidate tour route are added together, and the sum is used as the total tour cost corresponding to the candidate tour route.

[0103] In some optional implementations, step S350, "determining the total tour cost corresponding to each candidate tour route based on the arrival distance," may include: determining the time penalty factor corresponding to each candidate attraction based on the current environmental data, and determining the interest decay factor corresponding to each candidate attraction based on the attractions already visited by the user; and determining the total tour cost corresponding to each candidate tour route based on the arrival distance, the time penalty factor, and the interest decay factor.

[0104] The time penalty factor for the candidate attractions can be the increased time cost due to large crowds and long queues. The interest decay factor for the candidate attractions can be the reduced interest value due to users having already visited similar attractions.

[0105] Specifically, for each candidate attraction in each candidate tour route, the weighted sum of the reach distance, time penalty factor, and interest decay factor corresponding to that attraction can be used as the tour cost of that attraction. For example, f(n) = g(n) + αt(n) + βi(n), where f(n) is the tour cost of the nth candidate attraction, g(n) is the reach distance of the nth candidate attraction, t(n) and i(n) are the time penalty factor and interest decay factor corresponding to the nth candidate attraction, respectively, and α and β are the coefficients of the time penalty factor and the interest decay factor, respectively. The tour costs corresponding to all candidate attractions in the candidate tour route are summed, and the sum is used as the total tour cost of the candidate tour route. This embodiment not only considers the reach distance but also incorporates the time penalty factor and interest decay factor, thereby more accurately determining the total tour cost corresponding to each candidate tour route.

[0106] In some optional implementations, determining the time penalty factor for each candidate attraction based on current environmental data and the interest decay factor for each candidate attraction based on the user's already visited attractions may include: determining the current queue time and current crowd density for each candidate attraction based on current environmental data, and determining the time penalty factor for each candidate attraction based on the current queue time, current crowd density, preset queue time, and preset crowd density; determining the number of similar already visited attractions for each candidate attraction based on the attraction type of each candidate attraction and the attraction type of the user's already visited attractions, and determining the interest decay factor for each candidate attraction based on the number of similar already visited attractions.

[0107] The preset queuing time can be a pre-set baseline queuing time, which can be obtained statistically based on historical data of the scenic area. The preset crowd density can refer to the optimal crowd density that the scenic spot can handle. The type of scenic spot visited by the user can be determined based on the user's historical visit records within the current scenic area. These historical visit records can be obtained from the user's historical behavior database, which can be collected and reported by the scenic area application when the user uses the application.

[0108] Specifically, for each candidate attraction within a chosen tour route, the current queue length and current crowd density are determined based on current environmental data. A first ratio between the current queue length and a preset queue length, and a second ratio between the current crowd density and a preset crowd density, are also determined. These first and second ratios are then weighted and summed to obtain the time penalty factor for that candidate attraction. For example, the time penalty factor = queue length coefficient × (1 + first ratio) + crowd density coefficient × second ratio, where the queue length coefficient and crowd density coefficient are pre-determined adjustment weights based on actual conditions. By determining the time penalty factor, real-time environmental resistance can be quantified as an additional cost for path searching.

[0109] Based on a user's historical visit history within the current scenic area, the types of attractions the user has visited can be determined, thus obtaining the attraction types of the attractions the user has visited. The attraction type of the candidate attraction is then matched with the attraction types of the attractions the user has already visited to determine the number of similar visited attractions corresponding to the candidate attraction. An exponential decay can be applied based on the number of similar visited attractions to obtain the interest decay factor for the candidate attraction. For example, the interest decay factor = γ^(number of similar visited attractions), where γ is the decay rate (0 < γ < 1). For each additional similar visited attraction the user adds, the interest decay factor decreases exponentially, thereby reducing the priority of duplicate attraction types in route planning.

[0110] In some alternative implementations, the time penalty factor can also be adjusted based on road congestion information leading to candidate attractions. For example, when a user needs to travel from their current location to a candidate attraction, the congestion coefficient is determined based on the road congestion information leading to that attraction, and the time penalty factor is updated accordingly to obtain the updated time penalty factor. For instance, a higher congestion coefficient results in a larger time penalty factor, increasing the total cost of the path and thus reducing its likelihood of being selected later.

[0111] In some alternative implementations, the interest decay factor can also be adjusted based on the distance or time required to reach the candidate attraction. For example, the higher the distance or time required to reach the candidate attraction, the lower its attractiveness, and the interest decay factor is appropriately increased to increase the total cost of the path, thereby reducing the likelihood of it being selected subsequently.

[0112] S360: Based on the current environmental data, user profile information, and current movement speed in the current status data, determine the current movement time between candidate attractions, the current queuing time for each candidate attraction, and the recommended visit time.

[0113] The current travel time between candidate attractions refers to the time required for a user to move from one candidate attraction to another. The current queue time for a candidate attraction refers to the queuing time required to visit that attraction. The suggested visit time refers to the recommended visit duration for the user. Specifically, by analyzing current environmental data, user profile information, and current travel speed, the current travel time between each pair of candidate attractions, as well as the current queue time and suggested visit time for each candidate attraction, are determined.

[0114] In some optional implementations, step S360 may include: determining the current travel time between candidate attractions and the current queuing time for each candidate attraction based on the current movement speed in the current environmental data and current state data; determining a physical fitness adjustment factor based on physical fitness parameters in the user profile information, and determining a time compression factor based on time sensitivity in the user profile information; and adjusting the preset tour duration for each candidate attraction based on the physical fitness adjustment factor and the time compression factor to obtain a suggested tour duration for each candidate attraction.

[0115] The physical exertion adjustment factor reflects the positive or negative impact of a user's physical strength on the tour duration. For example, a physical exertion adjustment factor greater than 1 indicates that the user is physically strong, and the tour duration can be increased. The time compression factor reflects the user's preference for time pressure. The preset tour duration for candidate attractions can be the default tour duration set in advance.

[0116] Specifically, the current travel time between each pair of candidate attractions can be determined based on the distance between them and the user's current movement speed. The current queue length for each candidate attraction is determined based on the current number of people in the queue. Physical fitness parameters in the user profile are mapped to physical fitness values ​​to obtain a physical fitness adjustment factor. For example, "low" physical fitness parameter is mapped to a physical fitness adjustment factor of 0.8, "medium" to 1.0, and "high" to 1.2. Similarly, time sensitivity in the user profile is mapped to time values ​​to obtain a time compression factor. For example, "high efficiency" time sensitivity is mapped to a time compression factor of 0.7, "normal" to 0.9, and "leisurely" to 1.1. After determining the user's physical fitness adjustment factor and time compression factor, the preset tour duration for each candidate attraction is multiplied by the physical fitness adjustment factor and time compression factor, and the result is used as the corresponding suggested tour duration. The predetermined suggested tour duration can accommodate both physical limitations and time efficiency requirements. By dynamically adjusting the preset tour duration for each candidate attraction, a more suitable suggested tour duration can be obtained for the user.

[0117] For example, taking the candidate attraction "Ancient Temple" as an example, if the user's physical condition parameter is "High" and their time sensitivity is "Leisurely," it means the user has ample energy and is not pursuing an efficient tour. In this case, the suggested tour time for the "Ancient Temple" can be appropriately extended beyond the preset tour time. For instance, if the preset tour time for the "Ancient Temple" is 1 hour, considering the user's situation, the suggested tour time can be extended to 1.5 hours, allowing the user more time to appreciate the temple's architectural style, historical culture, and tranquil atmosphere. If the user's physical condition parameter is "Low" and their time sensitivity is "Highly Efficient," it means the user has limited energy and hopes to have a good tour experience in a shorter time. In this case, the suggested tour time for the "Ancient Temple" needs to be shortened. For example, the suggested tour time can be adjusted to 45 minutes, ensuring that the user can get a general understanding of the temple's main features without excessively expending energy.

[0118] S370. Based on the current travel time, current queue time, and suggested tour time between the candidate attractions in each candidate tour route, determine the total tour time corresponding to each candidate tour route.

[0119] Specifically, for each candidate tour route, the current travel time between every two adjacent candidate attractions is added together to obtain the total travel time; the current queue time for each candidate attraction in the candidate tour route is added together to obtain the total queue time; and the suggested tour time for each candidate attraction in the candidate tour route is added together to obtain the total tour time. The total travel time, total queue time, and total tour time are then added together to obtain the total tour time for that candidate tour route.

[0120] S380. Based on the total tour cost, total tour time, and current remaining tour time, determine the user's target tour path.

[0121] The technical solution of this embodiment determines the reach distance to each candidate attraction in each candidate tour route based on current environmental data, and then determines the total tour cost for each candidate tour route based on the reach distance, thereby achieving an accurate estimate of the total tour cost. By determining the current travel time between candidate attractions, the current queue time for each candidate attraction, and the suggested tour time based on current environmental data, user profile information, and the current movement speed in current status data, the solution determines the total tour time for each candidate tour route. This achieves an accurate estimate of the total tour time, making the determined tour route more compatible with the user and improving the user experience.

[0122] Figure 4This is a flowchart illustrating another method for determining a scenic tour route according to an embodiment of the present invention. This embodiment, based on the above embodiments, provides a detailed description of the process for determining the user's target tour route. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0123] See Figure 4 The alternative method for determining a scenic area tour route provided in this embodiment specifically includes the following steps:

[0124] S410. Obtain the user's current tour data and the scenic area's current environment data, wherein the current tour data includes the user's current location, current remaining tour time, and current status data.

[0125] S420. Based on the current remaining tour duration and current status data, determine the user profile information.

[0126] S430. Based on the current environmental data, determine the current visitor experience value for each attraction in the scenic area.

[0127] S440. Based on user profile information and current tour experience value, determine multiple candidate attractions for the user, and based on the current user location and multiple candidate attractions, determine multiple candidate tour routes for the user.

[0128] S450. Based on the current environmental data and user profile information, determine the total cost and total time spent on each candidate tour route.

[0129] S460. Based on the total tour cost, determine a preset number of first tour paths from the candidate tour paths, and detect whether the total tour time corresponding to the first tour path is greater than the current remaining tour time, so as to obtain a second tour path that is greater than the current remaining tour time and a third tour path that is less than or equal to the current remaining tour time.

[0130] The first tour route is the candidate tour route with the lowest total tour cost. The second tour route is the first tour route whose total tour time is greater than the current remaining tour time. The third tour route is the first tour route whose total tour time is less than or equal to the current remaining tour time.

[0131] Specifically, based on the total cost of each candidate tour route, all candidate tour routes are arranged in ascending order of total cost. The first preset number of candidate tour routes are then designated as the first tour routes, for example, the first two candidate tour routes are designated as the first tour routes. It is then checked whether the total tour time for each first tour route is greater than the current remaining tour time to determine whether the estimated queuing time and suggested tour time for each first tour route are appropriate. This allows all first tour routes to be divided into second tour routes (inappropriate for the time limit) and third tour routes (appropriate for the time limit).

[0132] S470. Compress the current queuing time and suggested tour time for each candidate attraction in the second tour route so that the total tour time for the compressed second tour route is less than or equal to the current remaining tour time.

[0133] Specifically, since the total time spent on the second tour route is greater than the current remaining tour time, it is necessary to compress the current queuing time and suggested tour time for each candidate attraction in the second tour route. For example, based on the difference between the total time spent on the second tour route and the current remaining tour time, the current queuing time and suggested tour time for each candidate attraction are compressed proportionally so that the total time spent on the compressed second tour route is less than or equal to the current remaining tour time.

[0134] In some optional implementations, step S470 may include: determining the total time compression duration corresponding to the second tour path; determining the tag matching degree corresponding to each candidate attraction in the second tour path based on the core preference tags in the user profile information, and determining the attraction time compression duration corresponding to each candidate attraction in the second tour path based on the tag matching degree and the total time compression duration; and compressing the current queuing time and suggested tour time corresponding to each candidate attraction in the second tour path based on the attraction time compression duration corresponding to each candidate attraction in the second tour path to obtain the compressed current queuing time and suggested tour time.

[0135] One approach is to determine the total time compression period for the second tour route by comparing the total tour time with the remaining tour time. A pre-established mapping between each core preference tag and each attraction within the scenic area can be built. For example, the core preference tag "history and culture" has a 0.9 match with the attraction "ancient temple," and the core preference tag "history and culture" has a 0.7 match with the attraction "museum." Based on this mapping, the matching degree of the core preference tags in the user profile information and each candidate attraction in the second tour route is queried to obtain the matching degree between the core preference tags in the user profile information and each candidate attraction in the second tour route—that is, the tag matching degree corresponding to each candidate attraction in the second tour route. Since a higher tag matching degree requires a smaller compression ratio, the inverse ratio of the tag matching degree corresponding to each candidate attraction can be used as the time compression ratio between each candidate attraction. Based on the time compression ratio and the total time compression period, the time compression period for each candidate attraction in the second tour route is determined. For each candidate attraction in the second tour route, based on the time compression period corresponding to the attraction, the current queuing time and suggested tour time corresponding to each candidate attraction in the second tour route are compressed accordingly, so that the total time reduction is equal to the time compression period corresponding to the candidate attraction, thereby making the total tour time of the compressed second tour route less than or equal to the current remaining tour time.

[0136] As another implementation, a total time compression ratio can be preset. The total tour time corresponding to the second tour route is multiplied by this total time compression ratio to obtain the total time compression duration for the second tour route. Based on the tag matching degree and total time compression duration for each candidate attraction in the second tour route, the time compression duration for each candidate attraction in the second tour route is determined. For each candidate attraction in the second tour route, the current queue time and suggested tour time for each candidate attraction are compressed accordingly, so that the total time reduction equals the time compression duration for that candidate attraction. The total tour time for the second tour route is recalculated based on the compressed current queue time and suggested tour time. If the recalculated total tour time is still greater than the current remaining tour time, it is compressed again based on the total time compression ratio until the compressed total tour time for the second tour route is less than or equal to the current remaining tour time.

[0137] For example, if the total tour time for a certain second tour route "Entrance → Ancient Temple → Museum" is: 10 (time to walk from the entrance to the ancient temple) + 40 (suggested tour time for the ancient temple) + 15 (time to walk from the ancient temple to the museum) + 50 (suggested tour time for the museum) + 15 (queue time for the ancient temple) + 15 (queue time for the museum) = 145 minutes. If the current remaining tour time is 119 minutes, then the total time reduction for the second tour route is 26 minutes. The tag matching degree for "Ancient Temple" is 0.9, and the tag matching degree for "Museum" is 0.7. The compression ratio for "Ancient Temple" and "Museum" is "1 / 0.9 : 1 / 0.7", that is, "1.1; 1.4". The time reduction for the attraction corresponding to "Ancient Temple" is: 26 × (1.1 / 2.5) ≈ 11.4 minutes, and the time reduction for the attraction corresponding to "Museum" is: 26 × (1.4 / 2.5) ≈ 14.6 minutes. For the "ancient temple," a portion of the suggested 40-minute visit time can be reduced, for example, by 10 minutes, and the queuing time can be reduced by 1.4 minutes (since queuing time is difficult to reduce precisely, adjustments can be made based on the actual situation). The adjusted suggested visit time for the "ancient temple" becomes 40 - 10 = 30 minutes, and the queuing time becomes 15 - 1.4 = 13.6 minutes. For the "museum," a portion of the suggested 50-minute visit time can be reduced by 12 minutes, and the queuing time can be reduced by 2.6 minutes from the 15-minute queuing time. The adjusted suggested visit time for the "museum" becomes 50 - 12 = 38 minutes, and the queuing time becomes 15 - 2.6 = 12.4 minutes. The total time required for the compressed second tour route "Entrance → Ancient Temple → Museum" is: 10 (time to walk from the entrance to the ancient temple) + 30 (suggested tour time of the ancient temple) + 15 (time to walk from the ancient temple to the museum) + 38 (suggested tour time of the museum) + 13.6 (queue time at the ancient temple) + 12.4 (queue time at the museum) = 119 minutes, which meets the time constraint.

[0138] For example, this embodiment can also compress the suggested tour time for each candidate attraction in the second tour route based on the time compression duration of each attraction, to obtain the compressed suggested tour time. For instance, the compressed time duration of each attraction can be subtracted from the suggested tour time of each candidate attraction in the second tour route, and the result of the subtraction is the compressed suggested tour time.

[0139] S480. Determine the compressed second and third tour paths as the user's target tour paths.

[0140] Specifically, the second and third tour paths that meet the time constraints are both used as target tour paths that match the user, thus enabling dynamic and flexible determination of tour paths.

[0141] The technical solution of this embodiment compresses the current queuing time and suggested tour time for each candidate attraction in the second tour route that is longer than the current remaining tour time, so that the total tour time for the compressed second tour route is less than or equal to the current remaining tour time. This achieves fine-tuning of the tour route time and ensures the rationality of the second tour route recommendation.

[0142] The following are embodiments of the scenic area tour route determination system provided by the present invention. This system and the scenic area tour route determination methods in the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the scenic area tour route determination system, please refer to the embodiments of the above scenic area tour route determination methods.

[0143] Figure 5 This is a schematic diagram of a scenic area tour route determination system provided in an embodiment of the present invention. This embodiment is applicable to situations where a tour route matching a user is dynamically determined when the user is visiting a scenic area. Figure 5 As shown, the system specifically includes: a current data acquisition module 510, a user profile information determination module 520, a tour experience value determination module 530, a candidate tour path determination module 540, a path information determination module 550, and a target tour path determination module 560.

[0144] The system includes the following modules: a current data acquisition module 510, used to acquire the user's current tour data and the scenic area's current environmental data, wherein the current tour data includes the user's current location, current remaining tour time, and current status data; a user profile information determination module 520, used to determine the user's user profile information based on the current remaining tour time and the current status data; a tour experience value determination module 530, used to determine the current tour experience value of each attraction in the scenic area based on the current environmental data; a candidate tour route determination module 540, used to determine multiple candidate attractions for the user based on the user profile information and the current tour experience value, and to determine multiple candidate tour routes for the user based on the current user location and the multiple candidate attractions; a route information determination module 550, used to determine the total tour cost and total tour time corresponding to each candidate tour route based on the current environmental data and the user profile information; and a target tour route determination module 560, used to determine the user's target tour route based on the total tour cost, the total tour time, and the current remaining tour time.

[0145] The technical solution of this embodiment obtains dynamic spatiotemporal data by acquiring the user's current tour data and the scenic area's current environmental data. Based on the remaining tour time and current status data in the current tour data, it determines the user's profile information to dynamically construct the user profile. Based on the current environmental data, it determines the current tour experience value of each attraction in the scenic area to dynamically measure the impact of the scenic area's environment on the tour experience. Based on the user profile information and the current tour experience value, it determines multiple candidate attractions for the user, and based on the current user location and multiple candidate attractions, it determines multiple candidate tour routes for the user. Based on the current environmental data and user profile information, it determines the total tour cost and total tour time corresponding to each candidate tour route. Based on the total tour cost, total tour time, and the remaining tour time, it determines a target tour route that matches the user. This achieves dynamic and intelligent determination of scenic area tour routes, improving the feasibility and flexibility of tour routes, as well as the matching degree between tour routes and users, thereby improving the user's tour experience.

[0146] Optionally, the user profile information includes: the user's core preference tags, physical condition parameters, and time sensitivity;

[0147] The current status data includes: the user's browsing interest characteristics, current movement speed, and current browsing duration;

[0148] The user profile information determination module 520 is specifically used for:

[0149] Based on the user's browsing interest characteristics data, the user's core preference tags are determined;

[0150] Based on the user's current movement speed and / or current browsing time, determine the user's physical condition parameters;

[0151] Based on the current remaining tour time, the user's time sensitivity is determined.

[0152] Optionally, the tour experience value determination module 530 includes:

[0153] The adaptability determination unit is used to determine the adaptability of the visitor flow, weather, supporting facilities, traffic flow, and opening hours for each attraction in the scenic area based on the current environmental data of that attraction.

[0154] The visitor experience value determination unit is used to determine the current visitor experience value of the attraction based on the population flow suitability, the weather suitability, the completeness of supporting facilities, the traffic flow, and the opening time suitability.

[0155] Optionally, the fit determination unit is specifically used for:

[0156] Determine the visitor flow suitability of the attraction based on its current visitor flow density and its preset visitor flow density.

[0157] Based on the current weather information and the suitable weather information for the attraction, determine the weather suitability of the attraction;

[0158] Based on the information on the supporting facilities of the attraction, determine the completeness of the supporting facilities corresponding to the attraction;

[0159] Determine the traffic flow level of the attraction based on road congestion information leading to it;

[0160] Determine the suitability of the opening hours for the attraction based on its closing time and the current time.

[0161] Optionally, the visitor experience value determination unit is specifically used for:

[0162] The visitor experience value of the attraction is obtained by weighted summation of the population flow suitability, weather suitability, supporting facility completeness, and traffic flow.

[0163] The reference visit experience value of the attraction is multiplied by the opening time suitability, and the result is taken as the current visit experience value of the attraction.

[0164] Optionally, the candidate tour route determination module 540 is specifically used for:

[0165] The attractions that match the core preference tags and attraction types in the user profile information are taken as the user's preferred attractions;

[0166] Based on the current visit experience value of the preferred attractions, multiple candidate attractions are determined from the preferred attractions for the user.

[0167] Optionally, the candidate tour route determination module 540 is specifically used for:

[0168] Using the current user's location as the starting point of the tour route, the multiple candidate attractions are sorted and combined, and each sorting and combination result is used as a candidate tour route for the user.

[0169] Optionally, the path information determination module 550 includes:

[0170] The total tour cost determination unit is used to determine the reach distance corresponding to each candidate attraction in each candidate tour route based on the current environmental data, and to determine the total tour cost corresponding to each candidate tour route based on the reach distance;

[0171] The duration determination unit is used to determine the current travel time between candidate attractions, the current queuing time for each candidate attraction, and the suggested tour time based on the current environmental data, the user profile information, and the current movement speed in the current status data.

[0172] The total tour time determination unit is used to determine the total tour time corresponding to each candidate tour route based on the current travel time between candidate attractions in each candidate tour route, the current queuing time, and the suggested tour time.

[0173] Optionally, the total tour cost determination unit includes:

[0174] The factor determination subunit is used to determine the time penalty factor corresponding to each candidate attraction based on the current environmental data, and to determine the interest decay factor corresponding to each candidate attraction based on the attractions already visited by the user.

[0175] The total tour cost determination subunit is used to determine the total tour cost corresponding to each candidate tour path based on the arrival distance, the time penalty factor, and the interest decay factor.

[0176] Optionally, the factor determines the sub-unit, specifically for:

[0177] Based on the current environmental data, determine the current queuing time and current crowd density for each candidate attraction, and based on the current queuing time, current crowd density, preset queuing time, and preset crowd density for each candidate attraction, determine the time penalty factor for each candidate attraction.

[0178] Based on the attraction type of each candidate attraction and the attraction type of the attractions already visited by the user, the number of similar visited attractions corresponding to each candidate attraction is determined, and the interest decay factor corresponding to each candidate attraction is determined based on the number of similar visited attractions.

[0179] Optionally, the duration determination unit is specifically used for:

[0180] Based on the current movement speed in the current environment data and the current state data, determine the current movement time between candidate attractions and the current queuing time for each candidate attraction;

[0181] A physical fitness adjustment factor is determined based on the physical fitness status parameters in the user profile information, and a time compression factor is determined based on the time sensitivity in the user profile information.

[0182] Based on the physical exertion adjustment factor and the time compression factor, the preset tour duration for each candidate attraction is adjusted to obtain the suggested tour duration for each candidate attraction.

[0183] Optionally, the target tour path determination module 560 includes:

[0184] The first tour route determination unit is used to determine a preset number of first tour routes from the candidate tour routes based on the total tour cost, and to detect whether the total tour time corresponding to the first tour route is greater than the current remaining tour time, so as to obtain a second tour route that is greater than the current remaining tour time and a third tour route that is less than or equal to the current remaining tour time.

[0185] The time compression unit is used to compress the current queuing time and suggested tour time for each candidate attraction in the second tour route, so that the total tour time for the compressed second tour route is less than or equal to the current remaining tour time.

[0186] The target tour path determination unit is used to determine the compressed second tour path and the third tour path as the user's target tour path.

[0187] Optionally, the duration compression unit is specifically used for:

[0188] Based on the total tour time corresponding to the second tour route, determine the total tour time compression duration corresponding to the second tour route;

[0189] Based on the core preference tags in the user profile information, determine the tag matching degree corresponding to each candidate attraction in the second tour path, and based on the tag matching degree and the total time compression duration, determine the attraction time compression duration corresponding to each candidate attraction in the second tour path;

[0190] Based on the time compression duration of each candidate attraction in the second tour route, the current queuing time and suggested tour duration of each candidate attraction in the second tour route are compressed to obtain the compressed current queuing time and suggested tour duration.

[0191] Optionally, the device further includes:

[0192] The route information display module is used to display the target tour route and the target attraction information corresponding to each target attraction in the target tour route on the user's terminal interface after determining the user's target tour route based on the total tour cost, the total tour time and the current remaining tour time.

[0193] The target attraction information includes: the name of the target attraction, the current visit experience value, the current queue time, and the recommended visit time.

[0194] Optionally, the device further includes: a tour path adjustment module, used for at least one of the following:

[0195] If it is detected that the user's actual tour path deviates from the target tour path, or if the current environmental data of the scenic area changes abruptly, the user's current tour data and the current environmental data of the scenic area are reacquired to update the determined target tour path;

[0196] Every preset time interval or every preset distance the user moves, the user's current tour data and the scenic area's current environmental data are re-acquired to update the determined target tour path;

[0197] Based on the user's feedback on the displayed target tour path, the target tour path is redefined.

[0198] The scenic area tour route determination system provided in this embodiment of the invention can execute the scenic area tour route determination method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the scenic area tour route determination method.

[0199] It is worth noting that in the above-mentioned embodiment of the scenic area tour route determination system, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0200] Figure 6 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile systems, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing systems. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0201] like Figure 6As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0202] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0203] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various scenic area tour route determination methods and processes described above.

[0204] In some embodiments, the scenic area tour route determination method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the scenic area tour route determination method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the scenic area tour route determination method by any other suitable means (e.g., by means of firmware).

[0205] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0206] Computer programs used to implement the scenic area tour route determination method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0207] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0208] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0209] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0210] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0211] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the scenic area tour route determination method provided in any embodiment of this invention.

[0212] In the implementation of a computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​as well as conventional procedural programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0213] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0214] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining a scenic tour path, characterized by, The method comprises: obtaining current tour data of a user and current environment data of a scenic spot, wherein the current tour data comprises a current user position, a current remaining tour duration and current state data of the user; determining user portrait information of the user based on the current remaining tour duration and the current state data; determining a current tour experience value of each scenic spot in the scenic spot based on the current environment data; determining a plurality of candidate scenic spots of the user based on the user portrait information and the current tour experience value, and determining a plurality of candidate tour paths of the user based on the current user position and the plurality of candidate scenic spots; determining a total tour cost and a total tour time of each candidate tour path corresponding to the current environment data and the user portrait information; determining a target tour path of the user based on the total tour cost, the total tour time and the current remaining tour duration.

2. The method of claim 1, wherein, The user portrait information comprises a core preference label, a physical state parameter information and a time sensitivity of the user. The current state data comprises tour interest feature data, a current moving speed and a current toured duration of the user. The determination of the user portrait information based on the current remaining tour duration and the current state data comprises: determining the core preference label of the user based on the tour interest feature data of the user; determining the physical state parameter information of the user based on the current moving speed and / or the current toured duration of the user; determining the time sensitivity of the user based on the current remaining tour duration.

3. The method of claim 1, wherein, The determination of the current tour experience value of each scenic spot in the scenic spot based on the current environment data comprises: for each scenic spot in the scenic spot, determining a people flow adaptation degree, a weather adaptation degree, a supporting facility perfection degree, a traffic smoothness degree and an opening time adaptation degree corresponding to the scenic spot based on current environment data of the scenic spot; determining the current tour experience value of the scenic spot based on the people flow adaptation degree, the weather adaptation degree, the supporting facility perfection degree, the traffic smoothness degree and the opening time adaptation degree.

4. The method of claim 3, wherein, The determination of the people flow adaptation degree, the weather adaptation degree, the supporting facility perfection degree, the traffic smoothness degree and the opening time adaptation degree corresponding to the scenic spot based on the current environment data of the scenic spot comprises: determining the people flow adaptation degree corresponding to the scenic spot according to a current people flow density of the scenic spot and a preset bearing people flow density of the scenic spot; determining the weather adaptation degree corresponding to the scenic spot according to current weather information and adaptation weather information of the scenic spot; determining the supporting facility perfection degree corresponding to the scenic spot according to supporting facility information of the scenic spot; determining the traffic smoothness degree corresponding to the scenic spot according to road congestion information to the scenic spot; determining the opening time adaptation degree corresponding to the scenic spot according to a closing time of the scenic spot and a current time.

5. The method of claim 3, wherein, The determination of the current tour experience value of the scenic spot based on the people flow adaptation degree, the weather adaptation degree, the supporting facility perfection degree, the traffic smoothness degree and the opening time adaptation degree comprises: The reference tour experience value of the scenic spot is multiplied by the opening time fitness degree, and a multiplication result obtained is taken as a current tour experience value of the scenic spot. The reference tour experience value of the scenic spot is multiplied by the opening time fitness degree, and a multiplication result obtained is taken as a current tour experience value of the scenic spot.

6. The method of claim 1, wherein, The plurality of candidate scenic spots of the user are determined based on the user portrait information and the current tour experience value, including: The scenic spot matching the core preference label in the user portrait information and the scenic spot type is taken as a preferred scenic spot of the user. The plurality of candidate scenic spots of the user are determined from the preferred scenic spot according to the current tour experience value of the preferred scenic spot.

7. The method of claim 1, wherein, The plurality of candidate tour paths of the user are determined based on the current user location and the plurality of candidate scenic spots, including: The plurality of candidate scenic spots are sorted and combined with the current user location as a starting point of a tour path, and each sorting and combining result is taken as a candidate tour path of the user.

8. The method of claim 1, wherein, The total tour cost and the total tour time corresponding to each candidate tour path are determined based on the current environment data and the user portrait information, including: The arrival distance of each candidate scenic spot in each candidate tour path is determined based on the current environment data, and the total tour cost corresponding to each candidate tour path is determined based on the arrival distance; The current moving time length between candidate scenic spots, the current queuing time length of each candidate scenic spot and the recommended tour time length are determined based on the current environment data, the user portrait information and the current moving speed in the current state data; The total tour time corresponding to each candidate tour path is determined based on the current moving time length, the current queuing time length and the recommended tour time length between candidate scenic spots in each candidate tour path.

9. The method of claim 8, wherein, The total tour cost corresponding to each candidate tour path is determined based on the arrival distance, including: The time penalty factor corresponding to each candidate scenic spot is determined based on the current environment data, and the interest decay factor corresponding to each candidate scenic spot is determined based on the user's visited scenic spot; The total tour cost corresponding to each candidate tour path is determined based on the arrival distance, the time penalty factor and the interest decay factor.

10. The method of claim 9, wherein, The time penalty factor corresponding to each candidate scenic spot is determined based on the current environment data, and the interest decay factor corresponding to each candidate scenic spot is determined based on the user's visited scenic spot, including: The current queuing time length and the current crowd density corresponding to each candidate scenic spot are determined based on the current environment data, and the time penalty factor corresponding to each candidate scenic spot is determined based on the current queuing time length, the current crowd density, the preset queuing time length and the preset crowd density of each candidate scenic spot; The number of same-type visited scenic spots corresponding to each candidate scenic spot is determined based on the scenic spot type of each candidate scenic spot and the scenic spot type of the user's visited scenic spot, and the interest decay factor corresponding to each candidate scenic spot is determined based on the number of same-type visited scenic spots.

11. The method of claim 8, wherein, determine, based on the current moving speed in the current environment data and the current state data, a current moving time length between the candidate scenic spots and a current queuing time length of each candidate scenic spot; determine, based on the physical state parameter information in the user portrait information, a physical adjustment factor, and determine, based on the time sensitivity in the user portrait information, a time compression factor; adjust, based on the physical adjustment factor and the time compression factor, a preset tour time length of each candidate scenic spot to obtain a recommended tour time length of each candidate scenic spot. determine, based on the total tour cost, the total tour time length, and the current remaining tour time length, a target tour path of the user, including:

12. The method of claim 1, wherein, determine, based on the total tour cost, a preset number of first tour paths from the candidate tour paths, and detect whether the total tour time length corresponding to the first tour paths is greater than the current remaining tour time length to obtain a second tour path greater than the current remaining tour time length and a third tour path less than or equal to the current remaining tour time length; compress the current queuing time length and the recommended tour time length corresponding to each candidate scenic spot in the second tour path so that the total tour time length corresponding to the compressed second tour path is less than or equal to the current remaining tour time length; determine the compressed second tour path and the third tour path as the target tour path of the user. determine, based on the total tour time length corresponding to the second tour path, a total time compression time length corresponding to the second tour path; 13. The method of claim 12, wherein, determine, according to the core preference label in the user portrait information, a label matching degree corresponding to each candidate scenic spot in the second tour path, and based on the label matching degree and the total time compression time length, determine a scenic spot time compression time length corresponding to each candidate scenic spot in the second tour path; compress, based on the scenic spot time compression time length corresponding to each candidate scenic spot in the second tour path, the current queuing time length and the recommended tour time length corresponding to each candidate scenic spot in the second tour path to obtain a compressed current queuing time length and a recommended tour time length. After determining the target tour path of the user based on the total tour cost, the total tour time length, and the current remaining tour time length, the method further includes: display the target tour path and target scenic spot information corresponding to each target scenic spot in the target tour path on a terminal interface of the user; 14. The method of claim 1, wherein, wherein the target scenic spot information includes the name, current tour experience value, current queuing time length, and recommended tour time length of the target scenic spot. The method further includes at least one of the following: ​ 15. The method according to any one of claims 1 to 14, characterized in that, ​ If it is detected that the actual visiting path of the user deviates from the target visiting path, or the current environmental data of the scenic spot mutates, the current visiting data of the user and the current environmental data of the scenic spot are re-acquired to update the determined target visiting path; The current visiting data of the user and the current environmental data of the scenic spot are re-acquired every preset time or every preset distance moved by the user to update the determined target visiting path; The target visiting path is re-determined based on feedback information of the user on the displayed target visiting path.

16. A scenic area tour path determination system characterized by comprising: The method comprises: a current data acquisition module configured to acquire current visiting data of the user and current environmental data of the scenic spot, wherein the current visiting data comprises a current user position, a current remaining visiting time length and current state data of the user; a user portrait information determination module configured to determine user portrait information of the user based on the current remaining visiting time length and the current state data; a visiting experience value determination module configured to determine a current visiting experience value of each scenic spot in the scenic spot based on the current environmental data; a candidate visiting path determination module configured to determine a plurality of candidate scenic spots of the user based on the user portrait information and the current visiting experience value, and determine a plurality of candidate visiting paths of the user based on the current user position and the plurality of candidate scenic spots; a path information determination module configured to determine a visiting total cost and a visiting total time consumption corresponding to each candidate visiting path based on the current environmental data and the user portrait information; a target visiting path determination module configured to determine a target visiting path of the user based on the visiting total cost, the visiting total time consumption and the current remaining visiting time length.

17. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the scenic spot visiting path determination method in any one of claims 1-15.

18. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to execute the scenic spot visiting path determination method in any one of claims 1-15 when executed by the processor.

19. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the scenic spot visiting path determination method in any one of claims 1-15.

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