Scenic area tourism guide system based on artificial intelligence technology

Abstract

The invention discloses a scenic spot tourism guide system based on an artificial intelligence technology, which relates to the field of tourism management and comprises a front-end module, a data processing module, a scenic spot database, a guide route planning module and a function module. The function module is used for classifying the users in multiple dimensions according to the user labels and endowing the users with corresponding sentiment labels at the same time, generating a multi-node scenic spot touring route in combination with a scenic spot database, and dynamically adjusting the generated multi-node scenic spot touring route according to weather data and congestion marks. According to the invention, the scenic spot route conforming to the corresponding sentiment in the scenic spot is automatically planned according to the playing sentiment, so that the tourist can experience the scenic spot conforming to the own sentiment preferentially, the tourist does not need to find the playing route, and the emotional value of the scenic spot to the tourist is greatly improved; meanwhile, reasonable rest points can be arranged between adjacent scenic spots according to the physical strength level of the tourists, and the physical strength of the tourists is perfectly distributed.

Description

Technical Field

[0001] The present invention relates to the field of tourism management, and in particular to a scenic spot tourism guide system based on artificial intelligence technology. Background Art

[0002] With the development of economy, people are increasingly pursuing the quality of life, and tourism has become an important leisure activity in people's lives. With the rapid development of science and technology, smart tourism, as a cutting-edge concept, has been accepted by more and more tourism companies. In addition to the ticketing system, the scenic spot guide system is also a major breakthrough in smart tourism. While giving tourists a better travel experience, it also realizes the transparent display of scenic spot information. The scenic area guide system deeply integrates artificial intelligence, mobile Internet, Internet of Things and other technologies, allowing tourists to obtain one-to-one in-depth tour guide services through their mobile phones, meeting tourists' needs for scenic area information search, thereby improving the service quality of scenic areas and improving tourists' sightseeing experience; During our research, we found that most of the scenic spot tourism guide systems currently on the market only show people a map of the entire scenic spot after the user logs in. This is equivalent to an electronic version of the scenic spot map. People still need to find the route themselves, and they cannot visit the attractions suitable for them within a reasonable time. The efficiency is very low, and the travel experience is also very bad. Summary of the invention

[0003] The purpose of the present invention is to provide a scenic spot tourism guide system based on artificial intelligence technology. When the user logs in, he / she selects his / her own interest preferences and assigns a corresponding travel mood. Then, according to the travel mood, a scenic spot route that meets the corresponding mood is automatically planned in the scenic spot, so that the user's travel experience can be optimized, thereby solving the problems raised in the above-mentioned background technology.

[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a scenic spot tourism guide system based on artificial intelligence technology, comprising a front-end module, a data processing module, a scenic spot database, a guide route planning module and a functional module; The front-end module is provided with single-user and multi-user user entrances, and collects user information data including physical strength level and interest preference tags; The data processing module processes the user information data, classifies the users in multiple dimensions according to the user tags and assigns corresponding sentiment tags; The guided route planning module generates a multi-node scenic spot tour route based on the user's multi-dimensional classification and corresponding mood tags combined with the scenic spot database. The functional module monitors the scenic spot flow in real time, marks congested areas, and simultaneously connects to weather monitoring to dynamically adjust the generated multi-node scenic spot tour route based on weather data and congestion marks.

[0005] Preferably, the scenic area database includes a three-dimensional map of the scenic area, on which the best time and location for taking photos of each scenic spot are marked, as well as the scenic area terrain, trail length, slope, number of steps, dangerous areas, etc.

[0006] Preferably, the data processing module classifies users in multiple dimensions, including classifying users in basic dimensions according to the single or multiple person data selected by the user and the identity information data input, wherein the classification of the basic dimensions includes single tourists, couple tourists, family tourists and group tourists, and further classifying the classified basic dimensions into preference dimensions according to interest preference tags, wherein the classification of the preference dimensions includes historical and cultural categories, natural scenery categories and leisure and vacation categories.

[0007] Preferably, the attribution of the mood labels includes assigning corresponding mood labels to individual tourists according to the classification of preference dimensions, the historical and cultural category is assigned a literary mood label, the natural scenery category is assigned a natural mood label, and the leisure and vacation category is assigned a travel mood label.

[0008] Preferably, the attribution of mood labels also includes attributing romantic mood labels to couple tourists, attributing travel mood labels to family tourists, and attributing corresponding mood labels to group tourists according to the category with the most preference dimension categories among group members.

[0009] Preferably, the guided route planning module generates a multi-node scenic spot tour route, including building a preliminary tour path between various scenic spots in the scenic spot with assigned mood labels, setting corresponding rest function nodes in the tour path between two adjacent scenic spots according to the user's physical strength level, and selecting the lowest physical strength level in the classification of multiple tourists in the classification of basic dimensions.

[0010] As a preferred option, the multi-node scenic area tour route includes: The artistic route prioritizes the scenic spots with historical background and visual beauty in the scenic area according to the physical strength level, and then arranges the remaining scenic spots when the physical strength level is sufficient; The natural path gives priority to the original ecological attractions in the scenic area according to the physical strength level. The paths between adjacent attractions are given priority to mountain forest paths. If the physical strength level is sufficient, other attractions will be supplemented and arranged; The romantic path prioritizes the scenic spots with historical background and visual beauty in the scenic area according to the physical strength level. At the same time, the scenic spots with beautiful sunrise and sunset views are inserted at the corresponding time points. When the physical strength level is sufficient, the remaining scenic spots will be supplemented and arranged; The travel sentiment route arranges the historical background, visual beauty and original ecological attractions in the scenic area according to the physical fitness level.

[0011] Preferably, the functional module sends a corresponding congestion notification to the user's front-end module one scenic spot in advance in the multi-node scenic spot tour route generated by the user according to the marked congested area, asking the user whether to choose to avoid the congestion; If you choose to avoid, the function module will adjust the tour route at the previous scenic spot of the congested area, bypass the congested area and transfer to a nearby non-congested scenic spot for transfer, and then re-enter the scenic spot of the original tour route; If you choose not to avoid it, you will continue along the tour route, and at the same time add rest function nodes corresponding to the congestion situation in the tour path between the congested area and the previous attraction in the congested area.

[0012] Preferably, the functional module receives weather data in real time, adjusts the tour route in advance when it rains, guides tourists to the nearest node with rain shelter, and re-enters the tour route from the current node after the rain stops.

[0013] In summary, the beneficial effects of the present invention are: The present invention collects the user's interest preference and physical strength level data, assigns corresponding travel mood tags, and then automatically plans scenic spot routes that meet the corresponding moods in the scenic area according to the travel moods, so that tourists can experience the scenic spots that meet their own moods first, avoiding tourists from searching for travel routes while greatly improving the emotional value of the scenic spot to tourists. At the same time, reasonable rest points can be arranged between adjacent scenic spots according to the tourists' physical strength levels, perfectly allocating the tourists' physical strength and further improving the tourists' travel experience. At the same time, when congestion occurs in the scenic area, the planned tour routes can be dynamically adjusted to allow tourists to avoid congested sections. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1 This is a schematic diagram of the overall process structure of a scenic spot tourism guide system based on artificial intelligence technology in the present invention; Figure 2 A schematic diagram of assigning mood to a scenic spot tourism guide system based on artificial intelligence technology according to the present invention; Figure 3 A schematic diagram of route planning for a scenic spot tourist guide system based on artificial intelligence technology according to the present invention; Figure 4The present invention is a schematic diagram of route congestion avoidance for a scenic spot tourism guide system based on artificial intelligence technology. DETAILED DESCRIPTION

[0016] The present invention will now be further described in detail in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. These drawings are all simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic way, and therefore they only show the structures related to the present invention.

[0017] To facilitate understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0018] All features disclosed in this specification, or steps in all methods or processes disclosed, except mutually exclusive features and / or steps, can be combined in any manner.

[0019] Any feature disclosed in this specification (including any additional claims, abstract and drawings), unless otherwise stated, may be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

[0020] In the present invention, unless otherwise clearly defined and specified, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of at least two elements or the interaction relationship between at least two elements, unless otherwise clearly defined. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0021] Combine the following Figure 1-4 The present invention is described in detail. An embodiment of the present invention is as follows: a scenic spot tourism guide system based on artificial intelligence technology, including a front-end module, a data processing module, a scenic spot database, a guide route planning module and a functional module; The front-end module can be a mobile phone APP or WeChat applet, which is provided to users to log in and make reservations to enter the scenic spot. In the reservation interface, there are single-person and multi-person reservation entrances, and each tourist's identity information needs to be filled in, including name, ID number, age, gender, physical strength level and interest preferences. It should be noted that in order to facilitate information collection, physical strength level and interest preferences are respectively provided with corresponding selection options; The physical strength levels are set as high intensity (hiking enthusiasts), medium intensity (ordinary tourists), and low intensity (elderly people or children, etc.); interest preferences are set as historical and cultural, natural scenery, and leisure and vacation, for example:

[0022] After the user inputs the identity information through the front-end module, the data processing module will process the information data input by the user, classify the user in multiple dimensions according to the user tag and assign the corresponding mood tag; The data processing module receives the user data collected in the front-end module, first distinguishes whether it is a single-person or multi-person trip, and classifies it into single tourists and multi-person tourists. Among the multi-person tourists, it is automatically divided into couple tourists, family tourists and group tourists according to the filled-in tourist identity information data, thereby forming a basic dimensional classification of personnel. The multi-person 01 team in the above table, one man, one woman and one child, obviously forms a family combination, and is thus classified as a family tourist. Under the basic dimensional classification, the preference dimension is further refined according to the interest preferences filled in by the user, and the corresponding mood labels are assigned at the same time. The single-person tourist is assigned a corresponding mood label according to the classification of the preference dimension, the historical and cultural category is assigned a literary mood label, the natural scenery category is assigned a natural mood label, and the leisure and vacation category is assigned a travel mood label; In the classification of multi-person tourists, due to the different needs of multiple users, in the classification of group tourists, the corresponding mood label is assigned according to the category with the most preference dimension categories among the group members, while couple tourists are assigned the romantic mood label by default, and family tourists are assigned the travel mood label; Literary and artistic sentiment label: mainly based on history and culture, supplemented by natural environment; Natural sentiment label: centered on getting close to nature and feeling the beauty of ecology; Travel sentiment label: centered on exploring the unique culture of the scenic spot, integrating the landscapes of all components of the scenic spot; Romantic Tag: With emotional resonance as the core, it focuses on creating a warm, sweet and unique atmosphere.

[0023] refer to Figure 2 , the labels in the above table are: Single 01: Literary and artistic label, Single 02: Natural and artistic label; Multi-person 01 (family tourists): travel mood label.

[0024] After the multi-dimensional classification of users and the corresponding emotional labels are assigned, the guide route planning module generates a multi-node scenic spot tour route in combination with the scenic spot database; The scenic area database includes a three-dimensional map of the scenic area, in which the best time and location for taking photos of each scenic spot are marked, as well as the terrain of the scenic area, the length of the trail, the slope, the number of steps, dangerous areas, etc. At the same time, each scenic spot in the scenic area is marked with a corresponding category, including: Mark scenic spots with unique architectural styles and regional cultural characteristics as cultural and artistic scenes; Scenic spots that have not been overdeveloped and remain in their natural state, and scenic spots featuring original features and pure natural environments are marked as natural scenery; The scenic spots that intersect with the scenic area buildings with exquisite artificial design and unique light and shadow effects as the core are marked as visual beauties; The tour route planning module builds a preliminary tour route between various scenic spots in the scenic area according to the mood tags assigned by the user, and sets corresponding rest function nodes in the tour route between two adjacent scenic spots according to the user's physical strength level, thereby forming a multi-node scenic area tour route; For example: Single 01: Literary Tag, Medium Strength Level, Reference Figure 3 Build a literary and artistic path, arrange the scenic spots with literary and artistic scenes and visual beauty in the scenic area from near to far from the location where the user enters the scenic area, and build a preliminary tour route. If the user has a medium-intensity physical level, set two nodes with rest functions between two adjacent scenic spots. If the distance between the two scenic spots is far or the altitude is high, set one more node. If the user has sufficient physical strength, add the remaining scenic spots.

[0025] Single 02: Natural mood label, high intensity physical level Build a natural atmosphere path, arrange the original ecological scenic spots with natural scenery marks in the scenic area from near to far from the location where the user enters the scenic area, and build a preliminary tour path. For users with high-intensity physical strength, set a node with rest function between two adjacent scenic spots. If the distance between the two scenic spots is far or the altitude is high, set one more node. When the physical strength level is sufficient, add the remaining scenic spots.

[0026] Multiplayer 01 (Family Tourists): Travel mood label, with one child, and the lowest physical strength level is selected as low intensity; Build travel mood labels, arrange the original ecological scenic spots marked with literary and artistic scenes, visual beauties and natural scenes in the scenic area from near to far from the location where the user enters the scenic area, build a preliminary tour route, and set up three nodes with rest functions between two adjacent scenic spots. If the distance between two scenic spots is far or the altitude is high, set up one more node. When the physical level is sufficient, supplement and arrange the remaining scenic spots.

[0027] It should be noted that in the romantic route corresponding to couples, the selection and construction of attractions are roughly the same as that of the literary and artistic route. The difference is that attractions with beautiful sunrise and sunset views are interspersed at corresponding time points.

[0028] It is also worth mentioning that the functional module monitors the flow of people in the scenic area in real time. One solution for monitoring the flow of people is: deploy multiple Wi-Fi probe devices in the scenic area to cover the main areas. The probe devices capture the MAC addresses of tourists' devices and upload them to the background system. The background system counts the number of people and the flow direction according to the changes in the MAC addresses. The Wi-Fi probe devices detect the Wi-Fi signals (MAC addresses) emitted by mobile devices such as user mobile phones, count the number of devices in the area to estimate the flow of people, mark the congested areas, and mark the excessively congested areas as red, the generally congested areas as yellow, and the lightly congested areas as green according to the congestion situation. The functional module sends a corresponding congestion notification to the user's front-end module one scenic spot in advance in the multi-node scenic spot tour route generated by the user according to the marked congested section, asking the user whether to choose to avoid the congested section, and the user chooses whether to avoid it according to his own needs; If you choose to avoid, the function module will adjust the tour route at the previous scenic spot of the congested area, bypass the congested area and transfer to a nearby non-congested scenic spot for transfer, and then re-enter the scenic spot of the original tour route; refer to Figure 4 Taking the literary and artistic path as an example, enter from the entrance and tour along the path of "Visual Beauty 2 - Visual Beauty 1 - Literary Scene 2 - Literary Scene 1 - Visual Beauty 3 - Exit". A red congestion appears between "Literary Scene 2 - Literary Scene 1". At this time, when the user leaves the "Visual Beauty 1" scenic spot, the user can choose whether to avoid the congested section in the front-end module. When the user chooses to avoid, the path will turn from "Literary Scene 2" to "Natural Scene 2" and then to "Literary Scene 1" to bypass the congestion and return to the tour route.

[0029] If you choose not to avoid it, you will continue along the tour route, and at the same time, add a number of rest function nodes corresponding to the congestion situation in the tour path between the congested area and the previous scenic spot in the congested area; When encountering a red congestion mark, for the rest function nodes set for high-intensity physical levels, twice as many nodes are added to the tour path between the congested section and the previous attraction in the congested section. For example, when there are 2 nodes in the tour path between the congested section and the previous attraction in the congested section, the number of nodes will be increased to 6 when encountering a red congestion mark, slowing down the user's movement speed and preventing the user from entering the congested section and causing more serious congestion. It should be noted that when the congestion mark turns green midway, the subsequent added nodes will be automatically eliminated.

[0030] For rest function nodes set at a moderate physical strength level, the number of nodes is doubled in the tour path between the congested area and the previous scenic spot in the congested area; For rest function nodes set at low-intensity physical strength levels, 0.5 times more nodes are added to the tour path between the congested area and the previous scenic spot in the congested area; The users with lower physical strength levels move slower, so fewer nodes need to be added, which can most effectively delay users from entering congested areas. When they arrive at congested areas, the congestion in the area has disappeared, greatly improving the tourists' travel experience.

[0031] It is also worth mentioning that in this embodiment, the functional module is connected to the weather monitoring, receives weather data in real time, adjusts the tour route in advance when it rains, guides tourists to the nearest node with rain shelter function, and re-enters the tour route from the current node after the rain stops. The above is only a specific implementation of the invention, but the protection scope of the invention is not limited to it. Any changes or substitutions that are not conceived through creative work should be included in the protection scope of the invention. Therefore, the protection scope of the invention should be based on the protection scope defined in the claims.

Claims

1. A scenic spot tourism guide system based on artificial intelligence technology, characterized by: It includes front-end module, data processing module, scenic area database, tour route planning module and functional module; The front-end module is provided with single-user and multi-user user entrances, and collects user information data including physical strength level and interest preference tags; The data processing module processes the user information data, classifies the users in multiple dimensions according to the user tags and assigns corresponding sentiment tags; The guided route planning module generates a multi-node scenic spot tour route based on the user's multi-dimensional classification and corresponding mood tags combined with the scenic spot database. The functional module monitors the scenic spot flow in real time, marks congested areas, and simultaneously connects to weather monitoring to dynamically adjust the generated multi-node scenic spot tour route based on weather data and congestion marks.

2. The scenic area tourism guide system based on artificial intelligence technology according to claim 1 is characterized by: The scenic area database includes a three-dimensional map of the scenic area, in which the best time and location for taking photos of each scenic spot are marked, as well as the terrain of the scenic area, the length of the trail, the slope, the number of steps, dangerous areas, etc.

3. The scenic area tourism guide system based on artificial intelligence technology according to claim 1 is characterized by: The data processing module classifies users in multiple dimensions, including classifying users in basic dimensions according to the single or multiple person data selected by the user and the identity information data input, wherein the classification in basic dimensions includes single tourists, couple tourists, family tourists and group tourists, and further classifying the classified basic dimensions into preference dimensions according to interest preference tags, wherein the classification in preference dimensions includes historical and cultural categories, natural scenery categories and leisure and vacation categories.

4. The scenic area tourism guide system based on artificial intelligence technology according to claim 3 is characterized by: The attribution of the mood labels includes assigning corresponding mood labels to individual tourists according to the classification of preference dimensions, assigning literary mood labels to the historical and cultural categories, assigning natural mood labels to the natural scenery categories, and assigning travel mood labels to the leisure and vacation categories.

5. The scenic area tourism guide system based on artificial intelligence technology according to claim 4 is characterized by: The attribution of mood labels also includes attributing romantic mood labels to couple tourists, attributing travel mood labels to family tourists, and attributing corresponding mood labels to group tourists based on the category with the most preference dimensions among group members.

6. The scenic area tourism guide system based on artificial intelligence technology according to claim 5 is characterized by: The guide route planning module generates a multi-node scenic spot tour route, including building a preliminary tour path between various scenic spots in the scenic spot with the assigned mood tags, setting corresponding rest function nodes in the tour path between two adjacent scenic spots according to the user's physical strength level, and selecting the lowest physical strength level in the classification of multiple tourists in the basic dimension classification.

7. The scenic area tourism guide system based on artificial intelligence technology according to claim 6 is characterized by: The multi-node scenic area tour route includes: The literary and artistic route prioritizes the scenic spots with historical background and visual beauty in the scenic area according to the physical strength level, and then arranges the remaining scenic spots when the physical strength level is sufficient; The natural path gives priority to the original ecological attractions in the scenic area according to the physical strength level. The paths between adjacent attractions are given priority to mountain forest paths. If the physical strength level is sufficient, other attractions will be supplemented and arranged; The romantic path prioritizes the scenic spots with historical background and visual beauty in the scenic area according to the physical strength level. At the same time, the scenic spots with beautiful sunrise and sunset views are inserted at the corresponding time points. When the physical strength level is sufficient, the remaining scenic spots will be supplemented and arranged; The travel sentiment route arranges the historical background, visual beauty and original ecological attractions in the scenic area according to the physical fitness level.

8. The scenic area tourism guide system based on artificial intelligence technology according to claim 7 is characterized by: The functional module will send a corresponding congestion notification to the user's front-end module one scenic spot in advance in the multi-node scenic spot tour route generated by the user according to the marked congested area, asking the user whether to choose to avoid the congestion; If you choose to avoid, the function module will adjust the tour route at the previous scenic spot of the congested area, bypass the congested area and transfer to a nearby non-congested scenic spot for transfer, and then re-enter the scenic spot of the original tour route; If you choose not to avoid it, you will continue along the tour route, and at the same time add rest function nodes corresponding to the congestion situation in the tour path between the congested area and the previous attraction in the congested area.

9. The scenic area tourism guide system based on artificial intelligence technology according to claim 8 is characterized by: The functional module receives weather data in real time, adjusts the tour route in advance when it rains, guides tourists to the nearest node with rain shelter, and returns to the tour route from the current node for sightseeing after the rain stops.

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