A rural tourism service management system based on artificial intelligence

Abstract

The present invention relates to the field of rural tourism service management, and specifically discloses a rural tourism service management system based on artificial intelligence. The present invention collects visitor information of various scenic spots in various rural tourist attractions, analyzes popular tourist attractions and popular scenic spots in tourist attractions, which is conducive to rural tourism enterprises to formulate corresponding marketing strategies and promote the vigorous development of rural tourism; collects agricultural product sales information at sales points in various scenic spots in various rural tourist attractions, analyzes hot-selling agricultural products and the best sales points for agricultural products sold in tourist attractions, which is conducive to rural tourism enterprises to formulate corresponding management strategies, promote rural tourism consumption, and enhance the attractiveness of rural tourism; analyzes the integration degree of various scenic spots in various rural tourist attractions and agricultural products sold in the scenic spots, which is conducive to rural tourism enterprises to take corresponding measures to achieve a high integration degree between scenic spots and agricultural products sold, promote agricultural product sales, and enhance the comprehensive benefits of rural tourism.

Description

Technical Field

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

[0002] With the economic globalization and the improvement of people's living standards, more and more people are eager to pursue a simple and natural lifestyle and a pure and beautiful environment, which has promoted the rapid development of rural tourism. In the operation of rural tourism, high-quality rural tourism services play a key role, which is directly related to tourists' satisfaction and loyalty. However, with the continuous expansion of rural tourism, its management difficulty is also increasing day by day. The traditional management model is difficult to cope with the increasingly complex problems of tourists' needs, resource allocation and service quality monitoring.

[0003] Therefore, the intelligence of the rural tourism service management system is particularly important. It can use the powerful data processing, intelligent analysis and precise decision-making capabilities of artificial intelligence to achieve intelligent and efficient management of rural tourism services, thereby improving the overall quality and competitiveness of rural tourism, optimizing the tourist experience, and laying a solid foundation for the sustainable development of rural tourism.

[0004] However, the existing rural tourism service management methods still have some limitations and shortcomings in practical applications.

[0005] For example, the existing Chinese patent with publication number CN114565483A discloses a digital rural tourism service management system, which uses the market information module and the environment collection module to obtain the market stall usage information, commodity type information, planting information and environmental quality information, and uploads them to the internal private chain for storage, so as to facilitate mutual supervision between each employee node. The data judgment module is used to judge whether the stall owner or scenic spot employee uploads the information within the preset time, and timely processes it according to the judgment result to avoid the situation where the message is not updated in time. The information analysis module is used to compare and analyze the collected information with the market stall usage information and commodity type information to ensure the authenticity of the information. Tourists can initiate an update request to the cloud server through the client to remotely understand the information of the scenic spot. The technical problems of the existing digital rural tourism service management system, such as the lack of an information supervision platform, low management efficiency, frequent untimely message updates, and reduced tourists' interest in playing, are solved.

[0006] The above-mentioned patent manages rural tourism services, which improves tourists' interest in travel from the perspective of timeliness of information updates and management efficiency. It does not take into account factors such as tourists' preferences and the degree of integration between scenic spots and goods for sale to help rural tourism companies develop more effective marketing strategies and enhance tourists' experience and satisfaction. As a result, the management of rural tourism services is not perfect and cannot effectively achieve the effect of promoting the development of rural tourism. Summary of the invention

[0007] In view of the above problems, the present invention proposes a rural tourism service management system based on artificial intelligence to realize the function of rural tourism service management.

[0008] The technical solution adopted by the present invention to solve its technical problems is: the present invention provides a rural tourism service management system based on artificial intelligence, including: a tourist attraction visitor information collection module: used to record each sub-area of ​​the target village where various crops are planted for tourists to visit as each scenic spot in each tourist attraction in the target village, and collect the tourist visit information of each scenic spot in each tourist attraction in the target village during the monitoring time period, wherein the tourist visit information includes the cumulative number of visiting tourists, the average visiting time of tourists, the average flow of people, and the average passenger flow density.

[0009] Tourist attraction popularity analysis module: It is used to analyze the popularity coefficient of each attraction in each tourist attraction in the target village during the monitoring period according to the tourist visit information of each attraction in the tourist attraction in the target village during the monitoring period, obtain the popular tourist attractions in the target village during the monitoring period and the popular attractions in each tourist attraction, and provide feedback.

[0010] Agricultural product sales information collection module at tourist attractions: used to collect agricultural product sales information at sales points in each tourist attraction in the target village during the monitoring period, where the agricultural product sales information includes the cumulative sales volume of agricultural products and the average length of stay of tourists at the sales points.

[0011] Popularity analysis module for selling agricultural products: It is used to analyze the popularity coefficient of agricultural products sold at sales points in various scenic spots in various tourist attractions in the target village during the monitoring period based on the sales information of agricultural products sold at the sales points in various tourist attractions in the target village during the monitoring period, obtain the hot-selling agricultural products in the target village during the monitoring period and the best sales points for selling agricultural products in each tourist attraction, and provide feedback.

[0012] The module for evaluating the degree of integration between tourist attractions and agricultural products sold is used to analyze the degree of integration between each tourist attraction in each tourist attraction in the target village and the agricultural products sold at the sales points within each tourist attraction according to the popularity coefficient of each tourist attraction in the target village during the monitoring period, and to provide feedback.

[0013] Database: used to store scenic area maps of target villages.

[0014] On the basis of the above-mentioned embodiment, the specific working process of the tourist attraction visitor information collection module also includes: setting the duration of the monitoring time period, collecting video data of each scenic spot in each tourist scenic spot in the target village during the monitoring time period through high-definition cameras deployed in each scenic spot in each tourist scenic spot in the target village, and further obtaining the cumulative number of visitors to each scenic spot in each tourist scenic spot in the target village during the monitoring time period, and recording it as , The target village The number of the tourist attraction. , Indicates the first The number of the attraction. .

[0015] According to the video data of each scenic spot in each tourist attraction in the target village during the monitoring period, the visiting time of each tourist in each scenic spot in the target village during the monitoring period is obtained, and the average, median, mode, maximum and minimum values ​​of the visiting time of each tourist in each scenic spot in the target village during the monitoring period are further obtained, and they are recorded as , by analyzing the formula Get the average visit time of tourists to each scenic spot in each tourist attraction in the target village during the monitoring period .

[0016] On the basis of the above-mentioned embodiment, the specific working process of the tourist attraction visit information collection module also includes: dividing the monitoring time period into sampling time intervals according to the preset equal time length principle, obtaining the number of tourists passing through each scenic spot in each tourist scenic spot in the target village at each sampling time interval during the monitoring time period according to the video data of each scenic spot in each tourist scenic spot in the target village during the monitoring time period, and recording it as the flow of people at each scenic spot in each tourist scenic spot in the target village at each sampling time interval during the monitoring time period, calculating the average flow of people at each scenic spot in each tourist scenic spot in the target village at each sampling time interval during the monitoring time period, and obtaining the average flow of people at each scenic spot in each tourist scenic spot in the target village during the monitoring time period, and recording it as .

[0017] According to the preset equal time interval principle, each sampling time point is set within the monitoring time period. According to the video data of each scenic spot in each tourist attraction in the target village during the monitoring time period, the number of tourists in each scenic spot area in each tourist attraction in the target village at each sampling time point during the monitoring time period is obtained, and the area area of ​​each scenic spot in each tourist attraction in the target village is obtained. The number of tourists in each scenic spot area in each tourist attraction in the target village at each sampling time point during the monitoring time period is divided by the area area of ​​the scenic spot to obtain the passenger flow density of each scenic spot in each tourist attraction in the target village at each sampling time point during the monitoring time period, and the average value is calculated to obtain the average passenger flow density of each scenic spot in each tourist attraction in the target village during the monitoring time period, which is recorded as .

[0018] Based on the above embodiment, the specific working process of the tourist attraction popularity analysis module includes: calculating the cumulative number of visitors to each scenic spot in each tourist attraction in the target village during the monitoring period. , Average visit duration of tourists , average traffic volume , average passenger flow density Substitute into the analysis formula Get the popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period ,in Indicates the correction factor of the popularity coefficient of the preset scenic spot, They represent the preset thresholds of the cumulative number of visitors, the average visit time, the average flow of people, and the average passenger flow density. They represent the weights of the preset cumulative number of visitors, average visit time, average flow of visitors, and average passenger flow density. .

[0019] Based on the above embodiment, the specific working process of the tourist attraction popularity analysis module also includes: comparing the popularity coefficients of each attraction in each tourist attraction in the target village during the monitoring period, recording the attraction corresponding to the maximum popularity coefficient as a popular attraction, and screening the popular attractions in each tourist attraction in the target village during the monitoring period.

[0020] The attractions whose popularity coefficient is greater than the preset popularity coefficient threshold are recorded as hot attractions. According to the popularity coefficient of each attraction in each tourist attraction in the target village during the monitoring period, the number of hot attractions in each tourist attraction in the target village during the monitoring period is obtained. The tourist attraction corresponding to the largest number of hot attractions is recorded as a popular tourist attraction, and the popular tourist attractions in the target village during the monitoring period are screened.

[0021] On the basis of the above embodiments, the popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period is compared with the popularity coefficient of agricultural products sold at the sales points in the scenic spot, and the absolute value of the difference between the popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period and the popularity coefficient of agricultural products sold at the sales points in the scenic spot is obtained, which is recorded as the relative popularity coefficient deviation between each scenic spot in each tourist attraction in the target village and the agricultural products sold at the scenic spot during the monitoring period, and substituted into the preset relationship function between the relative popularity coefficient deviation and the integration degree to obtain the integration degree between each scenic spot in each tourist attraction in the target village and the agricultural products sold at the scenic spot.

[0022] Compared with the prior art, the artificial intelligence-based rural tourism service management system described in the present invention has the following beneficial effects: 1. The present invention collects the cumulative number of visitors to each scenic spot in each tourist attraction in the target village, the average visiting time of tourists, the average flow of people, and the average passenger flow density, analyzes the popular tourist attractions in the target village and the popular attractions in each tourist attraction, and provides feedback, which is conducive to rural tourism enterprises to formulate corresponding marketing strategies and promote the vigorous development of rural tourism.

[0023] 2. The present invention collects the cumulative sales volume of agricultural products at sales points in each scenic spot in each tourist attraction in the target village, the average length of stay of tourists at the sales points, analyzes the hot-selling agricultural products in the target village and the best sales points for selling agricultural products in each tourist attraction, and provides feedback, which is conducive to rural tourism enterprises to formulate corresponding management strategies, enrich rural tourism content, enhance tourist participation, promote rural tourism consumption, and further enhance the attractiveness of rural tourism.

[0024] 3. The present invention analyzes the degree of integration between each scenic spot in each tourist attraction in the target village and the agricultural products sold at the scenic spot, and provides feedback, which is conducive to rural tourism enterprises to take corresponding measures in time to achieve a high degree of integration between the scenic spot and the agricultural products sold, thereby increasing the richness and fun of the tourism experience, promoting the sales of agricultural products, driving the development of the rural economy, and improving the comprehensive benefits of rural tourism. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0026] Figure 1 This is a system module connection diagram of the present invention.

[0027] Figure 2 It is a structural block diagram of the tourist attraction popularity analysis module of the present invention.

[0028] Figure 3 It is a structural block diagram of the popularity analysis module for selling agricultural products of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] See also Figure 1 As shown, the present invention provides a rural tourism service management system based on artificial intelligence, including a tourist attraction visitor information collection module, a tourist attraction popularity analysis module, a tourist attraction agricultural product sales information collection module, a sales agricultural product popularity analysis module, a tourist attraction and sales agricultural product integration evaluation module, and a database.

[0031] The tourist attraction visitor information collection module is connected to the tourist attraction popularity analysis module, the tourist attraction agricultural product sales information collection module is connected to the agricultural product sales popularity analysis module, the tourist attraction and agricultural product sales integration evaluation module is respectively connected to the tourist attraction popularity analysis module and the agricultural product sales popularity analysis module, and the database is connected to the tourist attraction visitor information collection module.

[0032] The tourist attraction visitor information collection module is used to record the sub-areas of the target village where various crops are planted for tourists to visit as the attractions of each tourist attraction in the target village, and collect the tourist visit information of each attraction in each tourist attraction in the target village during the monitoring period, wherein the tourist visit information includes the cumulative number of visiting tourists, the average visiting time of tourists, the average flow of people, and the average passenger flow density.

[0033] Furthermore, the specific working process of the tourist attraction visitor information collection module includes: obtaining areas in the target village where various crops are planted for tourists to visit, and recording them as various tourist attractions in the target village.

[0034] Extract the scenic area map of the target village stored in the database, obtain the sales points for selling agricultural products set up in the area of ​​the target village where various crops are planted for tourists to visit, divide the area of ​​the target village where various crops are planted for tourists to visit according to the sales points, and obtain the sub-areas of the area of ​​the target village where various crops are planted for tourists to visit, which are recorded as the attractions of the tourist attractions in the target village.

[0035] As a preferred solution, each sales point established in the area where various crops are planted sells agricultural products corresponding to the crops planted. In a specific embodiment, each sales point established in the area where rice is planted is used to sell rice, and each sales point established in the area where rapeseed is planted is used to sell rapeseed oil.

[0036] As a preferred solution, the areas in the target village where various crops are grown for tourists to visit are divided according to sales points, that is, the number of sales points selling agricultural products in the areas where various crops are grown is the number of sub-areas in the areas where various crops are grown.

[0037] As a preferred solution, the tourist attractions in the target village include but are not limited to: rice fields, vegetable fields, etc.

[0038] As a preferred solution, the areas where the same crop is grown may be dispersed in different locations.

[0039] Furthermore, the specific working process of the tourist attraction visitor information collection module also includes: setting the duration of the monitoring time period, collecting video data of each scenic spot in each tourist attraction in the target village during the monitoring time period through high-definition cameras deployed in each scenic spot in each tourist attraction in the target village, and further obtaining the cumulative number of visitors to each scenic spot in each tourist attraction in the target village during the monitoring time period, and recording it as , The target village The number of the tourist attraction. , Indicates the first The number of the attraction. .

[0040] In a specific embodiment, the duration of the monitoring period may be one day, three days, one week, or the like.

[0041] As a preferred solution, the collected video data of each scenic spot in each tourist attraction in the target village is only used for the service and management of the target village tourism.

[0042] As a preferred solution, based on the video data of each scenic spot in each tourist attraction in the target village during the monitoring period, the tourist visit information of each scenic spot in the target village during the monitoring period is obtained. This involves computer vision technology, video analysis technology, deep learning algorithms, machine learning algorithms, intelligent video surveillance systems and other technologies, which are relatively mature existing technologies and will not be elaborated here.

[0043] In another specific embodiment, the visitor information of each scenic spot in each tourist attraction in the target village during the monitoring period is obtained by manual counting or sensor technology such as infrared sensors.

[0044] According to the video data of each scenic spot in each tourist attraction in the target village during the monitoring period, the visiting time of each tourist in each scenic spot in the target village during the monitoring period is obtained, and the average, median, mode, maximum and minimum values ​​of the visiting time of each tourist in each scenic spot in the target village during the monitoring period are further obtained, and they are recorded as , by analyzing the formula Get the average visit time of tourists to each scenic spot in each tourist attraction in the target village during the monitoring period .

[0045] As a preferred solution, the visiting duration of each tourist in each scenic spot in each tourist attraction in the target village during the monitoring period is obtained. The specific method is: delineate the regional boundary lines of each scenic spot in each tourist attraction in the target village, record the interval between the time point corresponding to the tourist entering the scenic spot area and the time point corresponding to the tourist leaving the scenic spot area as the tourist's visiting duration, and count the visiting duration of each tourist in each scenic spot in each tourist attraction in the target village during the monitoring period.

[0046] Furthermore, the specific working process of the tourist attraction visit information collection module also includes: dividing the monitoring time period into sampling time intervals according to a preset equal time principle, obtaining the number of tourists passing through each scenic spot in each tourist scenic spot in the target village at each sampling time interval during the monitoring time period based on the video data of each scenic spot in each tourist scenic spot in the target village during the monitoring time period, and recording it as the flow of people at each scenic spot in each tourist scenic spot in the target village at each sampling time interval during the monitoring time period, calculating the average flow of people at each scenic spot in each tourist scenic spot in the target village at each sampling time interval during the monitoring time period, and obtaining the average flow of people at each scenic spot in each tourist scenic spot in the target village during the monitoring time period, and recording it as .

[0047] According to the preset equal time interval principle, each sampling time point is set within the monitoring time period. According to the video data of each scenic spot in each tourist attraction in the target village during the monitoring time period, the number of tourists in each scenic spot area in each tourist attraction in the target village at each sampling time point during the monitoring time period is obtained, and the area area of ​​each scenic spot in each tourist attraction in the target village is obtained. The number of tourists in each scenic spot area in each tourist attraction in the target village at each sampling time point during the monitoring time period is divided by the area area of ​​the scenic spot to obtain the passenger flow density of each scenic spot in each tourist attraction in the target village at each sampling time point during the monitoring time period, and the average value is calculated to obtain the average passenger flow density of each scenic spot in each tourist attraction in the target village during the monitoring time period, which is recorded as .

[0048] The tourist attraction popularity analysis module is used to analyze the popularity coefficient of each attraction in each tourist attraction in the target village during the monitoring period based on the tourist visit information of each attraction in the tourist attraction in the target village during the monitoring period, obtain the popular tourist attractions in the target village and the popular attractions in each tourist attraction during the monitoring period, and provide feedback.

[0049] Further, see Figure 2 As shown, the specific working process of the tourist attraction popularity analysis module includes: calculating the cumulative number of visitors to each scenic spot in each tourist attraction in the target village during the monitoring period. , Average visit duration of tourists , average traffic volume , average passenger flow density Substitute into the analysis formula Get the popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period ,in Indicates the correction factor of the popularity coefficient of the preset scenic spot, They represent the preset thresholds of the cumulative number of visitors, the average visiting time of visitors, the average flow of people, and the average passenger flow density. They represent the weights of the preset cumulative number of visitors, average visitor duration, average passenger flow, and average passenger flow density. .

[0050] As a preferred solution, the correction factor of the popularity coefficient of the scenic spot plays the role of amplifying, reducing or rounding the popularity coefficient of the scenic spot to facilitate calculation and analysis.

[0051] As a preferred solution, the thresholds of the cumulative number of visiting tourists, the average visiting time of tourists, the average flow of people, and the average passenger flow density are set according to actual application requirements.

[0052] As a preferred solution, the weights of the cumulative number of visiting tourists, the average visiting time of tourists, the average flow of people, and the average passenger flow density are set according to the importance of evaluating the popularity of each scenic spot in each tourist attraction in the target village during the monitoring period. In a specific embodiment, the weights of the cumulative number of visiting tourists, the average visiting time of tourists, the average flow of people, and the average passenger flow density are 0.25, 0.25, 0.25, and 0.25, respectively.

[0053] Furthermore, the specific working process of the tourist attraction popularity analysis module also includes: comparing the popularity coefficients of each attraction in each tourist attraction in the target village during the monitoring period, recording the attraction corresponding to the maximum popularity coefficient as a popular attraction, and screening the popular attractions in each tourist attraction in the target village during the monitoring period.

[0054] The attractions whose popularity coefficient is greater than the preset popularity coefficient threshold are recorded as hot attractions. According to the popularity coefficient of each attraction in each tourist attraction in the target village during the monitoring period, the number of hot attractions in each tourist attraction in the target village during the monitoring period is obtained. The tourist attraction corresponding to the largest number of hot attractions is recorded as a popular tourist attraction, and the popular tourist attractions in the target village during the monitoring period are screened.

[0055] It should be noted that the present invention collects the cumulative number of visitors to each scenic spot in each tourist attraction in the target village, the average visiting time of tourists, the average flow of people, and the average passenger flow density, analyzes the popular tourist attractions in the target village and the popular attractions in each tourist attraction, and provides feedback, which is conducive to rural tourism enterprises to formulate corresponding marketing strategies and promote the vigorous development of rural tourism.

[0056] The tourist attraction agricultural product sales information collection module is used to collect agricultural product sales information at sales points in each tourist attraction in the target village during the monitoring period, wherein the agricultural product sales information includes the cumulative sales volume of agricultural products and the average length of stay of tourists at the sales points.

[0057] Furthermore, the specific working process of the tourist attraction agricultural product sales information collection module is: obtaining the sales records of the sales points in each tourist attraction in the target village during the monitoring period, obtaining the cumulative sales volume of agricultural products in each tourist attraction in the target village during the monitoring period, and recording it as .

[0058] Through the high-definition cameras deployed at the sales points in each scenic spot in each tourist attraction in the target village, the video data of the sales points in each scenic spot in the target village during the monitoring period are collected, the length of stay of each tourist at the sales points in each scenic spot in each tourist attraction in the target village during the monitoring period is obtained, and the average value is calculated to obtain the average length of stay of tourists at the sales points in each scenic spot in each tourist attraction in the target village during the monitoring period, which is recorded as .

[0059] As a preferred solution, the agricultural products sold at the sales points in each scenic spot in the same tourist attraction are the same, and are agricultural products corresponding to the crops grown in the tourist attraction.

[0060] As a preferred solution, the video data collected at the sales points in each scenic spot in the target village during the monitoring period is only used for the service and management of the target village tourism.

[0061] As a preferred solution, the length of time that a tourist stays at the sales point refers to the length of time between the time point corresponding to the arrival of the tourist at the sales point and the time point corresponding to the departure of the tourist from the sales point.

[0062] The agricultural product sales popularity analysis module is used to analyze the popularity coefficient of agricultural products sold at sales points in each scenic spot in each tourist attraction in the target village during the monitoring period based on the agricultural product sales information of the sales points in each scenic spot in the target village during the monitoring period, obtain the hot-selling agricultural products in the target village during the monitoring period and the best sales points for agricultural products in each tourist attraction, and provide feedback.

[0063] Further, see Figure 3 As shown, the specific working process of the agricultural product popularity analysis module includes: calculating the cumulative sales volume of agricultural products at each sales point in each scenic spot in each tourist attraction in the target village during the monitoring period. and the average length of stay of tourists at the point of sale Substitute into the analysis formula Obtain the popularity coefficient of agricultural products sold at sales points in each scenic spot in the target village during the monitoring period ,in A correction factor indicating the popularity coefficient of agricultural products sold at a preset sales point. represents a natural constant, They respectively represent the thresholds for the preset cumulative sales volume of agricultural products and the average length of time that tourists stay at the sales point.

[0064] As a preferred solution, the correction factor of the popularity coefficient of the agricultural products sold at the sales point serves to amplify, reduce or round the popularity coefficient of the agricultural products sold at the sales point to facilitate calculation and analysis.

[0065] As a preferred solution, the thresholds of the cumulative sales volume of agricultural products and the average length of stay of tourists at the sales point are set according to actual application requirements.

[0066] Furthermore, the specific working process of the popularity analysis module for selling agricultural products also includes: comparing the popularity coefficients of the sales points of agricultural products in each scenic spot in each tourist attraction in the target village during the monitoring period, recording the sales point in the scenic spot corresponding to the largest popularity coefficient of agricultural products sold in the tourist attraction as the best sales point for agricultural products in the tourist attraction, and counting the best sales points for agricultural products in each tourist attraction in the target village during the monitoring period.

[0067] The popularity coefficients of agricultural products sold at sales points in each scenic spot in each tourist attraction in the target village during the monitoring period are accumulated to obtain the cumulative popularity coefficients of agricultural products sold in each tourist attraction in the target village during the monitoring period, and the coefficients are compared with each other. The agricultural products sold in the tourist attraction corresponding to the largest cumulative popularity coefficient are recorded as hot-selling agricultural products, and the hot-selling agricultural products in the target village during the monitoring period are screened.

[0068] It should be noted that the present invention collects the cumulative sales volume of agricultural products at sales points in each scenic spot in each tourist attraction in the target village, the average length of stay of tourists at the sales points, analyzes the hot-selling agricultural products in the target village and the best sales points for selling agricultural products in each tourist attraction, and provides feedback, which is conducive to rural tourism enterprises to formulate corresponding management strategies, enrich rural tourism content, enhance tourist participation, promote rural tourism consumption, and further enhance the attractiveness of rural tourism.

[0069] The module for evaluating the degree of integration of tourist attractions and agricultural products sold is used to analyze the degree of integration of each tourist attraction in each tourist attraction in the target village and the agricultural products sold at the sales points within each tourist attraction according to the popularity coefficient of each tourist attraction in the target village during the monitoring period, and to provide feedback.

[0070] Furthermore, the specific working process of the tourist attraction and agricultural product sales integration evaluation module is: compare the popularity coefficient of each tourist attraction in each tourist attraction in the target village during the monitoring period with the popularity coefficient of agricultural products sold at the sales points in the tourist attraction, obtain the absolute value of the difference between the popularity coefficient of each tourist attraction in each tourist attraction in the target village during the monitoring period and the popularity coefficient of agricultural products sold at the sales points in the tourist attraction, record it as the relative popularity coefficient deviation of each tourist attraction in each tourist attraction in the target village during the monitoring period and the agricultural products sold by the tourist attraction, and substitute it into the preset relationship function between the relative popularity coefficient deviation and the integration degree to obtain the integration degree of each tourist attraction in each tourist attraction in the target village and the agricultural products sold by the tourist attraction.

[0071] As a preferred solution, the relationship function between the relative popularity coefficient deviation and the integration degree is a negative correlation function, that is, the larger the relative popularity coefficient deviation is, the smaller the integration degree is.

[0072] It should be noted that if the degree of integration between a tourist attraction and the agricultural products sold within the attraction is high, the popularity of the tourist attraction and the popularity of the agricultural products sold at the sales points within the attraction should change synchronously and follow each other.

[0073] It should be noted that the present invention analyzes the degree of integration between each scenic spot in each tourist attraction in the target village and the agricultural products sold at the scenic spot, and provides feedback, which is conducive to rural tourism enterprises to take corresponding measures in time to achieve a high degree of integration between the scenic spot and the agricultural products sold, thereby increasing the richness and fun of the tourism experience, promoting the sales of agricultural products, driving the development of the rural economy, and improving the comprehensive benefits of rural tourism.

[0074] The database is used to store a scenic area map of the target village.

[0075] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A rural tourism service management system based on artificial intelligence, characterized in that: include: Tourist attraction visit information collection module: used to record the sub-areas of the target village where various crops are planted for tourists to visit as the attractions of the target village, and collect the visit information of the tourists in the target village during the monitoring period, where the visit information includes the cumulative number of tourists, the average visit time, the average flow of people, and the average passenger flow density; Tourist attraction popularity analysis module: used to analyze the popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period according to the visitor information of each scenic spot in each tourist attraction in the target village during the monitoring period, obtain the popular tourist attractions in the target village during the monitoring period and the popular attractions in each tourist attraction, and provide feedback; Agricultural product sales information collection module at tourist attractions: used to collect agricultural product sales information at sales points in each tourist attraction in the target village during the monitoring period, where the agricultural product sales information includes the cumulative sales volume of agricultural products and the average length of stay of tourists at the sales points; The module for analyzing the popularity of agricultural products sold is used to analyze the popularity coefficients of agricultural products sold at the sales points in each scenic spot in each tourist attraction in the target village during the monitoring period according to the agricultural product sales information of the sales points in each tourist attraction in the target village during the monitoring period, obtain the hot-selling agricultural products in the target village during the monitoring period and the best sales points for agricultural products in each tourist attraction, and provide feedback; The module for evaluating the integration of tourist attractions and agricultural products sold is used to analyze the integration of various scenic spots in various tourist attractions in the target villages and agricultural products sold at the sales points in the scenic spots according to the popularity coefficient of each scenic spot in the target villages during the monitoring period, and to provide feedback; Database: used to store scenic area maps of target villages.

2. According to claim 1, a rural tourism service management system based on artificial intelligence is characterized by: The specific working process of the tourist attraction visitor information collection module includes: Acquire areas in the target village where various crops are planted for tourists to visit, and record them as tourist attractions in the target village; Extract the scenic area map of the target village stored in the database, obtain the sales points for selling agricultural products set up in the area of ​​the target village where various crops are planted for tourists to visit, divide the area of ​​the target village where various crops are planted for tourists to visit according to the sales points, and obtain the sub-areas of the area of ​​the target village where various crops are planted for tourists to visit, which are recorded as the attractions of the tourist attractions in the target village.

3. According to claim 2, a rural tourism service management system based on artificial intelligence is characterized in that: The specific working process of the tourist attraction visitor information collection module also includes: The duration of the monitoring period is set, and the video data of each scenic spot in each tourist scenic spot in the target village during the monitoring period is collected through the high-definition cameras deployed in each scenic spot in the target village. The cumulative number of visitors to each scenic spot in each tourist scenic spot in the target village during the monitoring period is further obtained and recorded as , The target village The number of the tourist attraction. , Indicates the first The number of the attraction. ; According to the video data of each scenic spot in each tourist attraction in the target village during the monitoring period, the visiting time of each tourist in each scenic spot in the target village during the monitoring period is obtained, and the average, median, mode, maximum and minimum values ​​of the visiting time of each tourist in each scenic spot in the target village during the monitoring period are further obtained, and they are recorded as , by analyzing the formula Get the average visit time of tourists to each scenic spot in each tourist attraction in the target village during the monitoring period .

4. According to claim 3, the rural tourism service management system based on artificial intelligence is characterized by: The specific working process of the tourist attraction visitor information collection module also includes: The monitoring time period is divided into sampling time intervals according to the preset equal time length principle. According to the video data of each scenic spot in each tourist attraction in the target village during the monitoring time period, the number of tourists passing through each scenic spot in each tourist attraction in the target village during each sampling time interval during the monitoring time period is obtained, and it is recorded as the flow of people at each scenic spot in each tourist attraction in the target village during each sampling time interval during the monitoring time period. The average flow of people at each scenic spot in each tourist attraction in the target village during each sampling time interval during the monitoring time period is calculated to obtain the average flow of people at each scenic spot in each tourist attraction in the target village during the monitoring time period, which is recorded as ; According to the preset equal time interval principle, each sampling time point is set within the monitoring time period. According to the video data of each scenic spot in each tourist attraction in the target village during the monitoring time period, the number of tourists in each scenic spot area in each tourist attraction in the target village at each sampling time point during the monitoring time period is obtained, and the area area of ​​each scenic spot in each tourist attraction in the target village is obtained. The number of tourists in each scenic spot area in each tourist attraction in the target village at each sampling time point during the monitoring time period is divided by the area area of ​​the scenic spot to obtain the passenger flow density of each scenic spot in each tourist attraction in the target village at each sampling time point during the monitoring time period, and the average value is calculated to obtain the average passenger flow density of each scenic spot in each tourist attraction in the target village during the monitoring time period, which is recorded as .

5. According to claim 4, the rural tourism service management system based on artificial intelligence is characterized by: The specific working process of the tourist attraction popularity analysis module includes: The cumulative number of visitors to each scenic spot in each tourist attraction in the target village during the monitoring period , Average visit duration of tourists , average traffic volume , average passenger flow density Substitute into the analysis formula Get the popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period ,in Indicates the correction factor of the popularity coefficient of the preset scenic spot, They represent the preset thresholds of the cumulative number of visitors, the average visiting time of visitors, the average flow of people, and the average passenger flow density. They represent the weights of the preset cumulative number of visitors, average visitor duration, average passenger flow, and average passenger flow density. .

6. The rural tourism service management system based on artificial intelligence according to claim 1 is characterized by: The specific working process of the tourist attraction popularity analysis module also includes: The popularity coefficients of the various scenic spots in the target villages during the monitoring period are compared with each other, and the scenic spots corresponding to the maximum popularity coefficients are recorded as popular scenic spots, and the popular scenic spots in the target villages during the monitoring period are screened; The attractions whose popularity coefficient is greater than the preset popularity coefficient threshold are recorded as hot attractions. According to the popularity coefficient of each attraction in each tourist attraction in the target village during the monitoring period, the number of hot attractions in each tourist attraction in the target village during the monitoring period is obtained. The tourist attraction corresponding to the largest number of hot attractions is recorded as a popular tourist attraction, and the popular tourist attractions in the target village during the monitoring period are screened.

7. The rural tourism service management system based on artificial intelligence according to claim 3 is characterized by: The specific working process of the tourist attraction agricultural product sales information collection module is as follows: Obtain the sales records of each sales point in each scenic spot in the target village during the monitoring period, and obtain the cumulative sales volume of agricultural products in each scenic spot in each scenic spot in the target village during the monitoring period, which is recorded as ; Through the high-definition cameras deployed at the sales points in each scenic spot in each tourist attraction in the target village, the video data of the sales points in each scenic spot in the target village during the monitoring period are collected, the length of stay of each tourist at the sales points in each scenic spot in each tourist attraction in the target village during the monitoring period is obtained, and the average value is calculated to obtain the average length of stay of tourists at the sales points in each scenic spot in each tourist attraction in the target village during the monitoring period, which is recorded as .

8. The artificial intelligence-based rural tourism service management system according to claim 7 is characterized by: The specific working process of the popularity analysis module for selling agricultural products includes: The cumulative sales volume of agricultural products at each sales point in each scenic spot in the target village during the monitoring period and the average length of stay of tourists at the point of sale Substitute into the analysis formula Obtain the popularity coefficient of agricultural products sold at sales points in each scenic spot in the target village during the monitoring period ,in A correction factor indicating the popularity coefficient of agricultural products sold at a preset sales point. represents a natural constant, They respectively represent the thresholds for the preset cumulative sales volume of agricultural products and the average length of time that tourists stay at the sales point.

9. The rural tourism service management system based on artificial intelligence according to claim 1, characterized in that: The specific working process of the sales agricultural product popularity analysis module also includes: The popularity coefficients of agricultural products sold at various points in various scenic spots in the target villages during the monitoring period are compared with each other, and the sales point in the scenic spot corresponding to the largest popularity coefficient of agricultural products sold in the tourist scenic spot is recorded as the best sales point for agricultural products in the tourist scenic spot. The best sales points for agricultural products sold in various tourist scenic spots in the target villages during the monitoring period are counted; The popularity coefficients of agricultural products sold at sales points in each scenic spot in each tourist attraction in the target village during the monitoring period are accumulated to obtain the cumulative popularity coefficients of agricultural products sold in each tourist attraction in the target village during the monitoring period, and the coefficients are compared with each other. The agricultural products sold in the tourist attraction corresponding to the largest cumulative popularity coefficient are recorded as hot-selling agricultural products, and the hot-selling agricultural products in the target village during the monitoring period are screened.

10. The rural tourism service management system based on artificial intelligence according to claim 1, characterized in that: The specific working process of the tourist attractions and agricultural products integration evaluation module is as follows: The popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period is compared with the popularity coefficient of agricultural products sold at the sales points in the scenic spot, and the absolute value of the difference between the popularity coefficient of each scenic spot in each tourist attraction in the target village during the monitoring period and the popularity coefficient of agricultural products sold at the sales points in the scenic spot is obtained. It is recorded as the relative popularity coefficient deviation of each scenic spot in each tourist attraction in the target village during the monitoring period and the agricultural products sold at the scenic spot, and substituted into the preset relationship function between the relative popularity coefficient deviation and the integration degree to obtain the integration degree of each scenic spot in each tourist attraction in the target village and the agricultural products sold at the scenic spot.

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