Global text and travel industry monitoring system and method

Abstract

The invention discloses a global tourism industry monitoring system and method, and relates to the technical field of tourism technology, and the system comprises a data monitoring unit, a resource distribution unit and a background monitoring unit. The resource allocation unit comprises a resource evaluation module, a human traffic recognition module, an emergency response module, a resource scheduling module and an analog simulation module, and the resource scheduling module is in one-way connection with the analog simulation module. According to the system, key resources such as traffic tools, accommodation facilities and catering services in the scenic area are comprehensively and carefully evaluated, the use efficiency of various resources and the tourist demand matching degree are deeply analyzed, and the system can monitor and predict the visitor flow change in the scenic area in real time, so that various resources are intelligently dispatched, and the tourist experience is improved. According to the intelligent resource scheduling mode, the utilization efficiency of resources is improved, the operation cost is reduced, and the sightseeing experience and satisfaction of tourists are greatly improved.

Description

Technical Field

[0001] This system belongs to the field of tourism technology, and in particular, relates to a global cultural tourism industry monitoring system and method. Background Art

[0002] With the vigorous development of the global tourism industry, the cultural tourism industry has become an important force to promote economic growth. However, it is accompanied by a series of challenges such as the rational allocation of tourism resources, the effective management of tourist flow, and the timely response to emergency events. The traditional tourism management model often relies on manual experience and on-site management, lacks in-depth mining and intelligent analysis of big data, and is difficult to achieve optimal allocation of resources and improve tourists' travel experience. How to use modern information technology to build a comprehensive and efficient cultural tourism industry monitoring system has become a problem waiting to be solved in the cultural tourism industry. Therefore, we propose a global cultural tourism industry monitoring system and method. Summary of the invention

[0004] The purpose of this system is to provide a global cultural tourism industry monitoring system and method. Through its resource evaluation module, a comprehensive and detailed evaluation is conducted on key resources such as transportation, accommodation facilities, and catering services in the scenic area, and an in-depth analysis is made on the utilization efficiency of various resources and the matching degree with tourists' needs. The system can monitor and predict the changes in the flow of people in the scenic area in real time, so as to intelligently dispatch various resources. This intelligent resource scheduling method not only improves the utilization efficiency of resources and reduces operating costs, but also greatly improves the tourists' tour experience and satisfaction. It solves the problem that the traditional tourism management model often relies on manual experience and on-site management, lacks in-depth mining and intelligent analysis of big data, and is difficult to achieve optimal allocation of resources and cannot improve the tourists' travel experience.

[0005] To solve the above technical problems, this system is implemented through the following technical solutions:

[0006] This system is a global cultural tourism industry monitoring system and method, including a data monitoring unit, a resource allocation unit and a background monitoring unit;

[0007] The resource allocation unit includes a resource assessment module, a human flow identification module, an emergency response module, a resource scheduling module and a simulation module. The resource assessment module is unidirectionally connected to the human flow identification module; the human flow identification module is unidirectionally connected to the emergency response module; the emergency response module is unidirectionally connected to the resource scheduling module; the resource scheduling module is unidirectionally connected to the simulation module;

[0008] The resource assessment module is responsible for a comprehensive assessment of currently available resources, including transportation tools (such as buses, taxis and shared bicycles), accommodation facilities (such as hotels, homestays and guesthouses), catering services, parking capacity, and scenic area reception capacity, and clarifying the total amount and distribution of various resources; the crowd flow identification module is responsible for real-time monitoring of the crowd density in the scenic area based on the crowd flow data uploaded by the data detection unit, judging whether congestion occurs by analyzing the crowd density, and automatically uploading alarm information when the preset threshold is reached; the emergency response module is responsible for preparing emergency plans in advance upon receiving the alarm information uploaded by the crowd flow identification module or the data of unforeseen events (such as extreme weather, traffic accidents) uploaded by the data monitoring unit, and immediately launching them once they occur to minimize the negative experience of tourists; the resource scheduling module is responsible for setting the goal of optimizing scheduling according to the results of resource evaluation, increasing the frequency and routes of public transportation to attract more passengers to use public transportation, and at the same time, guiding the reasonable diversion of private cars through price mechanisms (such as congestion fees and parking fees); the simulation module is responsible for testing different scheduling schemes through computer simulation technology before actual implementation to evaluate their effects and potential risks.

[0009] As a preferred technical solution, the human flow recognition module annotates the images collected by the camera, marks the center point of each passenger's head, records its two-dimensional coordinates and total number, and converts the annotated data into a density map, which is usually generated by convolving each delta function with a normalized one; a small weight matrix is ​​slid on the input data, and the dot product of the weight matrix and the corresponding part of the input data is calculated to generate feature information. The calculation method is as follows;

[0010]

[0011] Where yi,j is the value of the output feature map at position (i,j), Wm,n is the element of the weight matrix, Xi+m,j+n is the value of the input image at position (i+m,j+n), and M and N are the height and width of the weight matrix respectively;

[0012] The VGG-16 pre-trained model is used as the front-end network to extract shallow features of the image. A multi-scale feature extraction module (MFEM) is introduced to process features of different scales through dilated convolutions. The feature map is upsampled using transposed convolutions to restore the spatial resolution and generate a high-resolution density map of the same size as the input image. The generated density map is integrated to obtain the estimated number of people in the crowd.

[0013] The number of people can be estimated by summing all pixel values ​​in the density map:

[0014]

[0015] Where D(x,y) is the value of the density map at position (x,y);.

[0016] As a preferred technical solution, the data monitoring unit includes a crawler system, a camera, an environmental sensor, a passenger flow counter, a data acquisition module, a data processing module and an intelligent analysis and prediction module.

[0017] As a preferred technical solution, the crawler system, camera, environmental sensor and passenger flow counter are respectively unidirectionally connected to the data acquisition module; the data acquisition module is unidirectionally connected to the data processing module; the data processing module is unidirectionally connected to the intelligent analysis and prediction module; the intelligent analysis and prediction module is unidirectionally connected to the resource evaluation module.

[0018] As a preferred technical solution, the crawler system is responsible for automatically capturing user comments and ratings on social media platforms. The data reflects the real experience and feelings of tourists. The web crawler also obtains information about the scenic spot from major travel booking platforms and travel guide websites, such as hotel reservations, ticket sales data, and user reviews, to understand market demand trends and provide a basis for the formulation of marketing strategies; the camera is responsible for installing high-definition cameras in roads, parking lots and other areas around the scenic spot, which can monitor traffic conditions in real time, including vehicle flow, vehicle speed, lane occupancy, passenger flow and safety hazards, and provide data support for the passenger flow identification module and resource scheduling module; the environmental sensor is responsible for sensors used to monitor environmental parameters such as air quality, temperature and humidity, and light intensity. These data provide data support for evaluating the carrying capacity of the scenic spot, the comfort of tourists, and the formulation of emergency plans; the passenger flow counter is responsible for installing passenger flow counters at key locations such as the entrance of the scenic spot and the parking lot, which can monitor the number of tourists entering and leaving in real time. These counters automatically record the number of people passing by through infrared and laser technology.

[0019] As a preferred technical solution, the data acquisition module is responsible for realizing all-round real-time collection of cultural tourism industry data through crawler systems, cameras, environmental sensors and passenger flow counters. These data include tourist flow statistics, consumption pattern analysis, social media APIs, online travel platform interfaces, public Wi-Fi hotspot tracking, scenic area environmental quality monitoring (such as air quality, noise level), and tourist satisfaction evaluation; the data processing module is responsible for cleaning, integrating and storing the collected data to confirm the accuracy and completeness of the data; the intelligent analysis and prediction module integrates a variety of artificial intelligence algorithms, including machine learning, deep learning and complex event processing (CEP) technology. It can not only identify the development trends and potential problems of the cultural tourism industry, but also predict market changes, providing a scientific basis for policy formulation and corporate strategic planning.

[0020] As a preferred technical solution, the background monitoring unit includes a visualization window, online traffic promotion, personalized recommendation and user interaction module; the simulation module is unidirectionally connected to the visualization window; the visualization window is unidirectionally connected to the online traffic promotion and personalized recommendation respectively; the online traffic promotion is unidirectionally connected to the user interaction module; the user interaction module is bidirectionally connected to the personalized recommendation; the user interaction module is unidirectionally connected to the crawler system.

[0021] As a preferred technical solution, the visualization window is responsible for converting complex data analysis results into intuitive and easy-to-understand charts, maps and dashboards, supporting multi-dimensional screening and operation. Users can customize views as needed and quickly obtain required information. In addition, the module also supports mobile access, so that managers can keep abreast of the latest developments in the cultural and tourism industry no matter where they are; the online traffic diversion and promotion is responsible for placing targeted advertisements on platforms frequently used by the target audience, improving the ranking of the official website on the search engine results page, and publishing high-quality blog articles and video content to attract tourists; the personalized recommendation is responsible for establishing a user portrait based on the user's search history, browsing behavior and preferences, and recommending related tourism products or services based on the user portrait.

[0022] This system has the following beneficial effects:

[0023] Through its resource assessment module, this system conducts a comprehensive and detailed assessment of key resources such as transportation, accommodation facilities, and catering services in the scenic area. This not only covers the total amount and distribution of resources, but also deeply analyzes the utilization efficiency of various resources and the matching degree of tourists' needs. Combined with crowd flow identification technology and simulation technology, the system can monitor and predict the changes in crowd flow in the scenic area in real time, so as to intelligently dispatch various resources. During peak periods, the system can automatically increase the frequency and routes of public transportation, guide private cars to be reasonably diverted, and effectively alleviate congestion in scenic areas; in the off-season, resource allocation can be adjusted according to tourists' needs to avoid waste of resources. This intelligent resource scheduling method not only improves the utilization efficiency of resources and reduces operating costs, but also greatly enhances tourists' sightseeing experience and satisfaction.

[0024] This system has excellent emergency response capabilities. It can quickly activate emergency plans when it receives unforeseen events (such as extreme weather, traffic accidents) or when the flow of people reaches a preset threshold. Through a variety of pre-prepared emergency plans and rapid response mechanisms, the system can organize relevant departments and personnel to carry out emergency disposal in a short time to ensure the safety and comfort of tourists. Moreover, the system can monitor the progress and scope of impact of events in real time, adjust emergency measures in time, and minimize the negative impact of emergencies on scenic spot operations. This efficient emergency response and risk management capability provides strong support for scenic spot managers and ensures the stable operation of the scenic spot and the safety of tourists.

[0025] By integrating a variety of artificial intelligence algorithms and big data analysis technologies, this system can deeply mine cultural and tourism industry data, identify development trends and potential problems, and predict market changes. These analysis results not only provide a scientific basis for policymakers to help them formulate more accurate and effective policy measures, but also provide strong support for corporate strategic planning, promoting the sustainable development and innovation of the cultural and tourism industry. In addition, the system also has personalized recommendations and online traffic diversion and promotion functions. After establishing a user portrait based on the user's search history, browsing behavior and preferences, the system can accurately recommend tourism products or services that meet user needs, improve marketing effectiveness and conversion rate, and the online traffic diversion and promotion function attracts more potential tourists to pay attention to and visit local cultural and tourism official websites by placing targeted advertisements on platforms frequently used by the target audience and improving the ranking of official websites on search engine results pages, thereby further enhancing the local cultural and tourism influence and popularity.

[0026] Of course, any product implementing this system does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solution of the embodiment of the present system, the drawings required for describing the embodiment will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present system. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 This is a flow chart of the system and method for monitoring the entire cultural and tourism industry of this system. DETAILED DESCRIPTION

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

[0030] See also Figure 1 As shown, this system is a global cultural tourism industry monitoring system and method, including a data monitoring unit, a resource allocation unit and a background monitoring unit;

[0031] The resource allocation unit includes a resource assessment module, a human flow identification module, an emergency response module, a resource scheduling module and a simulation module. The resource assessment module is unidirectionally connected to the human flow identification module; the human flow identification module is unidirectionally connected to the emergency response module; the emergency response module is unidirectionally connected to the resource scheduling module; and the resource scheduling module is unidirectionally connected to the simulation module.

[0032] The resource assessment module is responsible for conducting a comprehensive assessment of currently available resources, including transportation tools (such as buses, taxis and shared bicycles), accommodation facilities (such as hotels, homestays and guesthouses), catering services, parking capacity, and scenic area reception capacity, and clarifying the total amount and distribution of various resources; the crowd flow identification module is responsible for real-time monitoring of the crowd density in the scenic area based on the crowd flow data uploaded by the data detection unit, judging whether congestion occurs by analyzing the crowd density, and automatically uploading alarm information when the preset threshold is reached; the emergency response module is responsible for preparing emergency plans in advance after receiving the alarm information uploaded by the crowd flow identification module or the data of unforeseen events (such as extreme weather, traffic accidents) uploaded by the data monitoring unit, and immediately launching them once they occur to minimize the negative experience of tourists; the resource scheduling module is responsible for setting the goal of optimizing scheduling based on the results of resource assessment, increasing the frequency and routes of public transportation to attract more passengers to use public transportation, and at the same time, guiding the reasonable diversion of private cars through price mechanisms (such as congestion fees and parking fees); the simulation module is responsible for testing different scheduling schemes through computer simulation technology before actual implementation to evaluate their effectiveness and potential risks.

[0033] The crowd flow recognition module annotates the images collected by the camera, marks the center point of each passenger's head, records its two-dimensional coordinates and total number, and converts the annotated data into a density map, which is usually generated by convolving each delta function with a normalized one; a small weight matrix is ​​slid on the input data, and the dot product of the weight matrix and the corresponding part of the input data is calculated to generate feature information. The calculation method is as follows;

[0034]

[0035] Where yi,j is the value of the output feature map at position (i,j), Wm,n is the element of the weight matrix, Xi+m,j+n is the value of the input image at position (i+m,j+n), and M and N are the height and width of the weight matrix respectively;

[0036] The VGG-16 pre-trained model is used as the front-end network to extract shallow features of the image. A multi-scale feature extraction module (MFEM) is introduced to process features of different scales through dilated convolutions. The feature map is upsampled using transposed convolutions to restore the spatial resolution and generate a high-resolution density map of the same size as the input image. The generated density map is integrated to obtain the estimated number of people in the crowd.

[0037] The number of people can be estimated by summing all pixel values ​​in the density map:

[0038]

[0039] Where D(x,y) is the value of the density map at position (x,y);.

[0040] The data monitoring unit includes a crawler system, a camera, an environmental sensor, a passenger flow counter, a data acquisition module, a data processing module and an intelligent analysis and prediction module.

[0041] The crawler system, camera, environmental sensor and passenger flow counter are respectively connected to the data acquisition module in one direction; the data acquisition module is connected to the data processing module in one direction; the data processing module is connected to the intelligent analysis and prediction module in one direction; the intelligent analysis and prediction module is connected to the resource evaluation module in one direction.

[0042] The crawler system is responsible for automatically capturing user comments and ratings on social media platforms. The data reflects the real experience and feelings of tourists. The web crawler also obtains information about the scenic spot from major travel booking platforms and travel guide websites, such as hotel reservations, ticket sales data, and user reviews, to understand market demand trends and provide a basis for the formulation of marketing strategies; the camera is responsible for installing high-definition cameras in roads, parking lots and other areas around the scenic spot, which can monitor traffic conditions in real time, including vehicle flow, vehicle speed, lane occupancy, passenger flow and safety hazards, and provide data support for the passenger flow identification module and resource scheduling module; the environmental sensor is responsible for sensors used to monitor environmental parameters such as air quality, temperature and humidity, and light intensity. These data provide data support for evaluating the carrying capacity of the scenic spot, the comfort of tourists, and the formulation of emergency plans; the passenger flow counter is responsible for installing passenger flow counters at key locations such as the entrance of the scenic spot and the parking lot, which can monitor the number of tourists entering and leaving in real time. These counters automatically record the number of people passing by through infrared and laser technology.

[0043] The data collection module is responsible for realizing all-round real-time collection of cultural tourism industry data through crawler systems, cameras, environmental sensors and passenger flow counters. These data include tourist flow statistics, consumption pattern analysis, social media APIs, online travel platform interfaces, public Wi-Fi hotspot tracking, scenic area environmental quality monitoring (such as air quality, noise level), and tourist satisfaction evaluation; the data processing module is responsible for cleaning, integrating and storing the collected data to confirm the accuracy and completeness of the data; the intelligent analysis and prediction module integrates a variety of artificial intelligence algorithms, including machine learning, deep learning and complex event processing (CEP) technology. It can not only identify the development trends and potential problems of the cultural tourism industry, but also predict market changes, providing a scientific basis for policy formulation and corporate strategic planning.

[0044] The background monitoring unit includes a visualization window, online traffic diversion and promotion, personalized recommendation and user interaction module; the simulation module is unidirectionally connected to the visualization window; the visualization window is unidirectionally connected to the online traffic diversion and promotion and personalized recommendation respectively; the online traffic diversion and promotion is unidirectionally connected to the user interaction module; the user interaction module is bidirectionally connected to the personalized recommendation; the user interaction module is unidirectionally connected to the crawler system.

[0045] The visualization window is responsible for converting complex data analysis results into intuitive and easy-to-understand charts, maps and dashboards, supporting multi-dimensional filtering and operations. Users can customize views as needed and quickly obtain required information. In addition, this module also supports mobile access, so that managers can keep abreast of the latest developments in the cultural and tourism industry no matter where they are; online traffic promotion is responsible for placing targeted advertisements on platforms frequently used by the target audience, improving the ranking of the official website on the search engine results page, and publishing high-quality blog articles and video content to attract tourists; personalized recommendations are responsible for establishing user portraits based on users' search history, browsing behavior and preferences, and recommending related tourism products or services based on user portraits.

[0046] A specific application of this embodiment is: first, the data monitoring units such as crawler system, camera, environmental sensor and passenger flow counter are used to realize the all-round real-time collection of cultural tourism industry data. Then, the data processing module cleans, integrates and stores the collected raw data to ensure the accuracy and integrity of the data. The intelligent analysis and prediction module uses artificial intelligence algorithms such as machine learning and deep learning to deeply explore the value behind the data, identify the development trend and potential problems of the cultural tourism industry, and predict market changes. Based on these data, the resource evaluation module comprehensively evaluates the currently available transportation, accommodation facilities, catering services and other resources, and clarifies the total amount and distribution of resources. The flow recognition module monitors the flow density in the scenic area in real time according to the image data collected by the camera, and automatically uploads the alarm information when the preset threshold is reached. After receiving the alarm information or unforeseen event data, the emergency response module immediately starts the pre-prepared emergency plan to minimize the bad experience of tourists. The resource scheduling module sets the optimization scheduling target according to the resource evaluation results, and reasonably guides the diversion of tourists by increasing the number of public transportation flights and adjusting the price mechanism. Before executing any scheduling plan, the simulation module tests the effects and potential risks of different plans through computer simulation technology to provide a scientific basis for managers. At the same time, the visualization window converts complex data analysis results into intuitive and easy-to-understand charts and maps, supports multi-dimensional screening and operations, and enables managers to quickly obtain the required information; the online traffic promotion module places targeted advertisements on platforms frequently used by the target audience, improves the ranking of the official website on the search engine results page, and publishes high-quality content to attract tourists; the personalized recommendation module recommends travel products or services that meet the needs of users based on their search history, browsing behavior and preferences, thereby improving user experience and satisfaction. Finally, the user interaction module serves as a bridge connecting users and the system. It not only supports users to query travel information and book services, but also encourages users to share travel experiences and make suggestions. These feedback information are captured again by the crawler system and incorporated into the data analysis process, forming a closed-loop continuous optimization process.

[0047] It is worth noting that in the above system embodiment, the various units 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 the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of this system.

[0048] In addition, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by instructing related hardware through a program, and the corresponding program can be stored in a computer-readable storage medium.

[0049] The preferred embodiments of the system disclosed above are only used to help explain the system. The preferred embodiments do not describe all details in detail, nor do they limit the system to the specific implementation methods described. Obviously, many modifications and changes can be made based on the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the system, so that technicians in the relevant technical field can better understand and use the system. The system is limited only by the claims and their full scope and equivalents.

Claims

1. A global cultural tourism industry monitoring system and method, comprising a data monitoring unit, a resource allocation unit and a background monitoring unit; characterized in that: The resource allocation unit includes a resource assessment module, a human flow identification module, an emergency response module, a resource scheduling module and a simulation module. The resource assessment module is unidirectionally connected to the human flow identification module; the human flow identification module is unidirectionally connected to the emergency response module; the emergency response module is unidirectionally connected to the resource scheduling module; the resource scheduling module is unidirectionally connected to the simulation module; The resource assessment module is responsible for a comprehensive assessment of currently available resources, including transportation tools (such as buses, taxis and shared bicycles), accommodation facilities (such as hotels, homestays and guesthouses), catering services, parking capacity, and scenic area reception capacity, and clarifying the total amount and distribution of various resources; the crowd flow identification module is responsible for real-time monitoring of the crowd density in the scenic area based on the crowd flow data uploaded by the data detection unit, judging whether congestion occurs by analyzing the crowd density, and automatically uploading alarm information when the preset threshold is reached; the emergency response module is responsible for preparing emergency plans in advance upon receiving the alarm information uploaded by the crowd flow identification module or the data of unforeseen events (such as extreme weather, traffic accidents) uploaded by the data monitoring unit, and immediately launching them once they occur to minimize the negative experience of tourists; the resource scheduling module is responsible for setting the goal of optimizing scheduling according to the results of resource evaluation, increasing the frequency and routes of public transportation to attract more passengers to use public transportation, and at the same time, guiding the reasonable diversion of private cars through price mechanisms (such as congestion fees and parking fees); the simulation module is responsible for testing different scheduling schemes through computer simulation technology before actual implementation to evaluate their effects and potential risks.

2. A global cultural tourism industry monitoring system and method according to claim 1, characterized in that: The human flow recognition module annotates the images collected by the camera, marks the center point of each passenger's head, records its two-dimensional coordinates and total number, and converts the annotated data into a density map, which is usually generated by convolving each delta function with a normalized one; a small weight matrix is ​​slid on the input data, and the dot product of the weight matrix and the corresponding part of the input data is calculated to generate feature information. The calculation method is as follows; Where yi,j is the value of the output feature map at position (i,j), Wm,n is the element of the weight matrix, Xi+m,j+n is the value of the input image at position (i+m,j+n), and M and N are the height and width of the weight matrix respectively; The VGG-16 pre-trained model is used as the front-end network to extract shallow features of the image. A multi-scale feature extraction module (MFEM) is introduced to process features of different scales through dilated convolutions. The feature map is upsampled using transposed convolutions to restore the spatial resolution and generate a high-resolution density map of the same size as the input image. The generated density map is integrated to obtain the estimated number of people in the crowd. The number of people can be estimated by summing all pixel values ​​in the density map: Where D(x,y) is the value of the density map at position (x,y).

3. A global cultural tourism industry monitoring system and method according to claim 1, characterized in that: The data monitoring unit includes a crawler system, a camera, an environmental sensor, a passenger flow counter, a data acquisition module, a data processing module and an intelligent analysis and prediction module.

4. A global cultural tourism industry monitoring system and method according to claim 3, characterized in that: The crawler system, camera, environmental sensor and passenger flow counter are respectively connected to the data acquisition module in one direction; the data acquisition module is connected to the data processing module in one direction; the data processing module is connected to the intelligent analysis and prediction module in one direction; the intelligent analysis and prediction module is connected to the resource evaluation module in one direction.

5. A global cultural tourism industry monitoring system and method according to claim 3, characterized in that: The crawler system is responsible for automatically capturing user comments and ratings on social media platforms. The data reflects the real experience and feelings of tourists. The web crawler also obtains information about the scenic spot from major travel booking platforms and travel guide websites, such as hotel reservations, ticket sales data, and user reviews, to understand market demand trends and provide a basis for the formulation of marketing strategies; the camera is responsible for installing high-definition cameras in roads, parking lots and other areas around the scenic spot, which can monitor traffic conditions in real time, including vehicle flow, vehicle speed, lane occupancy, passenger flow and safety hazards, and provide data support for the passenger flow identification module and resource scheduling module; the environmental sensor is responsible for sensors used to monitor environmental parameters such as air quality, temperature and humidity, and light intensity. These data provide data support for evaluating the carrying capacity of the scenic spot, the comfort of tourists, and the formulation of emergency plans; the passenger flow counter is responsible for installing passenger flow counters at key locations such as the entrance of the scenic spot and the parking lot, which can monitor the number of tourists entering and leaving in real time. These counters automatically record the number of people passing by through infrared and laser technology.

6. A global cultural tourism industry monitoring system and method according to claim 3, characterized in that: The data collection module is responsible for realizing all-round real-time collection of cultural tourism industry data through crawler systems, cameras, environmental sensors and passenger flow counters. These data include tourist flow statistics, consumption pattern analysis, social media APIs, online travel platform interfaces, public Wi-Fi hotspot tracking, scenic area environmental quality monitoring (such as air quality, noise level), and tourist satisfaction evaluation; the data processing module is responsible for cleaning, integrating and storing the collected data to confirm the accuracy and completeness of the data; the intelligent analysis and prediction module integrates a variety of artificial intelligence algorithms, including machine learning, deep learning and complex event processing (CEP) technology. It can not only identify the development trends and potential problems of the cultural tourism industry, but also predict market changes, providing a scientific basis for policy formulation and corporate strategic planning.

7. A global cultural tourism industry monitoring system and method according to claim 1, characterized in that: The background monitoring unit includes a visualization window, online traffic diversion and promotion, personalized recommendation and user interaction module; the simulation module is unidirectionally connected to the visualization window; the visualization window is unidirectionally connected to the online traffic diversion and promotion and personalized recommendation respectively; the online traffic diversion and promotion is unidirectionally connected to the user interaction module; the user interaction module is bidirectionally connected to the personalized recommendation; the user interaction module is unidirectionally connected to the crawler system.

8. A global cultural tourism industry monitoring system and method according to claim 7, characterized in that: The visualization window is responsible for converting complex data analysis results into intuitive and easy-to-understand charts, maps and dashboards, supporting multi-dimensional screening and operations. Users can customize views as needed and quickly obtain required information. In addition, this module also supports mobile access, so that managers can keep abreast of the latest developments in the cultural and tourism industry no matter where they are; the online traffic diversion and promotion is responsible for placing targeted advertisements on platforms frequently used by the target audience, improving the ranking of the official website on the search engine results page, and publishing high-quality blog articles and video content to attract tourists; the personalized recommendation is responsible for establishing a user portrait based on the user's search history, browsing behavior and preferences, and recommending relevant tourism products or services based on the user portrait.

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