Security comprehensive management and control method and system based on big data

Abstract

The invention relates to the technical field of security and protection management and control, in particular to a security and protection comprehensive management and control method and system based on big data. The method comprises the following steps: acquiring scenic spot information, analyzing the scenic spot information, and determining scenic spot nodes; according to the scenic spot nodes, determining the scenic spot carrying capacity; and obtaining a reservation request, and performing touring planning according to the scenic spot capacity and the reservation request to obtain a touring route. The tourist flow is optimized; and the sightseeing experience is improved. The reasonable capacity of each scenic spot is determined through a scientific method, overcrowding is avoided, the safety and comfort of tourists are guaranteed, and meanwhile the operation efficiency of the scenic spot is improved. The reservation data of the tourists are collected, the touring demands and preferences of the tourists are known, and a basis is provided for personalized touring planning and resource allocation. Clear tour paths and recommended journeys are provided for tourists, the satisfaction degree of the tourists is improved, and meanwhile real-time people stream guidance and regulation and control basis is provided for scenic spot management.

Description

Technical Field

[0001] The present application relates to the field of security management and control technology, and in particular to a comprehensive security management and control method and system based on big data. Background Art

[0002] With the rapid development of the tourism industry, especially in the context of popular attractions and large-scale tourism activities, the surge in the number of tourists has put forward higher and higher requirements for the management and safety of scenic spots. The management and scheduling of tourist flow, tour routes, reservation needs, etc. in scenic spots have become key factors in improving the operational efficiency of scenic spots and the experience of tourists.

[0003] Traditional scenic area management methods usually rely on manual scheduling and basic passenger flow monitoring, which makes it difficult to respond to the complex and changing tourist flow in the scenic area in real time. Especially when dealing with the surge in tourist flow during peak periods and emergency safety incidents, traditional methods are difficult to achieve accurate and efficient emergency response. Summary of the invention

[0004] The present application provides a comprehensive security management and control method and system based on big data to solve the above problems.

[0005] In a first aspect, the present application provides a comprehensive security management and control method based on big data, the method comprising: Acquire scenic spot information, analyze the scenic spot information, and determine scenic spot nodes; Determining the capacity of the scenic spot according to the scenic spot node; A reservation request is obtained, and a tour plan is performed according to the capacity of the scenic spot and the reservation request to obtain a tour route.

[0006] Through this solution, by integrating multi-source data, a complete scenic spot information database is established to provide basic data support for subsequent tour planning and crowd control. Identify key locations and areas within the scenic spot to provide a basis for determining the capacity of the scenic spot and tour route planning, which helps to optimize tourist flow and enhance the tour experience. Determine the reasonable capacity of each scenic spot through scientific methods to avoid overcrowding, ensure the safety and comfort of tourists, and improve the operational efficiency of the scenic spot. Collect tourists' reservation data, understand tourists' tour needs and preferences, and provide a basis for personalized tour planning and resource allocation. Provide tourists with clear tour routes and recommended itineraries to improve tourist satisfaction, and provide real-time crowd guidance and regulation basis for scenic spot management.

[0007] Optionally, performing tour planning according to the capacity of the scenic spot and the reservation request to obtain a tour route includes: Analyze the reservation request, determine the reservation time and the number of reservation persons; Analyze the scenic spot information to determine the scenic spot features of each scenic spot node; Acquire historical tour data, and determine the tour time of each scenic spot node according to the characteristics of the scenic spot and the historical tour data; According to the capacity of the scenic spot and the historical sightseeing data, predict the real-time change of the flow of people within a preset time period after the reservation time; According to the real-time crowd flow changes, the number of reservations and the tour time, a tour plan is performed to obtain a tour route.

[0008] Through this solution, by analyzing reservation requests, the scenic spot can grasp the visit time and number of tourists in advance, providing a data basis for subsequent resource allocation and crowd control. By analyzing the scenic spot information, the scenic spot can understand the characteristics and appeal of each scenic spot and provide tourists with more targeted tour suggestions. It helps to improve the tourists' tour experience, and at the same time, it can guide tourists to disperse to different scenic spots to avoid excessive concentration. By analyzing historical tour data, it is possible to understand the flow of people and tour time of each scenic spot in different time periods, and provide tourists with more accurate tour time estimates. By predicting the changes in the flow of people in future time periods, the scenic spot can make crowd control and safety plans in advance. It helps to avoid excessive concentration of tourists and reduce congestion and safety accidents. By comprehensively considering the real-time flow of people, the number of reservations and the tour time, the scenic spot can provide tourists with personalized tour route suggestions. It helps tourists avoid congestion, improve tour efficiency, and also improve tourists' tour satisfaction.

[0009] Optionally, the reservation request includes a tour selection; the tour planning is performed according to the real-time crowd flow change, the number of reservations and the tour time to obtain a tour route, including: analyzing the tour selections to determine tour preferences; Determine the intended attractions based on the tour preferences; Analyze the scenic spot information to determine the location of the intended scenic spot; Determine the unobstructed time period of the intended scenic spot according to the real-time crowd flow change and the sightseeing time; According to the number of reservations, the unobstructed time period and the location of the scenic spot, a tour plan is made to obtain a tour route.

[0010] Through this solution, by analyzing tourists' tour choices, scenic spots can understand tourists' points of interest and provide more personalized services. According to tourists' preferences, scenic spots can recommend suitable attractions to help tourists save time in choosing and improve tour efficiency. By determining the location of intended attractions, scenic spots can better guide the flow of people and allocate resources to avoid tourists getting lost or congested in the scenic area. By analyzing real-time changes in passenger flow and tour time, scenic spots can predict the peak passenger flow period of each attraction and adjust the tour plan accordingly to avoid tourists visiting during peak hours, thereby reducing congestion and waiting time. According to the number of reservations, unobstructed time periods and the location of attractions, scenic spots can plan the best tour routes for tourists, which helps tourists better plan their tour itineraries and improve tour efficiency. Through tour planning, scenic spots can provide tourists with personalized tour routes, including the recommended sequence of attractions, expected stay time, walking paths, etc.

[0011] Optionally, determining the intended attractions according to the tour preferences includes: Analyze the reservation request to determine the type of visitor; Determine whether to bind the visitor according to the visitor type; If it is determined to bind the tourist, the reservation request is analyzed to determine the identity of the tourist; Determine the intended attractions based on the identity of the tourists.

[0012] Through this solution, by analyzing reservation requests, scenic spots can identify different types of tourists, which helps scenic spots provide services and facilities that better meet the needs of tourists. Based on the type of tourists, scenic spots can decide whether to group or bind tourists for easier management and scheduling, such as planning unified routes. By analyzing reservation requests, scenic spots can identify and verify the identity of tourists to ensure the accuracy and security of tourist information. Combined with tourists' identity information and tour preferences, scenic spots can recommend and identify attractions that tourists are interested in, thereby improving tourists' tour satisfaction and experience.

[0013] Optionally, determining the unobstructed time period of the intended scenic spot according to the real-time crowd flow change and the sightseeing time includes: Determine whether there is congestion at the scenic spot within a preset time period according to the real-time change in the flow of people; If it is determined that there is congestion at the scenic spot, obtaining a site image corresponding to the historical tour data of the congested scenic spot, and determining the number of on-site tourists of the historical tour according to the site image; Determining the layout of the scenic spot according to the location of the scenic spot and the information of the scenic spot; Determine a dredging plan based on the layout of the scenic spot and the number of tourists on site; Determine the dredging time according to the dredging plan; The unobstructed time period of the intended scenic spot is determined according to the unobstructed time and the sightseeing time.

[0014] Through this solution, the dynamics of the flow of people in the scenic area can be monitored in real time, and potential congestion points can be discovered in time, providing a basis for subsequent unblocking work. Through historical tour data and on-site images, the causes of congestion can be analyzed, such as whether it is due to insufficient capacity of the scenic spot, unreasonable tour route design, etc., providing an intuitive reference for the design of unblocking solutions. The layout of scenic spots helps to analyze the flow patterns of tourists and provide spatial references for the design of unblocking solutions, such as adjusting tour routes or adding guide signs. Specific unblocking measures are formulated, such as temporarily adjusting tour routes, adding temporary guides, and limiting the number of tourists entering scenic spots, to alleviate congestion. By determining the unblocked time period, the scenic spot can provide tourists with the best tour time suggestions to avoid tourists arriving during congested periods, thereby improving the tour experience.

[0015] Optionally, after predicting the real-time crowd flow change within a preset time period after the reservation time according to the capacity of the scenic spot and the historical sightseeing data, the method further includes: Determine popular attractions and peak hours based on the real-time changes in crowd flow; Determine the location of security deployment based on the popular attractions; Determine high-intensity patrol periods based on the peak periods; A security deployment plan is determined based on the security deployment locations and the high-intensity patrol periods.

[0016] Through this solution, by real-time monitoring of changes in the flow of people, it is possible to accurately identify which attractions are popular choices for tourists and which time periods are peak times for tourists to visit, which helps scenic area managers to rationally allocate resources and optimize tour routes. Based on the identification of popular attractions, it is possible to determine the locations where security measures need to be strengthened, such as entrances, exits, and around attractions, to ensure the safety of tourists. By analyzing peak hours, it is possible to arrange to strengthen patrols during these crowded time periods to improve the efficiency and effectiveness of security work. Based on the comprehensive security deployment locations and high-intensity patrol periods, a comprehensive security deployment plan can be developed to ensure the safe operation of the scenic area.

[0017] Optionally, predicting the real-time change of crowd flow within a preset time period after the reservation time according to the capacity of the scenic spot and the historical sightseeing data includes: Determine the tour influencing factors of the reservation time and the impact of each tour influencing factor on the real-time flow of people at the scenic spot node according to the historical tour data; According to the influence of the tour and the influence of each tour influencing factor on the real-time flow of people at the scenic spot node, the real-time flow of people at the scenic spot node at different times is calculated using the following formula: ; in, Indicates time Real-time flow of people at scenic spots; Indicates the factors affecting the tourism The impact of real-time traffic flow at each scenic spot node; Indicates scenic spot nodes; Indicates time; Indicates the number of scenic spot nodes; Indicates the factors affecting the visit in time Time to scenic spot nodes The impact of According to the real-time flow of people at scenic spots at different times, the real-time flow of people within a preset period after the reservation time is predicted.

[0018] Through this solution, by analyzing historical data, it is possible to identify which factors have a significant impact on tourist flow, which helps scenic area managers understand tourist behavior patterns and predict future changes in passenger flow. By calculating the real-time passenger flow of scenic spots at different times, scenic area managers can understand the distribution and changing trends of passenger flow, providing a basis for optimizing tour routes and deploying security resources. The formula can comprehensively consider the impact of multiple tour influencing factors on the passenger flow of scenic spots, and provide more accurate prediction results. By predicting real-time passenger flow changes, scenic area managers can optimize tour routes, deploy security resources, and manage facilities in advance, improve the operational efficiency of the scenic area, reduce the inconvenience of tourists, and ensure the safety of tourists.

[0019] Optionally, the scenic spot information includes the location of the scenic spot entrance; and the tour planning is performed according to the number of reservations, the unobstructed time period and the location of the scenic spot to obtain a tour route, including: Determine the distance between any two intended attractions according to the locations of the attractions; Determine the priority of sightseeing among the intended attractions according to the entrance locations of the attractions and the distance between any two intended attractions; According to the location of the scenic spot, the unobstructed time period and the tour priority, a tour plan is performed to obtain a basic tour route; Predicting actual tour time based on the number of reservations and the historical tour data; According to the actual tour time, the basic tour route is adjusted to obtain a final tour route.

[0020] Through this solution, by calculating the distance between scenic spots, a reasonable tour route can be planned, which can reduce tourists' walking time and improve tour efficiency. According to the distance between scenic spots and tourists' preferences, the tour priority can be determined to ensure that tourists can visit the most interesting attractions within a limited time. Based on the location of scenic spots, unobstructed time periods and tour priorities, basic tour routes can be planned to help tourists avoid congestion during peak hours and improve the tour experience. Predicting the actual tour time by the number of reservations and historical tour data can help scenic area managers arrange tour routes reasonably to ensure that tourists complete the tour within the scheduled time. Adjusting the tour route according to the actual tour time can ensure that tourists can visit more attractions within a limited time and improve tour satisfaction.

[0021] Optionally, performing tour planning according to the location of the scenic spot, the unobstructed time period and the tour priority to obtain a basic tour route includes: Determine walking time based on the location of the scenic spot; Determine, based on the walking time, whether there is a situation where, when arriving at a desired scenic spot, the desired scenic spot is not within the unobstructed time period; If so, determining whether there are other scenic spot nodes between the two intended scenic spots according to the scenic spot information and the scenic spot location; If so, determining the best supplementary node according to the visiting time of the remaining scenic spot nodes and the locations of the remaining scenic spot nodes; According to the optimal supplementary node, the location of the scenic spot, the unobstructed time period and the tour priority, a tour planning is performed to obtain a basic tour route.

[0022] Through this solution, by calculating the walking distance and expected walking speed between scenic spots, the walking time of tourists from one scenic spot to another can be determined, thus providing basic data for tour route planning. Evaluating the relationship between walking time and the unobstructed time of scenic spots can help avoid peak hours when planning tour routes and improve tourists' tour experience. Finding other scenic spot nodes as supplements between scenic spots can provide more tour options and enrich tourists' tour experience. Selecting the best supplementary nodes can optimize the tour route, allowing tourists to avoid peak hours during the tour and visit more attractions at the same time. Comprehensively considering the location of scenic spots, unobstructed time periods, tour priorities and the best supplementary nodes, a basic tour route is planned to ensure that tourists can avoid peak hours during the tour and visit all interesting or important attractions at the same time.

[0023] In a second aspect, the present application provides a comprehensive security management and control system based on big data, the system comprising: An information analysis module, used to obtain scenic spot information, analyze the scenic spot information, and determine scenic spot nodes; An accommodation analysis module, used to determine the accommodation capacity of the scenic spot according to the scenic spot node; The route planning module is used to obtain a reservation request, and to carry out a tour planning according to the capacity of the scenic spot and the reservation request to obtain a tour route.

[0024] Optionally, the route planning module performs tour planning according to the capacity of the scenic spot and the reservation request, and when the tour route is obtained, is used to: Analyze the reservation request, determine the reservation time and the number of reservation persons; Analyze the scenic spot information to determine the scenic spot features of each scenic spot node; Acquire historical tour data, and determine the tour time of each scenic spot node according to the characteristics of the scenic spot and the historical tour data; According to the capacity of the scenic spot and the historical sightseeing data, predict the real-time change of the flow of people within a preset time period after the reservation time; According to the real-time crowd flow changes, the number of reservations and the tour time, a tour plan is performed to obtain a tour route.

[0025] Optionally, the reservation request includes a tour selection; the route planning module performs tour planning according to the real-time crowd flow change, the number of reservations and the tour time, and when the tour route is obtained, is used to: analyzing the tour selections to determine tour preferences; Determine the intended attractions based on the tour preferences; Analyze the scenic spot information to determine the location of the intended scenic spot; Determine the unobstructed time period of the intended scenic spot according to the real-time crowd flow change and the sightseeing time; According to the number of reservations, the unobstructed time period and the location of the scenic spot, a tour plan is made to obtain a tour route.

[0026] Optionally, when the route planning module determines the intended attractions according to the tour preferences, it is used to: Analyze the reservation request to determine the type of visitor; Determine whether to bind the visitor according to the visitor type; If it is determined to bind the tourist, the reservation request is analyzed to determine the identity of the tourist; Determine the intended attractions based on the identity of the tourists.

[0027] Optionally, when the route planning module determines the unobstructed time period of the intended scenic spot according to the real-time crowd flow change and the sightseeing time, it is used to: Determine whether there is congestion at the scenic spot within a preset time period according to the real-time change in the flow of people; If it is determined that there is congestion at the scenic spot, obtaining a site image corresponding to the historical tour data of the congested scenic spot, and determining the number of on-site tourists of the historical tour according to the site image; Determining the layout of the scenic spot according to the location of the scenic spot and the information of the scenic spot; Determine a dredging plan based on the layout of the scenic spot and the number of tourists on site; Determine the dredging time according to the dredging plan; The unobstructed time period of the intended scenic spot is determined according to the unobstructed time and the sightseeing time.

[0028] Optionally, the comprehensive security management and control system based on big data further includes a security deployment module, which is used to: Determine popular attractions and peak hours based on the real-time changes in crowd flow; Determine the location of security deployment based on the popular attractions; Determine high-intensity patrol periods based on the peak periods; A security deployment plan is determined based on the security deployment locations and the high-intensity patrol periods.

[0029] Optionally, when the route planning module predicts the real-time change of the flow of people within a preset period after the reservation time according to the capacity of the scenic spot and the historical sightseeing data, it is used to: Determine the tour influencing factors of the reservation time and the impact of each tour influencing factor on the real-time flow of people at the scenic spot node according to the historical tour data; According to the influence of the tour and the influence of each tour influencing factor on the real-time flow of people at the scenic spot node, the real-time flow of people at the scenic spot node at different times is calculated using the following formula: ; in, Indicates time Real-time flow of people at scenic spots; Indicates the factors affecting the tourism The impact of real-time traffic flow at each scenic spot node; Indicates scenic spot nodes; Indicates time; Indicates the number of scenic spot nodes; Indicates the factors affecting the visit in time Time to scenic spot nodes The impact of According to the real-time flow of people at scenic spots at different times, the real-time flow of people within a preset period after the reservation time is predicted.

[0030] Optionally, the scenic spot information includes the location of the scenic spot entrance; the route planning module performs tour planning according to the number of reservations, the unobstructed time period and the location of the scenic spot, and when the tour route is obtained, is used to: Determine the distance between any two intended attractions according to the locations of the attractions; Determine the priority of sightseeing among the intended attractions according to the entrance locations of the attractions and the distance between any two intended attractions; According to the location of the scenic spot, the unobstructed time period and the tour priority, a tour plan is performed to obtain a basic tour route; Predicting actual tour time based on the number of reservations and the historical tour data; According to the actual tour time, the basic tour route is adjusted to obtain a final tour route.

[0031] Optionally, the route planning module performs tour planning according to the location of the scenic spot, the unobstructed time period and the tour priority, and when a basic tour route is obtained, is used to: Determine the walking time according to the location of the scenic spot; determine whether a desired scenic spot is not within the unobstructed time period when arriving at the desired scenic spot according to the walking time; if so, determine whether there are other scenic spot nodes between the two desired scenic spots according to the scenic spot information and the scenic spot location; if so, determine the best supplementary node according to the visiting time of the other scenic spot nodes and the location of the other scenic spot nodes; perform tour planning according to the best supplementary node, the scenic spot location, the unobstructed time period and the tour priority to obtain a basic tour route. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flowchart of a comprehensive security management and control method based on big data provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a security integrated management and control system based on big data is provided for one embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0036] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0037] With the rapid development of the tourism industry, especially in the context of popular attractions and large-scale tourism activities, the surge in the number of tourists has put forward higher and higher requirements for the management and safety of scenic spots. The management and scheduling of tourist flow, tour routes, reservation needs, etc. in scenic spots have become key factors in improving the operational efficiency of scenic spots and the experience of tourists.

[0038] Traditional scenic area management methods usually rely on manual scheduling and basic passenger flow monitoring, which makes it difficult to respond to the complex and changing tourist flow in the scenic area in real time. Especially when dealing with the surge in tourist flow during peak periods and emergency safety incidents, traditional methods are difficult to achieve accurate and efficient emergency response.

[0039] Based on this, the present application provides a security integrated management and control method and system based on big data, which obtains scenic spot information, analyzes scenic spot information, and determines scenic spot nodes; determines the capacity of scenic spots according to scenic spot nodes; obtains reservation requests, and conducts tour planning according to the capacity of scenic spots and reservation requests to obtain tour routes. By integrating multi-source data, a complete scenic spot information database is established to provide basic data support for subsequent tour planning and crowd control. Identifying key locations and areas within scenic spots provides a basis for determining the capacity of scenic spots and tour route planning, which helps to optimize tourist flow and enhance the tour experience. Determine the reasonable capacity of each scenic spot through scientific methods to avoid overcrowding, ensure the safety and comfort of tourists, and improve the operational efficiency of scenic spots. Collect tourists' reservation data, understand tourists' tour needs and preferences, and provide a basis for personalized tour planning and resource allocation. Provide tourists with clear tour routes and recommended itineraries to improve tourist satisfaction, and provide real-time crowd guidance and regulation basis for scenic spot management.

[0040] Figure 1A schematic diagram of an application scenario provided by this application is used to deal with the surge in tourist traffic and emergency safety incidents during peak periods. Specifically, the method provided by this application is applied to any server, and the server interacts with the construction planning database and the reservation platform. The basic information inside the scenic area is collected using GIS technology from the construction planning database inside the scenic area, and the collected information is analyzed using data mining and machine learning algorithms. The complete scenic spot information database provides accurate basic data for tour planning and crowd control, ensuring the accuracy and real-time nature of planning decisions. Identify the key nodes in the scenic area, and calculate the maximum capacity of each scenic spot based on factors such as the physical area, facility capacity and safety standards of the scenic spot. Identifying the key locations and areas in the scenic spot helps to reasonably plan the tour route, optimize the flow of tourists, reduce congestion, and enhance the tour experience. Use historical data and real-time monitoring information to adjust the dynamic capacity of the scenic spot to adapt to the flow of tourists in different time periods. The reasonable capacity determined by scientific methods avoids overcrowding in the scenic area, ensures the safety and comfort of tourists, and improves operational efficiency. Collect tourists' reservation requests through reservation platforms such as the official website of the scenic spot and mobile applications. Collect tourists' reservation data, understand tourists' tour needs and preferences, and provide data support for personalized services. Summarize and analyze tourists' reservation requests to determine the overall needs and distribution of tourists. Combine the capacity of scenic spots and tourists' reservation requests, and use optimization algorithms to plan tour routes. Consider tourists' tour preferences and historical tour data to generate personalized tour routes. Provide tourists with clear tour paths and recommended itineraries, improve tourists' satisfaction, and enhance tourists' overall impression of the scenic spot.

[0041] For specific implementation methods, please refer to the following embodiments.

[0042] Figure 2 This is a flowchart of a security integrated management and control method based on big data provided by an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201, obtaining scenic spot information, analyzing the scenic spot information, and determining scenic spot nodes; Scenic spot information may be detailed information about each scenic spot in the scenic area, including the name, geographical location, historical background, feature introduction, opening hours, ticket price, visitor rating, etc.

[0043] Scenic spot nodes can be places with specific functions and significances in the scenic area, such as entrances, exits, important attractions, rest areas, catering service areas, etc.

[0044] Specifically, the basic information of scenic spots is collected through the Geographic Information System (GIS) within the scenic area, such as the geographical location of the scenic spots, the distribution of facilities, historical passenger flow data, etc. The collected scenic spot information is analyzed using data mining and machine learning algorithms to identify the key nodes of the scenic spots, such as entrances, exits, popular attractions, rest areas, etc.

[0045] S202, determining the capacity of the scenic spot according to the scenic spot nodes; The capacity of an attraction can be the maximum number of tourists that each attraction in the scenic area can accommodate at the same time.

[0046] Specifically, the maximum capacity of each scenic spot is calculated based on factors such as the physical area, facility capacity, safety standards, etc. The dynamic capacity of the scenic spot is adjusted using historical data and real-time monitoring information to adapt to the tourist flow in different time periods.

[0047] S203: Obtain a reservation request, make a tour plan based on the capacity of the scenic spot and the reservation request, and obtain a tour route.

[0048] The reservation request can be the tour reservation information submitted by tourists through the official channels of the scenic spot or other tourism service platforms, including the tour date, number of tourists, special needs, etc.

[0049] Tour planning can be the tour route and time arrangement designed for tourists based on factors such as the capacity of scenic spots, tourist reservation requests, and historical tour data.

[0050] The tour route can be the specific path that tourists take in the scenic area, such as the order of attractions that tourists will visit, the estimated duration of stay, and the mode of transportation.

[0051] Specifically, tourists' reservation requests are collected through official scenic spot websites, mobile applications and other channels, including information such as tour dates, number of people, preferences, etc. The reservation requests are aggregated and analyzed to determine the overall needs and distribution of tourists. Tour route planning is performed using optimization algorithms (such as genetic algorithms, simulated annealing algorithms, etc.) based on the capacity of scenic spots and tourist reservation requests. Taking into account tourists' tour preferences and historical tour data, personalized tour routes are generated, including recommended attractions, expected stay time, and optimal tour paths.

[0052] Through this solution, by integrating multi-source data, a complete scenic spot information database is established to provide basic data support for subsequent tour planning and crowd control. Identify key locations and areas within the scenic spot to provide a basis for determining the capacity of the scenic spot and tour route planning, which helps to optimize tourist flow and enhance the tour experience. Determine the reasonable capacity of each scenic spot through scientific methods to avoid overcrowding, ensure the safety and comfort of tourists, and improve the operational efficiency of the scenic spot. Collect tourists' reservation data, understand tourists' tour needs and preferences, and provide a basis for personalized tour planning and resource allocation. Provide tourists with clear tour routes and recommended itineraries to improve tourist satisfaction, and provide real-time crowd guidance and regulation basis for scenic spot management.

[0053] In some embodiments, reservation requests are analyzed to determine reservation time and number of reservations; scenic spot information is analyzed to determine the characteristics of each scenic spot node; historical tour data is obtained, and the tour time of each scenic spot node is determined based on the characteristics of the scenic spot and the historical tour data; based on the capacity of the scenic spot and the historical tour data, real-time changes in crowd flow within a preset time period after the reservation time are predicted; based on real-time changes in crowd flow, the number of reservations and the tour time, tour planning is carried out to obtain a tour route.

[0054] The reservation time can be the specific date and time that the tourist plans to visit the scenic spot, and is usually booked by the tourist through the scenic spot’s official website, mobile application or other reservation platforms.

[0055] The number of reservations can be the number of tourists who have made reservations to visit a scenic spot, including adults, children, etc. This information is very important for crowd control and resource allocation in the scenic spot.

[0056] The characteristics of an attraction can be the unique features of the attraction or the specific factors that attract tourists, such as historical sites, natural scenery, cultural displays, etc.

[0057] Historical tour data may include data such as the tourist flow, tour mode, length of stay, and tourist feedback of a scenic spot over a period of time in the past.

[0058] The visiting time can be the average time that tourists stay in the scenic spot, which can be estimated based on factors such as the size of the scenic spot, the speed of tourists' visiting and the attractiveness of the scenic spot.

[0059] Real-time crowd flow changes can be real-time changes in the number of tourists in a scenic area.

[0060] Specifically, extract the reservation time (date, time period) and number of reservations from the reservation request. Analyze the tourist preference information in the reservation request, such as attraction selection, activity participation, special needs, etc. Analyze the attraction information to determine the characteristics of each attraction node, such as historical background, cultural value, natural landscape, etc. Estimate the average visit time of each attraction node based on the characteristics of the attraction and historical tour data. Collect historical tour data, including the number of tourists, visit time, and crowd distribution. Analyze historical data to identify tourist visit patterns, peak traffic hours, etc. Based on historical tour data and real-time monitoring data, build a prediction model, such as time series analysis, machine learning model, etc. Use the prediction model to predict the real-time crowd flow changes within a preset period after the reservation time. Select a suitable tour planning algorithm, such as genetic algorithm, ant colony algorithm, etc. Dynamically adjust the tour route based on real-time crowd monitoring data to avoid congestion and waiting. Generate a personalized tour route based on the reservation request and preferences of tourists. Push the tour route to tourists through scenic spot APP, SMS, etc.

[0061] Through this solution, by analyzing reservation requests, the scenic spot can grasp the visit time and number of tourists in advance, providing a data basis for subsequent resource allocation and crowd control. By analyzing the scenic spot information, the scenic spot can understand the characteristics and appeal of each scenic spot and provide tourists with more targeted tour suggestions. It helps to improve the tourists' tour experience, and at the same time, it can guide tourists to disperse to different scenic spots to avoid excessive concentration. By analyzing historical tour data, it is possible to understand the flow of people and tour time of each scenic spot in different time periods, and provide tourists with more accurate tour time estimates. By predicting the changes in the flow of people in future time periods, the scenic spot can make crowd control and safety plans in advance. It helps to avoid excessive concentration of tourists and reduce congestion and safety accidents. By comprehensively considering the real-time flow of people, the number of reservations and the tour time, the scenic spot can provide tourists with personalized tour route suggestions. It helps tourists avoid congestion, improve tour efficiency, and also improve tourists' tour satisfaction.

[0062] In some embodiments, tour selections are analyzed to determine tour preferences; based on the tour preferences, intended attractions are determined; attraction information is analyzed to determine the locations of intended attractions; based on real-time changes in passenger flow and tour time, unobstructed time periods for intended attractions are determined; tour planning is performed based on the number of reservations, unobstructed time periods and attraction locations to obtain tour routes.

[0063] Tour preferences can be derived based on historical tour behavior analysis, such as the types of attractions that tourists often visited in the past, attractions with high ratings, etc.

[0064] The intended attractions can be the attractions specified by the tourists when making a reservation, or the attractions recommended by analyzing the tourists' travel preferences and historical data.

[0065] The location of a scenic spot may be a specific location of the scenic spot in geographic space, usually including latitude and longitude coordinates or a location description relative to other landmarks in the scenic area.

[0066] The smooth period can be the time period when the number of tourists in the scenic area is small, the sightseeing experience is good, and the flow of people is relatively smooth. It is based on historical data analysis, such as the fluctuation of the number of tourists in a certain scenic spot in a specific time period, or the flow of people in the current period determined by real-time monitoring data.

[0067] Specifically, data mining technology is used to analyze tourists' tour choices and identify tourists' preferences, such as preferences for natural landscapes, historical sites, and cultural activities. Based on tourists' tour preferences, recommendation algorithms such as collaborative filtering and content-based recommendations are used to select attractions that meet tourists' interests from the scenic spot information database. The specific location of the intended attractions is located using the geographic information system (GIS), including latitude and longitude coordinates, relative position in the scenic area, etc. The location of the intended attractions is analyzed, considering factors such as its relative distance from other attractions in the scenic area and traffic convenience. The flow of people in the scenic area is obtained through real-time monitoring equipment such as cameras and sensors. Real-time flow of people data is analyzed to identify the unobstructed time period of each attraction, that is, the time period with less traffic and better tour experience. The expected flow of people at each attraction is calculated based on the number of reservations and the capacity of the attraction. The best path from the tourist starting point to the intended attraction is planned using path planning algorithms such as the Dijkstra algorithm and the A* algorithm. Based on the planning results, a tour route is generated, including the recommended sequence of attractions, expected stay time, walking path, etc.

[0068] Through this solution, by analyzing tourists' tour choices, scenic spots can understand tourists' points of interest and provide more personalized services. According to tourists' preferences, scenic spots can recommend suitable attractions to help tourists save time in choosing and improve tour efficiency. By determining the location of intended attractions, scenic spots can better guide the flow of people and allocate resources to avoid tourists getting lost or congested in the scenic area. By analyzing real-time changes in passenger flow and tour time, scenic spots can predict the peak passenger flow period of each attraction and adjust the tour plan accordingly to avoid tourists visiting during peak hours, thereby reducing congestion and waiting time. According to the number of reservations, unobstructed time periods and the location of attractions, scenic spots can plan the best tour routes for tourists, which helps tourists better plan their tour itineraries and improve tour efficiency. Through tour planning, scenic spots can provide tourists with personalized tour routes, including the recommended sequence of attractions, expected stay time, walking paths, etc.

[0069] In some embodiments, the reservation request is analyzed to determine the type of tourist; based on the type of tourist, it is determined whether to bind the tourist; if it is determined that the tourist is to be bound, the reservation request is analyzed to determine the identity of the tourist; based on the identity of the tourist, the intended attractions are determined.

[0070] Tourist types can be classified according to their specific attributes or behavioral characteristics.

[0071] Tourist binding can be used to facilitate management and service, by grouping tourists with the same characteristics into a group or team and managing them uniformly during the tour.

[0072] The tourist identity may be the personal identity information of the tourist when visiting a scenic spot.

[0073] Specifically, collect tourists' reservation request information, including tour time, number of people, special needs, etc. Use data analysis techniques, such as cluster analysis, machine learning classification algorithms, etc. to identify the types of tourists, such as family tourists, couple tourists, group tourists, etc. Determine whether tourists need to be bound based on the scenic area's operational needs and tourist types. For example, for group tourists, binding may be required for unified management and scheduling. Use tools such as rule engines or decision trees to make decisions on whether to bind based on the type of tourists and the actual situation of the scenic area. For tourists who need to be bound, determine the identity of the tourists through the information in the reservation request (such as name, contact information, etc.). Verify the accuracy of the tourist's identity information through SMS verification, email confirmation, etc. Analyze the attractions that tourists may be interested in based on their tour preferences and identity information.

[0074] Through this solution, by analyzing reservation requests, scenic spots can identify different types of tourists, which helps scenic spots provide services and facilities that better meet the needs of tourists. Based on the type of tourists, scenic spots can decide whether to group or bind tourists for easier management and scheduling, such as planning unified routes. By analyzing reservation requests, scenic spots can identify and verify the identity of tourists to ensure the accuracy and security of tourist information. Combined with tourists' identity information and tour preferences, scenic spots can recommend and identify attractions that tourists are interested in, thereby improving tourists' tour satisfaction and experience.

[0075] In some embodiments, based on the real-time changes in crowd flow, it is determined whether there is congestion at a tourist attraction within a preset time period; if it is determined that there is congestion at the tourist attraction, an on-site image corresponding to the historical tour data of the congested tourist attraction is obtained, and the number of on-site tourists for the historical tour is determined based on the on-site image; the layout of the tourist attraction is determined based on the location and information of the tourist attraction; a clearing plan is determined based on the layout of the tourist attraction and the number of on-site tourists; based on the clearing plan, the clearing time is determined; based on the clearing time and the tour time, the unblocked time period of the intended tourist attraction is determined.

[0076] Scenic spot congestion can be a phenomenon in which the number of tourists in one or more scenic spots in a scenic area exceeds its capacity, resulting in slow or stagnant tourist flow. Historical tour data can be a record of tourist visits to a scenic spot over a period of time in the past, including information such as the number of tourists, visit time, and source of tourists. On-site images can be real-time or historical pictures of scenic spots taken by cameras and other equipment. The number of on-site tourists can be the number of tourists at a scenic spot or scenic spot within a certain period of time. Scenic spot layout can be the spatial arrangement of various scenic spots, facilities, and tour routes in a scenic spot. A dredging plan can be a series of measures and action plans formulated to solve the problem of congestion in scenic spots. The dredging time can be the time period required to implement the dredging plan. The unblocked period can be a time period when there are fewer tourists in the scenic spot, the tour experience is better, and the flow of people is relatively unblocked.

[0077] Specifically, real-time crowd flow data is collected through sensors, cameras and other equipment installed in the scenic area. Data analysis and visualization tools, such as real-time data flow analysis and heat maps, are used to monitor the distribution and flow of crowds in the scenic area. Through the preset congestion threshold or algorithm model, it is identified whether there is congestion in the scenic spot within the preset time period. The tour data of the congested scenic spot, including the number of tourists and the tour time, are queried from the historical database. According to the timestamp of the historical tour data, the corresponding on-site image is obtained from the image storage system. The geographical location and surrounding environment of the scenic spot are analyzed using GIS tools. The layout of the scenic spot is planned based on the scenic spot information and historical data, including the tour route, rest area, service facilities, etc. Based on the layout of the scenic spot and the number of tourists on site, a dredging plan is designed, including adjusting the tour route, adding service facilities, guiding the flow of tourists, etc. The effect of the dredging plan is tested by simulation software to ensure the feasibility and effectiveness of the plan. According to the dredging plan and real-time crowd flow data, the time required for dredging is predicted. The dredging plan can also be a process of waiting for the crowd flow to be automatically dredged when no action is taken. According to the time required for dredging, a detailed timetable is formulated, including the start and end time points of dredging. Combine the unblocking time and the visiting time to analyze and determine the unblocking time of the intended scenic spot. According to the real-time changes in the flow of people and the unblocking effect, the unblocking time is dynamically adjusted to ensure that tourists can visit smoothly.

[0078] Through this solution, the dynamics of the flow of people in the scenic area can be monitored in real time, and potential congestion points can be discovered in time, providing a basis for subsequent unblocking work. Through historical tour data and on-site images, the causes of congestion can be analyzed, such as whether it is due to insufficient capacity of the scenic spot, unreasonable tour route design, etc., providing an intuitive reference for the design of unblocking solutions. The layout of scenic spots helps to analyze the flow patterns of tourists and provide spatial references for the design of unblocking solutions, such as adjusting tour routes or adding guide signs. Specific unblocking measures are formulated, such as temporarily adjusting tour routes, adding temporary guides, and limiting the number of tourists entering scenic spots, to alleviate congestion. By determining the unblocked time period, the scenic spot can provide tourists with the best tour time suggestions to avoid tourists arriving during congested periods, thereby improving the tour experience.

[0079] In some embodiments, popular attractions and peak hours are determined based on real-time changes in passenger flow; security deployment locations are determined based on popular attractions; high-intensity patrol periods are determined based on peak periods; and security deployment plans are determined based on security deployment locations and high-intensity patrol periods.

[0080] Popular attractions can be the attractions that attract the largest number of tourists in a scenic area, usually places with special landscapes, cultural values ​​or entertainment facilities. Peak hours can be the time period of the day or year when the tourist flow of a scenic area or popular attractions reaches its peak. Security deployment locations can be the locations of security personnel and facilities set up in specific areas to maintain the safety of the scenic area. High-intensity patrol periods can be the time periods when the frequency and intensity of security patrols are increased within a specific time period in order to improve the safety level of the scenic area. Security deployment plans can be a series of security measures and action plans formulated to maintain the safety of the scenic area.

[0081] Specifically, collect and record the maximum capacity of each scenic spot, which is the basic data for predicting changes in passenger flow. Collect the visitor records of tourists in the past period of time, including the number of tourists, visit time, and visit routes. Clean the collected data, remove outliers and erroneous data, and ensure the quality of the data. Use statistical analysis methods to analyze historical visit data and identify trends and patterns in passenger flow changes. According to historical visit data, establish prediction models, such as time series models and regression analysis models, to predict future changes in passenger flow. According to the capacity of scenic spots and historical data, set the parameters of the model, such as seasonal adjustments and holiday impacts. Collect passenger flow data in the scenic area in real time through cameras, sensors and other equipment. Perform real-time analysis on real-time data to monitor changes in passenger flow. According to real-time passenger flow data, continuously adjust the prediction model to improve the accuracy of the prediction. According to real-time passenger flow data, continuously adjust the prediction model to improve the accuracy of the prediction. According to the prediction results, adjust the security deployment location and patrol time to ensure the safety of tourists. According to the predicted changes in passenger flow, optimize the tour route to avoid congestion.

[0082] Through this solution, by real-time monitoring of changes in the flow of people, it is possible to accurately identify which attractions are popular choices for tourists and which time periods are peak times for tourists to visit, which helps scenic area managers to rationally allocate resources and optimize tour routes. Based on the identification of popular attractions, it is possible to determine the locations where security measures need to be strengthened, such as entrances, exits, and around attractions, to ensure the safety of tourists. By analyzing peak hours, it is possible to arrange to strengthen patrols during these crowded time periods to improve the efficiency and effectiveness of security work. Based on the comprehensive security deployment locations and high-intensity patrol periods, a comprehensive security deployment plan can be developed to ensure the safe operation of the scenic area.

[0083] In some embodiments, based on historical tour data, the tour influencing factors of the reservation time and the impact of each tour influencing factor on the real-time flow of people at the scenic spot node are determined; based on the tour influence and the impact of each tour influencing factor on the real-time flow of people at the scenic spot node, the real-time flow of people at the scenic spot node at different times is calculated using the following formula (1): (1); in, Indicates time Real-time flow of people at scenic spots; Indicates the factors affecting the tourism The impact of real-time traffic flow at each scenic spot node; Indicates scenic spot nodes; Indicates time; Indicates the number of scenic spot nodes; Indicates the factors affecting the visit in time Time to scenic spot nodes The impact of According to the real-time flow of people at scenic spots at different times, the real-time flow changes within the preset time period after the reservation time are predicted.

[0084] Tourist influencing factors can be various factors that may affect tourists' sightseeing behavior in scenic spots, such as weather conditions, holiday arrangements, special events, tourism promotion, seasonal factors, traffic conditions, scenic spot popularity, tourist preferences, scenic spot policies, etc.

[0085] Real-time traffic volume can be the actual number of tourists in a scenic area or its specific attractions at a specific time point or time period.

[0086] Specifically, collect historical visitor data of scenic spots, including the number of tourists, visit time, and visit routes. Collect data on the maximum capacity of each scenic spot. Analyze historical data to determine factors that may affect the real-time flow of people at scenic spots, such as weather, holidays, special events, etc. Assess the degree of influence of each visitor factor on the flow of people at scenic spots and determine the weight. Formula (1) is used to calculate the real-time flow of people at scenic spots at different times. In formula (1), the factors affecting the flow of people at scenic spots are decomposed into multiple independent influencing factors. Each influencing factor Represents the degree of influence of a specific tourist influencing factor on the flow of people at the scenic spot node. By weighted summation, each influencing factor is multiplied by its corresponding influence value p(x_i,t), and then these products are added. It reflects the relative importance of each influencing factor on the flow of people, and the impact value It means at a specific time When The actual impact of and weight , can dynamically predict different time Time and place nodes This method takes into account the various factors that affect the flow of people and the changes of these factors over time, thereby improving the accuracy and real-time nature of the prediction. Indicates a comprehensive evaluation of all influencing factors to obtain the time Time and place nodes Real-time traffic flow . This comprehensive evaluation can more comprehensively reflect the various factors that affect the flow of people and reduce the impact of a single factor on the prediction results. Integrate real-time flow data, weather data, holiday information, etc. into the calculation process. Use historical tour data to train prediction models, such as time series models, machine learning models, etc. According to the trained model, predict the real-time flow changes within the preset time period after the reservation time. According to the predicted flow changes, optimize the tour route to avoid congestion. According to the prediction results, deploy security resources in advance to ensure the safety of tourists. According to the predicted flow of people, adjust the opening hours and capacity of scenic facilities to improve operational efficiency.

[0087] Through this solution, by analyzing historical data, it is possible to identify which factors have a significant impact on tourist flow, which helps scenic area managers understand tourist behavior patterns and predict future changes in passenger flow. By calculating the real-time passenger flow of scenic spots at different times, scenic area managers can understand the distribution and changing trends of passenger flow, providing a basis for optimizing tour routes and deploying security resources. The formula can comprehensively consider the impact of multiple tour influencing factors on the passenger flow of scenic spots, and provide more accurate prediction results. By predicting real-time passenger flow changes, scenic area managers can optimize tour routes, deploy security resources, and manage facilities in advance, improve the operational efficiency of the scenic area, reduce the inconvenience of tourists, and ensure the safety of tourists.

[0088] In some embodiments, the distance between any two intended attractions is determined based on the location of the attractions; the tour priority between the intended attractions is determined based on the location of the attraction entrance and the distance between any two intended attractions; tour planning is carried out based on the location of the attractions, unobstructed time periods and tour priorities to obtain a basic tour route; the actual tour time is predicted based on the number of reservations and historical tour data; the basic tour route is adjusted based on the actual tour time to obtain a final tour route.

[0089] The distance between two attractions can be the spatial distance between two attractions, usually in meters. The tour priority can be the importance ranking of the order of attractions based on factors such as tourists' preferences, characteristics of attractions, seasonality, etc. The basic tour route can be a preliminary tour route planned based on factors such as the location of the attractions, tour priority, and unobstructed time. The actual tour time can be the actual time tourists spend in the scenic area, including the time spent at each attraction and the time on the road.

[0090] Specifically, collect the entrance location information of each scenic spot so that tourists' entry and exit can be considered when planning the tour route. Use GPS or other positioning technology to determine the actual distance between scenic spots and provide basic data for tour route planning. Calculate the tour priority between scenic spots and determine the tour order based on factors such as the distance between scenic spots, the popularity of scenic spots, and tourists' preferences. Consider the unblocked time of scenic spots and plan a basic tour route to ensure that tourists avoid congested areas during peak tour hours. Combined with the tour priority, arrange the scenic spots in order to form a reasonable tour route. Predict the average time tourists stay at scenic spots based on the number of reservations and historical tour data. Analyze historical tour data to understand the time tourists stay at different scenic spots so as to more accurately predict the actual tour time. Adjust the basic tour route based on the predicted actual tour time to ensure that tourists can complete the tour within the scheduled time. Consider the tour time and optimize the tour route to avoid tourists missing important attractions or experiences due to time constraints. Comprehensively consider factors such as the location of scenic spots, unblocked time, tour priority, number of reservations, and actual tour time, adjust the basic tour route, and obtain the final tour route.

[0091] Through this solution, by calculating the distance between scenic spots, a reasonable tour route can be planned, which can reduce tourists' walking time and improve tour efficiency. According to the distance between scenic spots and tourists' preferences, the tour priority can be determined to ensure that tourists can visit the most interesting attractions within a limited time. Based on the location of scenic spots, unobstructed time periods and tour priorities, basic tour routes can be planned to help tourists avoid congestion during peak hours and improve the tour experience. Predicting the actual tour time by the number of reservations and historical tour data can help scenic area managers arrange tour routes reasonably to ensure that tourists complete the tour within the scheduled time. Adjusting the tour route according to the actual tour time can ensure that tourists can visit more attractions within a limited time and improve tour satisfaction.

[0092] In some embodiments, the walking time is determined based on the location of the scenic spot; based on the walking time, it is determined whether a desired scenic spot is not within a smooth period when arriving at the desired scenic spot; if so, it is determined whether there are other scenic spot nodes between the two intended scenic spots based on the scenic spot information and the scenic spot location; if so, the best supplementary node is determined based on the tour time of the other scenic spot nodes and the location of the other scenic spot nodes; based on the best supplementary node, the scenic spot location, the smooth period and the tour priority, a tour plan is carried out to obtain a basic tour route.

[0093] Walking time can be the time it takes for tourists to walk from one attraction to another, usually measured in minutes.

[0094] The best supplementary nodes can be one or more attractions between two intended attractions, which can serve as additional stops in the tour route to help tourists avoid peak hours or increase their tour experience.

[0095] Specifically, use a geographic information system (GIS) or map service API to obtain the distance between attractions, and calculate the walking time based on the average walking speed of tourists. Analyze historical data and real-time monitoring data to determine the smooth time period for each attraction, and then check whether the time when tourists arrive at the intended attraction coincides with the smooth time period. If the intended attraction is not within the smooth time period, use GIS or map service API to search for other attraction nodes between the two intended attractions. Select the best supplementary node based on the tour time and location of the remaining attraction nodes, and whether they are in the smooth time period. Considering the best supplementary node, attraction location, smooth time period and tour priority, use an algorithm to plan a basic tour route.

[0096] Through this solution, by calculating the walking distance and expected walking speed between scenic spots, the walking time of tourists from one scenic spot to another can be determined, thus providing basic data for tour route planning. Evaluating the relationship between walking time and the unobstructed time of scenic spots can help avoid peak hours when planning tour routes and improve tourists' tour experience. Finding other scenic spot nodes as supplements between scenic spots can provide more tour options and enrich tourists' tour experience. Selecting the best supplementary nodes can optimize the tour route, allowing tourists to avoid peak hours during the tour and visit more attractions at the same time. Comprehensively considering the location of scenic spots, unobstructed time periods, tour priorities and the best supplementary nodes, a basic tour route is planned to ensure that tourists can avoid peak hours during the tour and visit all interesting or important attractions at the same time.

[0097] Figure 3 A schematic diagram of the structure of a security integrated management and control system based on big data is provided in one embodiment of the present application, such as Figure 3 As shown, the big data-based integrated security management and control system 300 of this embodiment includes: an information analysis module 301, a containment analysis module 302, and a route planning module 303.

[0098] The information analysis module 301 is used to obtain scenic spot information, analyze the scenic spot information, and determine scenic spot nodes; The accommodation analysis module 302 is used to determine the accommodation capacity of the scenic spot according to the scenic spot node; The route planning module 303 is used to obtain a reservation request, perform a tour planning according to the capacity of the scenic spot and the reservation request, and obtain a tour route.

[0099] Optionally, the route planning module 303 performs tour planning based on the capacity of the scenic spot and the reservation request, and when the tour route is obtained, it is used to: analyze the reservation request to determine the reservation time and the number of reservations; analyze the scenic spot information to determine the scenic spot characteristics of each scenic spot node; obtain historical tour data, and determine the tour time of each scenic spot node based on the scenic spot characteristics and the historical tour data; predict the real-time crowd flow changes within a preset time period after the reservation time based on the scenic spot capacity and the historical tour data; perform tour planning based on the real-time crowd flow changes, the number of reservations and the tour time to obtain a tour route.

[0100] Optionally, the reservation request includes tour selection; the route planning module 303 performs tour planning according to the real-time crowd flow changes, the number of reservations and the tour time, and when the tour route is obtained, it is used to: analyze the tour selection and determine the tour preferences; determine the intended attractions according to the tour preferences; analyze the attraction information and determine the location of the intended attractions; determine the unobstructed time period of the intended attractions according to the real-time crowd flow changes and the tour time; perform tour planning according to the number of reservations, the unobstructed time period and the location of the attraction to obtain a tour route.

[0101] Optionally, when the route planning module 303 determines the intended attractions based on the tour preferences, it is used to: analyze the reservation request to determine the type of tourist; determine whether to bind the tourist based on the type of tourist; if it is determined that the tourist is to be bound, analyze the reservation request to determine the identity of the tourist; and determine the intended attractions based on the identity of the tourist.

[0102] Optionally, when the route planning module 303 determines the unobstructed time period of the intended scenic spot based on the real-time crowd flow changes and the tour time, it is used to: determine whether there is congestion at the scenic spot within a preset time period based on the real-time crowd flow changes; if it is determined that there is congestion at the scenic spot, obtain the on-site image corresponding to the historical tour data of the congested scenic spot, and determine the number of on-site tourists for the historical tour based on the on-site image; determine the layout of the scenic spot based on the location of the scenic spot and the scenic spot information; determine the unblocking plan based on the scenic spot layout and the number of on-site tourists; determine the unblocking time based on the unblocking plan; determine the unblocking time based on the unblocking time and the tour time.

[0103] Optionally, the big data-based integrated security management and control system 300 also includes a security deployment module 304, which is used to: determine popular attractions and peak hours based on the real-time changes in passenger flow; determine security deployment locations based on the popular attractions; determine high-intensity patrol periods based on the peak hours; determine a security deployment plan based on the security deployment locations and the high-intensity patrol periods.

[0104] Optionally, when the route planning module 303 predicts the change of real-time crowd flow within a preset time period after the reservation time according to the capacity of the scenic spot and the historical tour data, it is used to: determine the tour influencing factors of the reservation time and the influence of each tour influencing factor on the real-time crowd flow of the scenic spot node according to the historical tour data; calculate the real-time crowd flow of the scenic spot node at different times according to the tour influence and the influence of each tour influencing factor on the real-time crowd flow of the scenic spot node, using the following formula: ; in, Indicates time Real-time flow of people at scenic spots; Indicates the factors affecting the tourism The impact of real-time traffic flow at each scenic spot node; Indicates scenic spot nodes; Indicates time; Indicates the number of scenic spot nodes; Indicates the factors affecting the visit in time Time to scenic spot nodes The impact of According to the real-time flow of people at scenic spots at different times, the real-time flow of people within a preset period after the reservation time is predicted.

[0105] Optionally, the scenic spot information includes the location of the scenic spot entrance; the route planning module 303 performs tour planning according to the number of reservations, the unobstructed time period and the location of the scenic spot, and when the tour route is obtained, it is used to: determine the distance between any two intended scenic spots according to the location of the scenic spot; determine the tour priority between the intended scenic spots according to the location of the scenic spot entrance and the distance between any two intended scenic spots; perform tour planning according to the location of the scenic spot, the unobstructed time period and the tour priority to obtain a basic tour route; predict the actual tour time according to the number of reservations and the historical tour data; adjust the basic tour route according to the actual tour time to obtain the final tour route.

[0106] Optionally, the route planning module 303 performs tour planning according to the location of the scenic spot, the unobstructed time period and the tour priority, and when a basic tour route is obtained, it is used to: determine the walking time according to the location of the scenic spot; determine whether a desired scenic spot is not within the unobstructed time period when arriving at the desired scenic spot according to the walking time; if so, determine whether there are other scenic spot nodes between the two intended scenic spots according to the scenic spot information and the location of the scenic spot; if so, determine the best supplementary node according to the tour time of the other scenic spot nodes and the location of the other scenic spot nodes; perform tour planning according to the best supplementary node, the location of the scenic spot, the unobstructed time period and the tour priority to obtain a basic tour route.

[0107] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A comprehensive security management and control method based on big data, characterized in that: include: Acquire scenic spot information, analyze the scenic spot information, and determine scenic spot nodes; Determining the capacity of the scenic spot according to the scenic spot node; A reservation request is obtained, and a tour plan is performed according to the capacity of the scenic spot and the reservation request to obtain a tour route.

2. The method according to claim 1, characterized in that The step of performing tour planning according to the capacity of the scenic spot and the reservation request to obtain a tour route includes: Analyze the reservation request, determine the reservation time and the number of reservation persons; Analyze the scenic spot information to determine the scenic spot features of each scenic spot node; Acquire historical tour data, and determine the tour time of each scenic spot node according to the characteristics of the scenic spot and the historical tour data; According to the capacity of the scenic spot and the historical sightseeing data, predict the real-time change of the flow of people within a preset time period after the reservation time; According to the real-time crowd flow changes, the number of reservations and the tour time, a tour plan is performed to obtain a tour route.

3. The method according to claim 2, characterized in that The reservation request includes a tour selection; the tour planning is performed according to the real-time crowd flow change, the number of reservations and the tour time to obtain a tour route, including: analyzing the tour selections to determine tour preferences; Determine the intended attractions based on the tour preferences; Analyze the scenic spot information to determine the location of the intended scenic spot; Determine the unobstructed time period of the intended scenic spot according to the real-time crowd flow change and the sightseeing time; According to the number of reservations, the unobstructed time period and the location of the scenic spot, a tour plan is made to obtain a tour route.

4. The method according to claim 3, characterized in that Determining the intended attractions according to the tour preferences includes: Analyze the reservation request to determine the type of visitor; Determine whether to bind the visitor according to the visitor type; If it is determined to bind the tourist, the reservation request is analyzed to determine the identity of the tourist; Determine the intended attractions based on the identity of the tourists.

5. The method according to claim 3, characterized in that: The step of determining the unobstructed time period of the intended scenic spot according to the real-time crowd flow change and the sightseeing time includes: Determine whether there is congestion at the scenic spot within a preset time period according to the real-time change in the flow of people; If it is determined that there is congestion at the scenic spot, obtaining a site image corresponding to the historical tour data of the congested scenic spot, and determining the number of on-site tourists of the historical tour according to the site image; Determining the layout of the scenic spot according to the location of the scenic spot and the information of the scenic spot; Determine a dredging plan based on the layout of the scenic spot and the number of tourists on site; Determine the dredging time according to the dredging plan; The unobstructed time period of the intended scenic spot is determined according to the unobstructed time and the sightseeing time.

6. The method according to claim 2, characterized in that After predicting the real-time crowd flow changes within a preset time period after the reservation time according to the capacity of the scenic spot and the historical sightseeing data, the method further includes: Determine popular attractions and peak hours based on the real-time changes in crowd flow; Determine the location of security deployment based on the popular attractions; Determine high-intensity patrol periods based on the peak periods; A security deployment plan is determined based on the security deployment locations and the high-intensity patrol periods.

7. The method according to claim 2, characterized in that The predicting of the real-time crowd flow changes within a preset time period after the reservation time according to the capacity of the scenic spot and the historical sightseeing data includes: Determine the tour influencing factors of the reservation time and the impact of each tour influencing factor on the real-time flow of people at the scenic spot node according to the historical tour data; According to the influence of the tour and the influence of each tour influencing factor on the real-time flow of people at the scenic spot node, the real-time flow of people at the scenic spot node at different times is calculated using the following formula: ； in, Indicates time Real-time flow of people at scenic spots; Indicates the factors affecting the tourism The impact of real-time traffic flow at each scenic spot node; Indicates scenic spot nodes; Indicates time; Indicates the number of scenic spot nodes; Indicates the factors affecting the visit in time Time to scenic spot nodes The impact of According to the real-time flow of people at scenic spots at different times, the real-time flow of people within a preset period after the reservation time is predicted.

8. The method according to claim 3, characterized in that The scenic spot information includes the location of the scenic spot entrance; the tour planning is performed according to the number of reservations, the unobstructed time period and the location of the scenic spot to obtain a tour route, including: Determine the distance between any two intended attractions according to the locations of the attractions; Determine the tour priority between the intended attractions according to the locations of the attraction entrances and the distance between any two intended attractions; According to the location of the scenic spot, the unobstructed time period and the tour priority, a tour plan is performed to obtain a basic tour route; Predicting actual tour time based on the number of reservations and the historical tour data; According to the actual tour time, the basic tour route is adjusted to obtain a final tour route.

9. The method according to claim 8, characterized in that The tour planning is performed according to the location of the scenic spot, the unobstructed time period and the tour priority to obtain a basic tour route, including: Determine walking time based on the location of the scenic spot; Determine, based on the walking time, whether there is a situation where, when arriving at a desired scenic spot, the desired scenic spot is not within the unobstructed time period; If so, determining whether there are other scenic spot nodes between the two intended scenic spots according to the scenic spot information and the scenic spot location; If so, determining the best supplementary node according to the visiting time of the remaining scenic spot nodes and the locations of the remaining scenic spot nodes; According to the optimal supplementary node, the location of the scenic spot, the unobstructed time period and the tour priority, a tour planning is performed to obtain a basic tour route.

10. A comprehensive security management and control system based on big data, characterized in that: include: An information analysis module, used to obtain scenic spot information, analyze the scenic spot information, and determine scenic spot nodes; An accommodation analysis module, used to determine the accommodation capacity of the scenic spot according to the scenic spot node; The route planning module is used to obtain a reservation request, perform a tour planning according to the capacity of the scenic spot and the reservation request, and obtain a tour route.

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