Intelligent management method and system for sports events

Abstract

The invention relates to the technical field of personnel management, and particularly discloses an intelligent management method and system for sports events, and the method comprises the following steps: S1, carrying out the grid division of a target site, collecting the people flow data at grid intersection points, calculating a people flow congestion score, and determining a target score; s2, grouping the target scores, determining a standard score corresponding to a single target score in a group, and determining a contour line of the standard score; determining target routes according to the similarity between the initial route and the isoline, and sorting the target routes; and S3, starting from the first target route in the sorting, sequentially determining the service points on the target routes. The position of the service point can be adjusted according to the people flow change condition, and the convenience for people to seek help is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of personnel management, and in particular to an intelligent management method and system for sports events. Background Art

[0002] Sports events refer to various types of physical competitions and activities, usually held at a specific time and place, in which participants compete in the form of sports or athletics. Sports events vary in type and scale, ranging from small competitions at the local level to large-scale international championships.

[0003] In large-scale sports events, personnel management is one of the important links in the successful operation of the event. In reality, large-scale sports events usually have multiple sports events taking place at the same time. However, the start and end time of different events may not be the same, which leads to an unbalanced flow of people in the venue. When there are a large number of people, there may be more people seeking help from the staff (such as asking for directions, etc.), and the staff are generally located in a fixed position. When the audience seeks help from the staff, they may need to go to a farther place, which makes it difficult for the audience to get the corresponding help in time, which brings a bad viewing experience to the audience and is not conducive to the development of sports events. Summary of the invention

[0004] The purpose of the present invention is to provide a sports event intelligent management method and system to solve the following technical problems: Different events may start and end at different times, which may lead to an unbalanced flow of people in the venue. When there are a large number of people, more people may seek help from the staff (such as asking for directions, etc.), and the staff are generally located in a fixed position. When seeking help from the staff, the audience may need to go farther, making it difficult for the audience to get the corresponding help in a timely manner.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A sports event intelligent management method comprises the following steps: S1: Grid the preset target site, collect the crowd flow data at the grid intersections, the crowd flow data includes the average of the crowd flow, the crowd flow change rate and the instantaneous speed of people passing the target point, calculate the crowd congestion score based on the superior and inferior solution distance method, and take the average of the crowd congestion score in the preset monitoring period as the target score; S2: Grouping the target scores, if the difference between any two target scores in the same group is less than a preset target score difference threshold, calculating the mean C of the target scores in the same group, using the mean C as the standard score corresponding to the single target score in the group, and determining the contour line of the standard score; Taking a route of any length in the target site as an initial route, determining the similarity between the initial route and the contour line, taking the initial route corresponding to the maximum similarity as the target route, and sorting the target route according to a preset rule to obtain a route sorting; The process of obtaining the similarity between the initial route and the contour line specifically includes: Determine the intersection of the initial route and the contour line, determine the distance between two adjacent intersection points and calculate the average Sjl, start from the starting point of the initial route, set a number of route points on the initial route at a preset first route interval, determine the projection distance from the route point to the contour line and calculate the average Sty; Calculate the similarity P=η*n / (Sjl*Sty), where η is a preset correction coefficient and n represents the total number of intersections between the initial route and the contour line; S3: Determine the target route D that comes first in the route ranking, determine the target point, the target point is a grid intersection whose distance from the target route D is less than a second distance interval, the second distance interval is the distance between two adjacent grid intersections, and determine the target point K with the largest target score; The service points on the target route D are determined based on the target point, and the remaining service points are determined according to the determined service points.

[0006] As a further solution of the present invention: in step S3, the process of determining the service point specifically includes: Determine the projection point Kty of the target point K on the target route D, set a service point on the projection point Kty, and set a service point at a position on the target route D where the distance between the service point and the service point is a preset optimal distance interval LJG, and determine all service points on the target route D; Taking the service point as the center, determine a circular area with a radius of the optimal route interval LJG, update the target route whose sorting position belongs to the sorting position interval [2, m] in the route sorting, and remove the part of the target route in the circular area, where m represents the total number of the target routes; Remove the target route D that is ranked first in the sorting, and repeat the above steps to determine all the service points.

[0007] As a further solution of the present invention: the process of determining the service point also includes the following steps: Determine reference points on the target route y, the reference points include service points and endpoints of the target route y. After determining the service point Y, if the distance between the service point Y and the reference point is less than the optimal distance interval LJG, adjust the position of the Yth service point to the midpoint Yzd between the reference point and the service point Y-1, and the service point Y-1 is the previous service point adjacent to the service point Y on the target route y.

[0008] As a further solution of the present invention: the process of determining the service point also includes the following steps: The total number N of service personnel is determined. After the N service points are determined, no new service points are determined, and prompts are issued to the service personnel to remind them to go to the service points closest to them.

[0009] As a further solution of the present invention: when there is a position WZ on the target curve Ndy where the Nth service point is located, the distance between the position WZ and the Nth service point is greater than the optimal distance interval LJG, and there are no other service points on the target route Ndy within a range where the distance between the position WZ and the Nth service point is less than or equal to the optimal distance interval LJG, an early warning message is sent to alert the management personnel.

[0010] As a further solution of the present invention: when the distances between two or more service personnel and the service point F are the same and the service point F is the nearest service point corresponding to each of them, the following steps are performed: The service personnel who are at the same distance from service point F and whose nearest service point is service point F are marked as pending personnel, the service point closest to the pending personnel other than service point F is determined and used as the pending point, the distance Lmin between the pending point and the pending personnel is determined, and the pending personnel corresponding to the maximum value of the distance Lmin is prompted to go to service point F.

[0011] As a further solution of the present invention: in step S2, the process of determining the route sequence specifically includes: The target routes are sorted according to the standard scores of the corresponding contour lines. The larger the standard score of the contour line, the higher the ranking of the corresponding target route; When the standard scores of the corresponding contour lines of the target routes are the same, they are sorted according to the size of the average target scores on the contour lines. The larger the average target score on the contour line, the higher the ranking of the target route.

[0012] An intelligent sports event management system, comprising: Collection module: divide the preset target site into grids, collect the crowd flow data at the grid intersections, the crowd flow data includes the average of the crowd flow, the crowd flow change rate and the instantaneous speed of people passing through the target point, calculate the crowd congestion score based on the superior and inferior solution distance method, and take the average of the crowd congestion score in the preset monitoring period as the target score; Analysis module: grouping the target scores, if the difference between any two target scores in the same group is less than a preset target score difference threshold, calculating the mean C of the target scores in the same group, using the mean C as the standard score corresponding to the single target score in the group, and determining the isovalue line of the standard score; Taking a route of any length in the target site as an initial route, determining the similarity between the initial route and the contour line, taking the initial route corresponding to the maximum similarity as the target route, and sorting the target route according to a preset rule to obtain a route sorting; The process of obtaining the similarity between the initial route and the contour line specifically includes: Determine the intersection of the initial route and the contour line, determine the distance between two adjacent intersection points and calculate the average Sjl, start from the starting point of the initial route, set a number of route points on the initial route at a preset first route interval, determine the projection distance from the route point to the contour line and calculate the average Sty; Calculate the similarity P=η*n / (Sjl*Sty), where η is a preset correction coefficient and n represents the total number of intersections between the initial route and the contour line; Decision module: determine the target route D that is ranked first in the route ranking, determine the target point, the target point is a grid intersection whose distance from the target route D is less than a second distance interval, the second distance interval is the distance between two adjacent grid intersections, and determine the target point K with the largest target score; The service points on the target route D are determined based on the target point, and the remaining service points are determined according to the determined service points.

[0013] Beneficial effects of the present invention: In the present invention, firstly, by grid division and collecting crowd data at grid intersections, the crowd congestion score at each grid intersection is calculated, and the crowd congestion score is used to measure the relative congestion degree of each area, thereby providing a basis for the subsequent setting of service points; the superior and inferior solution distance method determines the relative congestion degree of each point by calculating the distance from each grid point to the ideal congestion condition (low congestion) and the worst congestion condition (high congestion), and can accurately evaluate the degree of deviation of each point from the optimal and worst states, thereby identifying relatively more crowded or more comfortable areas; in actual situations, there may be slight differences in the crowd congestion scores at different grid intersections, and such slight differences can be approximately regarded as non-existent The gap is that the target score in the group is replaced by the standard score and the contour line is drawn based on it. The drawing of the contour line belongs to the prior art and will not be repeated here. On the contour line, the degree of congestion is the same; considering that the contour line is not the actual route in the target venue, that is, the contour line does not necessarily coincide with the existing route (that is, the initial route), the similarity between the existing route and the contour line is determined, and the existing route with the greatest similarity is used as the target route; then, a service point is selected near the overlapping area between the target route and the contour line, and the layout of the service points of the subsequent routes is optimized by the coverage of the service point, so as to achieve a uniform distribution of service points in the venue, avoid repeated coverage of resources and redundant services, and ensure service coverage of the entire venue. The present invention can adjust the position of the service point according to the changes in the flow of people, and improve the convenience of people seeking help. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below in conjunction with the accompanying drawings.

[0015] Figure 1 It is a flow chart of an intelligent management method for sports events of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] See also Figure 1 As shown, the present invention is an intelligent management method for sports events, comprising the following steps: S1: Grid the preset target site, collect the crowd flow data at the grid intersections, the crowd flow data includes the average of the crowd flow, the crowd flow change rate and the instantaneous speed of people passing the target point, calculate the crowd congestion score based on the superior and inferior solution distance method, and take the average of the crowd congestion score in the preset monitoring period as the target score; S2: Grouping the target scores, if the difference between any two target scores in the same group is less than a preset target score difference threshold, calculating the mean C of the target scores in the same group, using the mean C as the standard score corresponding to the single target score in the group, and determining the contour line of the standard score; Taking a route of any length in the target site as an initial route, determining the similarity between the initial route and the contour line, taking the initial route corresponding to the maximum similarity as the target route, and sorting the target route according to a preset rule to obtain a route sorting; The process of obtaining the similarity between the initial route and the contour line specifically includes: Determine the intersection of the initial route and the contour line, determine the distance between two adjacent intersection points and calculate the average Sjl, start from the starting point of the initial route, set a number of route points on the initial route at a preset first route interval, determine the projection distance from the route point to the contour line and calculate the average Sty; Calculate the similarity P=η*n / (Sjl*Sty), where η is a preset correction coefficient and n represents the total number of intersections between the initial route and the contour line; S3: Determine the target route D that comes first in the route ranking, determine the target point, the target point is a grid intersection whose distance from the target route D is less than a second distance interval, the second distance interval is the distance between two adjacent grid intersections, and determine the target point K with the largest target score; The service points on the target route D are determined based on the target point, and the remaining service points are determined according to the determined service points.

[0018] It should be noted that, firstly, the crowd congestion score at each grid intersection is calculated by grid division and crowd flow data is collected at the grid intersections. The crowd congestion score is used to measure the relative degree of congestion in each area, thus providing a basis for the subsequent setting of service points. The superior-inferior solution distance method determines the relative degree of congestion at each point by calculating the distance from each grid point to the ideal congestion condition (low congestion) and the worst congestion condition (high congestion). It can accurately evaluate the degree of deviation of each point from the optimal and worst states, thereby identifying relatively more crowded or more comfortable areas. In actual situations, there may be slight differences in the crowd congestion scores at different grid intersections. This slight difference can be approximately regarded as no difference, because Here, the target score in the group is replaced by the standard score and the contour line is drawn based on it. The drawing of the contour line belongs to the existing technology and will not be repeated here. On the isolinear line, the degree of congestion is the same; considering that the contour line is not the actual route in the target venue, that is, the contour line does not necessarily coincide with the existing route (that is, the initial route), the similarity between the existing route and the contour line is determined, and the existing route with the greatest similarity is used as the target route; then, the service point is selected near the overlapping area of ​​the target route and the contour line, and the layout of the service points of the subsequent routes is optimized through the coverage of the service point, so as to achieve a uniform distribution of service points in the venue, avoid repeated coverage of resources and redundant services, and ensure service coverage of the entire venue.

[0019] In another preferred embodiment of the present invention, in step S3, the process of determining the service point specifically includes: Determine the projection point Kty of the target point K on the target route D, set a service point on the projection point Kty, and set a service point at a position on the target route D where the distance between the service point and the service point is a preset optimal distance interval LJG, and determine all service points on the target route D; Taking the service point as the center, determine a circular area with a radius of the optimal route interval LJG, update the target route whose sorting position belongs to the sorting position interval [2, m] in the route sorting, and remove the part of the target route in the circular area, where m represents the total number of the target routes; Remove the target route D that is ranked first in the sorting, and repeat the above steps to determine all the service points.

[0020] It is worth noting that the reason for first determining all the service points on the target route D is that after the first service point on the target route D is determined, although the circular coverage area of ​​the first service point may include the rest of the area on the target route D, since the covered area is close to the service point but may not have a passable path, people still cannot directly reach these points. Therefore, it is necessary to first determine all the service points on the target route D, giving priority to locations with greater potential service demand.

[0021] In another preferred embodiment of the present invention, the process of determining the service point further includes the following steps: Determine reference points on the target route y, the reference points include service points and endpoints of the target route y. After determining the service point Y, if the distance between the service point Y and the reference point is less than the optimal distance interval LJG, adjust the position of the Yth service point to the midpoint Yzd between the reference point and the service point Y-1, and the service point Y-1 is the previous service point adjacent to the service point Y on the target route y.

[0022] It can be understood that, when the midpoint Yzd between the reference point and the service point Y-1 is not on the target route y, the projection point of the midpoint Yzd on the target route y is determined, and the projection point Yzd is used as the service point Y; in a crowded venue, if the distance between the service points is too close, it will cause excessive overlap and redundancy of resources, reduce the service coverage efficiency, and through adjustment, the distance between the new service point (such as service point Y) and the previous service point Y-1 is as consistent as possible with the preset optimal interval (LJG), ensuring that the service points are evenly distributed, reducing resource waste, and improving the overall coverage of the venue; by calculating the midpoint Yzd of the reference point and the previous service point, the position of the service point can adapt to the actual situation. When Yzd is not on the target route y, the projection point is used instead to ensure that the service point still falls on the target route y and avoid the service point position deviating from the original route.

[0023] In another preferred embodiment of the present invention, the process of determining the service point further includes the following steps: The total number N of service personnel is determined. After the N service points are determined, no new service points are determined, and prompts are issued to the service personnel to remind them to go to the service points closest to them.

[0024] It should be noted that by limiting the number of service points to be equal to the number of service personnel, it is ensured that each service point can be equipped with service personnel, avoiding the situation where some service points are unattended due to too many service points, thereby improving the utilization rate of each service point, avoiding waste of resources, and ensuring a reasonable match between service points and service personnel.

[0025] In another preferred embodiment of the present invention, when there is a position WZ on the target curve Ndy where the Nth service point is located, the distance between the position WZ and the Nth service point is greater than the optimal distance interval LJG, and there are no other service points on the target route Ndy within a range where the distance between the position WZ and the Nth service point is less than or equal to the optimal distance interval LJG, an early warning message is sent to alert the management personnel.

[0026] It should be noted that through the above method, potential service gap areas can be identified. If there is a lack of service points in the area, people may not be able to receive timely services. Therefore, early warning information is sent to remind managers to pay attention to and deal with these coverage blind spots.

[0027] In another preferred embodiment of the present invention, when the distances between two or more service personnel and the service point F are the same and the service point F is the nearest service point corresponding to each of them, the following steps are performed: The service personnel who are at the same distance from service point F and whose nearest service point is service point F are marked as pending personnel, the service point closest to the pending personnel other than service point F is determined and used as the pending point, the distance Lmin between the pending point and the pending personnel is determined, and the pending personnel corresponding to the maximum value of the distance Lmin is prompted to go to service point F.

[0028] It can be understood that by marking the "pending personnel" and selecting the most suitable personnel to go to service point F, other service personnel go to other candidate service points (pending points), ensuring balanced coverage of the venue service points.

[0029] In another preferred embodiment of the present invention, in step S2, the process of determining the route sequence specifically includes: The target routes are sorted according to the standard scores of the corresponding contour lines. The larger the standard score of the contour line, the higher the ranking of the corresponding target route; When the standard scores of the corresponding contour lines of the target routes are the same, they are sorted according to the size of the average target scores on the contour lines. The larger the average target score on the contour line, the higher the ranking of the target route.

[0030] An intelligent sports event management system, comprising: Collection module: divide the preset target site into grids, collect the crowd flow data at the grid intersections, the crowd flow data includes the average of the crowd flow, the crowd flow change rate and the instantaneous speed of people passing through the target point, calculate the crowd congestion score based on the superior and inferior solution distance method, and take the average of the crowd congestion score in the preset monitoring period as the target score; Analysis module: grouping the target scores, if the difference between any two target scores in the same group is less than a preset target score difference threshold, calculating the mean C of the target scores in the same group, using the mean C as the standard score corresponding to the single target score in the group, and determining the isovalue line of the standard score; Taking a route of any length in the target site as an initial route, determining the similarity between the initial route and the contour line, taking the initial route corresponding to the maximum similarity as the target route, and sorting the target route according to a preset rule to obtain a route sorting; The process of obtaining the similarity between the initial route and the contour line specifically includes: Determine the intersection of the initial route and the contour line, determine the distance between two adjacent intersection points and calculate the average Sjl, start from the starting point of the initial route, set a number of route points on the initial route at a preset first route interval, determine the projection distance from the route point to the contour line and calculate the average Sty; Calculate the similarity P=η*n / (Sjl*Sty), where η is a preset correction coefficient and n represents the total number of intersections between the initial route and the contour line; Decision module: determine the target route D that is ranked first in the route ranking, determine the target point, the target point is a grid intersection whose distance from the target route D is less than a second distance interval, the second distance interval is the distance between two adjacent grid intersections, and determine the target point K with the largest target score; The service points on the target route D are determined based on the target point, and the remaining service points are determined according to the determined service points.

[0031] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A sports event intelligent management method, characterized in that: The following steps are involved: S1: Grid the preset target site, collect the crowd flow data at the grid intersections, the crowd flow data includes the average of the crowd flow, the crowd flow change rate and the instantaneous speed of people passing the target point, calculate the crowd congestion score based on the superior and inferior solution distance method, and take the average of the crowd congestion score in the preset monitoring period as the target score; S2: Grouping the target scores, if the difference between any two target scores in the same group is less than a preset target score difference threshold, calculating the mean C of the target scores in the same group, using the mean C as the standard score corresponding to the single target score in the group, and determining the contour line of the standard score; Taking a route of any length in the target site as an initial route, determining the similarity between the initial route and the contour line, taking the initial route corresponding to the maximum similarity as the target route, and sorting the target route according to a preset rule to obtain a route sorting; The process of obtaining the similarity between the initial route and the contour line specifically includes: Determine the intersection of the initial route and the contour line, determine the distance between two adjacent intersection points and calculate the average Sjl, start from the starting point of the initial route, set a number of route points on the initial route at a preset first route interval, determine the projection distance from the route point to the contour line and calculate the average Sty; Calculate the similarity P=η*n / (Sjl*Sty), where η is a preset correction coefficient and n represents the total number of intersections between the initial route and the contour line; S3: Determine the target route D that comes first in the route ranking, determine the target point, the target point is a grid intersection whose distance from the target route D is less than a second distance interval, the second distance interval is the distance between two adjacent grid intersections, and determine the target point K with the largest target score; The service points on the target route D are determined based on the target point, and the remaining service points are determined according to the determined service points.

2. A sports event intelligent management method according to claim 1, characterized in that: In step S3, the process of determining the service point specifically includes: Determine the projection point Kty of the target point K on the target route D, set a service point on the projection point Kty, and set a service point at a position on the target route D where the distance between the service point and the service point is a preset optimal distance interval LJG, and determine all service points on the target route D; Taking the service point as the center, determine a circular area with a radius of the optimal route interval LJG, update the target route whose sorting position belongs to the sorting position interval [2, m] in the route sorting, and remove the part of the target route in the circular area, where m represents the total number of the target routes; Remove the target route D that is ranked first in the sorting, and repeat the above steps to determine all the service points.

3. A sports event intelligent management method according to claim 2, characterized in that: The process of determining the service point also includes the following steps: Determine reference points on the target route y, the reference points include service points and endpoints of the target route y. After determining the service point Y, if the distance between the service point Y and the reference point is less than the optimal distance interval LJG, adjust the position of the Yth service point to the midpoint Yzd between the reference point and the service point Y-1, and the service point Y-1 is the previous service point adjacent to the service point Y on the target route y.

4. A sports event intelligent management method according to claim 3, characterized in that: The process of determining the service point also includes the following steps: The total number N of service personnel is determined. After the N service points are determined, no new service points are determined, and prompts are issued to the service personnel to remind them to go to the service points closest to them.

5. A sports event intelligent management method according to claim 4, characterized in that: When there is a position WZ on the target curve Ndy where the Nth service point is located, the distance between the position WZ and the Nth service point is greater than the optimal distance interval LJG, and there are no other service points on the target route Ndy within a range where the distance between the position WZ and the Nth service point is less than or equal to the optimal distance interval LJG, an early warning message is sent to alert the management personnel.

6. A sports event intelligent management method according to claim 4, characterized in that: When the distances between two or more service personnel and the service point F are the same and the service point F is the nearest service point corresponding to each of them, perform the following steps: The service personnel who are at the same distance from service point F and whose nearest service point is service point F are marked as pending personnel, the service point closest to the pending personnel other than service point F is determined and used as the pending point, the distance Lmin between the pending point and the pending personnel is determined, and the pending personnel corresponding to the maximum value of the distance Lmin is prompted to go to service point F.

7. The method for intelligent management of sports events according to claim 1, characterized in that: In step S2, the process of determining the route sequence specifically includes: The target routes are sorted according to the standard scores of the corresponding contour lines. The larger the standard score of the contour line, the higher the ranking of the corresponding target route; When the standard scores of the corresponding contour lines of the target routes are the same, they are sorted according to the size of the average target scores on the contour lines. The larger the average target score on the contour line, the higher the ranking of the target route.

8. An intelligent sports event management system, characterized in that: include: Collection module: divide the preset target site into grids, collect the crowd flow data at the grid intersections, the crowd flow data includes the average of the crowd flow, the crowd flow change rate and the instantaneous speed of people passing through the target point, calculate the crowd congestion score based on the superior and inferior solution distance method, and take the average of the crowd congestion score in the preset monitoring period as the target score; Analysis module: grouping the target scores, if the difference between any two target scores in the same group is less than a preset target score difference threshold, calculating the mean C of the target scores in the same group, using the mean C as the standard score corresponding to the single target score in the group, and determining the isovalue line of the standard score; Taking a route of any length in the target site as an initial route, determining the similarity between the initial route and the contour line, taking the initial route corresponding to the maximum similarity as the target route, and sorting the target route according to a preset rule to obtain a route sorting; The process of obtaining the similarity between the initial route and the contour line specifically includes: Determine the intersection of the initial route and the contour line, determine the distance between two adjacent intersection points and calculate the average Sjl, start from the starting point of the initial route, set a number of route points on the initial route at a preset first route interval, determine the projection distance from the route point to the contour line and calculate the average Sty; Calculate the similarity P=η*n / (Sjl*Sty), where η is a preset correction coefficient and n represents the total number of intersections between the initial route and the contour line; Decision module: determine the target route D that is ranked first in the route ranking, determine the target point, the target point is a grid intersection whose distance from the target route D is less than a second distance interval, the second distance interval is the distance between two adjacent grid intersections, and determine the target point K with the largest target score; The service points on the target route D are determined based on the target point, and the remaining service points are determined according to the determined service points.

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