Intelligent security service management system

Abstract

The application discloses a kind of wisdom security service management systems, it is related to wisdom security field, it solves the problem that existing wisdom security service management system has poor management effect, including: data acquisition module: mobile body trajectory dynamic acquisition and analysis are carried out to security sub-region, and the intersection of regional travel trajectory is obtained, the intersection intensity analysis data of region is obtained by analyzing the mobile body path deviation rate of regional travel trajectory intersection and mobile body density, mobile analysis module: the intersection of regional travel trajectory is divided into first type trajectory intersection and second type trajectory intersection, local traffic environment analysis is carried out to second type trajectory intersection, and traffic environment analysis data is obtained, congestion prediction module: according to traffic environment analysis data, the traffic area corresponding to the intersection of regional travel trajectory is predicted to be congested, and security service early warning is carried out according to the prediction result, the application can improve the pertinence and timeliness of wisdom security service management process.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of intelligent security, and relates to path prediction technology, in particular to an intelligent security service management system. BACKGROUND

[0002] In the existing intelligent security service management process, the following defects exist:

[0003] 1. The mobile trajectory is not predicted according to the real-time moving direction of the mobile body in the security area, it is difficult to effectively collect the mobile body density and the mobile body travel deviation rate of the trajectory initial extension area to obtain the mobile body intersection strength of the mobile trajectory intersection point, and the intersection point trajectory intersection point is not classified according to the above, so that appropriate security service strategies cannot be taken for different types of trajectory intersection points, and the pertinence and applicability of security services cannot be effectively improved.

[0004] 2. It is difficult to make security early warning in advance for the passing area with large intersection strength, and it is difficult to effectively combine the actual geometric characteristics of the trajectory intersection passing area to predict the congestion of the conventional intersection strength passing area, so that the congestion area prediction result has hysteresis, thereby resulting in poor security service effect.

[0005] Therefore, the application provides an intelligent security service management system. SUMMARY

[0006] In view of the defects in the prior art, the application aims to provide an intelligent security service management system, and aims to improve the pertinence and timeliness of the security service management process.

[0007] In order to achieve the above purpose, the application adopts the following technical scheme: an intelligent security service management system, and the specific working process of each module is as follows:

[0008] The data acquisition module: the mobile trajectory of the security sub-area in the target security area is dynamically collected and analyzed, the intersection point of the direction trajectory marker line corresponding to the security sub-area in the target security area is obtained according to the analysis result, the area travel trajectory intersection point is obtained, the mobile body intersection strength is obtained by analyzing the mobile body path deviation rate and the mobile body density of the area travel trajectory intersection point, and the area intersection strength analysis data is obtained.

[0009] The mobile analysis module: the area travel trajectory intersection point is divided into a first type trajectory intersection point and a second type trajectory intersection point according to the area intersection strength analysis data to obtain trajectory intersection point division data, the local passing environment of the second type trajectory intersection point is analyzed, and the passing environment analysis data is obtained according to the analysis result.

[0010] The congestion prediction module predicts congestion of a traffic area corresponding to the intersection of the regional travel trajectories according to the traffic environment analysis data, and issues a security service warning according to the prediction result.

[0011] Further, the regional intersection intensity analysis data is obtained, specifically as follows:

[0012] The target security area is obtained by acquiring the area of the scene area requiring intelligent security service management;

[0013] When the target security area is managed by the security service, a time window with a fixed time length is set with the time value corresponding to the current time as the window end time point;

[0014] The target security area is divided into a plurality of security sub-areas, the number of mobile bodies corresponding to each security sub-area is counted by the monitoring device to obtain the regional mobile body number value, the regional area value corresponding to each security sub-area is obtained to obtain the security sub-area area value, and the ratio of the regional mobile body number value to the security area area value is calculated to obtain the regional mobile body density;

[0015] A mobile body density preset interval is set, if the regional mobile body density is in the regional mobile body density preset interval, the security sub-area is divided into a path to be analyzed area, if the regional mobile body density is not in the regional mobile body density preset interval, the security sub-area is divided into a path without planning area, and a sample path to be analyzed area is randomly selected from the plurality of path to be analyzed areas, and the regional mainstream trajectory direction corresponding to the sample path to be analyzed area is obtained;

[0016] The angle bisector of the direction feature angle corresponding to each regional mainstream trajectory direction is obtained, and a plurality of direction trajectory marker lines corresponding to each regional mainstream trajectory direction are obtained;

[0017] The intersection points of the direction trajectory marker lines in the target security area are obtained to obtain a plurality of regional travel trajectory intersection points;

[0018] A sample trajectory intersection point is randomly selected from the plurality of regional travel trajectory intersection points, the sample trajectory intersection point is analyzed, and the mobile body intersection intensity corresponding to the sample trajectory intersection point is obtained according to the analysis result;

[0019] The process of obtaining the mobile body intersection intensity corresponding to the sample trajectory intersection point is repeated, and the mobile body intersection intensity corresponding to each regional travel trajectory intersection point is obtained to obtain the regional intersection intensity analysis data.

[0020] Further, the regional mainstream trajectory direction corresponding to the sample path to be analyzed area is obtained, specifically as follows:

[0021] set the time window in which the current time is located as a real-time time window, perform mobile path analysis on the sample path to-be-analyzed region in the real-time time window to obtain a mainstream trajectory direction corresponding to the real-time time window;

[0022] select a historical time window before a real-time time window, obtain a mainstream trajectory direction corresponding to each historical time window respectively, and perform quantity statistics on the mainstream trajectory directions belonging to a first direction interval to an a-th direction interval to obtain a first mainstream trajectory quantity value to an a-th mainstream trajectory quantity value, and perform value comparison on the first mainstream trajectory quantity value to the a-th mainstream trajectory quantity value, and set the mainstream trajectory quantity value with the largest value as a regional mainstream trajectory direction corresponding to the sample path to-be-analyzed region;

[0023] repeat the process of obtaining the regional mainstream trajectory direction corresponding to the sample path to-be-analyzed region to obtain the regional mainstream trajectory direction corresponding to each path to-be-analyzed region respectively.

[0024] Further, the mainstream trajectory direction corresponding to the real-time time window is obtained, specifically as follows:

[0025] obtained at the geometric center of the sample path to-be-analyzed region, a straight line perpendicular to the north is made through the security region center point to obtain a path positive direction marker line, the path positive direction marker line is taken as a direction starting edge, and the security region center point is taken as a starting point to set a feature direction line through the security region center point every interval a degree, and the included angle formed by any two adjacent feature direction lines is set as a direction feature included angle;

[0026] According to the value of the direction feature included angle, the feature direction lines are respectively named as a first regional direction line to an a-th regional direction line, and the angle interval covered by any two regional direction lines at the security region center point is respectively marked as a first direction interval to an a-th direction interval;

[0027] set a starting time point corresponding to the real-time time window as a first window feature time point, and obtain an ending time point corresponding to the real-time time window to obtain a second window feature time point;

[0028] obtain the mobile body position of each mobile body in the sample path to-be-analyzed region at the first window feature time point to obtain a plurality of mobile start positions, and obtain the mobile body position of each mobile body in the sample path to-be-analyzed region at the second window feature time point to obtain a plurality of mobile end positions;

[0029] Obtaining the position connecting line of each moving body at the moving start position and the moving end position, obtaining a plurality of real-time window moving paths, respectively obtaining the positive direction angle of each real-time moving path and the path positive direction marker line, and obtaining a plurality of real-time path moving azimuths;

[0030] Counting the number of real-time path moving azimuths in the first azimuth interval to the αth azimuth interval to obtain a first azimuth trajectory number value to an αth azimuth trajectory number value, and comparing the values of the obtained first azimuth trajectory number value to the αth azimuth trajectory number value, and setting the azimuth interval corresponding to the maximum azimuth trajectory number value as the main flow trajectory azimuth corresponding to the real-time time window.

[0031] Further, the moving body intersection intensity is obtained as follows:

[0032] Obtaining the intersection azimuth trajectory marker line at the sample trajectory intersection point, and setting the obtained azimuth trajectory marker line as F1 moving trajectory line to Fb moving trajectory line, respectively;

[0033] Obtaining the path to be analyzed region corresponding to F1 moving trajectory line to Fb moving trajectory line to obtain F1 path to be analyzed region to Fb path to be analyzed region, obtaining the region moving body density corresponding to F1 path to be analyzed region to Fb path to be analyzed region to obtain F1 region moving body density to Fb region moving body density;

[0034] Analyzing the moving body in F1 path to be analyzed region, and obtaining F1 region deviation rate according to the analysis result;

[0035] Repeating the process of obtaining F1 region deviation rate, obtaining region deviation rate corresponding to F2 path to be analyzed region to Fb path to be analyzed region to obtain F2 region deviation rate to Fb region deviation rate;

[0036] Calculating F1 region deviation rate to Fb region deviation rate and F1 region moving body density to Fb region moving body density to obtain the moving body intersection intensity corresponding to the sample trajectory intersection point;

[0037] Calculating the moving body intersection intensity corresponding to the sample trajectory intersection point, and the specific formula is as follows:

[0038]

[0039] Wherein, Jhq is the moving body intersection intensity corresponding to the sample trajectory intersection point, Ymzi is the Fi region moving body density, Pyli is the Fi region deviation rate, b is the number value of the intersection azimuth trajectory marker line at the sample trajectory intersection point, and b is an integer greater than 0.

[0040] Further, the F1 area offset rate is obtained, and the specific process is as follows:

[0041] An arbitrary characteristic mobile body is selected from the mobile bodies in the F1 path to be analyzed area, a time window in which the a characteristic mobile bodies move is obtained, two time windows that are continuous in time range are set as a time window combination, and c time window combinations are obtained;

[0042] The two time windows in the time window combination are respectively named as a first time window and a second time window, the window moving paths corresponding to the first time window and the second time window are obtained, and a first window moving path and a second window moving path are obtained;

[0043] The transition time point between the first time window and the second time window is obtained, a window characteristic time point is obtained, and the area position of the characteristic mobile body at the window characteristic time point is obtained, and a window transition position point is obtained;

[0044] The included angle formed by the first window moving path and the second window moving path at the window transition position point is obtained, the trajectory offset angle corresponding to each time window combination is obtained, and the c trajectory offset angles are averaged to obtain the area offset angle corresponding to the characteristic mobile body;

[0045] The process of obtaining the area offset angle corresponding to the characteristic mobile body is repeated, and the area offset angle corresponding to each mobile body is obtained, and a plurality of area offset angles are obtained;

[0046] The time lengths covered by each time window combination are summed to obtain a window cumulative coverage duration, and the c area offset angles and the window cumulative coverage duration are used to obtain the F1 area offset rate through calculation;

[0047] The F1 area offset rate is calculated, and the specific formula is as follows:

[0048]

[0049] Wherein, Pyl1 is the F1 area offset rate, Qpji is an arbitrary area offset angle, Tcf is the window cumulative coverage duration, and c is the number of time window combinations.

[0050] Further, the passing environment analysis data is obtained, and the specific process is as follows:

[0051] The area intersection intensity analysis data is obtained, and the mobile body intersection intensity corresponding to each area travel trajectory intersection point is obtained according to the area intersection intensity analysis data;

[0052] Obtaining an intersection intensity preset interval, if the intersection intensity of the moving body is in the intersection intensity preset interval, then the corresponding regional travel trajectory intersection point is divided into a first type trajectory intersection point, if the intersection intensity of the moving body is not in the intersection intensity preset interval, then the corresponding regional travel trajectory intersection point is divided into a second type trajectory intersection point, and trajectory intersection point division data is obtained;

[0053] Performing a traffic environment analysis on the space region corresponding to the second type trajectory intersection point, and obtaining traffic environment analysis data according to the analysis result.

[0054] Further, the traffic environment analysis is performed on the space region corresponding to the second type trajectory intersection point, and the specific process is as follows:

[0055] Obtaining a traffic region corresponding to each first type trajectory intersection point, obtaining a plurality of intersection point traffic regions, and selecting a sample traffic region from the obtained plurality of intersection point traffic regions;

[0056] Obtaining a region area corresponding to the sample traffic region, obtaining a traffic region area value, obtaining a region perimeter corresponding to the sample traffic region, and obtaining a traffic region perimeter value;

[0057] The traffic region area value and the traffic region perimeter value are calculated to obtain a region geometric traffic index corresponding to the sample traffic region;

[0058] The region geometric traffic index corresponding to the sample traffic region is calculated, and the specific formula is as follows:

[0059]

[0060] Wherein, Jhz is the region geometric traffic index corresponding to the sample traffic region, Ymj is the traffic region area value, and Zcq is the traffic region perimeter value;

[0061] The process of obtaining the region geometric traffic index corresponding to the sample traffic region is repeated, and the region geometric traffic index corresponding to each intersection point traffic region is obtained, and the region geometric traffic index corresponding to the first type trajectory intersection point is obtained.

[0062] The region geometric traffic index corresponding to the first type trajectory intersection point and the trajectory intersection point division data are defined as traffic environment analysis data.

[0063] Further, the security service warning is performed on the traffic region, and the specific process is as follows:

[0064] Obtaining traffic environment analysis data, and obtaining trajectory intersection point division data according to the traffic environment analysis data;

[0065] According to the trajectory intersection point, the data is divided into a first type trajectory intersection point and a second type trajectory intersection point, and the passing area corresponding to the first type trajectory intersection point is predicted as a congestion area, and a security service warning is issued;

[0066] The passing area corresponding to the second type trajectory intersection point is subjected to geometric passing index analysis, and a security service warning is issued according to the analysis result.

[0067] Further, the geometric passing index analysis is performed on the passing area, and the specific process is as follows:

[0068] The geometric passing index of the area corresponding to each second type trajectory intersection point is obtained, a passing index congestion interval is set, if the geometric passing index of the area is in the passing index congestion interval, the passing area corresponding to the second type trajectory intersection point is predicted as a congestion area, and a security service warning is issued, if the geometric passing index of the area is not in the passing index congestion interval, the passing area corresponding to the second type trajectory intersection point is predicted as a non-congestion area, and no security service warning is issued.

[0069] As described above, due to the adoption of the above technical scheme, the present application has the following beneficial effects:

[0070] 1. According to the real-time moving direction of the mobile body in the security area, the moving trajectory is predicted, the density of the mobile body in the trajectory initial extension area and the moving offset rate of the mobile body are collected to obtain the intersection strength of the moving trajectory intersection point, and the trajectory intersection point is classified according to the intersection strength, different security service strategies are adopted for different types of trajectory intersection points, and the pertinence and applicability of security service can be further improved.

[0071] 2. The present application can effectively reduce the lag of the congestion area prediction result, thereby ensuring the security service effect. BRIEF DESCRIPTION OF DRAWINGS

[0072] In order to facilitate the understanding of those skilled in the art, the present application will be further described below with reference to the accompanying drawings.

[0073] Figure 1 The overall system block diagram of the present application is shown in the figure;

[0074] Figure 2 The angle diagram of the direction feature of the present application is shown in the figure;

[0075] Figure 3 The schematic diagram of the area running trajectory intersection point of the present application is shown in the figure. DETAILED DESCRIPTION

[0076] The technical solutions of the present application will be described clearly and completely below in connection with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0077] Embodiment one

[0078] Please refer to Figure 1 The present application provides a technical solution: a smart security service management system, comprising a data acquisition module, a mobile analysis module, a congestion prediction module and a server, the data acquisition module, the mobile analysis module and the congestion prediction module are connected with the server respectively, and the server controls the data acquisition module, the mobile analysis module and the congestion prediction module respectively.

[0079] The data acquisition module dynamically acquires and analyzes the moving body trajectory of the security sub-area in the target security area, obtains the intersection point of the orientation trajectory marker line corresponding to the security sub-area in the target security area according to the analysis result, obtains the regional travel trajectory intersection point, and obtains the moving body intersection intensity by analyzing the moving body path deviation rate and the moving body density of the regional travel trajectory intersection point, and obtains the regional intersection intensity analysis data.

[0080] Specifically as follows:

[0081] The target security area is obtained by acquiring the scene area which needs to be managed by the smart security service management system.

[0082] It should be noted that:

[0083] In the present application, the target security area is deployed with a smart security service management system, and the target security area referred to herein can be an outdoor scenic spot, an outdoor square and a subway station, etc.

[0084] When the target security area is managed by the security service, the time value corresponding to the current time is set as the window end time point to set a time window with fixed length, and as the time value corresponding to the current time changes, the set time window also slides.

[0085] It should be noted that:

[0086] In the present application, the length of time covered by the time window is set to 5 seconds.

[0087] The time window in which the current time is located is set as a real-time time window, and the moving body path of the target security area in the real-time time window is analyzed, and the mainstream trajectory direction corresponding to the real-time time window is obtained according to the analysis result.

[0088] Specifically as follows:

[0089] The target security area is divided into a plurality of security sub-areas, the number of moving bodies corresponding to each security sub-area is counted by a monitoring device to obtain a region moving body number value, the area number value corresponding to each security sub-area is obtained to obtain a security sub-area area number value, the ratio of the region moving body number value to the security area area number value is calculated to obtain a region moving body density;

[0090] It should be noted here that:

[0091] In this application, the moving body referred to here is specifically a pedestrian.

[0092] A moving body density preset interval is set, if the region moving body density is in the region moving body density preset interval, the security sub-area is divided into a path to be analyzed area, if the region moving body density is not in the region moving body density preset interval, the security sub-area is divided into a path area without planning;

[0093] It should be noted here that:

[0094] The path to be analyzed area divided by the intelligent security service management system is obtained to obtain a plurality of path to be analyzed areas, the region moving body density corresponding to each path to be analyzed area is obtained, the minimum value of the obtained region moving body density is set as the lower limit of the moving body density preset interval, and the minimum value of the obtained region moving body density is set as the upper limit of the moving body density preset interval to obtain the moving body density preset interval;

[0095] In addition, if the target security area is the initial analysis site of the intelligent security service management system, and the intelligent security service management system does not have a path to be analyzed area, the upper and lower limits of the moving body density preset interval need to be set manually.

[0096] An arbitrary sample path to be analyzed area is selected from the obtained plurality of path to be analyzed areas, and the moving body moving path of the sample path to be analyzed area is analyzed, and the corresponding region mainstream trajectory direction of the sample path to be analyzed area is obtained according to the analysis result;

[0097] Specifically as follows:

[0098] Please refer to Figure 2 The security area center point is obtained at the geometric center of the sample path to be analyzed area, a straight line perpendicular to the north is made through the security area center point to obtain a path positive direction marker line, the path positive direction marker line is taken as the direction starting edge, and the security area center point is taken as the starting point to set a characteristic direction line through the security area center point every interval of α degrees, and the included angle formed by any two adjacent characteristic direction lines is set as a direction characteristic included angle;

[0099] It should be noted here that:

[0100] In this application, a here refers to the numerical value corresponding to the characteristic azimuth line, and a is an integer greater than 0.

[0101] According to the size of the azimuth characteristic angle value, the characteristic azimuth line is named as the first region azimuth line to the a region azimuth line, and the angle interval covered by any two region azimuth lines at the security region center point is marked as the first azimuth interval to the a azimuth interval.

[0102] It should be noted here that:

[0103] In this application, the first region azimuth line coincides with the path positive direction marker line of the due east extension direction.

[0104] The start time point corresponding to the real-time time window is set as the first window feature time point, and the end time point corresponding to the real-time time window is obtained to obtain the second window feature time point;

[0105] The moving body position of each moving body in the sample path to be analyzed region at the first window feature time point is obtained to obtain a plurality of moving start positions, and the moving body position of each moving body in the sample path to be analyzed region at the second window feature time point is obtained to obtain a plurality of moving end positions;

[0106] The position connecting line of each moving body at the moving start position and the moving end position is obtained to obtain a plurality of real-time window moving paths, and the positive angle of each real-time moving path and the path positive direction marker line is obtained to obtain a plurality of real-time path moving azimuth angles;

[0107] The real-time path moving azimuth angle in the first azimuth interval to the a azimuth interval is counted to obtain the first azimuth trajectory quantity value to the a azimuth trajectory quantity value, and the first azimuth trajectory quantity value to the a azimuth trajectory quantity value is compared in value size. The azimuth interval corresponding to the maximum azimuth trajectory quantity value is set as the mainstream trajectory direction of the real-time time window;

[0108] Select a historical time window before a real-time time window, obtain the mainstream trajectory direction corresponding to each historical time window, and count the number of mainstream trajectory directions belonging to the first azimuth interval to the a azimuth interval to obtain the first mainstream trajectory quantity value to the a mainstream trajectory quantity value. The first mainstream trajectory quantity value to the a mainstream trajectory quantity value is compared in value, and the mainstream trajectory quantity value with the maximum value is set as the region mainstream trajectory direction corresponding to the sample path to be analyzed region;

[0109] It should be noted here that:

[0110] In the present application, a here refers to the number value corresponding to the historical time window, and a is an integer greater than 0.

[0111] The acquisition process of the regional mainstream trajectory direction corresponding to the sample path to-be-analyzed area is repeated to acquire the regional mainstream trajectory direction corresponding to each path to-be-analyzed area;

[0112] Please refer to Figure 3 The angle bisector of the direction feature included angle corresponding to each regional mainstream trajectory direction is acquired to acquire a plurality of direction trajectory marker lines corresponding to each regional mainstream trajectory direction;

[0113] The intersection points of the direction trajectory marker lines in the target security area are acquired to obtain a plurality of regional travel trajectory intersection points;

[0114] An arbitrary sample trajectory intersection point is selected from the plurality of regional travel trajectory intersection points, and trajectory feature analysis is performed on the sample trajectory intersection point to obtain the moving body intersection intensity corresponding to the sample trajectory intersection point according to the analysis result;

[0115] Specifically as follows:

[0116] The intersection direction trajectory marker line at the sample trajectory intersection point is acquired, and the acquired direction trajectory marker line is set as F1 moving trajectory line to Fb moving trajectory line;

[0117] It should be noted here that:

[0118] In the present application, F1, F2, F3, …, Fb in F1 moving trajectory line to Fb moving trajectory line are respectively the marker symbols corresponding to the moving trajectory line, and b is an integer greater than 0.

[0119] The path to-be-analyzed area corresponding to F1 moving trajectory line to Fb moving trajectory line is acquired to obtain F1 path to-be-analyzed area to Fb path to-be-analyzed area, and the regional moving body density corresponding to F1 path to-be-analyzed area to Fb path to-be-analyzed area is acquired to obtain F1 regional moving body density to Fb regional moving body density;

[0120] The moving body in F1 path to-be-analyzed area is analyzed, and F1 regional offset rate is acquired according to the analysis result;

[0121] Specifically as follows:

[0122] An arbitrary characteristic moving body is selected from the moving body in F1 path to-be-analyzed area, a time window in which the a characteristic moving bodies move is acquired, and any two time window continuous time windows are set as a time window combination to obtain c time window combinations;

[0123] Two time windows in the time window combination are respectively named as a first time window and a second time window, and window moving paths corresponding to the first time window and the second time window are acquired to obtain a first window moving path and a second window moving path;

[0124] A transition time point between the first time window and the second time window is acquired to obtain a window feature time point, and a region position where the feature moving body is located at the window feature time point is acquired to obtain a window transition position point;

[0125] It should be noted that:

[0126] In the present application, the transition time point is the end time point of the first time window and the start time point of the second time window.

[0127] In the present application, the acquisition process of the first window moving path and the second window moving path is consistent with the acquisition process of the real-time window moving path.

[0128] An included angle formed by the first window moving path and the second window moving path at the window transition position point is numerically acquired to obtain a track offset included angle corresponding to each time window combination, and an average of the c track offset included angles is calculated to obtain a region offset included angle corresponding to the feature moving body.

[0129] The acquisition process of the region offset included angle corresponding to the feature moving body is repeated to acquire a region offset included angle corresponding to each moving body to obtain a plurality of region offset included angles.

[0130] A time length covered by each time window combination is summed to obtain a window cumulative coverage duration, and the c region offset included angles and the window cumulative coverage duration are calculated to obtain an F1 region offset rate.

[0131] The F1 region offset rate is calculated, and the specific formula is as follows:

[0132]

[0133] Wherein, Pyl1 is the F1 region offset rate, Qpji is any one region offset included angle, Tcf is the window cumulative coverage duration, and c is a numerical value corresponding to the time window combination.

[0134] The acquisition process of the F1 region offset rate is repeated to acquire region offset rates corresponding to the F2 path to be analyzed region to the Fb path to be analyzed region to obtain F2 region offset rate to Fb region offset rate.

[0135] The F1 region offset rate to the Fb region offset rate and the F1 region mobile body density to the Fb region mobile body density are obtained by calculating the mobile body intersection intensity corresponding to the sample trajectory intersection point;

[0136] The mobile body intersection intensity corresponding to the sample trajectory intersection point is calculated, and the specific formula is as follows:

[0137]

[0138] Wherein, Jhq is the mobile body intersection intensity corresponding to the sample trajectory intersection point, Ymzi is the Fi region mobile body density, Pyli is the Fi region offset rate, b is the number of intersection direction trajectory marking lines at the sample trajectory intersection point, and b is an integer greater than 0;

[0139] It should be noted here that:

[0140] In this application, the Fi region mobile body density can be any one of the F1 region mobile body density to the Fb region mobile body density, and the Fi region offset rate can be any one of the F1 region offset rate to the Fb region offset rate;

[0141] The process of obtaining the mobile body intersection intensity corresponding to the sample trajectory intersection point is repeated, and the mobile body intersection intensity corresponding to each region running trajectory intersection point is obtained, and region intersection intensity analysis data is obtained.

[0142] It should be noted here that:

[0143] The present application can predict the moving trajectory of the mobile body according to the real-time moving direction of the mobile body in the security area, can early understand the possible action trend of the mobile body, can provide forward-looking information for the security personnel, can make the security personnel make early preparation, can reasonably allocate security resources, and can effectively improve the initiative and preventiveness of security work. Meanwhile, the mobile body intersection intensity of the moving trajectory intersection point is obtained by collecting the mobile body density and the moving offset rate of the trajectory initial extension region, which can accurately quantify the busy degree and potential risk of the intersection point. The mobile body density reflects the personnel or object gathering situation of the intersection region, and the running offset rate reflects the regularity and stability of the mobile body running, and the combination of the two can comprehensively evaluate the congestion, conflict and other conditions that may occur at the intersection point, help the security personnel to take measures such as dredging and control in time, avoid the occurrence of safety accidents, and effectively protect the safety and order stability of the personnel in the security area, greatly enhance the scientificity and effectiveness of the security work.

[0144] The mobile analysis module divides the region travel trajectory intersection into a first type trajectory intersection and a second type trajectory intersection according to the region intersection intensity analysis data to obtain trajectory intersection division data, and analyzes the local traffic environment of the second type trajectory intersection to obtain traffic environment analysis data according to the analysis result;

[0145] Specifically as follows:

[0146] Obtain region intersection intensity analysis data, and obtain the mobile body intersection intensity corresponding to each region travel trajectory intersection according to the region intersection intensity analysis data;

[0147] Obtain an intersection intensity preset interval, if the mobile body intersection intensity is in the intersection intensity preset interval, the corresponding region travel trajectory intersection is divided into a first type trajectory intersection, if the mobile body intersection intensity is not in the intersection intensity preset interval, the corresponding region travel trajectory intersection is divided into a second type trajectory intersection, and trajectory intersection division data is obtained;

[0148] It should be noted here that:

[0149] In the present application, the history region travel trajectory intersection of the first type trajectory intersection divided by the intelligent security service management system is obtained, the mobile body intersection intensity corresponding to each history region travel trajectory intersection is obtained, the obtained plurality of mobile body intersection intensities are numerically compared, the maximum mobile body intersection intensity is set as the upper limit of the intersection intensity preset interval, and the minimum mobile body intersection intensity is set as the lower limit of the intersection intensity preset interval.

[0150] The space region corresponding to the second type trajectory intersection is analyzed, and traffic environment analysis data is obtained according to the analysis result;

[0151] Specifically as follows:

[0152] Each first type trajectory intersection corresponding to the traffic region is obtained, a plurality of intersection traffic regions are obtained, and a sample traffic region is randomly selected from the obtained plurality of intersection traffic regions;

[0153] It should be noted here that:

[0154] In the present application, the traffic region referred to here is specifically the traffic region closest to the first type trajectory intersection;

[0155] In the present application, the traffic region referred to here includes but is not limited to a narrow corridor, an elevator entrance and exit, and a gate;

[0156] In the present application, the traffic region referred to here is not a standard circle.

[0157] Obtaining the area of the region corresponding to the sample passing region to obtain the passing region area value, obtaining the perimeter of the region corresponding to the sample passing region to obtain the passing region perimeter value;

[0158] The passing region area value and the passing region perimeter value are calculated to obtain the region geometric passing index corresponding to the sample passing region;

[0159] The region geometric passing index corresponding to the sample passing region is calculated, and the specific formula is as follows:

[0160]

[0161] Wherein, Jhz is the region geometric passing index corresponding to the sample passing region, Ymj is the passing region area value, and Zcq is the passing region perimeter value;

[0162] It should be noted here that:

[0163] In the present application, the region geometric passing index corresponding to the sample passing region is collected, and the following data is collected:

[0164] Test data number Passing area area value Passing area perimeter value Area geometry passing index Test data 1 30m 2 ]]> 16m 44.16 Test data 2 42m 2 ]] 19m 61.37 Test data 3 36m 2 ]] 18m 50.23

[0165] The process of obtaining the region geometric passing index corresponding to the sample passing region is repeated, and the region geometric passing index corresponding to each intersection passing region is obtained, to obtain the region geometric passing index corresponding to the first type of trajectory intersection;

[0166] The region geometric passing index corresponding to the first type of trajectory intersection and the trajectory intersection division data are defined as passing environment analysis data;

[0167] It should be noted here that:

[0168] The present application classifies the trajectory intersection according to the intersection intensity of the moving body, and adopts differentiated security service strategy for different types, which is highly innovative and practical;

[0169] On the one hand, the passing region with high intersection intensity is early warned, which can make the security forces gather in advance, focus on defense, quickly respond to possible emergencies, effectively prevent safety accidents and chaotic situations, and nip the security risks in the bud;

[0170] On the other hand, the congestion prediction of the conventional interaction intensity area is combined with the actual geometric characteristics of the trajectory intersection passing area, the influence of the space layout on the personnel flow is fully considered, the prediction result is more in line with the actual situation, and the prediction hysteresis is reduced. In this way, the security service can accurately match the needs of different areas, reasonably allocate resources, timely guide the flow of people, avoid congestion intensification, and effectively ensure the smooth flow of personnel in the security area, safety, and significantly improve the overall effect and quality of security service.

[0171] The congestion prediction module predicts congestion in the passing area corresponding to the region travel trajectory intersection according to the passing environment analysis data, and issues a security service warning according to the prediction result;

[0172] Specifically as follows:

[0173] Obtain passing environment analysis data, and obtain trajectory intersection division data according to the passing environment analysis data;

[0174] According to the trajectory intersection division data, obtain the first type trajectory intersection and the second type trajectory intersection, and predict that the passing area corresponding to the first type trajectory intersection is a congestion area, and issue a security service warning;

[0175] Perform geometric passing index analysis on the passing area corresponding to the second type trajectory intersection, and issue a security service warning according to the analysis result;

[0176] Specifically as follows:

[0177] Obtain the region geometric passing index corresponding to each second type trajectory intersection, set a passing index congestion interval, if the region geometric passing index is in the passing index congestion interval, predict that the passing area corresponding to the corresponding second type trajectory intersection is a congestion area, and issue a security service warning, if the region geometric passing index is not in the passing index congestion interval, predict that the passing area corresponding to the corresponding second type trajectory intersection is a non-congestion area, and no security service warning is needed;

[0178] It should be noted here that:

[0179] In this application, the congestion area referred to here includes the case where the region geometric passing index is at the boundary of the passing index congestion interval.

[0180] In this application, the historical region geometric passing index corresponding to the second type trajectory intersection predicted by the intelligent security service management system as a congestion area is obtained, and the obtained multiple historical region geometric communication indexes are compared in value size. The largest historical region geometric communication index is set as the upper limit of the passing index congestion interval, and the smallest historical region geometric communication index is set as the lower limit of the passing index congestion interval, to obtain the passing index congestion interval.

[0181] The preferred embodiments of the application disclosed above are only to help explain the present application. The preferred embodiments are not intended to be exhaustive or to limit the application to the specific form disclosed. Many modifications and variations are possible in light of this teaching. It is intended that the specification and examples be considered as exemplary only, with the fact that over time, the preferred embodiments can be modified in many ways within the scope and spirit of the application. The application is defined by the claims and their full scope of equivalents.

Claims

1. A smart security service management system, characterized by, Comprise: Data acquisition module: the mobile trajectory dynamic acquisition and analysis of the security sub-area in the target security area, according to the analysis result, the intersection point of the direction trajectory marker line corresponding to the security sub-area in the target security area is obtained, the region trajectory intersection point is obtained, the mobile body intersection intensity is obtained by analyzing the mobile body path offset rate and the mobile body density of the region trajectory intersection point, and the region intersection intensity analysis data is obtained; The region intersection intensity analysis data is obtained, specifically as follows: The field region needing to be managed by intelligent security service is obtained, and the target security area is obtained; When the target security area is managed by security service, a time window is set with the time value corresponding to the current time as the window end time point; The target security area is divided into multiple security sub-areas, the number of mobile bodies corresponding to each security sub-area is counted to obtain the region mobile body number value, the region area value corresponding to each security sub-area is obtained to obtain the security sub-area area value, and the ratio of the region mobile body number value to the security area area value is calculated to obtain the region mobile body density; A mobile body density preset interval is set, if the region mobile body density is in the region mobile body density preset interval, the security sub-area is divided into path analysis region, if the region mobile body density is not in the region mobile body density preset interval, the security sub-area is divided into path region without planning, the region main flow trajectory direction corresponding to each path analysis region is obtained, and the angle bisector of the direction characteristic angle corresponding to the region main flow trajectory direction is obtained to obtain multiple direction trajectory marker lines; The intersection points of the direction trajectory marker lines in the target security area are obtained, and multiple region trajectory intersection points are obtained; Any sample trajectory intersection point is selected from the obtained multiple region trajectory intersection points, the trajectory feature of the sample trajectory intersection point is analyzed, and the mobile body intersection intensity corresponding to the sample trajectory intersection point is obtained according to the analysis result; The mobile body intersection intensity corresponding to each region trajectory intersection point is obtained, and the region intersection intensity analysis data is obtained; Mobile analysis module: according to the region intersection intensity analysis data, the region trajectory intersection point is divided into first type trajectory intersection point and second type trajectory intersection point to obtain trajectory intersection point division data, the local traffic environment of the second type trajectory intersection point is analyzed, and the traffic environment analysis data is obtained according to the analysis result; The space region corresponding to the second type trajectory intersection point is analyzed, specifically as follows: Each first type trajectory intersection point corresponding to the traffic area is obtained, multiple intersection traffic areas are obtained, and any sample traffic area is selected from the obtained multiple intersection traffic areas; The region area corresponding to the sample traffic area is obtained to obtain the traffic area value, and the region perimeter corresponding to the sample traffic area is obtained to obtain the traffic area perimeter value; The traffic area value and the traffic area perimeter value are calculated to obtain the region geometric traffic index corresponding to the sample traffic area; Obtain the region geometric passing index corresponding to each intersection passing region respectively to obtain the region geometric passing index corresponding to the first type trajectory intersection; Define the region geometric passing index corresponding to the first type trajectory intersection and the trajectory intersection division data as the passing environment analysis data; The congestion prediction module: according to the passing environment analysis data, the passing region corresponding to the region travel trajectory intersection is predicted, and the security service warning is carried out according to the prediction result.

2. The intelligent security service management system according to claim 1, wherein The region mainstream trajectory direction corresponding to the sample path to be analyzed region is obtained, specifically as follows: In the obtained multiple path to be analyzed regions, a sample path to be analyzed region is selected at random, the time window at the current time is set as the real-time time window, the mobile body moving path analysis is carried out on the sample path to be analyzed region in the real-time time window, and the mainstream trajectory direction corresponding to the real-time time window is obtained; Select a historical time window before a real-time time window, obtain the mainstream trajectory direction corresponding to each historical time window respectively, and count the number of mainstream trajectory directions belonging to the first direction interval to the alpha direction interval to obtain the first mainstream trajectory number value to the alpha mainstream trajectory number value. The maximum mainstream trajectory number value is set as the region mainstream trajectory direction corresponding to the sample path to be analyzed region.

3. The intelligent security service management system according to claim 2, wherein The mainstream trajectory direction corresponding to the real-time time window is obtained, specifically as follows: The security region center point is obtained at the geometric center of the sample path to be analyzed region, a straight line perpendicular to the north is made through the security region center point, the path positive direction marker line is obtained, the path positive direction marker line is taken as the direction starting edge, and the security region center point is taken as the starting point. A feature direction line passing through the security region center point is set every a degree, and the included angle formed by any two adjacent feature direction lines is set as the direction feature included angle; According to the numerical value of the direction feature included angle, the feature direction lines are respectively named as the first region direction line to the alpha region direction line, and the angle interval covered by any two region direction lines at the security region center point is respectively marked as the first direction interval to the alpha direction interval; The starting time point corresponding to the real-time time window is set as the first window feature time point, and the ending time point corresponding to the real-time time window is obtained to obtain the second window feature time point; The mobile body position of each mobile body in the sample path to be analyzed region corresponding to the first window feature time point is obtained to obtain a plurality of mobile start positions, and the mobile body position of each mobile body in the sample path to be analyzed region corresponding to the second window feature time point is obtained to obtain a plurality of mobile end positions; The position connecting line of the mobile body at the mobile start position and the mobile end position is obtained to obtain a plurality of real-time window moving paths, the forward included angle between each real-time moving path and the path positive direction marker line is obtained to obtain a plurality of real-time path moving azimuth angles; The number of real-time path moving azimuth angles in the first direction interval to the alpha direction interval is counted, and the direction interval corresponding to the maximum direction trajectory number value is set as the mainstream trajectory direction corresponding to the real-time time window.

4. The intelligent security service management system of claim 1, wherein The mobile body intersection intensity is acquired in the following manner: A plurality of azimuth trajectory marker lines intersecting at the sample trajectory intersection point are acquired, a path to-be-analyzed region corresponding to each azimuth trajectory marker line is acquired, a plurality of path to-be-analyzed regions are obtained, a regional mobile body density in the path to-be-analyzed region is acquired, and the regional mobile body density is obtained. The regional offset rate corresponding to each path to-be-analyzed region is acquired respectively, and the regional offset rate is obtained. The regional mobile body density and the regional offset rate are used to calculate the mobile body intersection intensity corresponding to the sample trajectory intersection point.

5. The intelligent security service management system according to claim 4, wherein, The regional offset rate is acquired in the following manner: An F1 path to-be-analyzed region is selected from the acquired path to-be-analyzed regions, a mobile body in the F1 path to-be-analyzed region is subjected to mobile offset analysis, and an F1 regional offset rate is acquired according to the analysis result. An arbitrary characteristic mobile body is selected from the mobile bodies in the F1 path to-be-analyzed region, a time window in which the a characteristic mobile bodies move is acquired, two time windows that are continuous in time range are set as a time window combination, and c time window combinations are obtained. The two time windows in the time window combination are named as a first time window and a second time window respectively, a window moving path of the characteristic mobile body corresponding to the first time window and the second time window is acquired, and a first window moving path and a second window moving path are obtained. A transition time point between the first time window and the second time window is acquired, a window characteristic time point is obtained, and a window transition position point at which the characteristic mobile body is located at the window characteristic time point is acquired. An included angle formed by the first window moving path and the second window moving path at the window transition position point is acquired, a trajectory offset included angle corresponding to each time window combination is obtained, and the c trajectory offset included angles are averaged to obtain a regional offset included angle corresponding to the characteristic mobile body. A regional offset included angle corresponding to each mobile body is acquired, and a plurality of regional offset included angles are obtained. The time lengths covered by each time window combination are summed to obtain a window cumulative coverage duration, and the c regional offset included angles and the window cumulative coverage duration are used to calculate the F1 regional offset rate.

6. The intelligent security service management system of claim 1, wherein The passing environment analysis data is acquired in the following manner: Regional intersection intensity analysis data is acquired, the mobile body intersection intensity corresponding to each regional travel trajectory intersection point is acquired according to the regional intersection intensity analysis data; An intersection intensity preset interval is acquired, if the mobile body intersection intensity is in the intersection intensity preset interval, the corresponding regional travel trajectory intersection point is divided into a first type trajectory intersection point, if the mobile body intersection intensity is not in the intersection intensity preset interval, the corresponding regional travel trajectory intersection point is divided into a second type trajectory intersection point, and trajectory intersection point division data is obtained; The space region corresponding to the second type trajectory intersection point is subjected to passing environment analysis, and the passing environment analysis data is obtained according to the analysis result.

7. The intelligent security service management system of claim 1, wherein The passing region is subjected to security service early warning in the following manner: The passing environment analysis data is acquired, and the trajectory intersection point division data is acquired according to the passing environment analysis data. According to the trajectory intersection, the data is divided into first type trajectory intersection and second type trajectory intersection, and the passing area corresponding to the first type trajectory intersection is predicted as a congestion area, and a security service warning is issued; The passing area corresponding to the second type trajectory intersection is analyzed by geometric passing index, and a security service warning is issued according to the analysis result.

8. The intelligent security service management system according to claim 7, wherein, The geometric passing index of the passing area is analyzed, and the specific steps are as follows: The geometric passing index of the area corresponding to each second type trajectory intersection is obtained, the passing index congestion interval is set, if the geometric passing index of the area is in the passing index congestion interval, the passing area corresponding to the second type trajectory intersection is predicted as a congestion area, and a security service warning is issued, if the geometric passing index of the area is not in the passing index congestion interval, the passing area corresponding to the second type trajectory intersection is predicted as a non-congestion area, and no security service warning is needed.

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