A smart campus security monitoring management method and system based on the Internet of Things

Abstract

This invention discloses a smart campus security monitoring and management method and system based on the Internet of Things (IoT), belonging to the field of campus security monitoring technology. By traversing the locations of cameras and access control devices within the campus, a monitoring route set is generated, achieving comprehensive coverage of key areas of the campus. Through IoT-synchronized settings for data collection from cameras and access control devices, a synchronized collection sequence set is generated, improving data accuracy and synchronization. Based on the collected data, a mean regression sequence is obtained, quantifying the vulnerable time segments of different access routes and assessing the monitoring intensity of different access control device locations. This invention achieves coordinated monitoring of cameras and access control devices within the campus while simultaneously uncovering potential patterns in the data, thereby enabling real-time assessment of the campus security situation and providing a sequence basis for security checks based on different levels of importance, thus improving the effectiveness of campus security monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of campus safety monitoring, and in particular to a smart campus safety monitoring management method and system based on the Internet of Things. Background Art

[0002] With the rapid development and popularization of Internet of Things technology, the construction of smart campuses has become an important means to improve school safety management and optimize the allocation of educational resources. In the construction of smart campuses, security monitoring management not only requires real-time monitoring of the security situation on campus, but also provides strong support for security management through data analysis;

[0003] Traditional campus security monitoring and management methods mainly rely on manual patrols and video surveillance playback, which have problems such as low monitoring efficiency, slow response speed, and insufficient information integration. Especially in large campuses, due to the large number of monitoring points and wide range, manual monitoring is difficult to achieve comprehensive coverage and timely response, resulting in limited monitoring effects. Summary of the invention

[0004] The purpose of the present invention is to provide a smart campus security monitoring management method and system based on the Internet of Things to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A smart campus security monitoring and management system based on the Internet of Things, the system comprises: an Internet of Things module, a data archive module, a data analysis center module and a data update module; the data update module is respectively connected to the Internet of Things module, the data archive module and the data analysis center module in sequence, the data archive module is respectively connected to the Internet of Things module and the data analysis center module in sequence, and the Internet of Things module is connected to the data analysis center module;

[0007] The Internet of Things module is used to build an Internet of Things channel between the camera device and the access control device, and to synchronize the data collection between the camera device and the access control device through a time encoder;

[0008] The data archive module is used to import the campus map and traverse the route of traffic on the archived campus;

[0009] The data analysis center module analyzes and evaluates the monitoring intensity of the access control device locations on campus based on the synchronous behavior and passage routes of the data collection to generate a security checklist;

[0010] The data update module is used to update the campus map, update the operating status of the camera equipment and the access control equipment, regularly adjust the synchronization of the data collection, continuously evaluate the monitoring intensity of the location points of the access control equipment on campus, and output the security inspection list in real time.

[0011] Further, the Internet of Things module includes a synchronization sequence generation unit and a synchronization control unit which are sequentially connected in sequence;

[0012] The synchronization sequence generating unit is used to generate a synchronization acquisition sequence set, wherein the synchronization acquisition sequence set includes a plurality of synchronization sequence segments;

[0013] The synchronization control unit controls the camera device and the access control device to collect data according to the synchronization acquisition sequence set based on the Internet of Things channel between the camera device and the access control device to obtain feedback data and observation data.

[0014] Further, the data archive module includes a device statistics unit and a traffic route statistics unit which are sequentially connected;

[0015] The device counting unit is used to count the number of camera device location points and access control device location points respectively, and encode them respectively;

[0016] The passing route statistics unit is used to obtain all passing routes between any two access control device location points to generate a monitoring route set.

[0017] Further, the data analysis center module includes a data processing unit and a data mining unit connected in sequence;

[0018] The data processing unit obtains the data proportion and the mean value of the data proportion at the camera position point in the synchronization sequence segment based on the feedback data and the observation data, and depicts the dynamic coordinate points in the form of a two-dimensional coordinate system to obtain a mean regression sequence;

[0019] The data mining unit quantifies the monitoring security weak time segment set of the passage route based on the mean regression sequence, and evaluates the monitoring security weakness between the access control device location points and the monitoring strength of the access control device location points to prepare a security checklist.

[0020] Furthermore, when the operating status of the camera device or the access control device is faulty, the traffic route information within the campus is updated to the data archive module.

[0021] A smart campus security monitoring and management method based on the Internet of Things, the method comprises the following steps:

[0022] Step S1: traverse the camera device location points and access control device location points in the campus, and form a monitoring route set by all the passage routes between any two access control device location points, and the monitoring route set also includes a monitoring point set, and the monitoring point set is composed of the camera device location points included in the passage route;

[0023] Step S2: Synchronous settings of the Internet of Things for data collection of camera devices and access control devices are performed to generate a synchronous collection sequence set, in which feedback data of access control device locations and observation data of camera device locations are collected respectively, wherein the feedback data is the sum of the number of people passing through any two access control device locations, and the observation data is the number of people photographed by the camera installed at the camera location;

[0024] Step S3: Based on the feedback data and the observation data, the data proportions and the mean values ​​of the data proportions at different camera device position points in the synchronization sequence segment are obtained, and a dynamic observation curve generated by the data proportions and a straight line generated by the mean values ​​of the data proportions are respectively depicted in a two-dimensional coordinate system, and the horizontal coordinate values ​​of the dynamic coordinate points where the dynamic observation curve and the straight line intersect constitute a mean regression sequence of different camera device position points;

[0025] Step S4: Taking the monitoring point set as the quantization range, perform an intersection operation on the mean regression sequence, and perform a set subtraction operation between the synchronous acquisition sequence set and the set obtained by the intersection operation to obtain a monitoring security weak time segment set, average the ratio of the number of synchronous sequence segments contained in the monitoring security weak time segment set to the number of synchronous sequence segments contained in the synchronous acquisition sequence set, use the average value as the monitoring intensity value of the access control device location point, and generate a security inspection list.

[0026] Furthermore, the specific implementation process of step S1 includes:

[0027] Importing a campus map, marking camera location points and access control device location points in the campus map, and counting the number of camera location points and access control device location points, wherein the camera devices are installed on the routes in the campus, and one camera device is installed corresponding to one camera location point, and the camera device has a rotating camera function;

[0028] Uniformly number the access control device locations, obtain all the routes between any two access control device locations, and generate a monitoring route set, recorded as ,in, and Respectively represent the i-th and j-th access control device locations, and i≠j, represents the ath pass route, Indicates the route The monitoring point set consists of the camera device location points contained in , and , A represents the total number of accessible routes, represents the bth camera device location point, and B represents the total number of camera device location points.

[0029] Furthermore, the specific implementation process of step S2 includes:

[0030] An IoT channel is established between the camera device and the access control device, so that the camera device and the access control device have synchronization of data acquisition, and a synchronous acquisition sequence set is generated, which is recorded as ,in, represents the xth synchronization sequence segment composed of two adjacent synchronization time nodes, and y represents the total number of synchronization sequence segments;

[0031] In the synchronization sequence segment Internal statistics of access control device locations and The sum of the number of people passing through is recorded as feedback data ; In the synchronization sequence segment Count the number of people photographed by each camera device and click the camera location The number of people photographed by the corresponding camera equipment is recorded as observation data .

[0032] Furthermore, the specific implementation process of step S3 includes:

[0033] Based on the feedback data and observation data, the synchronization sequence fragment is obtained Internal camera location The proportion of data ; Calculate the camera position point within the scope of the synchronous acquisition sequence set T The average value of the data proportion ;

[0034] Take the synchronization time node as the horizontal axis and the data ratio as the vertical axis to get the dynamic coordinate point , sequentially and smoothly connect each dynamic coordinate point to obtain the camera device position point within the scope of the synchronous acquisition sequence set T The dynamic observation curve at ;

[0035] Get the average value of data proportion Generated straight lines and dynamic observation curves The horizontal coordinate value of the intersecting dynamic coordinate point is rounded down to get the camera device position point The mean reversion sequence of ,and ;

[0036] According to the above method, by utilizing the phenomenon that a set of data usually regresses to its mean value or long-term trend line over a period of time, the flow dynamics of people on campus and the mean flow of people on each route are characterized. The straight line generated by the mean of the data proportions intersects with the dynamic observation curve to obtain a mean reversion sequence. Each synchronized sequence segment in the mean reversion sequence represents the flow pattern of the route.

[0037] Furthermore, the specific implementation process of step S4 includes:

[0038] Based on monitoring point set , quantify the route through the mean reversion sequence Monitoring security weak time segment set , quantified formula ;

[0039] Evaluate the location of access control devices on campus based on the set of vulnerable time segments monitored The intensity of monitoring , the evaluation formula , , where Indicates the location of the access control device and The monitoring security weakness between them, I represents the total number of access control device location points, Indicates the set of time segments for monitoring security vulnerabilities Find the set obtained by the union operation The number of synchronization sequence fragments contained in ;

[0040] According to the above method, the monitoring security weak time segment set records the synchronous sequence segments other than the overlap in the mean regression sequence of each passage route, and these synchronous sequence segments can reflect the irregular phenomenon of the passage route; when passing through a certain access control device location point to other access control device location points, the superposition evaluation of the irregular phenomena of each passage route is used to obtain the monitoring intensity of the access control device location point, and the greater the monitoring intensity, the lower the security level of the access control device location point;

[0041] The access control device locations are sorted in descending order of monitoring intensity to obtain a security checklist.

[0042] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in a smart campus security monitoring management method and system based on the Internet of Things provided by the present invention, a monitoring route set is generated by traversing the camera equipment location points and the access control equipment location points in the campus, thereby achieving comprehensive coverage of key areas of the campus; a synchronous acquisition sequence set is generated by performing Internet of Things synchronization settings for data collection on the camera equipment and the access control equipment, thereby improving the accuracy and synchronization of the data; based on the collected data, a mean reversion sequence is analyzed to quantify the monitoring security weak time segment sets of different passage routes, and evaluate the monitoring strength of different access control equipment location points; while realizing the linkage monitoring of the camera equipment and the access control equipment in the campus, the present invention mines the potential rules in the data, thereby being able to evaluate the safety status of the campus in real time, and provide a sequential basis of different importance levels for security inspections in the campus, thereby improving the campus safety monitoring effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0044] Figure 1 It is a schematic diagram of the steps of a smart campus security monitoring and management method based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0045] 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.

[0046] In the first embodiment of the present invention, a smart campus security monitoring and management system based on the Internet of Things is provided, the system comprising: an Internet of Things module, a data archive module, a data analysis center module and a data update module; the data update module is respectively connected to the Internet of Things module, the data archive module and the data analysis center module in sequence, the data archive module is respectively connected to the Internet of Things module and the data analysis center module in sequence, and the Internet of Things module and the data analysis center module are connected.

[0047] The Internet of Things module is used to build an Internet of Things channel between the camera device and the access control device, and to synchronize the data collection between the camera device and the access control device through a time encoder;

[0048] Wherein, the Internet of Things module comprises a synchronization sequence generation unit and a synchronization control unit which are sequentially connected;

[0049] The synchronization sequence generating unit is used to generate a synchronization acquisition sequence set, wherein the synchronization acquisition sequence set includes a plurality of synchronization sequence segments;

[0050] The synchronization control unit controls the camera device and the access control device to collect data according to the synchronization acquisition sequence set based on the Internet of Things channel between the camera device and the access control device to obtain feedback data and observation data.

[0051] The data archive module is used to import the campus map and traverse the route of traffic on the archived campus;

[0052] Wherein, the data archive module includes a device statistics unit and a traffic route statistics unit which are sequentially connected;

[0053] The device counting unit is used to count the number of camera device location points and access control device location points respectively, and encode them respectively;

[0054] The passing route statistics unit is used to obtain all passing routes between any two access control device location points to generate a monitoring route set.

[0055] The data analysis center module analyzes and evaluates the monitoring intensity of the access control device locations on campus based on the synchronous behavior and passage routes of the data collection to generate a security checklist;

[0056] Wherein, the data analysis center module includes a data processing unit and a data mining unit connected in sequence;

[0057] The data processing unit obtains the data proportion and the mean value of the data proportion at the camera position point in the synchronization sequence segment based on the feedback data and the observation data, and depicts the dynamic coordinate points in the form of a two-dimensional coordinate system to obtain a mean regression sequence;

[0058] The data mining unit quantifies the monitoring security weak time segment set of the passage route based on the mean regression sequence, and evaluates the monitoring security weakness between the access control device location points and the monitoring strength of the access control device location points to prepare a security checklist.

[0059] The data update module is used to update the campus map, update the operating status of the camera equipment and the access control equipment, regularly adjust the synchronization of the data collection, continuously evaluate the monitoring intensity of the access control equipment location points on campus, and output the security checklist in real time;

[0060] Among them, when the operating status of the camera equipment or the access control equipment is faulty, the traffic route information within the campus is updated to the data archive module.

[0061] See also Figure 1 In the second embodiment, a smart campus security monitoring management method based on the Internet of Things is provided, which is applied to the smart campus security monitoring management system introduced in the first embodiment. The method includes the following steps:

[0062] Step S1: traverse the camera device location points and access control device location points in the campus, and form a monitoring route set by all the passage routes between any two access control device location points, and the monitoring route set also includes a monitoring point set, and the monitoring point set is composed of the camera device location points included in the passage route;

[0063] Exemplarily, a campus map is imported, and camera device location points and access control device location points are marked in the campus map, and the number of camera device location points and access control device location points are counted, wherein the camera devices are installed on the routes in the campus, and one camera device is installed corresponding to one camera device location point, and the camera device has a rotating camera function;

[0064] Uniformly number the access control device locations, obtain all the routes between any two access control device locations, and generate a monitoring route set, recorded as ,in, and Respectively represent the i-th and j-th access control device locations, and i≠j, represents the ath pass route, Indicates the route The monitoring point set consists of the camera device location points contained in , and , A represents the total number of accessible routes, represents the bth camera device location point, and B represents the total number of camera device location points.

[0065] Step S2: Synchronous settings of the Internet of Things for data collection of camera devices and access control devices are performed to generate a synchronous collection sequence set, in which feedback data of access control device locations and observation data of camera device locations are collected respectively, wherein the feedback data is the sum of the number of people passing through any two access control device locations, and the observation data is the number of people photographed by the camera installed at the camera location;

[0066] For example, an IoT channel is established between the camera device and the access control device, so that the camera device and the access control device have synchronization of data collection, and a synchronous collection sequence set is generated, which is recorded as ,in, represents the xth synchronization sequence segment composed of two adjacent synchronization time nodes, and y represents the total number of synchronization sequence segments;

[0067] In the synchronization sequence segment Internal statistics of access control device locations and The sum of the number of people passing through is recorded as feedback data ; In the synchronization sequence segment Count the number of people photographed by each camera device and click the camera location The number of people photographed by the corresponding camera equipment is recorded as observation data .

[0068] Step S3: Based on the feedback data and the observation data, the data proportions and the mean values ​​of the data proportions at different camera device position points in the synchronization sequence segment are obtained, and a dynamic observation curve generated by the data proportions and a straight line generated by the mean values ​​of the data proportions are respectively depicted in a two-dimensional coordinate system, and the horizontal coordinate values ​​of the dynamic coordinate points where the dynamic observation curve and the straight line intersect constitute a mean regression sequence of different camera device position points;

[0069] Exemplarily, based on the feedback data and the observation data, a synchronization sequence segment is obtained Internal camera location The proportion of data ; Calculate the camera position point within the scope of the synchronous acquisition sequence set T The average value of the data proportion ;

[0070] Take the synchronization time node as the horizontal axis and the data ratio as the vertical axis to get the dynamic coordinate point , sequentially and smoothly connect each dynamic coordinate point to obtain the camera device position point within the scope of the synchronous acquisition sequence set T The dynamic observation curve at ;

[0071] Get the average value of data proportion Generated straight lines and dynamic observation curves The horizontal coordinate value of the intersecting dynamic coordinate point is rounded down to get the camera device position point The mean reversion sequence of ,and .

[0072] Step S4: Taking the monitoring point set as the quantization range, performing an intersection operation on the mean regression sequence, and performing a set subtraction operation between the synchronous acquisition sequence set and the set obtained by the intersection operation to obtain a monitoring security weak time segment set, averaging the ratio of the number of synchronous sequence segments contained in the monitoring security weak time segment set to the number of synchronous sequence segments contained in the synchronous acquisition sequence set, taking the average value as the monitoring intensity value of the access control device location point, and generating a security inspection list;

[0073] For example, based on the monitoring point set , quantify the route through the mean reversion sequence Monitoring security weak time segment set , quantified formula ;

[0074] Evaluate the location of access control devices on campus based on the set of vulnerable time segments monitored The intensity of monitoring , the evaluation formula , , where Indicates the location of the access control device and The monitoring security weakness between them, I represents the total number of access control device location points, Indicates the set of time segments for monitoring security vulnerabilities Find the set obtained by the union operation The number of synchronization sequence fragments contained in ;

[0075] The access control device locations are sorted in descending order of monitoring intensity to obtain a security checklist.

[0076] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0077] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A smart campus security monitoring and management method based on the Internet of Things, characterized in that: The method comprises the following steps: Step S1: traverse the camera device location points and access control device location points in the campus, and form a monitoring route set by all the passage routes between any two access control device location points, and the monitoring route set also includes a monitoring point set, and the monitoring point set is composed of the camera device location points included in the passage route; Step S2: Synchronous settings of the Internet of Things for data collection of camera devices and access control devices are performed to generate a synchronous collection sequence set, in which feedback data of access control device locations and observation data of camera device locations are collected respectively, wherein the feedback data is the sum of the number of people passing through any two access control device locations, and the observation data is the number of people photographed by the camera installed at the camera location; Step S3: Based on the feedback data and the observation data, the data proportions and the mean values ​​of the data proportions at different camera device position points in the synchronization sequence segment are obtained, and a dynamic observation curve generated by the data proportions and a straight line generated by the mean values ​​of the data proportions are respectively depicted in a two-dimensional coordinate system, and the horizontal coordinate values ​​of the dynamic coordinate points where the dynamic observation curve and the straight line intersect constitute a mean regression sequence of different camera device position points; Step S4: Taking the monitoring point set as the quantization range, perform an intersection operation on the mean regression sequence, and perform a set subtraction operation between the synchronous acquisition sequence set and the set obtained by the intersection operation to obtain a monitoring security weak time segment set, average the ratio of the number of synchronous sequence segments contained in the monitoring security weak time segment set to the number of synchronous sequence segments contained in the synchronous acquisition sequence set, use the average value as the monitoring intensity value of the access control device location point, and generate a security inspection list.

2. According to the method for security monitoring and management of a smart campus based on the Internet of Things in claim 1, it is characterized in that: The specific implementation process of step S1 includes: Importing a campus map, marking camera location points and access control device location points in the campus map, and counting the number of camera location points and access control device location points, wherein the camera devices are installed on the routes in the campus, and one camera device is installed corresponding to one camera location point, and the camera device has a rotating camera function; Uniformly number the access control device locations, obtain all the routes between any two access control device locations, and generate a monitoring route set, recorded as ,in, and Respectively represent the i-th and j-th access control device locations, and i≠j, represents the ath pass route, Indicates the route The monitoring point set consists of the camera device location points contained in , and , A represents the total number of accessible routes, represents the bth camera device location point, and B represents the total number of camera device location points.

3. According to the method for security monitoring and management of a smart campus based on the Internet of Things in claim 2, it is characterized in that: The specific implementation process of step S2 includes: An IoT channel is established between the camera device and the access control device, so that the camera device and the access control device have synchronization of data acquisition, and a synchronous acquisition sequence set is generated, which is recorded as ,in, represents the xth synchronization sequence segment composed of two adjacent synchronization time nodes, and y represents the total number of synchronization sequence segments; In the synchronization sequence segment Internal statistics of access control device locations and The sum of the number of people passing through is recorded as feedback data ; In the synchronization sequence segment Count the number of people photographed by each camera device and click the camera location The number of people photographed by the corresponding camera equipment is recorded as observation data .

4. According to the method for security monitoring and management of a smart campus based on the Internet of Things in claim 3, it is characterized in that: The specific implementation process of step S3 includes: Based on the feedback data and observation data, the synchronization sequence fragment is obtained Internal camera location The proportion of data ; Calculate the camera position point within the scope of the synchronous acquisition sequence set T The average value of the data proportion ; Take the synchronization time node as the horizontal axis and the data ratio as the vertical axis to get the dynamic coordinate point , sequentially and smoothly connect each dynamic coordinate point to obtain the camera device position point within the scope of the synchronous acquisition sequence set T The dynamic observation curve at ; Get the average value of data proportion Generated straight lines and dynamic observation curves The horizontal coordinate value of the intersecting dynamic coordinate point is rounded down to get the camera device position point The mean reversion sequence of ,and .

5. According to the method for security monitoring and management of a smart campus based on the Internet of Things in claim 4, it is characterized in that: The specific implementation process of step S4 includes: Based on monitoring point set , quantify the route through the mean reversion sequence Monitoring security weak time segment set , quantified formula ; Evaluate the location of access control devices on campus based on the set of vulnerable time segments monitored The intensity of monitoring , the evaluation formula , , where Indicates the location of the access control device and The monitoring security weakness between them, I represents the total number of access control device location points, Indicates the set of time segments for monitoring security vulnerabilities Find the set obtained by the union operation The number of synchronization sequence fragments contained in ; The access control device locations are sorted in descending order of monitoring intensity to obtain a security checklist.

6. A smart campus security monitoring and management system based on the Internet of Things, executing a smart campus security monitoring and management method based on the Internet of Things as described in any one of claims 1-5, characterized in that: The system comprises: an Internet of Things module, a data archive module, a data analysis center module and a data update module; the data update module is respectively connected to the Internet of Things module, the data archive module and the data analysis center module in sequence, the data archive module is respectively connected to the Internet of Things module and the data analysis center module in sequence, and the Internet of Things module is connected to the data analysis center module; The Internet of Things module is used to build an Internet of Things channel between the camera device and the access control device, and to synchronize the data collection between the camera device and the access control device through a time encoder; The data archive module is used to import the campus map and traverse the route of traffic on the archived campus; The data analysis center module analyzes and evaluates the monitoring intensity of the access control device locations on campus based on the synchronous behavior and passage routes of the data collection to generate a security checklist; The data update module is used to update the campus map, update the operating status of the camera equipment and the access control equipment, regularly adjust the synchronization of the data collection, continuously evaluate the monitoring intensity of the location points of the access control equipment on campus, and output the security inspection list in real time.

7. The smart campus security monitoring and management system based on the Internet of Things according to claim 6 is characterized in that: The Internet of Things module includes a synchronization sequence generation unit and a synchronization control unit that are sequentially connected; The synchronization sequence generating unit is used to generate a synchronization acquisition sequence set, wherein the synchronization acquisition sequence set includes a plurality of synchronization sequence segments; The synchronization control unit controls the camera device and the access control device to collect data according to the synchronization acquisition sequence set based on the Internet of Things channel between the camera device and the access control device to obtain feedback data and observation data.

8. The smart campus security monitoring and management system based on the Internet of Things according to claim 6 is characterized in that: The data archive module includes a device statistics unit and a traffic route statistics unit which are sequentially connected; The device counting unit is used to count the number of camera device location points and access control device location points respectively, and encode them respectively; The passing route statistics unit is used to obtain all passing routes between any two access control device location points to generate a monitoring route set.

9. The smart campus security monitoring and management system based on the Internet of Things according to claim 6 is characterized in that: The data analysis center module includes a data processing unit and a data mining unit connected in sequence; The data processing unit obtains the data proportion and the mean value of the data proportion at the camera position point in the synchronization sequence segment based on the feedback data and the observation data, and depicts the dynamic coordinate points in the form of a two-dimensional coordinate system to obtain a mean regression sequence; The data mining unit quantifies the monitoring security weak time segment set of the passage route based on the mean regression sequence, and evaluates the monitoring security weakness between the access control device location points and the monitoring strength of the access control device location points to prepare a security checklist.

10. The smart campus security monitoring and management system based on the Internet of Things according to claim 6 is characterized in that: When the operating status of the camera equipment or the access control equipment is faulty, the traffic route information within the campus is updated to the data archive module.

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