Public place security inspection management system based on Internet of Things

Abstract

The invention relates to the field of security inspection management, and particularly discloses a public place security inspection management system based on Internet of Things, which is characterized in that a plurality of fixed inspection nodes are arranged in a key inspection area according to public place types and layout identification, and the rationality of the arrangement of the fixed inspection nodes is ensured; each to-be-selected inspection route of the inspection equipment is formulated according to a fixed inspection node, a historical emergency location and current pedestrian flow distribution, and an optimal inspection route is screened according to an inspection coverage degree and an inspection equipment energy consumption evaluation index, so that the dynamic planning and adjustment of the inspection route of the inspection equipment are realized, and the inspection efficiency is improved; according to the method, video data and measurement data collected by fixed inspection nodes and inspection equipment are extracted, hidden danger points in a public place are identified and safety risk levels are evaluated and corresponding early warning is performed in combination with a safety event sample map library and an environment parameter range, multi-source data fusion is realized, and the judgment precision of safety risks in a complex scene is improved.

Description

Technical Field

[0001] The present invention relates to the field of security patrol management, and more particularly to a public place security patrol management system based on the Internet of Things. Background Art

[0002] With the rapid economic development and the acceleration of urbanization, the number and scale of public places are constantly expanding, such as shopping malls, stations, schools, hospitals, etc. These places are densely populated, highly mobile, and have frequent activities, which increases security risks. Accidents such as theft, robbery, fire, and stampede occur from time to time, posing a serious threat to people's lives and property.

[0003] Through regular security inspections, various safety hazards can be discovered and eliminated in a timely manner, such as facility and equipment failures, fire hazards, public security issues, etc., thereby effectively preventing the occurrence of various safety accidents and ensuring the life and property safety of people in public places.

[0004] However, the existing security inspection management in public places still has some limitations and shortcomings in practical applications.

[0005] For example, the existing Chinese patent with authorization announcement number CN111862380B discloses a smart security patrol management method, which analyzes whether a first security event occurs at a patrol security node based on the first discrimination data of the patrol security node; when the first security event occurs, analyzes whether a second security event occurs at an adjacent security node based on the second discrimination data; when the second security event occurs, updates the first discrimination data based on the second discrimination data to obtain security patrol data, and obtains a protection warning level based on the security patrol data; when the protection warning level is higher than the patrol warning level, analyzes the security patrol data based on environmental factors and behavioral factors to obtain a target patrol area, and the patrol robot performs patrol operations in the target patrol area. This invention determines the target patrol area through collaborative management of security nodes, thereby improving patrol accuracy and efficiency.

[0006] For example, an existing Chinese patent with publication number CN118262426A discloses a security patrol method and related equipment, and its application embodiment method includes: obtaining target image data and target position data of a security patrol area; generating target map data corresponding to the security patrol area based on the target image data and the target position data, and sending the target map data to the security robot; configuring a target patrol plan of the security robot according to the target map data; wherein the target patrol plan at least includes the security robot executing a corresponding patrol plan and corresponding patrol reference data in the security patrol area; obtaining target parameter data collected by the security robot according to the target patrol plan, and comparing the patrol reference data with the target parameter data to perform statistical analysis on the security patrol area.

[0007] The above patent does not carry out real-time planning and adjustment of the inspection path of the inspection robot, which may make the inspection incomplete and lack of specificity, and thus the efficiency of the inspection cannot be effectively improved. Summary of the invention

[0008] In view of the above problems, the present invention proposes a public place security patrol management system based on the Internet of Things to realize the function of security patrol management.

[0009] The technical solution adopted by the present invention to solve its technical problem is: the present invention provides a public place security patrol management system based on the Internet of Things, including: a patrol node deployment module: identifying key patrol areas according to the type and layout of the public place, and deploying a number of fixed patrol nodes.

[0010] Inspection route planning module: formulates the candidate inspection routes for inspection equipment according to fixed inspection nodes, historical emergency locations and current traffic distribution, and selects the best inspection route according to inspection coverage and inspection equipment energy consumption evaluation indicators.

[0011] Potential danger point identification module: extracts video data and measurement data collected by fixed inspection nodes and inspection equipment, and combines them with the security event sample gallery and environmental parameter range to identify potential danger points in public places and send their locations.

[0012] Security risk assessment module: Assess the security risk level and issue corresponding warnings based on the security event sample images and environmental parameter values ​​matched with the video data of each potential risk point.

[0013] Database: Stores the layout of public places, key inspection areas of various public places, and sample libraries of security incidents, as well as the inspection speed of inspection equipment and energy consumption per unit inspection time. 。

[0014] Based on the above embodiments, the specific working process of the inspection route planning module includes: retrieving historical emergency information from the emergency management department of the public place, obtaining the locations of each historical emergency in the public place, comparing and removing duplicates, and obtaining the locations of each historical emergency in the public place.

[0015] Through the high-definition cameras installed at each fixed inspection node in the public place, the real-life images within the field of view of each fixed inspection node in the current public place are collected and spliced ​​to obtain the current real-life images of the public place. According to the preset principles, the areas in the real-life images of the public place are divided into sub-areas, and the real-life images of the current sub-areas are intercepted. Through image processing technology, the number of people in the real-life images of the current sub-areas is identified to obtain the current flow distribution of people in the public place.

[0016] The sub-areas in the real-life image where the number of people is greater than or equal to the set crowd number threshold are recorded as crowd-dense points, and the crowd-dense points in public places are counted.

[0017] The fixed inspection nodes, historical emergency locations, and crowd-dense points of public places are marked in the public place layout map stored in the database. The path planning and optimization algorithm is used to obtain the routes passing through the fixed inspection nodes, historical emergency locations, and crowd-dense points, and they are recorded as the inspection routes to be selected for the inspection equipment.

[0018] Based on the above embodiment, the specific working process of the inspection route planning module also includes: recording the ratio between the area of ​​the area swept along the inspection route and the total area of ​​the public place as the inspection coverage, and obtaining the inspection coverage of each selected inspection route of the inspection equipment.

[0019] Obtain the distance and road condition information of each inspection route to be selected by the inspection equipment, where the road condition information includes the frequency of slope changes and the number of turns.

[0020] According to the slope change frequency and the number of turns of each inspection route to be selected by the inspection equipment, the road condition influencing factors of each inspection route to be selected by the inspection equipment are analyzed. The calculation formula of the road condition influencing factors is: ,in Indicates The road condition influencing factors of the inspection routes to be selected, Indicates The number of the inspection route to be selected, , represents a natural constant, Respectively represent The slope change frequency and turning number of the inspection routes to be selected, They respectively represent the influencing factors corresponding to the preset unit slope change frequency and unit turning number.

[0021] The inspection speed of the inspection equipment stored in the database is extracted, and the inspection time corresponding to each candidate inspection route of the inspection equipment is obtained according to the distance of each candidate inspection route and the inspection speed of the inspection equipment. Combined with the energy consumption per unit inspection time of the inspection equipment stored in the database, the estimated energy consumption of each candidate inspection route of the inspection equipment is analyzed.

[0022] According to the estimated energy consumption of each inspection route to be selected by the inspection equipment and the road condition influencing factors, the energy consumption of the inspection equipment on each inspection route to be selected by the inspection equipment is analyzed. The calculation formula of the energy consumption of the inspection equipment is: ,in Indicates Energy consumption of inspection equipment for the inspection routes to be selected, Indicates The estimated energy consumption of the inspection routes to be selected, Indicates the preset compensation amount for the energy consumption of the inspection equipment.

[0023] On the basis of the above embodiment, the specific working process of the inspection route planning module also includes: analyzing the recommended coefficients of each inspection route to be selected by the inspection equipment according to the inspection coverage of each inspection route to be selected and the energy consumption of the inspection equipment, wherein the calculation formula of the recommended coefficient is: ,in Indicates The recommended coefficient of the inspection routes to be selected, Indicates the correction factor of the preset recommended coefficient, Indicates The inspection coverage of the inspection routes to be selected, They represent the preset inspection coverage and the weight of the inspection equipment energy consumption respectively. .

[0024] Based on the above embodiment, the specific working process of the inspection route planning module also includes: comparing the recommended coefficients of each inspection route to be selected by the inspection equipment, and recording the inspection route to be selected corresponding to the maximum recommended coefficient as the best inspection route.

[0025] Compared with the prior art, the public place security patrol management system based on the Internet of Things described in the present invention has the following beneficial effects: 1. The present invention identifies potential hazards based on the video data and detected environmental data sent back by fixed patrol nodes and patrol equipment, realizes multi-source data fusion, reduces false alarm rate, and combines the two-dimensional perception data of fixed patrol and mobile patrol to improve the accuracy of judging security risks in complex scenarios.

[0026] 2. The present invention dynamically plans and adjusts the inspection path of the inspection equipment based on real-time crowd density, historical emergency locations, and key inspection areas, thereby improving the efficiency of the inspection.

[0027] 3. The distribution of human traffic monitored by the fixed inspection nodes in the present invention provides a reference for the inspection route planning of the inspection equipment. At the same time, the data collected by the inspection equipment at the fixed inspection nodes supplements and improves the data collected by the fixed inspection nodes, thereby realizing the linkage and coordination between different monitoring systems and improving the accuracy and reliability of security inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0029] Figure 1 This is a system module connection diagram of the present invention.

[0030] Figure 2 This is a workflow diagram of the inspection route planning module of the present invention.

[0031] Figure 3 This is a workflow diagram of the hidden danger point identification module of the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] See also Figure 1 As shown, the present invention provides a public place security patrol management system based on the Internet of Things, including a patrol node deployment module, a patrol route planning module, a hidden danger point identification module, a safety risk assessment module, and a database.

[0034] The inspection route planning module is respectively connected to the inspection node layout module and the hidden danger point identification module, the safety risk assessment module is connected to the hidden danger point identification module, and the database is respectively connected to the inspection node layout module, the inspection route planning module, and the hidden danger point identification module.

[0035] The inspection node layout module identifies key inspection areas according to the type and layout of public places, and layouts a number of fixed inspection nodes.

[0036] Furthermore, the specific working process of the inspection node deployment module is: obtaining the type of public places, extracting the key inspection areas of various types of public places stored in the database, and screening to obtain the key inspection areas of public places.

[0037] Extract the layout map of public places stored in the database, mark the location of each key inspection area in the public places, deploy fixed inspection nodes in each key inspection area of ​​the public places, and further install high-definition cameras and environmental detection sensors at each fixed inspection node in the public places.

[0038] As a preferred solution, the number of key inspection areas in public places is the number of fixed inspection nodes.

[0039] As a preferred solution, the key inspection areas of various public places stored in the database are specifically shown in Table 1.

[0040] Table 1. Key inspection areas corresponding to public places

[0041]

[0042] The inspection route planning module formulates various candidate inspection routes for inspection equipment according to fixed inspection nodes, historical emergency locations and current pedestrian flow distribution, and selects the best inspection route according to inspection coverage and inspection equipment energy consumption evaluation indicators.

[0043] Further, see Figure 2 As shown, the specific working process of the inspection route planning module includes: retrieving historical emergency information from the emergency management department of the public place, obtaining the location of each historical emergency in the public place, comparing and removing duplicates, and obtaining the locations of each historical emergency in the public place.

[0044] Through the high-definition cameras installed at each fixed inspection node in the public place, the real-life images within the field of view of each fixed inspection node in the current public place are collected and spliced ​​to obtain the current real-life images of the public place. According to the preset principles, the areas in the real-life images of the public place are divided into sub-areas, and the real-life images of the current sub-areas are intercepted. Through image processing technology, the number of people in the real-life images of the current sub-areas is identified to obtain the current flow distribution of people in the public place.

[0045] The sub-areas in the real-life image where the number of people is greater than or equal to the set crowd number threshold are recorded as crowd-dense points, and the crowd-dense points in public places are counted.

[0046] The fixed inspection nodes, historical emergency locations, and crowd-dense points of public places are marked in the public place layout map stored in the database. The path planning and optimization algorithm is used to obtain the routes passing through the fixed inspection nodes, historical emergency locations, and crowd-dense points, and they are recorded as the inspection routes to be selected for the inspection equipment.

[0047] As a preferred solution, the method of identifying the number of people in the real-life image of each sub-area by image processing technology is a relatively mature technical means currently available, which involves background subtraction technology, morphological processing technology, feature extraction and matching technology, etc., which will not be elaborated here.

[0048] As a preferred solution, the crowd flow distribution refers to the distribution of the number of people in different areas and locations within a certain spatial range.

[0049] As a preferred solution, the path planning and optimization algorithm is mainly used to solve problems such as finding the best path between points or optimizing the connection order of multiple points in a given space or graph structure. It involves Dijkstra algorithm, A* algorithm, genetic algorithm, ant colony algorithm, etc., and is a relatively mature technical means available, which will not be elaborated here.

[0050] As a preferred solution, the inspection equipment in the public places includes but is not limited to intelligent inspection robots or drones, and the inspection equipment is equipped with high-definition cameras and environmental detection sensors.

[0051] Furthermore, the specific working process of the inspection route planning module also includes: recording the ratio between the area of ​​the area swept along the inspection route and the total area of ​​the public place as the inspection coverage, and obtaining the inspection coverage of each inspection route to be selected by the inspection equipment.

[0052] Obtain the distance and road condition information of each inspection route to be selected by the inspection equipment, where the road condition information includes the frequency of slope changes and the number of turns.

[0053] According to the slope change frequency and the number of turns of each inspection route to be selected by the inspection equipment, the road condition influencing factors of each inspection route to be selected by the inspection equipment are analyzed. The calculation formula of the road condition influencing factors is: ,in Indicates The road condition influencing factors of the inspection routes to be selected, Indicates The number of the inspection route to be selected, , represents a natural constant, Respectively represent The slope change frequency and turning number of the inspection routes to be selected, They respectively represent the influencing factors corresponding to the preset unit slope change frequency and unit turning number.

[0054] As a preferred solution, the slope change frequency refers to the number of times the slope on the route changes.

[0055] It should be noted that the road condition impact factor calculation formula Used to measure the comprehensive impact of road conditions on inspection equipment on each inspection route; Indicates the contribution of slope change frequency to the road condition influencing factor; It represents the contribution of the number of turns to the road condition influencing factor; the whole formula obtains the comprehensive road condition influencing factor by weighted combination of the influence of slope change frequency and the number of turns.

[0056] It should be noted that the road condition impact factor calculation formula selects natural constant related items to better reflect the basic characteristics of road condition impact, and is consistent with the potential law of the impact of actual road conditions on patrol equipment, providing a suitable benchmark scaling for subsequent calculations; the formula adopts a linear weighted form of multiplying the slope change frequency and the number of turns by the corresponding impact factors and then adding them together, which can reflect the impact of slope changes and turns on the operation of patrol equipment, and by setting different impact factors, the relative importance of the slope change frequency and the number of turns to the final road condition impact factor can be flexibly adjusted according to actual conditions.

[0057] It should be noted that, by collecting multiple sets of specific numerical data of the slope change frequency and the number of turns of each inspection route to be selected by the inspection equipment, and performing simulation calculation through the road condition influence factor calculation formula, a feasible simulation process is assumed to be a single inspection route to be selected, and the preset unit slope change frequency and the unit turn number corresponding influence factors are manually set at the beginning of the system operation. The value is 0.5. The simulation results can be obtained by taking the value of 0.3. Please refer to Table 2 for details, which lists some representative data.

[0058] Table 2. Slope change frequency, number of turns and calculation results of some samples

[0059]

[0060] Through the above simulation calculations, when the frequency of slope changes or the number of turns increases, the road condition influencing factor increases significantly, which is in line with the expectation that "the complexity of road conditions increases with parameters."

[0061] The inspection speed of the inspection equipment stored in the database is extracted, and the inspection time corresponding to each candidate inspection route of the inspection equipment is obtained according to the distance of each candidate inspection route and the inspection speed of the inspection equipment. Combined with the energy consumption per unit inspection time of the inspection equipment stored in the database, the estimated energy consumption of each candidate inspection route of the inspection equipment is analyzed.

[0062] According to the estimated energy consumption of each inspection route to be selected by the inspection equipment and the road condition influencing factors, the energy consumption of the inspection equipment on each inspection route to be selected by the inspection equipment is analyzed. The calculation formula of the energy consumption of the inspection equipment is: ,in Indicates Energy consumption of inspection equipment for the inspection routes to be selected, Indicates The estimated energy consumption of the inspection routes to be selected, Indicates the preset compensation amount for the energy consumption of the inspection equipment.

[0063] It should be noted that the calculation formula for the energy consumption of inspection equipment Represents the actual energy consumed by the inspection equipment under a specific inspection route to be selected. It indicates the energy consumption of the inspection route equipment estimated under normal circumstances without considering additional influencing factors such as road conditions; It is a value preset based on experience or equipment characteristics, used to take into account some general additional energy consumption factors that are not included in the estimated energy consumption; Used to quantify the impact of different road conditions on the energy consumption of inspection equipment. The larger the value, the greater the impact of road conditions on energy consumption.

[0064] It should be noted that the calculation formula for the energy consumption of the inspection equipment adopts a function form containing cube roots, which can more flexibly reflect that as the road condition influencing factors change, the energy consumption compensation presents a nonlinear change trend, which is more in line with the impact pattern of complex road conditions on energy consumption in actual situations.

[0065] It should be noted that the inspection equipment travels at a constant speed at a set inspection speed.

[0066] It should be noted that the inspection coverage of the candidate inspection route reflects the extent to which the inspection route can cover the inspection area.

[0067] It should be noted that the energy consumption of the inspection equipment of the selected inspection route reflects the equipment energy required to execute the inspection route, and is a key factor in evaluating the cost and feasibility of the inspection route.

[0068] Furthermore, the specific working process of the inspection route planning module also includes: analyzing the recommended coefficients of each inspection route to be selected by the inspection equipment according to the inspection coverage of each inspection route to be selected and the energy consumption of the inspection equipment, wherein the calculation formula of the recommended coefficient is: ,in Indicates The recommended coefficient of the inspection routes to be selected, Indicates the correction factor of the preset recommended coefficient, Indicates The inspection coverage of the inspection routes to be selected, They represent the preset inspection coverage and the weight of the inspection equipment energy consumption respectively. .

[0069] It should be noted that the recommended coefficients of each candidate inspection route in the calculation formula are Used to measure the recommendation degree of each inspection route; correction factor of the recommendation coefficient It is a manually settable constant used to adjust the final recommendation coefficient as a whole to meet different business needs or scenario characteristics; the weight of inspection coverage and inspection equipment energy consumption It is used to reflect the relative importance of inspection coverage and energy consumption when evaluating inspection routes, and can be adjusted according to actual conditions.

[0070] It should be noted that the calculation formula of the recommended coefficient can flexibly adjust the contribution of these two factors to the recommended coefficient according to actual business needs by weighting the inspection coverage and the energy consumption of the inspection equipment respectively; the correction factor can easily adjust the entire recommended coefficient.

[0071] Furthermore, the specific working process of the inspection route planning module also includes: comparing the recommended coefficients of each inspection route to be selected by the inspection equipment, and recording the inspection route to be selected corresponding to the maximum recommended coefficient as the best inspection route.

[0072] It should be noted that the present invention dynamically plans and adjusts the inspection path of the inspection equipment based on the real-time crowd density, the location of historical emergencies, and key inspection areas, thereby improving the efficiency of the inspection.

[0073] The potential hazard point identification module extracts video data and measurement data collected by fixed inspection nodes and inspection equipment, and combines the security event sample library and environmental parameter range to identify various potential hazard points in public places and send their locations.

[0074] Further, see Figure 3As shown, the specific working process of the hidden danger point identification module includes: obtaining video data collected by each fixed inspection node in a public place, and obtaining video data collected by inspection equipment at each fixed inspection node in a public place, each location of historical emergencies, and each crowded point, summarizing and integrating them, obtaining video data collected by each fixed inspection node in a public place, each location of historical emergencies, and each crowded point, recording them as video data of each point in the public place, and using video decoding technology to obtain an image set of each point in the public place.

[0075] Obtain environmental measurement data collected by fixed inspection nodes in public places, and obtain environmental measurement data collected by inspection equipment at fixed inspection nodes in public places, locations of historical emergencies, and points with dense crowds, summarize and integrate them, obtain environmental measurement data of each point in the public place, and further obtain various environmental parameters of each point in the public place.

[0076] As a preferred solution, if the environmental measurement data collected by the fixed inspection nodes in public places is inconsistent with the environmental measurement data collected by the inspection equipment at the fixed inspection nodes in public places, the average value of the two is used as the final environmental measurement data.

[0077] As a preferred solution, the environmental parameters of the public place include but are not limited to temperature, humidity, carbon dioxide concentration, carbon monoxide concentration, inhalable particulate matter concentration, etc.

[0078] Furthermore, the specific working process of the hidden danger point identification module also includes: extracting the security event sample library stored in the database to obtain a set of sample images of various security events.

[0079] Set appropriate ranges for various environmental parameters in public places.

[0080] As a preferred solution, the suitable range of each environmental parameter in the public place is set according to actual application requirements.

[0081] If the similarity between an image at a certain point in a public place and an image in a set of sample images of a certain type of security incident is greater than the set similarity threshold, or if an environmental parameter at a certain point in a public place exceeds the appropriate range of its environmental parameters, then the point in the public place will be recorded as a potential hazard point, and the potential hazard points in the public place will be counted and their locations will be sent.

[0082] As a preferred solution, comparing the similarity between images is a relatively mature technology available now and will not be described in detail here.

[0083] As a preferred solution, the image similarity threshold is set according to actual application requirements. In a specific embodiment, the image similarity threshold is 80%.

[0084] It should be noted that the present invention identifies potential danger points based on the video data sent back by fixed inspection nodes and inspection equipment and the detected environmental data, realizes multi-source data fusion, reduces the false alarm rate, and combines the two-dimensional perception data of fixed inspection and mobile inspection to improve the accuracy of safety risk judgment in complex scenarios.

[0085] The safety risk assessment module assesses the safety risk level and issues corresponding warnings based on the safety event sample images and environmental parameter values ​​matched with the video data of each potential hazard point.

[0086] Furthermore, the specific working process of the security risk assessment module includes: comparing the image set of each hidden danger point in the public place with the sample image set of each type of security incident; if the similarity between an image in the image set of a hidden danger point in the public place and an image in the sample image set of a certain type of security incident is greater than a set similarity threshold, then the image in the image set of the hidden danger point is recorded as a security incident sample image that matches the video data of the hidden danger point with the security incident of this type; and the number of security incident sample images that match the video data of each hidden danger point in the public place with each type of security incident is counted and recorded as , Indicates The number of the potential danger point, , Indicates The number of the security incident. .

[0087] Compare the values ​​of various environmental parameters at various potential danger points in public places with the appropriate range of their environmental parameters to obtain the offset of various environmental parameters at various potential danger points in public places, which is recorded as , Indicates The number of the environmental parameter. .

[0088] As a preferred solution, the offset of the environmental parameter refers to the amount by which the value of the environmental parameter exceeds its appropriate range.

[0089] As a preferred solution, the number of sample images of various types of security incidents matched by each potential risk point reflects the degree of association between each potential risk point and various types of security incidents in history.

[0090] As a preferred solution, the offset of each environmental parameter at each potential hazard point reflects the deviation of the current environmental parameter from the standard or normal state.

[0091] The number of security incident sample images that match the video data of various potential danger points in public places with various security incidents and the offset of various environmental parameters at each potential hazard point , analyze the risk coefficient of each hidden danger point, where the calculation formula of the risk coefficient is: ,in Indicates The risk factor of each potential risk point is Respectively represent the preset Class 1 security incident and The influence weight of each environmental parameter, They respectively represent the preset thresholds for the number of matching security event sample images and the environmental parameter offset.

[0092] It should be noted that the risk coefficient in the calculation formula Used to measure the size of the risk of each hidden danger point; the impact weight of each type of security event reflects the difference in the degree of impact of different types of security events on the risk of hidden danger points. The higher the weight, the greater the impact of this type of security event; the preset threshold of the number of matching security event sample images is used for normalization processing to make different orders of magnitude comparable; and by taking the weighted sum of various types of security events, the contribution of historical security events to the risk of hidden danger points is measured; the preset threshold of environmental parameter offset is used for normalization processing, so that the offsets of different parameters can be compared on a unified scale, and by taking the weighted sum of various environmental parameters, the impact of environmental factors on the risk of hidden danger points is measured.

[0093] It should be noted that the calculation formula of the risk coefficient comprehensively considers two key factors, safety events and environmental parameters, to fully evaluate the risk of potential hazards. At the same time, it flexibly adjusts the degree of influence of different safety events and environmental parameters on the risk coefficient according to actual conditions, so that the risk assessment is more in line with specific locations and needs. The threshold is used to normalize the relevant data to avoid the interference of data of different dimensions on the calculation results, making the calculation results comparable and reasonable, which facilitates the unified analysis and ranking of the risk factors of different potential hazards.

[0094] Furthermore, the specific working process of the safety risk assessment module also includes: setting the risk coefficient range corresponding to each safety risk level, matching the safety risk level of each potential risk point according to the risk coefficient of each potential risk point and issuing corresponding warnings.

[0095] In a specific embodiment, the security risk levels include high risk, medium risk, and low risk.

[0096] It should be noted that the distribution of pedestrian flow monitored by the fixed patrol nodes in the present invention provides a reference for the patrol route planning of the patrol equipment. At the same time, the data collected by the patrol equipment at the fixed patrol nodes supplements and improves the data collected by the fixed patrol nodes, thereby realizing the linkage and coordination between different monitoring systems and improving the accuracy and reliability of security patrols.

[0097] The database stores a layout diagram of public places, key inspection areas of various public places, and a sample library of security incidents, and stores the inspection speed of inspection equipment and the energy consumption per unit inspection time.

[0098] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A public place security inspection management system based on the Internet of Things, characterized in that: include: Inspection node layout module: Identify key inspection areas according to the type and layout of public places, and layout several fixed inspection nodes; Inspection route planning module: formulates the inspection routes for inspection equipment according to fixed inspection nodes, historical emergency locations and current traffic distribution, and selects the best inspection route according to inspection coverage and inspection equipment energy consumption evaluation indicators; Hidden danger point identification module: extracts video data and measurement data collected by fixed inspection nodes and inspection equipment, and combines it with the security event sample library and environmental parameter range to identify hidden danger points in public places and send their locations; Security risk assessment module: assesses the security risk level and issues corresponding warnings based on the security event sample images and environmental parameter values ​​matched with the video data of each potential risk point; Database: Stores the layout of public places, key inspection areas of various public places, and sample libraries of security incidents, as well as the inspection speed of inspection equipment and energy consumption per unit inspection time.

2. According to the Internet of Things-based public place security inspection and management system according to claim 1, it is characterized by: The specific working process of the inspection node deployment module is as follows: Obtain the type of public places, extract the key inspection areas of various types of public places stored in the database, and screen out the key inspection areas of public places; Extract the layout map of public places stored in the database, mark the location of each key inspection area in the public places, deploy fixed inspection nodes in each key inspection area of ​​the public places, and further install high-definition cameras and environmental detection sensors at each fixed inspection node in the public places.

3. According to the Internet of Things-based public place security inspection and management system of claim 1, it is characterized by: The specific working process of the inspection route planning module includes: Retrieving historical emergency information from the emergency management department of a public place, obtaining the locations of each historical emergency in the public place, comparing and removing duplicates, and obtaining the locations of each historical emergency in the public place; Through the high-definition cameras installed at each fixed inspection node in the public place, the real-life images within the field of view of each fixed inspection node in the current public place are collected, and the current real-life images of the public place are obtained by splicing. According to the preset principle, the areas in the real-life images of the public place are divided into sub-areas, and the real-life images of the current sub-areas are intercepted. Through the image processing technology, the number of people in the real-life images of the current sub-areas is identified to obtain the current flow distribution of people in the public place; The sub-areas in the real scene image where the number of people is greater than or equal to the set crowd number threshold are recorded as crowd-dense points, and the crowd-dense points in public places are counted; The fixed inspection nodes, historical emergency locations, and crowd-dense points of public places are marked in the public place layout map stored in the database. The path planning and optimization algorithm is used to obtain the routes passing through the fixed inspection nodes, historical emergency locations, and crowd-dense points, and they are recorded as the inspection routes to be selected for the inspection equipment.

4. According to the Internet of Things-based public place security inspection and management system as described in claim 1, it is characterized by: The specific working process of the inspection route planning module also includes: The ratio between the area of ​​the area swept along the inspection route and the total area of ​​the public place is recorded as the inspection coverage, and the inspection coverage of each inspection route to be selected by the inspection equipment is obtained; Obtain the distance and road condition information of each inspection route to be selected by the inspection equipment, where the road condition information includes the frequency of slope changes and the number of turns; According to the slope change frequency and the number of turns of each inspection route to be selected by the inspection equipment, the road condition influencing factors of each inspection route to be selected by the inspection equipment are analyzed. The calculation formula of the road condition influencing factors is: ,in Indicates The road condition influencing factors of the inspection routes to be selected, Indicates The number of the inspection route to be selected, , represents a natural constant, Respectively represent The slope change frequency and number of turns of the inspection routes to be selected, Respectively represent the influence factors corresponding to the preset unit slope change frequency and unit turning number; Extract the inspection speed of the inspection equipment stored in the database, obtain the inspection time corresponding to each inspection route to be selected by the inspection equipment according to the distance of each inspection route to be selected and the inspection speed of the inspection equipment, and analyze the estimated energy consumption of each inspection route to be selected by the inspection equipment in combination with the energy consumption per unit inspection time of the inspection equipment stored in the database; According to the estimated energy consumption of each inspection route to be selected by the inspection equipment and the road condition influencing factors, the energy consumption of the inspection equipment on each inspection route to be selected by the inspection equipment is analyzed. The calculation formula of the energy consumption of the inspection equipment is: ,in Indicates Energy consumption of inspection equipment for the inspection routes to be selected, Indicates The estimated energy consumption of the inspection routes to be selected, Indicates the preset compensation amount for the energy consumption of the inspection equipment.

5. According to the Internet of Things-based public place security inspection and management system of claim 4, it is characterized by: The specific working process of the inspection route planning module also includes: According to the inspection coverage of each inspection route to be selected by the inspection equipment and the energy consumption of the inspection equipment, the recommended coefficient of each inspection route to be selected by the inspection equipment is analyzed. The calculation formula of the recommended coefficient is: ,in Indicates The recommended coefficient of the inspection routes to be selected, Indicates the correction factor of the preset recommended coefficient, Indicates The inspection coverage of the inspection routes to be selected, They represent the preset inspection coverage and the weight of the inspection equipment energy consumption respectively. .

6. The public place security inspection and management system based on the Internet of Things according to claim 5 is characterized by: The specific working process of the inspection route planning module also includes: comparing the recommended coefficients of each inspection route to be selected by the inspection equipment, and recording the inspection route to be selected corresponding to the maximum recommended coefficient as the best inspection route.

7. The public place security inspection and management system based on the Internet of Things according to claim 3 is characterized by: The specific working process of the hidden danger point identification module includes: Obtain video data collected by each fixed inspection node in a public place, and obtain video data collected by inspection equipment at each fixed inspection node in a public place, each location of historical emergencies, and each crowded point, summarize and integrate them, obtain video data collected by each fixed inspection node in a public place, each location of historical emergencies, and each crowded point, record them as video data of each point in the public place, and use video decoding technology to obtain an image set of each point in the public place; Obtain environmental measurement data collected by fixed inspection nodes in public places, and obtain environmental measurement data collected by inspection equipment at fixed inspection nodes in public places, locations of historical emergencies, and points with dense crowds, summarize and integrate them, obtain environmental measurement data of each point in the public place, and further obtain various environmental parameters of each point in the public place.

8. The public place security inspection and management system based on the Internet of Things according to claim 7 is characterized by: The specific working process of the hidden danger point identification module also includes: Extract the security incident sample image library stored in the database to obtain a collection of sample images of various security incidents; Set appropriate ranges for various environmental parameters in public places; If the similarity between an image at a certain point in a public place and an image in a set of sample images of a certain type of security incident is greater than the set similarity threshold, or if an environmental parameter at a certain point in a public place exceeds the appropriate range of its environmental parameters, then the point in the public place will be recorded as a potential hazard point, and the potential hazard points in the public place will be counted and their locations will be sent.

9. The public place security inspection and management system based on the Internet of Things according to claim 8 is characterized by: The specific working process of the security risk assessment module includes: The image set of each hidden danger point in a public place is compared with the sample image set of each type of security incident. If the similarity between an image in the image set of a hidden danger point in a public place and an image in the sample image set of a certain type of security incident is greater than the set similarity threshold, the image in the image set of the hidden danger point is recorded as a security incident sample image that matches the video data of the hidden danger point with the security incident of this type. The number of security incident sample images that match the video data of each hidden danger point in a public place with each type of security incident is counted and recorded as , Indicates The number of the potential danger point, , Indicates The number of the security incident. ; Compare the values ​​of various environmental parameters at various potential danger points in public places with the appropriate range of their environmental parameters to obtain the offset of various environmental parameters at various potential danger points in public places, which is recorded as , Indicates The number of the environmental parameter. ; The number of security incident sample images that match the video data of various potential danger points in public places with various security incidents And the offset of various environmental parameters at each potential hazard point , analyze the risk coefficient of each hidden danger point, where the calculation formula of the risk coefficient is: ,in Indicates The risk factor of each potential risk point is Respectively represent the preset Class 1 security incident and The influence weight of each environmental parameter, They respectively represent the preset thresholds for the number of matching security event sample images and the environmental parameter offset.

10. The public place security inspection and management system based on the Internet of Things according to claim 9 is characterized in that: The specific working process of the security risk assessment module also includes: Set the risk coefficient range corresponding to each safety risk level, match the safety risk level of each potential risk point according to the risk coefficient of each potential risk point, and issue corresponding warnings.

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