CN-121982825-A - Intelligent campus intelligent security early warning system

CN121982825ACN 121982825 ACN121982825 ACN 121982825ACN-121982825-A

Abstract

The application relates to the technical field of campus security management, in particular to an intelligent campus security early warning system, which comprises a data acquisition module, a vulnerability thermodynamic diagram construction module, an early warning module, a patrol scheduling module and a role coordination module, wherein the data acquisition module is used for acquiring campus security data through multi-dimensional security equipment and patrol robots, the vulnerability thermodynamic diagram construction module is used for constructing a risk simulation model to calculate security vulnerability coefficients of all geographic grid units of a campus, dividing risk levels and generating vulnerability thermodynamic diagrams, the early warning module is used for carrying out multi-dimensional analysis, identifying security abnormality types and triggering corresponding early warning, the patrol scheduling module is used for dynamically planning patrol routes of the patrol robots, when the early warning is triggered, the patrol robots closest to an early warning area are scheduled to go to the site for checking, and the role coordination module is used for pushing differentiated tasks to different security roles based on the risk level distribution and the early warning types of the vulnerability thermodynamic diagrams. Therefore, the problems of single data dimension, risk perception lag, resource scheduling stiffness, multi-role cooperation inefficiency and the like are solved.

Inventors

CHANG JINLONG
LI BOYA

Assignees

广州科技贸易职业学院

Dates

Publication Date: 20260505
Application Date: 20260122

Claims (10)

1. An intelligent campus intelligent security early warning system is characterized by comprising a data acquisition module, a vulnerability thermodynamic diagram construction module, an early warning module, a patrol scheduling module and a role coordination module, wherein, The data acquisition module is used for acquiring campus security data through the multi-dimensional security equipment and the patrol robot, wherein the security data comprises personnel flow data, environment perception data and equipment operation data; The vulnerability thermodynamic diagram construction module is used for constructing a risk simulation model based on the safety data and the historical safety event data and combining campus geographic information data, calculating the safety vulnerability coefficient of each geographic grid unit of the campus through the risk simulation model, classifying risk levels according to the safety vulnerability coefficient, and generating a vulnerability thermodynamic diagram; the early warning module is used for carrying out multidimensional analysis based on the safety data and the vulnerability thermodynamic diagram, identifying the type of safety abnormality and triggering corresponding early warning; The patrol scheduling module is used for dynamically planning a patrol route of the patrol robot based on the risk level distribution of the vulnerability thermodynamic diagram, and scheduling the patrol robot closest to the early warning area to go to the field for checking when the early warning is triggered; The role coordination module is used for pushing differentiated tasks to different security roles based on the risk level distribution and the early warning type of the vulnerability thermodynamic diagram.
2. The intelligent campus security and early warning system according to claim 1, wherein the data acquisition module comprises a security device acquisition unit, a patrol robot acquisition unit, and a data preprocessing unit, wherein, The security equipment acquisition unit is used for acquiring personnel identity verification information, access right matching data, video monitoring data, environment data and self operation parameters of the fixed security equipment in real time through multi-dimensional security equipment deployed in a key area; The patrol robot acquisition unit is used for completing blind supplement acquisition and dynamic scene data acquisition of a coverage blind area of the fixed security equipment through a mobile patrol robot carrying a multi-perception module, and acquiring personnel gathering density, personnel moving track, environment data, video data and audio data in a patrol area in real time; The data preprocessing unit comprises a data cleaning unit and a data integration unit, wherein the data cleaning unit is used for carrying out denoising, abnormal value detection, missing value filling and format standardization processing on collected original data, the data integration unit is used for carrying out time-space alignment on cleaned data according to geographic information and a time stamp, and the aligned data is classified and stored according to personnel flow data, environment perception data and equipment operation data to obtain safety data.
3. The intelligent campus security and protection early warning system according to claim 1, wherein the vulnerability thermodynamic diagram construction module comprises a feature extraction unit, a risk simulation model calculation engine, and a vulnerability thermodynamic diagram generation unit, wherein, The feature extraction unit is used for dividing the geographic grid units based on campus geographic information data, extracting and aggregating data in the corresponding geographic grid units from the safety data, and carrying out feature extraction on the data to obtain feature vectors of the current state of the geographic grid units; the risk simulation model calculation engine is used for constructing a risk simulation model based on historical security event data and regional geographic attribute weights, inputting the feature vector into the risk simulation model, and calculating to obtain a security vulnerability coefficient of the geographic grid unit; The vulnerability thermodynamic diagram generating unit is used for dynamically dividing risk grades according to the statistical distribution of the security vulnerability coefficients of each geographic grid unit, the risk grades comprise red, orange, yellow and blue, grid data with risk grade labels are superimposed on a school digital map, the colors are filled according to the risk grades, and a vulnerability thermodynamic diagram is generated, and the updating frequency of the vulnerability thermodynamic diagram is synchronous with the period of the risk simulation model.
4. The intelligent campus security and protection early warning system according to claim 1, wherein the early warning module comprises a risk area acquisition unit, an anomaly identification unit and an early warning unit, wherein, The risk area acquisition unit is used for extracting geographical grid units with red and orange risk levels from the vulnerability thermodynamic diagram and converging adjacent or similar high-risk grids into a risk area; The anomaly identification unit is used for extracting and aggregating the data in the corresponding risk area from the safety data of the data in each risk area, analyzing the video data, the audio data and the equipment operation data in the safety data through the video intelligent analysis engine, the audio intelligent analysis engine and the equipment fault analysis engine respectively, identifying dominant risk factors based on a multi-engine analysis result, judging the anomaly type according to the dominant risk factors and quantifying the confidence; The early warning unit is used for matching a preset early warning plan from a risk coping library preset by risks based on the identified abnormal type and the confidence level and the risk level of the vulnerability thermodynamic diagram.
5. The intelligent campus security and early warning system according to claim 1, wherein the patrol scheduling module comprises a patrol route planning unit and an emergency response scheduling unit, wherein, The patrol route planning unit is used for generating a group of candidate routes through constraint solving by taking the risk level of the vulnerability thermodynamic diagram as a core weight and based on a multi-objective optimization algorithm of risk weighting, and distributing the candidate routes to the patrol robot for patrol; The emergency response scheduling unit is used for receiving the early warning information, analyzing the early warning position, the early warning type and the risk level information, adopting a principle of matching a proximity principle with the capability based on the real-time position, the state and the functional configuration of the patrol robot, selecting one or more optimal robots from the idle or interruptible robots to execute response tasks, and planning an emergency path with optimal time for the selected robots to go to the site.
6. The intelligent campus security and protection early warning system according to claim 1, wherein the role coordination module comprises a role responsibility library and an early warning task allocation unit, wherein, The role responsibility library is used for establishing a defined security role portrait for different security roles, and the security role portrait comprises security roles, responsible areas, skills and rights; The early warning task allocation unit is used for generating a standardized task list comprising early warning positions, abnormal details, treatment requirements and time limit priorities based on the risk level distribution and the early warning types of the vulnerability thermodynamic diagram, and allocating the corresponding standardized task list to the corresponding security roles through a task matching mechanism for processing.
7. An intelligent campus intelligent security early warning method is characterized by comprising the following steps: Acquiring campus security data through multi-dimensional security equipment and patrol robots, wherein the security data comprises personnel flow data, environment perception data and equipment operation data; based on the safety data and the historical safety event data, constructing a risk simulation model by combining campus geographic information data, calculating the safety vulnerability coefficient of each geographic grid unit of the campus through the risk simulation model, dividing risk levels according to the safety vulnerability coefficient, and generating a vulnerability thermodynamic diagram; based on the safety data and the vulnerability thermodynamic diagram, carrying out multidimensional analysis, identifying a safety abnormality type and triggering corresponding early warning; dynamically planning a patrol route of the patrol robot based on the risk level distribution of the vulnerability thermodynamic diagram, and when an early warning is triggered, scheduling the patrol robot closest to an early warning area to go to field inspection; And based on the risk level distribution and the early warning type of the vulnerability thermodynamic diagram, pushing differentiated tasks to different security roles.
8. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the intelligent campus intelligent security early warning method of claim 7.
9. A computer readable storage medium having stored thereon a computer program, the program being executable by a processor for implementing a smart campus intelligent security early warning method as claimed in claim 7.
10. A computer program product comprising a computer program or instructions which, when executed, implement the intelligent campus security early warning method of claim 7.

Description

Intelligent campus intelligent security early warning system Technical Field The application relates to the technical field of campus security management, in particular to an intelligent campus security early warning system. Background With the deep advancement of education informatization and intelligent campus construction, campus security requirements are changed from traditional 'post-retrospection' to 'early warning in advance and rapid disposal in advance', at present, most campus security systems still rely on independent monitoring of single equipment such as fixed cameras, access control and the like, and a plurality of technical short boards exist in a manual patrol mode, namely, the phenomenon of data islanding is prominent, data dispersion acquisition and storage of personnel flowing, environmental states, equipment operation and the like are achieved, effective fusion of multi-source data is not achieved, so that research and judgment on security risks are on one side, and composite potential safety hazards are difficult to accurately identify; secondly, the risk prejudging capability is deficient, the system triggers an alarm based on real-time abnormal data, mining and utilization of historical safety event rules are lacking, safety vulnerability of each area of a campus cannot be perceived in advance, a 'passive response' prevention and control situation is easy to form, thirdly, patrol and disposal efficiency is low, manual patrol is limited by labor cost and time period, full period and full area coverage are difficult to realize, patrol routes are mostly fixed planning and cannot be dynamically adjusted for high risk areas, meanwhile, cooperative linkage mechanisms are lacking among security roles (security, facility maintenance personnel and the like), task allocation is lack of accuracy, potential safety hazard disposal flows are tedious, and optimal intervention opportunities are missed. Disclosure of Invention The application provides an intelligent campus intelligent security early warning system which aims to solve the problems of single data dimension, risk perception lag, resource scheduling rigidification, multi-role cooperation inefficiency and the like. The embodiment of the first aspect of the application provides an intelligent campus security early warning system, which comprises a data acquisition module, a vulnerability thermodynamic diagram construction module, an early warning module, a patrol scheduling module and a role coordination module, wherein the data acquisition module is used for acquiring campus security data through multi-dimensional security equipment and patrol robots, the security data comprise personnel flow data, environment perception data and equipment operation data, the vulnerability thermodynamic diagram construction module is used for constructing a risk simulation model based on the security data and historical security event data by combining with campus geographic information data, the risk simulation model is used for calculating security vulnerability coefficients of each geographic grid unit of a campus, dividing risk levels according to the security vulnerability coefficients and generating vulnerability thermodynamic diagrams, the early warning module is used for carrying out multi-dimensional analysis based on the security data and the vulnerability thermodynamic diagrams, identifying security anomaly types and triggering corresponding early warning routes based on risk level distribution of the vulnerability thermodynamic diagrams, and when triggering early warning, the scheduling module is used for planning the closest to the patrol robots based on the role classification of the security thermodynamic diagrams, and the role coordination module is used for checking the role coordination of the security thermodynamic diagrams based on the security level distribution of the vulnerability thermodynamic diagrams. The data acquisition module comprises a security equipment acquisition unit, a patrol robot acquisition unit and a data preprocessing unit, wherein the security equipment acquisition unit is used for acquiring personnel identity verification information, access permission matching data, video monitoring data, environment data and self operation parameters of fixed security equipment in real time through multi-dimensional security equipment deployed in a key area, the patrol robot acquisition unit is used for completing blind supplement acquisition and dynamic scene data acquisition of a fixed security equipment coverage blind area through a mobile patrol robot carrying a multi-perception module, acquiring personnel aggregation density, personnel movement tracks, environment data, video and audio data in the patrol area in real time, the data preprocessing unit comprises a data cleaning unit and a data integration unit, the data cleaning unit is used for conducting denoising, outlier detection, missing value filling and format standar