Safety management method and system based on smart campus

Abstract

The invention discloses a safety management method and system based on a smart campus, and relates to the technical field of smart campus safety management, and the system comprises an information receiving unit, an information processing unit, a judgment decision unit and an auxiliary intervention unit. The abnormal condition processing module judges the threat level, carries out light color temperature adjustment and directional sound wave warning in the primary state to avoid intensified contradictions, schedules security personnel in the intermediate state to avoid personnel scheduling problems, and the auxiliary intervention unit covers three roles of an abnormal behavior initiator, a victim and a bystander, and combines high and new technologies to achieve the purpose of improving the safety of the security personnel. Through VR, AI, a block chain, a holographic technology and physiological signal feedback, timely disposal, psychological guidance, behavior correction and educational excitation of campus injury are realized, a multi-level campus injury intervention ecological system is formed, the probability of re-attacking of an abnormal behavior initiator is reduced, physical and psychological protection is performed on a victim, the emotional ability of bystants is improved, and the probability of occurrence of campus injury is reduced.

Description

Technical Field

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

[0002] A smart campus is a system that uses new-generation information technologies such as the Internet of Things, big data, artificial intelligence, cloud computing, and 5G to build an intelligent, digital, and personalized campus management and service system, achieving efficient collaboration and optimization of education management, teaching and research, and campus life.

[0003] The safety management of smart campuses is a multi-dimensional and systematic project that involves multiple levels such as physical space, digital environment, and human behavior. Among them, preventing and responding to campus injuries is an important part of smart campus safety management. Campus injuries not only affect students' mental health, but may also escalate into violent incidents.

[0004] Chinese patent publication number CN118262475B discloses an AI-powered sound-wave-assisted campus anti-bullying system, which includes: capturing environmental sounds through multiple sound sensors deployed within the campus; introducing a sound feature extraction module to extract sound features related to bullying behavior, integrating a machine learning classification algorithm, monitoring sound signals in the environment in real time, and importing the real-time extracted sound signal features into the machine learning classification algorithm. Based on the analysis results, it is determined whether there is bullying behavior; introducing an environmental monitoring module, combined with the analysis results of the sound feature extraction module, to assist in determining bullying behavior; triggering an alarm when bullying behavior is identified; introducing a positioning module, using the location information of the sound sensor and combined with the positioning algorithm analysis to determine the exact location of the alarm event and transmit it to the receiving device. This invention achieves timely response and disposal of bullying incidents, effectively improving campus safety.

[0005] The system in the above patent has a crude response mechanism during use. When campus injuries occur, the alarm is used to determine the exact time and location of the alarm, which can easily intensify conflicts and cannot improve the safety of the victims. There is no hierarchical processing strategy, which can easily cause personnel scheduling problems. After campus injuries occur, there is a lack of education and correction, and the initiators of abnormal behavior are prone to recidivism. The victims are affected physically and mentally, and bystanders are indifferent. Summary of the Invention

[0006] The purpose of the present invention is to provide a safety management method and system based on a smart campus, which solves the problems of the existing system's rough response mechanism during use. When campus injuries occur, the alarm is used to determine the exact time and location of the alarm, which easily intensifies the conflict and cannot improve the safety of the victims. There is no hierarchical processing strategy, which easily causes personnel scheduling problems. After campus injuries occur, there is a lack of education and correction, the initiators of abnormal behavior are likely to reoffend, the victims are affected physically and mentally, and bystanders are indifferent.

[0007] The present invention solves the above technical problems through the following technical solutions, which are based on a security management system for smart campuses, including an information receiving unit, an information processing unit, a judgment and decision-making unit, and an auxiliary intervention unit;

[0008] The information receiving unit is used to obtain various data and event information on campus through various sensors, cameras, microphones and other campus information collection equipment to form original input data;

[0009] The information processing unit is used to perform preliminary pre-processing, cleaning and formatting of the received original information in preparation for subsequent discrimination and analysis;

[0010] The judgment and decision-making unit is used to conduct in-depth analysis and judgment on the pre-processed information and classify the current situation into two categories: normal or abnormal;

[0011] The auxiliary intervention unit provides multi-dimensional intervention for abnormal events, including behavioral correction of the initiators of abnormal behavior, psychological counseling for victims, and education and guidance for bystanders, to promote the restoration of a safe campus environment and ensure the safety of teachers and students.

[0012] Preferably, the information receiving unit includes a physical contact monitoring module and an environmental change detection module, specifically including the following steps:

[0013] Step S1, physical contact monitoring module: Use the wall vibration sensor to detect the vibration information of the wall or other fixed structure, and capture whether there is a physical collision or pushing event through the vibration change, and use the formula ViolenceScore = ∫(A(f)·W(f))df / (1+e (-k·Δt)), where A(f) represents the vibration energy in the 30-200 Hz frequency band, W(f) represents the position weight coefficient, with toilet cubicles = 1.2 and corridor corners = 0.9, and k represents the duration correction factor, which increases by 0.5 every 10 seconds. This assists in identifying potential violent behavior and uses ultrasonic sensing technology to track the movement trajectory and distance changes of human bodies or objects in real time. MovementVector = argmin(∥Φ·S(t)-Δf(t)∥2+λ·TV(S)), where Φ represents the ultrasonic transmit-receive topology matrix, S(t) represents the spatial motion field intensity distribution, and TV(S) represents the total variation regularization term. This accurately captures abnormal movement and contact situations, enhancing the detection capability of limb movements.

[0014] Step S2, environmental change detection module: Analyze the collected campus sound data, use voiceprint recognition technology to detect emotional changes and abnormal sounds in the language of teachers and students, provide voice clues for injury incidents and abnormal social behaviors, monitor changes in air flow, such as abnormal airflow caused by rapid movement, to help assist in judging group behavior or emergencies, and enhance the overall safety situation awareness of the environment.

[0015] Preferably, the information processing unit includes a spatiotemporal alignment module and an information alignment module, specifically including the following steps:

[0016] Step N1, Spatiotemporal Alignment Module: Uses time-frequency analysis to process signals collected by vibration sensors, identifies changes in frequency characteristics within different time periods, improves the accuracy of abnormal behavior detection, extracts features from electromagnetic sensor data, and generates a unique electromagnetic fingerprint to distinguish different events or identities, assist in locating and identifying abnormal behavior, and uses ultrasonic sensors to capture Doppler frequency shift information to accurately analyze the speed and direction of objects, enabling detailed analysis of dynamic behavior within the campus environment.

[0017] Step N2, information alignment module: associates sensor data with student identity information to bind behavior to specific individuals, supports subsequent personalized intervention and tracking, loads students' past behavior patterns and records, and conducts comprehensive analysis based on current data to identify abnormal behavior or repetitive risks, thereby improving the ability to predict safety incidents.

[0018] Preferably, the judgment and decision-making unit includes a normal situation processing module and an abnormal situation processing module. The normal situation processing module archives the data when it determines that the behavior is normal, systematically stores the information collected and processed under normal conditions, and forms a complete data archive to facilitate subsequent query and analysis. The specific work includes the following steps:

[0019] Step M1: Update behavioral baselines: Regularly update the basic models and standards of student and campus behavior to adapt to the environment

[0020] Hexing

[0021] To ensure the accuracy of anomaly detection for changes;

[0022] Step M2, equipment self-test: Perform regular self-tests on monitoring and acquisition equipment to ensure the normal operation of hardware and sensors and the quality of data collection;

[0023] Step M3, Privacy Erasure: Automatically clear unnecessary personal privacy information, comply with relevant privacy protection laws and regulations, and ensure data usage compliance.

[0024] Preferably, the abnormal situation processing module works as a threat level assessment, comprehensively analyzes the severity of abnormal events, assesses the security threat level, and guides subsequent processing steps. The specific work includes the following steps:

[0025] Step K1, Environmental Intervention: When the threat level is primary, adjust the lighting color temperature. Switch to 5000K cool white light in the direction of the initiator's field of view to make them feel subconsciously uneasy. Maintain 3000K warm yellow light in the direction of the victim to provide psychological comfort. Use directional sound wave warnings to warn or disperse the affected area through specific directional sound waves to reduce the escalation of the conflict.

[0026] Step K2, personnel dispatch: When the threat level is medium, the system will automatically notify and direct the nearest security personnel to the incident location to rush to the scene, navigate to medical personnel, and dispatch medical personnel for a rapid response when necessary to ensure timely treatment for the injured;

[0027] Step K3, system-level response: When the threat level is high, the access control area is blocked and access control is automatically performed in the area where the incident occurred to prevent the incident from spreading or the escape of those involved. Data is reported and the event data and processing status are uploaded to the school management center or relevant security departments in real time to support decision-making and filing.

[0028] Preferably, the auxiliary intervention unit includes an abnormal behavior initiator correction module, a victim counseling module and a bystander education module, wherein the abnormal behavior initiator correction module specifically includes the following steps:

[0029] Step P1, immediate handling: electronically record the behavior of the initiator of abnormal behavior in real time to facilitate tracking and management, notify the initiator's parents as soon as possible to promote family intervention, and issue service orders or restrictive measures against the initiator of abnormal behavior within the school;

[0030] Step P2, special topic education: Conduct VR injury simulation courses, using virtual reality technology to enhance empathy, conduct anti-injury law exams to enhance the legal awareness of those who initiate abnormal behavior through exams, conduct social and emotional learning, implement social and emotional courses, and cultivate the emotional management and social skills of those who initiate abnormal behavior;

[0031] Step P3, long-term tracking: Use AI technology to track the behavioral data of the initiators of abnormal behavior over a long period of time to assist in correction, conduct regular mental health assessments every month, and monitor changes in the psychological state of the initiators of abnormal behavior.

[0032] Preferably, the victim counseling module specifically includes the following steps:

[0033] Step T1: Immediate support: Intelligent robots provide psychological counseling and emotional support to victims, guiding them to quickly find a safe shelter;

[0034] Step T2, social support: Through the Peer Guardian Program, mobilize peers to participate, form a protection network, and use blockchain technology to create an anonymous and secure platform for victims to confide and seek help.

[0035] Preferably, the bystander education module specifically includes the following steps:

[0036] Step R1, scenario teaching: holographic injury scene re-enactment is carried out. Holographic technology is used to re-enact the injury scene to enhance the sensitivity and sense of responsibility of bystanders. The wearable device can show the physiological pressure caused by the injury, allowing bystanders to experience the pain of the injury in an immersive way.

[0037] Step R2, positive reinforcement: Give credits to students who actively intervene in harmful behaviors, provide social currency incentives, and increase the enthusiasm of bystanders to help victims.

[0038] The security management method based on the smart campus specifically includes the following steps:

[0039] Step 1: Obtain various data and event information on campus through various sensors, cameras, microphones, and other campus information collection devices;

[0040] Step 2: Preliminary preprocessing, cleaning, and formatting of the received raw information to prepare for subsequent discrimination and analysis to determine whether campus injury has occurred;

[0041] Step 3: Conduct in-depth analysis and judgment of the pre-processed information, classifying the current situation as normal or abnormal. If no campus injury has occurred, archive the data and systematically store the information collected and processed under normal conditions. If a campus injury has occurred, comprehensively analyze the severity of the abnormal event, assess the security threat level, and guide subsequent processing steps.

[0042] Step 4: After a campus injury occurs, conduct multi-dimensional intervention to correct the behavior of the initiator of the abnormal behavior, provide psychological counseling to the victim, and educate and guide the bystanders, promote the restoration of a safe campus environment, and ensure the safety of teachers and students.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] 1. When campus injuries occur, the abnormal situation processing module in the present invention determines the threat level and implements corresponding measures. In the primary state, it adjusts the light color temperature and directional sound wave warnings to avoid intensifying conflicts, reduce conflict escalation, and improve the safety of victims. In the intermediate state, it dispatches security guards to avoid insufficient security guards after the primary dispatch of security guards, resulting in no security guards in the intermediate and advanced states. In the advanced state, the access control area is blocked to prevent the spread of the incident or the escape of the people involved, thereby improving safety.

[0045] 2. The auxiliary intervention unit in the present invention covers three roles: the initiator of abnormal behavior, the victim and the bystander. It combines high-tech, VR, AI, blockchain, holographic technology and physiological signal feedback to achieve timely handling of campus injuries, psychological counseling, behavior correction and educational incentives, forming a multi-level and comprehensive campus injury intervention ecosystem, reducing the probability of recidivism of the initiator of abnormal behavior, protecting the physical and mental health of the victim, improving the empathy of bystanders, avoiding bystanders from standing idly by, reducing the probability of campus injuries, and improving campus safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a structural diagram of the safety management system in the present invention.

[0047] Figure 2 It is a structural diagram of the information receiving unit in the present invention.

[0048] Figure 3 It is a structural diagram of the information processing unit in the present invention.

[0049] Figure 4 It is a structural diagram of the normal situation processing module in the present invention.

[0050] Figure 5 It is a structural diagram of the abnormal situation processing module in the present invention.

[0051] Figure 6 Schematic diagram of the structure of the auxiliary intervention unit in the present invention. DETAILED DESCRIPTION

[0052] The above and other technical features and advantages of the present invention are described in more detail below with reference to the accompanying drawings.

[0053] This embodiment provides a technical solution: a security management system based on a smart campus, such as Figure 1-6 As shown, it includes an information receiving unit, an information processing unit, a judgment and decision-making unit, and an auxiliary intervention unit;

[0054] The information receiving unit is used to obtain various data and event information on campus through various sensors, cameras, microphones and other campus information collection equipment to form original input data;

[0055] The information processing unit is used to perform preliminary preprocessing, cleaning and formatting of the received raw information in preparation for subsequent discrimination and analysis;

[0056] The judgment and decision-making unit is used to conduct in-depth analysis and judgment of the pre-processed information and classify the current situation into two categories: normal or abnormal;

[0057] The auxiliary intervention unit provides multi-dimensional intervention for abnormal incidents, including behavioral correction for the initiators of abnormal behavior, psychological counseling for victims, and education and guidance for bystanders, to promote the restoration of a safe campus environment and ensure the safety of teachers and students;

[0058] Furthermore, the information receiving unit includes a physical contact monitoring module and an environmental change detection module, which specifically includes the following steps:

[0059] Step S1, physical contact monitoring module: Use the wall vibration sensor to detect the vibration information of the wall or other fixed structure, and capture whether there is a physical collision or pushing event through the vibration change, and use the formula ViolenceScore = ∫(A(f)·W(f))df / (1+e (-k·Δt) ), where A(f) represents the vibration energy in the 30-200 Hz frequency band, W(f) represents the position weight coefficient, with toilet cubicles = 1.2 and corridor corners = 0.9, and k represents the duration correction factor, which increases by 0.5 every 10 seconds. This assists in identifying potential violent behavior and uses ultrasonic sensing technology to track the movement trajectory and distance changes of human bodies or objects in real time. MovementVector = argmin(∥Φ·S(t)-Δf(t)∥2+λ·TV(S)), where Φ represents the ultrasonic transmit-receive topology matrix, S(t) represents the spatial motion field intensity distribution, and TV(S) represents the total variation regularization term. This accurately captures abnormal movement and contact situations, enhancing the detection capability of limb movements.

[0060] Step S2, environmental change detection module: Analyze the collected campus sound data, use voiceprint recognition technology to detect emotional changes and abnormal sounds in the language of teachers and students, provide voice clues for injury incidents and abnormal social behavior, monitor changes in air flow, such as abnormal airflow caused by rapid movement, help to assist in judging group behavior or emergencies, and enhance the overall safety situation awareness of the environment.

[0061] The information receiving unit is based on a variety of sensing devices and technologies, including physical signal monitoring and environmental feature perception, to achieve comprehensive perception and collection of campus safety-related behaviors and atmosphere, providing accurate data support for subsequent security incident judgment and emergency response;

[0062] Furthermore, the information processing unit includes a spatiotemporal alignment module and an information alignment module, which specifically includes the following steps:

[0063] Step N1, Spatiotemporal Alignment Module: Uses time-frequency analysis to process signals collected by vibration sensors, identifies changes in frequency characteristics within different time periods, improves the accuracy of abnormal behavior detection, extracts features from electromagnetic sensor data, and generates a unique electromagnetic fingerprint to distinguish different events or identities, assist in locating and identifying abnormal behavior, and uses ultrasonic sensors to capture Doppler frequency shift information to accurately analyze the speed and direction of objects, enabling detailed analysis of dynamic behavior within the campus environment.

[0064] Step N2, information alignment module: associates sensor data with student identity information to bind behavior to specific individuals, supports subsequent personalized intervention and tracking, loads students' past behavior patterns and records, combines current data for comprehensive analysis, searches for abnormal behavior or repetitive risks, and improves security incident prediction capabilities.

[0065] Through the two modules of time-space alignment and information alignment, deep data integration and intelligent analysis are achieved, providing accurate and comprehensive decision-making basis for subsequent campus safety judgment and auxiliary intervention.

[0066] Furthermore, the judgment and decision-making unit includes a normal situation processing module and an abnormal situation processing module. The normal situation processing module archives the data when it determines that the behavior is normal, systematically stores the information collected and processed under normal conditions, and forms a complete data archive to facilitate subsequent query and analysis. The specific work includes the following steps:

[0067] Step M1, Behavioral Baseline Update: Regularly update the basic models and standards of student and campus behavior to adapt to the environment

[0068] Hexing

[0069] To ensure the accuracy of anomaly detection for changes;

[0070] Step M2, equipment self-test: Perform regular self-tests on monitoring and acquisition equipment to ensure the normal operation of hardware and sensors and the quality of data collection;

[0071] Step M3, Privacy Erasure: Automatically clear unnecessary personal privacy information, comply with relevant privacy protection laws and regulations, and ensure data usage compliance;

[0072] The abnormal situation handling module works as a threat level assessment, comprehensively analyzing the severity of abnormal events, assessing the security threat level, and guiding subsequent processing steps. The specific work includes the following steps:

[0073] Step K1, Environmental Intervention: When the threat level is primary, adjust the lighting color temperature. Switch to 5000K cool white light in the direction of the initiator's field of view to make them feel subconsciously uneasy. Maintain 3000K warm yellow light in the direction of the victim to provide psychological comfort. Use directional sound wave warnings to warn or disperse the affected area through specific directional sound waves to reduce the escalation of the conflict.

[0074] Step K2, personnel dispatch: When the threat level is medium, the system will automatically notify and direct the nearest security personnel to the incident location to rush to the scene, navigate to medical personnel, and dispatch medical personnel for a rapid response when necessary to ensure timely treatment for the injured;

[0075] Step K3, system-level response: When the threat level is high, the access control area is blocked, and access control is automatically performed in the area where the incident occurred to prevent the incident from spreading or the escape of the people involved. Data is reported and the event data and processing status are uploaded to the school management center or relevant security departments in real time to support decision-making and filing.

[0076] When campus injuries occur, the threat level is judged and corresponding measures are implemented. In the primary state, the light color temperature is adjusted and directional sound wave warnings are issued to avoid intensifying conflicts, reduce escalation of conflicts, and improve the safety of victims. In the intermediate state, security guards are dispatched to avoid insufficient security guards after the primary dispatch of security guards, resulting in no security guards in the intermediate and advanced states. In the advanced state, the access control area is blocked to prevent the spread of the incident or the escape of those involved, thereby improving safety.

[0077] Furthermore, the auxiliary intervention unit includes a module for correcting the initiator of abnormal behavior, a module for counseling victims, and a module for educating bystanders. The module for correcting the initiator of abnormal behavior specifically includes the following steps:

[0078] Step P1, immediate handling: electronically record the behavior of the initiator of abnormal behavior in real time to facilitate tracking and management, notify the initiator's parents as soon as possible to promote family intervention, and issue service orders or restrictive measures against the initiator of abnormal behavior within the school;

[0079] Step P2, special topic education: Conduct VR injury simulation courses, using virtual reality technology to allow the initiators of abnormal behavior to experience the consequences of injury and enhance their empathy; conduct anti-injury law examinations to enhance the legal awareness of the initiators of abnormal behavior through examinations; conduct social and emotional learning and implement social and emotional courses to cultivate the emotional management and social skills of the initiators of abnormal behavior;

[0080] Step P3, long-term tracking: Use AI technology to track the behavioral data of the initiators of abnormal behavior over a long period of time to assist in correction. Conduct regular monthly mental health assessments to monitor changes in the psychological state of the initiators of abnormal behavior.

[0081] The victim counseling module specifically includes the following steps:

[0082] Step T1: Immediate support: Intelligent robots provide psychological counseling and emotional support to victims, guiding them to quickly find a safe shelter;

[0083] Step T2, social support: Through the Peer Guardian Program, mobilize peers to participate, form a protection network, and use blockchain technology to create an anonymous and secure platform for victims to confide and seek help;

[0084] The bystander education module specifically includes the following steps:

[0085] Step R1, scenario teaching: holographic injury scene re-enactment is carried out. Holographic technology is used to re-enact the injury scene to enhance the sensitivity and sense of responsibility of bystanders. The wearable device can show the physiological pressure caused by the injury, allowing bystanders to experience the pain of the injury in an immersive way.

[0086] Step R2, positive reinforcement: Give credits to students who actively intervene in harmful behaviors, provide social currency incentives, and increase the enthusiasm of bystanders to help victims;

[0087] Through auxiliary intervention units covering the three roles of abnormal behavior initiators, victims and bystanders, combined with high-tech, VR, AI, blockchain, holographic technology and physiological signal feedback, timely handling of campus injuries, psychological counseling, behavior correction and educational incentives can be achieved, forming a multi-level, comprehensive campus injury intervention ecosystem, reducing the probability of recidivism of abnormal behavior initiators, protecting the physical and mental health of victims, avoiding bystanders from standing idly by, reducing the probability of campus injuries, and improving campus safety.

[0088] The security management method based on the smart campus specifically includes the following steps:

[0089] Step 1: Obtain various data and event information on campus through various sensors, cameras, microphones, and other campus information collection devices;

[0090] Step 2: Preliminary preprocessing, cleaning, and formatting of the received raw information to prepare for subsequent discrimination and analysis to determine whether campus injury has occurred;

[0091] Step 3: Conduct in-depth analysis and judgment of the pre-processed information, classifying the current situation as normal or abnormal. If no campus injury has occurred, archive the data and systematically store the information collected and processed under normal conditions. If a campus injury has occurred, comprehensively analyze the severity of the abnormal event, assess the security threat level, and guide subsequent processing steps.

[0092] Step 4: After a campus injury occurs, conduct multi-dimensional intervention to correct the behavior of the initiator of the abnormal behavior, provide psychological counseling to the victim, and educate and guide the bystanders, promote the restoration of a safe campus environment, and ensure the safety of teachers and students.

[0093] By deeply combining technical means with educational psychology, we systematically construct a three-pronged intervention system of science and technology + education + justice to reduce the probability of campus injuries and improve campus safety.

[0094] The above are only preferred embodiments of the present invention and are merely illustrative, not restrictive, of the present invention. Those skilled in the art will appreciate that many changes, modifications, and even equivalents may be made to the embodiments within the spirit and scope of the claims, all of which fall within the scope of protection of the present invention.

Claims

1. The security management system based on smart campus is characterized by: It includes information receiving unit, information processing unit, judgment and decision-making unit and auxiliary intervention unit; The information receiving unit is used to obtain various data and event information on campus through various sensors, cameras, microphones and other campus information collection equipment to form original input data; The information processing unit is used to perform preliminary pre-processing, cleaning and formatting of the received original information in preparation for subsequent discrimination and analysis; The judgment and decision-making unit is used to conduct in-depth analysis and judgment on the pre-processed information and classify the current situation into two categories: normal or abnormal; The auxiliary intervention unit provides multi-dimensional intervention for abnormal events, including behavioral correction of the initiators of abnormal behavior, psychological counseling for victims, and education and guidance for bystanders, to promote the restoration of a safe campus environment and ensure the safety of teachers and students.

2. The security management system based on smart campus according to claim 1, characterized in that: The information receiving unit includes a physical contact monitoring module and an environmental change detection module, and specifically includes the following steps: Step S1, physical contact monitoring module: Use the wall vibration sensor to detect the vibration information of the wall or other fixed structure, and capture whether there is a physical collision or pushing event through the vibration change, and use the formula ViolenceScore = ∫(A(f)·W(f))df / (1+e (-k·Δt) ), where A(f) represents the vibration energy in the 30-200 Hz frequency band, W(f) represents the position weight coefficient, with toilet cubicles = 1.2 and corridor corners = 0.9, and k represents the duration correction factor, which increases by 0.5 every 10 seconds. This assists in identifying potential violent behavior and uses ultrasonic sensing technology to track the movement trajectory and distance changes of human bodies or objects in real time. MovementVector = argmin(∥Φ·S(t)-Δf(t)∥2+λ·TV(S)), where Φ represents the ultrasonic transmit-receive topology matrix, S(t) represents the spatial motion field intensity distribution, and TV(S) represents the total variation regularization term. This accurately captures abnormal movement and contact situations, enhancing the detection capability of limb movements. Step S2, environmental change detection module: Analyze the collected campus sound data, use voiceprint recognition technology to detect emotional changes and abnormal sounds in the language of teachers and students, provide voice clues for injury incidents and abnormal social behaviors, monitor changes in air flow, such as abnormal airflow caused by rapid movement, to help assist in judging group behavior or emergencies, and enhance the overall safety situation awareness of the environment.

3. The security management system based on smart campus according to claim 1, characterized in that: The information processing unit includes a spatiotemporal alignment module and an information alignment module, and specifically includes the following steps: Step N1, Spatiotemporal Alignment Module: Uses time-frequency analysis to process signals collected by vibration sensors, identifies changes in frequency characteristics within different time periods, improves the accuracy of abnormal behavior detection, extracts features from electromagnetic sensor data, and generates a unique electromagnetic fingerprint to distinguish different events or identities, assist in locating and identifying abnormal behavior, and uses ultrasonic sensors to capture Doppler frequency shift information to accurately analyze the speed and direction of objects, enabling detailed analysis of dynamic behavior within the campus environment. Step N2, information alignment module: associates sensor data with student identity information to bind behavior to specific individuals, supports subsequent personalized intervention and tracking, loads students' past behavior patterns and records, and conducts comprehensive analysis based on current data to identify abnormal behavior or repetitive risks, thereby improving the ability to predict safety incidents.

4. The security management system based on smart campus according to claim 1, characterized in that: The judgment and decision-making unit includes a normal situation processing module and an abnormal situation processing module. The normal situation processing module archives the data when it determines that the behavior is normal, systematically stores the information collected and processed under normal conditions, and forms a complete data archive to facilitate subsequent query and analysis. The specific work includes the following steps: Step M1, behavioral baseline update: Regularly update the basic model and standards of student and campus behavior to adapt to the environment and behavior. To ensure the accuracy of anomaly detection for changes; Step M2, equipment self-test: Perform regular self-tests on monitoring and acquisition equipment to ensure the normal operation of hardware and sensors and the quality of data collection; Step M3, Privacy Erasure: Automatically clear unnecessary personal privacy information, comply with relevant privacy protection laws and regulations, and ensure data usage compliance.

5. The security management system based on smart campus according to claim 4, characterized in that: The abnormal situation processing module works to assess the threat level, comprehensively analyze the severity of abnormal events, evaluate the security threat level, and guide subsequent processing steps. The specific work includes the following steps: Step K1, Environmental Intervention: When the threat level is primary, adjust the lighting color temperature. Switch to 5000K cool white light in the direction of the initiator's field of view to make them feel subconsciously uneasy. Maintain 3000K warm yellow light in the direction of the victim to provide psychological comfort. Use directional sound wave warnings to warn or disperse the affected area through specific directional sound waves to reduce the escalation of the conflict. Step K2, personnel dispatch: When the threat level is medium, the system will automatically notify and direct the nearest security personnel to the incident location to rush to the scene, navigate to medical personnel, and dispatch medical personnel for a rapid response when necessary to ensure timely treatment for the injured; Step K3, system-level response: When the threat level is high, the access control area is blocked and access control is automatically performed in the area where the incident occurred to prevent the incident from spreading or the escape of those involved. Data is reported and the event data and processing status are uploaded to the school management center or relevant security departments in real time to support decision-making and filing.

6. The security management system based on smart campus according to claim 1, characterized in that: The auxiliary intervention unit includes an abnormal behavior initiator correction module, a victim counseling module, and a bystander education module, wherein the abnormal behavior initiator correction module specifically includes the following steps: Step P1, immediate handling: electronically record the behavior of the initiator of abnormal behavior in real time to facilitate tracking and management, notify the initiator's parents as soon as possible to promote family intervention, and issue service orders or restrictive measures against the initiator of abnormal behavior within the school; Step P2, special topic education: Conduct VR injury simulation courses, using virtual reality technology to allow the initiators of abnormal behavior to experience the consequences of injury and enhance their empathy; conduct anti-injury law examinations to enhance the legal awareness of the initiators of abnormal behavior through examinations; conduct social and emotional learning and implement social and emotional courses to cultivate the emotional management and social skills of the initiators of abnormal behavior; Step P3, long-term tracking: Use AI technology to track the behavioral data of the initiators of abnormal behavior over a long period of time to assist in correction, conduct regular mental health assessments every month, and monitor changes in the psychological state of the initiators of abnormal behavior.

7. The security management system based on smart campus according to claim 6, characterized in that: The victim counseling module specifically includes the following steps: Step T1: Immediate support: Intelligent robots provide psychological counseling and emotional support to victims, guiding them to quickly find a safe shelter; Step T2, social support: Through the Peer Guardian Program, mobilize peers to participate, form a protection network, and use blockchain technology to create an anonymous and secure platform for victims to confide and seek help.

8. The security management system based on smart campus according to claim 7, characterized in that: The bystander education module specifically includes the following steps: Step R1, scenario teaching: holographic injury scene re-enactment is carried out. Holographic technology is used to re-enact the injury scene to enhance the sensitivity and sense of responsibility of bystanders. The wearable device can show the physiological pressure caused by the injury, allowing bystanders to experience the pain of the injury in an immersive way. Step R2, positive reinforcement: Give credits to students who actively intervene in harmful behaviors, provide social currency incentives, and increase the enthusiasm of bystanders to help victims.

9. The security management method based on smart campus is characterized by: The security management method is applied to the security management system according to any one of claims 1 to 8, and specifically comprises the following steps: Step 1: Obtain various data and event information on campus through various sensors, cameras, microphones, and other campus information collection devices; Step 2: Preliminary preprocessing, cleaning, and formatting of the received raw information to prepare for subsequent discrimination and analysis to determine whether campus injury has occurred; Step 3: Conduct in-depth analysis and judgment of the pre-processed information, classifying the current situation as normal or abnormal. If no campus injury has occurred, archive the data and systematically store the information collected and processed under normal conditions. If a campus injury has occurred, comprehensively analyze the severity of the abnormal event, assess the security threat level, and guide subsequent processing steps. Step 4: After a campus injury occurs, conduct multi-dimensional intervention to correct the behavior of the initiator of the abnormal behavior, provide psychological counseling to the victim, and educate and guide the bystanders, promote the restoration of a safe campus environment, and ensure the safety of teachers and students.

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