Internet-of-things campus supervision and management security system

Abstract

The invention discloses an internet-of-things campus supervision and management security system. The system comprises a sensing layer, a transmission layer, a processing layer and an application layer. The sensing layer collects campus data through a camera and various sensors; the transmission layer transmits data in a wireless and wired combined mode; the processing layer analyzes data by using big data and artificial intelligence technologies; and the application layer provides multi-user service. The system is provided with a personnel management module, an equipment and facility management module, an environment monitoring module, a safety early warning module, an emergency command module and the like. The functions of personnel identity recognition and trajectory tracking, equipment state monitoring and repair management, environmental parameter monitoring and regulation, abnormal behavior and potential safety hazard early warning, emergency resource optimization and allocation and the like are realized. The campus safety management efficiency is effectively improved, the monitoring comprehensiveness and the early warning accuracy are enhanced, the emergency management system is perfected, and the campus safety is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of campus safety management, and in particular to an Internet of Things campus supervision management safety system. Background Art

[0002] With the vigorous development of education, the continuous expansion of campuses and the increasing number of students and faculty, campus security management faces unprecedented challenges. Traditional campus security management methods have many limitations. For example, manual patrols are inefficient and lack comprehensive, real-time monitoring. While surveillance cameras can record some campus conditions, they often have blind spots and rely on manual video review, making it difficult to detect and address safety hazards in a timely manner. Furthermore, traditional methods struggle to achieve efficient and accurate management of campus equipment and facilities, personnel access control, and environmental monitoring.

[0003] In the current digital age, IoT technology has experienced rapid development and has been widely applied in various fields. Introducing IoT technology into campus security management has the potential to build a more intelligent, efficient, and comprehensive campus supervision and management security system, improving campus security management and creating a safe and harmonious learning and working environment for teachers and students. Summary of the Invention

[0004] The purpose of the present invention is to provide an Internet of Things campus supervision and management security system to solve the problems of low efficiency, incomplete monitoring, difficulty in timely detection and treatment of safety hazards in existing campus safety management methods, and to achieve intelligent, precise and real-time management of campus safety.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solutions: an Internet of Things campus supervision and management security system, including a perception layer, a transmission layer, a processing layer and an application layer;

[0006] The perception layer is used to collect information on personnel activities, equipment and facility status, and environmental parameters on campus;

[0007] The transmission layer is used to transmit the data collected by the perception layer to the processing layer;

[0008] The processing layer uses big data analysis, artificial intelligence, and machine learning technologies to conduct in-depth data mining and analysis;

[0009] The application layer provides diverse application services for different users.

[0010] As a further improvement of the technical solution of the present invention, the perception layer includes a camera, an access control sensor, a smoke sensor, a temperature and humidity sensor, a human infrared sensor, and a vibration sensor; the camera is used to collect video image information; the access control sensor is used to detect the entry and exit of people; the smoke sensor and the temperature and humidity sensor are used to monitor environmental safety and comfort, respectively; the human infrared sensor is used to detect the presence and movement of people in the area; and the vibration sensor is used to monitor abnormal vibration and perimeter intrusion of equipment and facilities.

[0011] As a further improvement to the technical solution of the present invention, the transmission layer adopts a combination of wireless communication networks and wired communication networks, the wireless communication networks include Wi-Fi, Bluetooth, ZigBee and NB-IoT, and the wired communication network is Ethernet.

[0012] As a further improvement of the technical solution of the present invention, the processing layer includes a server and data processing software; the server receives, stores and processes data from the perception layer; the data processing software includes a data management module, a system configuration module and a user authority management module.

[0013] As a further improvement to the technical solution of the present invention, the application layer includes a web application and a mobile application. Users can view the campus safety status in real time, receive safety warning information, and perform equipment and facility management and personnel information management operations through the web application or the mobile application.

[0014] As a further improvement to the technical solution of the present invention, the system also includes a personnel management module, which includes an identity recognition and authentication unit, a personnel trajectory tracking unit and an attendance management unit; the identity recognition and authentication unit uses facial recognition technology and a campus card to perform personnel identity recognition and authentication; the personnel trajectory tracking unit tracks personnel activity trajectories by analyzing access control sensors and camera data; the attendance management unit automatically generates attendance reports based on personnel entry and exit records.

[0015] As a further improvement to the technical solution of the present invention, the system also includes an equipment and facility management module, which includes an equipment status monitoring unit, an equipment maintenance reminder unit and an equipment repair management unit; the equipment status monitoring unit monitors the equipment operating status through sensors; the equipment maintenance reminder unit generates maintenance reminder information based on the equipment operating status and maintenance cycle; the equipment repair management unit receives equipment repair information submitted by users through a web application or a mobile application and tracks the processing progress.

[0016] As a further improvement of the technical solution of the present invention, the system also includes an environmental monitoring module, which includes an air quality monitoring unit, a temperature and humidity monitoring unit, and a noise monitoring unit; the air quality monitoring unit monitors the concentration of pollutants in the air and issues an early warning when it exceeds the standard; the temperature and humidity monitoring unit monitors the ambient temperature and humidity and automatically adjusts it, and issues an early warning when it is abnormal; the noise monitoring unit monitors the ambient noise level and issues an early warning when it exceeds the standard.

[0017] As a further improvement to the technical solution of the present invention, the system also includes a security warning module, which includes an abnormal behavior warning unit, a fire warning unit and an intrusion warning unit; the abnormal behavior warning unit uses an artificial intelligence algorithm to analyze video images to identify abnormal behavior and issue a warning; the fire warning unit monitors fire hazards and issues a warning through smoke sensors, temperature sensors and flame sensors; the intrusion warning unit detects illegal intrusions and issues a warning through infrared counter-radiation sensors and vibration sensors.

[0018] As a further improvement of the technical solution of the present invention, the system also includes an emergency command module, which includes an emergency plan management unit, an emergency command and dispatch unit and an emergency resource management unit; the emergency plan management unit digitally manages emergency plans for various types of campus safety incidents; the emergency command and dispatch unit activates the emergency plan for command and dispatch when a safety incident occurs; the emergency resource management unit manages campus emergency resources and deploys them according to demand.

[0019] The present invention has the following beneficial effects:

[0020] The Internet of Things campus supervision and management safety system provided by the present invention integrates multi-module functions through the perception layer, transmission layer, processing layer and application layer architecture, and utilizes technologies such as the Internet of Things, big data, and artificial intelligence to achieve comprehensive monitoring and management of campus personnel, equipment, and environment. It can accurately warn of safety hazards in real time, optimize resource allocation and emergency response, greatly improve campus safety management efficiency, monitoring comprehensiveness, and emergency response capabilities, effectively protect the safety of teachers and students, and create a safe and harmonious campus environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0022] FIG1 is a schematic diagram of a framework of an Internet of Things campus supervision and management security system according to an embodiment of the present invention;

[0023] FIG2 is a schematic diagram of a framework of a perception layer according to an embodiment of the present invention;

[0024] FIG3 is a schematic diagram of a transport layer framework according to an embodiment of the present invention;

[0025] FIG4 is a schematic diagram of a framework of a processing layer according to an embodiment of the present invention;

[0026] FIG5 is a schematic diagram of the framework of the application layer according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The exemplary embodiments and descriptions of the present invention are used to explain the present invention but are not intended to limit the present invention.

[0028] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, upper end, lower end, top, bottom...) are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0029] In the present invention, unless otherwise specified or limited, the term "connection" should be understood in a broad sense. For example, "connection" can mean fixed connection, detachable connection, or integration; mechanical connection, electrical connection; direct connection, or indirect connection through an intermediate medium; internal communication between two elements, or interaction between two elements, unless otherwise specified. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0030] In addition, the terms "first," "second," and so on, used in this disclosure are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly indicating the number of the technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include at least one such feature. Furthermore, the technical solutions of various embodiments may be combined with each other, but only on the basis that they can be implemented by a person of ordinary skill in the art. If the combination of technical solutions contradicts or cannot be implemented, it shall be deemed that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this disclosure.

[0031] The present invention will be further described in detail below with reference to the accompanying drawings.

[0032] Reference Figures 1 to 5 , an Internet of Things campus supervision and management security system, the system includes:

[0033] The perception layer consists of a variety of sensors and data acquisition devices, including but not limited to cameras, access control sensors, smoke sensors, temperature and humidity sensors, infrared sensors for human presence, and vibration sensors. These devices are distributed throughout the campus and collect real-time information on human activity, equipment and facility status, and environmental parameters. For example, cameras are installed at key locations such as campus entrances and exits, teaching building corridors, and playgrounds to capture video images. Access control sensors are installed at the school gate, teaching building entrances, and dormitory entrances to detect entry and exit. Smoke sensors and temperature and humidity sensors are installed in classrooms, laboratories, libraries, and other places to monitor environmental safety and comfort.

[0034] The transport layer uses a combination of wireless communication technologies (such as Wi-Fi, Bluetooth, ZigBee, and NB-IoT) and wired communication technologies (such as Ethernet) to transmit data collected by the perception layer to the processing layer. Wireless communication technologies are suitable for scenarios where cabling is difficult or flexible deployment is required, such as outdoor areas and temporary locations on campus. Wired communication technologies ensure stable and reliable data transmission, such as network connections within buildings like teaching and office buildings. By building a stable and efficient communication network, timely and accurate data transmission is ensured.

[0035] The processing layer is primarily composed of servers and data processing software. The servers are responsible for receiving, storing, and processing data from the perception layer, applying technologies such as big data analytics, artificial intelligence, and machine learning to conduct in-depth data mining and analysis. For example, video image data analysis enables human behavior recognition and abnormal behavior warnings; access control data analysis identifies entry and exit patterns and promptly identifies abnormal entry and exit situations; and environmental parameter data analysis predicts potential safety hazards such as fires and water leaks. The data processing software also provides functions such as data management, system configuration, and user rights management to ensure the normal operation of the system and data security.

[0036] Application layer: Provides diverse application services for campus security managers, teachers, students, and other users. Through web and mobile applications, users can view campus security status in real time, receive safety alerts, and manage equipment, facilities, and personnel information. For example, security managers can use the application to view surveillance video from various areas of the campus anytime, anywhere, receive alerts, and respond promptly. Teachers can check the status of classroom equipment and report equipment repairs. Students can use the mobile application to request leave and view campus event notifications.

[0037] Furthermore, an Internet of Things campus supervision and management security system further includes:

[0038] Personnel management module

[0039] Identity recognition and authentication: Facial recognition technology and campus cards are used to identify and authenticate personnel. Facial recognition devices are installed at key locations such as campus entrances and exits, teaching buildings, and dormitories. When a person passes through, the device automatically captures their facial image and compares it with the information in the database. Once the identity is confirmed, entry is allowed. Furthermore, combined with the campus card system, card entry and exit are implemented, providing dual security for personnel access management.

[0040] Personnel Tracking: By analyzing data collected by access control sensors, cameras, and other devices, the movement of people on campus can be tracked in real time. When a security incident occurs, the movement routes of relevant personnel can be quickly checked, providing important clues for the investigation.

[0041] Attendance Management: Automatically generate attendance reports based on entry and exit records, allowing teachers and school administrators to track the attendance of students and faculty. It also provides early warnings for abnormal situations such as lateness, early departure, and absences.

[0042] Equipment and facility management module

[0043] Equipment status monitoring: Sensors are installed on various equipment and facilities on campus (such as electrical equipment, lighting equipment, firefighting equipment, elevators, etc.) to monitor the operating status of the equipment in real time, including its on / off status, operating parameters, and fault information. For example, by monitoring parameters such as current and voltage of electrical equipment, the normal operation of the equipment can be determined; smoke sensors and temperature sensors are used to monitor the environmental parameters around firefighting equipment to promptly detect fire hazards.

[0044] Equipment maintenance reminders: Based on the equipment's operating status and maintenance cycle, the system automatically generates equipment maintenance reminders, notifying relevant maintenance personnel to perform equipment maintenance and upkeep. At the same time, the system records the equipment's repair and maintenance history, providing data support for equipment management.

[0045] Equipment Repair Management: Teachers, students, or other personnel who discover a device fault can report it through the web or mobile app. Reports include the device name, fault description, and the person reporting the fault. The system then sends the report to the relevant maintenance personnel and tracks the progress of the report in real time, allowing them to easily understand the repair status.

[0046] Environmental monitoring module

[0047] Air quality monitoring: Air quality monitoring sensors are installed in multiple areas across campus to monitor real-time concentrations of air pollutants, such as PM2.5, PM10, sulfur dioxide, nitrogen oxides, and carbon monoxide. When air quality exceeds standards, the system automatically issues warnings, reminding teachers and students to take protective measures and implement appropriate measures to improve air quality, such as activating air purification equipment and increasing ventilation.

[0048] Temperature and humidity monitoring: Temperature and humidity sensors are installed in classrooms, laboratories, libraries, and other places to monitor ambient temperature and humidity in real time. The system automatically adjusts the temperature and humidity based on the appropriate temperature and humidity range for each location, such as through air conditioning, humidifiers, and dehumidifiers, to provide a comfortable learning and working environment for teachers and students. Furthermore, when temperature and humidity are abnormal, the system issues an early warning so that timely measures can be taken to resolve the problem.

[0049] Noise monitoring: Noise monitoring sensors are installed in teaching areas, living areas, and other areas on campus to monitor ambient noise levels in real time. When noise levels exceed specified standards, the system automatically issues an alert, prompting personnel to take measures to reduce noise levels, such as restricting vehicle traffic and prohibiting loud noises, to ensure a quiet campus environment.

[0050] Security warning module

[0051] Abnormal behavior warning: AI algorithms analyze video data collected by cameras to identify unusual behaviors, such as fighting, running, and falling. When abnormal behavior is detected, the system automatically issues a warning message, notifying security personnel to promptly address the situation.

[0052] Fire Warning: Using smoke, temperature, and flame sensors, the system monitors fire hazards on campus in real time. When smoke concentration, temperature, or flames exceed set thresholds, the system immediately issues a fire warning and activates the fire alarm system, notifying security personnel and the fire department. It also automatically shuts down power and ventilation systems in the affected area to prevent the fire from spreading.

[0053] Intrusion warning: Infrared sensors, vibration sensors, and other intrusion detection devices are installed around the campus perimeter. When a person or object is detected illegally entering the campus, the system automatically issues an intrusion warning message, notifying security personnel to take appropriate action. Simultaneously, cameras monitor the intrusion area in real time, providing video evidence for incident handling.

[0054] Emergency command module

[0055] Emergency Plan Management: Develop emergency plans for various campus safety incidents, including fires, earthquakes, sudden illnesses, and violent incidents. These plans include the emergency organization structure, division of responsibilities, emergency response procedures, and rescue measures. The system digitally manages emergency plans for easy access and updating.

[0056] Emergency Command and Dispatch: When a security incident occurs, security managers can use the emergency command module to activate the corresponding emergency plan and conduct emergency command and dispatch. The system integrates various campus resources, such as personnel, equipment, and supplies, to achieve unified command and coordinated operations. Through video conferencing and voice communication, they can communicate with on-site personnel in a timely manner, understand the progress of the incident, and issue command instructions.

[0057] Emergency Resource Management: Manage emergency resources on campus, including firefighting equipment, first aid medications, and emergency lighting. Maintain real-time information on emergency resource inventory, storage location, and expiration dates. Regularly inspect and maintain emergency resources to ensure their availability in emergency situations. Furthermore, rationally deploy emergency resources based on emergency needs to improve emergency rescue efficiency.

[0058] Implementation Cases:

[0059] 1. Personnel Management Module Implementation Case

[0060] Identity recognition and authentication: Facial recognition equipment is installed at campus entrances and exits. The equipment uses high-definition cameras and advanced facial recognition algorithms. When a person approaches an entrance or exit, the camera automatically captures a facial image I and transmits the image to a server via the network for comparison. The server stores a database of facial information for all faculty, students, and staff on campus. Let Ti be the i-th facial template in the database. The Euclidean distance formula is used to calculate the similarity d between the captured image and the template image:

[0061]

[0062] Among them, n is the number of image feature points, I j is the value of the jth feature point of the collected image, T ij For the

[0063] The value of the jth feature point of the i-th template image. When d is less than the set threshold D, it is judged that the recognition is successful, the system automatically opens the access control, and records the time and identity information of the personnel entering and exiting; for unregistered personnel, the system prompts that it cannot be recognized, and records the relevant information, and notifies the security management personnel to handle it. Personnel trajectory tracking: In the teaching building and dormitory, multiple cameras are installed in the corridors of each floor, combined with human infrared sensors. When someone moves in the corridor, the human infrared sensor triggers the camera to start recording and transmit the video data to the server. The server analyzes the video data and tracks the activity trajectory of the personnel in the teaching building or dormitory in real time. The Kalman filter algorithm is used to predict and update the personnel position. Let X k is the state vector of the person at time k (including position and speed information), Z k is the observation vector at time k (the position of the person detected by the camera), then the prediction equation of the Kalman filter is:

[0064]

[0065] The update equation is:

[0066]

[0067] Among them, F k is the state transfer matrix, B k is the control matrix, u k is the control vector, H k is the observation matrix, K k The Kalman gain is calculated through continuous iterative calculations to accurately track individual trajectories. When a student enters the building, the system records their entry time, floor location, and movement paths within each floor. If a student remains in a classroom for an extended period outside of class time or exhibits unusual behavior, the system automatically issues an alert to notify relevant teachers or administrators.

[0068] Attendance management: Teachers log in to the system through the web application and can view the attendance of students in their classes on the attendance management interface. The system automatically generates attendance reports based on the data collected by the access control sensors and cameras, showing student attendance, lateness, early departure, absences, etc. start , the actual arrival time is t arrive , the late time threshold is set to Δt late , the early departure time threshold is Δt early , the school time is t end , then the attendance status judgment formula is as follows:

[0069] like , determined to be late;

[0070] like (t leave (The actual time the student leaves) is considered as early leaving;

[0071] If no student entry or exit records are detected, the student will be considered absent.

[0072] Teachers can check and modify attendance data and make notes in the system if there are any special circumstances that need to be explained. At the same time, students and parents can check students' attendance records through mobile applications to keep abreast of their children's school status.

[0073] 2. Equipment and Facility Management Module Implementation Case

[0074] Equipment status monitoring: Install current sensors and temperature sensors on electrical equipment in the laboratory (such as experimental instruments, computers, etc.). The sensors collect the current I and temperature T of the electrical equipment in real time.

[0075] The data is transmitted to the server through the wireless communication module. The server analyzes the data and assumes that the average current of the device during normal operation is μ I , with a standard deviation of σ I , the mean temperature is μ T , with a standard deviation of σ T , the 3σ principle is used to determine whether the equipment is abnormal, that is, the equipment is considered abnormal when the following conditions are met:

[0076] or

[0077] If the current or temperature of an electrical device is abnormally high, exceeding a set threshold, the system automatically issues a fault warning, notifying lab managers and maintenance personnel. Upon receiving the notification, maintenance personnel can view the fault information and location via a mobile app and promptly visit the lab to perform repairs. After the repair is complete, the maintenance personnel will record the repair in the system, including time, details, and replaced parts.

[0078] Equipment maintenance reminder: Let the equipment running time be t run , the maintenance cycle of the equipment is T maintain , when t run ≥T maintain When the system is in operation, it will automatically generate equipment maintenance reminder information to notify relevant maintenance personnel to carry out equipment maintenance and servicing. At the same time, it will record the equipment's repair history and maintenance records to provide data support for equipment management.

[0079] Equipment repair management: A student finds a leaking faucet in the dormitory and enters the equipment repair interface through the mobile application. On the repair interface, the student selects the equipment type (such as faucet), fills in the fault description (such as the leak location, leak severity, etc.), uploads on-site photos (if necessary), and submits the repair application. Let the repair time be t report , the maintenance personnel's order acceptance time is t accept , the maintenance completion time is t finish , then the repair processing time is T process =t finish −t report The system tracks the progress of repair requests in real time, making it easier for repair personnel to understand the repair status. After the repair is completed, students can evaluate the repair service in the system, and the repair personnel and dormitory management staff can view the evaluation results.

[0080] 3. Environmental Monitoring Module Implementation Case

[0081] Air quality monitoring: Air quality monitoring stations are installed in multiple areas of the campus (such as teaching buildings, playgrounds, cafeterias, etc.). The monitoring stations are equipped with a variety of gas sensors and particulate matter sensors, which can monitor the concentration of pollutants such as PM2.5, PM10, sulfur dioxide, nitrogen oxides, and carbon monoxide in the air in real time. Suppose the current concentration of a pollutant is C, and the safe concentration threshold of the pollutant is C threshold , when C>C threshold When the air quality is high, the system will automatically issue an early warning message to remind teachers and students to take precautions. At the same time, the school can take corresponding measures according to the air quality, such as suspending outdoor activities and improving classroom ventilation.

[0082] Temperature and humidity monitoring: Temperature and humidity sensors are installed in classrooms and offices. The sensors are connected to the server via Bluetooth or Wi-Fi. The server collects temperature and humidity data in real time. Let the current temperature be T, the current humidity be H, and the suitable temperature range be [T min , T max ], the suitable humidity range is [H min , H max ],when

[0083] T <T min When T>T max When H <H min When H>H max At the same time, teachers and students can view the real-time temperature and humidity conditions in the classroom through the mobile application. If they feel uncomfortable, they can also request adjustment in the application, and the system will make corresponding adjustments based on the request.

[0084] Noise monitoring: Noise monitoring sensors are installed at the boundaries of the teaching area and living area on campus. The sensors transmit the noise data they detect to the server via wireless communication modules. Assume that the current noise decibel value is N, and the daytime noise standard value of the teaching area is N. day , the noise standard value at night is N night , when N>N during the day day Or at night N>N night When a noise level is exceeded, the system automatically issues a noise warning message, notifying relevant departments and personnel to take measures to reduce noise. For example, it notifies construction units on campus to suspend work, reminds vehicles to slow down, prohibits honking, and dissuades people from making loud noises.

[0085] 4. Security Early Warning Module Implementation Case

[0086] Abnormal behavior warning: Multiple high-definition cameras are installed in crowded areas on campus, such as playgrounds and cafeterias. AI algorithms are used to analyze the captured video images in real time. This behavior recognition algorithm uses HOG (Histogram of Oriented Gradients) feature extraction combined with an SVM (Support Vector Machine) classifier to identify abnormal behavior. The extracted image feature vector is f, and the SVM classifier's decision function is g(f). A classification model is trained to detect abnormal behavior when g(f) outputs an abnormal behavior category. The system automatically issues an alert, notifying security personnel to address the situation. Security personnel can view the alert and related video footage via a mobile app, understanding the situation and responding quickly.

[0087] Fire warning: Fire alarm systems are installed in teaching buildings, libraries, laboratories and other places. The fire alarm system consists of smoke sensors, temperature sensors, flame sensors and alarm controllers. Let the smoke concentration be S, the temperature be T, the flame intensity be F, and the corresponding alarm threshold be S threshold 、

[0088] T threshold 、F threshold , when S≥S threshold or T ≥ T threshold or F ≥ F threshold When a fire occurs, the alarm controller immediately issues a fire warning and transmits the information to the campus safety management center. Simultaneously, the system automatically activates firefighting equipment, such as the sprinkler system and fire alarm system, notifying teachers and students to evacuate. Upon receiving the fire warning, the safety management center staff quickly activates the emergency plan and organizes personnel for firefighting and rescue operations.

[0089] Intrusion warning: Infrared sensors and vibration sensors are installed around the campus perimeter to form an intrusion detection system. Infrared sensors are installed in pairs on both sides of the campus wall or fence. When an object blocks the infrared light, the sensor triggers an alarm signal. The vibration sensor is installed on the wall or fence and will also trigger an alarm signal when it detects vibration caused by climbing or vandalism. Let the number of times the infrared sensor is triggered be n. infrared , the vibration intensity of the vibration sensor is V, and the corresponding alarm threshold is n threshold 、V threshold , when n infrared ≥n threshold or V ≥ V threshold When an intrusion occurs, the system automatically issues an intrusion warning message to notify the security management personnel. At the same time, the system links the cameras near the perimeter to monitor the intrusion area in real time, providing video evidence for the security management personnel to take timely measures to stop the intrusion.

[0090] 5. Emergency Command Module Implementation Case

[0091] Emergency plan management: The school has developed a detailed fire emergency plan, which includes the emergency organization structure in the event of a fire, the division of responsibilities of various departments and personnel, the emergency response process, evacuation routes, rescue measures, etc. Graph theory is used to model the various links and processes in the emergency plan. The emergency plan graph is G=(V, E), where V is a set of nodes, representing each task or decision point in the emergency process; E is an edge set, representing the sequence or relationship between tasks. In this way, the emergency plan is digitally managed, making it easy to access and update at any time. The school regularly organizes fire emergency drills for teachers and students. During the drills, the emergency command module is used to simulate fire scenarios to test the feasibility and effectiveness of the emergency plan.

[0092] Emergency command and dispatch: When a security incident occurs, the security management personnel can activate the corresponding emergency plan through the emergency command module and conduct emergency command and dispatch. The system integrates various resources on campus, such as personnel, equipment, and materials, and uses a resource allocation optimization model to allocate resources. Suppose the resource set is

[0093] , the task set is , resources i For task t j The utility value is u ij , the goal is to maximize the total utility while satisfying resource constraints and task requirements:

[0094]

[0095] Among them, x ijis a decision variable, when resource r i Assigned to task t j Time x ij =1, otherwise x ij = 0. By solving this optimization model, we can achieve rational resource allocation and unified command and coordinated operations. Through video conferencing, voice communication, and other functions, we can communicate with on-site personnel in a timely manner, understand the progress of the incident, and issue command instructions.

[0096] Emergency resource management: Manage emergency resources on campus, including firefighting equipment, first aid medicines, emergency lighting equipment, etc. Real-time knowledge of emergency resource inventory quantity Q, storage location L, and expiration date D expire Information such as emergency resources are regularly inspected and maintained to ensure normal use in emergency situations. Let the current time be t now , when t now ≥D expire −Δt check (Δt check When the system issues a resource expiration warning (for early inspection time), it reminds relevant personnel to handle the issue. At the same time, it rationally allocates emergency resources according to the needs of the emergency event to improve the efficiency of emergency rescue.

[0097] In summary, the present invention has the following beneficial effects:

[0098] Improved campus security management efficiency: IoT technology enables real-time collection and automated processing of information about campus personnel, equipment, facilities, and the environment, significantly reducing manual intervention and improving management efficiency. For example, automated attendance management and equipment repair reporting save significant manpower and time.

[0099] Enhanced comprehensiveness and real-time monitoring of campus security: The system covers every area of ​​the campus, enabling comprehensive, real-time monitoring through a variety of sensors and cameras. This enables timely detection of safety hazards and anomalies, and prompts early warnings, buying valuable time for incident resolution. Furthermore, the personnel tracking function provides real-time monitoring of on-campus personnel movements, further enhancing the refinement of campus security management.

[0100] Improving the accuracy and timeliness of campus safety warnings: Leveraging technologies such as big data analytics and artificial intelligence to conduct in-depth analysis of collected data can accurately identify abnormal behavior and safety hazards, and issue timely warnings. Compared to traditional manual judgment methods, the accuracy and timeliness of warnings have been significantly improved. For example, the fire warning system can detect and alert fires in their early stages, effectively preventing them from expanding and spreading.

[0101] Optimize campus environmental management: The environmental monitoring module monitors campus air quality, temperature, humidity, noise, and other environmental parameters in real time, and automatically adjusts and optimizes them based on the monitoring results, providing teachers and students with a more comfortable and healthy learning and working environment. Real-time monitoring of environmental parameters also helps to promptly identify environmental safety hazards and ensure campus safety.

[0102] Improve the campus emergency management system: The emergency command module implements digital management of emergency plans and intelligent emergency command and dispatch, enhancing the campus's ability to respond to emergencies. In the event of a security incident, the emergency plan can be quickly activated, campus resources can be integrated, and efficient emergency rescue and disposal can be carried out to minimize casualties and property losses.

[0103] The technical solutions provided by the embodiments of the present invention are introduced in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the embodiments of the present invention. The description of the above embodiments is only applicable to help understand the principles of the embodiments of the present invention. At the same time, for those skilled in the art, according to the embodiments of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. An Internet of Things campus supervision and management security system, characterized by: Includes perception layer, transport layer, processing layer and application layer; The perception layer is used to collect information on personnel activities, equipment and facility status, and environmental parameters on campus; The transmission layer is used to transmit the data collected by the perception layer to the processing layer; The processing layer uses big data analysis, artificial intelligence, and machine learning technologies to conduct in-depth data mining and analysis; The application layer provides diverse application services for different users.

2. The Internet of Things campus supervision and management security system according to claim 1 is characterized by: The perception layer includes cameras, access control sensors, smoke sensors, temperature and humidity sensors, human infrared sensors, and vibration sensors; The camera is used to collect video image information; the access control sensor is used to detect the entry and exit of people; the smoke sensor and the temperature and humidity sensor are used to monitor environmental safety and comfort respectively; the human infrared sensor is used to detect the presence and movement of people in the area; the vibration sensor is used to monitor abnormal vibration of equipment and facilities and perimeter intrusion.

3. The Internet of Things campus supervision and management security system according to claim 1 is characterized by: The transmission layer adopts a combination of wireless communication network and wired communication network. The wireless communication network includes Wi-Fi, Bluetooth, ZigBee and NB-IoT, and the wired communication network is Ethernet.

4. The Internet of Things campus supervision and management security system according to claim 1 is characterized by: The processing layer includes a server and data processing software; the server receives, stores and processes data from the perception layer; the data processing software includes a data management module, a system configuration module and a user authority management module.

5. The Internet of Things campus supervision and management security system according to claim 1 is characterized by: The application layer includes a web application and a mobile application. Users can use the web application or the mobile application to view campus safety conditions in real time, receive safety warning information, and perform equipment and facility management and personnel information management operations.

6. The Internet of Things campus supervision and management security system according to claim 1 is characterized by: The system also includes a personnel management module, which includes an identity recognition and authentication unit, a personnel trajectory tracking unit and an attendance management unit; the identity recognition and authentication unit uses facial recognition technology and a campus card to perform personnel identity recognition and authentication; the personnel trajectory tracking unit tracks personnel activity trajectories by analyzing access control sensors and camera data; the attendance management unit automatically generates attendance reports based on personnel entry and exit records.

7. The Internet of Things campus supervision and management security system according to claim 5 is characterized by: The system also includes an equipment and facility management module, which includes an equipment status monitoring unit, an equipment maintenance reminder unit, and an equipment repair management unit; the equipment status monitoring unit monitors the equipment operating status through sensors; the equipment maintenance reminder unit generates maintenance reminder information based on the equipment operating status and maintenance cycle; The equipment repair management unit receives equipment repair information submitted by the user through a Web application or a mobile application and tracks the processing progress.

8. The Internet of Things campus supervision and management security system according to claim 1 is characterized by: The system also includes an environmental monitoring module, which includes an air quality monitoring unit, a temperature and humidity monitoring unit, and a noise monitoring unit; the air quality monitoring unit monitors the concentration of pollutants in the air and issues an early warning when it exceeds the standard; the temperature and humidity monitoring unit monitors the ambient temperature and humidity and automatically adjusts them, issuing an early warning when an abnormality occurs; the noise monitoring unit monitors the ambient noise level and issues an early warning when it exceeds the standard.

9. The Internet of Things campus supervision and management security system according to claim 2 is characterized by: The system also includes a security warning module, which includes an abnormal behavior warning unit, a fire warning unit and an intrusion warning unit; the abnormal behavior warning unit uses an artificial intelligence algorithm to analyze video images to identify abnormal behavior and issue a warning; the fire warning unit monitors fire hazards and issues a warning through smoke sensors, temperature sensors and flame sensors; the intrusion warning unit detects illegal intrusions and issues a warning through infrared counter-radiation sensors and vibration sensors.

10. The Internet of Things campus supervision and management security system according to claim 1 is characterized by: The system also includes an emergency command module, which includes an emergency plan management unit, an emergency command and dispatch unit, and an emergency resource management unit; the emergency plan management unit digitally manages emergency plans for various types of campus safety incidents; the emergency command and dispatch unit activates the emergency plan for command and dispatch when a safety incident occurs; the emergency resource management unit manages campus emergency resources and deploys them according to demand.

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