Intelligent campus security management system based on Internet of Things

Abstract

The invention belongs to the technical field of smart campus security management, and relates to a smart campus security management system based on Internet of Things, comprising: a logic management region division module, each logic management region being deployed with at least two types of Internet of Things security devices; the local event detection module is used for generating a standardized event information message; the central area locking module is used for triggering the campus security center platform to highlight a target area on an electronic map according to the logic management area identifier, and calling real-time state information of all Internet of Things security equipment in the target area; the adjacent physical region retrieval module is used for generating a collaborative equipment list; and the equipment linkage response module is used for driving associated equipment of the target area and the adjacent physical area to execute linkage operation according to the event type. The problems that equipment linkage depends on manual triggering instructions, and key channels cannot be opened in time in emergency scenes such as fire disasters are solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart campus security management and relates to a smart campus security management system based on the Internet of Things. Background Art

[0002] Campus environments typically consist of multiple functional areas, such as teaching buildings, dormitories, and sports fields. Independently deployed security equipment in each area creates information silos. When an unusual event occurs, such as an intruder moving across zones or smoke spreading from a fire, surveillance data from a single area cannot support global risk assessment. Traditional manual inspections combined with fixed cameras struggle to capture dynamic threats in real time, and the direct upload of massive amounts of raw data to a central platform can overwhelm critical information.

[0003] Traditional solutions rely primarily on manual scheduling and single-point device response. Security personnel must continuously monitor the central screen, determine the event location based on experience, and manually switch between different screens. For cross-regional incidents, patrol personnel are verbally notified to proceed to the target location. Access control relies on preset timing strategies or manual on-site operation, and is unable to dynamically adjust channel status based on the type of event. This approach is highly reliant on personnel experience and is prone to response blind spots in low-staff scenarios such as nighttime and holidays.

[0004] In response to the above problems, the disadvantages of traditional methods are mainly manifested in that cross-regional collaboration requires multiple switching of system interfaces, equipment linkage relies on manual triggering commands, and key channels fail to be opened in time in emergency scenarios such as fire. Summary of the Invention

[0005] In order to solve the above problems, the present invention provides a smart campus security management system based on the Internet of Things.

[0006] The smart campus security management system based on the Internet of Things includes:

[0007] The logical management area division module is used to divide the campus physical space into multiple independent logical management areas, and each logical management area is deployed with at least two types of IoT security devices;

[0008] The local event detection module is used to obtain the original data stream uploaded by the IoT security devices in each logical management area through the local computing devices deployed in the area, judge the abnormal events of the original data stream based on the preset rule base, and generate a standardized event information message containing the event type, occurrence time, and unique identity code;

[0009] The central area locking module is used to send standardized event information messages to the campus security center platform, triggering the campus security center platform to highlight the target area on the electronic map according to the logical management area identification and retrieve the real-time status information of all IoT security devices in the target area;

[0010] The adjacent physical area retrieval module identifies adjacent physical areas that share a boundary line with the target area based on the boundary vertex coordinate set of the target area, retrieves information on security devices that can be collaboratively operated in the adjacent physical areas, and generates a collaborative device list;

[0011] The device linkage response module drives the associated devices in the target area and adjacent physical areas to perform linkage operations based on the event type.

[0012] A further solution of the present invention is to divide the physical space of the campus into multiple independent logical management areas, including the following steps:

[0013] Measure the actual distribution of buildings, roads and open spaces on campus to obtain spatial distribution data;

[0014] Based on spatial distribution data and preset functional block isolation properties, the continuous physical space is divided into several independent units. Each independent unit covers the complete functional area boundary, forming multiple independent logical management areas.

[0015] A further solution of the present invention is to deploy at least two types of IoT security devices in each logical management area, including the following steps:

[0016] Deploy at least two types of IoT security equipment, including image acquisition equipment, environmental sensing equipment, access control equipment, and active alarm equipment;

[0017] generating a unique identity code based on the unique area identifier of the logical management area and the device type code;

[0018] The unique identity code is written into the device firmware via the campus local area network and registered in the device registration database.

[0019] A further solution of the present invention is to judge abnormal events on the original data stream based on a preset rule base, including the following steps:

[0020] Parsing the raw data stream to obtain image frame sequences, sensor value changes, state switching signals or alarm signals;

[0021] Calling the logical conditions in the preset rule base to perform matching analysis on the image frame sequence, sensor value change, state switching signal or alarm signal;

[0022] If the trajectory of a moving object overlaps with the infrared intrusion signal within a preset time window, or if the smoke concentration monitoring value continuously exceeds the preset threshold, it is determined to be an abnormal event;

[0023] Among them, the rule base refers to a text configuration file preset for local computing devices, which is set based on the experience of security experts and industry standards.

[0024] A further solution of the present invention generates a standardized event information message including the event type, occurrence time, and unique identity code, comprising the following steps:

[0025] Extract the event type name and current system timestamp of the abnormal event;

[0026] Extracting a logical management area identification field from the unique identity code;

[0027] The event type name, the current system timestamp, and the logical management area identification field of the unique identity code are combined to generate a standardized event information message.

[0028] A further solution of the present invention triggers the campus security center platform to highlight the target area on the electronic map according to the logical management area identifier, and retrieves the real-time status information of all IoT security devices in the target area, including the following steps:

[0029] Parsing the logical management area identification field of the standardized event information message;

[0030] Based on the logical management area identification field and the preset campus electronic map data, locate the target area and highlight it;

[0031] Retrieve the unique identity codes of all associated IoT security devices within the target area and retrieve their real-time status parameters;

[0032] Integrate highlighted information and real-time status parameters to generate locked area status information.

[0033] A further embodiment of the present invention includes identifying an adjacent physical area that shares a boundary with the target area and retrieving information about security devices that can be cooperatively operated within the adjacent physical area, including the following steps:

[0034] The campus security center platform completes the locking operation of the area where the abnormal incident occurred;

[0035] Get the region boundary vertex coordinate set in the locked region status information;

[0036] Based on the coordinate set of the region boundary vertices and the preset spatial topological relationship, calculate other logical management areas that share the boundary line with the current region;

[0037] When it is detected that the coordinates of the endpoints of the boundary segments coincide, they are determined to be adjacent physical areas, and a list of adjacent physical area identifiers is generated.

[0038] A further solution of the present invention generates a collaborative device list, comprising the following steps:

[0039] Based on the list of neighboring physical area identifiers, query the device registration database;

[0040] Screen image acquisition devices that support pan / tilt control, access control devices that can be remotely locked, and security personnel terminals that are on standby;

[0041] Integrate the unique identification code, coordinate location and working mode of the device to generate a list of collaborative devices.

[0042] A further solution of the present invention drives the associated devices in the target area and the adjacent physical area to perform a linkage operation according to the event type, including the following steps:

[0043] If the event type is an abnormal intrusion event, a pan / tilt control command is sent to the image acquisition device in the area where the abnormal event occurred to focus on the incident point, and a path coverage command is sent to the image acquisition device in the adjacent physical area to adjust the viewing angle to cover the potential movement path;

[0044] If the event type is a fire initial event, channel commands are sent to the access control devices in the area where the abnormal event occurred and the adjacent physical areas to open and close key channels;

[0045] If the event type is a rescue incident, based on the real-time location information of the security personnel and the geometric center point of the area where the abnormal event occurred, the standby personnel with the smallest distance value will be dispatched to handle the situation, and a coordination instruction will be sent to the security personnel terminal in the adjacent physical area;

[0046] Among them, pan-tilt control instructions, path coverage instructions, channel instructions, and collaborative instructions are generated based on the collaborative device list, and collaborative response is achieved by combining event types and neighboring device capabilities.

[0047] In summary, the present invention has the following beneficial technical effects:

[0048] 1. By dividing the campus physical space into independent logical management areas and deploying various types of IoT security devices, combined with local computing devices, real-time rule matching is performed on raw data streams to effectively filter non-critical information. Based on the relationship between event type and spatial topology, the central platform automatically locates the incident area and accurately dispatches adjacent security resources to perform coordinated operations, significantly shortening the delay from event occurrence to initiation of response and significantly improving the accuracy of key security operations.

[0049] 2. By searching the device registration database to screen for collaborative image acquisition devices, access control devices, and security personnel terminals, a structured collaborative device list is generated. Based on the event type, cross-regional devices are dynamically driven to execute focused tracking, channel control, or personnel dispatch instructions, breaking through the limitations of traditional security systems' single-point response and forming a spatial blockade network covering the event diffusion path, greatly enhancing the prevention and control capabilities of mobile targets or chain risks.

[0050] 3. The division of independent logical management areas and the unique device identification coding system provide a modular deployment foundation for large-scale campus environments. Preliminary rule judgments executed by local computing devices effectively disperse the load on the central platform, ensuring system stability in high-concurrency scenarios. The structured design of standardized event information messages and collaborative device lists ensures that adding new areas or device types only requires expanding the mapping relationship and rule base, without refactoring the core processing logic. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. The drawings are used to provide a further understanding of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 It is a schematic diagram of the framework in the embodiment of the present application.

[0053] Figure 2 It is a schematic diagram of the process flow in the embodiment of this application. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0055] The following is combined with Figure 1-Figure 2 The preferred embodiments of the present invention are described in detail.

[0056] Refer to the attached Figure 1-Figure 2 As shown, the present invention proposes a smart campus security management system based on the Internet of Things, which includes the following modules:

[0057] The logical management area division module is used to divide the campus physical space into multiple independent logical management areas, and each logical management area is deployed with at least two types of IoT security devices;

[0058] The local event detection module is used to obtain the original data stream uploaded by the IoT security devices in each logical management area through the local computing devices deployed in the area, judge the abnormal events of the original data stream based on the preset rule base, and generate a standardized event information message containing the event type, occurrence time, and unique identity code;

[0059] The central area locking module is used to send standardized event information messages to the campus security center platform, triggering the campus security center platform to highlight the target area on the electronic map according to the logical management area identification and retrieve the real-time status information of all IoT security devices in the target area;

[0060] The adjacent physical area retrieval module identifies adjacent physical areas that share a boundary line with the target area based on the boundary vertex coordinate set of the target area, retrieves information on security devices that can be collaboratively operated in the adjacent physical areas, and generates a collaborative device list;

[0061] The device linkage response module drives the associated devices in the target area and adjacent physical areas to perform linkage operations based on the event type.

[0062] In one embodiment of the present invention, the physical space of a campus is divided into multiple independent logical management areas, and at least two types of IoT security devices are deployed in each logical management area, including the following steps:

[0063] The campus physical space is divided into multiple logical management areas. At least two types of IoT security devices are deployed in each logical management area. All IoT security devices register the unique identifier of the logical management area to which they belong. IoT security devices include image acquisition devices, environmental sensing devices, access control devices, and active alarm devices.

[0064] Specifically, when dividing the physical space of the campus into multiple logical management areas, the actual distribution of buildings, roads and open spaces on campus is first measured, and the continuous physical space is divided into several independent units based on the physical isolation properties of the functional blocks and the flow paths of personnel. Each independent unit covers the complete boundary of the functional area, and then each independent unit is deployed with no less than two types of IoT security equipment. The IoT security equipment includes image acquisition equipment for collecting visual information, environmental sensing equipment for sensing environmental anomalies, access control equipment for controlling access rights, and manually triggered active alarm equipment. After each independent unit is deployed, all IoT security devices are configured with the unique identity code of the independent unit to which they belong. The unique identity code is generated by combining the area location code and the device type code, and is written into the device firmware through the campus LAN.

[0065] Among them, independent logical management areas refer to independent units demarcated by physical walls, building structures, and virtual electronic fences. The boundaries of each independent unit ensure non-overlapping and cover the complete functional area boundaries, such as a single building floor or an enclosed green area.

[0066] Image acquisition devices refer to network cameras installed on ceilings or walls within an area. Environmental sensing devices refer to sensors that detect smoke concentration, sudden temperature changes, or abnormal vibrations. Access control devices refer to gates or doors with electronically controlled locks. Active alarm devices refer to emergency buttons installed in public areas.

[0067] The unique identity code is generated by combining the area location code and the device type code. It is set using the rule of "area location letter number + device type three-digit serial number, digital serial number ∈ [001,999]". The digital serial number is assigned sequentially from 001 to 999 to ensure that each device obtains a unique code. For example, the unique identity code of device No. 5 in area A is A005.

[0068] For example, a three-story teaching building is selected. Each floor of the three-story teaching building is divided into an independent logical management area, and the area location of each independent logical management area is numbered L1, L2, and L3 respectively. Two image acquisition devices are deployed on both sides of the corridor in the L1 area, an environmental sensing device is deployed in the stairwell, access control equipment is installed at the main entrance and exit, and active alarm equipment is deployed in the teacher's office. All IoT security devices are connected to the floor switch via network cables;

[0069] The alphabetical code for the area location is derived from the first letter of the area name (e.g., L for L1). The three-digit serial number for the device type is automatically generated by the backend management system according to the order in which the devices are registered. Use the configuration tool to register the image acquisition device on the east side of the corridor with code L101, the image acquisition device on the west side of the corridor with code L102, the environmental sensing device in the stairwell with code L103, the access control device at the main entrance with code L104, and the active alarm device in the teacher's office with code L105. After completing the coding, enter the device location description in the backend management system: code L101 corresponds to "2 meters from the stairwell in the east corridor of L1 floor."

[0070] In one embodiment of the present invention, abnormal event judgment is performed on the original data stream based on a preset rule base to generate a standardized event information message including the event type, occurrence time, and unique identity code, including the following steps:

[0071] Utilize local computing devices deployed in each logical management area to continuously receive the original data stream uploaded by IoT security devices in this area; local computing devices obtain image frame sequences, sensor value changes, status switching signals, and alarm signals of devices in this area in real time.

[0072] Based on the preset rules, the original data is preliminarily judged to identify whether it meets the conditions of abnormal events. Only when an abnormal event is identified, standardized event information containing "event type + occurrence time + unique identity code" is generated.

[0073] Specifically, the logical management area division module has already divided the area into independent logical management areas and completed the deployment of IoT security devices. Local computing devices installed in each logical management area continuously receive raw data streams uploaded by all IoT security devices in the area through wired or wireless communication protocols. The local computing devices analyze in real time the image frame sequences transmitted by image acquisition devices, sensor value changes reported by environmental sensing devices, status switching signals from access control devices, and alarm signals from active alarm devices.

[0074] Call the rule base pre-stored in the local computing device to perform logical judgment:

[0075] If the trajectory of a moving object detected in the image frame sequence overlaps with the infrared intrusion signal within the time window, it is determined to be an abnormal event. The time window refers to the time interval from the first detection of the moving object to the triggering of the infrared intrusion signal. If the smoke concentration monitoring value exceeds the threshold limit for three consecutive times, it is determined to be an initial fire event. The threshold limit refers to the critical smoke concentration value set according to the safety standard. Only when any type of abnormal event judgment condition is met, the local computing device will combine the event type name, the current system timestamp, and the logical management area identification field in the unique identity code to generate a standardized event information message, which will be transmitted to the security center platform through the campus internal network. The original data streams of other conditions that did not trigger abnormal events will be automatically overwritten after being cached locally.

[0076] A local computing device refers to an embedded computer deployed in an independent logical management area and capable of data parsing and logical operations. The logical management area identifier field is the unique identifier representing the area's location, such as "L1" in the unique identifier L103. A standardized event information message is a JSON-formatted data packet containing fixed fields, with standardized event information structured as "event type + occurrence time + unique identifier."

[0077] The rule base refers to a text configuration file preset for local computing devices. It is set based on the experience of security experts and industry standards. It verifies the validity of thresholds by analyzing historical events (such as replaying past campus monitoring data) and solidifies preset logical conditions (such as time window values, consecutive times of exceeding the standard, etc.). It supports manual iterative updates.

[0078] For example, taking the three-story teaching building in the verification example of the logical management area division module as an example, the local computing device in the L1 area continuously receives the image frame sequence of the image acquisition device with registration code L101 and the sensor value changes of the environmental sensing device with registration code L103. The image frame sequence analysis of registration code L101 found that there was a moving object on the east side of the corridor. At the same time, registration code L103 triggered the intrusion alarm of the active alarm device with registration code L105 within 0.5 seconds. The local computing device determined that the rule of "the trajectory of the moving object and the infrared intrusion signal overlap within a 2-second time window (set to 2 seconds)" was met, and a standardized event information message was generated: the event type is "abnormal intrusion", the timestamp is taken from the system clock accurate to milliseconds, and the unique identity code intercepts the "L1" field in the L103 device code. The standardized event information message is uploaded to the security center platform through the floor switch.

[0079] According to the critical smoke concentration value set by the safety standard, the threshold limit is set at 15% obs / m. If the smoke concentration monitoring value of the environmental sensing device with registration code L103 exceeds the threshold limit three times in a row, it is determined to be an initial fire incident.

[0080] In one embodiment of the present invention, triggering a campus security center platform to highlight a target area on an electronic map based on a logical management area identifier and retrieving real-time status information of all IoT security devices within the target area includes the following steps:

[0081] Standardized event information messages are sent to the campus security center platform, triggering the campus security center platform to perform area locking operations. According to the logical management area identification, the area is automatically located and highlighted on the electronic map, and the real-time status information of all associated security devices in the logical management area is automatically retrieved.

[0082] Specifically, the campus security center platform receives standardized event information messages from each independent logical management area via the campus internal network and immediately parses the logical management area identification field in the standardized event information message. It then calls pre-stored campus electronic map data and, based on the logical management area identification field, determines the mapping relationship between the area boundary coordinates and the campus electronic map data, automatically locating the target area. On the campus electronic map interface, the boundary line of the target area flashes red, and a semi-transparent block covering the area is simultaneously generated, achieving visual highlighting. Based on the logical management area identification field, the campus security center platform retrieves the unique identification codes of all associated IoT security devices and proactively initiates real-time status requests to these IoT security devices. The IoT security devices respond to the requests and return their current operating parameters. The campus security center platform displays real-time thumbnails of image acquisition devices, sensor value changes of environmental sensing devices, the on / off status of access control devices, and alarm signal triggering records of active alarm devices in a column-based display on the monitoring panel next to the highlighted area. This operation is completed within the polling interval after receiving the standardized event information message.

[0083] Campus electronic map data refers to a vector map file pre-imported into the platform, containing the coordinates of the boundary vertices of each independent logical management area. Translucent color blocks refer to the 20%-50% transparent red layer superimposed on the campus electronic map area. The mapping relationship refers to the correspondence between the independent logical management area identification fields and the campus electronic map area names. For example, the identification field "L1" corresponds to "1F Teaching Building East Area" on the campus electronic map. The polling interval refers to the maximum time from receiving a message to completing the interface refresh. The default setting is 1 second and is adjusted based on historical event data.

[0084] For example, taking the three-story teaching building in the logical management area division module verification example, the campus security center platform receives a standardized event information message: {Event type: "Abnormal intrusion", Timestamp: "2024-08-01 14:05:30.250", Area ID: "L1"}. After parsing, the logical management area identification field "L1" is extracted, and the mapping relationship is queried to confirm the corresponding "1F Teaching Building East District" in the campus electronic map data. The boundary line of the target area on the campus electronic map will turn red and flash, and a semi-transparent color block covering the area will be generated synchronously to achieve visual highlighting. Retrieve the unique identity code (L101, L102, L103, L104, L105) belonging to "L1" and actively initiate a real-time status request to these IoT security devices:

[0085] The local computing device parses in real time data such as the real-time picture thumbnail (640×480 pixels) transmitted by the image acquisition device with registration code L101, the sensor value changes of the environmental sensing device with registration code L103 (the fire has not yet occurred), and the status switching signal of the access control device with registration code L104 (door closed). The above operations are completed within the polling time interval (set to 1 second) after receiving the standardized event information message. The left side of the monitoring panel displays the real-time picture of the corridor of the image acquisition device with registration code L101, and the right side displays the status of each related IoT security device.

[0086] In one embodiment of the present invention, generating a collaborative device list includes the following steps:

[0087] Based on the spatial location relationship, at least one other independent logical management area adjacent to the area where the abnormal event occurred is automatically identified, and the information of security equipment that can be collaboratively operated in the adjacent physical area is retrieved and called.

[0088] Specifically, the campus security center platform completes the locking operation of the area where the abnormal event occurs, and automatically determines other independent logical management areas that share boundary lines with the current visually highlighted area based on the area boundary vertex coordinate set stored in the campus electronic map data.

[0089] Set the visual highlight area as A and the other independent logical management area as B. Calculate the vector direction of the boundary line segment between the two areas A and B to satisfy the following formula:

[0090]

[0091] Among them, Adjacent is whether the two areas are adjacent; Vertex A and Vertex B are the coordinates of the vertices of the area boundary, obtained from the campus electronic map data; Is "at least one exists"; Region A It is the area where the abnormal event occurred, and it is the area identification locked by the central area locking module; Region B Is to be determined other independent logic management area; ≡ represents the congruence symbol, that is (x A =x B ∧y A =y B ∧z A =z B ); coordinate comparison accuracy is controlled within the range of less than 0.01 meters.

[0092] Traverse the area where the abnormal event occurred and all boundary segments of other independent logical management areas to be judged. If it is found that two segments have at least one identical area boundary vertex coordinate, the boundary segment endpoints coincide and are determined to be adjacent physical areas. The campus security center platform traverses all other independent logical management areas that meet this condition and generates a list of adjacent physical area identifiers. Based on the adjacent physical area identifier list, the device registration database is retrieved to filter out the image acquisition devices that support pan-tilt control, access control devices that can be remotely locked, and security personnel terminal information in standby state in the adjacent physical area. The unique identity codes, real-time coordinate locations, and current working modes of these devices are integrated into a collaborative device list.

[0093] The regional boundary vertex coordinate set refers to the sequence of longitude and latitude coordinates of the boundary inflection points of each independent logical management area in the school's electronic map file. A shared boundary line refers to the overlap of boundary segments between two areas. The device registration database is a structured table that stores metadata for all IoT security devices. During system deployment, core attributes such as the device's unique identity code, region identifier, device type, installation coordinates, and physical capability parameters (such as pan / tilt steering range / lock control method) are entered through the backend management tool.

[0094] A "neighboring physical area" specifically refers to a spatial unit directly adjacent to the area where an abnormal event occurred. Endpoint coordinate overlap refers to two line segments sharing the same latitude and longitude coordinates. An image acquisition device supporting pan / tilt control refers to a pan / tilt camera that supports 355-degree horizontal and 90-degree vertical rotation. A remotely controlled access control device refers to an electronically controlled lock equipped with a network communication module. A standby security personnel terminal refers to an online heartbeat detection device worn by a security personnel.

[0095] The collaborative device list is in JSON array format and contains the following fields: {device code, device type, coordinates, working mode}.

[0096] For example, continuing with the L1 area (1F Teaching Building East Area) locked in the central area locking module verification example, based on the area boundary vertex coordinate set stored in the campus electronic map data, it is calculated that the west boundary line of the L1 area coincides with the endpoint of the east boundary line segment of the "1F Teaching Building West Area" (identification field L0) on the same floor, and L0 is determined to be an adjacent physical area; at the same time, the ceiling vertex of the L1 area coincides with the floor boundary point of the "2F Teaching Building East Area" (identification field L2) on the second floor, and L2 is determined to be an adjacent physical area.

[0097] After generating the adjacent physical area identification list ["L0", "L2"], the device registration database is searched: the image acquisition device L001 supporting pan-tilt control is found in the L0 area, and the controllable access control device L204 and the patrol security terminal L210 are found in the L2 area. The collaborative device list is output:

[0098] [{Device code "L001", device type "image acquisition", coordinates "(102.3, 55.7, 3.0)", working mode "standby"}, {Device code "L204", device type "access control", coordinates "(120.5, 60.1, 6.2)", working mode "locked"}, {Device code "L210", device type "personnel terminal", coordinates "(118.9, 62.3, 6.0)", working mode "online"}].

[0099] In one embodiment of the present invention, driving the associated devices of the target area and the adjacent physical area to perform a linkage operation according to the event type includes the following steps:

[0100] Based on the event type, the associated devices in the area where the abnormal event occurred and the adjacent physical areas are driven to perform linkage operations;

[0101] 1. If an abnormal event requires tracking the target: Control the image acquisition equipment in the area where the abnormal event occurred to focus on the incident point, and control the image acquisition equipment in the adjacent physical area to adjust the viewing angle to cover the potential movement path;

[0102] 2. If an abnormal event requires channel control: automatically open and close designated access control devices in the area where the abnormal event occurred and adjacent physical areas, and lock or open key channels;

[0103] 3. If an abnormal event requires personnel handling: Based on the real-time location information of the security personnel, dispatch security personnel who have a connected path to the area where the abnormal event occurred, and notify security personnel in adjacent physical areas to coordinate the response.

[0104] Specifically, the campus security center platform performs differentiated operations based on the event type field in the standardized event information message, targeting the area where the abnormal event occurred and the list of collaborative devices:

[0105] For abnormal intrusion events, a pan / tilt control command is sent to the image acquisition device in the area where the abnormal event occurred, so that its lens focuses on the coordinates of the incident point. A path coverage command is sent to the image acquisition device in the adjacent physical area. The potential movement direction is calculated based on the spatial topology relationship, and the image acquisition device's field of view is adjusted to cover path nodes such as corridors or stairwells to meet the following formula:

[0106]

[0107] Where θ represents the target horizontal rotation angle, which is used to control the gimbal steering. (x cam ,y cam ) represents the camera installation coordinates, which are obtained from the device registration database. (x target ,y target ) represents the coordinates of the incident point.

[0108] For initial fire incidents, channel instructions are sent to the access control devices in the area where the abnormal incident occurred and the adjacent physical areas to open all channel access control devices leading to safe exits and close isolation access control devices that may spread the fire.

[0109] For rescue incidents, calculate the straight-line distance between the geometric center of the abnormal event area and the terminal coordinates of the security personnel, dispatch the standby personnel with the smallest distance value to handle the situation, and at the same time, dispatch the security personnel terminal in the adjacent physical area and notify the security personnel in the adjacent physical area to move to the boundary of the abnormal event area, satisfying the following formula:

[0110]

[0111] Among them, S represents the minimum scheduling distance value. (x k ,y k , z k ) is the coordinate of the kth security personnel terminal, which is reported in real time via GPS. (x e ,y e , z e ) is the geometric center coordinate of the abnormal event area, which is calculated by the mean of the boundary vertex coordinates: (y e , z e Similarly). StandbySet represents the set of security personnel in the "standby" state. The security personnel terminal in the standby state refers to the heartbeat detection device worn by the security personnel and is online.

[0112] Among them, pan / tilt control instructions refer to commands that include the target pitch angle and horizontal rotation angle. Path coverage instructions refer to pan / tilt angle parameters generated based on the coordinates of path nodes in an electronic map. Spatial topology refers to the spatial connectivity characteristics of corridors connecting classrooms and stairways connecting floors. Channel instructions refer to the relay signals that control the opening or closing of access control locks. The geometric center point refers to the center position coordinates calculated from the coordinates of the vertices on the boundary of the area where the abnormal event occurred. Collaboration instructions refer to the vibration alarm and target position coordinates sent to the security personnel's terminal.

[0113] For example, for abnormal intrusion incidents in the L1 area (eastern area of ​​the 1F teaching building), a pan / tilt command (pitch angle -10°, horizontal angle 45°) is first sent to the image acquisition device with the registration code L101 in the area where the abnormal incident occurred to focus on the incident point at the east end of the corridor. The west stairwell is then calculated as the key path node, and a pan / tilt command (horizontal angle 280°) is sent to the image acquisition device with the registration code L001 in the adjacent physical area L0 to cover the stair entrance. The security terminal L210 in the L2 area is retrieved as being closest to the center point of the incident (straight-line distance 15.2 meters), and is dispatched to the east area of ​​the L1 floor; a coordination command is sent to the security terminal L007 in the L0 area to move to the junction of L1 and L0.

[0114] It should be noted that the formulas described above can translate physical quantities of different attributes into unitless standard values ​​or superimposable parameters of the same dimension through the principle of dimensional consistency and mathematical standardization (e.g., normalization, dimensionless parameter conversion, or unit system unification). This eliminates the interference of different dimensions on the operational logic, allowing the formulas to retain the distribution characteristics of the original data while maintaining mathematical rationality and adaptability to objective laws. The above are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention.

[0115] The modules can be implemented in whole or in part through software, hardware, or a combination thereof, supporting hardware embedded in or independent of a processor in a computer device, and also supporting software stored in a memory in a computer device, so that the processor can call and execute operations corresponding to the modules.

[0116] It should be noted that the human body information (including but not limited to human device information and personal information, etc.) and data (including but not limited to data used for analysis, stored data and displayed data, etc.) involved in the present invention are all information and data authorized by the human body or fully authorized by all parties. The collection, use and processing of relevant data require relevant legal standards.

[0117] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. The smart campus security management system based on the Internet of Things is characterized by: include: The logical management area division module is used to divide the campus physical space into multiple independent logical management areas, and each logical management area is deployed with at least two types of IoT security devices; The local event detection module is used to obtain the original data stream uploaded by the IoT security devices in each logical management area through the local computing devices deployed in the area, judge the abnormal events of the original data stream based on the preset rule base, and generate a standardized event information message containing the event type, occurrence time, and unique identity code; The central area locking module is used to send standardized event information messages to the campus security center platform, triggering the campus security center platform to highlight the target area on the electronic map according to the logical management area identification and retrieve the real-time status information of all IoT security devices in the target area; The adjacent physical area retrieval module identifies adjacent physical areas that share a boundary line with the target area based on the boundary vertex coordinate set of the target area, retrieves information on security devices that can be collaboratively operated in the adjacent physical areas, and generates a collaborative device list; The device linkage response module drives the associated devices in the target area and adjacent physical areas to perform linkage operations based on the event type.

2. The smart campus security management system based on the Internet of Things according to claim 1 is characterized in that: Dividing the campus physical space into multiple independent logical management areas includes the following steps: Measure the actual distribution of buildings, roads and open spaces on campus to obtain spatial distribution data; Based on spatial distribution data and preset functional block isolation properties, the continuous physical space is divided into several independent units. Each independent unit covers the complete functional area boundary, forming multiple independent logical management areas.

3. The smart campus security management system based on the Internet of Things according to claim 2 is characterized in that: Deploy at least two types of IoT security devices in each logical management area, including the following steps: Deploy at least two types of IoT security equipment, including image acquisition equipment, environmental sensing equipment, access control equipment, and active alarm equipment; generating a unique identity code based on the unique area identifier of the logical management area and the device type code; The unique identity code is written into the device firmware via the campus local area network and registered in the device registration database.

4. The smart campus security management system based on the Internet of Things according to claim 1 is characterized in that: Based on the preset rule base, the original data stream is judged for abnormal events, including the following steps: Parsing the raw data stream to obtain image frame sequences, sensor value changes, state switching signals or alarm signals; Calling the logical conditions in the preset rule base to perform matching analysis on the image frame sequence, sensor value change, state switching signal or alarm signal; If the trajectory of a moving object overlaps with the infrared intrusion signal within a preset time window, or if the smoke concentration monitoring value continuously exceeds the preset threshold, it is determined to be an abnormal event; Among them, the rule base refers to a text configuration file preset for local computing devices, which is set based on the experience of security experts and industry standards.

5. The smart campus security management system based on the Internet of Things according to claim 4 is characterized in that: Generate a standardized event information message containing the event type, occurrence time, and unique identification code, including the following steps: Extract the event type name and current system timestamp of the abnormal event; Extracting a logical management area identification field from the unique identity code; The event type name, the current system timestamp, and the logical management area identification field of the unique identity code are combined to generate a standardized event information message.

6. The smart campus security management system based on the Internet of Things according to claim 1 is characterized in that: Triggering the campus security center platform to highlight the target area on the electronic map based on the logical management area identifier and retrieve the real-time status information of all IoT security devices in the target area includes the following steps: Parsing the logical management area identification field of the standardized event information message; Based on the logical management area identification field and the preset campus electronic map data, locate the target area and highlight it; Retrieve the unique identity codes of all associated IoT security devices within the target area and retrieve their real-time status parameters; Integrate highlighted information and real-time status parameters to generate locked area status information.

7. The smart campus security management system based on the Internet of Things according to claim 6 is characterized in that: Identifying an adjacent physical area that shares a boundary line with a target area, and retrieving information about security devices that can be co-operated within the adjacent physical area, including the following steps: The campus security center platform completes the locking operation of the area where the abnormal incident occurred; Get the region boundary vertex coordinate set in the locked region status information; Based on the coordinate set of the region boundary vertices and the preset spatial topological relationship, calculate other logical management areas that share the boundary line with the current region; When it is detected that the coordinates of the endpoints of the boundary segments coincide, they are determined to be adjacent physical areas, and a list of adjacent physical area identifiers is generated.

8. The smart campus security management system based on the Internet of Things according to claim 7 is characterized in that: Generating a collaborative device list includes the following steps: Based on the list of neighboring physical area identifiers, query the device registration database; Screen image acquisition devices that support pan / tilt control, access control devices that can be remotely locked, and security personnel terminals that are on standby; Integrate the unique identification code, coordinate location and working mode of the device to generate a list of collaborative devices.

9. The smart campus security management system based on the Internet of Things according to claim 8 is characterized in that: Based on the event type, the associated devices in the target area and adjacent physical areas are driven to perform linkage operations, including the following steps: If the event type is an abnormal intrusion event, a pan / tilt control command is sent to the image acquisition device in the area where the abnormal event occurred to focus on the incident point, and a path coverage command is sent to the image acquisition device in the adjacent physical area to adjust the viewing angle to cover the potential movement path; If the event type is a fire initial event, channel commands are sent to the access control devices in the area where the abnormal event occurred and the adjacent physical areas to open and close key channels; If the event type is a rescue incident, based on the real-time location information of the security personnel and the geometric center point of the area where the abnormal event occurred, the standby personnel with the smallest distance value will be dispatched to handle the situation, and a coordination instruction will be sent to the security personnel terminal in the adjacent physical area; Among them, pan-tilt control instructions, path coverage instructions, channel instructions, and collaborative instructions are generated based on the collaborative device list, and collaborative response is achieved by combining event types and neighboring device capabilities.

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