Safety management system and method suitable for port complex environment

Abstract

The invention relates to the technical field of port safety management, and discloses a safety management system and method suitable for a port complex environment, and the system comprises a positioning collection module which employs UWB and RTK technologies to carry out the positioning of the dynamic positions of indoor and outdoor personnel; the spatial modeling module is used for constructing a three-dimensional model of the belt conveyor system based on laser point cloud scanning and a BIM technology, and marking equipment coordinates; the hierarchical management and control module is used for dividing an electronic fence area based on the three-dimensional model; a data fusion module; an intelligent early warning module; and a scheduling execution module. According to the method, the UWB is used for inhibiting steel structure signal attenuation to guarantee indoor continuous tracking, the RTK is used for achieving outdoor centimeter-level positioning, outputting three-dimensional coordinates and mapping the three-dimensional coordinates to a transfer tower floor, the three-dimensional coordinates serve as a core base to be fused into a space-time engine, an electronic fence is driven in real time to trigger dynamic equipment emergency stop control, and a digital human system is linked to automatically dispatch recent security officers to execute closed-loop protection. And linkage regulation and control of personnel and equipment resources are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of port safety management, and particularly relates to a safety management system and method suitable for a complex port environment. BACKGROUND

[0002] Due to the complex structure, large quantity, and large personnel mobility of port belt conveyor system equipment and facilities, and the serious signal shielding around the steel structure, operation safety management can ensure the safety and health of personnel operation, effectively reduce operation interruption and economic loss, improve the overall operation efficiency and compliance of the port, ensure the continuity and reliability of the supply chain, optimize resource utilization and reduce insurance costs through preventive measures, thereby strengthening the social responsibility image and sustainable development ability of the port industry, and creating a safer working environment for employees. However, the positioning accuracy and stability of traditional positioning technology cannot meet the positioning requirements of the complex port environment, and accurate positioning of personnel and safety of equipment are current industry problems.

[0003] In related technologies, GPS and other outdoor positioning technologies are suitable for planar positioning on roads and cannot position three-dimensional space and relative distance positioning of multiple targets. In addition, indoor Wi-Fi and Bluetooth precise positioning technologies are greatly interfered by signals and are difficult to position multi-dimensional targets, and cannot link position data with equipment status and personnel behavior in real time. SUMMARY

[0004] In order to make up for the above shortcomings, the present application provides a safety management system and method suitable for a complex port environment, aiming to improve the problems of being unable to realize continuous indoor and outdoor positioning, being unable to link position data with equipment status and personnel behavior in real time, leading to lagging behind in equipment risk control, and low efficiency of safety resource scheduling.

[0005] In a first aspect, the present application provides the following technical solution: a safety management system suitable for a complex port environment, comprising:

[0006] A positioning collection module uses UWB and RTK technologies to position the dynamic positions of personnel indoors and outdoors;

[0007] A space modeling module constructs a three-dimensional model of the belt conveyor system based on laser point cloud scanning and BIM technology, and labels the equipment coordinates;

[0008] A hierarchical control module divides the electronic fence area based on the three-dimensional model, sets a dynamic radius, and triggers a hierarchical response mechanism;

[0009] A data fusion module integrates positioning data, equipment monitoring data, and video data for multi-source time and space synchronous fusion;

[0010] An intelligent early warning module generates risk early warning through an LSTM behavior prediction model and a random forest fault prediction model;

[0011] The scheduling and execution module automatically matches security resources and executes equipment control commands through the digital human system.

[0012] Preferably, the positioning and acquisition module includes:

[0013] Outdoor positioning units are deployed using a cluster of RTK positioning base stations to cover the port area, achieving centimeter-level positioning accuracy through satellite signal reception.

[0014] Indoor positioning units deploy UWB anti-interference base stations on each floor of the transfer tower and in the conveyor belt corridor, penetrating the signal shielding of the steel structure;

[0015] The switching control unit automatically switches between indoor and outdoor positioning modes based on real-time signal strength detection.

[0016] Preferably, the hierarchical control module includes:

[0017] The point cloud acquisition unit acquires three-dimensional point cloud data of the belt conveyor system and the transfer tower through laser scanning equipment;

[0018] Model building unit, based on BIM technology, generates 3D models with centimeter-level precision;

[0019] The coordinate calibration unit marks the three-dimensional coordinates of the equipment in the port in the model.

[0020] Preferably, the data fusion module includes:

[0021] The positioning data access unit receives UWB and RTK positioning information in real time, generates three-dimensional coordinate data of personnel, and maps the coordinates to a three-dimensional model.

[0022] The equipment monitoring and access unit binds the temperature data from the thermal imaging sensor and the status data from the vibration sensor to the equipment coordinates in the three-dimensional model.

[0023] The video linkage unit automatically retrieves monitoring footage based on the spatial coordinates of the target area and extracts behavioral features through computer vision algorithms, including human posture analysis, abnormal behavior recognition, and dynamic target tracking.

[0024] The spatiotemporal synchronization engine establishes a unified spatiotemporal coordinate system, integrates multi-source data, and outputs correlated data.

[0025] Preferably, the spatiotemporal synchronization engine establishes a unified time reference through dual-mode timing of BeiDou and GPS, and uses a spatial coordinate transformation matrix to achieve multi-source data alignment: T world =K -1 P·depth, outputs spatiotemporal correlated data packets;

[0026] Where K is the camera calibration matrix, P is the pixel coordinates, and depth is the depth information.

[0027] Preferably, the intelligent early warning module includes:

[0028] Behavior prediction unit: Analyzes the dynamic trajectory of personnel based on an LSTM neural network model and calculates the probability of risk.

[0029] Where v is the movement speed of the personnel, s is the dwell time of the personnel, θ is the posture angle of the personnel, w1=0.2, w2=0.4, w3=0.4 are the weights of each parameter in the port scenario, and b is the bias term.

[0030] The fault prediction unit calculates the fault probability by fusing equipment status data using the random forest algorithm.

[0031] Where ΔT is the rate of temperature rise, and A v d is the vibration amplitude, k1, k2 and k3 are the influence weights of adjusting the temperature rise rate, vibration amplitude and personnel distance on the failure probability in the port belt conveyor scenario, and C is the decision boundary adjustment constant.

[0032] The early warning decision unit makes predictions based on behavioral risk probability values ​​and failure risk probability values:

[0033] When the probability value of behavioral risk is greater than 0.85 or the probability value of failure risk is greater than 0.85, a level 1 response command is generated, triggering an emergency stop operation of the equipment and the dispatch of the safety officer.

[0034] When the probability value of behavioral risk is greater than 0.7 or the probability value of fault risk is greater than 0.8, a level 2 response command is generated, triggering mobile terminal alarms and video surveillance push notifications.

[0035] Preferably, the scheduling execution module includes:

[0036] The resource matching unit, based on real-time location data, automatically matches the nearest safe resources through the digital human system.

[0037] Access control unit, remotely locks operating permissions for high-risk equipment and executes emergency stop commands.

[0038] The information dispatch unit automatically sends early warning information to safety management personnel and retrieves related data.

[0039] Secondly, the present invention provides the following technical solution: a safety management method applicable to complex port environments, the method comprising:

[0040] S1. Real-time dynamic location data of personnel is obtained through the fusion positioning technology of UWB and RTK;

[0041] S2. Construct a three-dimensional model of the belt conveyor system based on laser point cloud scanning and label the coordinates of key equipment;

[0042] S3. Set up a dynamic electronic fence based on the 3D model and establish a hierarchical response mechanism;

[0043] S4. Perform spatiotemporal correlation analysis by integrating positioning data, equipment monitoring data, and video data;

[0044] S5. Generate risk warnings using LSTM behavior prediction models and random forest fault prediction models;

[0045] S6. The digital human system automatically schedules security resources and executes equipment control commands.

[0046] Thirdly, the invention provides the following technical solution: a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the aforementioned safety management method applicable to complex port environments.

[0047] Fourthly, the present invention provides the following technical solution: a readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned safety management method applicable to complex port environments.

[0048] The present invention has the following beneficial effects:

[0049] 1. In this invention, UWB is used to suppress the signal attenuation of the steel structure to ensure continuous indoor tracking, RTK is used to achieve centimeter-level positioning outdoors, and the output three-dimensional coordinates are mapped to the floor of the transfer tower. As the core base, it is integrated into the spatiotemporal engine to drive the electronic fence in real time to trigger the dynamic equipment emergency stop control, and link the digital human system to automatically dispatch the nearest safety officer to perform closed-loop protection, so as to realize the linkage control of personnel and equipment resources.

[0050] 2. In this invention, a centimeter-level model is constructed based on laser point cloud and BIM to label the coordinates of the equipment. A dynamic electronic fence is set up to adaptively adjust according to the equipment status. When personnel are close to high-risk equipment, the equipment is stopped suddenly. When personnel are at medium distance, alarm linkage video is pushed to achieve active protection and timely warning of unsafe behavior of personnel and rapid response.

[0051] 3. In this invention, a time reference is established by using BeiDou and GPS dual-mode timing, and data is aligned by combining spatial coordinate transformation matrix to generate spatiotemporal correlation data that integrates location, status and behavior, thereby locating risk sources and supporting early warning decisions.

[0052] 4. In this invention, the dynamic trajectory characteristics of personnel are analyzed based on the LSTM model to predict behavioral risks, and the random forest algorithm is combined with the overall equipment operating status to predict fault trends. The intelligent hierarchical response mechanism is triggered by the output results of the dual models, so as to realize the fundamental transformation of port safety management from passive response to active defense and improve the safety of port operations. Attached Figure Description

[0053] Figure 1 This is an architecture diagram of a safety management system suitable for complex port environments proposed in this invention;

[0054] Figure 2 This is a flowchart of a safety management method applicable to complex port environments proposed in this invention. Detailed Implementation

[0055] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] Example 1

[0057] Reference Figure 1 In the first embodiment of the present invention, the present invention provides a safety management system suitable for complex port environments, comprising:

[0058] The positioning and acquisition module uses UWB and RTK technologies to locate the dynamic positions of people indoors and outdoors;

[0059] The spatial modeling module constructs a three-dimensional model of the belt conveyor system based on laser point cloud scanning and BIM technology, and annotates the equipment coordinates;

[0060] The hierarchical control module divides the electronic fence area based on a 3D model, sets the dynamic radius, and triggers a hierarchical response mechanism.

[0061] The data fusion module integrates positioning data, equipment monitoring data, and video data to perform multi-source spatiotemporal synchronous fusion.

[0062] The intelligent early warning module generates risk warnings through LSTM behavior prediction models and random forest fault prediction models;

[0063] The scheduling and execution module automatically matches security resources and executes equipment control commands through the digital human system.

[0064] Specifically, the positioning and acquisition module uses UWB technology to suppress signal attenuation in the steel structure, uses an RTK dual-frequency receiver to achieve outdoor positioning, and combines UWB time difference positioning technology to ensure accuracy in complex indoor areas. It synchronously outputs the three-dimensional spatial coordinates of personnel and maps them to the floor position of the transfer tower, providing a location benchmark for the hierarchical control of electronic fences, behavior trajectory analysis and risk positioning.

[0065] The spatial modeling module constructs a three-dimensional model of the belt conveyor system based on laser point cloud scanning and BIM technology, and accurately marks the equipment coordinates of rollers and drive motors. This achieves a dimensional breakthrough from the traditional two-dimensional plane to three-dimensional space, providing a spatial benchmark for the electronic fence setting and personnel behavior trajectory analysis of the hierarchical control module, and supporting the three-dimensional safety control of port equipment.

[0066] The hierarchical control module divides electronic fence areas based on a 3D model. It automatically adapts to changes in equipment operating status through dynamic radius settings and triggers a hierarchical response mechanism. When personnel approach areas with different risk levels, it automatically executes preset protective measures, avoiding the problem that fixed fences cannot adapt to dynamic working conditions and realizing safety control from passive monitoring to active protection.

[0067] The data fusion module establishes a unified spatiotemporal coordinate system through BeiDou and GPS dual-mode timing technology, realizing the time synchronization and spatial coordinate mapping of positioning data, equipment monitoring data and video data. It deeply integrates and correlates the three-dimensional position coordinates of personnel, equipment temperature and vibration status parameters and video image behavior characteristics under the same spatiotemporal reference, constructs a multi-dimensional risk feature vector, and outputs standardized spatiotemporal correlation data packets to the intelligent early warning module, providing data support for the location and trend prediction of risk events.

[0068] The intelligent early warning module analyzes the trajectory characteristics of personnel, such as movement speed, dwell time and posture angle, through the LSTM behavior prediction model. It combines the random forest fault prediction model with the parameters of equipment temperature rise rate, vibration amplitude and personnel-equipment distance to generate personnel behavior risk probability and equipment failure probability. Based on the output results of the dual models, a graded response mechanism is triggered to realize risk trend prediction and active protection.

[0069] The scheduling and execution module analyzes the location and level of risk events in real time through the digital human system, automatically matches the nearest safety resources, such as safety personnel ≤20 meters away from the accident point, and generates the optimal scheduling path. At the same time, it sends emergency stop lockout commands or speed reduction control commands to high-risk equipment through the industrial bus protocol, realizing a closed-loop response from risk warning to resource scheduling to equipment management.

[0070] The positioning and acquisition module includes:

[0071] Outdoor positioning units are deployed using a cluster of RTK positioning base stations to cover the port area, achieving centimeter-level positioning accuracy through satellite signal reception.

[0072] Indoor positioning units deploy UWB anti-interference base stations on each floor of the transfer tower and in the conveyor belt corridor, penetrating the signal shielding of the steel structure;

[0073] The switching control unit automatically switches between indoor and outdoor positioning modes based on real-time signal strength detection.

[0074] Specifically, the outdoor positioning unit covers the open area of ​​the port by deploying a cluster of RTK positioning base stations and uses satellite signal receiving technology to locate people in outdoor activity areas, providing a stable position reference for the entire system.

[0075] The indoor positioning unit deploys UWB anti-interference base stations on each floor of the transfer tower and in the conveyor belt corridor. Through ultra-wideband signals, it penetrates the shielded environment of the steel structure to ensure continuous and stable tracking of personnel positions in complex indoor spaces.

[0076] The switching control unit detects changes in GPS signal strength in real time and automatically and seamlessly switches between indoor and outdoor positioning modes to ensure the continuity of personnel positioning in the transition area between indoor and outdoor areas of the port.

[0077] The hierarchical management and control module includes:

[0078] The point cloud acquisition unit acquires three-dimensional point cloud data of the belt conveyor system and the transfer tower through laser scanning equipment;

[0079] Model building unit, based on BIM technology, generates 3D models with centimeter-level precision;

[0080] The coordinate calibration unit marks the three-dimensional coordinates of the equipment in the port in the model.

[0081] Specifically, the point cloud acquisition unit acquires three-dimensional point cloud data of the belt conveyor system and transfer tower through laser scanning equipment, accurately capturing the geometric structure and spatial features of the equipment and facilities, and providing the original data foundation for the construction of the three-dimensional model;

[0082] The model building unit uses BIM technology to integrate point cloud data to generate a three-dimensional model with centimeter-level precision, realizing the spatial digital reconstruction of port equipment and facilities and establishing a spatial reference system;

[0083] The coordinate calibration unit accurately marks the three-dimensional spatial coordinates of key equipment such as rollers and drive motors in the three-dimensional model, providing a spatial reference for the setting of electronic fences and risk positioning.

[0084] The data fusion module includes:

[0085] The positioning data access unit receives UWB and RTK positioning information in real time, generates three-dimensional coordinate data of personnel, and maps the coordinates to a three-dimensional model.

[0086] The equipment monitoring and access unit binds the temperature data from the thermal imaging sensor and the status data from the vibration sensor to the equipment coordinates in the three-dimensional model.

[0087] The video linkage unit automatically retrieves monitoring footage based on the spatial coordinates of the target area and extracts behavioral features through computer vision algorithms, including human posture analysis, abnormal behavior recognition, and dynamic target tracking.

[0088] The spatiotemporal synchronization engine establishes a unified spatiotemporal coordinate system, integrates multi-source data, and outputs correlated data.

[0089] Specifically, the positioning data access unit receives the three-dimensional coordinate data of personnel generated by UWB and RTK positioning information in real time, and maps the coordinates to the corresponding positions in the three-dimensional model to realize the dynamic visualization of personnel spatial position;

[0090] The equipment monitoring access unit collects equipment temperature data through thermal imaging sensors and obtains status data through vibration sensors, and binds the monitoring data to the spatial coordinates of the corresponding equipment in the three-dimensional model, thereby realizing the integrated association between the equipment's operating status and spatial location.

[0091] The video linkage unit automatically retrieves monitoring footage based on the spatial coordinates of the target area, and extracts behavioral features such as human posture analysis, abnormal behavior recognition, and dynamic target tracking in real time through computer vision algorithms, thereby realizing intelligent linkage analysis of video data and spatial location.

[0092] The spatiotemporal synchronization engine establishes a unified spatiotemporal coordinate system, integrates multi-source data such as positioning coordinates, device status, and video behavior characteristics, and generates spatiotemporally correlated data packets to provide a full-dimensional data foundation for risk warning.

[0093] The spatiotemporal synchronization engine establishes a unified time reference through dual-mode timing of BeiDou and GPS, and uses a spatial coordinate transformation matrix to achieve multi-source data alignment: T world =K -1 P·depth, outputs spatiotemporal correlated data packets;

[0094] Where K is the camera calibration matrix, P is the pixel coordinates, and depth is the depth information.

[0095] Specifically, a unified time reference is established through BeiDou / GPS dual-mode timing technology to achieve millisecond-level time synchronization of positioning data, equipment monitoring data, and video stream data, eliminating timestamp deviations of multi-source data and ensuring the temporal consistency of risk event analysis. Furthermore, a spatial coordinate transformation matrix is ​​used to map video pixel coordinates to a three-dimensional world coordinate system, achieving spatial alignment between video images and positioning data. At the same time, based on the spatiotemporal alignment results, multi-source data features are fused to generate standardized spatiotemporal correlated data packets, providing the intelligent early warning module with associated risk feature vectors of location, status, and behavior.

[0096] The intelligent early warning module includes:

[0097] The behavior prediction unit analyzes the dynamic trajectory of personnel based on an LSTM neural network model and calculates the risk probability.

[0098] Where v is the movement speed of the personnel, s is the dwell time of the personnel, θ is the posture angle of the personnel, w1=0.2, w2=0.4, w3=0.4 are the weights of each parameter in the port scenario, and b is the bias term.

[0099] The fault prediction unit calculates the fault probability by fusing equipment status data using the random forest algorithm.

[0100] Where ΔT is the rate of temperature rise, and A v d is the vibration amplitude, k1, k2 and k3 are the influence weights of adjusting the temperature rise rate, vibration amplitude and personnel distance on the failure probability in the port belt conveyor scenario, and C is the decision boundary adjustment constant.

[0101] The early warning decision unit makes predictions based on behavioral risk probability values ​​and failure risk probability values:

[0102] When the probability value of behavioral risk is greater than 0.85 or the probability value of failure risk is greater than 0.85, a level 1 response command is generated, triggering an emergency stop operation of the equipment and the dispatch of the safety officer.

[0103] When the probability value of behavioral risk is greater than 0.7 or the probability value of fault risk is greater than 0.8, a level 2 response command is generated, triggering mobile terminal alarms and video surveillance push notifications.

[0104] Specifically, behavior prediction unit

[0105] This unit analyzes the dynamic trajectory parameters of personnel based on the LSTM neural network model, and calculates the probability of behavioral risks by optimizing the weight parameter w and the bias term b in the port scenario, so as to predict abnormal behaviors such as personnel falling and being stranded, and support proactive safety protection.

[0106] The fault prediction unit integrates the equipment temperature rise rate ΔT and vibration amplitude A using a random forest algorithm. v Based on state parameters such as the distance d between personnel and equipment, the probability of equipment failure is calculated, enabling predictive judgment of failure trends of key equipment such as drive motors and rollers.

[0107] The early warning decision unit makes tiered decisions based on the probability of behavioral risk and the probability of fault risk. When the probability value is >0.85, a level 1 response is triggered, which involves emergency equipment shutdown and safety personnel dispatch. When the probability value is >0.7 / 0.8, a level 2 response is triggered, which involves sending video to the mobile terminal to provide an alarm relative to the risk location, thus forming a risk level adaptive response mechanism.

[0108] The scheduling and execution module includes:

[0109] The resource matching unit, based on real-time location data, automatically matches the nearest safe resources through the digital human system.

[0110] Access control unit, remotely locks operating permissions for high-risk equipment and executes emergency stop commands.

[0111] The information dispatch unit automatically sends early warning information to safety management personnel and retrieves related data.

[0112] Specifically, the resource matching unit uses real-time location data and a digital human system to automatically match the nearest security resources, achieving optimal spatial matching between risk events and response personnel, and ensuring that the nearest available security personnel can be quickly dispatched to the scene to handle emergencies.

[0113] The access control unit remotely locks the operating permissions of high-risk equipment and executes emergency stop commands. It directly intervenes in the equipment's operating status through industrial control protocols, cutting off the source of danger before the risk escalates and ensuring the safety of on-site personnel and equipment.

[0114] The information dispatch unit automatically sends structured early warning information to the mobile terminals of safety management personnel, and simultaneously retrieves related video surveillance and equipment status data to achieve real-time synchronous push of early warning information and on-site evidence.

[0115] Example 2:

[0116] Reference Figure 2 In a second embodiment of the present invention, the present invention provides a safety management method suitable for complex port environments, the method comprising:

[0117] S1. Real-time dynamic location data of personnel is obtained through the fusion positioning technology of UWB and RTK;

[0118] S2. Construct a three-dimensional model of the belt conveyor system based on laser point cloud scanning and label the coordinates of key equipment;

[0119] S3. Set up a dynamic electronic fence based on the 3D model and establish a hierarchical response mechanism;

[0120] S4. Perform spatiotemporal correlation analysis by integrating positioning data, equipment monitoring data, and video data;

[0121] S5. Generate risk warnings using LSTM behavior prediction models and random forest fault prediction models;

[0122] S6. The digital human system automatically schedules security resources and executes equipment control commands.

[0123] Specifically, S1 uses UWB indoor and RTK outdoor fusion positioning technology to obtain the three-dimensional coordinates of people in real time, realize continuous positioning indoors and outdoors, and provide a position reference for the system;

[0124] S2 constructs a 3D model of the belt conveyor system based on laser point cloud scanning and BIM technology, marking the spatial coordinates of key equipment such as rollers and drive motors, avoiding the problem that the planar model cannot locate the vertical space, and establishing a spatial benchmark for setting up electronic fences.

[0125] S3 divides risk areas in a 3D model, sets dynamic electronic fence radii, and establishes a graded response mechanism. For example, when the distance between people is less than 1 meter, it triggers an emergency stop of the equipment and an audible and visual alarm. When the distance is less than 3 meters, it activates mobile alarms and video linkage to achieve proactive protection against risk distances.

[0126] S4 integrates positioning coordinates, equipment temperature and vibration data, and video behavior features, and achieves alignment and spatial mapping through a spatiotemporal synchronization engine, thereby improving the accuracy of locating the location of hazardous events.

[0127] S5 analyzes personnel trajectory characteristics using an LSTM model and predicts equipment failure trends using a random forest algorithm. When the behavioral risk is greater than 0.85 or the failure risk is greater than 0.85, a level 1 response is initiated, and when the risk is greater than 0.7, a level 2 response is triggered, thus achieving proactive intervention before risks occur.

[0128] The S6 uses a digital human system to automatically match the nearest safety operator, and issues emergency stop commands for the equipment via the Modbus RTU protocol, while simultaneously pushing structured alarm information.

[0129] Example 3

[0130] In the third embodiment of the present invention, based on the same inventive concept, the present invention proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a safety management method applicable to a complex port environment as described in the above embodiments.

[0131] Example 4

[0132] In the fourth embodiment of the present invention, based on the same inventive concept, the present invention proposes a terminal, the terminal comprising: a processor and a memory; the processor and the memory communicate with each other; the memory is used to store instructions; the processor is used to execute the instructions in the memory to execute a safety management method applicable to complex port environments as described in the above embodiment.

[0133] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0134] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A safety management system suitable for complex port environments, characterized in that, include: The positioning and acquisition module uses UWB and RTK technologies to locate the dynamic positions of people indoors and outdoors; The spatial modeling module constructs a three-dimensional model of the belt conveyor system based on laser point cloud scanning and BIM technology, and annotates the equipment coordinates; The hierarchical control module divides the electronic fence area based on a 3D model, sets the dynamic radius, and triggers a hierarchical response mechanism. The data fusion module integrates positioning data, equipment monitoring data, and video data to perform multi-source spatiotemporal synchronous fusion. The intelligent early warning module generates risk warnings through LSTM behavior prediction models and random forest fault prediction models; The scheduling and execution module automatically matches security resources and executes equipment control commands through the digital human system.

2. The safety management system suitable for complex port environments according to claim 1, characterized in that, The positioning acquisition module includes: Outdoor positioning units are deployed using a cluster of RTK positioning base stations to cover the port area, achieving centimeter-level positioning accuracy through satellite signal reception. Indoor positioning units deploy UWB anti-interference base stations on each floor of the transfer tower and in the conveyor belt corridor, penetrating the signal shielding of the steel structure; The switching control unit automatically switches between indoor and outdoor positioning modes based on real-time signal strength detection.

3. A safety management system suitable for complex port environments according to claim 1, characterized in that, The hierarchical control module includes: The point cloud acquisition unit acquires three-dimensional point cloud data of the belt conveyor system and the transfer tower through laser scanning equipment; Model building unit, based on BIM technology, generates 3D models with centimeter-level precision; The coordinate calibration unit marks the three-dimensional coordinates of the equipment in the port in the model.

4. A safety management system suitable for complex port environments according to claim 1, characterized in that, The data fusion module includes: The positioning data access unit receives UWB and RTK positioning information in real time, generates three-dimensional coordinate data of personnel, and maps the coordinates to a three-dimensional model. The equipment monitoring and access unit binds the temperature data from the thermal imaging sensor and the status data from the vibration sensor to the equipment coordinates in the three-dimensional model. The video linkage unit automatically retrieves monitoring footage based on the spatial coordinates of the target area and extracts behavioral features through computer vision algorithms, including human posture analysis, abnormal behavior recognition, and dynamic target tracking. The spatiotemporal synchronization engine establishes a unified spatiotemporal coordinate system, integrates multi-source data, and outputs correlated data.

5. A safety management system suitable for complex port environments according to claim 4, characterized in that, The spatiotemporal synchronization engine establishes a unified time reference through dual-mode timing of BeiDou and GPS, and uses a spatial coordinate transformation matrix to achieve multi-source data alignment: T world =K -1 P·depth, outputs spatiotemporal correlated data packets; Where K is the camera calibration matrix, P is the pixel coordinates, and depth is the depth information.

6. A safety management system suitable for complex port environments according to claim 1, characterized in that, The intelligent early warning module includes: The behavior prediction unit analyzes the dynamic trajectory of personnel based on an LSTM neural network model and calculates the risk probability. Where v is the movement speed of the personnel, s is the dwell time of the personnel, θ is the posture angle of the personnel, w1=0.2, w2=0.4, w3=0.4 are the weights of each parameter in the port scenario, and b is the bias term. The fault prediction unit calculates the fault probability by fusing equipment status data using the random forest algorithm. Where ΔT is the rate of temperature rise, A v d is the vibration amplitude, k1, k2 and k3 are the influence weights of adjusting the temperature rise rate, vibration amplitude and personnel distance on the failure probability in the port belt conveyor scenario, and C is the decision boundary adjustment constant. The early warning decision unit makes predictions based on behavioral risk probability values ​​and failure risk probability values: When the probability value of behavioral risk is greater than 0.85 or the probability value of failure risk is greater than 0.85, a level 1 response command is generated, triggering an emergency stop operation of the equipment and the dispatch of the safety officer. When the probability value of behavioral risk is greater than 0.7 or the probability value of fault risk is greater than 0.8, a level 2 response command is generated, triggering mobile terminal alarms and video surveillance push notifications.

7. A safety management system suitable for complex port environments according to claim 1, characterized in that, The scheduling execution module includes: The resource matching unit, based on real-time location data, automatically matches the nearest safe resources through the digital human system. Access control unit, remotely locks operating permissions for high-risk equipment and executes emergency stop commands. The information dispatch unit automatically sends early warning information to safety management personnel and retrieves related data.

8. A safety management method suitable for complex port environments, characterized in that, The method for a safety management system suitable for complex port environments as described in any one of claims 1-7 includes: S1. Real-time dynamic location data of personnel is obtained through the fusion positioning technology of UWB and RTK; S2. Construct a three-dimensional model of the belt conveyor system based on laser point cloud scanning and label the coordinates of key equipment; S3. Set up a dynamic electronic fence based on the 3D model and establish a hierarchical response mechanism; S4. Perform spatiotemporal correlation analysis by integrating positioning data, equipment monitoring data, and video data; S5. Generate risk warnings using LSTM behavior prediction models and random forest fault prediction models; S6. The digital human system automatically schedules security resources and executes equipment control commands.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a safety management method applicable to complex port environments as described in claim 8.

10. A readable storage medium, characterized in that, The readable storage medium stores a computer program, which, when executed by a processor, implements the safety management method for complex port environments as described in claim 8.

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