A Real-Time Visualization System and Method for Multiple Port Areas

Abstract

This invention discloses a real-time visualization system and method for multiple port areas, relating to the field of data visualization. The system includes a real-time port area data acquisition and access module, a port area scheduling data visualization module, a loading and unloading machinery and equipment operation status visualization module, an AIS data access visualization module for vessels not yet arriving at the port, a multi-indicator layer visualization control module, and a multi-menu data visualization information center. It aims to connect with video surveillance equipment, weather forecast data, vessel scheduling data, and equipment control systems deployed in various port areas through standardized interfaces. AIS data enables real-time acquisition, unified aggregation, and preprocessing of multi-source data in the port area. It flexibly overlays multiple business-themed layers, such as the distribution of port facilities and pipelines, to provide a real-time and accurate data foundation for upper-level visualization applications, achieving one-stop port operation situation awareness.

Description

Technical Field

[0001] This invention relates to the field of data visualization, specifically a real-time visualization system and method for multiple port areas. Background Technology

[0002] With the continuous growth of port business volume and the advancement of smart port construction, port managers have put forward higher requirements for real-time monitoring, efficient scheduling and scientific decision-making of production operations. Existing port management technologies suffer from problems such as information silos, low visualization, difficulties in multi-port area collaboration, insufficient data real-time performance, lack of customized analysis tools, and weak intelligent decision support capabilities. Port business systems operate independently, with inconsistent data formats and interface standards, hindering effective data aggregation and sharing. Managers struggle to grasp the real-time production and operational dynamics of each port area from a holistic perspective. Cross-port collaborative scheduling lacks unified data support, preventing managers from quickly mapping data to actual locations on-site, resulting in low decision-making efficiency and slow response times. Furthermore, most existing systems are developed for single business areas, failing to integrate heterogeneous data from different port areas, hindering unified monitoring, scheduling, and resource optimization across port areas. The system architecture also lacks openness and scalability. This application aims to connect with video surveillance equipment, weather forecast data, ship scheduling data, and equipment control systems deployed in various port areas through standardized interfaces. AIS data enables real-time collection, unified aggregation, and preprocessing of multi-source data in the port area. It flexibly overlays multiple business thematic layers, such as the distribution of port facilities and pipelines, to provide a real-time and accurate data foundation for upper-level visualization applications, thereby achieving one-stop port operation situation awareness. Summary of the Invention

[0003] The purpose of this invention is to provide a real-time visualization system and method for multiple port areas to solve the problems in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A real-time visualization system for multiple port areas includes a real-time port area data acquisition and access module, a port area scheduling data visualization module, a loading and unloading machinery and equipment operation status visualization module, an AIS data access and visualization module for vessels that have not yet arrived at the port, a multi-indicator layer visualization control module, and a multi-menu data visualization information center. The real-time port area full-area data acquisition and access module connects to video surveillance equipment and weather forecasting systems deployed in various port areas through standardized interfaces to collect real-time video data and meteorological data. The port area's full-area dispatch data visualization module collects ship dispatch data, production data, and ship identification data, and visualizes core data on ship dynamics, yard inventory, and berth throughput schedule on a map. The visual module for the operation status of loading and unloading machinery and equipment collects operation line management data, equipment management data, and equipment information monitoring data to achieve real-time visual monitoring of the perception information of belt conveyor lines and large machinery throughout the entire process. The AIS data access visualization module for vessels that have not yet arrived at the port is based on both vessel identification data and vessel scheduling data. It monitors vessels in the anchorage area outside the port area and updates their positions in real time, enabling data collection and information query for vessels that have not yet arrived at the port. The multi-indicator layer visualization control module constructs a multi-indicator layer management interface. The multi-indicator layer includes the configuration of multiple types of facility positioning, port area personnel information positioning, and distributed pipeline positioning, and constructs a port area multi-layer visualization panel. The multi-menu data visualization information center summarizes and integrates the data collected from each module to build a port production visualization panel for comprehensive information display.

[0005] Further configuration: The real-time port area full-area data acquisition and access module includes a multi-key location camera acquisition submodule and a real-time weather access submodule. The multi-key location camera acquisition submodule includes a GPS locator, a multi-point camera information deployment unit, and a port area map association unit. The multi-point camera information deployment unit accesses a list of camera devices deployed in different key locations in the port area, extracts the unique identifier, name, latitude and longitude coordinates of the installation location, device status, and real-time video stream address of several cameras, and constructs a multi-camera monitoring form. The port area map association unit includes several GPS locators, which locate the point coordinates of cameras in different key locations, spatially match the point coordinates of several cameras with the port area map, generate camera point layer data, and match different camera point layers with the real-time video stream acquisition address of the camera. The real-time weather access submodule accesses external weather forecast data according to different weather configuration parameters. At the same time, it obtains the port area's geographical location identifier and the weather forecast data update time for marking. Through the multi-menu data visualization information center, it presets fixed time intervals and accesses external weather forecast data according to the preset time intervals to build a real-time weather storage database.

[0006] Further configuration: The port area-wide dispatch data visualization module includes a ship visualization sub-module, a yard visualization sub-module, and a berth throughput progress analysis sub-module. The ship visualization sub-module includes a ship dispatch data association unit and a ship status timed polling unit. The ship dispatch data association unit obtains real-time data on ships currently in port and constructs a ship dispatch list. The ship dispatch list includes ship body data and ship loading data. The ship body data includes the name, voyage, length, beam, current berth code, berthing time, and planned departure time of each ship in port. The ship loading data includes the hold number, cargo type, overall ship operation progress, completed workload, and remaining workload of each ship. The timed polling unit sends information update requests to the ship dispatch data association unit at preset fixed time intervals through the multi-menu data visualization information center, and updates the current ship data in port through the ship dispatch data association unit. The yard visualization submodule includes a yard and cargo stack data acquisition unit and a yard information window construction unit. The yard and cargo stack data acquisition unit pre-locates the location coordinates of different yards in the port area using GPS locators and acquires the basic data of each yard in the port area in real time. The basic data includes yard code, yard name, maximum storage capacity of the yard, and current storage capacity. At the same time, it collects the data of cargo stacks within each yard, including cargo stack number, cargo stack 3D coordinates, associated cargo name, and cargo owner name, and constructs a yard data list for the port area. The yard information window construction unit acquires the maximum storage capacity and real-time storage capacity of each yard within the yard data list for the port area, calculates the storage capacity fill ratio data of each yard, and constructs a real-time storage capacity information window for the yard. When the storage capacity fill ratio exceeds a set threshold, it sends an early warning information to the multi-menu data visualization information center.

[0007] Further configuration: The berth throughput progress analysis submodule includes a production data acquisition unit and a yard data acquisition unit. The production data acquisition unit acquires production operation data of each berth in the port area in real time according to preset time intervals. The production operation data includes berth code, vessel name, operation start time, operation end time, loaded / unloaded volume, planned load / unloaded volume, and operation duration. It constructs a list of vessel throughput data for each berth in the port area, calculates the loading efficiency of vessels at each berth in the port area, and collects the historical loading efficiency of each vessel at each berth in real time. It connects to the historical data source according to the vessel code in the current port area. The historical data source includes the daily loading efficiency records of each vessel over the past week, month, quarter, and last year. It interfaces with the historical data source according to each vessel number. For the access data source for different historical periods, a certain vessel in port is preset. The loading efficiency record for the past week is The loading efficiency record for the past month was The loading efficiency record for the past quarter was The record for loading efficiency over the past full year was The average loading efficiency of vessels currently in port over the past week is calculated as follows: The average loading efficiency over the past month was The average loading efficiency in the past quarter was The average loading efficiency over the past year was Screen the minimum loading efficiency of vessels currently at the port berth for each historical period, and set the minimum loading efficiency for each historical period as [value missing]. ,Right now Set the vessels currently in port berths. The real-time loading efficiency is ,like Determine the vessels currently in port. If the loading efficiency is lower than the lowest value in the historical period, an early warning signal is sent to the multi-menu data visualization information center. The early warning signal includes the ship number and its port area, the name of the ship currently in operation, the real-time loading efficiency value, and the early warning timestamp. The storage data acquisition unit collects historical storage data of each storage yard in the port area in real time, and collects the daily, weekly and monthly change rates of storage volume in the storage yards in real time, and constructs real-time data packets of storage volume for each storage yard in the port area.

[0008] Further settings: The visualization module for the operating status of loading and unloading machinery and equipment includes a belt conveyor visualization sub-module, a multi-type machinery visualization sub-module, and an equipment perception information visualization sub-module; The belt conveyor operation line visualization submodule includes a spatial coordinate data acquisition unit and a real-time status data acquisition unit. The spatial coordinate data acquisition unit acquires the spatial coordinate data of the belt conveyor operation line and tippler within the port area. For multi-segment belt conveyors, it extracts the start and end coordinates of each belt conveyor operation line, establishes the topological relationship between the belt conveyor operation line and the tippler, and collects the start and end coordinates of each belt conveyor operation line, as well as the tippler number, equipment name, equipment model, and rated power it serves, and constructs a belt conveyor operation line storage data list. The real-time status data acquisition unit monitors the real-time operating status of each belt conveyor and the tippler it serves. It reads the operating status data of the belt conveyor and the corresponding tippler at a preset fixed acquisition frequency. The real-time operating status data of the belt conveyor includes the start / stop status, running direction, running speed, and load current. The real-time operating status data of the tippler includes the start / stop status, tipping angle, and number of operation cycles. The monitored operating status data is assigned a collection timestamp for data caching. The multi-type machinery visualization submodule includes an equipment data integration and acquisition unit and a detailed information window construction unit. The equipment data integration and acquisition unit acquires basic information of several large-scale machinery and equipment in the port area, forms a list of machinery and equipment in the port area, and sends it to the system backend for verification. After verification, the unit collects the verified and modified list of machinery and equipment in the port area, and collects information data of the list of machinery and equipment in the port area in sequence. The information data includes equipment number, equipment name, equipment type, equipment model, rated parameters, port area, and work area. The unit collects real-time location data and real-time operation status data of several machinery and equipment in the list of machinery and equipment in the port area. The unit obtains real-time coordinate data of different machinery and equipment through GPS locators at a preset acquisition frequency, assigns real-time acquisition timestamps, and connects to the equipment control system to obtain the operation status of machinery and equipment in the list of machinery and equipment in the port area in real time. The operation status includes start / stop status, current operation mode, and current operation parameters. The detailed information window construction unit matches the real-time location data and real-time operation status data of each piece of machinery and equipment according to the list of machinery and equipment in the port area, and constructs a multi-machinery detailed information window and a historical trajectory data database. The historical trajectory data database is used to store the data collected by the machinery and equipment, which is arranged in ascending order of time and generates a trajectory point sequence for easy querying. The Equipment Perception Information Visualization Submodule is used to summarize the stored data list of the belt conveyor line and the detailed information window of multiple mechanical equipment, build a data perception model for each piece of equipment, and combine the information data of each piece of equipment to construct a data visualization layer.

[0009] Further configuration: The AIS data access visualization module for vessels not yet arriving includes a sub-module for collecting location data of vessels not yet arriving and a sub-module for visualizing information of vessels at anchorage. The sub-module for collecting location data of vessels not yet arriving connects to the AIS data interface and vessel scheduling data to obtain real-time data on vessels reporting to port within the port area. It pre-collects and verifies basic information of vessels reporting to port. The basic information includes vessel body information and reporting information. The vessel body information includes vessel name, IMO number, call sign, vessel type, length, and beam. The reporting information includes the planned berthing port area, planned berthing berth, estimated arrival time, cargo type, planned loading / unloading volume, and cargo owner information. The basic information of the vessels reporting to port is sent to the system backend for verification. After verification, the system obtains real-time dynamic information of the vessels reporting to port according to the set update interval. The dynamic information includes the vessel's current draft, current location latitude and longitude, heading, speed, and reporting status, and constructs a dynamic information data package for each vessel reporting to port. The anchorage vessel information visualization submodule pre-obtains the spatial range of the pre-defined anchorage sea area in the port area, calibrates the boundary spatial coordinates of the spatial range to form a polygonal coordinate geofence, and simultaneously connects to the AIS data interface and vessel scheduling data to obtain pre-marked vessels within the anchorage sea area of ​​the port area. It extracts the position coordinates of the pre-marked vessels and determines whether the position coordinates of the pre-marked vessels are within the polygonal coordinate geofence of any anchorage sea area. If the position is within the polygonal coordinate geofence of any anchorage sea area, the pre-marked vessels are marked as anchorage vessels, generating a list of anchorage vessels in the port area. The list includes basic vessel information, position information, port reporting information, and anchorage affiliation information. It traverses several anchorage vessels within the port area and constructs an anchorage vessel summary window.

[0010] Further settings: The multi-indicator layer visualization control module includes a port area facility visualization sub-module, a personnel positioning visualization sub-module, and a port area pipeline distribution visualization sub-module. The port area facility visualization sub-module acquires facility data for the port area, collecting the center point latitude and longitude coordinates and basic information data of each facility. The basic information data includes facility number, facility name, facility type, facility status, building area, construction date, maintenance cycle, department, person in charge, contact information, and remarks. The center point latitude and longitude coordinates of each facility in the port area are matched with the basic information data. If there are facilities with missing center point latitude and longitude coordinates, they are sent to the backend administrator for manual annotation. After that, a multi-facility maintenance management information list is constructed. According to the location of different facilities within the multi-facility maintenance management information list, different blocks in the port area are pre-divided. Different facilities are divided into different blocks in the port area according to their location. Several multi-point cameras within the set area of ​​each facility are associated with the facilities within the multi-facility maintenance management information list, and video data within the facility area is collected in real time and uploaded. The personnel positioning visualization submodule includes a real-time personnel trajectory generation unit and a facility anomaly triggering unit. The real-time personnel trajectory generation unit uses a GPS locator to locate the latitude and longitude coordinates of port area workers, determines the different blocks of the port area to which the workers belong based on the workers' latitude and longitude coordinates, marks the blocks to which the workers belong, extracts the blocks to which each worker works, continuously records the location coordinates of workers at different time points, generates the historical movement trajectory of each worker, and constructs a personnel location summary window. The facility anomaly triggering unit pre-sets different thresholds for anomalies of facilities and machinery in the background of the multi-index layer visualization control module. It compares the facility area data and the machinery data in real time with the anomaly thresholds. When there is abnormal data in the facilities or machinery, it triggers the real-time coordinates of the workers in the personnel location summary window and the association process of the abnormal machinery and facilities. It extracts the port area block to which the abnormal facilities and machinery belong, collects the coordinates of several workers in the block in real time, uses the center point coordinates of the abnormal machinery and facilities in the block as the anomaly reference coordinates, compares the coordinates of several workers in the block with the anomaly reference coordinates, analyzes the shortest distance range between the workers in the port area block and the anomaly reference coordinates, and pushes the workers within the short distance range to carry out emergency anomaly handling. The port area pipeline distribution visualization submodule collects basic information, spatial location, and maintenance records of pipelines. The basic information includes: pipeline number, pipeline name, pipeline type, material, pipe diameter, length, design pressure, construction date, design service life, burial depth, maintenance unit, person in charge, and contact information. It constructs a pipeline distribution label list and, based on the spatial location of different pipelines in the port area, constructs a pipeline distribution map. Each pipeline in the pipeline distribution map is associated with the corresponding pipeline distribution label list data and uploaded to the multi-menu data visualization information center for data backup.

[0011] Further settings: The facility anomaly triggering unit is configured to detect an anomaly in a specific port area block where the faulty facility or machinery is located, and to define the specific worker involved. Coordinates are The anomaly reference coordinates of the port area block are: Calculation workers The straight-line distance between the plane and the abnormal reference coordinates is calculated using the formula: In the above formula, Indicates the workers The semi-versus of the angular distance between the reference coordinates and the anomaly. For the workers The difference in latitude between the coordinates and the abnormal reference coordinates, i.e. , For the workers The difference in latitude between the coordinates and the abnormal reference coordinates, i.e. , Indicates personnel working on the sphere The central angle subtended by the great circle arc between the reference coordinates and the abnormal reference coordinates. The average radius of the Earth For the workers The planar straight-line distances between the abnormal reference coordinates and the abnormal facilities and machinery are summarized. The straight-line distances between a worker and the abnormal facility or machinery within the port area block to which the abnormal facility or machinery belongs are then identified. The shortest straight-line distance is then selected and set as the minimum straight-line distance. The backend administrator presets distance expansion ratio thresholds under different abnormal conditions. The straight-line range of the screening distance from the abnormal reference coordinate point is less than or equal to The system identifies the coordinates of the workers, marks the identified workers as key personnel, and sends emergency anomaly handling signals and abnormal reference coordinates of facilities and machinery to these key personnel.

[0012] A real-time visualization method for multiple port areas: S1: Use the real-time port area full-area data acquisition and access module to connect with video surveillance equipment and weather forecasting systems deployed in various port areas through standardized interfaces to collect real-time video data and weather data; S2: Use the port area full-area scheduling data visualization module to collect ship scheduling data, production data and ship identification data, and visualize the core data of ship dynamics, yard inventory and berth throughput scheduling on the map; S3: Utilize the visual module for the operation status of loading and unloading machinery and equipment to collect operation line management data, equipment management data, and equipment information monitoring data, thereby achieving real-time visual monitoring of the perception information of belt conveyor lines and large machinery throughout the entire process of equipment perception information. S4: Utilize the AIS data of vessels that have not yet arrived at the port to access the visualization module. Simultaneously, based on vessel identification data and vessel scheduling data, monitor vessels in the anchorage area outside the port area and update their positions in real time according to the AIS data, thereby realizing the data collection and information query of vessels that have not yet arrived at the port. S5: Utilize the multi-indicator layer visualization control module to build a multi-indicator layer management interface. The multi-indicator layer includes configuring the location of multiple types of facilities, port area personnel information location, and distributed pipeline location, and constructs a port area multi-layer visualization panel. S6: Utilize the multi-menu data visualization information center to summarize and integrate the data collected from each module, construct a port production visualization panel, and display comprehensive information.

[0013] Compared with the prior art, the beneficial effects of the present invention are: The aim is to collect core scheduling data in advance and in real time, such as ship location and operation progress, cargo stack distribution and storage utilization rate in the yard, and berth loading efficiency and throughput, so as to provide intuitive and dynamic decision support for production scheduling. Secondly, real-time monitoring of conveyor belt operation lines, large machinery, and equipment throughout the entire process is used to collect equipment status data for differentiated analysis, thereby improving the real-time nature and visualization of equipment management. Then, it acquires AIS location data and ship dispatch reporting data of ships that have not yet arrived in port in real time, collects detailed information on ships, summarizes ships at anchorage, and performs statistics by window according to the expected arrival time, providing data support for the pre-allocation of berth resources; at the same time, it flexibly overlays multiple business thematic layers such as the distribution of port facilities and pipelines to provide a real-time and accurate data foundation for upper-level visualization applications, realizes one-stop port operation situation awareness, and realizes dynamic visualization monitoring and intelligent management of the port. Attached Figure Description

[0014] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0015] Figure 1 This is a schematic diagram of the overall structure of a real-time visualization system for multiple port areas according to the present invention; Figure 2 This is a schematic diagram of the structure of a real-time visualization system for multiple port areas according to the present invention. Figure 1 ; Figure 3 This is a schematic diagram of the structure of a real-time visualization system for multiple port areas according to the present invention. Figure 2 ; Figure 4 This is a schematic diagram of the structure of a real-time visualization system for multiple port areas according to the present invention. Figure 3 ; Figure 5 This is a schematic diagram of the structure of a real-time visualization system for multiple port areas according to the present invention. Figure 4 ; Figure 6 This is a schematic diagram of the structure of a real-time visualization system for multiple port areas according to the present invention. Figure 5 ; Figure 7 This is a schematic diagram illustrating the specific steps of a real-time visualization method for multiple port areas according to the present invention. Detailed Implementation

[0016] The technical solutions of 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.

[0017] according to Figures 1-6As shown, a real-time visualization system for multiple port areas is provided. The system includes a real-time port area data acquisition and access module, a port area scheduling data visualization module, a loading and unloading machinery and equipment operation status visualization module, an AIS data access and visualization module for ships that have not yet arrived at the port, a multi-indicator layer visualization control module, and a multi-menu data visualization information center. Among them, the real-time port area full-area data acquisition and access module, the port area full-area dispatch data visualization module, the loading and unloading machinery and equipment operation status visualization module, the AIS data access visualization module for ships that have not yet arrived at the port, and the multi-index layer visualization control module are all wirelessly connected to the multi-menu data visualization information center.

[0018] The real-time port area full-area data acquisition and access module connects to video surveillance equipment and weather forecasting systems deployed in various port areas through standardized interfaces to collect real-time video data and meteorological data. like Figure 2 As shown, it needs to be specifically explained that the real-time port area full-area data acquisition and access module includes a multi-key location camera acquisition submodule and a real-time weather access submodule. The multi-key location camera acquisition submodule includes a GPS locator, a multi-point camera information deployment unit, and a port area map association unit. The multi-point camera information deployment unit accesses a list of camera devices deployed in different key locations in the port area. Key locations include, but are not limited to, the port area yard, berths, port area machinery area, port area facilities area, and port area berthing area. It extracts the unique identifier, name, latitude and longitude coordinates of the installation location, equipment status, and real-time video stream address of several cameras to construct a multi-camera monitoring form. The port area map association unit includes several GPS locators. It locates the point coordinates of cameras in different key locations using several GPS locators, performs spatial matching of the point coordinates of several cameras with the port area map, generates camera point layer data, and matches different camera point layers with the real-time video stream acquisition address of the camera. The real-time weather access submodule accesses external weather forecast data according to different weather configuration parameters. At the same time, it obtains the port area's geographical location identifier and the weather forecast data update time for marking. Through the multi-menu data visualization information center, it presets fixed time intervals and accesses external weather forecast data according to the preset time intervals to build a real-time weather storage database.

[0019] The port area's full-area dispatch data visualization module collects ship dispatch data, production data, and ship identification data, and visualizes core data on ship dynamics, yard inventory, and berth throughput schedule on a map. like Figure 3As shown, further explanation is needed. The port area full-area dispatch data visualization module includes a ship visualization sub-module, a yard visualization sub-module, and a berth throughput progress analysis sub-module. The ship visualization sub-module includes a ship dispatch data association unit and a ship status timed polling unit. The ship dispatch data association unit obtains the current ship data in the port area in real time and constructs a ship dispatch list. The ship dispatch list includes ship body data and ship loading data. The ship body data includes the name, voyage number, length, beam, current berth code, berthing time, and planned departure time of each ship in port. The ship loading data includes the hold number, cargo type, overall ship operation progress, completed workload, and remaining workload of each ship. The timed polling unit sends information update requests to the ship dispatch data association unit at preset fixed time intervals through the multi-menu data visualization information center, and updates the current ship data in the port area through the ship dispatch data association unit. The yard visualization submodule includes a yard and cargo stack data acquisition unit and a yard information window construction unit. The yard and cargo stack data acquisition unit pre-locates the location coordinates of different yards in the port area using GPS locators and acquires the basic data of each yard in the port area in real time. The basic data includes yard code, yard name, maximum storage capacity of the yard, and current storage capacity. At the same time, it collects the data of cargo stacks within each yard, including cargo stack number, cargo stack 3D coordinates, associated cargo name, and cargo owner name, and constructs a yard data list for the port area. The yard information window construction unit acquires the maximum storage capacity and real-time storage capacity of each yard within the yard data list for the port area, calculates the storage capacity fill ratio data of each yard, and constructs a real-time storage capacity information window for the yard. When the storage capacity fill ratio exceeds a set threshold, it sends an early warning information to the multi-menu data visualization information center.

[0020] It should be specifically noted that the berth throughput progress analysis submodule includes a production data acquisition unit and a yard data acquisition unit. The production data acquisition unit acquires production operation data of each berth in the port area in real time according to a preset time interval. The production operation data includes berth code, vessel name, operation start time, operation end time, loaded / unloaded volume, planned load / unloaded volume, and operation duration. It constructs a list of vessel throughput data for each berth in the port area, calculates the loading efficiency of vessels at each berth, and collects the historical loading efficiency of each vessel at each berth in real time. It connects to the historical data source according to the vessel code in the current port area. The historical data source includes the daily loading efficiency records of each vessel over the past week, month, quarter, and last year. It interfaces with the historical data source according to each vessel number. For the access data source for different historical periods, a certain vessel in port is pre-set. The loading efficiency record for the past week is The loading efficiency record for the past month was The loading efficiency record for the past quarter was The record for loading efficiency over the past full year was The average loading efficiency of vessels currently in port over the past week is calculated as follows: The average loading efficiency over the past month was The average loading efficiency in the past quarter was The average loading efficiency over the past year was Screen the minimum loading efficiency of vessels currently at the port berth for each historical period, and set the minimum loading efficiency for each historical period as [value missing]. ,Right now Set the vessels currently in port berths. The real-time loading efficiency is ,like Determine the vessels currently in port. If the loading efficiency is lower than the lowest value in the historical period, an early warning signal is sent to the multi-menu data visualization information center. The early warning signal includes the ship number and its port area, the name of the ship currently in operation, the real-time loading efficiency value, and the early warning timestamp. The storage data acquisition unit collects historical storage data of each storage yard in the port area in real time, and collects the daily, weekly and monthly change rates of storage volume in the storage yards in real time, and constructs real-time data packets of storage volume for each storage yard in the port area.

[0021] The visual module for the operation status of loading and unloading machinery and equipment collects operation line management data, equipment management data, and equipment information monitoring data to achieve real-time visual monitoring of the perception information of belt conveyor lines and large machinery throughout the entire process. like Figure 4 As shown, it needs further explanation that the visualization module for the operation status of loading and unloading machinery and equipment includes a belt conveyor operation line visualization sub-module, a multi-type machinery visualization sub-module, and an equipment perception information visualization sub-module. The belt conveyor operation line visualization submodule includes a spatial coordinate data acquisition unit and a real-time status data acquisition unit. The spatial coordinate data acquisition unit acquires the spatial coordinate data of the belt conveyor operation line and tippler within the port area. For multi-segment belt conveyors, it extracts the start and end coordinates of each belt conveyor operation line, establishes the topological relationship between the belt conveyor operation line and the tippler, and collects the start and end coordinates of each belt conveyor operation line, as well as the tippler number, equipment name, equipment model, and rated power it serves, and constructs a belt conveyor operation line storage data list. The real-time status data acquisition unit monitors the real-time operating status of each belt conveyor and the tippler it serves. It reads the operating status data of the belt conveyor and the corresponding tippler at a preset fixed acquisition frequency. The real-time operating status data of the belt conveyor includes the start / stop status, running direction, running speed, and load current. The real-time operating status data of the tippler includes the start / stop status, tipping angle, and number of operation cycles. The monitored operating status data is assigned a collection timestamp for data caching. The multi-type machinery visualization submodule includes an equipment data integration and acquisition unit and a detailed information window construction unit. The equipment data integration and acquisition unit acquires basic information of several large-scale machinery and equipment in the port area, forms a list of machinery and equipment in the port area, and sends it to the system backend for verification. After verification, the unit collects the verified and modified list of machinery and equipment in the port area, and collects information data of the list of machinery and equipment in the port area in sequence. The information data includes equipment number, equipment name, equipment type, equipment model, rated parameters, port area, and work area. The unit collects real-time location data and real-time operation status data of several machinery and equipment in the list of machinery and equipment in the port area. The unit obtains real-time coordinate data of different machinery and equipment through GPS locators at a preset acquisition frequency, assigns real-time acquisition timestamps, and connects to the equipment control system to obtain the operation status of machinery and equipment in the list of machinery and equipment in the port area in real time. The operation status includes start / stop status, current operation mode, and current operation parameters. The detailed information window construction unit matches the real-time location data and real-time operation status data of each piece of machinery and equipment according to the list of machinery and equipment in the port area, and constructs a multi-machinery detailed information window and a historical trajectory data database. The historical trajectory data database is used to store the data collected by the machinery and equipment, which is arranged in ascending order of time and generates a trajectory point sequence for easy querying. The Equipment Perception Information Visualization Submodule is used to summarize the stored data list of the belt conveyor line and the detailed information window of multiple mechanical equipment, build a data perception model for each piece of equipment, and combine the information data of each piece of equipment to construct a data visualization layer.

[0022] The AIS data access visualization module for vessels that have not yet arrived at the port is based on both vessel identification data and vessel scheduling data. It monitors vessels in the anchorage area outside the port area and updates their positions in real time, enabling data collection and information query for vessels that have not yet arrived at the port. like Figure 5As shown, it should be further explained that the AIS data access visualization module for vessels that have not yet arrived at the port includes a sub-module for collecting location data of vessels that have not yet arrived at the port and a sub-module for visualizing information of vessels at anchorage. The sub-module for collecting location data of vessels that have not yet arrived at the port connects to the AIS data interface and vessel scheduling data to obtain real-time data on vessels reporting to the port. It collects basic information of the reporting vessels in advance for verification. The basic information includes the vessel's body information and the reporting information. The vessel's body information includes the vessel name, IMO number, call sign, vessel type, length, and beam. The reporting information includes the planned berthing port area, planned berthing berth, estimated arrival time, cargo type, planned loading / unloading volume, and cargo owner information. The basic information of the reporting vessels is sent to the system backend for verification. After verification, the system obtains real-time dynamic information of the reporting vessels at set update intervals. The dynamic information includes the vessel's current draft, current location latitude and longitude, heading, speed, and reporting status, and constructs a dynamic information data package for each reporting vessel. The anchorage vessel information visualization submodule pre-obtains the spatial range of the pre-defined anchorage sea area in the port area, calibrates the boundary spatial coordinates of the spatial range to form a polygonal coordinate geofence, and simultaneously connects to the AIS data interface and vessel scheduling data to obtain pre-marked vessels within the anchorage sea area of ​​the port area. It extracts the position coordinates of the pre-marked vessels and determines whether the position coordinates of the pre-marked vessels are within the polygonal coordinate geofence of any anchorage sea area. If the position is within the polygonal coordinate geofence of any anchorage sea area, the pre-marked vessels are marked as anchorage vessels, generating a list of anchorage vessels in the port area. The list includes basic vessel information, position information, port reporting information, and anchorage affiliation information. It traverses several anchorage vessels within the port area and constructs an anchorage vessel summary window.

[0023] The multi-indicator layer visualization control module constructs a multi-indicator layer management interface. The multi-indicator layer includes the configuration of multiple types of facility positioning, port area personnel information positioning, and distributed pipeline positioning, and constructs a port area multi-layer visualization panel. like Figure 6As shown, further explanation is needed. The multi-indicator layer visualization control module includes a port area facility visualization sub-module, a personnel positioning visualization sub-module, and a port area pipeline distribution visualization sub-module. The port area facility visualization sub-module acquires facility data for the port area, collecting the center point latitude and longitude coordinates and basic information data of each facility. The basic information data includes facility number, facility name, facility type, facility status, building area, construction date, maintenance cycle, department, person in charge, contact information, and remarks. The center point latitude and longitude coordinates of each facility in the port area are matched with the basic information data. If there are facilities with missing center point latitude and longitude coordinates, they are sent to the backend administrator for manual annotation. After that, a multi-facility maintenance management information list is constructed. Based on the location of different facilities within the multi-facility maintenance management information list, different blocks in the port area are pre-divided. Different facilities are divided into different blocks in the port area according to their location. Several multi-point cameras within the set area of ​​each facility are associated with the facilities within the multi-facility maintenance management information list, and video data within the facility area is collected in real time and uploaded. The personnel positioning visualization submodule includes a real-time personnel trajectory generation unit and a facility anomaly triggering unit. The real-time personnel trajectory generation unit uses a GPS locator to locate the latitude and longitude coordinates of port area workers, determines the different blocks of the port area to which the workers belong based on the workers' latitude and longitude coordinates, marks the blocks to which the workers belong, extracts the blocks to which each worker works, continuously records the location coordinates of workers at different time points, generates the historical movement trajectory of each worker, and constructs a personnel location summary window. The facility anomaly triggering unit pre-sets different thresholds for anomalies of facilities and machinery in the background of the multi-index layer visualization control module. It compares the facility area data and the machinery data in real time with the anomaly thresholds. When there is abnormal data in the facilities or machinery, it triggers the real-time coordinates of the workers in the personnel location summary window and the association process of the abnormal machinery and facilities. It extracts the port area block to which the abnormal facilities and machinery belong, collects the coordinates of several workers in the block in real time, uses the center point coordinates of the abnormal machinery and facilities in the block as the anomaly reference coordinates, compares the coordinates of several workers in the block with the anomaly reference coordinates, analyzes the shortest distance range between the workers in the port area block and the anomaly reference coordinates, and pushes the workers within the short distance range to carry out emergency anomaly handling. The port area pipeline distribution visualization submodule collects basic information, spatial location, and maintenance records of pipelines. The basic information includes: pipeline number, pipeline name, pipeline type, material, pipe diameter, length, design pressure, construction date, design service life, burial depth, maintenance unit, person in charge, and contact information. It constructs a pipeline distribution label list and, based on the spatial location of different pipelines in the port area, constructs a pipeline distribution map. Each pipeline in the pipeline distribution map is associated with the corresponding pipeline distribution label list data and uploaded to the multi-menu data visualization information center for data backup.

[0024] Further details are needed regarding the facility anomaly triggering unit, which is set to detect abnormal facilities and machinery belonging to a specific worker in the port area. Coordinates are The anomaly reference coordinates of the port area block are: Calculation workers The straight-line distance between the plane and the abnormal reference coordinates is calculated using the formula: In the above formula, Indicates the workers The semi-versus of the angular distance between the reference coordinates and the anomaly. For the workers The difference in latitude between the coordinates and the abnormal reference coordinates, i.e. , For the workers The difference in latitude between the coordinates and the abnormal reference coordinates, i.e. , Indicates personnel working on the sphere The central angle subtended by the great circle arc between the reference coordinates and the abnormal reference coordinates. The average radius of the Earth For the workers The planar straight-line distances between the abnormal reference coordinates and the abnormal facilities and machinery are summarized. The straight-line distances between a worker and the abnormal facility or machinery within the port area block to which the abnormal facility or machinery belongs are then identified. The shortest straight-line distance is then selected and set as the minimum straight-line distance. The backend administrator presets distance expansion ratio thresholds under different abnormal conditions. The straight-line range of the screening distance from the abnormal reference coordinate point is less than or equal to The system identifies the coordinates of the workers, marks the identified workers as key personnel, and sends emergency anomaly handling signals and abnormal reference coordinates of facilities and machinery to these key personnel.

[0025] The multi-menu data visualization information center summarizes and integrates the data collected from each module to build a port production visualization panel for comprehensive information display.

[0026] Example 2, as Figure 7 As shown, a real-time visualization method for multiple port areas is proposed: S1: Use the real-time port area full-area data acquisition and access module to connect with video surveillance equipment and weather forecasting systems deployed in various port areas through standardized interfaces to collect real-time video data and weather data; S2: Use the port area full-area scheduling data visualization module to collect ship scheduling data, production data and ship identification data, and visualize the core data of ship dynamics, yard inventory and berth throughput scheduling on the map; S3: Utilize the visual module for the operation status of loading and unloading machinery and equipment to collect operation line management data, equipment management data, and equipment information monitoring data, thereby achieving real-time visual monitoring of the perception information of belt conveyor lines and large machinery throughout the entire process of equipment perception information. S4: Utilize the AIS data of vessels that have not yet arrived at the port to access the visualization module. Simultaneously, based on vessel identification data and vessel scheduling data, monitor vessels in the anchorage area outside the port area and update their positions in real time according to the AIS data, thereby realizing the data collection and information query of vessels that have not yet arrived at the port. S5: Utilize the multi-indicator layer visualization control module to build a multi-indicator layer management interface. The multi-indicator layer includes configuring the location of multiple types of facilities, port area personnel information location, and distributed pipeline location, and constructs a port area multi-layer visualization panel. S6: Utilize the multi-menu data visualization information center to summarize and integrate the data collected from each module, construct a port production visualization panel, and display comprehensive information.

[0027] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A multi-port oriented global real-time visualization system, characterized by: The system includes a real-time port area full-area data acquisition and access module, a port area full-area scheduling data visualization module, a loading and unloading machinery and equipment operation status visualization module, an AIS data access and visualization module for vessels that have not yet arrived at the port, a multi-indicator layer visualization control module, and a multi-menu data visualization information center. The real-time port area full-area data acquisition and access module connects to video surveillance equipment and weather forecasting systems deployed in various port areas through standardized interfaces to collect real-time video data and meteorological data. The port area's full-area dispatch data visualization module collects ship dispatch data, production data, and ship identification data, and visualizes core data on ship dynamics, yard inventory, and berth throughput schedule on a map. The visual module for the operation status of loading and unloading machinery and equipment collects operation line management data, equipment management data, and equipment information monitoring data to achieve real-time visual monitoring of the perception information of belt conveyor lines and large machinery throughout the entire process. The AIS data access visualization module for vessels that have not yet arrived at the port is based on both vessel identification data and vessel scheduling data. It monitors vessels in the anchorage area outside the port area and updates their positions in real time, enabling data collection and information query for vessels that have not yet arrived at the port. The multi-indicator layer visualization control module constructs a multi-indicator layer management interface. The multi-indicator layer includes the configuration of multiple types of facility positioning, port area personnel information positioning, and distributed pipeline positioning, and constructs a port area multi-layer visualization panel. The multi-menu data visualization information center summarizes and integrates the data collected from each module to build a port production visualization panel for comprehensive information display.

2. A multi-port oriented global real-time visualization system according to claim 1, characterized in that The real-time port area full-domain data acquisition and access module includes a multi-key location camera acquisition submodule and a real-time weather access submodule. The multi-key location camera acquisition submodule includes a GPS locator, a multi-point camera information deployment unit, and a port area map association unit. The multi-point camera information deployment unit accesses a list of camera devices deployed at different key locations in the port area, extracts the unique identifier, name, latitude and longitude coordinates of the installation location, device status, and real-time video stream address of several cameras, and constructs a multi-camera monitoring form. The port area map association unit includes several GPS locators, which locate the point coordinates of cameras at different key locations, spatially match the point coordinates of several cameras with the port area map, generate camera point layer data, and match different camera point layers with the real-time video stream acquisition address of the camera. The real-time weather access submodule accesses external weather forecast data according to different weather configuration parameters. At the same time, it obtains the port area's geographical location identifier and the weather forecast data update time for marking. Through the multi-menu data visualization information center, it presets fixed time intervals and accesses external weather forecast data according to the preset time intervals to build a real-time weather storage database.

3. A multi-port oriented global real-time visualization system according to claim 1, characterized in that The port area-wide dispatch data visualization module includes a ship visualization submodule, a yard visualization submodule, and a berth throughput progress analysis submodule. The ship visualization submodule includes a ship dispatch data association unit and a ship status timed polling unit. The ship dispatch data association unit obtains real-time data on ships currently in port and constructs a ship dispatch list. The ship dispatch list includes ship body data and ship loading data. The ship body data includes the name, voyage, length, beam, current berth code, berthing time, and planned departure time of each ship in port. The ship loading data includes the hold number, cargo type, overall ship operation progress, completed workload, and remaining workload of each ship. The timed polling unit sends information update requests to the ship dispatch data association unit at preset fixed time intervals through the multi-menu data visualization information center, and updates the current ship data in port through the ship dispatch data association unit. The yard visualization submodule includes a yard and cargo stack data acquisition unit and a yard information window construction unit. The yard and cargo stack data acquisition unit pre-locates the location coordinates of different yards in the port area using GPS locators and acquires the basic data of each yard in the port area in real time. The basic data includes yard code, yard name, maximum storage capacity of the yard, and current storage capacity. At the same time, it collects the data of cargo stacks within each yard, including cargo stack number, cargo stack 3D coordinates, associated cargo name, and cargo owner name, and constructs a yard data list for the port area. The yard information window construction unit acquires the maximum storage capacity and real-time storage capacity of each yard within the yard data list for the port area, calculates the storage capacity fill ratio data of each yard, and constructs a real-time storage capacity information window for the yard. When the storage capacity fill ratio exceeds a set threshold, it sends an early warning information to the multi-menu data visualization information center.

4. A real-time visualization system for multiple port areas according to claim 3, characterized in that... The berth throughput progress analysis submodule includes a production data acquisition unit and a site data acquisition unit. The production data acquisition unit acquires production operation data of each berth in the port area in real time at preset time intervals. The production operation data includes berth code, vessel name, operation start time, operation end time, loaded / unloaded volume, planned loading / unloaded volume, and operation duration. It constructs a list of vessel throughput data for each berth in the port area, calculates the loading efficiency of vessels at each berth, and collects the historical loading efficiency of each vessel at each berth in real time. It connects to the historical data source according to the vessel code in the current port area. The historical data source includes the daily loading efficiency records of each vessel over the past week, month, quarter, and last year. It interfaces with the historical data source according to each vessel number. For the access data source for different historical periods, a certain vessel in port is preset. The loading efficiency record for the past week is The loading efficiency record for the past month was The loading efficiency record for the past quarter was The record for loading efficiency over the past full year was The average loading efficiency of vessels currently in port over the past week is calculated as follows: The average loading efficiency over the past month was The average loading efficiency in the past quarter was The average loading efficiency over the past year was Screen the minimum loading efficiency of vessels currently at the port berth for each historical period, and set the minimum loading efficiency for each historical period as [value missing]. ,Right now Set the vessels currently in port berths. The real-time loading efficiency is ,like Determine the vessels currently in port. If the loading efficiency is lower than the lowest value in the historical period, an early warning signal is sent to the multi-menu data visualization information center. The early warning signal includes the ship number and its port area, the name of the ship currently in operation, the real-time loading efficiency value, and the early warning timestamp. The storage data acquisition unit collects historical storage data of each storage yard in the port area in real time, and collects the daily, weekly and monthly change rates of storage volume in the storage yards in real time, and constructs real-time data packets of storage volume for each storage yard in the port area.

5. A real-time visualization system for multiple port areas according to claim 1, characterized in that... The visualization module for the operation status of loading and unloading machinery and equipment includes a belt conveyor visualization submodule, a multi-type machinery visualization submodule, and an equipment perception information visualization submodule. The belt conveyor operation line visualization submodule includes a spatial coordinate data acquisition unit and a real-time status data acquisition unit. The spatial coordinate data acquisition unit acquires the spatial coordinate data of the belt conveyor operation line and tippler within the port area. For multi-segment belt conveyors, it extracts the start and end coordinates of each belt conveyor operation line, establishes the topological relationship between the belt conveyor operation line and the tippler, and collects the start and end coordinates of each belt conveyor operation line, as well as the tippler number, equipment name, equipment model, and rated power it serves, and constructs a belt conveyor operation line storage data list. The real-time status data acquisition unit monitors the real-time operating status of each belt conveyor and the tippler it serves. It reads the operating status data of the belt conveyor and the corresponding tippler at a preset fixed acquisition frequency. The real-time operating status data of the belt conveyor includes the start / stop status, running direction, running speed, and load current. The real-time operating status data of the tippler includes the start / stop status, tipping angle, and number of operation cycles. The monitored operating status data is assigned a collection timestamp for data caching. The multi-type machinery visualization submodule includes an equipment data integration and acquisition unit and a detailed information window construction unit. The equipment data integration and acquisition unit acquires basic information of several large-scale machinery and equipment in the port area, forms a list of machinery and equipment in the port area, and sends it to the system backend for verification. After verification, the unit collects the verified and modified list of machinery and equipment in the port area, and collects information data of the list of machinery and equipment in the port area in sequence. The information data includes equipment number, equipment name, equipment type, equipment model, rated parameters, port area, and work area. The unit collects real-time location data and real-time operation status data of several machinery and equipment in the list of machinery and equipment in the port area. The unit obtains real-time coordinate data of different machinery and equipment through GPS locators at a preset acquisition frequency, assigns real-time acquisition timestamps, and connects to the equipment control system to obtain the operation status of machinery and equipment in the list of machinery and equipment in the port area in real time. The operation status includes start / stop status, current operation mode, and current operation parameters. The detailed information window construction unit matches the real-time location data and real-time operation status data of each piece of machinery and equipment according to the list of machinery and equipment in the port area, and constructs a multi-machinery detailed information window and a historical trajectory data database. The historical trajectory data database is used to store the data collected by the machinery and equipment, which is arranged in ascending order of time and generates a trajectory point sequence for easy querying. The Equipment Perception Information Visualization Submodule is used to summarize the stored data list of the belt conveyor line and the detailed information window of multiple mechanical equipment, build a data perception model for each piece of equipment, and combine the information data of each piece of equipment to construct a data visualization layer.

6. A real-time visualization system for multiple port areas according to claim 1, characterized in that... The AIS data access visualization module for vessels not yet arriving at port includes a sub-module for collecting location data of vessels not yet arriving at port and a sub-module for visualizing information of vessels at anchorage. The sub-module for collecting location data of vessels not yet arriving at port connects to the AIS data interface and vessel scheduling data to obtain real-time data on vessels reporting to port within the port area. It pre-collects and verifies basic information of vessels reporting to port. The basic information includes vessel body information and reporting information. The vessel body information includes vessel name, IMO number, call sign, vessel type, length, and beam. The reporting information includes the planned berthing port area, planned berthing berth, estimated arrival time, cargo type, planned loading / unloading volume, and cargo owner information. The basic information of the vessels reporting to port is sent to the system backend for verification. After verification, the system obtains real-time dynamic information of the vessels reporting to port according to the set update interval. The dynamic information includes the vessel's current draft, current location latitude and longitude, heading, speed, and reporting status, and constructs a dynamic information data package for each vessel reporting to port. The anchorage vessel information visualization submodule pre-obtains the spatial range of the pre-defined anchorage sea area in the port area, calibrates the boundary spatial coordinates of the spatial range to form a polygonal coordinate geofence, and simultaneously connects to the AIS data interface and vessel scheduling data to obtain pre-marked vessels within the anchorage sea area of ​​the port area. It extracts the position coordinates of the pre-marked vessels and determines whether the position coordinates of the pre-marked vessels are within the polygonal coordinate geofence of any anchorage sea area. If the position is within the polygonal coordinate geofence of any anchorage sea area, the pre-marked vessels are marked as anchorage vessels, generating a list of anchorage vessels in the port area. The list includes basic vessel information, position information, port reporting information, and anchorage affiliation information. It traverses several anchorage vessels within the port area and constructs an anchorage vessel summary window.

7. A real-time visualization system for multiple port areas according to claim 1, characterized in that... The multi-indicator layer visualization control module includes a port area facility visualization sub-module, a personnel positioning visualization sub-module, and a port area pipeline distribution visualization sub-module. The port area facility visualization sub-module acquires facility data of the port area, collects the center point latitude and longitude coordinates and basic information data of each facility. The basic information data includes facility number, facility name, facility type, facility status, building area, construction date, maintenance cycle, department, person in charge, contact information, and remarks. The center point latitude and longitude coordinates of each facility in the port area are matched with the basic information data. If there are facilities with missing center point latitude and longitude coordinates, they are sent to the backend administrator for manual annotation. After that, a multi-facility maintenance management information list is constructed. According to the location of different facilities in the multi-facility maintenance management information list, different blocks in the port area are pre-divided. Different facilities are divided into different blocks in the port area according to their location. Several multi-point cameras are associated with each facility within the set area of ​​the multi-facility maintenance management information list to collect video data in the facility area in real time and upload it. The personnel positioning visualization submodule includes a real-time personnel trajectory generation unit and a facility anomaly triggering unit. The real-time personnel trajectory generation unit uses a GPS locator to locate the latitude and longitude coordinates of port area workers, determines the different blocks of the port area to which the workers belong based on the workers' latitude and longitude coordinates, marks the blocks to which the workers belong, extracts the blocks to which each worker works, continuously records the location coordinates of workers at different time points, generates the historical movement trajectory of each worker, and constructs a personnel location summary window. The facility anomaly triggering unit pre-sets different thresholds for anomalies of facilities and machinery in the background of the multi-index layer visualization control module. It compares the facility area data and the machinery data in real time with the anomaly thresholds. When there is abnormal data in the facilities or machinery, it triggers the real-time coordinates of the workers in the personnel location summary window and the association process of the abnormal machinery and facilities. It extracts the port area block to which the abnormal facilities and machinery belong, collects the coordinates of several workers in the block in real time, uses the center point coordinates of the abnormal machinery and facilities in the block as the anomaly reference coordinates, compares the coordinates of several workers in the block with the anomaly reference coordinates, analyzes the shortest distance range between the workers in the port area block and the anomaly reference coordinates, and pushes the workers within the short distance range to carry out emergency anomaly handling. The port area pipeline distribution visualization submodule collects basic information, spatial location, and maintenance records of pipelines. The basic information includes: pipeline number, pipeline name, pipeline type, material, pipe diameter, length, design pressure, construction date, design service life, burial depth, maintenance unit, person in charge, and contact information. It constructs a pipeline distribution label list and, based on the spatial location of different pipelines in the port area, constructs a pipeline distribution map. Each pipeline in the pipeline distribution map is associated with the corresponding pipeline distribution label list data and uploaded to the multi-menu data visualization information center for data backup.

8. A real-time visualization system for multiple port areas according to claim 7, characterized in that... The facility anomaly triggering unit is set to detect an anomaly in a specific port area where the faulty facility or machinery is located, and to identify a specific worker in that area. Coordinates are The anomaly reference coordinates of the port area block are: Calculation workers The straight-line distance between the plane and the abnormal reference coordinates is calculated using the formula: In the above formula, Indicates the workers The semi-versus of the angular distance between the reference coordinates and the anomaly. For the workers The difference in latitude between the coordinates and the abnormal reference coordinates, i.e. , For the workers The difference in latitude between the coordinates and the abnormal reference coordinates, i.e. , Indicates personnel working on the sphere The central angle subtended by the great circle arc between the reference coordinates and the abnormal reference coordinates. The average radius of the Earth For the workers The planar straight-line distances between the abnormal reference coordinates and the abnormal facilities and machinery are summarized. The straight-line distances between a worker and the abnormal facility or machinery within the port area block to which the abnormal facility or machinery belongs are then identified. The shortest straight-line distance is then selected and set as the minimum straight-line distance. The backend administrator presets distance expansion ratio thresholds under different abnormal conditions. The straight-line range of the screening distance from the abnormal reference coordinate point is less than or equal to The system identifies the coordinates of the workers, marks the identified workers as key personnel, and sends emergency anomaly handling signals and abnormal reference coordinates of facilities and machinery to these key personnel.

9. A method for real-time visualization of the entire area across multiple port areas, characterized in that... : S1: Use the real-time port area full-area data acquisition and access module to connect with video surveillance equipment and weather forecasting systems deployed in various port areas through standardized interfaces to collect real-time video data and weather data; S2: Use the port area full-area scheduling data visualization module to collect ship scheduling data, production data and ship identification data, and visualize the core data of ship dynamics, yard inventory and berth throughput scheduling on the map; S3: Utilize the visual module for the operation status of loading and unloading machinery and equipment to collect operation line management data, equipment management data, and equipment information monitoring data, thereby achieving real-time visual monitoring of the perception information of belt conveyor lines and large machinery throughout the entire process of equipment perception information. S4: Utilize the AIS data of vessels that have not yet arrived at the port to access the visualization module. Simultaneously, based on vessel identification data and vessel scheduling data, monitor vessels in the anchorage area outside the port area and update their positions in real time according to the AIS data, thereby realizing the data collection and information query of vessels that have not yet arrived at the port. S5: Utilize the multi-indicator layer visualization control module to build a multi-indicator layer management interface. The multi-indicator layer includes configuring the location of multiple types of facilities, port area personnel information location, and distributed pipeline location, and constructs a port area multi-layer visualization panel. S6: Utilize the multi-menu data visualization information center to summarize and integrate the data collected from each module, construct a port production visualization panel, and display comprehensive information.

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