Digital Twin-Based Multi-System Interconnection Control Method and Equipment for Industrial Parks

Abstract

The present invention provides a method and device for multi-system linkage control of a park based on digital twin. The method includes the following steps: constructing a digital twin model, where the digital twin model includes a virtual mapping of physical facilities in the park; establishing data communication between the digital twin model and at least two independently operating subsystems in the park; in response to a trigger event, generating at least one control instruction based on decision logic associated with the digital twin model, where the trigger event includes an interaction operation event on a virtual object in the digital twin model and / or a rule trigger event determined based on the operating data of the subsystems obtained through the data communication; adapting and sending the control instruction to the target subsystem for execution. This method for multi-system linkage control of a park based on digital twin not only realizes intelligent and refined management and control of the park, but also improves the management efficiency of the park, enhances the security and intelligent level of the park.

Description

Technical Field

[0001] This invention belongs to the field of smart park management technology, and specifically relates to a method and equipment for multi-system linkage control of a park based on digital twins. Background Technology

[0002] Existing smart parks typically integrate multiple subsystems such as security monitoring, facility operation, collaborative office, and energy management. However, these systems employ independent architectures and technical standards, resulting in inconsistent data formats and hindering interoperability, creating "information silos." Cross-system collaboration mechanisms are weak, limiting the efficiency of incident response and handling. Park management relies heavily on manual monitoring and operation, with room for improvement in precision and intelligence. Overall visualization is insufficient, making it difficult for managers to intuitively grasp the overall operational status of the park, and decision-making often lacks real-time data support. Currently, although some smart parks have introduced digital twin technology, its application is mostly limited to 3D visualization, and it still falls short in cross-system data fusion, intelligent linkage control, and scenario-based applications, failing to fully leverage the collaborative management value of digital twin technology. Summary of the Invention

[0003] This invention provides a method and equipment for multi-system linkage control in a park based on digital twins, which not only realizes intelligent and refined management and control of the park, but also improves the efficiency of park management and enhances the park's security and intelligence level.

[0004] The technical solution of the present invention is as follows:

[0005] A method for multi-system linkage control in a park based on digital twins includes the following steps:

[0006] S1: Construct a digital twin model, which includes a virtual mapping of physical facilities within the park;

[0007] S2: Establish data communication between the digital twin model and at least two independently operating subsystems within the park;

[0008] S3: In response to a triggering event, generate at least one control command based on decision logic associated with the digital twin model, wherein the triggering event includes an interactive operation event on a virtual object within the digital twin model, and / or a rule-triggered event determined based on subsystem operation data obtained from the data communication;

[0009] S4: Adapt the control command and send it to the target subsystem for execution.

[0010] Furthermore, in the aforementioned digital twin-based multi-system linkage control method for the park, the establishment of data communication in step S2 includes: collecting the operating data of each subsystem through a data integration platform, wherein the collection is based on a communication protocol compatible with each subsystem, and the operating data is output after being standardized.

[0011] Furthermore, in the aforementioned digital twin-based multi-system linkage control method for the park, the communication protocol includes at least one of OPC UA, BACnet / IP, MQTT, and HTTPS.

[0012] Furthermore, in the aforementioned digital twin-based multi-system linkage control method for the park, the decision logic includes a pre-configured linkage rule base and / or an artificial intelligence analysis model. The artificial intelligence analysis model is trained based on historical operating data and is used for anomaly detection or state prediction.

[0013] Furthermore, in the aforementioned digital twin-based multi-system linkage control method for the park, the linkage rule base supports custom editing, and the artificial intelligence analysis model supports iterative updates using new data.

[0014] Furthermore, in the aforementioned digital twin-based multi-system linkage control method for the park, the digital twin model is a 1:1 model with a modeling accuracy of no less than L3 level, and the modeling data sources include geographic information system data, building information model data, and IoT device parameter data.

[0015] Furthermore, in the aforementioned digital twin-based multi-system linkage control method for the park, the data twin model is constructed using irregular structure modeling technology, and the data twin model supports the simulation rendering of dynamic ambient lighting and weather effects.

[0016] Furthermore, the aforementioned digital twin-based multi-system linkage control method for the park also includes:

[0017] S5: Receive feedback information from the target subsystem executing the control command, and update the state of the corresponding virtual object in the digital twin model according to the feedback information.

[0018] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the aforementioned digital twin-based multi-system linkage control method for a campus.

[0019] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aforementioned digital twin-based multi-system linkage control method for a campus.

[0020] The beneficial effects of this invention are as follows:

[0021] This invention provides a digital twin-based multi-system linkage control method for industrial parks. By constructing a digital twin model to integrate data from multiple systems within the park and establishing a collaborative linkage mechanism, it enables intelligent and refined management and control of the park, improves park management efficiency, reduces operating costs, enhances park security and intelligence, and solves problems such as independent operation of existing smart park systems, data disconnection, delayed response, and insufficient refined management and control.

[0022] This digital twin-based multi-system linkage control method for industrial parks, by constructing a unified data integration platform and using standardized communication protocols to connect with the various independent subsystems of the park, effectively breaks down data barriers between subsystems by standardizing heterogeneous data. It realizes data interoperability and sharing between the digital twin model and each subsystem, as well as between subsystems, and solves the core pain point of traditional industrial parks where multiple systems operate independently and data cannot be linked, thus laying a solid data foundation for multi-system collaborative linkage.

[0023] This digital twin-based multi-system linkage control method for the park utilizes high-precision modeling technology to construct a 1:1 digital twin model with an accuracy of at least Level 3. This model accurately reproduces the form and characteristics of the park's physical facilities, supports lighting and weather simulation, and, combined with a visualization platform, provides a clear and intuitive view of the entire park. Managers can quickly grasp the operational status and spatial relationships of each subsystem through the digital twin model, eliminating the need to monitor multiple subsystems individually. This significantly improves the convenience and intuitiveness of management and reduces workload.

[0024] This digital twin-based multi-system linkage control method for the park, combined with a pre-configured linkage rule base and an artificial intelligence analysis model, enables automatic identification of triggered events and automatic generation and transmission of control commands. It can complete the collaborative operation of multiple subsystems in scenarios such as emergency response and energy consumption optimization without human intervention, significantly improving the efficiency of park operation and management. At the same time, the anomaly detection function of the AI ​​model can predict safety hazards, equipment failures and other problems in advance, and link emergency response rules to achieve rapid response, effectively shortening emergency response time, reducing the probability of risk escalation, and significantly improving the safety of the park. Attached Figure Description

[0025] Figure 1 This is a flowchart of a multi-system linkage control method for a park based on digital twins according to the present invention. Detailed Implementation

[0026] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description and claims. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0027] like Figure 1 As shown, this embodiment provides a multi-system linkage control method for a park based on digital twins, including the following steps: S1-S4, and may also include S5.

[0028] S1: Construct a digital twin model, which includes a virtual mapping of physical facilities within the park. These physical facilities specifically include buildings, roads, pipelines, and equipment. The digital twin model is constructed using irregular structure modeling technology and supports simulated rendering of dynamic ambient lighting and weather effects. The digital twin model is a 1:1 model with a modeling accuracy of at least Level 3. The modeling data sources include Geographic Information System (GIS) data, Building Information Modeling (BIM) data, and IoT device parameter data.

[0029] Specifically, multi-source data, including park geographic information, architectural drawings, and equipment parameters, are collected to ensure the comprehensiveness and accuracy of the modeling data. High-precision modeling techniques for irregular eaves and hyperboloid facades, along with modeling methods covering structure, MEP (Mechanical, Electrical, and Construction) disciplines, are employed. Dynamic global illumination and real-time shadowing technologies are combined to construct a 1:1 scale 3D digital twin model corresponding to the park. This 3D digital twin model achieves Level 3 accuracy, accurately reproducing the spatial location, structural form, and material characteristics of various physical facilities within the park, such as buildings, landscapes, facilities, and pipelines. It also supports simulated rendering of lighting effects and weather changes, realistically recreating the park's actual operating status at different times and under different weather conditions, providing managers with intuitive visual references. The digital twin model reserves interfaces for future expansion, allowing for flexible updates to the model content based on park renovation and expansion needs, ensuring long-term consistency between the model and the physical park.

[0030] S2: Establish data communication between the digital twin model and at least two independently operating subsystems within the park. Establishing data communication includes: collecting operational data from each subsystem through a data integration platform, wherein the collection is based on a communication protocol compatible with each subsystem, and the operational data is standardized before being output.

[0031] Specifically, the core of establishing data communication is building a unified data integration platform (i.e., a data middle platform). This platform breaks down data barriers between subsystems, enabling centralized data management and sharing. Based on standardized communication protocols compatible with each subsystem, real-time operational data is collected. These protocols include at least one of OPC UA, BACnet / IP, MQTT, and HTTPS, and can be flexibly adapted to different subsystem types, ensuring comprehensive integration with various subsystems using different protocols, such as those for campus security, fire protection, energy consumption, and office operations.

[0032] After collecting heterogeneous data from various subsystems, the data integration platform standardizes it, including unifying data formats, removing outliers, and supplementing missing data, ensuring data standardization and usability. Simultaneously, the data integration platform possesses full-process functions including data standard management, quality control, security protection, data analysis, and data sharing. It supports the storage and rapid retrieval of massive amounts of operational data, providing high-quality and highly reliable data support for subsequent decision-making logic. Furthermore, it enables bidirectional data exchange between the data integration platform and the digital twin model, as well as between the various subsystems, synchronizing standardized operational data to the digital twin model and establishing a link between the data and the virtual model.

[0033] S3: In response to a triggering event, generate at least one control instruction based on decision logic associated with the digital twin model, wherein the triggering event includes an interactive operation event on a virtual object within the digital twin model, and / or a rule-triggered event determined based on subsystem operation data obtained from the data communication.

[0034] Specifically, the decision-making logic is the core of intelligent linkage control, including a pre-configured linkage rule base and / or artificial intelligence analysis model. These can be used individually or in combination to provide scientific and accurate intelligent decision support for the generation of control commands. The linkage rule base pre-sets linkage logic for multiple scenarios such as park security, energy consumption optimization, office scenarios, and emergency response. It also supports administrators in customizing and editing rule content, allowing for flexible addition, modification, and deletion of linkage rules based on changes in park operational needs, adapting to the personalized management requirements of different parks. The artificial intelligence analysis model is trained based on historical operational data from various subsystems within the park. It is primarily used to achieve functions such as anomaly detection, energy consumption prediction, and pedestrian and vehicle flow analysis. It can accurately identify abnormal states in subsystem operation or predict future energy consumption and pedestrian flow in the park, providing forward-looking decision support for linkage control.

[0035] The triggering events are specifically divided into two types, comprehensively covering both manual operation and automatic triggering scenarios: First, operation events triggered by managers clicking, dragging, or performing other interactive operations on virtual objects on the visualization platform of the digital twin model. For example, remotely clicking a virtual access control device triggers an opening command, achieving manual remote control. Second, rule-triggered events are determined by the data integration platform after acquiring real-time operating data from each subsystem through data communication and comparing it with preset thresholds in the linkage rule library or prediction results from artificial intelligence analysis models. For example, an intrusion detector in the security subsystem detects an abnormal signal, triggering a security linkage rule. When a triggering event occurs, the decision logic automatically generates corresponding control commands based on information such as the event type and severity. The number of control commands can be determined according to actual linkage needs, ensuring the targeted and comprehensive nature of the linkage operation.

[0036] S4: Adapt the control command and send it to the target subsystem for execution.

[0037] A dedicated control center is constructed to serve as the core for adapting, sending, and receiving control commands, connecting the decision-making logic with each target subsystem. After receiving the control commands generated in step S3, the control center first adapts the commands according to the communication protocols and data format requirements of the target subsystems to ensure that the target subsystems can accurately identify and execute the control commands, avoiding the inability to execute control commands properly due to protocol incompatibility.

[0038] Once the adaptation is complete, the control center will send control commands to the corresponding target subsystems, enabling coordinated operation of multiple subsystems and achieving full-process linkage without manual intervention. Simultaneously, the control center supports manual intervention. In special circumstances (such as accidental triggering of linkages, emergency manual adjustments, etc.), managers can manually send control commands to replace automatic linkage control, improving management flexibility and emergency response capabilities.

[0039] Furthermore, to achieve real-time synchronization between the physical and digital worlds and ensure closed-loop management of the linkage control, the method further includes:

[0040] Step S5: Receive feedback information from the target subsystem executing the control command, and update the state of the corresponding virtual object in the digital twin model according to the feedback information.

[0041] Specifically, after the target subsystem executes the control command, it immediately generates corresponding execution feedback information. This feedback information includes core content such as execution success, execution failure, and current operating status, and is sent to the control center through the data integration platform. After receiving the feedback information, the control center quickly synchronizes it to the digital twin model. The digital twin model updates the state of the corresponding virtual object in real time based on the feedback information, ensuring that the state of the virtual object remains highly consistent with the operating state of the physical subsystem, thus achieving real-time synchronization between the physical and digital worlds.

[0042] This step allows managers to intuitively grasp the coordinated execution effect of each subsystem through a digital twin model, promptly identify problems in the execution of control commands, facilitate rapid adjustment of control strategies, and improve the accuracy of coordinated control.

[0043] The above method integrates data from multiple systems in the park by constructing a digital twin model, establishes a collaborative mechanism, realizes intelligent and refined management and control of the park, improves park management efficiency, reduces operating costs, enhances park security and intelligence level, and solves problems such as independent operation of various systems in existing smart parks, data disconnection, delayed response, and insufficient refined management and control.

[0044] As a preferred implementation method, to adapt to the dynamic needs of long-term park operation and ensure the continuous optimization of decision-making logic, the artificial intelligence analysis model supports iterative updates using new operational data. As park operational data accumulates, the artificial intelligence analysis model is continuously trained with new data, which can continuously improve the model's anomaly detection and state prediction accuracy, and optimize the intelligent decision-making effect. The linkage rule library supports custom editing, and managers can flexibly add, modify, and delete linkage rules according to changes in park operational needs, thereby improving the adaptability and flexibility of linkage control.

[0045] This embodiment also provides an electronic device, which serves as the hardware execution carrier for the above-described digital twin-based multi-system linkage control method for a park. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements all the steps of the above-described digital twin-based multi-system linkage control method for a park.

[0046] Specifically, the electronic devices can be servers, industrial control computers, embedded devices, or other equipment with data processing and control capabilities, adapting to different deployment scenarios within the park. The memory is used to store various core contents such as modeling data, subsystem operation data, linkage rule bases, artificial intelligence analysis models, and computer programs. It preferably adopts a combination architecture of solid-state drives (SSDs) and hard disk drives (HDDs). The SSDs are used to store computer programs, linkage rule bases, and other content requiring rapid access, while the HDDs are used to store massive amounts of modeling data and operation data, ensuring that the storage capacity meets the long-term operational needs of the park. The processor uses a high-performance multi-core processor with strong data processing and computing capabilities, enabling rapid execution of computer programs and efficient implementation of all steps, including the construction of the digital twin model, the establishment of data communication, the generation and transmission of control commands, the processing of feedback information, and the updating of model status, ensuring the real-time performance and stability of the linkage control.

[0047] This embodiment also provides a computer-readable storage medium for storing a computer program that implements the above-described linkage control method. The computer program is stored thereon, and when the computer program is executed by a processor, it implements the above-described multi-system linkage control method for a park based on digital twins.

[0048] Specifically, the computer-readable storage medium can be a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), disk, optical disk, or other conventional media capable of storing computer programs. By storing the computer program on this medium, the transmission, installation, and operation of the computer program can be facilitated, enabling related electronic devices to quickly deploy the linkage control method described in this invention without complex configuration processes, effectively improving the implementation efficiency and accessibility of the park's intelligent management system.

[0049] Example 1:

[0050] The specific implementation process of the multi-system linkage control method for the park based on digital twins is as follows:

[0051] Step 1: Collect GIS geographical information data, building CAD drawings, BIM model data of the incubation center, and parameter data of various Internet of Things devices such as 500 cameras, 200 intrusion detectors, access control devices, and energy consumption meters in the park to ensure the comprehensiveness and accuracy of the modeling data. Adopt the high-precision modeling technology of special-shaped eaves + double-curved facades and the full-professional integration modeling method of structure-mechanical-decoration, combined with the dynamic global illumination and real-time shadow technology, to construct a 1:1 corresponding three-dimensional digital twin model of the incubation center. The modeling accuracy of this digital twin model reaches the L3 level standard, comprehensively covering all physical facilities such as 13 buildings, roads, greenery, and pipe networks in the park, and accurately restoring the material characteristics of various facilities through a dedicated material library; supporting the simulation rendering of light and shadow effects and weather changes (sunny, rainy, cloudy, etc.), and being able to truly restore the actual state of the park at different times and under different weathers; reserving later expansion interfaces, and the model content can be updated according to the park's renovation and expansion requirements. At the same time, the terrain and road errors of this model are ≤ 0.5 meters, ensuring a high degree of consistency with the physical park and providing an accurate visual carrier for subsequent linkage control.

[0052] Step 2: Build a unified data integration platform (i.e., data middle platform), which serves as the core carrier for the data interconnection of multiple systems in the park. Based on four standardized communication protocols of OPC UA, BACnet / IP, MQTT, and HTTPS, comprehensively connect to various independent subsystems in the park, including the intelligent monitoring system composed of 500 cameras, the intrusion alarm system composed of 200 intrusion detectors, the fire alarm system, the energy consumption monitoring system, the office automation system, etc., to achieve full-coverage connection of the park's subsystems.

[0053] The data integration platform collects the operation data of each subsystem in real time through the corresponding communication protocol, including real-time camera images, detector status, energy consumption data, operation parameters of fire-fighting equipment, usage status of office equipment, etc.; after the collection is completed, standardize these heterogeneous data, including unifying the data format, eliminating abnormal data, supplementing missing data, etc., to achieve standardized management of the data. This data middle platform has full-process functions such as data standard management, quality control, security protection, data analysis, and data sharing, adopts a high-performance storage architecture, supports the storage and rapid retrieval of a large amount of operation data, and at the same time realizes two-way data interconnection with the digital twin model, synchronizes the standardized operation data to the digital twin model, and realizes the accurate association of data and virtual models.

[0054] Step 3: Preset a linkage rule library and an artificial intelligence analysis model, which serve as the core of the intelligent linkage decision-making in the park. The two are used in combination to ensure the accuracy and pertinence of control instructions.

[0055] The system includes a set of interconnected rules pre-configured to meet the operational needs of the research and development incubation park. These rules cover various scenarios, including security, fire safety, energy optimization, office environments, and emergency response. For example, the security rule pre-sets that "when an intrusion detector triggers an alarm, it automatically activates three nearby cameras to focus on the alarm area, closes access control systems around the alarm area, and sends alarm information and location data to management personnel." The energy optimization rule pre-sets that "when an AI model predicts that energy consumption in a certain area of ​​the park exceeds the standard, it automatically adjusts the air conditioning temperature in that area and turns off unused lighting equipment." The office environment rule pre-sets that "when office workers make a meeting room reservation through a digital twin model, it automatically controls the meeting room lights and air conditioning to turn on and off after the reservation ends." Furthermore, the rule set allows management personnel to customize and edit the rules through a visual platform, enabling them to flexibly add, modify, and delete rules based on changes in the park's operational needs.

[0056] Artificial Intelligence Analysis Model: Based on one year of historical operational data from the park (including security data, energy consumption data, pedestrian and vehicle flow data, etc.), three core AI models—anomaly detection model, an energy consumption prediction model, and pedestrian and vehicle flow analysis model—were trained. The anomaly detection model can accurately identify abnormal states such as intrusion, fire hazards, and equipment malfunctions, with an accuracy rate exceeding 90%. The energy consumption prediction model can predict the park's daily and monthly energy consumption with an error controlled within 10% (prediction accuracy exceeding 90%), providing precise support for coordinated energy consumption optimization. The pedestrian and vehicle flow analysis model can analyze the distribution and changing trends of pedestrian and vehicle flow within the park, providing decision support for park security scheduling and parking management. This AI analysis model supports iterative updates using new operational data; as park operational data accumulates, the model's accuracy continuously improves.

[0057] When a trigger event occurs, corresponding control commands are generated based on the above decision logic. For example, if an intrusion detector on the 5th floor of Building 3, Plot 27 in the park triggers an alarm (a rule-triggered event), the decision logic automatically generates three control commands based on preset security linkage rules: ① Invoke three cameras in the surrounding area to focus on the alarm area and start recording; ② Close all access control systems on that floor to prevent personnel from entering or exiting; ③ Push alarm information and alarm location to the park management personnel's mobile phones and visualization platform. As another example, if a manager clicks on a virtual access control device in an office on the digital twin model (an interactive operation event), the decision logic generates a control command: to open the physical access control device in that office, enabling manual remote control.

[0058] Step 4: Construct the park's control center, serving as the core for adapting, sending, and receiving control commands, connecting the decision-making logic with each target subsystem. After receiving the control commands generated in Step 3, the control center adapts the commands according to the communication protocols and data format requirements of each target subsystem. For example, for cameras using the MQTT protocol, the control commands are adapted to the MQTT protocol format to ensure that the target subsystem can accurately recognize and execute the control commands.

[0059] After adaptation, the control center sends control commands to the corresponding target subsystems (cameras, access control devices, management terminals, etc.). Upon receiving the control commands, each target subsystem immediately executes the corresponding operation: the camera points at the alarm area and records video, the access control device closes, and the management terminal receives the alarm information, achieving coordinated operation of multiple subsystems. The entire process requires no manual intervention, with response time controlled within seconds. Simultaneously, the control center supports manual intervention. If management personnel discover that the alarm is falsely triggered, they can manually send control commands to unlock the access control device and stop camera recording, improving management flexibility.

[0060] Step 5: After each target subsystem executes the control command, it will immediately generate corresponding feedback information: for example, the camera will report "Alarm area has been pointed at and recording has started", the access control device will report "Closed", and the management terminal will report "Alarm information received". Each subsystem will send the feedback information to the control center through the data platform. After receiving the feedback information, the control center will quickly synchronize the feedback information to the digital twin model.

[0061] The digital twin model updates the status of corresponding virtual objects in real time based on feedback information: the virtual camera's view switches to the real-time view of the alarm area, the virtual access control device displays as "closed," and the alarm location is displayed as a red warning sign, ensuring that the status of the virtual objects is consistent with the operating status of the physical subsystem, achieving real-time synchronization between the physical and digital worlds. Managers can intuitively grasp the execution effect of the linkage control through the digital twin model, promptly identify problems, and adjust strategies.

[0062] Through the above steps, the incubation center has achieved collaborative linkage and intelligent management of various subsystems. Managers can use the digital twin model visualization platform to "view the entire park on one screen and control the entire area with one click", which greatly improves the efficiency and security of park management, while reducing manual management costs and energy waste, and fully meets the park's operation and management needs.

[0063] The digital twin-based multi-system linkage control method for parks described in this application is not limited to the incubation parks in the above embodiments. It can also be widely applied to various parks with multi-system management needs, such as industrial parks, business parks, industrial parks, and campuses. The modeling scope of the digital twin model, the specific content of the linkage rules, and the training data of the manually analyzed model can be flexibly adjusted according to the scale of the specific park, the type of subsystem, and the operational needs to achieve adaptation.

[0064] Furthermore, the modeling techniques, communication protocols, and AI model types mentioned above can all be flexibly adjusted according to actual needs. For example, modeling techniques can be tailored to the characteristics of the park's buildings using appropriate high-precision modeling methods; communication protocols can be adjusted by adding or removing corresponding protocol types based on the type of subsystem; and AI models can be added for environmental monitoring, equipment lifespan prediction, and other purposes based on park management needs. All of these adjustments fall within the scope of protection of this invention. Simultaneously, the configuration of each module can be flexibly adjusted according to the park's actual budget and needs. For example, small and medium-sized parks can simplify some modeling details and reduce the types of AI models, while large parks can increase modeling accuracy and expand the functionality of AI models, balancing practicality and economy, and possessing broad application prospects.

[0065] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the claims.

Claims

1. A method for multi-system linkage control in a park based on digital twins, characterized in that, Includes the following steps: S1: Construct a digital twin model, which includes a virtual mapping of physical facilities within the park; S2: Establish data communication between the digital twin model and at least two independently operating subsystems within the park; S3: In response to a triggering event, generate at least one control command based on decision logic associated with the digital twin model, wherein the triggering event includes an interactive operation event on a virtual object within the digital twin model, and / or a rule-triggered event determined based on subsystem operation data obtained from the data communication; S4: Adapt the control command and send it to the target subsystem for execution.

2. The multi-system linkage control method for a park based on digital twins as described in claim 1, characterized in that, The establishment of data communication in step S2 includes: collecting the operating data of each subsystem through a data integration platform. The collection is based on a communication protocol compatible with each subsystem, and the operating data is output after being standardized.

3. The multi-system linkage control method for a park based on digital twins as described in claim 2, characterized in that, The communication protocol includes at least one of OPC UA, BACnet / IP, MQTT, and HTTPS.

4. The multi-system linkage control method for a park based on digital twins as described in claim 1, characterized in that, The decision-making logic includes a pre-configured linkage rule base and / or an artificial intelligence analysis model, which is trained based on historical operating data and used for anomaly detection or state prediction.

5. The multi-system linkage control method for a park based on digital twins as described in claim 4, characterized in that, The linked rule base supports custom editing, and the artificial intelligence analysis model supports iterative updates using new data.

6. The multi-system linkage control method for a park based on digital twins as described in claim 1, characterized in that, The digital twin model is a 1:1 model with a modeling accuracy of no less than Level 3. The modeling data sources include geographic information system data, building information model data, and Internet of Things device parameter data.

7. The multi-system linkage control method for a park based on digital twins as described in claim 1, characterized in that, The data twin model is constructed using heterogeneous structure modeling technology, and the data twin model supports the simulation rendering of dynamic ambient lighting and weather effects.

8. The multi-system linkage control method for a park based on digital twins as described in claim 1, characterized in that, Also includes: S5: Receive feedback information from the target subsystem executing the control command, and update the state of the corresponding virtual object in the digital twin model according to the feedback information.

9. An electronic device, characterized in that, The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the multi-system linkage control method for a campus based on digital twins as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the multi-system linkage control method for a park based on digital twins as described in any one of claims 1 to 8.

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