An airport hub construction intelligent regulation and control method and system based on BIM+5G

Abstract

The application discloses an airport hub construction intelligent regulation and control method and system based on BIM+5G, relates to the technical field of construction scheduling optimization, and comprises the following steps: collecting real-time data on site to construct a path construction sequence model, constructing a dynamic construction state set consistent in space and time sequence through component coding and semantic attribute mapping, constructing a minimum disturbance optimization algorithm of four-dimensional disturbance cost based on a construction disturbance mapping diagram, outputting process sequence adjustment, resource rearrangement, path decoupling and environmental avoidance intervention suggestions, and tracking the construction response state in real time based on an intervention execution feedback mechanism. The method constructs a ternary structure and a construction disturbance mapping diagram, realizes unified modeling of construction plans, resource allocation and green indicators, dynamically collects on-site states in combination with 5G and edge perception systems, accurately identifies process abnormalities and resource conflicts, generates efficient and executable regulation and control strategies based on a multi-objective disturbance optimization algorithm, and significantly improves the intelligence, responsiveness and energy-saving level of the construction process.

Description

Technical Field

[0001] This invention relates to the field of construction scheduling optimization technology, specifically to an intelligent control method and system for airport hub construction based on BIM+5G. Background Technology

[0002] With the continuous expansion of urban infrastructure construction, large-scale transportation hub projects are becoming increasingly complex. The organization, coordination, and refined management of the construction process have become key factors in ensuring project schedule, safety, and resource utilization efficiency. Building Information Modeling (BIM) technology has been widely applied to component modeling and information integration during the construction phase, enabling the visualization of construction plans and the digitization of resource allocation through the construction of 3D models. Simultaneously, the high speed and low latency of 5G mobile communication technology provide technical support for large-scale sensing and remote scheduling at construction sites. Based on this, more and more research is focusing on the integrated application of BIM and 5G, attempting to achieve real-time data collection, dynamic model updates, and efficient transmission of management instructions to support the development trend of smart construction.

[0003] Although current BIM platforms have achieved 3D representation of construction plans and process logic modeling, existing technologies primarily focus on static modeling and linear schedule management, lacking the ability to perceive and control the multi-source states of the construction process in real time. In the complex scenario of airport hub construction, construction processes are highly coupled, resource allocation is frequent, and on-site environmental disturbances are severe. Traditional BIM models alone cannot dynamically respond to sudden conflicts, such as path blockages, equipment interference, and resource shortages. On the other hand, although some research has attempted to apply 5G technology to on-site image monitoring and remote equipment control, it lacks deep integration with construction semantic models, failing to form a dynamic state recognition mechanism based on processes, and even less able to support precise scheduling based on disturbance mapping. Furthermore, existing scheduling methods are often based on static optimization, unable to achieve local micro-disturbance control and closed-loop feedback based on real-time data, resulting in delayed actual intervention measures and serious deviations in execution. In comparison, this invention is the first to construct a dynamic construction sequence model with "process-resource-time" as the main axis, and combines 5G and edge computing to achieve high-frequency acquisition and semantic alignment of construction status; by using a perturbation mapping graph to characterize path deviations and risk nodes, and then introducing a multi-objective perturbation optimization algorithm, it achieves comprehensive control of schedule, safety, cost and carbon emissions during construction, with response efficiency and execution accuracy that cannot be matched by existing technologies. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that existing airport hub construction management and control methods suffer from static information models, isolated on-site perception, and lagging control feedback, as well as the problem of how to achieve disturbance identification, adaptive optimization, and closed-loop execution of control commands throughout the entire construction process.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a BIM+5G-based intelligent control method for airport hub construction, comprising collecting real-time on-site data to construct a path construction sequence model, describing the execution logic, resource requirements, and safety level requirements of civil engineering, steel structure, prefabricated component installation, and electromechanical pipeline layout processes; establishing a process-resource-time ternary structure matrix based on a BIM platform, and encoding and associating the carbon emission baseline value of each process; relying on a 5G network and edge computing architecture, collecting personnel positioning behavior, large equipment operating status, material flow trajectory, environmental disturbance data, and image-assisted recognition information at the construction site, and simultaneously... In the step-by-step construction sequence model, a dynamic construction state set consistent with space and time is constructed through component coding and semantic attribute mapping. Taking the process as the identification unit, a construction disturbance mapping map is constructed using a field comparison mechanism, and path deviation nodes, resource conflict points, path blocking sections, and risky process areas are marked. Based on the construction disturbance mapping map, a minimum disturbance optimization algorithm is constructed and run to address the four-dimensional disturbance costs of schedule, safety, cost, and carbon emissions. The algorithm outputs suggestions for process sequence adjustment, resource rearrangement, path decoupling, and environmental avoidance intervention, and pushes structured control instructions to responsible positions. Based on the intervention execution feedback mechanism, the construction response status is tracked in real time.

[0007] As a preferred embodiment of the intelligent control method for airport hub construction based on BIM+5G described in this invention, the real-time on-site data includes the location and behavior data of construction personnel, the operation data of construction machinery and equipment, the data on material entry, exit and consumption, environmental disturbance sensing data and image-assisted recognition data. The data is uploaded through an edge access gateway and semantically bound to the process nodes in the construction BIM model.

[0008] As a preferred embodiment of the intelligent control method for airport hub construction based on BIM+5G described in this invention, the construction disturbance mapping diagram includes a directed graph structure with work processes as nodes and inter-work process dependencies and conflict relationships as edges. The edges are labeled with the degree of impact on the construction period, the level of safety risk, the density of resource conflicts, and the carbon emission offset, representing the interference propagation link in the current construction process.

[0009] As a preferred embodiment of the intelligent control method for airport hub construction based on BIM+5G described in this invention, the minimum disturbance optimization algorithm includes adjusting the sequence or resource allocation in the path process under the premise of controlling the overall construction plan structure to remain unchanged, and adopting a rigid intervention mechanism for time sequence coordination and risk mitigation for conflict nodes on the path.

[0010] As a preferred embodiment of the BIM+5G-based intelligent control method for airport hub construction described in this invention, the intervention suggestions include a construction plan adjustment list, a resource allocation schedule, a construction sequence change map, a safety risk warning prompt, and an execution interface document, which are pushed to construction positions and the scheduling platform.

[0011] As a preferred embodiment of the intelligent control method for airport hub construction based on BIM+5G described in this invention, the intervention execution feedback mechanism includes triggering a disturbance correction process when the actual execution deviates from the intervention target, and responding through strategies such as range order adjustment, resource staggering, and equipment path recalculation.

[0012] As a preferred embodiment of the intelligent control method for airport hub construction based on BIM+5G described in this invention, the real-time tracking of construction response status includes archiving and modeling information on response timeliness, execution effect, risk changes and resource consumption during the construction process after the intervention plan is executed, forming a three-element knowledge sample set of execution event-response strategy-intervention effect, which is then used for disturbance function parameter optimization and control rule migration in subsequent construction tasks.

[0013] Another objective of this invention is to provide an intelligent control system for airport hub construction based on BIM+5G. This system can construct and run a minimum disturbance optimization algorithm based on a construction disturbance mapping map, which addresses the problem that current airport hub construction management and control methods cannot achieve disturbance identification, adaptive optimization, and closed-loop execution of control commands throughout the entire construction process.

[0014] As a preferred embodiment of the BIM+5G-based intelligent control system for airport hub construction described in this invention, it includes: a construction benchmark model construction and multi-objective parameter setting module, a real-time site status acquisition and conflict path identification module, and a minimum disturbance optimization execution and feedback closed-loop control module; the path planning module is used to construct baselines for construction sequence, resources, safety, cost, and carbon emission target parameters, providing a reference for control; the real-time site status acquisition and conflict path identification module is used to collect multi-source site status data, compare it with the benchmark to identify key conflicts, and extract disturbance propagation paths; the minimum disturbance optimization execution and feedback closed-loop control module is used to execute intervention plans and continuously monitor feedback, optimizing if it deviates from the target, thus achieving dynamic closed-loop control throughout the entire construction process.

[0015] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement a BIM+5G-based intelligent control method for airport hub construction.

[0016] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of a BIM+5G-based intelligent control method for airport hub construction.

[0017] The beneficial effects of this invention are as follows: The intelligent control method for airport hub construction based on BIM+5G provided by this invention constructs a full-cycle construction sequence model based on the critical path method, clarifies the process logic, resource allocation, safety level, and carbon emission indicators, and achieves the structured integration of construction plans, resources, and green goals, laying the foundation for a benchmark system for dynamic control. Relying on 5G and edge computing architecture, it collects multi-dimensional on-site data such as personnel positioning, equipment status, material flow, environmental disturbances, and image recognition, constructs a construction status set in real time, compares it with the benchmark model, identifies anomalies such as path delays, resource conflicts, and environmental exceedances, and then constructs a construction disturbance mapping map to accurately reconstruct the cascading risk propagation path. On this basis, a minimum disturbance optimization algorithm is constructed based on four-dimensional disturbance factors of schedule, safety, cost, and carbon emission, outputting suggestions for process sequence adjustment, resource rearrangement, and risk avoidance intervention, and pushing structured control instructions to the job terminals to realize the job-specific executableness of the scheduling plan. At the same time, the system continuously monitors execution feedback, identifies intervention deviations, and automatically triggers local micro-disturbance corrections, constructing a closed-loop response mechanism. The above methods enable rapid identification and dynamic response to complex anomalies during construction, improve the resilience of construction plans and the efficiency of resource allocation, strengthen the synergistic optimization of safety control and green construction, and improve the overall intelligence level and execution adaptability of airport hub project construction management, breaking through the bottlenecks of existing technologies in multi-objective regulation and closed-loop control. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 The first embodiment of the present invention provides an overall flowchart of an intelligent control method for airport hub construction based on BIM+5G.

[0020] Figure 2The first embodiment of the present invention provides a technical solution logic diagram of an intelligent control method for airport hub construction based on BIM+5G.

[0021] Figure 3 The following is an overall flowchart of an intelligent control system for airport hub construction based on BIM+5G, provided as a third embodiment of the present invention. Detailed Implementation

[0022] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0023] Example 1, referring to Figure 1 - Figure 2 As one embodiment of the present invention, a method for intelligent control of airport hub construction based on BIM+5G is provided, comprising: S1: Collect real-time on-site data to construct a path construction sequence model, describing the execution logic, resource requirements, and safety level requirements of civil engineering, steel structure, prefabricated component installation, and electromechanical pipeline layout processes. Based on the BIM platform, establish a process-resource-time ternary structure matrix and encode the carbon emission benchmark value associated with each process.

[0024] Furthermore, during the construction initiation phase, based on the overall construction control plan for the airport hub project, and comprehensively considering the construction arrangements of major systems such as civil engineering, steel structure engineering, prefabricated component installation, electromechanical pipeline layout, and interior and exterior decoration engineering, a path construction sequence model covering the entire lifecycle is established, represented as follows:

[0025] This includes extracting the original construction period for each node in the construction plan. Pre-dependencies Resource planning investment Budget costs carbon emission indicators Process risk level .

[0026] The path construction sequence model is based on the critical path method (CPM), which clarifies the process flow, execution start and end time, dependencies and logical path of each process, and identifies the critical path and flexible process sections.

[0027] To achieve resource matching and construction feasibility verification, the allocation plans for input elements such as human resources, machinery and equipment, and construction materials are entered simultaneously with the definition of work processes, forming a data matrix centered on the "work process-resource-time" ternary relationship. At the same time, for different types of work processes, safety operation levels (such as special operations, high-altitude operations, and temporary electrical operations), schedule control targets (expected completion amount per unit time), and their budget consumption limits are established.

[0028] Under the requirements of green building, it is also necessary to encode and associate the types of materials, energy types, work intensity and duration consumed in each process, calculate the carbon emission benchmark values ​​of various construction activities, and incorporate them into the initial allocation of carbon indicators for the entire construction process.

[0029] All the above data is imported into the construction information model of the BIM platform in a structured format to establish a unified time-series plan view across processes and disciplines. Through model semantic label definitions, component coding standards, and attribute table structures, the construction process management dimension and component dimension are strongly bound together to ensure consistent expression of information in both spatial and temporal dimensions.

[0030] S2: Relying on 5G network and edge computing architecture, it collects personnel positioning behavior, large equipment operation status, material flow trajectory, environmental disturbance data and image-assisted recognition information at the construction site, and synchronizes them to the path construction sequence model. Through component coding and semantic attribute mapping, it constructs a dynamic construction status set that is consistent in space and time. Taking the process as the identification unit, it uses the field comparison mechanism to construct a construction disturbance mapping map and marks path deviation nodes, resource conflict points, path blocking sections and risk process areas.

[0031] Furthermore, after the standard construction sequence model is established and synchronized to the control platform, a high-speed, low-latency communication network covering the entire work area is constructed based on the deployed 5G network infrastructure. The network architecture adopts the form of "edge access + multi-protocol fusion + distributed nodes". Edge access gateways and edge computing nodes are deployed in densely populated work areas (such as core tower crane areas, component storage yards, assembly areas, etc.) to realize the local collection and preprocessing of data from terminal devices.

[0032] The dimensions of on-site data collection mainly include the following five categories: Personnel positioning and work behavior data: Each construction worker entering the site wears a smart positioning terminal. The terminal supports Beidou / GNSS module, IMU motion sensor and SOS warning button functions. It can report personnel location information, movement trajectory, stay time and action characteristics in real time, automatically identify work status (construction, waiting, leaving the post) and record the historical trajectory of entering the risk area for subsequent safety risk analysis and work efficiency assessment.

[0033] Operational data of large machinery and equipment: Key construction equipment such as tower cranes, pump trucks, hoisting machines, and aerial work platforms are all connected to industrial IoT interfaces to collect their running time, load data, travel records, energy consumption data, and abnormal status information in real time; and through coding, they are bound to the equipment IDs in the BIM model to achieve a one-to-one correspondence between physical entities and model components.

[0034] Material entry, exit, and consumption tracking data: Based on an intelligent warehousing and distribution mechanism using RFID / QR code recognition, the time, batch, path, and consumption of each batch of components, steel, cement, pipelines, and prefabricated components during warehousing, outbound, delivery to the site, and assembly processes are fully recorded. This data is automatically matched with the resource allocation plan in the construction sequence to analyze material consumption deviations and supply chain timeliness bottlenecks.

[0035] Environmental disturbance and risk perception data: Multiple types of IoT nodes, including temperature and humidity sensors, dust / PM2.5 monitors, noise probes, wind speed and direction detectors, and vibration monitoring modules, are deployed in areas susceptible to disturbance to monitor the real-time status of the surrounding work environment. When environmental parameters exceed preset thresholds, the system automatically marks the relevant processes as high-risk and triggers control recommendations (such as suspending construction or evacuating personnel).

[0036] Work behavior and image-assisted recognition information: Utilizing 5G drone inspection and AI video analysis system, aerial photos, progress images and video streams of construction scenes are periodically acquired in the construction area, and intelligent image recognition is completed at the edge nodes to identify the actual completion status of key processes, process location and construction density, etc., forming a visual verification of the process progress of the BIM model.

[0037] After forming a complete real-time construction status set, the control platform uses a "plan-execution" dual-track model as a comparison framework to match and analyze the deviations between the real-time status set and the previously established standard construction sequence model item by item. This process uses the process ID as the primary key and compares it against multiple dimensions such as schedule, resources, location information, progress completion rate, working environment values, and equipment correlation to form a dynamic multi-field deviation matrix.

[0038] S3: Based on the construction disturbance mapping, construct and run the minimum disturbance optimization algorithm for four-dimensional disturbance costs of schedule, safety, cost and carbon emissions, output suggestions for process sequence adjustment, resource rearrangement, path decoupling and environmental avoidance intervention, push structured control instructions to responsible positions, and track the construction response status in real time based on the intervention execution feedback mechanism.

[0039] Furthermore, based on the conflict records and current construction objectives (remaining construction period, safety threshold, cost budget, carbon emission limit), the minimum disturbance algorithm is run to adjust the execution sequence or time segment of the process, optimize the allocation of resources (people, machines, materials), calculate the impact of the adjustment on the construction period, safety and green indicators, and finally generate a process change list and resource adjustment plan.

[0040] Without significantly disrupting the construction process, a multi-objective balance between construction period, safety, cost, and carbon emissions can be achieved through dynamic adjustment of limited resources and minimal adjustment of the sequence of procedures.

[0041] The set of disturbance costs is constituted as follows:

[0042] Construction period disturbance function Represented as:

[0043] Security risk disturbance function Represented as:

[0044] Cost disturbance function Represented as:

[0045] Carbon emission perturbation function Represented as:

[0046] in, This serves as the project's baseline duration. For process The original construction period (days); The amount of resources allocated after the disturbance (unit: person-day); Volatility in resource allocation; This refers to the frequency of process disturbance. For process Adjust the execution time; For process The basic security risk coefficient; For process The risk-increasing sensitivity coefficient; The amplitude of the time disturbance; Phase angle of construction environment disturbance; For resources The unit economic cost (yuan); For resources Usage (unit: piece); For resources The intensity of price fluctuations; This refers to random interference factors during the on-site construction phase of the resource project. Maximum budget for resource allocation (in yuan); For resources carbon emission coefficient ; This represents the nonlinear growth coefficient of carbon emissions. For resources Carbon emission disturbance terms in special scenarios; This refers to the sensitivity control parameter for the increase of the carbon emission Sigmoid function.

[0047] ,like A value less than 1 indicates that the project is completed ahead of schedule. An approx. 1 indicates that the project duration is maintained; if A value greater than 1 indicates a significant delay.

[0048] , The higher the value, the higher the security risk, and it increases exponentially.

[0049] ,like A value less than 1 indicates that the cost is below budget. A value exceeding 1 indicates a budget overrun.

[0050] , A higher value indicates that resource allocation leads to increased carbon emissions.

[0051] After the minimum disturbance optimization algorithm completes the scheduling calculation and outputs the intervention variable set, the system enters the intervention plan generation stage. Based on the disturbance optimization results, this stage transforms various calculation outputs into structured control instructions that are identifiable by the project and executable by the job positions, and constructs a set of intervention suggestions based on construction semantics.

[0052] The logic for generating intervention recommendations follows the output classification of the following four core dimensions: (1) List of adjustments to the construction plan Based on the optimal solution of the schedule disturbance function, the platform extracts a list of processes that require adjustment, including their original planned time, recommended start and end times for adjustment, whether upstream and downstream processes need to be modified in conjunction, the scope of buffer adjustment, and whether they affect the critical path. For processes in the flexible zone, the system recommends prioritizing sequential relocation or expansion; for critical path processes, they are marked as "rigid intervention" and accompanied by a scheduling risk index.

[0053] (2) Dynamic allocation of resources Combining the outputs of the cost disturbance function and the carbon emission disturbance function, the system proposes restructuring suggestions for resource allocation. It identifies high-carbon, high-cost resource concentration points and provides resource substitution suggestions, such as replacing high-energy-consuming construction machinery with low-emission equipment and implementing off-peak scheduling during specific time periods to avoid concentrated loads. The suggestions are detailed down to the day-level "human-machine-material" combination rearrangement list, specifying the corresponding responsible processes and work sections.

[0054] (3) Construction sequence update map Based on the conflict mapping diagram and the adjusted task dependencies, the system regenerates the construction sequence diagram and highlights all process nodes whose order has been adjusted. Each updated process node includes its original number, a description of the changes in preceding and following connections, the scope of affected processes, and whether it involves cross-disciplinary collaboration, facilitating the identification of changes in responsibilities by each professional team. This diagram is synchronized to the overall construction control interface and each professional team in a network structure.

[0055] (4) Recommendations for safety and environmental risk intervention Based on the safety disturbance function and environmental anomaly labels, the system prioritizes high-risk construction points and outputs a set of suggested interventions, including: suggestions for construction suspension periods, suggestions for limiting personnel flow in risk areas, suggestions for optimizing construction shielding, and suggestions for strengthening on-site ventilation or dust removal measures. For work nodes affected by multiple environmental parameters, the platform also provides integrated suggestions, such as "postponement + alternative work solutions," to avoid comprehensive project delays.

[0056] The platform automatically structures and encodes all intervention recommendations, resulting in five types of document / data interface outputs: Scheduling Execution Table: For project schedulers, it lists each adjustment suggestion and its corresponding time window, responsible person, related work process, etc.; Task Change Notification Form: Daily change notifications are sent out according to job position or work group; Graphical interactive model: The affected components or areas are highlighted in the BIM platform, and clicks can be used to view intervention instructions; Risk warning layer: Overlaid on the work area in the form of a heat map to alert construction personnel to critical areas; Data Interface / API: It can be linked with the construction task system, labor platform, and material platform to support the automatic push and execution of intervention content.

[0057] It should be noted that all intervention recommendations are prioritized according to the degree of influence of their corresponding perturbation functions: such as This results in the critical path duration exceeding 10%, or If a suggestion exhibits an exponentially increasing risk trend, it is designated as a top priority and immediately reviewed and issued by the project's lead coordinator. Other suggestions are archived in three categories: "Suggested Implementation – Approved Implementation – Reference Implementation," to ensure that the implementation of the plan does not disrupt the on-site schedule.

[0058] Once the intervention suggestion is generated, the platform automatically opens the execution tracking channel to record the execution status, implementation progress, and on-site feedback, providing a traceable data foundation for the next step of execution feedback and perturbation correction.

[0059] After intervention recommendations are issued to the relevant personnel on site, the construction site enters the controlled execution phase. The core objective of this phase is to ensure that the intervention instructions are "understandable, executable, and quantifiable," and to utilize digital sensing mechanisms to track the entire process and verify deviations during execution. This specifically includes the following five steps: (1) Intervention plan decomposition and job-level task binding The system decomposes the intervention and adjustment plans generated on the platform according to the work process dimension, automatically matches them to the construction responsibility teams and personnel, and synchronizes relevant change information to personal task terminals (such as mobile APP, AR visual terminal, voice broadcasting equipment, etc.). Each change record has a unique identifier, target time period, change type (sequence / resource / safety / energy consumption, etc.), task indicators, and feedback channel settings.

[0060] (2) Real-time tracking of execution status driven by multi-source data Leveraging the high-frequency data upload capabilities of 5G networks, the platform continuously receives feedback information from the following dimensions: Construction progress feedback: By comparing AI image recognition with BIM model, it is determined whether key components have been positioned and installed, and whether the work area has been transferred to the next stage on schedule; Feedback on actual resource consumption: By using RFID / warehousing systems to analyze the difference between allocated and used resources, we can identify trends of material backlog or shortage. Personnel work behavior feedback: Based on personnel terminal positioning and IMU identification, determine issues such as work density, work stagnation, and redundant personnel deployment; Risk and environmental feedback: By transmitting values ​​such as vibration, dust, and wind speed from sensors, the safety or carbon emission changes caused by construction disturbances can be dynamically assessed.

[0061] After time alignment, data cleaning, and model mapping, all feedback data are compared one by one with the predicted values ​​of each disturbance in the intervention recommendations.

[0062] (3) Deviation recognition and tolerance triggering mechanism The system sets automatic trigger rules based on the tolerance ranges corresponding to each intervention suggestion in the disturbance optimization (e.g., schedule deviation ±5%, carbon emission increase not exceeding 10%, personnel over-density duration not exceeding 15 minutes, etc.). When the actual feedback deviates from the predicted tolerance range, or when unexpected new conflicts occur (e.g., equipment overlap or material accumulation due to the intervention sequence), the platform automatically generates deviation events and categorizes them into the following three types: Acceptable fluctuations (no adjustment required); Warning level deviation (manual review recommended); Significant deviation (triggers automatic perturbation correction).

[0063] (4) Implementation of local re-optimization and perturbation correction strategies For events that trigger severe deviations, the system automatically invokes a local perturbation algorithm. While maintaining the overall construction structure, it makes minor adjustments only to the affected work processes, resource paths, or operation time windows. Common operations include: Borrow time buffers from adjacent flexible processes; Adjust material delivery batches to prioritize support for bottleneck processes; Change the order of operations to free up space intersections; Strengthen temporary safety measures to reduce the impact of environmental disturbances.

[0064] The revised plan after the perturbation does not require review by all personnel. It is directly issued after approval by the main control personnel and quickly synchronized to relevant positions to ensure on-site response efficiency and uninterrupted progress.

[0065] (5) Perform closed-loop modeling and knowledge accumulation The platform archives and models the data for each perturbation correction process and its effects, including: What is the triggering reason and how long is the response time? Changes in construction efficiency, risk, and resource consumption before and after the revision; Which types of interventions are most likely to fail, and in which scenarios are they most effective? Which parameters are predicted incorrectly, and can the perturbation function be optimized?

[0066] Example 2, one embodiment of the present invention, provides an intelligent control method for airport hub construction based on BIM+5G. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiment.

[0067] First, in the construction management test section of a large airport hub project, six typical construction processes—"assembly foundation," "main steel structure," "pipeline layout," "curtain wall installation," "interior decoration construction," and "electrical commissioning"—were selected. A standard construction sequence model was constructed and integrated into the BIM platform. During the test preparation phase, based on the overall control plan and the critical path method, the start and end times, logical dependencies, and buffer lengths of each process were marked, establishing a complete process sequence network structure. Within the BIM platform, each process was coded with its resource elements, work level, and green building indicators. Information such as personnel allocation, equipment hours, material lists, safety levels, and carbon emission data was imported, forming a process-resource-time ternary structure matrix.

[0068] On-site deployment of 5G edge computing gateways and sensor arrays, along with terminal nodes in high-density work areas, collects five key types of data during construction: real-time location and work status uploads from personnel terminals; operational load and anomaly records from large equipment via IoT interfaces; synchronized material entry and exit records via RFID identification from the materials system; continuous uploading of disturbance data such as dust, noise, and vibration from the environmental monitoring system; and image recognition by the AI ​​video unit to monitor process density and progress completion. The system simultaneously establishes a plan-execution comparison mechanism, analyzing each process's schedule deviation, resource allocation status, high-risk operation level, resource conflict frequency, carbon emission intensity, and budget deviation coefficient against a pre-existing standard model. Ultimately, a structured state matrix and disturbance mapping map are generated on the platform, triggering a minimum disturbance scheduling algorithm to locally optimize processes with significant deviations from the targets.

[0069] Table 1 Experimental Data

[0070] As can be seen from the table data, the method proposed in this invention can achieve precise quantification and process feedback of key disturbance dimensions during construction, and form a clear intervention logic in the output of control strategies. Among them, before the implementation of disturbance control, the schedule disturbance index of process E (interior construction) reached 6.3, which is significantly higher than that of other processes; at the same time, the personnel configuration was 46 people, the equipment operation time was 10.4 hours, the resource conflict frequency was 5 times, and the budget deviation coefficient reached 0.35, reflecting the combined risks of high resource concentration, frequent conflicts, and cost overruns.

[0071] After running the minimum disturbance algorithm, the platform adopted resource splitting, time window postponement, and cross-process decoupling strategies for this process, thus dispersing the construction pressure after resource restructuring. System feedback showed that the process's schedule disturbance index decreased to a reasonable range, while carbon emission intensity and budget deviation indices stabilized. In contrast, process A (assembly foundation) exhibited low disturbance characteristics in the experiment, with all indicators at low values, verifying the model's discriminative ability in flexible process identification and intervention priority allocation.

[0072] Meanwhile, although processes C and F in the table have high risk levels, they were not classified into the first-level intervention sequence by the algorithm due to their low frequency of resource conflicts and limited budget deviations. This indicates that the disturbance mapping and control priority strategy constructed in this invention can effectively avoid the phenomenon of "over-intervention," ensure that resources are used preferentially in critical path segments, and improve the overall resource allocation efficiency. Compared with the traditional static planning method that relies on manual judgment and experience-based adjustments, this system can dynamically identify actual deviations, automatically determine the intervention level, and output actionable implementation suggestions through disturbance functions and feedback comparison mechanisms, thus possessing stronger practicality, real-time performance, and system stability.

[0073] In summary, this embodiment verifies the entire process from model building, data collection, deviation analysis to dynamic scheduling, demonstrating that the method of the present invention has significant advantages in multi-objective optimization, intervention and control of complex processes, resource cost management, and response to green building indicators. It reflects the system intelligence, execution accuracy, and strategy adaptability that are superior to existing technologies in highly complex construction scenarios.

[0074] Example 3, referring to Figure 3 As an embodiment of the present invention, an intelligent control system for airport hub construction based on BIM+5G is provided, including a construction benchmark model construction and multi-objective parameter setting module, a real-time on-site status acquisition and conflict path identification module, and a minimum disturbance optimization execution and feedback closed-loop control module.

[0075] The path planning module is used to construct baseline parameters for construction sequence, resources, safety, cost, and carbon emission targets, providing a reference for regulation. The real-time site status acquisition and conflict path identification module is used to collect multi-source status data of the construction site, compare it with the benchmark to identify key conflicts, and extract disturbance propagation paths. The minimum disturbance optimization execution and feedback closed-loop control module is used to execute intervention plans and continuously monitor feedback. If it deviates from the target, it will be optimized to achieve dynamic closed-loop control of the entire construction process.

[0076] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0077] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0078] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0079] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc. It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0080] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for intelligent control of airport hub construction based on BIM+5G, characterized in that, include: Collect real-time on-site data to construct a construction sequence model, describing the execution logic, resource requirements, and safety level requirements of civil engineering, steel structure, prefabricated component installation, and electromechanical pipeline layout. Based on the BIM platform, establish a process-resource-time ternary structure matrix and encode the carbon emission benchmark value of each process. Relying on 5G network and edge computing architecture, the system collects personnel location behavior, large equipment operation status, material flow trajectory, environmental disturbance data and image-assisted recognition information at the construction site, and synchronizes them to the path construction sequence model. Through component coding and semantic attribute mapping, a dynamic construction status set consistent with space and time is constructed. Taking the process as the identification unit, the system uses a field comparison mechanism to construct a construction disturbance mapping map and marks path deviation nodes, resource conflict points, path blocking sections and risk process areas. Based on the construction disturbance mapping, a minimum disturbance optimization algorithm is constructed and operated to address the four-dimensional disturbance costs of schedule, safety, cost, and carbon emissions. The algorithm outputs suggestions for adjusting the sequence of work processes, rearranging resources, decoupling paths, and avoiding environmental interventions. Structured control instructions are pushed to responsible positions, and the construction response status is tracked in real time based on the intervention execution feedback mechanism. The set of disturbance costs is constituted as follows: Construction period disturbance function Represented as: Security risk disturbance function Represented as: Cost disturbance function Represented as: Carbon emission perturbation function Represented as: in, This serves as the project's baseline duration. For process The original construction period; The amount of resources allocated after the disturbance; Volatility in resource allocation; This refers to the frequency of process disturbance. For process Adjust the execution time; For process The basic security risk coefficient; For process The risk-increasing sensitivity coefficient; The amplitude of the time disturbance; Phase angle of construction environment disturbance; For resources The unit economic cost; For resources Usage; For resources The intensity of price fluctuations; This refers to random interference factors during the on-site construction phase of the resource project. Set a budget ceiling for resource allocation; For resources carbon emission coefficient This represents the nonlinear growth coefficient of carbon emissions. For resources Carbon emission disturbance terms in special scenarios; This is a parameter for controlling the sensitivity of carbon emission Sigmoid function growth; ,like A value less than 1 indicates that the project is completed ahead of schedule. A value of 1 indicates that the project duration is maintained. A value greater than 1 indicates a significant delay; , A higher value indicates a higher security risk, and the risk increases exponentially. ,like A value less than 1 indicates that the cost is below budget. A score exceeding 1 indicates a budget overrun; , A higher value indicates that resource allocation leads to increased carbon emissions; After the minimum disturbance optimization algorithm completes the scheduling calculation and outputs the set of intervention variables, the system enters the intervention plan generation stage. Based on the disturbance optimization results, the stage transforms various calculation outputs into structured control instructions that can be identified by the project and executed by the job, and constructs a set of intervention suggestions based on construction semantics. The intervention execution feedback mechanism includes triggering a disturbance correction process when the actual execution deviates from the intervention target, and responding through strategies such as range order adjustment, resource staggering, and device path recalculation. The real-time tracking of construction response status includes archiving and modeling information on response timeliness, execution effect, risk changes and resource consumption during the construction process after the intervention plan is executed, forming a three-element knowledge sample set of execution event-response strategy-intervention effect, which is then used for the optimization of disturbance function parameters and the migration of control rules in subsequent construction tasks.

2. The intelligent control method for airport hub construction based on BIM+5G as described in claim 1, characterized in that: The real-time on-site data includes the location and behavior data of construction personnel, the operation data of construction machinery and equipment, the data on the entry, exit and consumption of materials, the environmental disturbance sensing data and the image-assisted recognition data. The data is uploaded through the edge access gateway and semantically bound to the process nodes in the construction BIM model.

3. The intelligent control method for airport hub construction based on BIM+5G as described in claim 2, characterized in that: The construction disturbance mapping diagram includes a directed graph structure with work processes as nodes and inter-work process dependencies and conflict relationships as edges. The edges are labeled with the degree of impact on the construction period, safety risk level, resource conflict density and carbon emission offset, representing the disturbance propagation link in the current construction process.

4. The intelligent control method for airport hub construction based on BIM+5G as described in claim 3, characterized in that: The minimum disturbance optimization algorithm includes adjusting the sequence or resource allocation in the path process under the premise of keeping the overall construction plan structure unchanged, and adopting a rigid intervention mechanism for time sequence coordination and risk mitigation for conflict nodes on the path.

5. The intelligent control method for airport hub construction based on BIM+5G as described in claim 4, characterized in that: The intervention recommendations include a list of construction plan adjustments, a resource allocation schedule, a construction sequence change map, safety risk warning prompts, and execution interface documents, which are pushed to construction positions and the scheduling platform.

6. A system employing the intelligent control method for airport hub construction based on BIM+5G as described in any one of claims 1 to 5, characterized in that: It includes a construction benchmark model construction and multi-objective parameter setting module, a real-time site status acquisition and conflict path identification module, and a minimum disturbance optimization execution and feedback closed-loop control module; The construction benchmark model construction and multi-objective parameter setting module is used to construct baselines for construction sequence, resources, safety, cost and carbon emission target parameters, providing a reference for regulation; The real-time on-site status acquisition and conflict path identification module is used to collect multi-source status data of the construction site, compare it with the benchmark to identify key conflicts, and extract the disturbance propagation path. The minimum disturbance optimization execution and feedback closed-loop control module is used to execute intervention plans and continuously monitor feedback. If it deviates from the target, it will be optimized to achieve dynamic closed-loop control of the entire construction process.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent control method for airport hub construction based on BIM+5G as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent control method for airport hub construction based on BIM+5G as described in any one of claims 1 to 5.

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