Intelligent construction management method based on BIM

Abstract

The invention discloses an intelligent construction management method based on BIM, and relates to the technical field of data encryption, and the method comprises the steps: deploying IoT equipment environment monitoring equipment to collect progress data, resource data and environment data of a construction site, and integrating the collected data into a construction data set; by means of a distributed task decomposition algorithm, construction tasks in the BIM model are refined into executable tasks step by step, task description, resource requirements and dependency relationships of all the tasks are extracted, and the decomposed tasks are distributed to different construction devices and synchronized to the BIM model in real time; defining a state space, an action space and a reward mechanism of the BIM construction plan model; historical construction data is collected, a BIM construction plan model is constructed, the construction data set and the decomposed tasks are input into the BIM construction plan model, and construction plan priorities are output; and dynamically adjusting a construction resource allocation plan according to the construction plan priority output by the reinforcement learning model in combination with real-time data.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent building information modeling, and in particular to an intelligent construction management method based on BIM. Background Art

[0002] Building Information Modeling (BIM) technology has been widely used in the field of construction engineering. It provides strong support for construction management by integrating and visualizing various types of information in the life cycle of a building. However, the existing BIM construction management method is mainly based on static information, which is difficult to effectively deal with the complex and changeable construction site dynamics, such as construction progress delays, unreasonable resource allocation and environmental interference. Although the popularization of IoT technology has made it possible to collect data on the construction site in real time, the existing technology mostly stays at the data visualization level and lacks in-depth mining and application of multi-dimensional dynamic data, especially in the optimization and dynamic adjustment of construction plans. In addition, traditional construction management mainly relies on manual experience or static data, with limited response capabilities, and it is difficult to adjust the construction plan in real time to adapt to changes on site. There are still specific deficiencies in the existing technology in construction management: first, the granularity of construction task decomposition is relatively coarse, and there is a lack of distributed algorithms for the gradual refinement and precise allocation of complex tasks; second, there is insufficient use of historical construction data, and an intelligent data-driven optimization model has not been built; third, the construction plan optimization technology has failed to deeply combine reinforcement learning with BIM, which limits the dynamic adjustment capabilities of construction management and the overall efficiency improvement. To address these problems, there is an urgent need for an intelligent management method that can collect construction data in real time, optimize task allocation, and dynamically adjust construction plans. Summary of the invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the present invention provides a BIM-based intelligent construction management method to solve the problem of coarse granularity of construction task decomposition and lack of distributed algorithms for step-by-step refinement and precise allocation of complex tasks.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a BIM-based intelligent construction management method, which comprises: Deploy IoT device environment monitoring equipment to collect progress data, resource data, and environmental data at the construction site, and integrate the collected data into construction data sets; The construction data set is associated with the components and tasks in the BIM model through a unique identifier ID, and a mapping relationship between the real-time data of the construction site and the BIM model is established; Using the distributed task decomposition algorithm, the construction tasks in the BIM model are broken down into executable tasks step by step, the task description, resource requirements and dependencies of each task are extracted, the decomposed tasks are assigned to different construction equipment and synchronized to the BIM model in real time; Define the state space, action space and reward mechanism of the BIM construction planning model; Collect historical construction data and build a BIM construction plan model, input the construction data set and decomposed tasks into the BIM construction plan model, and output the construction plan priority; According to the construction plan priority output by the reinforcement learning model and combined with real-time data, the construction resource allocation plan is dynamically adjusted.

[0006] As a preferred solution of the BIM-based intelligent construction management method described in the present invention, the deployment of IoT device environment monitoring equipment to collect progress data, resource data and environmental data at the construction site, and integrating the collected data into a construction data set, the specific steps are: Laser scanners, RFID tags, cameras, temperature and humidity sensors, vibration sensors, and GPS positioning units are deployed near the construction site area and task nodes to collect construction progress data, resource data, and environmental data at the construction site through multiple sensors.

[0007] The construction data set is associated with the components and tasks in the BIM model through a unique identifier ID, and a mapping relationship between the real-time data of the construction site and the BIM model is established, which means that the multi-source data is pre-processed through the edge computing gateway, and the overall status of the construction site is obtained through a dynamic weight integration formula; The construction data set is uploaded to the cloud database in real time using the 5G wireless communication protocol, and is associated with the components and tasks in the BIM model through a unique identifier ID, forming a mapping relationship between the construction site data and the BIM model.

[0008] As a preferred solution of the BIM-based intelligent construction management method described in the present invention, the construction data set is associated with the components and tasks in the BIM model through a unique identifier ID, and a mapping relationship between the real-time data of the construction site and the BIM model is established, which means that the multi-source data is pre-processed through an edge computing gateway, and the overall status of the construction site is obtained through a dynamic weight integration formula; The construction data set is uploaded to the cloud database in real time using the 5G wireless communication protocol, and is associated with the components and tasks in the BIM model through a unique identifier ID, forming a mapping relationship between the construction site data and the BIM model.

[0009] As a preferred solution of the BIM-based intelligent construction management method of the present invention, the distributed task decomposition algorithm is used to gradually refine the construction tasks in the BIM model into executable tasks. The specific steps are: Decompose the construction tasks in the BIM model into top-level tasks, middle-level tasks and bottom-level tasks; The task decomposition formula is: ; in, Indicates The task is in The priority of the construction area Indicates The overall workload of the current middle-level tasks, The index variable representing the task, An index variable representing the construction area, Indicates The task is in The resources needed in each construction area, represents the logarithmic function, Indicates The task is in The dependency complexity of each construction area.

[0010] As a preferred solution of the BIM-based intelligent construction management method of the present invention, the task description, resource requirements and dependencies of each task are extracted, the decomposed tasks are assigned to different construction equipment and synchronized to the BIM model in real time. The specific steps are as follows: Obtaining the equipment status of the construction equipment through the IoT device; the equipment status includes equipment efficiency, equipment load and equipment location; Combined with the construction area priorities And device status, calculate the task allocation priority, the expression is: ; in, Indicates The task is in The priority of each device, Indicates The working efficiency of each device, Indicates The load of the device, Indicates The distance between each device and the task location; The task assignment results are dynamically associated with the components, resources and equipment in the BIM model through unique identifiers, and the task status is updated in real time in the BIM model; Using 5G communication protocols, task assignment and equipment status data are uploaded to the cloud database.

[0011] As a preferred solution of the BIM-based intelligent construction management method of the present invention, the state space, action space and reward mechanism of the BIM construction planning model are defined as follows: Set the state space of the construction area to , the state space includes task state, resource state and environment state; Set the action space of the construction area to , the action space includes task allocation action, resource allocation action and rescheduling action; Set the reward function to , the expression is: ; in, represents the base of natural logarithms, represents the adjustment parameter of the reward function, represents the completion rate of the construction plan, and Represent the positive contribution coefficient and negative contribution coefficient respectively, Indicates the total number of tasks, Indicates The importance of the task, Indicates The quality rating of each task, Indicates The expected completion time of a task, Indicates the total number of resources used. An index variable representing a resource, Indicates The amount of resources used, Indicates The loss of resources.

[0012] As a preferred solution of the BIM-based intelligent construction management method of the present invention, the specific steps of collecting historical construction data and building a BIM construction plan model, inputting the construction data set and the decomposed tasks into the BIM construction plan model, and outputting the construction plan priority are as follows: The deep reinforcement learning method DQN is used to build a BIM construction planning model; Input the state space into the BIM construction plan model and output the construction plan priority, which is expressed as: ; in, Indicates the construction plan priority; Use deep reinforcement learning DQN to optimize the construction plan and get the optimal construction plan by maximizing the cumulative reward value ; The construction plan optimization model is trained using historical construction data to maximize the reward function. .

[0013] As a preferred solution of the BIM-based intelligent construction management method of the present invention, the construction resource allocation plan is dynamically adjusted according to the construction plan priority output by the reinforcement learning model and combined with real-time data. The specific steps are as follows: According to the construction plan priority and combined with the real-time data of the construction site, the construction resource allocation plan is dynamically adjusted. The dynamic adjustment formula is: ; in, Indicates the priority of the construction plan after dynamic adjustment. represents the adjustment step size, represents partial derivative; The optimized construction plan is dynamically synchronized to the construction team through the unique identifier in the BIM model, and each team carries out specific tasks based on task description, resource allocation and execution.

[0014] In a second aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the BIM-based intelligent construction management method as described in the first aspect of the present invention is implemented.

[0015] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the BIM-based intelligent construction management method as described in the first aspect of the present invention.

[0016] The beneficial effects of the present invention are as follows: the present invention realizes the real-time collection and integration of construction progress, resources and environmental data by deploying Internet of Things (IoT) devices and environmental monitoring equipment, and establishes a unique identifier association with the components and tasks in the BIM model, thereby constructing a mapping relationship between the dynamic data of the construction site and the BIM model, and utilizing a distributed task decomposition algorithm to refine the construction tasks step by step and optimize the construction plan in combination with reinforcement learning technology, so that construction management can respond to site dynamics in real time, improve construction efficiency and resource utilization. The present invention solves the problems of lack of dynamic adjustment capability, insufficient task decomposition granularity and low data utilization in existing BIM construction management methods, and belongs to the technical field of intelligent building information modeling. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0018] Figure 1 This is a flow chart of the BIM-based intelligent construction management method in Example 1.

[0019] Figure 2 This is a flowchart of task allocation in Example 1. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0023] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a BIM-based intelligent construction management method, comprising the following steps: S1. Deploy IoT device environment monitoring equipment to collect progress data, resource data, and environmental data at the construction site, and integrate the collected data into a construction data set; Deploy laser scanners, RFID tags, cameras, temperature and humidity sensors, vibration sensors, and GPS positioning units near the construction site area and task nodes to collect construction progress data, resource data, and environmental data at the construction site through multiple sensors, including: Construction progress data: Capture the progress of the project (component completion and frequency of on-site personnel activities) through cameras and laser scanners; Resource data: Use RFID tags to track equipment operating hours and material inventory changes; Environmental data: collects ambient temperature, humidity, vibration frequency and device location through temperature and humidity sensors, vibration sensors and GPS modules; The construction data set is associated with the components and tasks in the BIM model through a unique identifier ID. Establishing the mapping relationship between the real-time data of the construction site and the BIM model means preprocessing the multi-source data through the edge computing gateway (including noise reduction, outlier removal, and data compression), and obtaining the overall status of the construction site through a dynamic weight integration formula; Use 5G wireless communication protocol to upload construction data sets to the cloud database in real time, and associate them with components and tasks in the BIM model through unique identifiers, forming a mapping relationship between construction site data and BIM models; The dynamic weight integration formula is: ; in, Indicates the overall status of the construction site. Indicates time, Indicates the start time of data collection. Indicates the end time of data collection. Indicates at time The weight of construction progress data, represents the natural logarithm function, Indicates at time Construction progress data, Indicates at time The weight of resource data, represents the sine function, Indicates at time resource data, Indicates the maximum value of resource data. Indicates at time The weight of environmental data, Indicates at time Environmental data, The differential unit representing the integral; Overall status of the construction site The larger the value, the more complex the dynamic state of the construction site is and the higher the task priority is. Conversely, the smaller the task priority is. S2. Use the distributed task decomposition algorithm to break down the construction tasks in the BIM model into executable tasks step by step, extract the task description, resource requirements and dependencies of each task, assign the decomposed tasks to different construction equipment and synchronize them to the BIM model in real time; Decompose the construction tasks in the BIM model into top-level tasks, middle-level tasks and bottom-level tasks; Top-level tasks: represent the overall task objectives of the entire construction project, such as completing the structural construction of a certain floor; Middle-level tasks: represent the phased subtasks of the top-level tasks, including completing the steel bar binding and formwork installation in a certain area; Low-level tasks: represent executable tasks, including tying steel bars and pouring concrete for a component; The task decomposition formula is: ; in, Indicates The task is in The priority of the construction area Indicates The overall workload of the current middle-level tasks, The index variable representing the task, An index variable representing the construction area, Indicates The task is in The resources needed in each construction area, represents the logarithmic function, Indicates The task is in The complexity of dependencies between construction areas; when Large (high resource requirements) and When it is small (dependencies are simple), the priority maximum; On the contrary, when task dependencies are complex or resource requirements are low, priority reduce; Extracting the task description of each task means extracting the task type (such as tying steel bars or pouring concrete), task location (determined by BIM model coordinates) and execution time limit for each decomposed underlying task; Extracting resource requirements for each task means recording the required materials (such as steel bars, formwork, concrete), equipment (such as cranes, mixers) and construction personnel requirements; Extracting the dependencies of each task means determining the pre-dependencies of the task (e.g., “concrete pouring” can only be carried out after “rebar tying” is completed); Dynamically associate task descriptions, resource requirements and dependencies with components in the BIM model through unique identifiers; Obtain equipment efficiency, equipment load, and equipment location of construction equipment, i.e., equipment status, through IoT devices; Combined with the construction area priorities And device status, calculate the task allocation priority, the expression is: ; in, Indicates The task is in The priority of each device, Indicates The working efficiency of each device (obtained through IoT device monitoring), Indicates The load of each device (the number of tasks assigned to the device), Indicates The distance between a device and the task location (calculated by the device GPS location and the task BIM coordinates); The larger the value of, the more suitable the task is for assigning to the current device; Assign priority when the equipment is efficient, lightly loaded, and closest to the task location maximum; When the device is highly loaded or far from the task, the priority reduce; The allocation logic is to calculate the allocation priority of each task and construction equipment according to the formula, and then allocate the task to the equipment with the highest allocation priority. When the equipment load exceeds the limit, the allocation priority is recalculated and the suboptimal equipment is selected; the equipment status is updated and the allocation results are recorded; The task assignment results are dynamically associated with the components, resources and equipment in the BIM model through unique identifiers, and the task status (such as "to be executed", "in progress" and "completed") is updated in real time in the BIM model; Using 5G communication protocols, task assignment and equipment status data are uploaded to the cloud database; S3, define the state space, action space and reward mechanism of the BIM construction planning model; Set the state space of the construction area to , the state space includes task state, resource state and environment state, and the state space expression is: ; ; in, Indicates at time The task status, Indicates at time The resource status, Indicates at time The environmental status, Indicates the total number of tasks, Indicates The importance of the task, Indicates The quality score of each task is given directly by the construction quality inspector or project manager based on the acceptance result after the task is completed. The score range is [0,1]. Indicates the total number of resources used. An index variable representing a resource, Indicates The amount of resources used, Indicates The loss of resources, An index variable representing the environment data, Indicates the total amount of environmental data, Indicates The value of the environmental data; Set the action space of the construction area to , the action space includes task allocation action, resource allocation action and rescheduling action, and the action space expression is: ; ; ; ; in, Indicates at time The task assignment action, Indicates at time The resource allocation action, Indicates at time Rescheduling actions caused by environmental changes, represents the sensitivity of the environment state to scheduling, Indicates the environmental threshold that triggers rescheduling; Set the reward function to , the expression is: ; in, represents the base of natural logarithms, Represents the adjustment parameter of the reward function, used to adjust right The extent of the impact, The bigger, Small changes in The greater the impact, represents the completion rate of the construction plan, and Represent the positive contribution coefficient and negative contribution coefficient respectively, Indicates the total number of tasks, Indicates The importance of the task, Indicates The quality score of each task is given directly by the construction quality inspector or project manager based on the acceptance result after the task is completed. The score range is [0,1]. Indicates the first The expected completion time of a task, Indicates the total number of resources used. An index variable representing a resource, Indicates The amount of resources used, represents the loss of the mth resource; The value range of is (0,1). =0, indicating the worst plan. =1, indicating the optimal plan; The reward mechanism is used to quantify the effect of the construction plan and find the optimal construction plan by maximizing the reward value; Collect historical construction data and build a BIM construction plan model, input the construction data set and decomposed tasks into the BIM construction plan model, and output the construction plan priority; The deep reinforcement learning method DQN is used to build a BIM construction planning model; Input the state space into the BIM construction plan model and output the construction plan priority, which is expressed as: ; in, Indicates the construction plan priority; Use deep reinforcement learning DQN to optimize the construction plan and get the optimal construction plan by maximizing the cumulative reward value ; Use historical construction data to input the construction plan optimization model for training, and train the reinforcement learning model so that it can maximize the reward function ; S4. Dynamically adjust the construction resource allocation plan based on the construction plan priority output by the reinforcement learning model and real-time data; According to the construction plan priority, combined with the real-time data of the construction site, the construction resource allocation plan is dynamically adjusted to ensure the real-time nature and execution efficiency of the construction plan. The dynamic adjustment formula is: ; in, Indicates the priority of the construction plan after dynamic adjustment. represents the adjustment step size, represents partial derivative; The optimized construction plan is dynamically synchronized to the construction team through the unique identifier in the BIM model, and each team carries out specific tasks based on task description, resource allocation and execution.

[0024] This embodiment also provides a computer device, which is suitable for the BIM-based intelligent construction management method, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the BIM-based intelligent construction management method proposed in the above embodiment.

[0025] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0026] The present embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the BIM-based intelligent construction management method proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0027] In summary, the present invention deploys IoT devices and environmental monitoring equipment to achieve real-time collection and integration of construction progress, resources and environmental data, and establishes a unique identifier association with the components and tasks in the BIM model, thereby constructing a mapping relationship between the dynamic data of the construction site and the BIM model, and using a distributed task decomposition algorithm to refine the construction tasks step by step and optimize the construction plan in combination with reinforcement learning technology, so that construction management can respond to site dynamics in real time, improve construction efficiency and resource utilization. The present invention solves the problems of lack of dynamic adjustment capability, insufficient task decomposition granularity and low data utilization in existing BIM construction management methods, and belongs to the technical field of intelligent building information modeling.

[0028] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A BIM-based intelligent construction management method, characterized by: include, Deploy IoT device environment monitoring equipment to collect progress data, resource data, and environmental data at the construction site, and integrate the collected data into construction data sets; The construction data set is associated with the components and tasks in the BIM model through a unique identifier ID, and a mapping relationship between the real-time data of the construction site and the BIM model is established; Using the distributed task decomposition algorithm, the construction tasks in the BIM model are broken down into executable tasks step by step, the task description, resource requirements and dependencies of each task are extracted, the decomposed tasks are assigned to different construction equipment and synchronized to the BIM model in real time; Define the state space, action space and reward mechanism of the BIM construction planning model; Collect historical construction data and build a BIM construction plan model, input the construction data set and decomposed tasks into the BIM construction plan model, and output the construction plan priority; According to the construction plan priority output by the reinforcement learning model and combined with real-time data, the construction resource allocation plan is dynamically adjusted.

2. The BIM-based intelligent construction management method according to claim 1, characterized in that: The deployment of IoT device environment monitoring equipment collects progress data, resource data and environmental data at the construction site, and integrates the collected data into a construction data set. The specific steps are as follows: Deploy laser scanners, RFID tags, cameras, temperature and humidity sensors, vibration sensors, and GPS positioning units in the construction site area and near task nodes to collect construction progress data, resource data, and environmental data on the construction site through multiple sensors; The construction data set is associated with the components and tasks in the BIM model through a unique identifier ID, and a mapping relationship between the real-time data of the construction site and the BIM model is established, which means that the multi-source data is pre-processed through the edge computing gateway, and the overall status of the construction site is obtained through a dynamic weight integration formula; The construction data set is uploaded to the cloud database in real time using the 5G wireless communication protocol, and is associated with the components and tasks in the BIM model through a unique identifier ID, forming a mapping relationship between the construction site data and the BIM model.

3. The BIM-based intelligent construction management method according to claim 2, characterized in that: The construction data set is associated with the components and tasks in the BIM model through a unique identifier ID, and a mapping relationship between the real-time data of the construction site and the BIM model is established, which means that the multi-source data is pre-processed through the edge computing gateway, and the overall status of the construction site is obtained through a dynamic weight integration formula; The construction data set is uploaded to the cloud database in real time using the 5G wireless communication protocol, and is associated with the components and tasks in the BIM model through a unique identifier ID, forming a mapping relationship between the construction site data and the BIM model.

4. The BIM-based intelligent construction management method according to claim 3, characterized in that: The distributed task decomposition algorithm is used to break down the construction tasks in the BIM model into executable tasks step by step. The specific steps are: Decompose the construction tasks in the BIM model into top-level tasks, middle-level tasks and bottom-level tasks; The task decomposition formula is: ； in, Indicates The task is in The priority of the construction area Indicates The overall workload of the current middle-level tasks, The index variable representing the task, An index variable representing the construction area, Indicates The task is in The resources needed in each construction area, represents the logarithmic function, Indicates The task is in The dependency complexity of each construction area.

5. The BIM-based intelligent construction management method according to claim 4, characterized in that: The specific steps of extracting the task description, resource requirements and dependencies of each task, assigning the decomposed tasks to different construction equipment and synchronizing them to the BIM model in real time are as follows: Obtaining the equipment status of the construction equipment through the IoT device; the equipment status includes equipment efficiency, equipment load and equipment location; Combined with the construction area priorities And device status, calculate the task allocation priority, the expression is: ； in, Indicates The task is in The priority of each device, Indicates The working efficiency of each device, Indicates The load of the device, Indicates The distance between each device and the task location; The task assignment results are dynamically associated with the components, resources and equipment in the BIM model through unique identifiers, and the task status is updated in real time in the BIM model; Using 5G communication protocols, task assignment and equipment status data are uploaded to the cloud database.

6. The BIM-based intelligent construction management method according to claim 5, characterized in that: The state space, action space and reward mechanism of the BIM construction planning model are defined as follows: The state space of the construction area is set to , the state space includes task state, resource state and environment state; Set the action space of the construction area to , the action space includes task allocation action, resource allocation action and rescheduling action; Set the reward function to , the expression is: ； in, represents the base of natural logarithms, represents the adjustment parameter of the reward function, represents the completion rate of the construction plan, and Represent the positive contribution coefficient and negative contribution coefficient respectively, Indicates the total number of tasks, Indicates The importance of the task, Indicates The quality rating of each task, Indicates The expected completion time of a task, Indicates the total number of resources used. An index variable representing a resource, Indicates The amount of resources used, Indicates The loss of resources.

7. The BIM-based intelligent construction management method according to claim 6, characterized in that: The steps of collecting historical construction data and building a BIM construction plan model, inputting the construction data set and the decomposed tasks into the BIM construction plan model, and outputting the construction plan priority are as follows: The deep reinforcement learning method DQN is used to build a BIM construction planning model; Input the state space into the BIM construction plan model and output the construction plan priority, which is expressed as: ； in, Indicates the construction plan priority; Use deep reinforcement learning DQN to optimize the construction plan and get the optimal construction plan by maximizing the cumulative reward value ; The construction plan optimization model is trained using historical construction data to maximize the reward function. .

8. The BIM-based intelligent construction management method according to claim 7, characterized in that: The construction resource allocation plan is dynamically adjusted according to the construction plan priority output by the reinforcement learning model and combined with real-time data. The specific steps are as follows: According to the construction plan priority and combined with the real-time data of the construction site, the construction resource allocation plan is dynamically adjusted. The dynamic adjustment formula is: ； in, Indicates the priority of the construction plan after dynamic adjustment. represents the adjustment step size, represents partial derivative; The optimized construction plan is dynamically synchronized to the construction team through the unique identifier in the BIM model, and each team carries out specific tasks based on task description, resource allocation and execution.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the BIM-based intelligent construction management method described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the BIM-based intelligent construction management method described in any one of claims 1 to 8 are implemented.

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