Steel structure construction site management platform based on Internet of Things

Abstract

The invention provides a steel structure construction site management platform based on the Internet of Things. The acquisition module is used for acquiring component information and construction environment information in real time. And the decision module carries out fusion analysis on the component information and the construction environment information, and carries out deep design on construction structure installation through a BIM technology in combination with a design drawing. And the application module performs review marking on the deepened design drawing, and automatically associates the deepened design drawing according to expert review opinions to further deepen the design drawing to obtain a final construction drawing. And the execution module calls installation equipment and formulates a component installation sequence through the final construction drawing and the component information, and feeds back an execution state to the acquisition module. Through cooperation of all the modules, the assembly efficiency can be improved, and the installation period can be shortened. The installation precision and the installation reasonable rate are greatly improved, the resource utilization rate can be optimized, and the turnover rate of a storage yard is improved.

Description

Technical Field

[0001] The present invention relates to the field of building information technology, and particularly to a steel structure construction site management platform based on the Internet of Things. Background Art

[0002] As the most basic components of a building, the production quality and delivery time of steel structure components have an important impact on the overall quality and construction progress of the building. In traditional steel structure buildings, due to the large number and variety of on-site components involved, the management difficulty of steel structure components is increased. Therefore, it is necessary to establish a perfect component transportation and installation management system. At the same time, in order to better coordinate management personnel, information technology should be combined to visualize component information.

[0003] The following problems exist in traditional steel frame structure construction management: Information silos: Data in links such as design, processing, and installation are fragmented, lacking a unified platform for integration, resulting in low communication efficiency and lagging decision-making.

[0004] Precision depends on manual experience: Component installation positioning and welding deformation control rely on manual measurement and experience judgment, with high error risks.

[0005] Rough resource scheduling: The use of equipment, materials, and sites lacks real-time dynamic optimization, easily causing resource waste or schedule conflicts.

[0006] Difficult to predict safety hazards: Risks such as cross-operation risks and abnormal equipment operations are difficult to detect and intervene in a timely manner.

[0007] Existing construction management platforms mostly have a single functional module (such as progress management or safety management), lacking the ability of full-process collaboration and intelligent analysis, and unable to meet the efficient management needs of complex steel frame structure projects. Summary of the Invention

[0008] In view of the above problems, the present invention is proposed to provide a steel structure construction site management platform based on the Internet of Things that overcomes the above problems, which can solve problems such as low efficiency in the traditional steel structure construction process and achieve the effect of improving the construction efficiency of the steel structure.

[0009] Specifically, the present invention provides a steel structure construction site management platform based on the Internet of Things. The steel structure construction site management platform based on the Internet of Things includes: A collection module, which is used to collect component information and construction environment information in real time; wherein, the component information includes component model, size, and number; the environment information includes terrain information and air temperature and humidity information at the location where the component is installed. A decision-making module that fuses and analyzes the component information and the construction environment information, and conducts a detailed design of the component structure installation through BIM technology in combination with the design drawings. A transmission module that is used to connect the acquisition module and the decision-making module. The transmission module constructs a hybrid network based on 5G communication and industrial Wi-Fi to achieve efficient information transmission between the acquisition module and the decision-making module. An application module that conducts review markings on the design drawings after the detailed design, and automatically associates and further deepens the design drawings according to the expert review opinions to obtain the final construction drawings. An execution module that calls installation equipment and formulates the construction and installation sequence of the components through the final construction drawings and the component information, and feeds back the execution status to the acquisition module.

[0010] Optionally, the acquisition module includes a component identification unit, a spatial positioning unit, an environment detection unit, and an image acquisition unit. The component identification unit uniquely encodes and binds the components through RFID tags or two-dimensional codes, and records the component type, the construction and installation sequence of the components, and the processing batch. The spatial positioning unit uses a total station and UWB positioning technology to real-time monitor the three-dimensional coordinates of the components, and automatically compares them with the design coordinates of the BIM model, with a deviation threshold ≤ 2mm. The environment detection unit monitors the construction site and yard environment parameters through temperature and humidity sensors and an anemometer. The image acquisition unit obtains the construction site image information, yard environment information, and the stacking status of the components through drones and fixed cameras, and identifies the yard occupancy rate.

[0011] Optionally, the execution module can also stack the components in a standardized manner according to the yard environment parameters, the construction and installation sequence of the components, and the processing sequence information, and in combination with the component codes, so that the components to be installed first or with a high usage frequency are stacked in a position above or convenient for grasping and placing.

[0012] Optionally, the decision-making module includes a welding prediction unit and a path planning unit. The welding prediction unit is connected to the cloud, and the cloud stores a historical data model. The welding prediction unit analyzes and outputs a construction welding sequence plan according to the historical data model, the component information, and the construction environment information. The path planning unit dynamically generates an obstacle avoidance installation path for the components through the design drawings and BIM spatial data.

[0013] Optionally, the decision-making module further includes a construction period evaluation unit. The construction period evaluation unit uses Monte Carlo simulation to predict the probability of construction period deviation and triggers a hierarchical warning.

[0014] Optionally, the execution module includes a resource scheduling dashboard; the resource scheduling dashboard can visually display the utilization rate of installation equipment, the occupancy rate of the storage yard, and the component arrival plan, and send the information to the acquisition module, so that the acquisition module and the decision-making module can dynamically plan the installation sequence of the components and the space usage of the storage yard.

[0015] Optionally, the steel structure construction site management platform based on the Internet of Things further includes: A safety warning module, the safety warning includes multiple groups of video monitoring units, a risk assessment unit, and a warning unit; the video monitoring unit is used to obtain video image information of the construction site, the storage yard, and the staff; a safety assessment report is preset in the risk assessment unit and / or transmitted through the cloud; the risk assessment unit conducts a control risk assessment on the construction site through the safety assessment report; the warning unit can issue risk warnings of different levels through the risk assessment.

[0016] In the steel structure construction site management platform based on the Internet of Things of the present invention, since the acquisition module is composed of an RFID tag array, a laser scanner network, and a meteorological monitoring station, which are respectively used for classifying and marking steel structure components, three-dimensional scanning of the construction site and the storage yard, and detecting changes in weather temperature and humidity. Further, the design drawings are designed in advance, and the design drawings are imported into the acquisition module. The acquisition module inputs the information of the involved drawings, and through BIM technology and in combination with component models, sizes, numbers, terrain information, and air temperature and humidity information, deepens the original design drawings, so as to adjust the deficiencies of the original design drawings, making subsequent construction more efficient and convenient and improving construction efficiency.

[0017] Further, the application module conducts review markings on the involved drawings, enabling the design party, the construction party, and the supervision party to directly mark problems (such as node conflicts, dimensional deviations) on the BIM model or two-dimensional drawings, forming visual markings (such as red circle annotations, arrow indications), and clarifying the problem locations and descriptions. Further, each marking is automatically associated with the responsible person, the resolution time limit, and the priority. The platform pushes the to-do tasks to the relevant parties in real time to ensure the closed-loop rectification of the problems. Further, the review markings are bound to the drawing version number to avoid using uncorrected old version drawings during construction. At the same time, the structural problems involved in the markings (such as errors in the deepening of the main truss nodes) are automatically associated with the revision requirements of the special construction plan, triggering the expert review process.

[0018] Further, the 5G + industrial Internet of Things hybrid networking supports the millisecond-level transmission of total station measurement data and installation equipment (such as cranes) control instructions. The transmission module constructs a multi-protocol compatible data transmission network to ensure the real-time interaction of construction instructions and data.

[0019] Furthermore, based on big data and AI algorithms, construction optimization strategies are generated. The yard (the site for stacking components) is dynamically planned based on the installation sequence, and areas such as the "upper layer easy-to-lift area" are marked, enabling hoisting coordination. Further, the setting of feeding back the execution status to the acquisition module enables the system module to form a closed loop, thus completing dynamic monitoring.

[0020] In summary, through the collaborative cooperation of each module, the present invention can improve the assembly efficiency, shorten the installation cycle, greatly improve the installation accuracy and installation rationality rate, optimize the resource utilization rate, and increase the turnover rate of the yard.

[0021] From the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more clear about the above and other objects, advantages and features of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Some specific embodiments of the present invention will be described in detail hereinafter with reference to the accompanying drawings in an illustrative but not restrictive manner. The same reference numerals in the drawings denote the same or similar components or parts. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 is a schematic structural diagram of an Internet of Things-based steel structure construction site management platform according to an embodiment of the present invention.

[0023] DESCRIPTION OF THE REFERENCE NUMERALS 100, acquisition module; 110, component identification unit; 120, spatial positioning unit; 130, environmental detection unit; 140, image acquisition unit; 200, decision-making module; 210, welding prediction unit; 220, path planning unit; 230, project duration evaluation unit; 300, transmission module; 400, application module; 500, execution module; 510, resource scheduling dashboard; 600, safety warning module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The following will refer to Figure 1 to describe the Internet of Things-based steel structure construction site management platform according to an embodiment of the present invention. In the description of this embodiment, it should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of such features, that is, including one or more of such features. In the description of the present invention, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined. When a certain feature "includes or contains" a certain or certain features it covers, unless otherwise specifically described, this indicates that other features are not excluded and other features may be further included.

[0025] In the description of this embodiment, the descriptions referring to terms such as "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0026] Figure 1 is a schematic structural diagram of a steel structure construction site management platform based on the Internet of Things, as Figure 1 shown, the embodiment of the present invention provides a steel structure construction site management platform based on the Internet of Things. The schematic structural diagram of the steel structure construction site management platform based on the Internet of Things includes a collection module 100, a decision-making module 200, a transmission module 300, an application module 400, and an execution module 500.

[0027] The collection module 100 is used to collect component information and construction environment information in real time. Among them, the component information includes component model, size, and number. The environment information includes terrain information and air temperature and humidity information at the location where the component is installed. The decision-making module 200 performs fusion analysis on the component information and construction environment information, and combines the design drawings to conduct in-depth design of the component structure installation through BIM technology.

[0028] The transmission module 300 is used to connect the collection module 100 and the decision-making module 200. The transmission module 300 constructs a hybrid network based on 5G communication and industrial Wi-Fi, so as to achieve efficient information transmission between the collection module 100 and the decision-making module 200.

[0029] The application module 400 conducts review markings on the design drawings after in-depth design, and automatically associates further in-depth design drawings according to the expert review opinions to obtain the final construction drawings. The execution module 500 calls the installation equipment and formulates the component construction and installation sequence through the final construction drawings and component information, and feeds back the execution status to the collection module 100.

[0030] Specifically, the acquisition module 100 is composed of an RFID tag array, a laser scanner network, and a meteorological monitoring station, which are respectively used for classifying and marking steel structure components, performing three-dimensional scanning on the construction site and storage yard, and detecting changes in weather temperature and humidity. Further, the design drawings are designed and completed in advance, and the design drawings are imported into the acquisition module 100. The acquisition module 100 enters the information related to the drawings, and through BIM technology and in combination with component models, dimensions, numbers, terrain information, and air temperature and humidity information, the original design drawings are further designed, so as to adjust the deficiencies of the original design drawings, make subsequent construction more efficient and convenient, and improve construction efficiency.

[0031] The application module 400 performs review markings on the drawings involved, enabling the design party, construction party, and supervision party to directly mark problems (such as node conflicts and dimension deviations) on the BIM model or two-dimensional drawings, forming visual markings (such as red circle annotations and arrow indications), and clarifying the problem locations and descriptions. Further, each marking is automatically associated with the responsible person, resolution time limit, and priority. The platform pushes the to-do tasks to the relevant parties in real time to ensure the closed-loop rectification of problems. Further, the review markings are bound to the drawing version numbers to avoid using uncorrected old versions of the drawings during construction. At the same time, the structural problems involved in the markings (such as incorrect deepening of the main truss nodes) are automatically associated with the revision requirements of the special construction plan, triggering the expert review process.

[0032] The 5G + industrial Internet of Things hybrid network supports the millisecond-level transmission of total station measurement data and control instructions for installation equipment (such as cranes). The transmission module 300 constructs a multi-protocol compatible data transmission network to ensure the real-time interaction of construction instructions and data.

[0033] Based on big data and AI algorithms, construction optimization strategies are generated. The storage yard (the site for stacking components) is dynamically planned based on the installation sequence, and "upper layer easy hoisting area" etc. are marked, so as to enable hoisting coordination. Further, the setting of feeding back the execution status to the acquisition module 100 enables the system modules to form a closed loop, thus completing dynamic monitoring.

[0034] In summary, the present invention provides that through the collaborative cooperation of each module, the assembly efficiency can be improved, and the installation cycle can be shortened. The installation accuracy and installation rationality rate are also greatly improved, and the resource utilization rate can be optimized, and the turnover rate of the storage yard can be increased.

[0035] During operation, the acquisition module 100 uses an RFID tag array, a laser scanner network, and a meteorological monitoring station to classify and label steel structural components, perform 3D scanning on the construction site and storage yard, and detect changes in temperature and humidity. The construction design drawings are imported into the acquisition module 100 in advance. The module combines BIM technology, component model, size, number, terrain information, and air temperature and humidity information to deepen the original design drawings, timely adjust the deficiencies of the design drawings, and thus improve construction efficiency. The application module 400 performs review markings on the drawings. The designer, constructor, and supervisor can mark problems (such as node conflicts and dimensional deviations) on the BIM model or 2D drawings, forming visual markings (such as red circle annotations and arrow indications) to clarify the problem location and description. Each mark is automatically associated with the responsible person, resolution time limit, and priority. The platform real-time pushes the to-do tasks to the relevant parties to ensure the closed-loop rectification of problems. The transmission module 300 uses a 5G + industrial Internet of Things hybrid network to support the millisecond-level transmission of total station measurement data and installation equipment (such as cranes) control instructions, build a multi-protocol compatible data transmission network, and ensure the real-time interaction of construction instructions and data. Based on big data and AI algorithms, construction optimization strategies are generated, the storage yard (the site for stacking components) is dynamically planned, and "upper layer easy-to-lift areas" are marked, etc., to achieve hoisting coordination and improve the utilization rate of the storage yard. The execution status is fed back to the acquisition module 100 to form a closed-loop system, complete dynamic monitoring, and ensure the high efficiency, precision, and controllability of the construction process.

[0036] In some embodiments of the present invention, as Figure 1 shown, the acquisition module 100 includes a component identification unit 110, a spatial positioning unit 120, an environmental detection unit 130, and an image acquisition unit 140. The component identification unit 110 uniquely encodes and binds components through RFID tags or two-dimensional codes, and records the component type, component construction and installation sequence, and processing batch. The spatial positioning unit 120 uses total station and UWB positioning technologies to real-time monitor the three-dimensional coordinates of components and automatically compare them with the design coordinates of the BIM model, with a deviation threshold ≤ 2 mm. The environmental detection unit 130 monitors the environmental parameters of the construction site and storage yard through temperature and humidity sensors and anemometers. The image acquisition unit 140 obtains the construction site image information, storage yard environmental information, and component stacking status through drones and fixed cameras, and identifies the occupancy rate of the storage yard.

[0037] Specifically, by setting the unique coding and binding of components through RFID tags or QR codes, the supply and demand quantities of components can be dynamically grasped, ensuring that the installation model corresponds to the installation position. Moreover, the position of the component after installation can be quickly determined through the QR code or tag, enabling rapid maintenance or welding of the component. Further, the spatial positioning unit 120 includes a total station positioning system, a UWB positioning system, and a coordinate comparison algorithm. The total station positioning system uses a Leica TS16 (angular accuracy 0.5", ranging accuracy 1mm + 1.5ppm) to establish a control network at the construction site for three-dimensional coordinate measurement (X / Y / Z) of the incoming components, with a sampling frequency of 2Hz. The UWB positioning system deploys Decawave DWM3000 modules to form a positioning network (working frequency band 6.5GHz); UWB tags (size 50×30×10mm) are installed at the component hoisting points to achieve real-time positioning with an accuracy of ±10cm; the coordinate comparison algorithm performs least squares matching between the measured coordinates and the BIM model design coordinates (IFC format); when the deviation exceeds 2mm, an audible and visual alarm is triggered.

[0038] Further, the environmental detection unit 130 includes a temperature and humidity monitoring subsystem, a wind speed monitoring subsystem, and an early warning logic. The temperature and humidity monitoring subsystem arranges Testo 480 recorders (range: -40~+120°C, 0~100%RH; accuracy: ±0.5°C / ±2%RH) to form a 5×5m grid monitoring layout in the storage yard area. The wind speed monitoring subsystem uses a Vaisala WXT530 weather station (range 0-60m / s, resolution 0.1m / s), and an ultrasonic anemometer is installed on top of the tower crane, with a data sampling interval of 5 seconds. The early warning logic activates the automatic sprinkler system when the environmental temperature in the storage yard > 40°C or the relative humidity > 80%, and forcibly locks the tower crane operation permission when the wind speed exceeds 12m / s (level 6 wind).

[0039] Further, the image acquisition unit 140 includes a drone inspection system, a fixed monitoring system, and an image analysis algorithm. The drone inspection system DJI Matrice 300 RTK is equipped with a Zenmuse H20T gimbal (20 million pixel visible light + 640×512 infrared) and performs a preset flight route daily (flight altitude 50m, ground resolution 1.2cm / pixel). The fixed monitoring system installs a Hikvision DS-2CD7A26G0 / P-IZHS 8 million pixel starlight camera (focal length 8-32mm), and a binocular stereo camera (baseline distance 300mm) is set at the entrance and exit of the storage yard. The image analysis algorithm trains a component stacking state recognizer based on the YOLOv5 model (mAP@0.5 reaches 95.2%), and uses OpenCV to calculate the occupancy rate of the storage yard. Occupancy rate = Σ(component projection area) / available area of the storage yard × 100%.

[0040] In some embodiments of the present invention, as Figure 1 shown, the execution module 500 can also standardize the stacking of components according to the information of the yard environment parameters, the construction and installation sequence of components, and the processing sequence, and then combine the component codes to stack the components so that the components to be installed first or with high usage frequency are stacked at the upper or convenient positions for grasping and placing.

[0041] Specifically, the construction and installation sequence of components basically determines the stacking sequence in the component yard. The components that are used first and frequently are located at the upper or easily hoisted positions of the stacking, so as to improve the installation and processing sequence of components.

[0042] In some embodiments of the present invention, as Figure 1 shown, the decision-making module 200 includes a welding prediction unit 210 and a path planning unit 220; the welding prediction unit 210 is connected to the cloud, and the cloud stores a historical data model; the welding prediction unit 210 analyzes and outputs a construction welding sequence plan according to the historical data model, component information, and construction environment information; the path planning unit 220 dynamically generates an obstacle avoidance installation path for components through design drawings and BIM spatial data.

[0043] The cloud is a cloud historical database, which stores material properties (such as Q345B / SUS304, etc.), joint forms (butt joint / corner joint / T-shaped joint), process parameters (current 180 - 320A, voltage 24 - 36V), and measured deformation amounts (in the range of 0.1 - 8.2mm). Further, a welding sequence plan is generated: segmental back welding is implemented for long welds (each segment length is 300 - 500mm); when the plate thickness ≥ 20mm, a hammering process node is automatically inserted; a preheating temperature curve is output (calculated according to JGJ 81-2002).

[0044] The path planning unit 220 imports the Revit model (LOD 400 standard) through BIM data parsing, and extracts: the centroid coordinates of components (millimeter-level accuracy), the geometric parameters of temporary support structures, and the safety operation space envelope. An octree space index (resolution 50mm) is constructed through a real-time obstacle avoidance algorithm, and an improved RRT* algorithm (biased sampling rate 35%) is adopted.

[0045] In some embodiments of the present invention, as Figure 1 shown, the decision-making module 200 also includes a construction period evaluation unit 230. The construction period evaluation unit 230 uses Monte Carlo simulation to predict the probability of construction period deviation and triggers a hierarchical early warning.

[0046] Specifically, the risk levels are as follows: early warning level: red; triggering condition: P(total construction period delay ≥ 10%) > 35%; response measure: start the emergency plan and hold a joint meeting of the headquarters.

[0047] Warning level: Orange; Trigger condition: 15% ≤ P(Delay ≥ 5%) < 35%; Response measures: Optimize the construction plan and increase standby resources.

[0048] Warning level: Yellow; Trigger condition: 5% ≤ P(Delay ≥ 3%) < 15%; Response measures: Strengthen progress monitoring and submit special reports daily.

[0049] Visual output generates a risk Sankey diagram to show the delay conduction path, constructs a decision tree model to recommend the optimal response plan, and outputs a 4D progress simulation comparison video (delay scenario vs. baseline plan).

[0050] In some embodiments of the present invention, as Figure 1 shown, the execution module 500 includes a resource scheduling dashboard 510. The resource scheduling dashboard 510 can visually display the utilization rate of installation equipment, the occupancy rate of the storage yard, and the component arrival plan, and send the information to the acquisition module 100, so that the acquisition module 100 and the decision-making module 200 can dynamically plan the installation sequence of components and the space usage of the storage yard.

[0051] In some embodiments of the present invention, as Figure 1 shown, the steel structure construction site management platform based on the Internet of Things further includes a safety warning module 600. The safety warning includes multiple groups of video monitoring units, a risk assessment unit, and a warning unit. The video monitoring unit is used to obtain video image information of the construction site, the storage yard, and the staff. The risk assessment unit presets and / or transmits a safety assessment report through the cloud. The risk assessment unit conducts a risk assessment of the construction site by comparing with the safety assessment report. The warning unit can issue risk warnings of different levels through risk assessment.

[0052] At this point, those skilled in the art should recognize that although many exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived from the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and recognized as covering all these other variations or modifications.

Claims

1. An Internet of Things-based steel structure construction site management platform, characterized in that, Including: A collection module, which is used to collect component information and construction environment information in real time; wherein, the component information includes component model, size and number; the environment information includes terrain information and air temperature and humidity information at the location where the component is installed; A decision-making module, which fuses and analyzes the component information and the construction environment information, and combines the design drawings to conduct in-depth design of the construction structure installation through BIM technology; A transmission module, which is used to connect the collection module and the decision-making module. The transmission module constructs a hybrid network based on 5G communication and industrial Wi-Fi, so as to realize efficient information transmission between the collection module and the decision-making module; An application module, which conducts review marking on the design drawings after in-depth design, and automatically associates and further deepens the design drawings according to the expert review opinions to obtain the final construction drawings; An execution module, which calls installation equipment and formulates the construction and installation sequence of the components through the final construction drawings and the component information, and feeds back the execution status to the collection module.

2. The Internet of Things-based steel structure construction site management platform according to claim 1, characterized in that The collection module includes a component identification unit, a spatial positioning unit, an environment detection unit and an image acquisition unit; the component identification unit binds a unique code to the component through an RFID tag or a two-dimensional code, and records the component type, the construction and installation sequence of the component and the processing batch; the spatial positioning unit uses a total station and UWB positioning technology to monitor the three-dimensional coordinates of the component in real time, and automatically compares with the design coordinates of the BIM model, and the deviation threshold ≤ 2mm; the environment detection unit monitors the construction site and yard environment parameters through temperature and humidity sensors and anemometers; the image acquisition unit obtains the construction site image information, yard environment information and the stacking state of the components through drones and fixed cameras, and identifies the yard occupancy rate.

3. The Internet of Things-based steel structure construction site management platform according to claim 2, characterized in that The execution module can also stack the components in a standardized manner according to the yard environment parameters, the construction and installation sequence of the components and the processing sequence information, and in combination with the component code, so that the components to be installed first or with a high usage frequency are stacked at the upper or convenient-to-grab positions.

4. The Internet of Things-based steel structure construction site management platform according to claim 1, characterized in that The decision-making module includes a welding prediction unit and a path planning unit; the welding prediction unit is connected to the cloud, and the cloud stores a historical data model; the welding prediction unit analyzes and outputs a construction welding sequence plan according to the historical data model, the component information and the construction environment information; the path planning unit dynamically generates an obstacle avoidance installation path for the component through the design drawings and BIM spatial data.

5. The Internet of Things-based steel structure construction site management platform according to claim 4, characterized in that The decision-making module further includes a construction period evaluation unit; the construction period evaluation unit uses Monte Carlo simulation to predict the probability of construction period deviation and triggers hierarchical early warnings.

6. The Internet of Things-based steel structure construction site management platform according to claim 5, wherein the execution module includes a resource scheduling dashboard; the resource scheduling dashboard can visually display the utilization rate of installation equipment, the occupancy rate of the storage yard, and the component arrival plan, and send the information to the acquisition module, so that the acquisition module and the decision-making module dynamically plan the installation sequence of the components and the space usage of the storage yard.

7. The steel structure construction site management platform based on the Internet of Things according to claim 1, characterized in that, It further includes: a safety early warning module, the safety early warning includes multiple groups of video monitoring units, a risk assessment unit, and an early warning unit; the video monitoring unit is used to obtain video image information of the construction site, the storage yard, and the staff; a safety assessment report is preset in and / or transmitted through the cloud in the risk assessment unit; the risk assessment unit conducts a control risk assessment on the construction site through the safety assessment report; the early warning unit can issue risk warnings of different levels through the risk assessment.

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