A construction safety intelligent management system and method based on big data

Abstract

The present invention discloses a construction safety intelligent management system and method based on big data, which belongs to the field of data processing technology. The system includes a data acquisition and transmission module, an unmanned aerial vehicle control module, a safety intelligent analysis module, a safety alarm module and an interactive display module; the data acquisition and transmission module is used to collect control instruction data of each dynamic device in the construction site; the unmanned aerial vehicle control module is used to control the unmanned aerial vehicle to perform safe cruising and collect video image data of safety monitoring points at the construction site; the safety intelligent analysis module is used to establish a metaverse model of the construction site and conduct risk assessment on the construction site; the safety alarm module is used to issue safety alarms to construction sites with potential safety hazards; the interactive display is used to display the collected video image data and mark the sites with potential safety hazards in the video image data.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a construction safety intelligent management system and method based on big data. Background Art

[0002] Intelligent construction safety management refers to the real-time monitoring, data analysis and risk warning of the safety conditions of the construction site through advanced information technology and intelligent equipment during the construction process, thereby improving the safety management efficiency of the construction site, reducing construction accidents, and protecting the lives of workers; at the same time, it improves construction efficiency and ensures project quality and progress.

[0003] Monitoring construction sites through drones can effectively help workers conduct safety inspections while reducing the risks of manual inspections. In existing technologies, drones usually rely on sensors to detect obstacles, but the detection range of sensors is limited. In addition, due to the complex environment of construction sites and the presence of various mobile devices, it is difficult for drones to predict the movement trajectory of moving obstacles in real time, which can easily lead to safety accidents and damage to equipment. At the same time, it also increases the risk of construction safety. Summary of the invention

[0004] The purpose of the present invention is to provide a social security early warning supervision system and method based on big data analysis to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a construction safety intelligent management method based on big data, the method comprising the following steps:

[0006] S10, collecting control instruction data of each dynamic device in the construction site; determining the moving path of each dynamic device according to the control instruction data and location information of each dynamic device;

[0007] S20, based on the construction site and safety monitoring points for safety intelligent management, plan the flight path of the drone and control the drone to the safety monitoring points;

[0008] S30, during the flight of the drone, video image data of surrounding objects is collected, and the collected video image data is identified to determine the dynamic devices in the video image; according to the dynamic devices in the video image and the moving paths of each dynamic device, the drone is controlled to cruise safely;

[0009] S40. The UAV arrives at the safety monitoring point and collects video image data of the safety monitoring point; and performs risk assessment on the safety monitoring point based on the collected video image data to determine whether there are safety hazards, and issues safety alarms for the safety monitoring points with safety hazards.

[0010] Furthermore, the safety monitoring area is divided into the personnel activity area and the monitoring blind area according to the construction site, and a metaverse model of the construction site is established; environmental data and video data of the construction site are collected, and the same metaverse environment as the construction site is deployed in the metaverse model according to the collected data; when planning the flight path of the drone, the flight path is determined according to the safety monitoring points determined by the management personnel, and the direct monitoring area is avoided;

[0011] The personnel activity area refers to a construction site where personnel activities exist and can be directly monitored by a camera; the monitoring blind area refers to a high-altitude environment where personnel cannot directly monitor and is monitored by a drone;

[0012] Since some monitoring areas are difficult to supervise directly by humans, they usually need to be supervised by drones. However, drones may interfere with people's work during flight, and people's activities are often difficult to predict and there are no standard specifications. Therefore, when planning the flight path of the drone, avoid areas where people are active.

[0013] Furthermore, the specific implementation process of step S10 includes:

[0014] S101, establish a function model for predicting the moving path of dynamic equipment on the construction site; determine the number n of each type of dynamic equipment on the construction site, and respectively determine the mathematical functions g1, g2, ..., g3 of the n dynamic equipment during the movement on the three orthogonal coordinate axes x, y and z of the function model; n ;

[0015] S102, analyzing the control instruction data of each dynamic device in the construction site, judging the current working state of each dynamic device, predicting the acceleration change of each dynamic device according to the control instruction, and calculating the acceleration change of each dynamic device according to the mathematical functions g1, g2, ..., g n Determine the movement path of each dynamic device;

[0016] By establishing a function model, the moving paths of different dynamic devices within the working range are determined, and the operating range of the dynamic devices is determined based on the moving paths, thereby facilitating the prediction of the location information of the dynamic devices.

[0017] Furthermore, the specific implementation process of step S30 includes:

[0018] S301, when the drone is flying, collects video image data of surrounding objects, uses a convolutional neural network to classify and identify the collected video image data, determines the dynamic device and device type i, and determines the mathematical function g of the device type i during the motion processi ; Where i=1, 2, ..., n;

[0019] S302: Determine the current moving speed and direction of the dynamic device i , the current spatial coordinate point position information (x0, y0, z0), substitute (x0, y0, z0) into the mathematical function g i In the above example, the motion trajectory range of the dynamic device i is determined, and the set of spatial coordinate points A within the motion trajectory range is obtained. i ;

[0020] S303: Determine whether the drone passes through set A according to the planned flight path of the drone. i If it passes through, it is determined that the drone will move from the current position to the set A. i The flight path of the spatial coordinate point is obtained, and step S205 is executed;

[0021] S304: Predict the direction of the drone from the current position to the set A based on the current flight speed of the drone. i The time required for the spatial coordinate point to be calculated is t0; the collected control instruction data is analyzed to determine the current working task type of the dynamic device i, and the acceleration change of the dynamic device i from 0 to t0 is obtained. , get the speed change of dynamic device i from 0 to t0 and the changes in motion trajectory ; According to the calculation formula:

[0022] ;

[0023] Where t represents the timestamp, t∈[0, t0]; ε and u represent the integral variables;

[0024] S305: Based on the current spatial coordinate point position information (x0, y0, z0) of the dynamic device i and the change of the motion trajectory and the mathematical function g i , determine the motion curve of dynamic device i over time t, and obtain the location information of dynamic device i at time t0 , and judge whether the drone will collide with dynamic device i according to the volume occupied by dynamic device i; if there is no collision, continue to fly along the flight path; if there is a collision, according to the volume size and motion trajectory changes of dynamic device i , re-plan the flight path to avoid;

[0025] Since the construction site environment is complex and contains a variety of construction equipment, the drone conducts a comprehensive analysis of the identified dynamic equipment during flight, and predicts the motion trajectory of the dynamic equipment in advance based on the control command data of each dynamic equipment in the construction site, so as to plan the path in advance to avoid emergencies; at the same time, it realizes the interconnection of various equipment and provides an intelligent management solution.

[0026] Furthermore, after arriving at the safety monitoring point, the drone collects video image data of the safety monitoring point and simulates and displays it in the established metaverse model; when a safety hazard is found, the site with the safety hazard is marked in the metaverse model, and the management personnel can determine the site with the safety hazard by checking the metaverse model.

[0027] A construction safety intelligent management system based on big data, the system includes a data acquisition and transmission module, a drone control module, a safety intelligent analysis module, a safety alarm module and an interactive display module;

[0028] The data acquisition and transmission module is used to collect control instruction data of various dynamic equipment in the construction site; the drone control module is used to control the drone to perform safe cruising and collect video image data of safety monitoring points at the construction site; the safety intelligent analysis module is used to establish a metaverse model of the construction site and conduct risk assessment on the construction site; the safety alarm module is used to issue safety alarms for construction sites with safety hazards; the interactive display is used to display the collected video image data and mark the sites with safety hazards in the video image data.

[0029] Further, the data acquisition and transmission module includes a construction equipment management unit and a command data acquisition unit;

[0030] The construction equipment management unit is used to interconnect with various dynamic devices in the form of the Internet of Things and record the working status of each dynamic device; the dynamic device represents an electrical device whose position may change during the construction process;

[0031] The command data acquisition unit is used to collect control command data of various dynamic devices in the construction site, and send the collected command data to the drone control module.

[0032] Furthermore, the drone control module includes a path planning unit, a video image data acquisition unit, an intelligent analysis unit and an automatic avoidance control unit;

[0033] The path planning unit is used to plan the flight path of the UAV based on the construction site and safety monitoring points that are managed with safety and intelligence;

[0034] The video image data acquisition unit is used to collect video image data of surrounding objects during the flight of the drone; when the drone arrives at a safety monitoring point, the video image data of the safety monitoring point is collected;

[0035] The intelligent analysis unit is used to classify and identify the collected video image data using a convolutional neural network, determine the dynamic device and device type, and determine the mathematical function of the device during the movement process; analyze the acceleration change, speed change and movement trajectory change of the dynamic device;

[0036] The automatic avoidance control unit is used to determine whether the drone will collide with the dynamic device according to the volume occupied by the dynamic device; if there is no collision, continue to fly along the flight path; if there is a collision, re-plan the flight path to avoid it according to the volume size and motion trajectory changes of the dynamic device.

[0037] Furthermore, the security intelligent analysis module includes a model building unit and a risk assessment unit;

[0038] The model building unit is used to build a metaverse model about the construction site; collect environmental data and video data of the construction site, and deploy the same metaverse environment as the construction site in the metaverse model according to the collected data;

[0039] The risk assessment unit is used to perform risk assessment on safety monitoring points based on the collected video image data to determine whether there are safety hazards.

[0040] Further, the interactive display module includes a video image display unit and a risk marking unit;

[0041] The video image display unit is used to simulate and display the collected security monitoring point video image data in the established metaverse model;

[0042] The risk marking unit is used to mark sites with potential safety hazards in the metaverse model, and management personnel can determine sites with potential safety hazards by viewing the metaverse model.

[0043] Compared with the prior art, the beneficial effects achieved by the present invention are: providing a big data-based intelligent construction safety management system and method, predicting the motion trajectory of the dynamic equipment in advance according to the control command data of each dynamic equipment in the construction site, thereby controlling the drone to plan the path in advance to avoid the occurrence of emergencies; at the same time, the interconnection of each device is realized, and an intelligent management solution is provided; by establishing a metaverse model of the construction site, the video image data collected in the construction site is displayed, and the sites with safety risks are marked, which facilitates the management personnel to carry out safety management. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0045] Figure 1 It is a structural schematic diagram of a construction safety intelligent management system based on big data in the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] See also Figure 1 The present invention provides a technical solution: a construction safety intelligent management method based on big data, the method comprising the following steps:

[0048] S10, collecting control instruction data of each dynamic device in the construction site; determining the moving path of each dynamic device according to the control instruction data and location information of each dynamic device;

[0049] S20, based on the construction site and safety monitoring points for safety intelligent management, plan the flight path of the drone and control the drone to the safety monitoring points;

[0050] S30, during the flight of the drone, video image data of surrounding objects is collected, and the collected video image data is identified to determine the dynamic devices in the video image; according to the dynamic devices in the video image and the moving paths of each dynamic device, the drone is controlled to cruise safely;

[0051] S40. The UAV arrives at the safety monitoring point and collects video image data of the safety monitoring point; and performs risk assessment on the safety monitoring point based on the collected video image data to determine whether there are safety hazards, and issues safety alarms for the safety monitoring points with safety hazards.

[0052] According to the construction site, the safety monitoring area is divided into the personnel activity area and the monitoring blind area, and a metaverse model of the construction site is established; the environmental data and video data of the construction site are collected, and the same metaverse environment as the construction site is deployed in the metaverse model based on the collected data; when planning the flight path of the drone, the flight path is determined according to the safety monitoring points determined by the management personnel, and the direct monitoring area is avoided;

[0053] Among them, the personnel activity area represents a construction site where personnel activities exist and can be directly monitored by a camera; the monitoring blind area represents a high-altitude environment that cannot be directly monitored by personnel and is a construction site that is monitored by a drone.

[0054] The specific implementation process of step S10 includes:

[0055] S101, establish a function model for predicting the moving path of dynamic equipment on the construction site; determine the number n of each type of dynamic equipment on the construction site, and respectively determine the mathematical functions g1, g2, ..., g3 of the n dynamic equipment during the movement on the three orthogonal coordinate axes x, y and z of the function model; n ;

[0056] S102, analyzing the control instruction data of each dynamic device in the construction site, judging the current working state of each dynamic device, predicting the acceleration change of each dynamic device according to the control instruction, and calculating the acceleration change of each dynamic device according to the mathematical functions g1, g2, ..., g n Determine the movement path of each dynamic device.

[0057] The specific implementation process of step S30 includes:

[0058] S301, when the drone is flying, collects video image data of surrounding objects, uses a convolutional neural network to classify and identify the collected video image data, determines the dynamic device and device type i, and determines the mathematical function g of the device type i during the motion process i ; Where i=1, 2, ..., n;

[0059] S302: Determine the current moving speed and direction of the dynamic device i , the current spatial coordinate point position information (x0, y0, z0), substitute (x0, y0, z0) into the mathematical function g i In the above example, the motion trajectory range of the dynamic device i is determined, and the set of spatial coordinate points A within the motion trajectory range is obtained. i ;

[0060] S303: Determine whether the drone passes through set A according to the planned flight path of the drone. i If it passes through, it is determined that the drone will move from the current position to the set A. i The flight path of the spatial coordinate point is obtained, and step S205 is executed;

[0061] S304: Predict the direction of the drone from the current position to the set A based on the current flight speed of the drone. iThe time required for the spatial coordinate point to be calculated is t0; the collected control instruction data is analyzed to determine the current working task type of the dynamic device i, and the acceleration change of the dynamic device i from 0 to t0 is obtained. , get the speed change of dynamic device i from 0 to t0 and the changes in motion trajectory ; According to the calculation formula:

[0062] ;

[0063] Where t represents the timestamp, t∈[0, t0]; ε and u represent the integral variables;

[0064] S305: Based on the current spatial coordinate point position information (x0, y0, z0) of the dynamic device i and the change of the motion trajectory and the mathematical function g i , determine the motion curve of dynamic device i over time t, and obtain the location information of dynamic device i at time t0 , and judge whether the drone will collide with dynamic device i according to the volume occupied by dynamic device i; if there is no collision, continue to fly along the flight path; if there is a collision, according to the volume size and motion trajectory changes of dynamic device i , re-plan the flight path to avoid it.

[0065] After arriving at the safety monitoring point, the drone collects video image data of the safety monitoring point and simulates and displays it in the established metaverse model; when safety hazards are found, the site with safety hazards is marked in the metaverse model, and managers can determine the site with safety hazards by checking the metaverse model.

[0066] A construction safety intelligent management system based on big data, the system includes a data acquisition and transmission module, a drone control module, a safety intelligent analysis module, a safety alarm module and an interactive display module;

[0067] The data acquisition and transmission module is used to collect control instruction data of various dynamic equipment in the construction site; the drone control module is used to control the drone to perform safe cruising and collect video image data of safety monitoring points at the construction site; the safety intelligent analysis module is used to establish a metaverse model of the construction site and conduct risk assessment on the construction site; the safety alarm module is used to issue safety alarms for construction sites with safety hazards; the interactive display is used to display the collected video image data and mark the sites with safety hazards in the video image data.

[0068] The data acquisition and transmission module includes a construction equipment management unit and a command data acquisition unit;

[0069] The construction equipment management unit is used to interconnect with various dynamic devices in the form of the Internet of Things and record the working status of each dynamic device; the dynamic device represents an electrical device whose position may change during the construction process;

[0070] The command data acquisition unit is used to collect control command data of various dynamic devices in the construction site, and send the collected command data to the drone control module.

[0071] The drone control module includes a path planning unit, a video image data acquisition unit, an intelligent analysis unit and an automatic avoidance control unit;

[0072] The path planning unit is used to plan the flight path of the UAV based on the construction site and safety monitoring points that are managed with safety and intelligence;

[0073] The video image data acquisition unit is used to collect video image data of surrounding objects during the flight of the drone; when the drone arrives at a safety monitoring point, the video image data of the safety monitoring point is collected;

[0074] The intelligent analysis unit is used to classify and identify the collected video image data using a convolutional neural network, determine the dynamic device and device type, and determine the mathematical function of the device during the movement process; analyze the acceleration change, speed change and movement trajectory change of the dynamic device;

[0075] The automatic avoidance control unit is used to determine whether the drone will collide with the dynamic device according to the volume occupied by the dynamic device; if there is no collision, continue to fly along the flight path; if there is a collision, re-plan the flight path to avoid it according to the volume size and motion trajectory changes of the dynamic device.

[0076] The security intelligent analysis module includes a model building unit and a risk assessment unit;

[0077] The model building unit is used to build a metaverse model about the construction site; collect environmental data and video data of the construction site, and deploy the same metaverse environment as the construction site in the metaverse model according to the collected data;

[0078] The risk assessment unit is used to perform risk assessment on safety monitoring points based on the collected video image data to determine whether there are safety hazards.

[0079] The interactive display module includes a video image display unit and a risk marking unit;

[0080] The video image display unit is used to simulate and display the collected security monitoring point video image data in the established metaverse model;

[0081] The risk marking unit is used to mark sites with potential safety hazards in the metaverse model, and management personnel can determine sites with potential safety hazards by viewing the metaverse model.

[0082] In this embodiment:

[0083] The system is specifically an intelligent monitoring and management system for high-altitude safety of construction sites. In this system, drones are used to automatically monitor the safety monitoring points at high altitudes of construction sites. The dynamic equipment on the construction site includes automated tower cranes, automated lifting platforms, and automated scaffolding systems.

[0084] Establish a function model for predicting the moving path of dynamic equipment on the construction site, perform training in the function model, and determine the mathematical functions g1, g2, and g3 of the three dynamic equipment: automated tower crane, automated lifting platform, and automated scaffolding system; collect control instruction data of each dynamic equipment on the construction site, predict the acceleration change of each dynamic equipment according to the control instruction, and obtain the moving path of each dynamic equipment;

[0085] Based on the construction site and safety monitoring points that are managed with intelligent safety, the flight path of the drone is planned, and the drone is controlled to go to the safety monitoring points. During the flight of the drone, video image data of the surrounding objects is collected, and the collected video image data is classified and identified using a convolutional neural network to determine that the video image contains dynamic equipment construction elevators and cranes.

[0086] Determine the current moving speed and direction of automated tower cranes and automated lifting platforms , the current spatial coordinate point position information (x0, y0, z0); substitute the spatial coordinate point position information into the mathematical functions g1 and g2 respectively, and determine the spatial coordinate point sets A1 and A2 within the motion trajectory of the automated tower crane and the automated lifting platform;

[0087] According to the planned flight path of the drone, determine the flight path from the current position of the drone to the spatial coordinate point in the set A2; where the mathematical function of g2 is the vertical rise and fall, and the expression is:

[0088] ;

[0089] Wherein, w represents the threshold used to limit the change of the value range of the automated lifting platform in the vertical direction, and the current value range of w is 0≤w≤5;

[0090] According to the current flight speed of the drone, the time t0=8 required for the drone to travel from its current position to the spatial coordinate point in set A2 is predicted; the collected control command data is analyzed to obtain the acceleration change of the dynamic device i within the time from 0 to 8s , get the speed change of dynamic device i within 0 to 8s and the changes in motion trajectory ; According to the calculation formula:

[0091] ;

[0092] Determine the motion curve of the automated lifting platform over time t, and obtain the location information of the automated lifting platform at time t0 ; At this time through The position information of the automated lifting platform determines the risk of collision between the automated lifting platform and the drone, and replans the flight path to avoid it;

[0093] After arriving at the safety monitoring point, the drone collects video image data of the safety monitoring point, simulates and displays it in the established metaverse model, and marks the sites with safety hazards in the metaverse model.

[0094] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0095] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A construction safety intelligent management method based on big data, characterized by: The method comprises the following steps: S10, collecting control instruction data of each dynamic device in the construction site; determining the moving path of each dynamic device according to the control instruction data and location information of each dynamic device; S20, based on the construction site and safety monitoring points for safety intelligent management, plan the flight path of the drone and control the drone to the safety monitoring points; S30, during the flight of the drone, video image data of surrounding objects is collected, and the collected video image data is identified to determine the dynamic devices in the video image; according to the dynamic devices in the video image and the moving paths of each dynamic device, the drone is controlled to cruise safely; S40, the drone arrives at the safety monitoring point and collects video image data of the safety monitoring point; and performs risk assessment on the safety monitoring point based on the collected video image data to determine whether there are safety hazards, and issues safety alarms for the safety monitoring points with safety hazards; According to the construction site, the safety monitoring area is divided into the personnel activity area and the monitoring blind area, and a metaverse model of the construction site is established; the environmental data and video data of the construction site are collected, and the same metaverse environment as the construction site is deployed in the metaverse model based on the collected data; when planning the flight path of the drone, the flight path is determined according to the safety monitoring points determined by the management personnel, and the direct monitoring area is avoided; The personnel activity area refers to a construction site where personnel activities exist and can be directly monitored by a camera; the monitoring blind area refers to a high-altitude environment where personnel cannot directly monitor and is monitored by a drone; The specific implementation process of step S10 includes: S101, establish a function model for predicting the moving path of dynamic equipment on the construction site; determine the number n of each type of dynamic equipment on the construction site, and respectively determine the mathematical functions g1, g2, ..., g3 of the n dynamic equipment during the movement on the three orthogonal coordinate axes x, y and z of the function model; n ; S102, analyzing the control instruction data of each dynamic device in the construction site, judging the current working state of each dynamic device, predicting the acceleration change of each dynamic device according to the control instruction, and calculating the acceleration change of each dynamic device according to the mathematical functions g1, g2, ..., g n Determine the movement path of each dynamic device; The specific implementation process of step S30 includes: S301, when the drone is flying, collects video image data of surrounding objects, uses a convolutional neural network to classify and identify the collected video image data, determines the dynamic device and device type i, and determines the mathematical function g of the device type i during the motion process i ; Wherein, i = 1, 2, ..., n; S302: Determine the current moving speed and direction of the dynamic device i The current spatial coordinate point position information (x0, y0, z0), substitute (x0, y0, z0) into the mathematical function g i In the above example, the motion trajectory range of the dynamic device i is determined, and the set of spatial coordinate points A within the motion trajectory range is obtained. i ; S303: Determine whether the drone passes through set A according to the planned flight path of the drone. i If it passes through, it is determined that the drone will move from the current position to the set A. i The flight path of the spatial coordinate point is obtained, and step S205 is executed; S304: Predict the direction of the drone from the current position to the set A based on the current flight speed of the drone. i The time required for the spatial coordinate point to be calculated is t0; the collected control instruction data is analyzed to determine the current working task type of the dynamic device i, and the acceleration change of the dynamic device i from 0 to t0 is obtained. Get the speed change of dynamic device i from 0 to t0 and the changes in motion trajectory According to the calculation formula: Where t represents the timestamp, t∈[0, t0]; ε and u represent the integral variables; S305: Based on the current spatial coordinate point position information (x0, y0, z0) of the dynamic device i and the change of the motion trajectory and the mathematical function g i , determine the motion curve of dynamic device i over time t, and obtain the location information of dynamic device i at time t0 And judge whether the drone will collide with dynamic device i according to the volume occupied by dynamic device i; if there is no collision, continue to fly along the flight path; if there is a collision, according to the volume size and motion trajectory changes of dynamic device i Replan the flight path to avoid the problem; After arriving at the safety monitoring point, the drone collects video image data of the safety monitoring point and simulates and displays it in the established metaverse model; when safety hazards are found, the site with safety hazards is marked in the metaverse model, and managers can determine the site with safety hazards by checking the metaverse model.

2. A construction safety intelligent management system based on big data, using the construction safety intelligent management method based on big data as claimed in claim 1, characterized in that: The system includes a data acquisition and transmission module, a drone control module, a safety intelligent analysis module, a safety alarm module and an interactive display module; The data acquisition and transmission module is used to collect control instruction data of various dynamic equipment in the construction site; the drone control module is used to control the drone to perform safe cruising and collect video image data of safety monitoring points at the construction site; the safety intelligent analysis module is used to establish a metaverse model of the construction site and conduct risk assessment of the construction site; the safety alarm module is used to issue safety alarms for construction sites with safety hazards; the interactive display is used to display the collected video image data and mark the sites with safety hazards in the video image data.

3. According to the big data-based intelligent construction safety management system of claim 2, it is characterized by: The data acquisition and transmission module includes a construction equipment management unit and a command data acquisition unit; The construction equipment management unit is used to interconnect with various dynamic devices in the form of the Internet of Things and record the working status of each dynamic device; the dynamic device represents an electrical device whose position may change during the construction process; The command data acquisition unit is used to collect control command data of various dynamic devices in the construction site, and send the collected command data to the drone control module.

4. According to the big data-based intelligent construction safety management system of claim 3, it is characterized by: The drone control module includes a path planning unit, a video image data acquisition unit, an intelligent analysis unit and an automatic avoidance control unit; The path planning unit is used to plan the flight path of the UAV based on the construction site and safety monitoring points that are managed with safety and intelligence; The video image data acquisition unit is used to collect video image data of surrounding objects during the flight of the drone; when the drone arrives at a safety monitoring point, the video image data of the safety monitoring point is collected; The intelligent analysis unit is used to classify and identify the collected video image data using a convolutional neural network, determine the dynamic device and device type, and determine the mathematical function of the device during the movement process; analyze the acceleration change, speed change and movement trajectory change of the dynamic device; The automatic avoidance control unit is used to determine whether the drone will collide with the dynamic device according to the volume occupied by the dynamic device; if there is no collision, continue to fly along the flight path; if there is a collision, re-plan the flight path to avoid it according to the volume size and motion trajectory changes of the dynamic device.

5. The intelligent construction safety management system based on big data according to claim 4 is characterized by: The security intelligent analysis module includes a model building unit and a risk assessment unit; The model building unit is used to build a metaverse model about the construction site; collect environmental data and video data of the construction site, and deploy the same metaverse environment as the construction site in the metaverse model according to the collected data; The risk assessment unit is used to perform risk assessment on safety monitoring points based on the collected video image data to determine whether there are safety hazards.

6. The intelligent construction safety management system based on big data according to claim 5 is characterized by: The interactive display module includes a video image display unit and a risk marking unit; The video image display unit is used to simulate and display the collected security monitoring point video image data in the established metaverse model; The risk marking unit is used to mark sites with potential safety hazards in the metaverse model, and management personnel can determine sites with potential safety hazards by viewing the metaverse model.

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