362 results about "Construction site safety" patented technology

The invention discloses a construction site safety risk intelligent assessment method and system, and belongs to the technical field of engineering supervision. The method comprises the following steps: S100, collecting multi-source data including an equipment state, an image video, a personnel state, an equipment distance, an environment parameter and an engineering text in real time; s200, performing space-time alignment, preprocessing and cross-modal feature fusion on the multi-source data; s300, outputting a risk score and a risk level label based on the dynamic risk knowledge graph and a multi-model fusion algorithm; s400, generating a hierarchical disposal strategy according to the risk scoring hierarchy, and realizing risk closed-loop management and control through rectification verification and cooperation of multiple parties; and S500, outputting a three-dimensional visual risk distribution map and a compliance report. Through technologies of multi-source data fusion, dynamic risk mapping knowledge, intelligent closed-loop management and the like, comprehensive perception, accurate evaluation, efficient management and control and compliance landing of engineering supervision safety risks are realized, the occurrence rate of safety accidents is remarkably reduced, and reliable technical support is provided for intelligent construction site construction.

The invention discloses a construction site safety risk intelligent early warning system and method based on BIM and big data analysis, relates to the technical field of building engineering construction safety, and solves the problem that it is difficult to transmit construction site multi-source data which is collected and preprocessed in real time in real time and carry out space mapping with a BIM model. A rule engine is difficult to carry out initial early warning; a machine learning model is difficult to analyze time series data, predict collapse risks and identify dangerous behaviors; a risk prediction model is difficult to construct and is difficult to integrate into a BIM model; and pushing and closed-loop management are difficult to carry out on the risk early warning information. According to the method, the multi-source data is collected at the construction site, the digital twinborn scene is constructed by mapping the multi-source data to the BIM model by means of space-time alignment, the multi-source data is analyzed and processed by applying technologies such as a rule engine and a machine learning algorithm, and the result is integrated to the BIM model, so that visual risk monitoring and early warning are realized.

The invention discloses a building construction safety risk assessment method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: constructing a neural network model, and recognizing an unsafe behavior mode of a worker; receiving a data stream from a construction site in real time, dynamically adjusting risk assessment parameters according to a current construction state and environment change, and predicting potential safety risks; according to the prediction result, generating corresponding prevention measure suggestions; key indexes and abnormal conditions are displayed through a monitoring interface, and a detailed analysis report is generated; according to the invention, through dynamic assessment and timely response to the safety risk of the construction site, the risk assessment parameters can be rapidly adjusted according to the environmental change, the potential risk can be predicted, and the prevention measures and suggestions can be provided, so that the occurrence probability of safety accidents is effectively reduced, and the construction efficiency is improved.

The invention discloses a railway intelligent construction site safety penetration type management messenger platform which comprises a multi-modal data fusion processing module, an edge computing node cluster module, a three-dimensional visual penetration type management interface module, an intelligent early warning and emergency response module, a self-adaptive network transmission module and the like. Real-time cleaning, alignment and correlation analysis are realized by using a dynamic data calibration algorithm, and a data island is broken; the edge computing node cluster carries out localization preprocessing and the like on data in a key area, so that the load of a central server is reduced; the three-dimensional visual interface is based on a digital twinborn construction model, supports drilling type viewing and realizes three-dimensional monitoring; the intelligent early warning system adopts a reinforcement learning model to automatically trigger multi-channel early warning; and the adaptive network transmission module dynamically switches communication modes to ensure low-delay transmission of key data. The platform realizes real-time acquisition and integration of construction site data and reduces manual intervention.

The invention discloses a construction site safety early warning method and system based on multi-dimensional data mining, and relates to the technical field of construction site early warning, and the method comprises the steps: collecting and preprocessing multi-dimensional data, and forming a multi-dimensional data set; performing feature extraction on the multi-dimensional data set by using a convolutional neural network, and fusing time sequence information through a space-time dynamic weighting mechanism to generate a multi-dimensional risk feature set; based on the multi-dimensional risk feature set, the risk features are converted into nodes, the incidence relation between the risk features is converted into edges, a causal correlation structure of the nodes and the edges is formed, and a dynamic risk map is constructed; analyzing the association strength among the risk factors by using the dynamic risk map, evaluating the overall risk level, and generating a risk event list; performing trend prediction on the risk events in the risk event list based on the time sequence to obtain a risk trend index; and performing dynamic early warning according to the risk trend index, and triggering a safety response. According to the invention, through multi-dimensional data mining and analysis, intelligentization of construction site safety early warning is realized.

The invention discloses an edge calculation method and system applied to construction site safety management. The method comprises the following steps: S1, collecting and preprocessing multi-modal data; s2, extracting and sharing risk features, and generating a preliminary risk feature map; s3, generating a local abnormal projection result by using a distributed high-dimensional abnormal mode projection module, and splicing to form a high-dimensional risk feature curved surface; s4, monitoring the data flow by using a dynamic event sensing module, identifying a high-risk event and outputting a high-risk event mark; s5, calling a dynamic risk weight tree search algorithm in a path optimization module to generate a dynamic security path; s6, generating a local risk prediction result by using the space-time hybrid prediction model; s7, generating a global dynamic prediction result through a layered space-time cooperation mechanism; and S8, providing real-time risk early warning and path optimization suggestions for construction management personnel through the mobile terminal. According to the invention, edge calculation and artificial intelligence technologies are combined, so that construction site dynamic risk identification and safety management are realized.

The invention discloses a construction site unsafe behavior detection method and system based on image recognition, and relates to the technical field of intelligent visual safety monitoring, and the method comprises the steps: collecting a construction image containing a constructor, carrying out the rectangular frame labeling of unsafe behaviors in the construction image, and generating a structured labeling data set; inputting the structured annotation data set into a YOLOv5 target detection model, performing training through Mosaic data enhancement and an adaptive anchor box generation algorithm, and outputting the trained YOLOv5 target detection model; based on the trained YOLOv5 target detection model, performing 128-dimensional feature vector extraction and track association matching on a detected target through a DeepSORT multi-target tracking algorithm, and outputting a track data table; and the recognition stability and behavior analysis depth of the system in a complex environment are enhanced, so that automation and intelligentization of safety management of a construction site are effectively supported.

The invention discloses a construction site intelligent safety management system and method based on a BIM technology, and relates to the technical field of constructional engineering, and the method comprises the following steps: S100, building a three-dimensional digital model of a construction site by using BIM software, and collecting construction site data by deploying a video camera, personnel positioning equipment and an environment sensor; s200, preprocessing the acquired data, and performing potential safety hazard identification and environment detection on the construction site; s300, fusing and displaying the generated BIM three-dimensional digital model and the processed data through spatial alignment, data mapping and dynamic updating; s400, calculating the probability of occurrence of potential safety hazards on the construction site and a comprehensive decision score; and S500, carrying out quantitative assessment on the potential safety hazards of the construction site by constructing a risk assessment model, sorting the calculated risk scores of the potential safety hazards, and determining the priority processing sequence of the potential safety hazards of the construction site, so that intelligent safety management of the construction site is realized.

The invention provides a construction site safety information supervision system based on the Internet of Things, and relates to the technical field of data processing, the risk assessment accuracy is remarkably improved and the data noise interference is inhibited through a deep reinforcement learning dynamic optimization grading early warning strategy and in combination with a multi-source data compression and federated learning framework; a risk coupling model is constructed based on a complex network theory, a conduction path and a linkage effect between regions are analyzed, a global early warning scheme is optimized, and the adaptability of the system to a complex construction environment is enhanced; the model is continuously optimized through a dynamic weight updating mechanism, high adaptability is kept under the environment change of a construction site, meanwhile, a resource dynamic allocation strategy is adopted, the problem of low high-concurrency processing efficiency is effectively solved, and the overall accident early warning accuracy is improved.

The invention belongs to the related technical field of construction safety inspection, and particularly relates to a construction site safety inspection method based on a multi-modal large language model, which comprises the following steps of: introducing the multi-modal large language model, and applying the multi-modal large language model for multiple times in combination with a knowledge base containing safety standard specifications and evaluation rules to obtain a construction site safety inspection result. The method specifically comprises the following steps: obtaining image content description through an image and a preset visual perception system prompt text; intelligently decomposing user input query into a plurality of sub-query tasks through user input query, image content description and preset task decomposition system prompt; searching construction safety management standard data related to each sub-query from the construction safety knowledge base, and analyzing and reasoning the sub-query based on the image content description in combination with the searched standard data to obtain the reasoning and conclusion of the sub-query; and finally, obtaining a total reasoning and conclusion based on each sub-query data. The method can accurately, scientifically and comprehensively realize the safety inspection of the construction site.

The invention provides an intelligent management and control system for real-time monitoring and early warning of construction site safety risks. The intelligent management and control system comprises a data acquisition module, a data preprocessing module, a risk identification module, a risk assessment module and an early warning and management and control module. According to the invention, through deep fusion of multi-module cooperation and multi-algorithm, full-process, high-precision and intelligent management and control of the safety risk of the construction site are realized, and the construction safety management efficiency and the risk early warning capability are effectively improved.

The invention discloses an intelligent safety inspection system for a construction site, and relates to the technical field of construction inspection, multiple data sources of the construction site are obtained through a data acquisition module, and a data fusion and processing module dynamically optimizes heterogeneous data through time synchronization, format standardization and noise filtering in combination with a self-adaptive weighted fusion algorithm, so that the construction site safety is improved. The intelligent analysis and early warning module evaluates the data difference degree based on machine learning, adopts clustering analysis to mine an abnormal mode for high-difference data, carries out safety risk identification on low-difference data, and dynamically adjusts an early warning strategy. The terminal interaction module pushes the inspection result and the early warning information to the mobile terminal APP, the monitoring center display screen and the voice broadcast device, so that a manager can remotely check the construction condition and quickly make a decision, the intelligent level of construction site safety inspection can be remarkably improved, efficient and accurate potential safety hazard recognition and dynamic early warning are achieved, and the safety inspection efficiency is improved. And the safety accident risk is effectively reduced.

The invention discloses a construction site safety monitoring method and system based on a large model and RAG, and the method comprises the steps: carrying out the intelligent analysis of real-time video data of a construction region based on a visual large model, and recognizing the behavior safety, violation operation, dangerous facilities and environment risks of construction personnel; adding a time label to the analyzed security event text to form a construction site security event log; reasoning and analyzing the security event log, determining whether security early warning is generated or not, and pushing early warning information; carrying out on-site intelligent voice broadcasting according to the early warning information; through a multi-RAG architecture, a construction site safety log database, a public construction safety management database and an enterprise internal safety management database are constructed, and construction safety information is stored by using a vector database and a graph database. By adopting the technical scheme of the invention, the problems of insufficient real-time monitoring capability, limited intelligent analysis capability and lack of effective knowledge base support in the existing construction site safety supervision are solved.

The invention relates to the technical field of construction site safety early warning, in particular to a multi-modal construction site safety early warning method and system for dynamic weight allocation, and the method comprises the following steps: deploying a multi-modal data collection module, and collecting and transmitting construction site data to a central processing unit in real time; constructing a correlation model according to the historical accident database; carrying out preprocessing and anomaly detection on real-time data, and dynamically adjusting a multi-modal weight according to a result; inputting the adjusted weight into the model, calculating a comprehensive early warning score and performing graded early warning; and correcting the model according to the early warning and accident matching degree. According to the method, the multi-modal data acquisition module is deployed to acquire sensor, visual and text data, and a dynamic weight distribution mechanism is combined, so that the weight of each modal can be adjusted in real time according to an anomaly detection result, the accuracy and comprehensiveness of potential safety hazard identification are remarkably improved, and the problems of one-sidedness and missing report of single-modal monitoring are effectively avoided.

The invention discloses an intelligent construction site safety evaluation method and system based on data elements, and relates to the technical field of computer platform load balancing, and the method comprises the steps: collecting construction site multi-source heterogeneous data, and carrying out the preprocessing of the construction site multi-source heterogeneous data; constructing a safety evaluation model of time sequence modeling and graph structure fusion through combination of a long short-term memory network and a graph neural network, performing feature selection and dimension compression operation on the processed multi-source heterogeneous data of the construction site to obtain an input feature tensor, and inputting the input feature tensor into the safety evaluation model; and calculating a comprehensive score according to a model output result, and generating a classification result and data feedback through an edge node. According to the intelligent construction site safety evaluation method based on the data elements provided by the invention, combined modeling of time sequence dependence and space association is realized through a deep modeling structure fusing LSTM and GNN, and the risk identification precision under multi-source heterogeneous data is effectively improved.

The invention discloses a building construction site safety monitoring management system and method, and relates to the technical field of building construction, the method adopts a calculation model of a multi-source vibration comprehensive influence index (MVTI), a foundation pit stress distribution value (GSF) and a foundation pit stability coefficient (GSC), and multidimensional data is extracted through an embedded database for real-time analysis. The influence of different vibration sources on the stability of the foundation pit can be comprehensively evaluated based on dynamic calculation of a multi-source vibration comprehensive influence index MVTI; meanwhile, the stress distribution of vibration to a foundation soil body is refined through the foundation pit stress distribution value GSF; the foundation pit stability coefficient GSC serves as a core index and is used for comprehensively analyzing the stability state of the foundation pit. When a foundation pit stability coefficient GSC value is lower than a safety threshold value, the system generates first early warning information, calculates a monitoring point risk value RIM in combination with a multi-source vibration comprehensive influence index MVTI, and locates an abnormal area through the monitoring point risk value RIM.

The embodiment of the invention provides a mobile tower crane border crossing detection method and device. Tower crane design drawing data are imported into a virtual simulation engine, a three-dimensional model is constructed, and warning tape marks are set. A physical engine is creatively utilized to simulate tower crane moving tracks under different working conditions, and a border crossing behavior data set is generated based on intersection-to-union ratio calculation. A deep neural network structure is constructed, a trunk feature extraction module and a target detection module are included, and model parameters are optimized through a cross entropy loss function. According to the method, the limitation of traditional mechanical limiting and manual monitoring is broken through, real-time intelligent monitoring of the movable boundary of the tower crane is achieved, and reliable technical support is provided for safety management of a construction site.

The invention discloses an intelligent construction site safety control method and system based on sensor monitoring, and relates to the technical field of management monitoring. Comprising the steps of obtaining control index data, enabling the control index data to act on a monitoring device in each detection control area, obtaining historical monitoring data in each detection control area, generating a plurality of preset thresholds based on the control index data and the historical monitoring data, and obtaining real-time monitoring data in each detection control area; and based on the real-time monitoring data and a preset threshold value, generating a plurality of safety early warning schemes corresponding to the types of the detection control areas, obtaining difference data between the safety early warning schemes, and based on the types and numerical values of the difference data, adjusting the control authority of the monitoring devices in the detection control areas. According to the invention, through the combination of the real-time monitoring data and the preset threshold value, a targeted safety early warning scheme can be quickly generated, so that the efficiency and accuracy of construction site safety management are improved.

The invention relates to the technical field of construction safety assessment, and discloses a construction safety assessment method based on multi-model fusion. The method comprises the following steps: acquiring a multi-source safety monitoring data set of a construction site, wherein the multi-source safety monitoring data set covers image sequence data, sensor time sequence data and operation log text data; performing parallel feature extraction processing on the multi-source data to generate an image feature vector, a sensor feature vector and a text feature vector; calling a multi-model fusion framework to carry out cross-modal fusion processing on the three feature vectors to obtain a fusion security feature set; carrying out security risk assessment analysis based on the fused security feature set, and generating a security risk prediction value and a high-risk region identifier; and finally, generating a security policy adjustment instruction according to the risk prediction value and the high-risk area identifier, and feeding back the security policy adjustment instruction to the field control system to trigger real-time intervention operation. According to the method, a high-risk area can be recognized in time, intervention is triggered, and intelligent support is provided for safety management of a construction site.

The invention relates to the technical field of intelligent construction site safety management and Internet of Things, and discloses a construction personnel safety protection system and method for intelligent construction site safety management, and the system comprises a data collection module, a four-dimensional space-time tensor construction module, an incremental tensor decomposition module, a dynamic risk field modeling module, and a federated learning parameter updating module. A multistage safety response module; the method comprises the steps of collecting personnel data through intelligent equipment and constructing a four-dimensional tensor, extracting core features through dynamic decomposition to establish a risk propagation model, optimizing parameters in combination with federal learning, and finally triggering three-level response according to a risk field gradient to realize full-process closed-loop management and control of construction safety. According to the method, multi-modal data are fused to construct a four-dimensional tensor, incremental decomposition is carried out to extract dynamic features, a physical field model is coupled to predict risks, federated learning is used for collaborative privacy optimization, hierarchical response is carried out for closed-loop linkage control, and construction safety and precise protection and efficient emergency are realized.

The invention provides a construction site safety supervision method and system based on multi-mode intelligent perception, and relates to the technical field of highway construction supervision. A construction area is scanned through a 5G camera, multi-mode intelligent sensing data such as videos, positioning and environment sensors are fused, a three-dimensional model of a construction site is constructed, and the positions of equipment and personnel are accurately determined. Beidou positioning and safe area setting are combined, real-time safety detection is carried out, illegal intrusion of external vehicles and personnel is effectively prevented, and construction of equipment and personnel outside a safe area is avoided. According to the method, illegal behaviors of not wearing safety helmets and the like are intelligently identified by using AI, post-accident tracing is realized through the Internet of Things, accurate traffic guidance information is published in combination with Atdes and Baidu maps, the collision risk and potential safety hazards are reduced, and the safety of a highway construction site is comprehensively improved.

The invention relates to a construction site hidden danger identification method and system based on a visual language large model. The method comprises the following steps: acquiring real-time acquired image data of high-place operation on a construction site; preprocessing the image data to obtain a to-be-detected image; inputting the to-be-detected image into the construction safety visual language model to obtain a hidden danger recognition result; the hidden danger recognition result comprises a high-altitude falling safety hidden danger type and standard natural language image subtitles. By adopting the method, intelligent technical support can be provided for safety management of the construction site, and the occurrence rate of high-altitude falling accidents is effectively reduced by identifying high-altitude falling hidden dangers of the construction site and generating standardized image subtitles.

The invention discloses a construction site safety evaluation method and system, and relates to the technical field of construction site safety management. According to the construction site safety evaluation method, when a high-rise building is constructed, construction equipment data and construction environment data of a to-be-evaluated construction site are obtained in real time, data analysis is carried out respectively, and a construction equipment reliability evaluation index and a construction environment risk evaluation index are obtained; meanwhile, construction image data are obtained, image analysis is carried out, a construction behavior compliance index is obtained, comprehensive analysis is carried out in combination with a construction equipment reliability evaluation index and a construction environment risk evaluation index, and a construction safety evaluation index is obtained; compared with the prior art, the construction safety evaluation index and the preset construction safety evaluation index threshold value are compared and analyzed, and the corresponding construction management measures are taken based on the comparison and analysis result, so that the synergistic effect of the multi-dimensional data is comprehensively evaluated, and the safety of the construction site is accurately evaluated.

The invention relates to the technical field of artificial intelligence, and provides a construction site safety detection method, device and equipment and a medium, which can utilize a mobile wearable portable camera to collect real-time images of a target construction site so as to provide comprehensive site pictures; the real-time image and the building information model are aligned according to the external parameters of the camera, it is ensured that follow-up detection is conducted on the same view angle and pixel, and the detection accuracy is improved; an improved Transform network architecture is used for carrying out difference detection on a real-time picture frame and a building information model frame, and the problems that manual inspection is not high in accuracy and low in efficiency are solved; and mapping the difference mask to a three-dimensional engineering coordinate system of the building information model according to the external parameters of the camera and the depth map of the real-time image to obtain a three-dimensional coordinate point, and identifying a difference component and generating a three-dimensional thermodynamic diagram according to the three-dimensional coordinate point so as to realize comprehensive, accurate and efficient safety detection of the target construction site.

The invention provides a railway tunnel construction safety risk management and control comprehensive early warning method based on controllability. The method comprises the following steps: constructing a railway tunnel construction safety risk management and control comprehensive early warning platform; the railway tunnel construction safety risk management and control comprehensive early warning platform comprises a construction safety risk state evaluation module based on monitoring measurement, a safety risk management and control level evaluation module based on hidden danger investigation and a safety risk management and control comprehensive early warning evaluation module based on correlation analysis. According to the method, on the basis of risk identification and risk assessment, the view of improving the safety risk management and control level is focused on, and on the basis of collecting normal operation data of safety management work of a construction site, a safety risk comprehensive early warning decision model based on risk controllability is constructed; problems and deficiencies in construction safety risk management are found in time and early warning is carried out, potential safety hazards are eliminated fundamentally, accidents are prevented, and decision support is provided for formulating a more targeted risk grading management and control scheme.

The invention discloses a construction hidden danger automatic detection method and system based on point cloud and image multi-mode. The method comprises the following steps: step 1, acquiring point cloud data and RGB image data and respectively preprocessing the point cloud data and the RGB image data; 2, safety equipment detection is carried out by establishing an improved YOLOv5 model; establishing a 3D-CNN model to qualitatively judge the abnormal behavior of the personnel; 3, combining a semantic segmentation model and point cloud data processing to carry out quantitative judgment of height calculation and coordinate conversion of the fence; and 4, realizing three-dimensional live-action model reconstruction based on point cloud feature matching, Poisson surface reconstruction and GPU rendering, and detecting potential safety hazards of a construction site. The accuracy of qualitative detection is further improved, the precision error of quantitative detection is reduced, the recognition efficiency and precision of potential safety hazards are greatly improved, intelligent and all-around guarantee is provided for safety management of a construction site, remote decision is assisted, the management cost is reduced, and the method is suitable for various construction scenes.

The invention discloses a building construction safety monitoring system based on the Internet of Things technology, and the system comprises the following steps: collecting various types of data of construction personnel, equipment and environment, constructing a unified data sequence, extracting feature information through employing an incremental principal component analysis method, and further employing an elliptical envelope line algorithm by the system, the method comprises the following steps: establishing an anomaly discrimination model in a plurality of local feature spaces, realizing the recognition of abnormal behaviors, integrating noise suppression processing and a dynamic parameter updating mechanism by a system, improving the monitoring accuracy and adaptive ability, combining the states of personnel, equipment and environment on a construction site, generating a corresponding risk level and an early warning control instruction by the system, and improving the early warning efficiency. Real-time risk identification and response linkage is realized, and the safety guarantee level of a construction site is improved. The method has the key characteristics of multi-source data fusion, boundary adaptive updating, risk response linkage and the like, and intelligent monitoring and dynamic intervention of construction site risks are realized.

The present invention belongs to the field of construction site safety technology, specifically a construction site construction safety assessment system, the system includes: a scene reconstruction design module, a data perception module, a data communication module and a data processing module. The present invention has the beneficial effects of being able to realize real-time, accurate and comprehensive data collection and transmission of construction sites, improving the data quality and timeliness of construction safety assessments; being able to realize clear, intuitive and dynamic scene reconstruction and display of construction sites, improving the visualization and interactivity of construction safety assessments; being able to realize scientific, objective and consistent risk analysis and assessment of construction sites, improving the systematicness and reliability of construction safety assessments; being able to realize efficient, accurate and intelligent design and construction optimization and adjustment of construction sites, improving the optimization and automation of construction safety assessments.

The application relates to the technical field of artificial intelligence, and provides a construction site safety detection method, device, equipment and medium, which can collect real-time images of a target construction site by using a mobile wearable portable camera to provide comprehensive site pictures; the real-time images and a building information model are aligned according to camera external parameters, so that subsequent detection is carried out on the same visual angle and pixels, and the accuracy of detection is improved; the improved Transformer network architecture is used for difference detection of real-time picture frames and building information model frames, so that the problem of low accuracy and low efficiency of artificial inspection is solved; the difference mask is mapped to a three-dimensional engineering coordinate system of the building information model according to the camera external parameters and a depth map of the real-time images to obtain three-dimensional coordinate points, and the difference components are identified according to the three-dimensional coordinate points and a three-dimensional heat map is generated, so that comprehensive, accurate and efficient safety detection of the target construction site is realized.

The invention belongs to the technical field of environment state monitoring, and particularly relates to a construction site environment state monitoring method based on satellite images and unmanned aerial vehicle data, which comprises the following steps: acquiring satellite image monitoring information and unmanned aerial vehicle monitoring information of a construction site environment state; performing construction site environment surface coverage change analysis, and outputting construction site environment change characteristics; on the basis of a portable PM2.5 monitor arranged on a construction site, PM2.5 concentration characteristics are obtained; performing construction site equipment YOLO target detection, outputting an equipment distribution thermodynamic diagram, and determining construction progress characteristics of a construction site; constructing a construction site safety risk framework, and determining a construction site safety risk level; and determining a construction site environment state monitoring grade. According to the invention, through fusion of satellite images and unmanned aerial vehicle data, comprehensive and dynamic monitoring of the construction site environment state is realized, the monitoring precision and efficiency are improved, and powerful support is provided for scientific management of the construction site.