Intelligent construction site supervision method and device under multi-source data fusion, medium and equipment

Abstract

The application relates to a smart construction site supervision method and device based on multi-source data fusion, a medium and equipment, and relates to the technical field of construction site supervision. The method comprises the following steps: through a preset multi-source data fusion algorithm, monitoring video data, environmental data and construction personnel positioning data are fused and processed to obtain current operation state information corresponding to a to-be-supervised construction site; when a monitoring interface viewing instruction sent by a terminal of a construction site manager is received, based on the current operation state information, a real-time monitoring interface corresponding to the to-be-supervised construction site is generated and displayed in the terminal; when a construction site early warning viewing instruction sent by the terminal of the construction site manager is received, the current operation state information is input into a preset construction site operation state prediction model to obtain safety early warning information corresponding to the to-be-supervised construction site, and the safety early warning information is sent to the terminal. The application has the effect of improving the comprehensiveness of construction site supervision.

Description

Technical Field

[0001] This application relates to the field of construction site supervision technology, specifically to a smart construction site supervision method, device, medium, and equipment based on multi-source data fusion. Background Technology

[0002] Multi-source data fusion refers to the technology of integrating and merging data from different sources and formats, aiming to create a more comprehensive, accurate, and insightful dataset for effective analysis and utilization. With the rapid development of the construction industry, the complexity and difficulty of construction site supervision are constantly increasing. Construction site supervision is crucial for construction safety, involving multiple aspects such as accident prevention, risk assessment, emergency response, improving project quality, and economic benefits. Good construction site management ensures that safety procedures and operating standards are strictly implemented on construction sites, reduces potential hazards, and improves workers' safety awareness. To address this challenge, many construction companies have begun to explore and implement the concept of smart construction sites to improve management efficiency and ensure project quality and safety. Smart construction sites refer to an engineering management model that utilizes advanced information technologies, such as the Internet of Things (IoT), to monitor and analyze construction sites in real time.

[0003] Currently, construction site supervision typically involves using various sensors and cameras as data sources to acquire sensor and monitoring data from the construction site. This data is then processed and analyzed through a traditional construction site management system to monitor the construction site. However, this traditional system can only process data from a single source, resulting in poor comprehensiveness in construction site supervision. Summary of the Invention

[0004] To improve the comprehensiveness of construction site supervision, this application provides a smart construction site supervision method, device, medium, and equipment based on multi-source data fusion.

[0005] The first aspect of this application provides a smart construction site supervision method based on multi-source data fusion, specifically including:

[0006] Acquire surveillance video data of each construction area in the construction site to be supervised, and acquire environmental data and location data of construction personnel of the construction site to be supervised;

[0007] By using a preset multi-source data fusion algorithm, the monitoring video data, the environmental data, and the construction personnel location data are fused to obtain the current operational status information of the construction site to be monitored.

[0008] When a monitoring interface viewing instruction is received from the terminal of the construction site manager, a real-time monitoring interface corresponding to the construction site to be monitored is generated based on the current operation status information and displayed on the terminal.

[0009] When a site management personnel receives a site warning viewing instruction from their terminal, the current operational status information is input into a preset site operational status prediction model to obtain the safety warning information corresponding to the site to be monitored, and the safety warning information is sent to the terminal.

[0010] By adopting the above technical solution, after acquiring the monitoring video data, environmental data, and construction worker location data of the construction site to be monitored, a multi-source data fusion algorithm is used to fuse the data from the three sources, thereby obtaining information that more comprehensively reflects the operational status of the construction site, namely, the current operational status information. Furthermore, when site managers want to view a visual overview of the entire construction site's operation, the current operational status information is used to generate a real-time monitoring interface for the construction site to be monitored and displayed on the site managers' terminals. When site managers want to understand the site's safety warning information, the construction site operational status prediction model uses the current operational status information to predict future operational status information and determine safety warning information, thus enabling site managers to have a more comprehensive understanding of the construction site's supervision.

[0011] Optionally, acquiring the monitoring video data of each construction area in the construction site to be monitored specifically includes:

[0012] The system acquires the target construction operations of construction workers in each construction area of ​​the construction site to be monitored. If the target construction operation is a non-standard construction operation, the system controls the preset camera in the corresponding construction area to switch from normal recording mode to target recording mode. The target recording mode is a mode that makes it easy to observe the details of the monitoring video.

[0013] The construction procedures performed by the construction personnel corresponding to the target construction operation are identified as potential construction procedures, and based on these potential construction procedures, the associated potential quality hazards are identified.

[0014] Determine whether there is any induced environmental data in the environmental data that could cause the potential quality hazard of the target. If so, determine the duration of the target recording mode based on the level of influence of the induced environmental data on the potential quality hazard of the target. The greater the level of influence, the longer the duration.

[0015] After the specified duration, the camera is controlled to switch from the target recording mode to the normal recording mode to obtain the corresponding monitoring video data of the construction area.

[0016] By adopting the above technical solution, if the target construction operation is a non-standard operation that may cause potential quality hazards in the corresponding construction process, switching to the target recording mode makes it easier for subsequent personnel to observe video details. Furthermore, based on this potentially hazardous construction process, the associated target quality hazards are identified; that is, this hazardous construction process is highly likely to cause construction quality hazards in the construction area. Finally, based on the impact level of the environmental data inducing the target quality hazard, the duration of the target recording mode is determined, thereby recording as many details leading to the target quality hazard as possible in the target recording mode. This facilitates tracing the cause of quality problems if they subsequently occur in the construction area.

[0017] Optionally, obtain the historical quality hazards generated by the construction process with potential hazards, count the first occurrence number of each historical quality hazard, and select the first historical quality hazard from the historical quality hazards in descending order of the first occurrence number and determine it as a potential hazard.

[0018] Obtain the historical non-standard construction operations in the construction process of each potential hidden danger when it occurs, count the second occurrence number of each historical non-standard construction operation, and select the second number of historical non-standard construction operations from each historical non-standard construction operation in descending order of the second occurrence number to determine the corresponding potential hidden danger-prone non-standard operation.

[0019] The potential hazards that are likely to occur in the target construction operation in the corresponding non-standard operation are identified as key quality hazards. The weighted product of the first weight of each key quality hazard and the second weight of the corresponding target construction operation is calculated. The first weight is the ratio of the first occurrence of each key quality hazard to the sum of the first occurrences of all potential hazards. The second weight is the ratio of the second occurrence of the target construction operation corresponding to each key quality hazard to the sum of the second occurrences of all the corresponding non-standard operations.

[0020] Select the largest weighted product from all the weighted products, and determine the key quality hazard corresponding to the largest weighted product as the associated target quality hazard.

[0021] By adopting the above technical solution, the greater the frequency of occurrence of the first occurrence, the more likely a corresponding historical quality hazard will arise once a non-standard construction operation occurs in this hidden danger construction process; the greater the frequency of occurrence of the second occurrence, the more likely a potential hazard will arise when a corresponding historical non-standard construction operation occurs in the hidden danger construction process. Furthermore, the potential hazards of the target construction operation within the corresponding potential non-standard operations are identified as key quality hazards, that is, quality hazards that the target construction operation is likely to cause in the corresponding construction area. The weighted product of the first weight of each key quality hazard and the second weight of the corresponding target construction operation is calculated. The larger the weighted product, the more likely the non-standard target construction operation is to lead to the corresponding key quality hazard. Finally, the key quality hazard corresponding to the largest weighted product is identified as the target quality hazard associated with this target construction operation, thereby accurately determining the most likely quality hazard to occur when the target construction operation is non-standard.

[0022] Optionally, the method further includes:

[0023] Establish a correspondence between the duration of the target recording mode in the monitoring video data corresponding to each construction area and the corresponding target quality hazard to obtain the corresponding time period matching table;

[0024] When a target quality problem occurs in the construction area, identify the associated quality hazards of the target quality problem, and determine the association level between each associated quality hazard and the target quality problem;

[0025] The construction area corresponding to the target quality problem is determined as the target construction area. The target duration period corresponding to the associated quality hazard is matched from the time period matching table corresponding to the target construction area. According to the association level of the associated quality hazard in descending order, the video segments of the corresponding target duration period are extracted from the monitoring video data corresponding to the target construction area and sent to the terminal.

[0026] By adopting the above technical solution, the time period matching table corresponding to the target construction area is selected from various time period matching tables, and the target duration period corresponding to each associated quality hazard is matched from it. That is, the monitoring video data is likely to record the duration period of the video details that produce the corresponding associated quality hazard. Finally, according to the order of the association level of the associated quality hazard that matches the target duration period from large to small, the video segments of the corresponding target duration period are extracted sequentially from the monitoring video data corresponding to the target construction area and sent to the terminal of the site management personnel, thereby enabling efficient and accurate investigation of the cause of the target quality problem.

[0027] Optionally, the method further includes:

[0028] If a target construction platform exists in the construction area, then create a target finite element model corresponding to the target construction platform;

[0029] Based on the target finite element model, the associated location points of the target location point in the target construction platform are determined. The target location point is the construction operation location point in the target construction platform, and the associated location point is the location point in the target construction platform where the stress increases when the number of construction personnel at the target location point changes.

[0030] Based on the stress values ​​of each associated location point corresponding to each target location point and the importance level of the stability of the target construction platform structure, the influence value of the corresponding target location point on the stability of the target construction platform structure is determined.

[0031] If the impact value is greater than the preset impact value threshold, a safety warning will be issued for the target construction platform when the actual change in the number of construction workers at the corresponding target location point is the target change.

[0032] By employing the aforementioned technical solution, a target finite element model corresponding to the target construction platform is created, thus intuitively reflecting the stress conditions at various locations on the target construction platform. Next, based on the target finite element model, the associated location points of each target location are determined, thereby identifying the associated location points that may affect the structural stability of the target construction platform. Then, based on the stress values ​​of each associated location point and its importance level to the structural stability of the target construction platform, the degree of impact on the structural stability of the target construction platform when a change occurs at the target location point is analyzed. If the impact value is greater than the impact threshold, it indicates that after a change in the number of construction workers at the corresponding target location point, the structure of the target construction platform is significantly affected by stress and is highly susceptible to instability. Therefore, when the actual change in the number of construction workers at the corresponding target location point constitutes a change in the target, a safety warning is issued, thereby improving the construction safety on the target construction platform.

[0033] Optionally, determining the influence value of the corresponding target location point on the stability of the target construction platform structure based on the stress value of each associated location point corresponding to each target location point and the importance level of the stability of the target construction platform structure specifically includes:

[0034] Substituting the stress value of each associated location point corresponding to the same target location point and the importance level of the target construction platform structure to the preset stress value weight calculation formula, the stress value weight of the corresponding associated location point is obtained. The stress value weight calculation formula is as follows:

[0035]

[0036] In the formula, This indicates the stress value weight of the associated location points. This indicates the importance level of location points other than associated location points, and S represents the stability of the target construction platform structure itself. Both β and β represent two positive real-valued parameters;

[0037] Calculate the product of the stress value of each of the associated locations of each target location and the corresponding stress value weight, and sum them to obtain the influence value of the corresponding target location on the stability of the target construction platform structure.

[0038] By adopting the above technical solution, after calculating the stress value weight of each associated location point corresponding to a single target location point according to the stress value weight calculation formula, the product of the stress value and the stress value weight of each associated location point is calculated and summed to obtain the impact value of the target location point on the stability of the target construction platform structure after the target changes. The larger the impact value, the greater the impact of the increase in stress at each associated location point on the stability of the target construction platform structure, and the greater the risk of the target construction platform becoming unstable.

[0039] Optionally, when the actual change in the number of construction workers at the corresponding target location point constitutes a target change, a safety warning is issued for the target construction platform, specifically including:

[0040] When the actual change in the number of construction workers at the corresponding target location point is the target change, determine the departure time of the construction workers leaving the target construction platform;

[0041] The number of construction workers whose absence time exceeds a preset time threshold is counted, and the warning time is determined based on the number of construction workers. The larger the number of construction workers, the longer the corresponding warning time.

[0042] A safety warning is issued for the specified duration for the target construction platform.

[0043] By adopting the above technical solution, if the departure time exceeds the preset time threshold, it indicates that once the target construction platform becomes unstable, the corresponding construction personnel will have a longer time to escape, resulting in a higher safety risk. Furthermore, the number of construction personnel whose departure time exceeds the time threshold is counted, and a corresponding warning time is matched according to the number of construction personnel. The larger the number of construction personnel, the greater the safety risk once the target construction platform becomes unstable, and the longer the corresponding warning time. Finally, a safety warning for the target construction platform is issued for the specified warning time, thereby improving the construction safety on the target construction platform.

[0044] A second aspect of this application provides a smart construction site monitoring device based on multi-source data fusion, specifically including:

[0045] The data acquisition module is used to acquire monitoring video data of each construction area in the construction site to be supervised, as well as environmental data and location data of construction personnel in the construction site to be supervised.

[0046] The status determination module is used to fuse the monitoring video data, the environmental data, and the construction personnel location data through a preset multi-source data fusion algorithm to obtain the current operating status information of the construction site to be monitored.

[0047] The monitoring and viewing module is used to generate a real-time monitoring interface for the construction site under supervision and display it on the terminal based on the current operation status information when it receives a monitoring interface viewing instruction sent by the terminal of the construction site manager.

[0048] The construction site early warning module is used to input the current operation status information into a preset construction site operation status prediction model when it receives a construction site early warning viewing instruction sent by the terminal of the construction site manager, to obtain the safety early warning information corresponding to the construction site to be monitored, and to send the safety early warning information to the terminal.

[0049] By adopting the above technical solution, the data acquisition module acquires monitoring video data, environmental data, and construction personnel location data. The status determination module, based on a multi-source data fusion algorithm, fuses the monitoring video data, environmental data, and construction personnel location data to obtain the current operating status information. Then, the monitoring and viewing module generates a real-time monitoring interface based on the current operating status information and displays it on the terminal. Finally, the construction site early warning module inputs the current operating status information into the construction site operating status prediction model to obtain safety early warning information.

[0050] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when loaded and executed by a processor, performs the steps of the method described in any one of the first aspects.

[0051] A fourth aspect of this application provides an electronic device, specifically comprising:

[0052] A processor, a memory, and a computer program stored in the memory and capable of running on the processor, the processor being configured to load and execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of the first aspects.

[0053] In summary, this application includes at least one of the following beneficial technical effects: After acquiring the monitoring video data, environmental data, and construction worker location data corresponding to the construction site to be monitored, a multi-source data fusion algorithm is used to fuse the data from the three sources, thereby obtaining information that more comprehensively reflects the operational status of the construction site, namely, the current operational status information. Furthermore, when construction site managers want to view a visual overview of the entire construction site's operation, the current operational status information is used to generate a real-time monitoring interface for the construction site to be monitored and displayed on the managers' terminals. When construction site managers want to understand the site's safety warning information, the construction site operational status prediction model is used to predict future operational status information based on the current operational status information and determine safety warning information, thereby enabling construction site managers to have a more comprehensive understanding of the construction site's supervision. Attached Figure Description

[0054] Figure 1 This is a flowchart illustrating a smart construction site supervision method based on multi-source data fusion provided in an embodiment of this application.

[0055] Figure 2 This is a flowchart illustrating another smart construction site supervision method based on multi-source data fusion provided in this application embodiment;

[0056] Figure 3 This is a schematic diagram of the structure of a smart construction site monitoring device based on multi-source data fusion provided in an embodiment of this application;

[0057] Figure 4 This is a schematic diagram of another smart construction site monitoring device based on multi-source data fusion provided in this application embodiment.

[0058] Explanation of reference numerals in the attached diagram: 11. Data acquisition module; 12. Status determination module; 13. Monitoring and viewing module; 14. Construction site early warning module; 15. Problem investigation module; 16. Platform early warning module. Detailed Implementation

[0059] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0060] In the description of the embodiments in this application, words such as "illustrative," "for example," or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "illustrative," "for example," or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of words such as "illustrative," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0061] In the description of the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, B existing alone, or A and B existing simultaneously. Furthermore, unless otherwise stated, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and their variations all mean "including but not limited to," unless otherwise specifically emphasized.

[0062] See Figure 1 This application discloses a flowchart illustrating a smart construction site monitoring method based on multi-source data fusion. This method can be implemented using a computer program or run on a smart construction site monitoring device based on multi-source data fusion using the von Neumann architecture. The computer program can be integrated into an application or run as a standalone tool application, specifically including:

[0063] S101: Obtain surveillance video data of each construction area in the construction site to be supervised, and obtain environmental data and location data of construction personnel in the construction site to be supervised.

[0064] Specifically, in this embodiment, the construction site to be monitored refers to a construction site related to building engineering and whose construction status is monitored in real time, such as civil building engineering (apartment buildings, schools, etc.) and industrial building engineering (factory buildings, industrial facilities, etc.). In other embodiments, the construction site to be monitored may also be a construction site related to hydraulic engineering. The construction site to be monitored includes at least one construction area, which may be a building under construction containing a construction platform. The construction platform is a temporary structure erected to provide working space for construction workers. The construction platform may be a scaffolding construction platform or a steel pipe material construction platform. In other embodiments, the construction area may also be inside the building under construction.

[0065] Furthermore, this application discloses a smart construction site supervision method based on multi-source data fusion, in which the execution entity is a server. The server can be an independent physical server, a server cluster composed of multiple physical servers, or a distributed system. One feasible way to obtain information about the construction site to be supervised is as follows: the server acquires corresponding monitoring video data through pre-set cameras in each construction area. Specifically, for each construction area in the construction site to be supervised, during monitoring via cameras, a pre-set action recognition model identifies the target construction operation of the construction worker from the real-time monitoring video. If the similarity between the target construction operation and the standard construction operation is lower than a similarity threshold, the target construction operation is determined to be a non-standard construction operation, which may cause quality hazards in the corresponding construction process. The method for determining the similarity is as follows: the target construction operation and the standard construction operation are mapped to a high-dimensional vector space to obtain corresponding vectors, and then the cosine value between the two vectors is calculated and determined as the similarity. The camera in this construction area is then switched from normal recording mode to target recording mode for monitoring. Target recording mode is a mode that makes it easier to observe the details of the monitoring video. In this embodiment, the target recording mode can be a slow recording mode, and in other embodiments, it can be a high-resolution recording mode, so that it is easier for subsequent personnel to observe the video details.

[0066] Furthermore, by using Building Information Modeling (BIM) technology to pre-establish a BIM model corresponding to the construction site under supervision, the construction sequence of the construction personnel corresponding to the target construction operation is determined, and this sequence is identified as a potential hazard—that is, a construction sequence that could lead to quality defects in the corresponding construction area. Further, based on this potential hazard, associated target quality defects are identified. These target quality defects are those that the potential hazard construction sequence is highly likely to cause quality defects in the construction area. One feasible method is to filter historical quality defect records for this construction area to identify those caused by the potential hazard construction sequence, and count the first occurrence frequency of each historical quality defect. The higher the first occurrence frequency, the more likely a corresponding historical quality defect will occur if a non-standard construction operation occurs in this potential hazard construction sequence. Finally, based on the order of the first occurrence frequency from largest to smallest, the historical quality defect with the highest occurrence frequency is selected and identified as a potential defect.

[0067] Furthermore, by analyzing historical monitoring videos of construction procedures that were prone to potential hazards in the construction area, we identified historical non-standard construction operations that had occurred during these procedures. Then, we counted the number of times each historical non-standard operation occurred; the higher the number of times the corresponding historical non-standard operation occurred, the more likely a potential hazard would arise. Finally, based on the number of times the second occurrence occurred, we selected the second-highest number of historical non-standard operations as the most likely to trigger a hazard—that is, the historical non-standard operation that, when it occurs, is most likely to induce the corresponding hazard. It should be noted that each potential hazard corresponds to at least one such easily-caused non-standard operation.

[0068] Furthermore, the potential hazards arising from the target construction operation within the corresponding non-standard operations are identified as key quality hazards; that is, the quality hazards that the target construction operation is likely to cause in the corresponding construction area. Next, the first weight of each key quality hazard and the second weight of the corresponding target construction operation are calculated. The first weight is the ratio of the first occurrence frequency of each key quality hazard to the sum of the first occurrence frequencies of all potential hazards. The second weight is the ratio of the second occurrence frequency of the target construction operation corresponding to each key quality hazard to the sum of the second occurrence frequencies of all corresponding non-standard operations. Then, the weighted product of the first weight of each key quality hazard and the second weight of the corresponding target construction operation is calculated. The larger the weighted product, the more likely the non-standard target construction operation is to lead to the corresponding key quality hazard. Finally, the key quality hazard corresponding to the largest weighted product is identified as the target quality hazard associated with this target construction operation.

[0069] Once the target quality hazard is identified, the corresponding triggering environmental data is matched from a pre-set trigger matching table in the database. This table contains environmental data that may trigger the target quality hazard in the corresponding construction area. The trigger matching table includes different quality hazards and their corresponding triggering environmental data, all set based on human experience. Specifically, it involves identifying the historical environmental data present when a single quality hazard occurred, based on historical records of hazard occurrences, and determining the historical environmental data with the most frequent occurrences as the corresponding triggering environmental data. If triggering environmental data exists in the environmental data for the construction site under supervision, the ratio of the number of times the triggering environmental data occurred when the target quality hazard occurred to the total number of times the triggering environmental data occurred determines the impact level of this triggering environmental data on the target quality hazard. A higher impact level indicates that the triggering environmental data is more likely to trigger the target quality hazard, requiring longer monitoring periods, and consequently, a longer target recording mode duration. Further, after the specified duration, the cameras in the corresponding construction area are switched from target recording mode to normal recording mode, and monitoring is conducted in this manner to ultimately obtain the monitoring video data for the corresponding construction area.

[0070] In other embodiments, during the recording of monitoring video data in each construction area, a correspondence is established between the duration of the target recording mode and the corresponding target quality hazard to obtain a time period matching table for the corresponding construction area.

[0071] Furthermore, if a target quality problem occurs during construction in the construction area, a pre-defined association matching table matches the target quality problem with associated quality hazards and their corresponding association levels. Associated quality hazards are those that cause the target quality problem; the higher the association level, the greater the probability that the associated quality hazard will induce the target quality problem. The association matching table includes combinations of different target quality problems and their corresponding associated quality hazards, along with their association levels, set based on human experience. Further, the construction area where the target quality problem occurs is identified as the target construction area. The time period matching table corresponding to this target construction area is selected from various time period matching tables, and the target duration period corresponding to each associated quality hazard is matched. Finally, according to the association levels of the associated quality hazards matching the target duration period from highest to lowest, video segments corresponding to the target duration period are sequentially extracted from the monitoring video data corresponding to this target construction area and sent to the terminal of the site management personnel. The terminal can be a smartphone or a personal computer, thereby enabling efficient and accurate investigation of the cause of the target quality problem.

[0072] In addition, environmental data refers to data such as temperature, humidity, and noise at the construction site to be monitored. One feasible way to obtain this data is by using pre-installed temperature, humidity, and noise sensors within the site. Furthermore, a feasible way to obtain the location data of construction workers is by using UltraWide Band (UWB) tags worn by the workers to acquire their corresponding location data. It should be noted that the pre-installed cameras, temperature sensors, humidity sensors, noise sensors, and the workers' UWB tags are all connected to the server via a wireless network.

[0073] S102: By using a preset multi-source data fusion algorithm, the monitoring video data, environmental data, and construction personnel location data are fused and processed to obtain the current operational status information of the construction site to be monitored.

[0074] Specifically, multi-source data fusion algorithms are mainly based on multiple similar or dissimilar information sources, combined spatially or temporally according to a specific standard to obtain a consistent interpretation or description of the object under test, thereby improving the performance of the information system. In this embodiment, the multi-source data fusion algorithm employs Bayesian estimation; in other embodiments, it may also employ Kalman filtering. Furthermore, through the multi-source data fusion algorithm, multidimensional data from different sources—namely, surveillance video data, environmental data, and construction worker location data—are fused and processed to achieve processing of data from multiple sources, ultimately obtaining the current operational status information of the construction site under supervision, thus realizing comprehensive monitoring of the construction site. Here, the current operational status information refers to the overall operational status of the construction site under supervision.

[0075] S103: Upon receiving a monitoring interface viewing instruction sent by the construction site management personnel's terminal, generate a real-time monitoring interface corresponding to the construction site to be monitored based on the current operational status information and display it on the terminal.

[0076] Specifically, in this embodiment, the construction site manager's terminal is equipped with a client related to construction site monitoring. When the construction site manager wants to view the overall monitoring status of the construction site, he / she opens the client through the terminal, clicks the "View Monitoring Interface" button on the client's main interface, and the client sends the monitoring interface viewing command to the server. Upon receiving the monitoring interface viewing command, the server generates a visualized real-time monitoring interface for the construction site to be monitored based on the current operational status information using the preset Grafana tool, and displays it on the terminal, making it easier for the construction site manager to better monitor the construction site situation.

[0077] S104: Upon receiving a site warning viewing instruction from the site management personnel's terminal, the current operational status information is input into the preset site operational status prediction model to obtain the corresponding safety warning information for the site to be monitored, and the safety warning information is sent to the terminal.

[0078] Specifically, if site managers want to view the overall safety warning status of the construction site, they can click the "View Site Warning" button on the client's main interface. The client sends a site warning viewing command to the server. Upon receiving the command, the server inputs the current operational status information into a preset site operational status prediction model to obtain the corresponding safety warning information for the site under supervision, and then sends the safety warning information back to the terminal. The site operational status prediction model can be a trained convolutional neural network model or a trained recurrent neural network model. The training process involves using historical operational status information marked with the sequential time points of the safety warning information as training samples, which are then input into the model for training. This is existing technology and will not be elaborated further.

[0079] See Figure 2 This application discloses a flowchart illustrating another method for smart construction site supervision based on multi-source data fusion. This method can be implemented using a computer program or run on a smart construction site supervision device based on multi-source data fusion using the von Neumann architecture. The computer program can be integrated into an application or run as a standalone tool application, specifically including:

[0080] S201: Obtain surveillance video data of each construction area in the construction site to be supervised, and obtain environmental data and location data of construction personnel in the construction site to be supervised.

[0081] S202: By using a preset multi-source data fusion algorithm, the monitoring video data, environmental data, and construction personnel location data are fused and processed to obtain the current operational status information of the construction site to be monitored.

[0082] S203: Upon receiving a monitoring interface viewing instruction sent by the construction site management personnel's terminal, generate a real-time monitoring interface corresponding to the construction site to be monitored based on the current operational status information and display it on the terminal.

[0083] S204: Upon receiving a site warning viewing instruction from the site management personnel's terminal, the current operational status information is input into the preset site operational status prediction model to obtain the corresponding safety warning information for the site to be monitored, and the safety warning information is sent to the terminal.

[0084] For details, please refer to steps S101-S104, which will not be repeated here.

[0085] S205: If a target construction platform exists in the construction area, create a target finite element model corresponding to the target construction platform.

[0086] S206: Based on the target finite element model, determine the associated location points of the target location points in the target construction platform.

[0087] Specifically, a finite element model (FEM) is a simulation model established using the finite element analysis method. It is a combination of elements connected only at nodes, transmitting forces only through nodes, and being constrained only at nodes. If a target construction platform exists in the construction area of ​​the site to be monitored, in this embodiment, the target construction platform is a scaffolding construction platform. Then, by using the corresponding 3D construction drawings of the target construction platform, the 3D model and material information of the target construction platform are determined. This information is then input into the finite element analysis software to simulate and recreate the 3D geometric model of the target construction platform in the real world. The finite element analysis software can be either ANSYS or ABAQUS.

[0088] Furthermore, the distribution of construction workers at target locations on the current target construction platform is determined using cameras, and the weight information of the construction workers is acquired through preset pressure sensors, ultimately determining the personnel load at the target locations where construction workers are present. Then, based on human experience, constraints are applied to the simulated 3D geometric model to simulate the constraints of the actual structure of the target construction platform. Corresponding personnel loads are applied to the target locations where construction workers are present in the 3D geometric model. Finally, the 3D geometric model is meshed using finite element methods, and the analysis type and solver options are set to obtain the target finite element model corresponding to the target construction platform, thus intuitively reflecting the stress situation at various locations on the target construction platform. This is existing technology and will not be elaborated further. Here, the target location point refers to the construction operation location point within the target construction platform.

[0089] Furthermore, the associated location point is the point where the stress in the target construction platform increases when the number of construction workers at the target location point changes. In this embodiment, the target change is a decrease of one construction worker. In other embodiments, the target change can also be an increase of one construction worker. A feasible way to determine the associated location point based on the target finite element model is to modify the personnel load at a single target location point in the target finite element model by increasing or decreasing the number of workers by one, i.e., simulating the target change to obtain the corresponding adjusted finite element model. Further, the stress value at the same location point is obtained from both the target finite element model and the corresponding adjusted finite element model. If the stress value increases after the target change, then it is determined as the associated location point of the target location point.

[0090] S207: Based on the stress values ​​of each associated location point corresponding to each target location point and the importance level of the target construction platform structure stability, determine the influence value of the corresponding target location point on the stability of the target construction platform structure.

[0091] Specifically, after determining the associated location points corresponding to a single target location point, the stress value of each associated location point and its importance level to the stability of the target construction platform structure are substituted into the preset stress value weight calculation formula to obtain the corresponding stress value weight of the associated location point. The stress value weight calculation formula is as follows:

[0092] In the formula, This indicates the stress value weight of the associated location points. Indicates the importance level of location points other than associated location points. The relative importance level of the associated location points is indicated by S, and the stability of the target construction platform structure itself is indicated by S. Both and β represent two positive real-valued parameters. Furthermore, S ranges from 0 to 1; a larger value indicates higher stability of the target construction platform structure itself. This indicates the influence of the importance level of the associated location point on the corresponding stress value weight. Used to adjust the sensitivity of the importance level to the stress value weight. This indicates the influence of the target construction platform's structural stability on the stress values ​​at associated locations. This is used to adjust the sensitivity of the stability of the target construction platform structure itself to the stress value weight of associated location points. The larger the stability S, the better. The smaller, The smaller the value, the more important the associated location point. The larger, The larger the value. In the denominator... The influence of location points other than associated location points on the stress value weights was considered, thus ensuring that the weights for associated location points were relatively reasonable. Furthermore, The +1 ensures that the denominator does not approach zero due to the small contributions of other points, thus avoiding numerical stability issues and making the stress values ​​of the related points more reasonable and accurate. The stability of the target construction platform is determined by using finite element analysis software to evaluate the stability of its three-dimensional geometric model and obtain the corresponding stability.

[0093] Furthermore, the higher the importance level, the greater the impact of increased stress at the corresponding associated locations on structural stability. Specifically, an importance level is matched to the associated locations from a pre-defined importance level matching table. This table includes different locations and their corresponding importance levels, all set based on human experience. A feasible setup method is for a professional structural engineer to send the importance level of different locations for the target construction platform's structural stability to the server via a terminal, with importance levels ranging from 0 to 1. Further, the product of the stress value and its weight at each associated location is calculated and summed to obtain the impact value of the corresponding target location on the target construction platform's structural stability. A larger impact value indicates a greater impact of increased stress at the corresponding associated locations on the target construction platform's structural stability, leading to a greater risk of platform instability.

[0094] In this embodiment, the target change corresponding to each target location point is the same. In other embodiments, the target change corresponding to each target location point may be different. The target change is determined according to the importance level of the target location point to the stability of the target construction platform structure. The higher the importance level, the smaller the corresponding target change, thereby achieving accurate and timely early warning of the stability of the target construction platform structure.

[0095] S208: If the impact value is greater than the preset impact value threshold, a safety warning will be issued for the target construction platform when the actual change in the number of construction personnel at the corresponding target location point is a target change.

[0096] Specifically, if the impact value exceeds the preset impact threshold, it indicates that the structure of the target construction platform is significantly affected by stress after the number of construction workers at the corresponding target location changes, making it highly susceptible to instability. Therefore, when the actual change in the number of construction workers at the corresponding target location is a target change, a safety warning is issued through the preset broadcasting equipment at the target construction platform to remind construction workers to be vigilant against potential instability. The specific process involves determining the departure trajectory of each construction worker leaving the target construction platform based on the 3D construction image of the platform. The corresponding departure time is determined. If the departure time exceeds the preset time threshold, it indicates that once the target construction platform becomes unstable, the corresponding construction personnel will have a longer time to escape, resulting in a higher safety risk. Furthermore, the number of construction personnel whose departure time exceeds the time threshold is counted. Based on the number of construction personnel, a corresponding warning time is matched from a preset time matching table. The time matching table includes different numbers of construction personnel and their corresponding warning times, all of which are set based on human experience. The larger the number of construction personnel, the longer the corresponding warning time. Finally, a safety warning for the target construction platform is issued for the specified warning time, thereby improving the construction safety on the target construction platform.

[0097] The implementation principle of the smart construction site supervision method based on multi-source data fusion in this application embodiment is as follows: After acquiring the monitoring video data, environmental data, and construction personnel location data corresponding to the construction site to be supervised, the data from the three sources are fused using a multi-source data fusion algorithm to obtain information that more comprehensively reflects the construction site's operational status, namely, the current operational status information. Furthermore, when construction site managers want to view a visual overview of the entire construction site's operation, a real-time monitoring interface corresponding to the construction site to be supervised is generated based on the current operational status information and displayed on the management personnel's terminal. When construction site managers want to understand the site's safety warning information, the construction site operational status prediction model predicts future operational status information based on the current operational status information and determines safety warning information, thereby enabling construction site managers to have a more comprehensive understanding of the construction site's supervision.

[0098] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0099] Please see Figure 3 This is a schematic diagram of the structure of a smart construction site monitoring device based on multi-source data fusion provided in this application embodiment. This smart construction site monitoring device applied to multi-source data fusion can be implemented as all or part of a device through software, hardware, or a combination of both. The device includes a data acquisition module 11, a status determination module 12, a monitoring and viewing module 13, and a construction site early warning module 14.

[0100] The data acquisition module 11 is used to acquire monitoring video data of each construction area in the construction site to be supervised, as well as environmental data and location data of construction personnel in the construction site to be supervised.

[0101] The status determination module 12 is used to fuse monitoring video data, environmental data and construction personnel location data through a preset multi-source data fusion algorithm to obtain the current operating status information of the construction site to be monitored.

[0102] The monitoring and viewing module 13 is used to generate a real-time monitoring interface for the construction site to be monitored and display it on the terminal based on the current operation status information when it receives a monitoring interface viewing instruction sent by the terminal of the construction site manager.

[0103] The construction site early warning module 14 is used to input the current operation status information into the preset construction site operation status prediction model when it receives the construction site early warning viewing instruction sent by the terminal of the construction site management personnel, to obtain the safety early warning information corresponding to the construction site to be supervised, and to send the safety early warning information to the terminal.

[0104] Optionally, the data acquisition module 11 is specifically used for:

[0105] The system acquires the target construction operations of construction workers in each construction area of ​​the construction site to be monitored. If the target construction operation is a non-standard construction operation, the system controls the preset camera in the corresponding construction area to switch from normal recording mode to target recording mode. Target recording mode is a mode that makes it easy to observe the details of the monitoring video.

[0106] The construction procedures performed by the construction personnel corresponding to the target construction operation are identified as potential construction procedures, and based on these potential construction procedures, the associated potential quality hazards are identified.

[0107] Determine whether there is any induced environmental data in the environmental data that could cause potential quality hazards to the target. If so, determine the duration of the target recording mode based on the impact level of the induced environmental data on the potential quality hazards to the target. The greater the impact level, the longer the corresponding duration.

[0108] After a certain duration, the camera is switched from target recording mode to normal recording mode to obtain the corresponding monitoring video data of the construction area.

[0109] Optionally, the data acquisition module 11 is specifically used for:

[0110] Obtain historical quality hazards generated by the construction process with potential risks, and count the number of times each historical quality hazard first occurs. Then, select the historical quality hazard with the highest number of first occurrences from all historical quality hazards in descending order of the number of first occurrences and identify it as a potential hazard.

[0111] Obtain the historical non-standard construction operations in the construction process of each potential hidden danger, count the second occurrence number of each historical non-standard construction operation, and select the historical non-standard construction operation with the second occurrence number in descending order to determine the corresponding potential hidden danger-prone non-standard operation.

[0112] The potential hazards that may occur in the target construction operation within the corresponding non-standard operations that are prone to stagnation are identified as key quality hazards. The weighted product of the first weight of each key quality hazard and the second weight of the corresponding target construction operation is calculated. The first weight is the ratio of the first occurrence of each key quality hazard to the sum of the first occurrences of all potential hazards. The second weight is the ratio of the second occurrence of the target construction operation corresponding to each key quality hazard to the sum of the second occurrences of all corresponding non-standard operations that are prone to stagnation.

[0113] Select the product with the largest weight from the products with the largest weight, and identify the key quality hazard corresponding to the product with the largest weight as the associated target quality hazard.

[0114] Optional, such as Figure 4 As shown, the device also includes a problem-solving module 15, specifically used for:

[0115] Establish a correspondence between the duration of the target recording mode in the monitoring video data corresponding to each construction area and the corresponding target quality hazard to obtain the corresponding time period matching table;

[0116] When a target quality problem occurs in the construction area, identify the associated quality hazards of the target quality problem and determine the correlation level between each associated quality hazard and the target quality problem;

[0117] The construction area corresponding to the target quality problem is identified as the target construction area. The target duration period corresponding to the associated quality hazard is matched from the time period matching table corresponding to the target construction area. According to the association level of the associated quality hazard from large to small, the video segments corresponding to the target duration period are extracted from the monitoring video data corresponding to the target construction area and sent to the terminal.

[0118] Optionally, the device also includes a platform early warning module 16, specifically used for:

[0119] If a target construction platform exists in the construction area, then create a target finite element model corresponding to the target construction platform;

[0120] Based on the target finite element model, the associated location points of the target location point in the target construction platform are determined. The target location point is the construction operation location point in the target construction platform, and the associated location point is the location point in the target construction platform where the stress increases when the number of construction personnel at the target location point changes.

[0121] Based on the stress values ​​of each associated location point corresponding to each target location point and the importance level of the target construction platform structure to the stability, determine the impact value of the corresponding target location point on the stability of the target construction platform structure.

[0122] If the impact value is greater than the preset impact value threshold, a safety warning will be issued for the target construction platform when the actual change in the number of construction workers at the corresponding target location point is a target change.

[0123] Optional, the platform early warning module 16 is specifically used for:

[0124] Substituting the stress value of each associated location point corresponding to the same target location point and its importance level to the stability of the target construction platform structure into the preset stress value weight calculation formula, the stress value weight of the corresponding associated location point is obtained. The stress value weight calculation formula is as follows:

[0125] In the formula, This indicates the stress value weight of the associated location points. This indicates the importance level of location points other than associated location points, and S represents the stability of the target construction platform structure itself. Both β and β represent two positive real-valued parameters;

[0126] Calculate the product of the stress value of each associated location point and the corresponding stress value weight for each target location point, and sum them to obtain the influence value of the corresponding target location point on the stability of the target construction platform structure.

[0127] Optional, the platform early warning module 16 is specifically used for:

[0128] When the actual change in the number of construction workers at the corresponding target location point is considered a target change, determine the duration of the departure of the construction workers from the target construction platform.

[0129] The number of construction workers who are away for more than a preset time threshold is counted, and the warning time is determined based on the number of construction workers. The larger the number of construction workers, the longer the corresponding warning time.

[0130] Issue safety warnings for the target construction platform with a specified duration.

[0131] It should be noted that the smart construction site monitoring device under multi-source data fusion provided in the above embodiments is only illustrated by the division of the above functional modules when executing the smart construction site monitoring method under multi-source data fusion. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the smart construction site monitoring device under multi-source data fusion and the smart construction site monitoring method embodiment provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiment, which will not be repeated here.

[0132] This application also discloses a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it employs a smart construction site supervision method based on multi-source data fusion as described in the above embodiments.

[0133] The computer program can be stored in a computer-readable medium. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or certain middleware. The computer-readable medium includes any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the computer-readable medium includes, but is not limited to, the above-mentioned components.

[0134] The above-described intelligent construction site supervision method based on multi-source data fusion is stored in the computer-readable storage medium and loaded and executed on the processor to facilitate the storage and application of the above method.

[0135] This application also discloses an electronic device in which a computer program is stored in a computer-readable storage medium. When the computer program is loaded and executed by a processor, the above-mentioned smart construction site supervision method under multi-source data fusion is adopted.

[0136] The electronic device can be a desktop computer, a laptop computer, or a cloud server, and includes, but is not limited to, a processor and a memory. For example, the electronic device may also include input / output devices, network access devices, and buses.

[0137] The processor can be a central processing unit (CPU). Of course, depending on the actual use, it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc., and this application does not limit it.

[0138] The memory can be an internal storage unit of an electronic device, such as a hard disk or RAM, or an external storage device, such as a plug-in hard disk, smart memory card (SMC), secure digital card (SD), or flash memory card (FC) equipped on the electronic device. Furthermore, the memory can be a combination of an internal storage unit and an external storage device. The memory is used to store computer programs and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or will be output. This application does not limit this.

[0139] In this electronic device, a smart construction site monitoring method based on multi-source data fusion, as described in the above embodiment, is stored in the memory of the electronic device and loaded and executed on the processor of the electronic device for convenient use.

[0140] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A smart construction site supervision method based on multi-source data fusion, characterized in that, The method includes: Acquiring surveillance video data of each construction area in the construction site under supervision includes: acquiring the target construction operation of construction personnel in each construction area of ​​the construction site under supervision; if the target construction operation is a non-standard construction operation, controlling the preset camera of the corresponding construction area to switch from normal recording mode to target recording mode, the target recording mode being a mode that makes it easy to observe the details of the surveillance video; identifying the construction procedure performed by the construction personnel corresponding to the target construction operation as a potential construction procedure, and based on the potential construction procedure, identifying the associated target quality hazards, including: acquiring historical quality hazards generated by the potential construction procedure, and counting the first occurrence count of each historical quality hazard, and selecting the first historical quality hazard from each historical quality hazard in descending order of the first occurrence count and identifying it as a potential hazard; acquiring the historical non-standard construction operation in the potential construction procedure when each potential hazard occurs, and counting the historical non-standard construction operation in each potential construction procedure. The second occurrence count of the historical non-standard construction operations is used to determine the second-number historical non-standard construction operations selected from all the historical non-standard construction operations in descending order of the second occurrence count. These are identified as the corresponding non-standard operations prone to potential hazards. The potential hazards of the target construction operation within these non-standard operations are identified as key quality hazards. A weighted product of a first weight for each key quality hazard and a second weight for the corresponding target construction operation is calculated. The first weight is the ratio of the first occurrence count of each key quality hazard to the sum of the first occurrence counts of all potential hazards. The second weight is the ratio of the second occurrence count of the target construction operation corresponding to each key quality hazard to the sum of the second occurrence counts of all corresponding non-standard operations. The maximum weighted product is selected from all the weighted products, and the key quality hazard corresponding to the maximum weighted product is identified as the associated target quality hazard. Determine whether there is any induced environmental data in the environmental data that could cause the target quality hazard. If so, determine the duration of the target recording mode based on the level of influence of the induced environmental data on the target quality hazard. The higher the level of influence, the longer the duration. After the specified duration, the camera is controlled to switch from the target recording mode to the normal recording mode to obtain the corresponding monitoring video data of the construction area; and the environmental data of the construction site to be monitored and the location data of the construction personnel are acquired. By using a preset multi-source data fusion algorithm, the monitoring video data, the environmental data, and the construction personnel location data are fused to obtain the current operational status information of the construction site to be monitored. When a monitoring interface viewing instruction is received from the terminal of the construction site manager, a real-time monitoring interface corresponding to the construction site to be monitored is generated based on the current operation status information and displayed on the terminal. When a site management personnel receives a site warning viewing instruction from their terminal, the current operational status information is input into a preset site operational status prediction model to obtain the safety warning information corresponding to the site to be monitored, and the safety warning information is sent to the terminal.

2. The smart construction site supervision method based on multi-source data fusion according to claim 1, characterized in that, The method further includes: Establish a correspondence between the duration of the target recording mode in the monitoring video data corresponding to each construction area and the corresponding target quality hazard to obtain the corresponding time period matching table; When a target quality problem occurs in the construction area, identify the associated quality hazards of the target quality problem, and determine the association level between each associated quality hazard and the target quality problem; The construction area corresponding to the target quality problem is determined as the target construction area. The target duration period corresponding to the associated quality hazard is matched from the time period matching table corresponding to the target construction area. According to the association level of the associated quality hazard in descending order, the video segments of the corresponding target duration period are extracted from the monitoring video data corresponding to the target construction area and sent to the terminal.

3. The smart construction site supervision method based on multi-source data fusion according to claim 1, characterized in that, The method further includes: If a target construction platform exists in the construction area, then create a target finite element model corresponding to the target construction platform; Based on the target finite element model, the associated location points of the target location point in the target construction platform are determined. The target location point is the construction operation location point in the target construction platform, and the associated location point is the location point in the target construction platform where the stress increases when the number of construction personnel at the target location point changes. Based on the stress values ​​of each associated location point corresponding to each target location point and the importance level of the stability of the target construction platform structure, the influence value of the corresponding target location point on the stability of the target construction platform structure is determined. If the impact value is greater than the preset impact value threshold, a safety warning will be issued for the target construction platform when the actual change in the number of construction workers at the corresponding target location point is the target change.

4. The smart construction site supervision method based on multi-source data fusion according to claim 3, characterized in that, The step of determining the influence value of the corresponding target location point on the stability of the target construction platform structure based on the stress value of each associated location point corresponding to each target location point and the importance level of the stability of the target construction platform structure specifically includes: Substituting the stress value of each associated location point corresponding to the same target location point and the importance level of the target construction platform structure to the preset stress value weight calculation formula, the stress value weight of the corresponding associated location point is obtained. The stress value weight calculation formula is as follows: In the formula, W A I represents the stress value weight of the associated location points. i γ represents the importance level of a location point other than the associated location point, S represents the stability of the target construction platform structure itself, and γ and β both represent two positive real number parameters. Calculate the product of the stress value of each of the associated locations of each target location and the corresponding stress value weight, and sum them to obtain the influence value of the corresponding target location on the stability of the target construction platform structure.

5. The smart construction site supervision method based on multi-source data fusion according to claim 3, characterized in that, When the actual change in the number of construction workers at the corresponding target location point constitutes a target change, a safety warning is issued for the target construction platform, specifically including: When the actual change in the number of construction workers at the corresponding target location point is the target change, determine the departure time of the construction workers leaving the target construction platform; The number of construction workers whose absence time exceeds a preset time threshold is counted, and the warning time is determined based on the number of construction workers. The larger the number of construction workers, the longer the corresponding warning time. A safety warning is issued for the specified duration for the target construction platform.

6. A smart construction site monitoring device based on multi-source data fusion, used to implement the smart construction site monitoring method based on multi-source data fusion as described in any one of claims 1 to 5, characterized in that, include: The data acquisition module (11) is used to acquire monitoring video data of each construction area in the construction site to be supervised, and to acquire environmental data and construction personnel location data of the construction site to be supervised. The status determination module (12) is used to perform fusion processing on the monitoring video data, the environmental data and the construction personnel positioning data through a preset multi-source data fusion algorithm to obtain the current operation status information of the construction site to be supervised; The monitoring and viewing module (13) is used to generate a real-time monitoring interface corresponding to the construction site to be monitored and display it on the terminal based on the current operation status information when it receives the monitoring interface viewing instruction sent by the terminal of the construction site manager; The construction site early warning module (14) is used to input the current operation status information into the preset construction site operation status prediction model when it receives the construction site early warning viewing instruction sent by the terminal of the construction site management personnel, to obtain the safety early warning information corresponding to the construction site to be supervised, and to send the safety early warning information to the terminal.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is loaded and executed by the processor, it employs the method described in any one of claims 1-5.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor loads and executes the computer program, it employs the method described in any one of claims 1-5.

Images